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Whitney Newey

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Author Profile
    1. Peers at Work --- June 2016
      by Matthew Kahn in Environmental and Urban Economics on 2016-07-05 05:57:00
    2. REPEC Issues a Monthly "Report Card" for Academic Economists
      by Matthew Kahn in Environmental and Urban Economics on 2016-12-05 03:41:00

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Newey, Whitney K, 1990. "Semiparametric Efficiency Bounds," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 99-135, April-Jun.

    Mentioned in:

    1. Semiparametric efficiency bounds (Journal of Applied Econometrics 1990) in ReplicationWiki ()

Working papers

  1. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2022. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," NBER Working Papers 30302, National Bureau of Economic Research, Inc.

    Cited by:

    1. Hünermund Paul & Louw Beyers & Caspi Itamar, 2023. "Double machine learning and automated confounder selection: A cautionary tale," Journal of Causal Inference, De Gruyter, vol. 11(1), pages 1-12, January.

  2. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.

    Cited by:

    1. Sören Blomquist, 2023. "Evaluating the Discrete Choice and BN Methods to Estimate Labor Supply Functions," CESifo Working Paper Series 10827, CESifo.

  3. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2021. "A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees," Papers 2105.15197, arXiv.org, revised Oct 2022.

    Cited by:

    1. Dmitry Arkhangelsky & Kazuharu Yanagimoto & Tom Zohar, 2024. "Flexible Analysis of Individual Heterogeneity in Event Studies: Application to the Child Penalty," Papers 2403.19563, arXiv.org.
    2. Jikai Jin & Vasilis Syrgkanis, 2024. "Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation," Papers 2402.14264, arXiv.org, revised Mar 2024.
    3. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Source Condition Double Robust Inference on Functionals of Inverse Problems," Papers 2307.13793, arXiv.org.
    4. Rahul Singh & Liyuan Xu & Arthur Gretton, 2021. "Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves," Papers 2111.03950, arXiv.org, revised Jul 2023.
    5. Rahul Singh, 2021. "Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection," Papers 2111.05277, arXiv.org.
    6. David Bruns-Smith & Oliver Dukes & Avi Feller & Elizabeth L. Ogburn, 2023. "Augmented balancing weights as linear regression," Papers 2304.14545, arXiv.org, revised Aug 2023.
    7. Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects," Papers 2112.14249, arXiv.org, revised Mar 2024.

  4. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.

    Cited by:

    1. Amandeep Singh & Ye Liu & Hema Yoganarasimhan, 2023. "Choice Models and Permutation Invariance: Demand Estimation in Differentiated Products Markets," Papers 2307.07090, arXiv.org, revised Feb 2024.
    2. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    3. Paul Goldsmith-Pinkham & Peter Hull & Michal Koles'ar, 2021. "Contamination Bias in Linear Regressions," Papers 2106.05024, arXiv.org, revised Feb 2024.
    4. Jonas Metzger, 2022. "Adversarial Estimators," Papers 2204.10495, arXiv.org, revised Jun 2022.
    5. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2022. "Automatic Debiased Machine Learning for Dynamic Treatment Effects and General Nested Functionals," Papers 2203.13887, arXiv.org, revised Jun 2023.
    6. Victor Quintas-Martinez, 2022. "Finite-Sample Guarantees for High-Dimensional DML," Papers 2206.07386, arXiv.org.
    7. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests," Papers 2110.03031, arXiv.org, revised Jun 2022.

  5. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Apr 2024.

    Cited by:

    1. Rahul Singh, 2021. "Debiased Kernel Methods," Papers 2102.11076, arXiv.org, revised Mar 2021.
    2. Qizhao Chen & Morgane Austern & Vasilis Syrgkanis, 2023. "Inference on Optimal Dynamic Policies via Softmax Approximation," Papers 2303.04416, arXiv.org, revised Dec 2023.
    3. Wenlong Ji & Lihua Lei & Asher Spector, 2023. "Model-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects," Papers 2310.08115, arXiv.org.
    4. AmirEmad Ghassami & Andrew Ying & Ilya Shpitser & Eric Tchetgen Tchetgen, 2021. "Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference," Papers 2104.02929, arXiv.org, revised Mar 2022.
    5. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    6. Jonas Metzger, 2022. "Adversarial Estimators," Papers 2204.10495, arXiv.org, revised Jun 2022.
    7. Anish Agarwal & Rahul Singh, 2021. "Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy," Papers 2107.02780, arXiv.org, revised Feb 2024.
    8. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2021. "A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees," Papers 2105.15197, arXiv.org, revised Oct 2022.
    9. Xiaohong Chen & Yuan Liao & Weichen Wang, 2022. "Inference on Time Series Nonparametric Conditional Moment Restrictions Using General Sieves," Papers 2301.00092, arXiv.org, revised Jan 2023.
    10. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Source Condition Double Robust Inference on Functionals of Inverse Problems," Papers 2307.13793, arXiv.org.
    11. Qizhao Chen & Vasilis Syrgkanis & Morgane Austern, 2022. "Debiased Machine Learning without Sample-Splitting for Stable Estimators," Papers 2206.01825, arXiv.org, revised Nov 2022.
    12. Dmitry Arkhangelsky & Guido W. Imbens & Lihua Lei & Xiaoman Luo, 2021. "Design-Robust Two-Way-Fixed-Effects Regression For Panel Data," Papers 2107.13737, arXiv.org, revised Mar 2024.
    13. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2022. "Automatic Debiased Machine Learning for Dynamic Treatment Effects and General Nested Functionals," Papers 2203.13887, arXiv.org, revised Jun 2023.
    14. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests," Papers 2110.03031, arXiv.org, revised Jun 2022.
    15. Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects," Papers 2112.14249, arXiv.org, revised Mar 2024.
    16. Masahiro Kato & Masaaki Imaizumi & Kenichiro McAlinn & Haruo Kakehi & Shota Yasui, 2021. "Learning Causal Models from Conditional Moment Restrictions by Importance Weighting," Papers 2108.01312, arXiv.org, revised Sep 2022.

  6. Drew Fudenberg & Whitney K. Newey & Philipp Strack & Tomasz Strzalecki, 2019. "Testing the Drift-Diffusion Model," Papers 1908.05824, arXiv.org.

    Cited by:

    1. Strittmatter, Anthony & Sunde, Uwe & Zegners, Dainis, 2022. "Speed, Quality, and the Optimal Timing of Complex Decisions: Field Evidence," Rationality and Competition Discussion Paper Series 317, CRC TRR 190 Rationality and Competition.
    2. Carlos Alós-Ferrer & Michele Garagnani, 2022. "Strength of preference and decisions under risk," Journal of Risk and Uncertainty, Springer, vol. 64(3), pages 309-329, June.
    3. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Aldo Rustichini, 2020. "Multinomial logit processes and preference discovery: inside and outside the black box," Papers 2004.13376, arXiv.org, revised Jan 2021.
    4. J r my Boccanfuso, 2022. "Consumption Response Heterogeneity and Dynamics with an Inattention Region," Working Papers wp1172, Dipartimento Scienze Economiche, Universita' di Bologna.

  7. Victor Chernozhukov & Jerry Hausman & Whitney K. Newey, 2019. "Demand analysis with many prices," CeMMAP working papers CWP59/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    2. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Ming Li, 2021. "A Time-Varying Endogenous Random Coefficient Model with an Application to Production Functions," Papers 2110.00982, arXiv.org.
    4. Dubois, Pierre & Griffith, Rachel & O'Connell, Martin, 2017. "How well targeted are soda taxes?," CEPR Discussion Papers 12484, C.E.P.R. Discussion Papers.
    5. Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
    6. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
    7. O'Connell, Martin & Smith, Kate, 2020. "Corrective Tax Design and Market Power," CEPR Discussion Papers 14582, C.E.P.R. Discussion Papers.
    8. Martin O'Connell & Kate Smith, 2021. "Optimal sin taxation and market power," IFS Working Papers W21/30, Institute for Fiscal Studies.
    9. Lin, Xirong, 2023. "Food demand and cash transfers: A collective household approach with Homescan data," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 233-259.

  8. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Inference on weighted average value function in high-dimensional state space," Papers 1908.09173, arXiv.org.

    Cited by:

    1. Minkyung Kim & K. Sudhir & Kosuke Uetake, 2022. "A Structural Model of a Multitasking Salesforce: Incentives, Private Information, and Job Design," Management Science, INFORMS, vol. 68(6), pages 4602-4630, June.

  9. Whitney Newey & Sami Stouli, 2018. "Control Variables, Discrete Instruments, and Identification of Structural Functions," Papers 1809.05706, arXiv.org, revised Dec 2019.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.
    2. Tadao Hoshino, 2021. "Estimating a Continuous Treatment Model with Spillovers: A Control Function Approach," Papers 2112.15114, arXiv.org, revised Jan 2023.
    3. Osama Khassawneh & Hamzah Elrehail, 2022. "The Effect of Participative Leadership Style on Employees’ Performance: The Contingent Role of Institutional Theory," Administrative Sciences, MDPI, vol. 12(4), pages 1-13, December.
    4. Whitney K. Newey & Sami Stouli, 2018. "Heterogenous coefficients, discrete instruments, and identification of treatment effects," CeMMAP working papers CWP66/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Christophe Bruneel-Zupanc, 2023. "Don't (fully) exclude me, it's not necessary! Identification with semi-IVs," Papers 2303.12667, arXiv.org, revised Jul 2023.

  10. Blomquist, Sören & Newey, Whitney K, 2018. "The Kink and Notch Bunching Estimators Cannot Identify the Taxable Income Elasticity," Working Paper Series 2018:4, Uppsala University, Department of Economics.

    Cited by:

    1. Bertanha, Marinho & McCallum, Andrew H. & Seegert, Nathan, 2023. "Better bunching, nicer notching," Journal of Econometrics, Elsevier, vol. 237(2).
    2. David Staubli, 2018. "The Elasticity of Corporate Income: Panel Data Evidence from Switzerland," Cahiers de Recherches Economiques du Département d'économie 18.01, Université de Lausanne, Faculté des HEC, Département d’économie.

  11. Whitney K. Newey & Sami Stouli, 2018. "Heterogenous Coefficients, Discrete Instruments, and Identification of Treatment Effects," Papers 1811.09837, arXiv.org.

    Cited by:

    1. Whitney K. Newey & Sami Stouli, 2018. "Control variables, discrete instruments, and identification of structural functions," CeMMAP working papers CWP55/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. W K Newey & S Stouli, 2022. "Heterogeneous coefficients, control variables and identification of multiple treatment effects [Multivalued treatments and decomposition analysis: An application to the WIA program]," Biometrika, Biometrika Trust, vol. 109(3), pages 865-872.

  12. Victor Chernozhukov & Whitney Newey & Rahul Singh, 2018. "De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers," Papers 1802.08667, arXiv.org, revised Oct 2022.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    3. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    4. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    5. Gyungbae Park, 2024. "Debiased Machine Learning when Nuisance Parameters Appear in Indicator Functions," Papers 2403.15934, arXiv.org.
    6. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Antonio R. Linero, 2023. "Prior and posterior checking of implicit causal assumptions," Biometrics, The International Biometric Society, vol. 79(4), pages 3153-3164, December.
    8. Zequn Jin & Lihua Lin & Zhengyu Zhang, 2022. "Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives," Papers 2211.07903, arXiv.org.
    9. David Bruns-Smith & Oliver Dukes & Avi Feller & Elizabeth L. Ogburn, 2023. "Augmented balancing weights as linear regression," Papers 2304.14545, arXiv.org, revised Aug 2023.

  13. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.

    Cited by:

    1. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    2. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    3. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
    4. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.
    5. Paul Clarke & Annalivia Polselli, 2023. "Double Machine Learning for Static Panel Models with Fixed Effects," Papers 2312.08174, arXiv.org, revised Dec 2023.
    6. Alejandro Sanchez-Becerra, 2023. "Robust inference for the treatment effect variance in experiments using machine learning," Papers 2306.03363, arXiv.org.
    7. Amandeep Singh & Ye Liu & Hema Yoganarasimhan, 2023. "Choice Models and Permutation Invariance: Demand Estimation in Differentiated Products Markets," Papers 2307.07090, arXiv.org, revised Feb 2024.
    8. Manu Navjeevan, 2023. "An Identification and Dimensionality Robust Test for Instrumental Variables Models," Papers 2311.14892, arXiv.org.
    9. Juan Carlos Escanciano & Telmo P'erez-Izquierdo, 2023. "Automatic Locally Robust Estimation with Generated Regressors," Papers 2301.10643, arXiv.org, revised Nov 2023.
    10. Gyungbae Park, 2024. "Debiased Machine Learning when Nuisance Parameters Appear in Indicator Functions," Papers 2403.15934, arXiv.org.
    11. Paul Goldsmith-Pinkham & Peter Hull & Michal Koles'ar, 2021. "Contamination Bias in Linear Regressions," Papers 2106.05024, arXiv.org, revised Feb 2024.
    12. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
    13. Zhang, Jeffrey & Li, Wei & Miao, Wang & Tchetgen Tchetgen, Eric, 2023. "Proximal causal inference without uniqueness assumptions," Statistics & Probability Letters, Elsevier, vol. 198(C).
    14. Jikai Jin & Vasilis Syrgkanis, 2024. "Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation," Papers 2402.14264, arXiv.org, revised Mar 2024.
    15. Melissa Newham & Marica Valente, 2023. "The Cost of Influence:How Gifts to Physicians Shape Prescriptions and Drug Costs," Working Papers 2023-03, Faculty of Economics and Statistics, Universität Innsbruck.
    16. Zequn Jin & Lihua Lin & Zhengyu Zhang, 2022. "Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives," Papers 2211.07903, arXiv.org.
    17. Manu Navjeevan & Rodrigo Pinto & Andres Santos, 2023. "Identification and Estimation in a Class of Potential Outcomes Models," Papers 2310.05311, arXiv.org.
    18. Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
    19. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    20. Paul Goldsmith-Pinkham & Peter Hull & Michal Kolesár, 2021. "On Estimating Multiple Treatment Effects with Regression," Working Papers 2021-41, Princeton University. Economics Department..

  14. Victor Chernozhukov & Whitney K. Newey & James Robins, 2018. "Double/de-biased machine learning using regularized Riesz representers," CeMMAP working papers CWP15/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Yiyan Huang & Cheuk Hang Leung & Xing Yan & Qi Wu & Nanbo Peng & Dongdong Wang & Zhixiang Huang, 2020. "The Causal Learning of Retail Delinquency," Papers 2012.09448, arXiv.org.
    3. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    4. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    5. Daoud, Adel, 2021. "The International Monetary Fund’s intervention in education systems and its impact on children’s chances of completing school," SocArXiv kbc34, Center for Open Science.
    6. Jann Spiess & Vasilis Syrgkanis & Victor Yaneng Wang, 2021. "Finding Subgroups with Significant Treatment Effects," Papers 2103.07066, arXiv.org, revised Dec 2023.
    7. Adel Daoud, 2021. "The International Monetary Funds intervention in education systems and its impact on childrens chances of completing school," Papers 2201.00013, arXiv.org.
    8. Daoud, Adel & Johansson, Fredrik, 2019. "Estimating Treatment Heterogeneity of International Monetary Fund Programs on Child Poverty with Generalized Random Forest," SocArXiv awfjt, Center for Open Science.

  15. Sören Blomquist & Whitney Newey & Anil Kumar & Che-Yuan Liang, 2017. "On Bunching and Identification of the Taxable Income Elasticity," NBER Working Papers 24136, National Bureau of Economic Research, Inc.

    Cited by:

    1. Andreas R. Kostøl & Andreas S. Myhre, 2021. "Labor Supply Responses to Learning the Tax and Benefit Schedule," American Economic Review, American Economic Association, vol. 111(11), pages 3733-3766, November.
    2. Juliana Londoño-Vélez & Javier Avila-Mahecha, 2024. "Behavioral Responses to Wealth Taxation: Evidence from Colombia," NBER Working Papers 32134, National Bureau of Economic Research, Inc.
    3. Matias D. Cattaneo & Rocio Titiunik, 2021. "Regression Discontinuity Designs," Papers 2108.09400, arXiv.org, revised Feb 2022.
    4. Alexander Bick & Adam Blandin & Richard Rogerson, 2022. "Hours and Wages," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(3), pages 1901-1962.
    5. Marinho Bertanha & Andrew H. McCallum & Nathan Seegert, 2021. "Better Bunching, Nicer Notching," Finance and Economics Discussion Series 2021-002, Board of Governors of the Federal Reserve System (U.S.).
    6. Aronsson, Thomas & Jenderny, Katharina & Lanot, Gauthier, 2022. "The quality of the estimators of the ETI," Journal of Public Economics, Elsevier, vol. 212(C).
    7. Myhre, Andreas, 2021. "Intensive and Extensive Margin Labor Supply Responses to Kinks in Disability Insurance Programs," MPRA Paper 109547, University Library of Munich, Germany.
    8. Anelli, Massimo & Koenig, Felix, 2021. "Willingness to Pay for Workplace Safety," IZA Discussion Papers 14919, Institute of Labor Economics (IZA).
    9. Neryvia Pillay Bell, 2020. "Taxpayer responsiveness to taxation: Evidence from bunching at kink points of the South African income tax schedule," WIDER Working Paper Series wp-2020-68, World Institute for Development Economic Research (UNU-WIDER).
    10. Mavrokonstantis, Panos & Seibold, Arthur, 2022. "Bunching and Adjustment Costs: Evidence from Cypriot Tax Reforms," Journal of Public Economics, Elsevier, vol. 214(C).
    11. Thomas Aronsson & Katharina Jenderny & Gauthier Lanot, 2024. "A maximum likelihood bunching estimator of the elasticity of taxable income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 200-216, January.
    12. Jeffrey L. Coles & Elena Patel & Nathan Seegert & Matthew Smith, 2022. "How Do Firms Respond to Corporate Taxes?," Journal of Accounting Research, Wiley Blackwell, vol. 60(3), pages 965-1006, June.
    13. Sebastiaan Maes & Raghav Malhotra, 2023. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," Papers 2303.01231, arXiv.org, revised Nov 2023.
    14. Marx, Benjamin M., 2018. "Dynamic Bunching Estimation with Panel Data," MPRA Paper 88647, University Library of Munich, Germany.
    15. David Sturrock & Stefan Groot & Jan Möhlmann, 2022. "Wealth, gifts, and estate planning at the end of life," CPB Discussion Paper 442, CPB Netherlands Bureau for Economic Policy Analysis.
    16. Massenz, Gabriella, 2023. "On the behavioral effects of tax policy," Other publications TiSEM eb44a9f7-b859-480d-b2e4-4, Tilburg University, School of Economics and Management.
    17. Pablo Gutierrez Cubillos, 2022. "Dividend tax credits and the elasticity of taxable income: evidence from small businesses," Working Papers 630, ECINEQ, Society for the Study of Economic Inequality.
    18. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," CRETA Online Discussion Paper Series 84, Centre for Research in Economic Theory and its Applications CRETA.
    19. Marius A. K. Ring & Thor Olav Thoresen, 2022. "Wealth Taxation and Charitable Giving," CESifo Working Paper Series 9700, CESifo.
    20. Escobar, Sebastian & Ohlsson, Henry & Selin, Håkan, 2023. "Giving to the children or the taxman?," European Economic Review, Elsevier, vol. 153(C).
    21. Tuomas Kosonen & Tuomas Matikka, 2023. "Discrete Labor Supply: Quasi-Experimental Evidence and Implications," Working Papers 9, Finnish Centre of Excellence in Tax Systems Research.
    22. Daniel Reck & Arthur Seibold, 2023. "The Welfare Economics of Reference Dependence," CRC TR 224 Discussion Paper Series crctr224_2023_450, University of Bonn and University of Mannheim, Germany.
    23. Daniel M. Hungerman & Mark Ottoni-Wilhelm, 2018. "Impure Impact Giving: Theory and Evidence," NBER Working Papers 24940, National Bureau of Economic Research, Inc.
    24. Aronsson, Thomas & Jenderny, Katharina & Lanot, Gauthier, 2021. "Maximum Likelihood Bunching Estimators of the ETI," Umeå Economic Studies 987, Umeå University, Department of Economics.
    25. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Beyond the Mean : Testing Consumer Rationality through Higher Moments of Demand," CRETA Online Discussion Paper Series 85, Centre for Research in Economic Theory and its Applications CRETA.
    26. Panos Mavrokonstantis & Arthur Seibold, 2022. "Bunching and Adjustment Costs: Evidence from Cypriot Tax Reforms," CESifo Working Paper Series 9773, CESifo.

  16. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Su, Miaomiao & Wang, Ruoyu & Wang, Qihua, 2022. "A two-stage optimal subsampling estimation for missing data problems with large-scale data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    2. Riccardo Di Francesco, 2022. "Aggregation Trees," CEIS Research Paper 546, Tor Vergata University, CEIS, revised 20 Nov 2023.
    3. Heiler, Phillip & Kazak, Ekaterina, 2021. "Valid inference for treatment effect parameters under irregular identification and many extreme propensity scores," Journal of Econometrics, Elsevier, vol. 222(2), pages 1083-1108.
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    420. Yang Ning & Sida Peng & Jing Tao, 2020. "Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data," Papers 2009.03151, arXiv.org.
    421. Koen Pauwels & Michael Peran & Zee Shah & German Schnaidt & Dauwe Vercamer, 2023. "Sponsored brands video rings up clicks and sales in the short and long run," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 275-286, September.
    422. Zimmert, Franziska & Zimmert, Michael, 2020. "Paid parental leave and maternal reemployment: Do part-time subsidies help or harm?," Economics Working Paper Series 2002, University of St. Gallen, School of Economics and Political Science.
    423. McNamara, Sarah, 2020. "Returns to higher education and dropouts: A double machine learning approach," ZEW Discussion Papers 20-084, ZEW - Leibniz Centre for European Economic Research.
    424. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
    425. Luis Antonio Fantozzi Alvarez & Rodrigo Toneto, 2024. "The interpretation of 2SLS with a continuous instrument: a weighted LATE representation," Working Papers, Department of Economics 2024_11, University of São Paulo (FEA-USP).
    426. David Bruns-Smith & Oliver Dukes & Avi Feller & Elizabeth L. Ogburn, 2023. "Augmented balancing weights as linear regression," Papers 2304.14545, arXiv.org, revised Aug 2023.
    427. Max Vilgalys, 2023. "A Machine Learning Approach to Measuring Climate Adaptation," Papers 2302.01236, arXiv.org.
    428. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    429. Zhexiao Lin & Peng Ding & Fang Han, 2021. "Estimation based on nearest neighbor matching: from density ratio to average treatment effect," Papers 2112.13506, arXiv.org.
    430. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    431. Martin Wiegand, 2019. "Do early-ending conditional cash transfer programs crowd out school enrollment?," Tinbergen Institute Discussion Papers 19-053/V, Tinbergen Institute.
    432. Di Liu, 2022. "Treatment-effects estimation using lasso," 2022 Stata Conference 07, Stata Users Group.
    433. Dong Xia & Ming Yuan, 2021. "Statistical inferences of linear forms for noisy matrix completion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(1), pages 58-77, February.
    434. Nicholas Williams & Michael Rosenblum & Iván Díaz, 2022. "Optimising precision and power by machine learning in randomised trials with ordinal and time‐to‐event outcomes with an application to COVID‐19," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2156-2178, October.
    435. Wang, Man & Yang, Qiuping, 2022. "The heterogeneous treatment effect of low-carbon city pilot policy on stock return: A generalized random forests approach," Finance Research Letters, Elsevier, vol. 47(PA).
    436. Raghavendra Addanki & Siddharth Bhandari, 2024. "Limits of Approximating the Median Treatment Effect," Papers 2403.10618, arXiv.org.
    437. Mullally, Conner & Rivas, Mayra & McArthur, Travis, 2019. "Livestock Transfers Can Improve Child Health: Evidence from a Randomized Phase-In Design in Guatemala," SocArXiv c6zg5, Center for Open Science.
    438. Michael P. Leung & Pantelis Loupos, 2022. "Graph Neural Networks for Causal Inference Under Network Confounding," Papers 2211.07823, arXiv.org, revised Mar 2024.
    439. Heejun Shin & Joseph Antonelli, 2023. "Improved inference for doubly robust estimators of heterogeneous treatment effects," Biometrics, The International Biometric Society, vol. 79(4), pages 3140-3152, December.
    440. Martin Huber & Jannis Kueck, 2022. "Testing the identification of causal effects in observational data," Papers 2203.15890, arXiv.org, revised Jun 2023.
    441. Wang, Xiqian & Bian, Yong & Zhang, Qin, 2023. "The effect of cooking fuel choice on the elderly’s well-being: Evidence from two non-parametric methods," Energy Economics, Elsevier, vol. 125(C).
    442. Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects," Papers 2112.14249, arXiv.org, revised Mar 2024.
    443. Alberto Caron & Gianluca Baio & Ioanna Manolopoulou, 2022. "Estimating individual treatment effects using non‐parametric regression models: A review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1115-1149, July.
    444. Masahiro Kato & Kenshi Abe & Kaito Ariu & Shota Yasui, 2020. "A Practical Guide of Off-Policy Evaluation for Bandit Problems," Papers 2010.12470, arXiv.org.
    445. Kai Feng & Han Hong, 2024. "Statistical Inference of Optimal Allocations I: Regularities and their Implications," Papers 2403.18248, arXiv.org, revised Apr 2024.
    446. Hodula, Martin & Melecký, Martin & Pfeifer, Lukáš & Szabo, Milan, 2023. "Cooling the mortgage loan market: The effect of borrower-based limits on new mortgage lending," Journal of International Money and Finance, Elsevier, vol. 132(C).
    447. Christopher D. Walker, 2023. "Parametrization, Prior Independence, and the Semiparametric Bernstein-von Mises Theorem for the Partially Linear Model," Papers 2306.03816, arXiv.org, revised Feb 2024.
    448. Johannes Jakubik & Stefan Feuerriegel, 2022. "Data‐driven allocation of development aid toward sustainable development goals: Evidence from HIV/AIDS," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2739-2756, June.
    449. Xiang Zhou, 2022. "Semiparametric estimation for causal mediation analysis with multiple causally ordered mediators," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 794-821, July.
    450. Fengshi Niu & Harsha Nori & Brian Quistorff & Rich Caruana & Donald Ngwe & Aadharsh Kannan, 2022. "Differentially Private Estimation of Heterogeneous Causal Effects," Papers 2202.11043, arXiv.org.
    451. Thomas Wiemann, 2023. "Optimal Categorical Instrumental Variables," Papers 2311.17021, arXiv.org.

  17. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Jacob Dorn & Kevin Guo, 2021. "Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing," Papers 2102.04543, arXiv.org, revised Aug 2023.
    2. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    3. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
    4. Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
    5. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
    6. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2018. "Deep Neural Networks for Estimation and Inference," Papers 1809.09953, arXiv.org, revised Sep 2019.

  18. Sören Blomquist & Whitney K. Newey, 2017. "The Bunching Estimator Cannot Identify the Taxable Income Elasticity," CESifo Working Paper Series 6736, CESifo.

    Cited by:

    1. Vincent Dekker & Karsten Schweikert, 2021. "A Comparison of Different Data-driven Procedures to Determine the Bunching Window," Public Finance Review, , vol. 49(2), pages 262-293, March.
    2. Zhao Chen & Zhikuo Liu & Juan Carlos Suárez Serrato & Daniel Yi Xu, 2021. "Notching R&D Investment with Corporate Income Tax Cuts in China," American Economic Review, American Economic Association, vol. 111(7), pages 2065-2100, July.
    3. Bertanha, Marinho & McCallum, Andrew H. & Seegert, Nathan, 2023. "Better bunching, nicer notching," Journal of Econometrics, Elsevier, vol. 237(2).
    4. Alinaghi, Nazila & Creedy, John & Gemmell, Norman, 2020. "Do Couples Bunch More? Evidence from Partnered and Single Taxpayers in New Zealand," Working Paper Series 21094, Victoria University of Wellington, Chair in Public Finance.
    5. Hargaden, Enda Patrick, 2020. "Taxpayer responses in good times and bad," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 653-690.
    6. Ulrich Glogowsky, 2020. "Behavioral Responses to Inheritance and Gift Taxation: Evidence from Germany," Economics working papers 2020-22, Department of Economics, Johannes Kepler University Linz, Austria.
    7. Stuart Adam & James Browne & David Phillips & Barra Roantree, 2017. "Frictions and taxpayer responses: evidence from bunching at personal tax thresholds," IFS Working Papers W17/14, Institute for Fiscal Studies.
    8. He, Daixin & Peng, Langchuan & Wang, Xiaxin, 2021. "Understanding the elasticity of taxable income: A tale of two approaches," Journal of Public Economics, Elsevier, vol. 197(C).
    9. Bierbrauer, Felix J. & Boyer, Pierre C. & Peichl, Andreas, 2020. "Politically Feasible Reforms of Non-Linear Tax Systems," Rationality and Competition Discussion Paper Series 236, CRC TRR 190 Rationality and Competition.
    10. Homonoff, Tatiana & Willage, Barton & Willén, Alexander, 2020. "Rebates as incentives: The effects of a gym membership reimbursement program," Journal of Health Economics, Elsevier, vol. 70(C).
    11. Helen Miller & Thomas Pope & Kate Smith, 2024. "Intertemporal Income Shifting and the Taxation of Business Owner-Managers," The Review of Economics and Statistics, MIT Press, vol. 106(1), pages 184-201, January.
    12. Nicole Bosch & Vincent Dekker & Kristina Strohmaier, 2020. "A data-driven procedure to determine the bunching window: an application to the Netherlands," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 27(4), pages 951-979, August.
    13. Nazila Alinaghi & John Creedy & Norman Gemmell, 2023. "Do couples bunch more? Evidence from partnered and single taxpayers," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(4), pages 1137-1184, August.
    14. Zareh Asatryan & Andreas Peichl, 2017. "Responses of Firms to Tax, Administrative and Accounting Rules: Evidence from Armenia," CESifo Working Paper Series 6754, CESifo.
    15. Tuomas Kosonen & Tuomas Matikka, 2019. "Discrete earnings responses to tax incentives: Empirical evidence and implications," Working Papers 326, Työn ja talouden tutkimus LABORE, The Labour Institute for Economic Research LABORE.
    16. M. Chatib Basri & Mayara Felix & Rema Hanna & Benjamin A. Olken, 2019. "Tax Administration vs. Tax Rates: Evidence from Corporate Taxation in Indonesia," NBER Working Papers 26150, National Bureau of Economic Research, Inc.
    17. Gudgeon, Matthew & Trenkle, Simon, 2020. "The Speed of Earnings Responses to Taxation and the Role of Firm Labor Demand," IZA Discussion Papers 13931, Institute of Labor Economics (IZA).
    18. Daniel M. Hungerman & Mark Ottoni-Wilhelm, 2018. "Impure Impact Giving: Theory and Evidence," NBER Working Papers 24940, National Bureau of Economic Research, Inc.
    19. Aronsson, Thomas & Jenderny, Katharina & Lanot, Gauthier, 2021. "Maximum Likelihood Bunching Estimators of the ETI," Umeå Economic Studies 987, Umeå University, Department of Economics.
    20. Marx, Benjamin M., 2018. "Dynamic Bunching Estimation with Panel Data," MPRA Paper 88647, University Library of Munich, Germany.
    21. Massenz, Gabriella, 2023. "On the behavioral effects of tax policy," Other publications TiSEM eb44a9f7-b859-480d-b2e4-4, Tilburg University, School of Economics and Management.
    22. Bohne, Albrecht & Nimczik, Jan Sebastian, 2018. "Information Frictions and Learning Dynamics: Evidence from Tax Avoidance in Ecuador," IZA Discussion Papers 11536, Institute of Labor Economics (IZA).

  19. Rajarshi Mukherjee & Whitney K. Newey & James Robins, 2017. "Semiparametric efficient empirical higher order influence function estimators," CeMMAP working papers CWP30/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Vladimir Koltchinskii & Mayya Zhilova, 2021. "Estimation of Smooth Functionals of Location Parameter in Gaussian and Poincaré Random Shift Models," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 569-596, August.
    2. Yiyan Huang & Cheuk Hang Leung & Xing Yan & Qi Wu & Shumin Ma & Zhiri Yuan & Dongdong Wang & Zhixiang Huang, 2022. "Robust Causal Learning for the Estimation of Average Treatment Effects," Papers 2209.01805, arXiv.org.
    3. Jikai Jin & Vasilis Syrgkanis, 2024. "Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation," Papers 2402.14264, arXiv.org, revised Mar 2024.
    4. Eric J. Tchetgen Tchetgen, 2022. "Eric J Tchetgen Tchetgen’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 723-725, July.
    5. Juan Carlos Escanciano & Joel Robert Terschuur, 2022. "Machine Learning Inference on Inequality of Opportunity," Papers 2206.05235, arXiv.org, revised Oct 2023.
    6. Shi, Chengchun & Xu, Tianlin & Bergsma, Wicher & Li, Lexin, 2021. "Double generative adversarial networks for conditional independence testing," LSE Research Online Documents on Economics 112550, London School of Economics and Political Science, LSE Library.
    7. Lin Liu & Chang Li, 2023. "New $\sqrt{n}$-consistent, numerically stable higher-order influence function estimators," Papers 2302.08097, arXiv.org.

  20. Victor Chernozhukov & Iv'an Fern'andez-Val & Whitney Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models," Papers 1711.02184, arXiv.org, revised Oct 2019.

    Cited by:

    1. Romuald Meango, 2023. "Identification of Ex Ante Returns Using Elicited Choice Probabilities," Papers 2303.03009, arXiv.org.
    2. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.
    4. Bruneel-Zupanc, Christophe Alain, 2021. "Discrete-Continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation," TSE Working Papers 21-1185, Toulouse School of Economics (TSE).
    5. Tadao Hoshino, 2021. "Estimating a Continuous Treatment Model with Spillovers: A Control Function Approach," Papers 2112.15114, arXiv.org, revised Jan 2023.
    6. Whitney K. Newey & Sami Stouli, 2018. "Heterogenous coefficients, discrete instruments, and identification of treatment effects," CeMMAP working papers CWP66/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.
    8. Nagasawa, Kenichi, 2020. "Identification and Estimation of Group-Level Partial Effects," The Warwick Economics Research Paper Series (TWERPS) 1243, University of Warwick, Department of Economics.
    9. Whitney K. Newey & Sami Stouli, 2018. "Control variables, discrete instruments, and identification of structural functions," CeMMAP working papers CWP55/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis & Peracchi, Franco, 2022. "Selection and the Distribution of Female Hourly Wages in the U.S," IZA Discussion Papers 15028, Institute of Labor Economics (IZA).
    11. Iván Fernández‐Val & Aico van Vuuren & Francis Vella & Franco Peracchi, 2023. "Selection and the distribution of female real hourly wages in the United States," Quantitative Economics, Econometric Society, vol. 14(2), pages 571-607, May.
    12. Romauld Méango, 2023. "Identification of ex ante returns using elicited choice probabilities," Economics Series Working Papers 1007, University of Oxford, Department of Economics.
    13. Christian Gische & Manuel C. Voelkle, 2022. "Beyond the Mean: A Flexible Framework for Studying Causal Effects Using Linear Models," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 868-901, September.
    14. Jonas Meier, 2020. "Multivariate Distribution Regression," Diskussionsschriften dp2023, Universitaet Bern, Departement Volkswirtschaft.
    15. Richard Spady & Sami Stouli, 2020. "Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions," Papers 2011.06416, arXiv.org.
    16. Jayeeta Bhattacharya, 2020. "Quantile regression with generated dependent variable and covariates," Papers 2012.13614, arXiv.org.

  21. Alexandre Belloni & Christian Hansen & Whitney Newey, 2017. "Simultaneous Confidence Intervals for High-dimensional Linear Models with Many Endogenous Variables," Papers 1712.08102, arXiv.org, revised Aug 2019.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
    3. Mehmet Caner, 2021. "Generalized Linear Models with Structured Sparsity Estimators," Papers 2104.14371, arXiv.org.
    4. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
    5. Baris Ata & Alexandre Belloni & Ozan Candogan, 2018. "Latent Agents in Networks: Estimation and Targeting," Papers 1808.04878, arXiv.org, revised Jan 2022.

  22. Victor Chernozhukov & Iv'an Fern'andez-Val & Whitney Newey, 2017. "Nonseparable Multinomial Choice Models in Cross-Section and Panel Data," Papers 1706.08418, arXiv.org, revised May 2018.

    Cited by:

    1. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    2. Wang, Ao, 2020. "Identifying the Distribution of Random Coefficients in BLP Demand Models Using One Single Variation in Product Characteristics," The Warwick Economics Research Paper Series (TWERPS) 1304, University of Warwick, Department of Economics.
    3. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Discussion Paper 2022-009, Tilburg University, Center for Economic Research.
    4. Wang, Ao, 2023. "Sieve BLP: A semi-nonparametric model of demand for differentiated products," Journal of Econometrics, Elsevier, vol. 235(2), pages 325-351.

  23. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers CWP06/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    2. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
    4. Isaiah Andrews & Matthew Gentzkow & Jesse M. Shapiro, 2020. "On the Informativeness of Descriptive Statistics for Structural Estimates," Econometrica, Econometric Society, vol. 88(6), pages 2231-2258, November.
    5. Rui Duan & C. Jason Liang & Pamela Shaw & Cheng Yong Tang & Yong Chen, 2020. "Missing at Random or Not: A Semiparametric Testing Approach," Papers 2003.11181, arXiv.org.
    6. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    7. Santiago Pereda Fernández, 2019. "Identification and estimation of triangular models with a binary treatment," Temi di discussione (Economic working papers) 1210, Bank of Italy, Economic Research and International Relations Area.
    8. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    9. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    10. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Dec 2017.
    11. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    12. Kotlyarova, Yulia & Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2021. "Rates of expansions for functional estimators," LSE Research Online Documents on Economics 113436, London School of Economics and Political Science, LSE Library.
    13. Riccardo D'Adamo, 2021. "Orthogonal Policy Learning Under Ambiguity," Papers 2111.10904, arXiv.org, revised Dec 2022.
    14. Numair Sani & Yizhen Xu & AmirEmad Ghassami & Ilya Shpitser, 2021. "Multiply Robust Causal Mediation Analysis with Continuous Treatments," Papers 2105.09254, arXiv.org, revised Feb 2024.
    15. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Yu-Chin Hsu & Martin Huber & Yu-Min Yen, 2023. "Doubly Robust Estimation of Direct and Indirect Quantile Treatment Effects with Machine Learning," Papers 2307.01049, arXiv.org.
    17. Juan Carlos Escanciano & Joel Robert Terschuur, 2022. "Machine Learning Inference on Inequality of Opportunity," Papers 2206.05235, arXiv.org, revised Oct 2023.
    18. Undral Byambadalai, 2022. "Identification and Inference for Welfare Gains without Unconfoundedness," Papers 2207.04314, arXiv.org.
    19. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2022. "Best Arm Identification with Contextual Information under a Small Gap," Papers 2209.07330, arXiv.org, revised Jan 2023.
    20. Vira Semenova, 2020. "Generalized Lee Bounds," Papers 2008.12720, arXiv.org, revised Feb 2023.
    21. Yuichi Kitamura, 2020. "A Comment on: “On the Informativeness of Descriptive Statistics for Structural Estimates” by Isaiah Andrews, Matthew Gentzkow, and Jesse M. Shapiro," Econometrica, Econometric Society, vol. 88(6), pages 2265-2269, November.
    22. Jens Klooster & Mikhail Zhelonkin, 2024. "Outlier robust inference in the instrumental variable model with applications to causal effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 86-106, January.
    23. Victor Quintas-Martinez, 2022. "Finite-Sample Guarantees for High-Dimensional DML," Papers 2206.07386, arXiv.org.
    24. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    26. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2020. "Deep Learning for Individual Heterogeneity: An Automatic Inference Framework," Papers 2010.14694, arXiv.org, revised Jul 2021.

  24. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey, 2016. "Double machine learning for treatment and causal parameters," CeMMAP working papers CWP49/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Jannis Kueck & Ye Luo & Martin Spindler & Zigan Wang, 2017. "Estimation and Inference of Treatment Effects with $L_2$-Boosting in High-Dimensional Settings," Papers 1801.00364, arXiv.org, revised Jul 2021.
    2. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    3. Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
    4. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    5. Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019. "LASSO-Driven Inference in Time and Space," CeMMAP working papers CWP20/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    7. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    8. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    9. Alexandrov, Alexei & Pittman, Russell & Ukhaneva, Olga, 2018. "Pricing of Complements in the U.S. freight railroads: Cournot versus Coase," MPRA Paper 86279, University Library of Munich, Germany.
    10. Bernard Koch & Tim Sainburg & Pablo Geraldo & Song Jiang & Yizhou Sun & Jacob Gates Foster, 2021. "A Primer on Deep Learning for Causal Inference," Papers 2110.04442, arXiv.org, revised Nov 2023.
    11. Zhengyuan Zhou & Susan Athey & Stefan Wager, 2023. "Offline Multi-Action Policy Learning: Generalization and Optimization," Operations Research, INFORMS, vol. 71(1), pages 148-183, January.
    12. Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
    13. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    14. Dmitry Arkhangelsky & Guido W. Imbens, 2019. "The Role of the Propensity Score in Fixed Effect Models," Working Papers wp2019_1905, CEMFI.
    15. Mochen Yang & Edward McFowland III & Gordon Burtch & Gediminas Adomavicius, 2020. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," Papers 2012.10790, arXiv.org.
    16. Jean-Pierre Dubé & Sanjog Misra, 2017. "Personalized Pricing and Consumer Welfare," NBER Working Papers 23775, National Bureau of Economic Research, Inc.
    17. Athey, Susan & Tibshirani, Julie & Wager, Stefan, 2017. "Generalized Random Forests," Research Papers 3575, Stanford University, Graduate School of Business.
    18. Alexandrov, Alexei & Pittman, Russell & Ukhaneva, Olga, 2017. "Royalty stacking in the U.S. freight railroads: Cournot vs. Coase," MPRA Paper 78249, University Library of Munich, Germany.
    19. Chiou, Yan-Yu & Chen, Mei-Yuan & Chen, Jau-er, 2018. "Nonparametric regression with multiple thresholds: Estimation and inference," Journal of Econometrics, Elsevier, vol. 206(2), pages 472-514.
    20. Daniel L. Chen & Markus Loecher, 2022. "Mood and the Malleability of Moral Reasoning: The Impact of Irrelevant Factors on Judicial Decisions," Working Papers hal-03864854, HAL.
    21. Khashayar Khosravi & Greg Lewis & Vasilis Syrgkanis, 2019. "Non-Parametric Inference Adaptive to Intrinsic Dimension," Papers 1901.03719, arXiv.org, revised Jun 2019.
    22. Victor Chernozhukov & Vira Semenova, 2018. "Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions," CeMMAP working papers CWP40/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Kueck, Jannis & Luo, Ye & Spindler, Martin & Wang, Zigan, 2023. "Estimation and inference of treatment effects with L2-boosting in high-dimensional settings," Journal of Econometrics, Elsevier, vol. 234(2), pages 714-731.
    24. Ryo Aruga & Keiichi Goshima & Takashi Chiba, 2022. "CO2 Emissions and Corporate Performance: Japan's Evidence with Double Machine Learning," IMES Discussion Paper Series 22-E-01, Institute for Monetary and Economic Studies, Bank of Japan.
    25. Lester Mackey & Vasilis Syrgkanis & Ilias Zadik, 2017. "Orthogonal Machine Learning: Power and Limitations," Papers 1711.00342, arXiv.org, revised Aug 2018.
    26. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    27. Lauren Cappiello & Zhiwei Zhang & Changyu Shen & Neel M. Butala & Xinping Cui & Robert W. Yeh, 2021. "Adjusting for population differences using machine learning methods," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 750-769, June.
    28. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations," Papers 1910.09004, arXiv.org, revised Aug 2020.
    29. Crane-Droesch, Andrew, 2017. "Semiparametric Panel Data Using Neural Networks," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258128, Agricultural and Applied Economics Association.
    30. Thai T. Pham & Yuanyuan Shen, 2017. "A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform," Papers 1706.02795, arXiv.org.
    31. Yan-Yu Chiou & Mei-Yuan Chen & Jau-er Chen, 2017. "Nonparametric Regression with Multiple Thresholds: Estimation and Inference," Papers 1705.09418, arXiv.org, revised Feb 2018.

  25. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2016. "Locally Robust Semiparametric Estimation," Papers 1608.00033, arXiv.org, revised Aug 2020.

    Cited by:

    1. Sokbae Lee & Ryo Okui & Yoon†Jae Whang, 2017. "Doubly robust uniform confidence band for the conditional average treatment effect function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1207-1225, November.
    2. Rahul Singh, 2021. "Debiased Kernel Methods," Papers 2102.11076, arXiv.org, revised Mar 2021.
    3. Karun Adusumilli & Dita Eckardt, 2019. "Temporal-Difference estimation of dynamic discrete choice models," Papers 1912.09509, arXiv.org, revised Dec 2022.
    4. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    5. Jiafeng Chen & David M. Ritzwoller, 2021. "Semiparametric Estimation of Long-Term Treatment Effects," Papers 2107.14405, arXiv.org, revised Aug 2023.
    6. Sasaki, Yuya & Ura, Takuya, 2023. "Estimation and inference for policy relevant treatment effects," Journal of Econometrics, Elsevier, vol. 234(2), pages 394-450.
    7. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2019. "Two-Step Estimation and Inference with Possibly Many Included Covariates," University of California at San Diego, Economics Working Paper Series qt86c7x315, Department of Economics, UC San Diego.
    9. Neng-Chieh Chang, 2020. "The Mode Treatment Effect," Papers 2007.11606, arXiv.org.
    10. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
    11. Cordier, J.; & Salvi, I.; & Steinbeck, V.; & Geissler, A.; & Vogel, J.;, 2023. "Is rapid recovery always the best recovery? - Developing a machine learning approach for optimal assignment rules under capacity constraints for knee replacement patients," Health, Econometrics and Data Group (HEDG) Working Papers 23/08, HEDG, c/o Department of Economics, University of York.
    12. Yi Zhang & Eli Ben-Michael & Kosuke Imai, 2022. "Safe Policy Learning under Regression Discontinuity Designs with Multiple Cutoffs," Papers 2208.13323, arXiv.org, revised Jul 2023.
    13. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    14. Lewbel, Arthur & Choi, Jin Young & Zhou, Zhuzhu, 2023. "Over-identified Doubly Robust identification and estimation," Journal of Econometrics, Elsevier, vol. 235(1), pages 25-42.
    15. Santiago Pereda Fernández, 2019. "Identification and estimation of triangular models with a binary treatment," Temi di discussione (Economic working papers) 1210, Bank of Italy, Economic Research and International Relations Area.
    16. Thomas H. Jørgensen, 2021. "Sensitivity to Calibrated Parameters," CEBI working paper series 20-14, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    17. Daniel Jacob, 2021. "CATE meets ML," Digital Finance, Springer, vol. 3(2), pages 99-148, June.
    18. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    19. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Dec 2017.
    20. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    21. Alejandro Sanchez-Becerra, 2023. "Robust inference for the treatment effect variance in experiments using machine learning," Papers 2306.03363, arXiv.org.
    22. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised Nov 2023.
    23. Zhengyuan Zhou & Susan Athey & Stefan Wager, 2023. "Offline Multi-Action Policy Learning: Generalization and Optimization," Operations Research, INFORMS, vol. 71(1), pages 148-183, January.
    24. Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
    25. Mert Demirer & Vasilis Syrgkanis & Greg Lewis & Victor Chernozhukov, 2019. "Semi-Parametric Efficient Policy Learning with Continuous Actions," Papers 1905.10116, arXiv.org, revised Jul 2019.
    26. Jacob, Daniel, 2020. "Cross-Fitting and Averaging for Machine Learning Estimation of Heterogeneous Treatment Effects," IRTG 1792 Discussion Papers 2020-014, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    27. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    28. Chaudhuri, Saraswata & Renault, Eric, 2023. "Efficient estimation of regression models with user-specified parametric model for heteroskedasticty," The Warwick Economics Research Paper Series (TWERPS) 1473, University of Warwick, Department of Economics.
    29. Gyungbae Park, 2024. "Debiased Machine Learning when Nuisance Parameters Appear in Indicator Functions," Papers 2403.15934, arXiv.org.
    30. Doğan, Osman & Taşpınar, Süleyman & Bera, Anil K., 2021. "A Bayesian robust chi-squared test for testing simple hypotheses," Journal of Econometrics, Elsevier, vol. 222(2), pages 933-958.
    31. Taisuke Otsu & Mengshan Xu, 2022. "Isotonic propensity score matching," STICERD - Econometrics Paper Series 623, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    32. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Causal Machine-Learning Approach," Papers 2103.10251, arXiv.org, revised Sep 2021.
    33. Matias D. Cattaneo & Michael Jansson, 2019. "Average Density Estimators: Efficiency and Bootstrap Consistency," Papers 1904.09372, arXiv.org, revised Dec 2020.
    34. Riccardo D'Adamo, 2021. "Orthogonal Policy Learning Under Ambiguity," Papers 2111.10904, arXiv.org, revised Dec 2022.
    35. Anish Agarwal & Rahul Singh, 2021. "Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy," Papers 2107.02780, arXiv.org, revised Feb 2024.
    36. Daniel Jacob, 2021. "CATE meets ML -- The Conditional Average Treatment Effect and Machine Learning," Papers 2104.09935, arXiv.org, revised Apr 2021.
    37. Sant’Anna, Pedro H.C. & Song, Xiaojun, 2019. "Specification tests for the propensity score," Journal of Econometrics, Elsevier, vol. 210(2), pages 379-404.
    38. Nathan Kallus, 2023. "Treatment Effect Risk: Bounds and Inference," Management Science, INFORMS, vol. 69(8), pages 4579-4590, August.
    39. Rahul Singh & Liyang Sun, 2019. "Double Robustness for Complier Parameters and a Semiparametric Test for Complier Characteristics," Papers 1909.05244, arXiv.org, revised Dec 2022.
    40. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Apr 2024.
    41. Ben Deaner, 2021. "Many Proxy Controls," Papers 2110.03973, arXiv.org.
    42. Khashayar Khosravi & Greg Lewis & Vasilis Syrgkanis, 2019. "Non-Parametric Inference Adaptive to Intrinsic Dimension," Papers 1901.03719, arXiv.org, revised Jun 2019.
    43. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
    44. Jooyoung Cha & Harold D. Chiang & Yuya Sasaki, 2021. "Inference in high-dimensional regression models without the exact or $L^p$ sparsity," Papers 2108.09520, arXiv.org, revised Dec 2022.
    45. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    46. Jikai Jin & Vasilis Syrgkanis, 2024. "Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation," Papers 2402.14264, arXiv.org, revised Mar 2024.
    47. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2021. "A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees," Papers 2105.15197, arXiv.org, revised Oct 2022.
    48. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    49. Neng-Chieh Chang, 2018. "Semiparametric Difference-in-Differences with Potentially Many Control Variables," Papers 1812.10846, arXiv.org, revised Jan 2019.
    50. Greg Lewis & Vasilis Syrgkanis, 2020. "Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation," Papers 2002.07285, arXiv.org, revised Jun 2021.
    51. Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2022. "Weighted-average quantile regression," Papers 2203.03032, arXiv.org.
    52. Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
    53. Victor Chernozhukov & Whitney K. Newey & James Robins, 2018. "Double/de-biased machine learning using regularized Riesz representers," CeMMAP working papers CWP15/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    54. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
    55. Keith Battocchi & Eleanor Dillon & Maggie Hei & Greg Lewis & Miruna Oprescu & Vasilis Syrgkanis, 2021. "Estimating the Long-Term Effects of Novel Treatments," Papers 2103.08390, arXiv.org, revised Feb 2022.
    56. Qizhao Chen & Vasilis Syrgkanis & Morgane Austern, 2022. "Debiased Machine Learning without Sample-Splitting for Stable Estimators," Papers 2206.01825, arXiv.org, revised Nov 2022.
    57. Victor Chernozhukov & Vira Semenova, 2018. "Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions," CeMMAP working papers CWP40/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    58. Liu, Yanghui & Li, Yehua & Carroll, Raymond J. & Wang, Naisyin, 2022. "Predictive functional linear models with diverging number of semiparametric single-index interactions," Journal of Econometrics, Elsevier, vol. 230(2), pages 221-239.
    59. Bertille Antoine & Xiaolin Sun, 2022. "Partially linear models with endogeneity: a conditional moment-based approach [Efficient estimation of models with conditional moment restrictions containing unknown functions]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 256-275.
    60. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2021. "Linear IV regression estimators for structural dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 222(1), pages 778-804.
    61. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust decision-making under risk and ambiguity," Papers 2104.12573, arXiv.org, revised Oct 2021.
    62. Stéphane Bonhomme & Martin Weidner, 2020. "Minimizing Sensitivity to Model Misspecification," CeMMAP working papers CWP37/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    63. Rahul Singh & Liyuan Xu & Arthur Gretton, 2021. "Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves," Papers 2111.03950, arXiv.org, revised Jul 2023.
    64. Rahul Singh, 2020. "Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments," Papers 2012.10315, arXiv.org, revised Mar 2023.
    65. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2018. "Deep Neural Networks for Estimation and Inference," Papers 1809.09953, arXiv.org, revised Sep 2019.
    66. Dylan J. Foster & Vasilis Syrgkanis, 2019. "Orthogonal Statistical Learning," Papers 1901.09036, arXiv.org, revised Jun 2023.
    67. Zequn Jin & Lihua Lin & Zhengyu Zhang, 2022. "Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives," Papers 2211.07903, arXiv.org.
    68. Matias D. Cattaneo & Michael Jansson, 2018. "Kernel†Based Semiparametric Estimators: Small Bandwidth Asymptotics and Bootstrap Consistency," Econometrica, Econometric Society, vol. 86(3), pages 955-995, May.
    69. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," CESifo Working Paper Series 9037, CESifo.
    70. Manu Navjeevan & Rodrigo Pinto & Andres Santos, 2023. "Identification and Estimation in a Class of Potential Outcomes Models," Papers 2310.05311, arXiv.org.
    71. Vira Semenova, 2020. "Generalized Lee Bounds," Papers 2008.12720, arXiv.org, revised Feb 2023.
    72. Yusuke Narita & Shota Yasui & Kohei Yata, 2020. "Debiased Off-Policy Evaluation for Recommendation Systems," Papers 2002.08536, arXiv.org, revised Aug 2021.
    73. Pietro Emilio Spini, 2021. "Robustness, Heterogeneous Treatment Effects and Covariate Shifts," Papers 2112.09259, arXiv.org.
    74. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
    75. Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
    76. Xinwei Ma & Jingshen Wang, 2018. "Robust Inference Using Inverse Probability Weighting," Papers 1810.11397, arXiv.org, revised May 2019.
    77. Stéphane Bonhomme & Martin Weidner, 2022. "Minimizing sensitivity to model misspecification," Quantitative Economics, Econometric Society, vol. 13(3), pages 907-954, July.
    78. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    79. Minkyung Kim & K. Sudhir & Kosuke Uetake, 2022. "A Structural Model of a Multitasking Salesforce: Incentives, Private Information, and Job Design," Management Science, INFORMS, vol. 68(6), pages 4602-4630, June.
    80. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust Decision-Making Under Risk and Ambiguity," ECONtribute Discussion Papers Series 104, University of Bonn and University of Cologne, Germany.
    81. Mengshan Xu & Taisuke Otsu, 2022. "Isotonic propensity score matching," Papers 2207.08868, arXiv.org.
    82. Yang Ning & Sida Peng & Jing Tao, 2020. "Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data," Papers 2009.03151, arXiv.org.
    83. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    84. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    85. Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects," Papers 2112.14249, arXiv.org, revised Mar 2024.
    86. Kai Feng & Han Hong, 2024. "Statistical Inference of Optimal Allocations I: Regularities and their Implications," Papers 2403.18248, arXiv.org, revised Apr 2024.
    87. Vasilis Syrgkanis & Ruohan Zhan, 2023. "Post-Episodic Reinforcement Learning Inference," Papers 2302.08854, arXiv.org, revised Jul 2023.

  26. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Dec 2017.

    Cited by:

    1. Heiler, Phillip & Kazak, Ekaterina, 2021. "Valid inference for treatment effect parameters under irregular identification and many extreme propensity scores," Journal of Econometrics, Elsevier, vol. 222(2), pages 1083-1108.
    2. Pradhi Aggarwal & Alec Brandon & Ariel Goldszmidt & Justin Holz & John List & Ian Muir & Gregory Sun & Thomas Yu, 2022. "High-frequency location data shows that race affects the likelihood of being stopped and fined for speeding," Natural Field Experiments 00764, The Field Experiments Website.
    3. Songul Cinaroglu, 2020. "Modelling unbalanced catastrophic health expenditure data by using machine‐learning methods," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 168-181, October.
    4. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    5. Delprato, Marcos & Frola, Alessia & Antequera, Germán, 2022. "Indigenous and non-Indigenous proficiency gaps for out-of-school and in-school populations: A machine learning approach," International Journal of Educational Development, Elsevier, vol. 93(C).
    6. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    7. Xiong, Ruoxuan & Koenecke, Allison & Powell, Michael & Shen, Zhu & Vogelstein, Joshua T. & Athey, Susan, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Research Papers 3990, Stanford University, Graduate School of Business.
    8. Matt Goldman & Brian Quistorff, 2018. "Pricing Engine: Estimating Causal Impacts in Real World Business Settings," Papers 1806.03285, arXiv.org, revised Jun 2018.
    9. Nikolaos Ignatiadis & Wolfgang Huber, 2021. "Covariate powered cross‐weighted multiple testing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 720-751, September.
    10. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Tinbergen Institute Discussion Papers 21-001/V, Tinbergen Institute.
    12. Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018. "Orthogonal Random Forest for Causal Inference," Papers 1806.03467, arXiv.org, revised Sep 2019.
    13. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    14. Gareth Liu-Evans & Shalini Mitra, 2023. "Formal sector enforcement and welfare," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(3), pages 706-728, June.
    15. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    16. Maximilian Maurice Gail & Phil-Adrian Klotz, 2021. "The Impact of the Agency Model on E-book Prices: Evidence from the UK," MAGKS Papers on Economics 202111, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    17. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    18. S Klaassen & J Kueck & M Spindler & V Chernozhukov, 2023. "Uniform inference in high-dimensional Gaussian graphical models," Biometrika, Biometrika Trust, vol. 110(1), pages 51-68.
    19. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
    20. Oliver Hines & Stijn Vansteelandt & Karla Diaz-Ordaz, 2021. "Robust Inference for Mediated Effects in Partially Linear Models," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 595-618, June.
    21. Jong Hee Park & Byung Koo Kim, 2020. "Why your neighbor matters: Positions in preferential trade agreement networks and export growth in global value chains," Economics and Politics, Wiley Blackwell, vol. 32(3), pages 381-410, November.
    22. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    23. Vira Semenova, 2017. "Debiased Machine Learning of Set-Identified Linear Models," Papers 1712.10024, arXiv.org, revised Dec 2022.
    24. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Mar 2024.
    25. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    26. Fernando Delbianco & Fernando Tohmé, 2023. "Individualized Conformal," Working Papers 247, Red Nacional de Investigadores en Economía (RedNIE).
    27. Sander Gerritsen & Mark Kattenberg & Sonny Kuijpers, 2019. "The impact of age at arrival on education and mental health," CPB Discussion Paper 389, CPB Netherlands Bureau for Economic Policy Analysis.
    28. Ziwei Cong & Jia Liu & Puneet Manchanda, 2021. "The Role of "Live" in Livestreaming Markets: Evidence Using Orthogonal Random Forest," Papers 2107.01629, arXiv.org, revised Sep 2022.
    29. Amit Sharma & Emre Kiciman, 2020. "DoWhy: An End-to-End Library for Causal Inference," Papers 2011.04216, arXiv.org.
    30. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised Nov 2023.
    31. Feng, Sanying & Kong, Kaidi & Kong, Yinfei & Li, Gaorong & Wang, Zhaoliang, 2022. "Statistical inference of heterogeneous treatment effect based on single-index model," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    32. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    33. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    34. Fukuyama, Hirofumi & Tsionas, Mike & Tan, Yong, 2023. "Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: Application to the Chinese banking industry," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1360-1373.
    35. Miquel Oliu-Barton & Bary S R Pradelski & Nicolas Woloszko & Lionel Guetta-Jeanrenaud & Philippe Aghion & Patrick Artus & Arnaud Fontanet & Philippe Martin & Guntram B Wolff, 2022. "The Effect of COVID Certificates on Vaccine Uptake, Health Outcomes, and the Economy," Post-Print hal-03813557, HAL.
    36. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    37. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Inference on weighted average value function in high-dimensional state space," Papers 1908.09173, arXiv.org.
    38. Gazeaud, Jules & Khan, Nausheen & Mvukiyehe, Eric & Sterck, Olivier, 2023. "With or without him? Experimental evidence on cash grants and gender-sensitive trainings in Tunisia," Journal of Development Economics, Elsevier, vol. 165(C).
    39. Marica Valente, 2020. "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Papers 2010.01105, arXiv.org, revised Nov 2022.
    40. Waverly Wei & Maya Petersen & Mark J van der Laan & Zeyu Zheng & Chong Wu & Jingshen Wang, 2023. "Efficient targeted learning of heterogeneous treatment effects for multiple subgroups," Biometrics, The International Biometric Society, vol. 79(3), pages 1934-1946, September.
    41. Jinyong Hahn & Jerry Hausman, 2021. "Problems with the Control Variable Approach in Achieving Unbiased Estimates in Nonlinear Models in the Presence of Many Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 39-58, December.
    42. Mark Kattenberg & Bas Scheer & Jurre Thiel, 2023. "Causal forests with fixed effects for treatment effect heterogeneity in difference-in-differences," CPB Discussion Paper 452, CPB Netherlands Bureau for Economic Policy Analysis.
    43. Wang, Hongning & Ma, Sanjun, 2022. "Preventing crimes against public health with artificial intelligence and machine learning capabilities," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    44. Jonas Metzger, 2022. "Adversarial Estimators," Papers 2204.10495, arXiv.org, revised Jun 2022.
    45. Yong Bian & Xiqian Wang & Qin Zhang, 2023. "How Does China's Household Portfolio Selection Vary with Financial Inclusion?," Papers 2311.01206, arXiv.org.
    46. Monica Andini & Emanuele Ciani & Guido de Blasio & Alessio D'Ignazio & Viola Salvestrini, 2017. "Targeting policy-compliers with machine learning: an application to a tax rebate programme in Italy," Temi di discussione (Economic working papers) 1158, Bank of Italy, Economic Research and International Relations Area.
    47. Dongcheng Zhang & Kunpeng Zhang, 2020. "Weighting-Based Treatment Effect Estimation via Distribution Learning," Papers 2012.13805, arXiv.org, revised May 2023.
    48. Sven Klaassen & Jannis Kueck & Martin Spindler, 2017. "Transformation Models in High-Dimensions," Papers 1712.07364, arXiv.org.
    49. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    50. Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
    51. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    52. Jikai Jin & Vasilis Syrgkanis, 2024. "Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation," Papers 2402.14264, arXiv.org, revised Mar 2024.
    53. Francesco Decarolis & Cristina Giorgiantonio, 2020. "Corruption red flags in public procurement: new evidence from Italian calls for tenders," Questioni di Economia e Finanza (Occasional Papers) 544, Bank of Italy, Economic Research and International Relations Area.
    54. Alexander Buchholz & Vito Bellini & Giuseppe Di Benedetto & Yannik Stein & Matteo Ruffini & Fabian Moerchen, 2022. "Fair Effect Attribution in Parallel Online Experiments," Papers 2210.08338, arXiv.org.
    55. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Source Condition Double Robust Inference on Functionals of Inverse Problems," Papers 2307.13793, arXiv.org.
    56. Vira Semenova, 2018. "Machine Learning for Dynamic Discrete Choice," Papers 1808.02569, arXiv.org, revised Nov 2018.
    57. Duncan Simester & Artem Timoshenko & Spyros I. Zoumpoulis, 2020. "Targeting Prospective Customers: Robustness of Machine-Learning Methods to Typical Data Challenges," Management Science, INFORMS, vol. 66(6), pages 2495-2522, June.
    58. Carl Bonander & Mikael Svensson, 2021. "Using causal forests to assess heterogeneity in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1818-1832, August.
    59. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    60. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Post-Print hal-03597819, HAL.
    61. Heigle, Julia & Pfeiffer, Friedhelm, 2019. "An analysis of selected labor market outcomes of college dropouts in Germany: A machine learning estimation approach. Research report," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 222378, September.
    62. Maria Cuellar & Edward H. Kennedy, 2020. "A non‐parametric projection‐based estimator for the probability of causation, with application to water sanitation in Kenya," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1793-1818, October.
    63. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Papers 2101.00878, arXiv.org.
    64. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    65. Falco J. Bargagli Stoffi & Kenneth De Beckker & Joana E. Maldonado & Kristof De Witte, 2021. "Assessing Sensitivity of Machine Learning Predictions.A Novel Toolbox with an Application to Financial Literacy," Papers 2102.04382, arXiv.org.
    66. Ashkan Ertefaie & Nima S. Hejazi & Mark J. van der Laan, 2023. "Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso," Biometrics, The International Biometric Society, vol. 79(2), pages 1029-1041, June.
    67. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    68. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    69. Andr'es Ram'irez-Hassan & Raquel Vargas-Correa & Gustavo Garc'ia & Daniel Londo~no, 2020. "Optimal selection of the number of control units in kNN algorithm to estimate average treatment effects," Papers 2008.06564, arXiv.org.
    70. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations," Papers 1910.09004, arXiv.org, revised Aug 2020.
    71. Zhen Li & Jie Chen & Eric Laber & Fang Liu & Richard Baumgartner, 2023. "Optimal Treatment Regimes: A Review and Empirical Comparison," International Statistical Review, International Statistical Institute, vol. 91(3), pages 427-463, December.
    72. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    73. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    74. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
    75. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    76. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    77. Wang, Xiqian & Bian, Yong & Zhang, Qin, 2023. "The effect of cooking fuel choice on the elderly’s well-being: Evidence from two non-parametric methods," Energy Economics, Elsevier, vol. 125(C).
    78. Johannes Jakubik & Stefan Feuerriegel, 2022. "Data‐driven allocation of development aid toward sustainable development goals: Evidence from HIV/AIDS," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2739-2756, June.

  27. Sören Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2015. "Individual Heterogeneity, Nonlinear Budget Sets, and Taxable Income," CESifo Working Paper Series 5320, CESifo.

    Cited by:

    1. Claudia Keser & David Masclet & Claude Montmarquette, 2020. "Labor Supply, Taxation, and the Use of Tax Revenues: A Real-Effort Experiment in Canada, France, and Germany," Public Finance Review, , vol. 48(6), pages 714-750, November.
    2. Einav, Liran & Finkelstein, Amy & Schrimpf, Paul, 2017. "Bunching at the kink: Implications for spending responses to health insurance contracts," Journal of Public Economics, Elsevier, vol. 146(C), pages 27-40.
    3. Bertanha, Marinho & McCallum, Andrew H. & Seegert, Nathan, 2023. "Better bunching, nicer notching," Journal of Econometrics, Elsevier, vol. 237(2).
    4. Sören Blomquist & Whitney Newey & Anil Kumar & Che-Yuan Liang, 2017. "On Bunching and Identification of the Taxable Income Elasticity," NBER Working Papers 24136, National Bureau of Economic Research, Inc.
    5. Einav, Liran & Finkelstein, Amy & Schrimpf, Paul, 2019. "Reprint of: Bunching at the kink: Implications for spending responses to health insurance contracts," Journal of Public Economics, Elsevier, vol. 171(C), pages 117-130.
    6. Liang, Che-Yuan, 2018. "Taxes and Household Labor Supply: Estimating Distributional Effects of Nonlinear Prices on Multidimensional Choice," Working Paper Series 2018:2, Uppsala University, Department of Economics.
    7. Sören Blomquist & Laurent Simula, 2019. "Marginal deadweight loss when the income tax is nonlinear," Post-Print halshs-01644460, HAL.
    8. Anil Kumar & Che-Yuan Liang, 2016. "Estimating Taxable Income Responses with Elasticity Heterogeneity," Working Papers 1611, Federal Reserve Bank of Dallas.
    9. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    10. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.
    11. Daniel Wilhelm, 2019. "Testing for the presence of measurement error," CeMMAP working papers CWP48/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    13. Gregory Cox, 2018. "Almost Sure Uniqueness of a Global Minimum Without Convexity," Papers 1803.02415, arXiv.org, revised Feb 2019.
    14. Soren Blomquist & Whitney K. Newey, 2017. "The bunching estimator cannot identify the taxable income elasticity," CeMMAP working papers 40/17, Institute for Fiscal Studies.
    15. Hernandez-Pizarro, Helena & Nicodemo, Catia & Casasnovas, Guillem López, 2020. "Discontinuous System of Allowances: The Response of Prosocial Health-Care Professionals," IZA Discussion Papers 13758, Institute of Labor Economics (IZA).
    16. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers 33/17, Institute for Fiscal Studies.
    17. Sören Blomquist, 2023. "Evaluating the Discrete Choice and BN Methods to Estimate Labor Supply Functions," CESifo Working Paper Series 10827, CESifo.
    18. Kumar, Anil & Liang, Che-Yuan, 2015. "The Taxable Income Elasticity: A Structural Differencing Approach," Working Paper Series, Center for Fiscal Studies 2015:1, Uppsala University, Department of Economics.
    19. Soren Blomquist & Whitney K. Newey, 2017. "The bunching estimator cannot identify the taxable income elasticity," CeMMAP working papers CWP40/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Leonard Goff, 2022. "Treatment Effects in Bunching Designs: The Impact of Mandatory Overtime Pay on Hours," Papers 2205.10310, arXiv.org, revised Nov 2023.
    21. Liang, Che-Yuan, 2014. "Distribution-Free Structural Estimation with Nonlinear Budget Sets," Working Paper Series, Center for Fiscal Studies 2014:4, Uppsala University, Department of Economics.
    22. Christopher Dobronyi & Christian Gouri'eroux, 2020. "Consumer Theory with Non-Parametric Taste Uncertainty and Individual Heterogeneity," Papers 2010.13937, arXiv.org, revised Jan 2021.
    23. Jerry Hausman & Whitney K. Newey, 2014. "Individual Heterogeneity and Average Welfare," CeMMAP working papers 42/14, Institute for Fiscal Studies.
    24. Richard Blundell, 2017. "What Have We Learned from Structural Models?," American Economic Review, American Economic Association, vol. 107(5), pages 287-292, May.

  28. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2015. "Constrained conditional moment restriction models," CeMMAP working papers CWP59/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Isaiah Andrews & Jonathan Roth & Ariel Pakes, 2023. "Inference for Linear Conditional Moment Inequalities," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(6), pages 2763-2791.
    2. Zheng Fang & Andres Santos & Azeem Shaikh & Alexander Torgovitsky, 2020. "Inference for Large-Scale Linear Systems with Known Coefficients," Working Papers 2020-134, Becker Friedman Institute for Research In Economics.
    3. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Fernández-Val, Iván, 2019. "Conditional quantile processes based on series or many regressors," Journal of Econometrics, Elsevier, vol. 213(1), pages 4-29.
    4. Zheng Fang & Juwon Seo, 2021. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Econometrica, Econometric Society, vol. 89(5), pages 2439-2458, September.
    5. Matias D. Cattaneo & Xinwei Ma & Yusufcan Masatlioglu & Elchin Suleymanov, 2020. "A Random Attention Model," Journal of Political Economy, University of Chicago Press, vol. 128(7), pages 2796-2836.
    6. Vira Semenova, 2023. "Adaptive Estimation of Intersection Bounds: a Classification Approach," Papers 2303.00982, arXiv.org.
    7. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
    8. Chen, Qihui, 2021. "Robust and optimal estimation for partially linear instrumental variables models with partial identification," Journal of Econometrics, Elsevier, vol. 221(2), pages 368-380.
    9. Christoph Breunig & Xiaohong Chen, 2020. "Adaptive, Rate-Optimal Hypothesis Testing in Nonparametric IV Models," Papers 2006.09587, arXiv.org, revised Feb 2024.
    10. Xiaohong Chen & Demian Pouzo & James L. Powell, 2019. "Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions," Papers 1902.10100, arXiv.org.
    11. Lee, Ying-Ying & Bhattacharya, Debopam, 2019. "Applied welfare analysis for discrete choice with interval-data on income," Journal of Econometrics, Elsevier, vol. 211(2), pages 361-387.
    12. Patrick Kline & Christopher Walters, 2021. "Reasonable Doubt: Experimental Detection of Job‐Level Employment Discrimination," Econometrica, Econometric Society, vol. 89(2), pages 765-792, March.
    13. Babii, Andrii & Kumar, Rohit, 2023. "Isotonic regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 234(2), pages 371-393.
    14. Ivan Korolev, 2018. "A Consistent Heteroskedasticity Robust LM Type Specification Test for Semiparametric Models," Papers 1810.07620, arXiv.org, revised Nov 2019.
    15. Khashayar Khosravi & Greg Lewis & Vasilis Syrgkanis, 2019. "Non-Parametric Inference Adaptive to Intrinsic Dimension," Papers 1901.03719, arXiv.org, revised Jun 2019.
    16. Kline, Patrick & Walters, Christopher, 2019. "Audits as Evidence: Experiments, Ensembles, and Enforcement," Institute for Research on Labor and Employment, Working Paper Series qt3z72m9kn, Institute of Industrial Relations, UC Berkeley.
    17. Roy Allen & John Rehbeck, 2020. "Identification of Random Coefficient Latent Utility Models," Papers 2003.00276, arXiv.org.
    18. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
    19. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers CWP14/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Isaac Loh, 2024. "Inference under partial identification with minimax test statistics," Papers 2401.13057, arXiv.org, revised Apr 2024.
    21. Matias D. Cattaneo & Max H. Farrell & Yingjie Feng, 2018. "Large Sample Properties of Partitioning-Based Series Estimators," Papers 1804.04916, arXiv.org, revised Jun 2019.
    22. Christoph Breunig & Xiaohong Chen, 2020. "Adaptive, Rate-Optimal Hypothesis Testing in Nonparametric IV Models," Cowles Foundation Discussion Papers 2238R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2021.
    23. Zheng Fang, 2021. "A Unifying Framework for Testing Shape Restrictions," Papers 2107.12494, arXiv.org, revised Aug 2021.
    24. Giovanni Compiani, 2022. "Market counterfactuals and the specification of multiproduct demand: A nonparametric approach," Quantitative Economics, Econometric Society, vol. 13(2), pages 545-591, May.

  29. Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2015. "Inference in Linear Regression Models with Many Covariates and Heteroskedasticity," Papers 1507.02493, arXiv.org, revised Jan 2017.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2019. "Two-Step Estimation and Inference with Possibly Many Included Covariates," University of California at San Diego, Economics Working Paper Series qt86c7x315, Department of Economics, UC San Diego.
    3. Sabrina L. Di Addario & Patrick M. Kline & Raffaele Saggio & Mikkel Sølvsten, 2021. "It Ain’t Where You’re From, It’s Where You’re At: Hiring Origins, Firm Heterogeneity, and Wages," NBER Working Papers 28917, National Bureau of Economic Research, Inc.
    4. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
    5. Yanqin Fan & Fang Han & Wei Li & Xiao-Hua Zhou, 2019. "On rank estimators in increasing dimensions," Papers 1908.05255, arXiv.org.
    6. Zhuan Pei & Jörn-Steffen Pischke & Hannes Schwandt, 2017. "Poorly Measured Confounders are More Useful on the Left Than on the Right," NBER Working Papers 23232, National Bureau of Economic Research, Inc.
    7. Anatolyev, Stanislav, 2021. "Mallows criterion for heteroskedastic linear regressions with many regressors," Economics Letters, Elsevier, vol. 203(C).
    8. Fan, Yanqin & Han, Fang & Li, Wei & Zhou, Xiao-Hua, 2020. "On rank estimators in increasing dimensions," Journal of Econometrics, Elsevier, vol. 214(2), pages 379-412.
    9. Michal Koles'ar & Ulrich K. Muller & Sebastian T. Roelsgaard, 2023. "The Fragility of Sparsity," Papers 2311.02299, arXiv.org, revised Jan 2024.
    10. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP04/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    12. Anatolyev, Stanislav & Sølvsten, Mikkel, 2023. "Testing many restrictions under heteroskedasticity," Journal of Econometrics, Elsevier, vol. 236(1).
    13. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    14. Patrick Kline & Raffaele Saggio & Mikkel S{o}lvsten, 2018. "Leave-out estimation of variance components," Papers 1806.01494, arXiv.org, revised Aug 2019.
    15. Braun, Martin & Verdier, Valentin, 2023. "Estimation of spillover effects with matched data or longitudinal network data," Journal of Econometrics, Elsevier, vol. 233(2), pages 689-714.
    16. Kuanhao Jiang & Rajarshi Mukherjee & Subhabrata Sen & Pragya Sur, 2022. "A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyond," Papers 2205.10198, arXiv.org, revised Oct 2022.
    17. Prat, Andrea & Montiel Olea , José Luis & Ortoleva, Pietro & Pai, Mallesh, 2019. "Competing Models," CEPR Discussion Papers 14066, C.E.P.R. Discussion Papers.
      • Jose Luis Montiel Olea & Pietro Ortoleva & Mallesh M Pai & Andrea Prat, 2019. "Competing Models," Papers 1907.03809, arXiv.org, revised Nov 2021.
    18. Mittag, Nikolas, 2019. "A simple method to estimate large fixed effects models applied to wage determinants," Labour Economics, Elsevier, vol. 61(C).
    19. Ng Cheuk Fai, 2022. "Robust Inference in High Dimensional Linear Model with Cluster Dependence," Papers 2212.05554, arXiv.org.
    20. Pötscher, Benedikt M. & Preinerstorfer, David, 2021. "Valid Heteroskedasticity Robust Testing," MPRA Paper 107420, University Library of Munich, Germany.
    21. Riccardo D'Adamo, 2018. "Cluster-Robust Standard Errors for Linear Regression Models with Many Controls," Papers 1806.07314, arXiv.org, revised Apr 2019.
    22. Sabrina Di Addario & Patrick Kline & Raffaele Saggio & Mikkel Soelvsten, 2022. "It ain't where you're from it's where you're at: firm effects, state dependence, and the gender wage gap," Temi di discussione (Economic working papers) 1374, Bank of Italy, Economic Research and International Relations Area.
    23. Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org.
    24. James G. MacKinnon, 2022. "Using Large Samples in Econometrics," Working Paper 1482, Economics Department, Queen's University.
    25. Liang Jiang & Liyao Li & Ke Miao & Yichong Zhang, 2023. "Adjustment with Many Regressors Under Covariate-Adaptive Randomizations," Papers 2304.08184, arXiv.org, revised Feb 2024.
    26. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
    27. Jochmans, K., 2019. "Heteroskedasticity-Robust Inference in Linear Regression Models," Cambridge Working Papers in Economics 1957, Faculty of Economics, University of Cambridge.
    28. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    29. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2023. "Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 235(1), pages 166-179.
    30. He, Yi & Jaidee, Sombut & Gao, Jiti, 2023. "Most powerful test against a sequence of high dimensional local alternatives," Journal of Econometrics, Elsevier, vol. 234(1), pages 151-177.
    31. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    32. Annalivia Polselli, 2023. "Robust Inference in Panel Data Models: Some Effects of Heteroskedasticity and Leveraged Data in Small Samples," Papers 2312.17676, arXiv.org.
    33. Valentin Verdier, 2020. "Estimation and Inference for Linear Models with Two-Way Fixed Effects and Sparsely Matched Data," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 1-16, March.
    34. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2020. "Deep Learning for Individual Heterogeneity: An Automatic Inference Framework," Papers 2010.14694, arXiv.org, revised Jul 2021.
    35. Richard, Patrick, 2019. "Residual bootstrap tests in linear models with many regressors," Journal of Econometrics, Elsevier, vol. 208(2), pages 367-394.

  30. Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2015. "Treatment Effects with Many Covariates and Heteroskedasticity," CREATES Research Papers 2015-31, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Fernández-Val, Iván, 2019. "Conditional quantile processes based on series or many regressors," Journal of Econometrics, Elsevier, vol. 213(1), pages 4-29.
    2. Holland, Ashley D., 2017. "Penalized spline estimation in the partially linear model," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 211-235.

  31. Jerry Hausman & Whitney K. Newey, 2013. "Individual heterogeneity and average welfare," CeMMAP working papers CWP34/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Rahul Deb & Yuichi Kitamura & John Quah & Jorg Stoye, 2018. "Revealed price preference: theory and empirical analysis," CeMMAP working papers CWP57/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    3. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2015. "Individual heterogeneity, nonlinear budget sets and taxable income," CeMMAP working papers 21/15, Institute for Fiscal Studies.
    4. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    5. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae Lee, 2018. "The identification power of smoothness assumptions in models with counterfactual outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 617-642, July.
    6. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae (Simon) Lee, 2014. "The identification power of smoothness assumptions in models with counterfactual outcomes," CeMMAP working papers 17/14, Institute for Fiscal Studies.
    7. Rachel Griffith & Lars Nesheim & Martin O'Connell, 2015. "Income effects and the welfare consequences of tax in differentiated product oligopoly," CeMMAP working papers CWP23/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Stefan Hoderlein & Hajo Holzmann & Alexander Meister, 2015. "The triangular model with random coefficients," CeMMAP working papers CWP33/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
    10. Michael Bates & Seolah Kim, 2019. "Estimating the Price Elasticity of Gasoline Demand in Correlated Random Coefficient Models with Endogeneity," Working Papers 202021, University of California at Riverside, Department of Economics, revised Jul 2020.
    11. Ming Li, 2021. "A Time-Varying Endogenous Random Coefficient Model with an Application to Production Functions," Papers 2110.00982, arXiv.org.
    12. Sören Blomquist & Laurent Simula, 2019. "Marginal deadweight loss when the income tax is nonlinear," Post-Print halshs-01644460, HAL.
    13. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    14. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    15. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.
    16. Stefan Hoderlein & Jörg Stoye, 2015. "Testing stochastic rationality and predicting stochastic demand: the case of two goods," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 3(2), pages 313-328, October.
    17. Bhattacharya, D., 2018. "The Empirical Content of Binary Choice Models," Cambridge Working Papers in Economics 1883, Faculty of Economics, University of Cambridge.
    18. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    19. Breunig, Christoph & Hoderlein, Stefan, 2018. "Specification Testing in Random Coefficient Models," Rationality and Competition Discussion Paper Series 77, CRC TRR 190 Rationality and Competition.
    20. Whitney K. Newey & Sami Stouli, 2018. "Heterogenous coefficients, discrete instruments, and identification of treatment effects," CeMMAP working papers CWP66/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    22. Chen, Haotian & Smyth, Russell & Zhang, Xibin, 2017. "A Bayesian sampling approach to measuring the price responsiveness of gasoline demand using a constrained partially linear model," Energy Economics, Elsevier, vol. 67(C), pages 346-354.
    23. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    24. Christoph Breunig & Stefan Hoderlein, 2016. "Nonparametric Specification Testing in Random Parameter Models," Boston College Working Papers in Economics 897, Boston College Department of Economics.
    25. Whitney K. Newey & Sami Stouli, 2018. "Control variables, discrete instruments, and identification of structural functions," CeMMAP working papers CWP55/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Thomas Demuynck, 2018. "Testing the homogeneous marginal utility of income assumption," ULB Institutional Repository 2013/251991, ULB -- Universite Libre de Bruxelles.
    27. Laurens Cherchye & Bram De Rock & Frederic Vermeulen, 2023. "Nonparametric Models in Consumer Behaviour," Working Papers ECARES 2023-04, ULB -- Universite Libre de Bruxelles.
    28. Krishna Pendakur, 2018. "Welfare analysis when people are different," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 51(2), pages 321-360, May.
    29. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Lee, Ying-Ying & Bhattacharya, Debopam, 2019. "Applied welfare analysis for discrete choice with interval-data on income," Journal of Econometrics, Elsevier, vol. 211(2), pages 361-387.
    31. Gregory Cox, 2018. "Almost Sure Uniqueness of a Global Minimum Without Convexity," Papers 1803.02415, arXiv.org, revised Feb 2019.
    32. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2019. "Demand and Welfare Analysis in Discrete Choice Models with Social Interactions," CREATES Research Papers 2019-09, Department of Economics and Business Economics, Aarhus University.
    33. Cherchye, Laurens & Demuynck, Thomas & Rock, Bram De, 2019. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Journal of Econometrics, Elsevier, vol. 211(2), pages 483-506.
    34. Bart Capéau & Liebrecht De Sadeleer & Sebastiaan Maes & André M.J. Decoster, 2021. "Nonparametric Welfare Analysis for Discrete Choice: Levels and Differences of Individual and Social Welfare," CESifo Working Paper Series 9071, CESifo.
    35. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
    36. KANEKO Shinji & KAWATA Keisuke & YIN Ting, 2019. "Estimating Family Preference for Home Elderly-care Services: Large-scale Conjoint Survey Experiment in Japan," Discussion papers 19092, Research Institute of Economy, Trade and Industry (RIETI).
    37. Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
    38. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers 33/17, Institute for Fiscal Studies.
    39. Joshua Lanier & Jeremy Large & John Quah, 2022. "Estimating very large demand systems," Economics Series Working Papers 998, University of Oxford, Department of Economics.
    40. Rahul Deb & Yuichi Kitamura & John K.-H. Quah & Jorg Stoye, 2017. "Revealed Price Preference: Theory and Stochastic Testing," Cowles Foundation Discussion Papers 2087, Cowles Foundation for Research in Economics, Yale University.
    41. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Beyond the Mean : Testing Consumer Rationality through Higher Moments of Demand," CRETA Online Discussion Paper Series 85, Centre for Research in Economic Theory and its Applications CRETA.
    42. Giovanni Compiani, 2022. "Market counterfactuals and the specification of multiproduct demand: A nonparametric approach," Quantitative Economics, Econometric Society, vol. 13(2), pages 545-591, May.
    43. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    44. Christopher Dobronyi & Christian Gouri'eroux, 2020. "Consumer Theory with Non-Parametric Taste Uncertainty and Individual Heterogeneity," Papers 2010.13937, arXiv.org, revised Jan 2021.
    45. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    46. Demuynck, T., 2015. "The homogeneous marginal utility of income assumption," Research Memorandum 013, Maastricht University, Graduate School of Business and Economics (GSBE).
    47. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," CRETA Online Discussion Paper Series 84, Centre for Research in Economic Theory and its Applications CRETA.
    48. Glenn W. Harrison, 2019. "The behavioral welfare economics of insurance," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 44(2), pages 137-175, September.
    49. Yadira Diaz, 2015. "Differences in needs and multidimensional deprivation measurement," Working Papers 387, ECINEQ, Society for the Study of Economic Inequality.

  32. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney Newey, 2013. "Nonparametric Identification in Panels using Quantiles," Papers 1312.4094, arXiv.org, revised Aug 2014.

    Cited by:

    1. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    4. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    5. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2016. "Maximum Likelihood Estimation in Possibly Misspeci ed Dynamic Models with Time-Inhomogeneous Markov Regimes," Department of Economics Working Papers 2016_04, Universidad Torcuato Di Tella.
    6. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    7. Čížek, Pavel & Lei, Jinghua, 2018. "Identification and estimation of nonseparable single-index models in panel data with correlated random effects," Journal of Econometrics, Elsevier, vol. 203(1), pages 113-128.
    8. Victor Chernozhukov & Iván Fernández‐Val & Ye Luo, 2018. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Econometrica, Econometric Society, vol. 86(6), pages 1911-1938, November.
    9. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    10. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
    11. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    12. Ishihara, Takuya, 2020. "Identification and estimation of time-varying nonseparable panel data models without stayers," Journal of Econometrics, Elsevier, vol. 215(1), pages 184-208.
    13. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    14. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    15. D’Haultfœuille, Xavier & Hoderlein, Stefan & Sasaki, Yuya, 2023. "Nonparametric difference-in-differences in repeated cross-sections with continuous treatments," Journal of Econometrics, Elsevier, vol. 234(2), pages 664-690.
    16. Matthew Harding & Carlos Lamarche, 2018. "A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment," Papers 1808.03364, arXiv.org.
    17. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2022. "Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities," Econometrica, Econometric Society, vol. 90(4), pages 1681-1710, July.
    18. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
    19. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers CWP12/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Linton, O. & Shiu, J-L., 2019. "Semiparametric Nonlinear Panel Data Models with Measurement Error," Cambridge Working Papers in Economics 1906, Faculty of Economics, University of Cambridge.
    21. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers 33/17, Institute for Fiscal Studies.
    22. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.
    23. Stefan Hoderlein & Hajo Holzmann & Maximilian Kasy & Alexander Meister, 2015. "Erratum regarding “Instrumental variables with unrestricted heterogeneity and continuous treatment”," Boston College Working Papers in Economics 896, Boston College Department of Economics, revised 01 Feb 2016.
    24. Irene Botosaru & Chris Muris & Krishna Pendakur, 2020. "Intertemporal Collective Household Models: Identification in Short Panels with Unobserved Heterogeneity in Resource Shares," Department of Economics Working Papers 2020-09, McMaster University.
    25. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Discussion Paper 2022-009, Tilburg University, Center for Economic Research.
    26. Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.
    27. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.

  33. Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2012. "Alternative Asymptotics and the Partially Linear Model with Many Regressors," CREATES Research Papers 2012-02, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Matias D. Cattaneo & Max H. Farrell & Michael Jansson & Ricardo Masini, 2022. "Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators," Papers 2301.00277, arXiv.org, revised Feb 2024.
    2. Wang, Wenjie, 2021. "Bootstrap Inference for Partially Linear Model with Many Regressors," MPRA Paper 106391, University Library of Munich, Germany.
    3. Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2019. "Two-Step Estimation and Inference with Possibly Many Included Covariates," University of California at San Diego, Economics Working Paper Series qt86c7x315, Department of Economics, UC San Diego.
    4. Yanqin Fan & Fang Han & Wei Li & Xiao-Hua Zhou, 2019. "On rank estimators in increasing dimensions," Papers 1908.05255, arXiv.org.
    5. Galbraith, John W. & Zinde-Walsh, Victoria, 2020. "Simple and reliable estimators of coefficients of interest in a model with high-dimensional confounding effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 609-632.
    6. Bruce E. Hansen, 2016. "The Risk of James--Stein and Lasso Shrinkage," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1456-1470, December.
    7. Anatolyev, Stanislav, 2021. "Mallows criterion for heteroskedastic linear regressions with many regressors," Economics Letters, Elsevier, vol. 203(C).
    8. Duncan Sheppard Gilchrist & Emily Glassberg Sands, 2016. "Something to Talk About: Social Spillovers in Movie Consumption," Journal of Political Economy, University of Chicago Press, vol. 124(5), pages 1339-1382.
    9. Fan, Yanqin & Han, Fang & Li, Wei & Zhou, Xiao-Hua, 2020. "On rank estimators in increasing dimensions," Journal of Econometrics, Elsevier, vol. 214(2), pages 379-412.
    10. Anatolyev, Stanislav & Sølvsten, Mikkel, 2023. "Testing many restrictions under heteroskedasticity," Journal of Econometrics, Elsevier, vol. 236(1).
    11. Kuanhao Jiang & Rajarshi Mukherjee & Subhabrata Sen & Pragya Sur, 2022. "A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyond," Papers 2205.10198, arXiv.org, revised Oct 2022.
    12. Mittag, Nikolas, 2019. "A simple method to estimate large fixed effects models applied to wage determinants," Labour Economics, Elsevier, vol. 61(C).
    13. Riccardo D'Adamo, 2018. "Cluster-Robust Standard Errors for Linear Regression Models with Many Controls," Papers 1806.07314, arXiv.org, revised Apr 2019.
    14. Holland, Ashley D., 2017. "Penalized spline estimation in the partially linear model," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 211-235.
    15. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    16. Harold D Chiang & Yuya Sasaki, 2023. "On Using The Two-Way Cluster-Robust Standard Errors," Papers 2301.13775, arXiv.org.
    17. Richard, Patrick, 2019. "Residual bootstrap tests in linear models with many regressors," Journal of Econometrics, Elsevier, vol. 208(2), pages 367-394.

  34. Xiaohong Chen & Victor Chernozhukov & Sokbae Lee & Whitney Newey, 2011. "Local Identification of Nonparametric and Semiparametric Models," Cowles Foundation Discussion Papers 1795, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999, Cowles Foundation for Research in Economics, Yale University.
    2. Timothy M. Christensen, 2014. "Nonparametric identification of positive eigenfunctions," CeMMAP working papers CWP37/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    4. Yu Zhu, 2020. "Inference in nonparametric/semiparametric moment equality models with shape restrictions," Quantitative Economics, Econometric Society, vol. 11(2), pages 609-636, May.
    5. Dalderop, Jeroen, 2023. "Semiparametric estimation of latent variable asset pricing models," Journal of Econometrics, Elsevier, vol. 236(1).
    6. Chen, Qihui, 2021. "Robust and optimal estimation for partially linear instrumental variables models with partial identification," Journal of Econometrics, Elsevier, vol. 221(2), pages 368-380.
    7. Patrick Bajari & Chenghuan Sean Chu & Denis Nekipelov & Minjung Park, 2013. "A Dynamic Model of Subprime Mortgage Default: Estimation and Policy Implications," NBER Working Papers 18850, National Bureau of Economic Research, Inc.
    8. Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Papers 1411.1144, arXiv.org, revised Mar 2015.
    9. Jaroslav Borovicka & Lars Peter Hansen & Jose A. Scheinkman, 2015. "Misspecified Recovery," Working Papers 063_2014, Princeton University, Department of Economics, Econometric Research Program..
    10. Xiaohong Chen & Demian Pouzo & James L. Powell, 2019. "Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions," Papers 1902.10100, arXiv.org.
    11. Pierre-Andre Chiappori & Ivana Komunjer & Dennis Kristensen, 2011. "Nonparametric Identification and Estimation of Transformation Models," CAM Working Papers 2011-01, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    12. Yingyao Hu & Ji‐Liang Shiu, 2018. "Identification and estimation of semi‐parametric censored dynamic panel data models of short time periods," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 55-85, February.
    13. Matzkin, Rosa L., 2016. "On independence conditions in nonseparable models: Observable and unobservable instruments," Journal of Econometrics, Elsevier, vol. 191(2), pages 302-311.
    14. Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," CeMMAP working papers 38/14, Institute for Fiscal Studies.
    15. Timothy M. Christensen, 2014. "Nonparametric identification of positive eigenfunctions," CeMMAP working papers 37/14, Institute for Fiscal Studies.
    16. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    17. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2015. "Constrained conditional moment restriction models," CeMMAP working papers CWP59/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Patrick Bajari & Chenghuan Sean Chu & Denis Nekipelov & Minjung Park, 2016. "Identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action," Quantitative Marketing and Economics (QME), Springer, vol. 14(4), pages 271-323, December.
    19. Victor Chernozhukov & Christian Hansen, 2013. "Quantile models with endogeneity," CeMMAP working papers CWP25/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    21. Andrew Chesher & Adam Rosen, 2013. "Generalized instrumental variable models," CeMMAP working papers CWP43/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. Cazals, Catherine & Feve, Frederique & Florens, Jean-Pierre & Simar, Leopold, 2016. "Non Parametric Instrumental Variables Estimation for Efficiency Frontier," LIDAM Reprints ISBA 2016014, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    23. Senay Sokullu & Irene Botosaru & Chris Muris, 2022. "Time-Varying Linear Transformation Models with Fixed Effects and Endogeneity for Short Panels," Bristol Economics Discussion Papers 22/756, School of Economics, University of Bristol, UK.
    24. Jason R. Blevins & Wei Shi & Donald R. Haurin & Stephanie Moulton, 2020. "A Dynamic Discrete Choice Model Of Reverse Mortgage Borrower Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1437-1477, November.
    25. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Dunker, Fabian & Florens, Jean-Pierre & Hohage, Thorsten & Johannes, Jan & Mammen, Enno, 2014. "Iterative estimation of solutions to noisy nonlinear operator equations in nonparametric instrumental regression," LIDAM Reprints ISBA 2014007, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    27. Christoph Breunig, 2016. "Specification Testing in Nonparametric Instrumental Quantile Regression," SFB 649 Discussion Papers SFB649DP2016-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Marcin Penconek & Paweł Strawiński, 2022. "Generalisation of the gross flows model," Working Papers 2022-17, Faculty of Economic Sciences, University of Warsaw.
    29. Victor H. Aguiar & Nail Kashaev, 2018. "Stochastic Revealed Preferences with Measurement Error," Papers 1810.05287, arXiv.org, revised Sep 2020.
    30. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness," Papers 2302.05404, arXiv.org.
    31. Loh, Isaac, 2023. "Genericity of the completeness condition with constrained instruments," Economics Letters, Elsevier, vol. 224(C).
    32. Doug J. Chung & Byungyeon Kim & Byoung G. Park, 2021. "The Comprehensive Effects of Sales Force Management: A Dynamic Structural Analysis of Selection, Compensation, and Training," Management Science, INFORMS, vol. 67(11), pages 7046-7074, November.
    33. Arthur Lewbel, 2018. "The Identification Zoo - Meanings of Identification in Econometrics," Boston College Working Papers in Economics 957, Boston College Department of Economics, revised 14 Dec 2019.
    34. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    35. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    36. Ben Deaner, 2018. "Proxy Controls and Panel Data," Papers 1810.00283, arXiv.org, revised Nov 2023.
    37. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    38. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    39. Fabian Dunker, 2015. "Adaptive estimation for some nonparametric instrumental variable models," Papers 1511.03977, arXiv.org, revised Aug 2021.
    40. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.

  35. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity," Departmental Working Papers 201118, Rutgers University, Department of Economics.

    Cited by:

    1. Walter Beckert, 2020. "A Note on Specification Testing in Some Structural Regression Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 686-695, June.
    2. Matej Tomec & Timotej Jagric, 2017. "Does the Amount and Time of Recapitalization Affect the Profitability of Commercial Banks?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(4), pages 318-341, August.
    3. Jafari-Sadeghi, Vahid & Sukumar, Arun & Pagán-Castaño, Esther & Dana, Léo-Paul, 2021. "What drives women towards domestic vs international business venturing? An empirical analysis in emerging markets," Journal of Business Research, Elsevier, vol. 134(C), pages 647-660.
    4. Frank Windmeijer, 2018. "Testing Over- and Underidentification in Linear Models, with Applications to Dynamic Panel Data and Asset-Pricing Models," Bristol Economics Discussion Papers 18/696, School of Economics, University of Bristol, UK.
    5. Hyunseok Jung & Xiaodong Liu, 2023. "Testing for Peer Effects without Specifying the Network Structure," Papers 2306.09806, arXiv.org, revised Mar 2024.
    6. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    7. Anatolyev, Stanislav & Sølvsten, Mikkel, 2023. "Testing many restrictions under heteroskedasticity," Journal of Econometrics, Elsevier, vol. 236(1).
    8. Crudu, Federico & Mellace, Giovanni & Sándor, Zsolt, 2021. "Inference In Instrumental Variable Models With Heteroskedasticity And Many Instruments," Econometric Theory, Cambridge University Press, vol. 37(2), pages 281-310, April.
    9. Wang, Wenjie, 2022. "Wild bootstrap test of overidentification with many instruments and heteroskedasticity," MPRA Paper 115168, University Library of Munich, Germany.
    10. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2020. "Optimal Minimax Rates against Non-smooth Alternatives," KIER Working Papers 1051, Kyoto University, Institute of Economic Research.
    11. Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2020. "Leave‐Out Estimation of Variance Components," Econometrica, Econometric Society, vol. 88(5), pages 1859-1898, September.
    12. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.
    13. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
    14. Paul Goldsmith-Pinkham & Isaac Sorkin & Henry Swift, 2020. "Bartik Instruments: What, When, Why, and How," American Economic Review, American Economic Association, vol. 110(8), pages 2586-2624, August.
    15. Matsushita, Yukitoshi & Otsu, Taisuke, 2022. "A jackknife Lagrange multiplier test with many weak instruments," LSE Research Online Documents on Economics 116392, London School of Economics and Political Science, LSE Library.
    16. Tugrul Gurgur, 2016. "Voice, exit and local capture in public provision of private goods," Economics of Governance, Springer, vol. 17(4), pages 397-424, November.
    17. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    18. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised Mar 2023.
    19. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    20. Alla Koblyakova & Larisa Fleishman & Orly Furman, 2022. "Accuracy of Households’ Dwelling Valuations, Housing Demand and Mortgage Decisions: Israeli Case," The Journal of Real Estate Finance and Economics, Springer, vol. 65(1), pages 48-74, July.
    21. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    22. Díaz Antonia & Puch Luis A., 2019. "Investment, technological progress and energy efficiency," The B.E. Journal of Macroeconomics, De Gruyter, vol. 19(2), pages 1-28, June.
    23. Marine Carrasco & Mohamed Doukali, 2022. "Testing overidentifying restrictions with many instruments and heteroscedasticity using regularised jackknife IV [Specification testing in models with many instruments]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 71-97.
    24. Tom Boot & Johannes W. Ligtenberg, 2023. "Identification- and many instrument-robust inference via invariant moment conditions," Papers 2303.07822, arXiv.org, revised Sep 2023.
    25. Jafari-Sadeghi, Vahid, 2020. "The motivational factors of business venturing: Opportunity versus necessity? A gendered perspective on European countries," Journal of Business Research, Elsevier, vol. 113(C), pages 279-289.
    26. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2018. "Rate Optimal Specification Test When the Number of Instruments is Large," KIER Working Papers 986, Kyoto University, Institute of Economic Research.
    27. Atsushi Inoue & Barbara Rossi, 2015. "Tests for the validity of portfolio or group choice in financial and panel regressions," Economics Working Papers 1523, Department of Economics and Business, Universitat Pompeu Fabra.
    28. Wang, Wenjie, 2020. "On Bootstrap Validity for the Test of Overidentifying Restrictions with Many Instruments and Heteroskedasticity," MPRA Paper 104858, University Library of Munich, Germany.
    29. Zhenhong Huang & Chen Wang & Jianfeng Yao, 2023. "Assessing the strength of many instruments with the first-stage F and Cragg-Donald statistics," Papers 2302.14423, arXiv.org.

  36. Chao & Swanson & Hausman & Newey & Woutersen, 2010. "Asymptotic Distribution of JIVE in a Heteroskedastic IV Regression with Many Instruments," Economics Working Paper Archive 567, The Johns Hopkins University,Department of Economics.

    Cited by:

    1. Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2015. "Alternative Asymptotics and the Partially Linear Model with Many Regressors," Papers 1505.08120, arXiv.org.
    2. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
    3. Cheng Hsiao & Qiankun Zhou, 2017. "JIVE for Panel Dynamic Simultaneous Equations Models," Departmental Working Papers 2017-10, Department of Economics, Louisiana State University.
    4. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2016. "Inference in High-Dimensional Panel Models With an Application to Gun Control," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 590-605, October.
    5. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity," Departmental Working Papers 201118, Rutgers University, Department of Economics.
    6. Matsushita, Yukitoshi & Otsu, Taisuke, 2020. "Jackknife empirical likelihood: small bandwidth, sparse network and high-dimension asymptotic," LSE Research Online Documents on Economics 106488, London School of Economics and Political Science, LSE Library.
    7. Joshua Angrist & Brigham Frandsen, 2019. "Machine Labor," NBER Working Papers 26584, National Bureau of Economic Research, Inc.
    8. Brian P. Poi, 2006. "Jackknife instrumental variables estimation in Stata," Stata Journal, StataCorp LP, vol. 6(3), pages 364-376, September.
    9. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.
    10. Hyunseok Jung & Xiaodong Liu, 2023. "Testing for Peer Effects without Specifying the Network Structure," Papers 2306.09806, arXiv.org, revised Mar 2024.
    11. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    12. Anatolyev, Stanislav & Mikusheva, Anna, 2021. "Limit Theorems For Factor Models," Econometric Theory, Cambridge University Press, vol. 37(5), pages 1034-1074, October.
    13. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
    14. Wang, Wenjie & Doko Tchatoka, Firmin, 2018. "On Bootstrap inconsistency and Bonferroni-based size-correction for the subset Anderson–Rubin test under conditional homoskedasticity," Journal of Econometrics, Elsevier, vol. 207(1), pages 188-211.
    15. Federico Crudu & Giovanni Mellace & Zsolt Sandor, 2017. "Inference in instrumental variables models with heteroskedasticity and many instruments," Department of Economics University of Siena 761, Department of Economics, University of Siena.
    16. Alena Skolkova, 2023. "Instrumental Variable Estimation with Many Instruments Using Elastic-Net IV," CERGE-EI Working Papers wp759, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    17. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
    18. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    19. Anatolyev, Stanislav & Sølvsten, Mikkel, 2023. "Testing many restrictions under heteroskedasticity," Journal of Econometrics, Elsevier, vol. 236(1).
    20. Michal Kolesár & Raj Chetty & John Friedman & Edward Glaeser & Guido W. Imbens, 2015. "Identification and Inference With Many Invalid Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 474-484, October.
    21. Andersson, Jonas & Møen, Jarle, 2009. "A simple improvement of the IV estimator for the classical errors-in-variables problem," Discussion Papers 2009/10, Norwegian School of Economics, Department of Business and Management Science.
    22. Yukitoshi Matsushita & Taisuke Otsu, 2020. "Jackknife Lagrange multiplier test with many weak instruments," STICERD - Econometrics Paper Series 613, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    23. Amanda Linell & Edwin Muchapondwa & Herbert Ntuli & Martin Sjöstedt & Sverker C. Jagers, 2018. "Factors influencing people’s perceptions towards conservation of transboundary wildlife resources. The case of the Great-Limpopo Trans-frontier Conservation Area," Working Papers 765, Economic Research Southern Africa.
    24. Díaz Antonia & Puch Luis A., 2019. "Investment, technological progress and energy efficiency," The B.E. Journal of Macroeconomics, De Gruyter, vol. 19(2), pages 1-28, June.
    25. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
    26. Marine Carrasco & Mohamed Doukali, 2022. "Testing overidentifying restrictions with many instruments and heteroscedasticity using regularised jackknife IV [Specification testing in models with many instruments]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 71-97.
    27. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    28. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
    29. Patrick Kline & Raffaele Saggio & Mikkel S{o}lvsten, 2018. "Leave-out estimation of variance components," Papers 1806.01494, arXiv.org, revised Aug 2019.
    30. Manu Navjeevan, 2023. "An Identification and Dimensionality Robust Test for Instrumental Variables Models," Papers 2311.14892, arXiv.org.
    31. Tom Boot & Johannes W. Ligtenberg, 2023. "Identification- and many instrument-robust inference via invariant moment conditions," Papers 2303.07822, arXiv.org, revised Sep 2023.
    32. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    33. Kirill S. Evdokimov & Michal Kolesár, 2018. "Inference in Instrumental Variable Regression Analysis with Heterogeneous Treatment Effects," Working Papers 2018-16, Princeton University. Economics Department..
    34. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    35. Bekker, Paul & Wansbeek, Tom, 2016. "Simple many-instruments robust standard errors through concentrated instrumental variables," Economics Letters, Elsevier, vol. 149(C), pages 52-55.
    36. Yukitoshi Matsushita & Taisuke Otsu, 2019. "Jackknife, small bandwidth and high-dimensional asymptotics," STICERD - Econometrics Paper Series 605, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    37. Anna Mikusheva & Liyang Sun, 2020. "Inference with Many Weak Instruments," Papers 2004.12445, arXiv.org, revised Oct 2021.
    38. Michal Kolesár, 2013. "Estimation in an Instrumental Variables Model With Treatment Effect Heterogeneity," Working Papers 2013-2, Princeton University. Economics Department..
    39. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.
    40. Lei Bill Wang, 2023. "Estimating overidentified linear models with heteroskedasticity and outliers," Papers 2305.17615, arXiv.org, revised Apr 2024.
    41. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
    42. Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org.
    43. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    44. John C. Chao & Jerry A. Hausman & Whitney K. Newey & Norman R. Swanson & Tiemen Woutersen, 2012. "Combining Two Consistent Estimators," Advances in Econometrics, in: Essays in Honor of Jerry Hausman, pages 33-53, Emerald Group Publishing Limited.
    45. Matsushita, Yukitoshi & Otsu, Taisuke, 2023. "Second-order refinements for t-ratios with many instruments," Journal of Econometrics, Elsevier, vol. 232(2), pages 346-366.
    46. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
    47. Chenchuan (Mark) Li & Ulrich K. Müller, 2020. "Linear Regression with Many Controls of Limited Explanatory Power," Working Papers 2020-57, Princeton University. Economics Department..
    48. Brian Asquith, 2019. "Do Rent Increases Reduce the Housing Supply Under Rent Control? Evidence from Evictions in San Francisco," Upjohn Working Papers 19-296, W.E. Upjohn Institute for Employment Research.
    49. Matsushita, Yukitoshi & Otsu, Taisuke, 2022. "A jackknife Lagrange multiplier test with many weak instruments," LSE Research Online Documents on Economics 116392, London School of Economics and Political Science, LSE Library.
    50. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    51. Matsushita, Yukitoshi & Otsu, Taisuke, 2023. "Second-order refinements for t-ratios with many instruments," LSE Research Online Documents on Economics 111065, London School of Economics and Political Science, LSE Library.
    52. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    53. Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.
    54. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    55. Stanislav Anatolyev, 2012. "Instrumental variables estimation and inference in the presence of many exogenous regressors," Working Papers w0162, Center for Economic and Financial Research (CEFIR).
    56. Luther Yap, 2023. "Valid Wald Inference with Many Weak Instruments," Papers 2311.15932, arXiv.org.
    57. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    58. Boot, Tom, 2023. "Joint inference based on Stein-type averaging estimators in the linear regression model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1542-1563.
    59. Atsushi Inoue & Barbara Rossi, 2015. "Tests for the validity of portfolio or group choice in financial and panel regressions," Economics Working Papers 1523, Department of Economics and Business, Universitat Pompeu Fabra.
    60. Wang, Wenjie, 2020. "On Bootstrap Validity for the Test of Overidentifying Restrictions with Many Instruments and Heteroskedasticity," MPRA Paper 104858, University Library of Munich, Germany.
    61. Jochmans, Koen, 2023. "Many (Weak) Judges in Judge-Leniency Designs," TSE Working Papers 23-1481, Toulouse School of Economics (TSE).
    62. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
    63. Anna Mikusheva & Liyang Sun, 2023. "Weak Identification with Many Instruments," Papers 2308.09535, arXiv.org, revised Jan 2024.
    64. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    65. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.

  37. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney Newey, 2009. "Identification and Estimation of Marginal Effects in Nonlinear Panel Models," Boston University - Department of Economics - Working Papers Series wp2009-b, Boston University - Department of Economics.

    Cited by:

    1. Shiu, Ji-Liang & Hu, Yingyao, 2013. "Identification and estimation of nonlinear dynamic panel data models with unobserved covariates," Journal of Econometrics, Elsevier, vol. 175(2), pages 116-131.
    2. Martin Browning & Jesus M. Carro, 2009. "Dynamic binary outcome models with maximal heterogeneity," Economics Series Working Papers 426, University of Oxford, Department of Economics.
    3. Ali Fakih, 2014. "Availability of Family-Friendly Work Practices and Implicit Wage Costs: New Evidence from Canada," CIRANO Working Papers 2014s-33, CIRANO.
    4. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2016. "Identification of panel data models with endogenous censoring," Journal of Econometrics, Elsevier, vol. 194(1), pages 57-75.
    5. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, vol. 166(1), pages 127-137.
    6. Andrei Markevich & Ekaterina Zhuravskaya, 2011. "M-form hierarchy with poorly-diversified divisions: A case of Khrushchev's reform in Soviet Russia," Post-Print halshs-00754499, HAL.
    7. Andrei Markevich & Ekaterina Zhuravskaya, 2009. "Career Concerns in a Political Hierarchy: A Case of Regional Leaders in Soviet Russia," Working Papers w0040, Center for Economic and Financial Research (CEFIR).
    8. Ali Fakih, 2014. "Vacation Leave, Work Hours And Wages: New Evidence From Linked Employer-Employee Data," CIRANO Papers 2014n-11a, CIRANO.
    9. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    10. Manuel Arellano & Stéphane Bonhomme, 2009. "Identifying Distributional Characteristics in Random Coefficients Panel Data Models," Working Papers wp2009_0904, CEMFI.
    11. Lewbel, Arthur & Yang, Thomas Tao, 2016. "Identifying the average treatment effect in ordered treatment models without unconfoundedness," Journal of Econometrics, Elsevier, vol. 195(1), pages 1-22.
    12. Philip Kostov & Julie Le Gallo, 2015. "Convergence: A Story of Quantiles and Spillovers," Kyklos, Wiley Blackwell, vol. 68(4), pages 552-576, November.
    13. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    14. Ciani, Emanuele, 2012. "Informal adult care and caregivers' employment in Europe," Labour Economics, Elsevier, vol. 19(2), pages 155-164.
    15. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
    16. Hyland, Marie & Bertsch, Valentin, 2018. "The Role of Community Involvement Mechanisms in Reducing Resistance to Energy Infrastructure Development," Ecological Economics, Elsevier, vol. 146(C), pages 447-474.
    17. Kyungchul Song, 2009. "Point Decisions for Interval-Identified Parameters," PIER Working Paper Archive 09-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    18. Hu, Yingyao, 2017. "The Econometrics of Unobservables -- Latent Variable and Measurement Error Models and Their Applications in Empirical Industrial Organization and Labor Economics [The Econometrics of Unobservables]," Economics Working Paper Archive 64578, The Johns Hopkins University,Department of Economics, revised 2021.
    19. Valentin Bertsch & Hyland, Marie & Mahony, Michael, 2016. "What Drives People’s Opinions of Electricity Infrastructure? Empirical Evidence from Ireland," Papers WP545, Economic and Social Research Institute (ESRI).
    20. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.

  38. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2009. "Quantile and average effects in nonseparable panel models," CeMMAP working papers CWP29/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    2. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, vol. 166(1), pages 127-137.
    3. Fernando Ubeda & Francisco Pérez-Hernández, 2017. "Absorptive Capacity and Geographical Distance Two Mediating Factors of FDI Spillovers: a Threshold Regression Analysis for Spanish Firms," Journal of Industry, Competition and Trade, Springer, vol. 17(1), pages 1-28, March.
    4. Gao, Yichen & Li, Cong & Liang, Zhongwen, 2015. "Binary response correlated random coefficient panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 421-434.
    5. Stefan Hoderlein & Yuya Sasaki, 2011. "On the role of time in nonseparable panel data models," CeMMAP working papers CWP15/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. David Powell, 2010. "Unconditional Quantile Treatment Effects in the Presence of Covariates," Working Papers WR-816, RAND Corporation.
    7. Charles F. Manski & John V. Pepper, 2011. "Deterrence and the Death Penalty: Partial Identification Analysis Using Repeated Cross Sections," NBER Working Papers 17455, National Bureau of Economic Research, Inc.
    8. Harding, Matthew & Lamarche, Carlos, 2012. "Estimating and Testing a Quantile Regression Model with Interactive Effects," IZA Discussion Papers 6802, Institute of Labor Economics (IZA).
    9. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.

  39. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney Newey, 2009. "Average and Quantile Effects in Nonseparable Panel Models," Papers 0904.1990, arXiv.org, revised Mar 2013.

    Cited by:

    1. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    2. Paulo M.M. Rodrigues & Matei Demetrescu, 2022. "Cross-Sectional Error Dependence in Panel Quantile Regressions," Working Papers w202213, Banco de Portugal, Economics and Research Department.
    3. Demetrescu, Matei & Hosseinkouchack, Mehdi & Rodrigues, Paulo M. M., 2023. "Tests of no cross-sectional error dependence in panel quantile regressions," Ruhr Economic Papers 1041, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-rank approximations of nonseparable panel models," CeMMAP working papers CWP52/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Xavier d'Haultfoeuille & Roland Rathelot, 2011. "Measuring Segregation on Small Units : A Partial Identification Analysis," Working Papers 2011-18, Center for Research in Economics and Statistics.
    7. Jesus M. Carro & Alejandra Traferri, 2014. "State Dependence And Heterogeneity In Health Using A Bias‐Corrected Fixed‐Effects Estimator," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 181-207, March.
    8. Peter Hull, 2018. "Estimating Treatment Effects in Mover Designs," Papers 1804.06721, arXiv.org.
    9. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    10. Carro, Jesús M. & Pronkina, Elizaveta, 2021. "The heterogeneous effects of the Great Recession on informal care to the elderly," UC3M Working papers. Economics 33444, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Christopher Dobronyi & Jiaying Gu & Kyoo il Kim, 2021. "Identification of Dynamic Panel Logit Models with Fixed Effects," Papers 2104.04590, arXiv.org, revised Apr 2021.
    12. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
    13. Victor Aguirregabiria & Jiaying Gu & Yao Luo, 2018. "Sufficient Statistics for Unobserved Heterogeneity in Structural Dynamic Logit Models," Working Papers tecipa-603, University of Toronto, Department of Economics.
    14. Kevin Dano, 2023. "Transition Probabilities and Moment Restrictions in Dynamic Fixed Effects Logit Models," Papers 2303.00083, arXiv.org, revised Dec 2023.
    15. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    16. Victor Aguirregabiria & Jesus M. Carro, 2021. "Identification of Average Marginal Effects in Fixed Effects Dynamic Discrete Choice Models," Papers 2107.06141, arXiv.org.
    17. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    18. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Desire Kedagni & Kala Krishna & Rigissa Megalokonomou & Yingyan Zhao, 2019. "Does Class Size Matter? How, and at What Cost?," NBER Working Papers 25736, National Bureau of Economic Research, Inc.
    20. Shu Yang & Yunshu Zhang, 2023. "Multiply robust matching estimators of average and quantile treatment effects," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 235-265, March.
    21. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney K. Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers 66/13, Institute for Fiscal Studies.
    22. Laurent Davezies & Xavier D'Haultfœuille & Martin Mugnier, 2023. "Fixed‐effects binary choice models with three or more periods," Quantitative Economics, Econometric Society, vol. 14(3), pages 1105-1132, July.
    23. Laurent Davezies & Xavier D'Haultfoeuille & Louise Laage, 2021. "Identification and Estimation of Average Marginal Effects in Fixed Effects Logit Models," Papers 2105.00879, arXiv.org, revised Oct 2022.
    24. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    25. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Andrew Chesher & Adam Rosen & Yuanqi Zhang, 2024. "Robust analysis of short panels," CeMMAP working papers 01/24, Institute for Fiscal Studies.
    27. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    28. Cavit Pakel & Martin Weidner, 2023. "Bounds on Average Effects in Discrete Choice Panel Data Models," Papers 2309.09299, arXiv.org, revised Dec 2023.
    29. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods," Papers 1803.09015, arXiv.org, revised Dec 2020.
    30. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2016. "Identification of panel data models with endogenous censoring," Journal of Econometrics, Elsevier, vol. 194(1), pages 57-75.
    31. Clément de Chaisemartin & Xavier D’haultfœuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," Post-Print hal-03873885, HAL.
    32. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    33. Pauline Givord & Lionel Wilner, 2015. "When Does the Stepping‐Stone Work? Fixed‐Term Contracts Versus Temporary Agency Work in Changing Economic Conditions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 787-805, August.
    34. Michelle Marcus & Pedro H. C. Sant’Anna, 2021. "The Role of Parallel Trends in Event Study Settings: An Application to Environmental Economics," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 8(2), pages 235-275.
    35. Xavier D'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear Difference-in-Differences in Repeated Cross Sections with Continuous Treatments," Boston College Working Papers in Economics 839, Boston College Department of Economics.
    36. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    37. Čížek, Pavel & Lei, Jinghua, 2018. "Identification and estimation of nonseparable single-index models in panel data with correlated random effects," Journal of Econometrics, Elsevier, vol. 203(1), pages 113-128.
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    1. Bruno Amable & Karim Azizi, 2014. "Counter-cyclical budget policy across varieties of capitalism," Post-Print hal-00941813, HAL.
    2. Daniel L. Bennett & Hugo J. Faria & James D. Gwartney & Hugo M. Montesinos-Yufa & Daniel R. Morales & Carlos E. Navarro, 2017. "Evidence on economic versus political institutions as determinants of development," Working Papers 2017-04, University of Miami, Department of Economics.

  41. Christian Hansen & James B. McDonald & Whitney K. Newey, 2007. "Instrumental variables estimation with flexible distribution," CeMMAP working papers CWP21/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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    1. Amsler, Christine & Artem, Prokhorov & Peter, Schmidt, 2015. "Endogeneity in Stochastic Frontier Models," Working Papers 2015-01, University of Sydney Business School, Discipline of Business Analytics.
    2. Jason Cook & James McDonald, 2013. "Partially Adaptive Estimation of Interval Censored Regression Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 119-131, June.
    3. James B. McDonald & Daniel B. Walton & Bryan Chia, 2020. "Distributional Assumptions and the Estimation of Contingent Valuation Models," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 431-460, August.
    4. Tsionas, Efthymios G., 2013. "Bayesian inference in regression with Pearson disturbances," Economics Letters, Elsevier, vol. 118(1), pages 177-181.
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    6. Siemsen, Thomas & Vilsmeier, Johannes, 2018. "On a quest for robustness: About model risk, randomness and discretion in credit risk stress tests," Discussion Papers 31/2018, Deutsche Bundesbank.
    7. Juraj Pekár & Mário Pčolár, 2022. "Empirical distribution of daily stock returns of selected developing and emerging markets with application to financial risk management," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 699-731, June.
    8. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.
    9. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    10. Sean C. Kerman & James B. McDonald, 2012. "Skewness-kurtosis bounds for the skewed generalized T and related distributions," BYU Macroeconomics and Computational Laboratory Working Paper Series 2012-10, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    11. Ng Serena & Bai Jushan, 2009. "Selecting Instrumental Variables in a Data Rich Environment," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-34, April.
    12. Guizzardi, Andrea & Ballestra, Luca Vincenzo & D'Innocenzo, Enzo, 2022. "Hotel dynamic pricing, stochastic demand and covid-19," Annals of Tourism Research, Elsevier, vol. 97(C).
    13. Sikora, Grzegorz & Michalak, Anna & Bielak, Łukasz & Miśta, Paweł & Wyłomańska, Agnieszka, 2019. "Stochastic modeling of currency exchange rates with novel validation techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1202-1215.
    14. Oh Kang Kwon & Stephen Satchell, 2020. "The Distribution of Cross Sectional Momentum Returns When Underlying Asset Returns Are Student’s t Distributed," JRFM, MDPI, vol. 13(2), pages 1-19, February.
    15. Scott Alan Carson & Wael M. Al-Sawai & Scott A. Carson, 2023. "Partially Adaptive Econometric Methods and Vertically Integrated Majors in the Oil and Gas Industry," CESifo Working Paper Series 10733, CESifo.
    16. Szarek, Dawid & Bielak, Łukasz & Wyłomańska, Agnieszka, 2020. "Long-term prediction of the metals’ prices using non-Gaussian time-inhomogeneous stochastic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    17. Zhi, Bangdong & Wang, Xiaojun & Xu, Fangming, 2020. "Impawn rate optimisation in inventory financing: A canonical vine copula-based approach," International Journal of Production Economics, Elsevier, vol. 227(C).
    18. John Deke & Mariel Finucane & Daniel Thal, "undated". "The BASIE (BAyeSian Interpretation of Estimates) Framework for Interpreting Findings from Impact Evaluations: A Practical Guide for Education Researchers," Mathematica Policy Research Reports 5a0d5dff375d42048799878be, Mathematica Policy Research.
    19. McDonald, James & Stoddard, Olga & Walton, Daniel, 2018. "On using interval response data in experimental economics," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 72(C), pages 9-16.
    20. Shum, Wai Yan, 2020. "Modelling conditional skewness: Heterogeneous beliefs, short sale restrictions and market declines," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    21. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.

  42. Jerry Hausman & Whitney K. Newey & Tiemen M. Woutersen & John Chao & Norman Swanson, 2007. "Instrumental variable estimation with heteroskedasticity and many instruments," CeMMAP working papers CWP22/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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    1. Jorge Gallego & Stanislao Maldonado & Lorena Trujillo, 2018. "Blessing a Curse? Institutional Reform and Resource Booms in Colombia," Working Papers 122, Peruvian Economic Association.
    2. Morricone, Serena & Munari, Federico & Oriani, Raffaele & de Rassenfosse, Gaetan, 2017. "Commercialization Strategy and IPO Underpricing," Research Policy, Elsevier, vol. 46(6), pages 1133-1141.
    3. Einiö, Elias, 2016. "The loss of production work: evidence from quasiexperimental identification of labour demand functions," LSE Research Online Documents on Economics 69019, London School of Economics and Political Science, LSE Library.
    4. Eric French & Jae Song, 2014. "The Effect of Disability Insurance Receipt on Labor Supply," American Economic Journal: Economic Policy, American Economic Association, vol. 6(2), pages 291-337, May.
    5. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
    6. Amanda Y. Agan & Jennifer L. Doleac & Anna Harvey, 2021. "Misdemeanor Prosecution," NBER Working Papers 28600, National Bureau of Economic Research, Inc.
    7. Bekker, Paul A. & Crudu, Federico, 2012. "Symmetric Jackknife Instrumental Variable Estimation," MPRA Paper 37853, University Library of Munich, Germany.
    8. Alyssa G. Anderson & Wenxin Du & Bernd Schlusche, 2021. "Arbitrage Capital of Global Banks," Finance and Economics Discussion Series 2021-032, Board of Governors of the Federal Reserve System (U.S.).
    9. Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. John C. Chao & Jerry A. Hausman & Whitney K. Newey & Norman R. Swanson & Tiemen Woutersen, 2012. "An Expository Note on the Existence of Moments of Fuller and HFUL Estimators," Advances in Econometrics, in: Essays in Honor of Jerry Hausman, pages 87-106, Emerald Group Publishing Limited.
    11. Regis Barnichon & Geert Mesters, 2020. "Identifying Modern Macro Equations with Old Shocks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(4), pages 2255-2298.
    12. Steven Andrew Culpepper & Herman Aguinis & Justin L. Kern & Roger Millsap, 2019. "High-Stakes Testing Case Study: A Latent Variable Approach for Assessing Measurement and Prediction Invariance," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 285-309, March.
    13. Matsushita, Yukitoshi & Otsu, Taisuke, 2020. "Jackknife empirical likelihood: small bandwidth, sparse network and high-dimension asymptotic," LSE Research Online Documents on Economics 106488, London School of Economics and Political Science, LSE Library.
    14. Attanasio, Orazio & Low, Hamish & Sánchez-Marcos, Virginia & Levell, Peter, 2015. "Aggregating Elasticities: Intensive and Extensive Margins of Female Labour Supply," CEPR Discussion Papers 10732, C.E.P.R. Discussion Papers.
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    73. Anna Mikusheva & Liyang Sun, 2020. "Inference with Many Weak Instruments," Papers 2004.12445, arXiv.org, revised Oct 2021.
    74. Bertille Antoine & Otilia Boldea, 2015. "Efficient Inference with Time-Varying Information and the New Keynesian Phillips Curve," Discussion Papers dp15-04, Department of Economics, Simon Fraser University, revised 25 Aug 2016.
    75. Alderighi, Stefano & Cleary, Siobhan & Varanasi, Padmasai, 2019. "Do institutional factors influence cross-border portfolio equity flows? New evidence from emerging markets," Journal of International Money and Finance, Elsevier, vol. 99(C).
    76. Simona Laura Dragoş & Codruţa Mare & Cristian Mihai Dragoş, 2019. "Institutional drivers of life insurance consumption: a dynamic panel approach for European countries," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 44(1), pages 36-66, January.
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    79. Guy Tchuente, 2021. "A Note on the Topology of the First Stage of 2SLS with Many Instruments," Papers 2106.15003, arXiv.org.
    80. Ryusei Shingaki & Hiroshi Kanda & Manabu Kuroki, 2021. "Selection and integration of generalized instrumental variables for estimating total effects," Statistical Papers, Springer, vol. 62(5), pages 2355-2381, October.
    81. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.
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    83. Guy Tchuente, 2019. "Weak Identification and Estimation of Social Interaction Models," Papers 1902.06143, arXiv.org.
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    85. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
    86. Marine Carrasco & Guy Tchuente, 2016. "Regularization Based Anderson Rubin Tests for Many Instruments," Studies in Economics 1608, School of Economics, University of Kent.
    87. Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org.
    88. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
    89. Doko Tchatoka, Firmin, 2012. "Testing for partial exogeneity with weak identification," Working Papers 14565, University of Tasmania, Tasmanian School of Business and Economics, revised 31 May 2012.
    90. Matsushita, Yukitoshi & Otsu, Taisuke, 2023. "Second-order refinements for t-ratios with many instruments," Journal of Econometrics, Elsevier, vol. 232(2), pages 346-366.
    91. Choi, Yoonseok, 2021. "Inflation dynamics, the role of inflation at different horizons and inflation uncertainty," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 649-662.
    92. Lee, Yoonseok & Okui, Ryo, 2012. "Hahn–Hausman test as a specification test," Journal of Econometrics, Elsevier, vol. 167(1), pages 133-139.
    93. Sina Golara & Kevin J. Dooley & Nasim Mousavi, 2021. "Are Dealers Still Relevant? How Dealer Service Quality Impacts Manufacturer Success," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3560-3578, October.
    94. Canay, Ivan A., 2010. "Simultaneous selection and weighting of moments in GMM using a trapezoidal kernel," Journal of Econometrics, Elsevier, vol. 156(2), pages 284-303, June.
    95. Emmanuel Abokyi & Dirk Strijker & Kofi Fred Asiedu & Michiel N. Daams, 2022. "Buffer Stock Operations and Well-Being: The Case of Smallholder Farmers in Ghana," Journal of Happiness Studies, Springer, vol. 23(1), pages 125-148, January.
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    100. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference for high-dimensional sparse econometric models," CeMMAP working papers CWP41/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    101. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
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    105. Bai Huang & Tae-Hwy Lee & Aman Ullah, 2017. "A combined estimator of regression models with measurement errors," Indian Economic Review, Springer, vol. 52(1), pages 73-91, December.
    106. Sébastien Mary & Avraham Stoler, 2021. "Does agricultural trade liberalization increase obesity in developing countries?," Review of Development Economics, Wiley Blackwell, vol. 25(3), pages 1326-1350, August.
    107. Zenou, Yves & Patacchini, Eleonora & Rainone, Edoardo, 2012. "Student Networks and Long-Run Educational Outcomes: The Strength of Strong Ties," CEPR Discussion Papers 9149, C.E.P.R. Discussion Papers.
    108. Calhoun, Gray, 2010. "Hypothesis Testing in Linear Regression when K/N is Large," Staff General Research Papers Archive 32216, Iowa State University, Department of Economics.
    109. Xuexin WANG, 2021. "Instrumental variable estimation via a continuum of instruments with an application to estimating the elasticity of intertemporal substitution in consumption," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    110. Zhu, Ying, 2013. "Sparse Linear Models and Two-Stage Estimation in High-Dimensional Settings with Possibly Many Endogenous Regressors," MPRA Paper 49846, University Library of Munich, Germany.
    111. Joel L. Horowitz, 2017. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers 46/17, Institute for Fiscal Studies.
    112. Michelle S. Goeree, 2009. "Caught in the Bulimic Trap: Do Eating Disorders Reflect Addictive Behavior?," 2009 Meeting Papers 241, Society for Economic Dynamics.
    113. Martín Besfamille & Diego Jorrat & Ósmel Manzano & Bernardo F. Quiroga & Pablo Sanguinetti & Martin Besfamille, 2021. "How Do Subnational Governments React to Shocks to Different Revenue Sources? Evidence from Hydrocarbon-Producing Provinces in Argentina," CESifo Working Paper Series 9251, CESifo.
    114. Herbst, Chris M., 2013. "The impact of non-parental child care on child development: Evidence from the summer participation “dip”," Journal of Public Economics, Elsevier, vol. 105(C), pages 86-105.
    115. Wenjie Wang & Qingfeng Liu, 2015. "Bootstrap-based Selection for Instrumental Variables Model," Economics Bulletin, AccessEcon, vol. 35(3), pages 1886-1896.
    116. Joel L. Horowitz, 2018. "Non-Asymptotic Inference in Instrumental Variables Estimation," Papers 1809.03600, arXiv.org.
    117. Davide Antonioli & Georgios Gioldasis & Antonio Musolesi, 2018. "Estimating a non-neutral production function: a heterogeneous treatment effect approach," SEEDS Working Papers 0618, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2018.
    118. Hyclak, Thomas J. & Skeels, Christopher L. & Taylor, Larry W., 2016. "The cardiovascular revolution and economic performance in the OECD countries," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 114-125.
    119. Horowitz, Joel L., 2021. "Bounding the difference between true and nominal rejection probabilities in tests of hypotheses about instrumental variables models," Journal of Econometrics, Elsevier, vol. 222(2), pages 1057-1082.
    120. Matthew C. Harding & Jerry Hausman & Christopher Palmer, 2015. "Finite sample bias corrected IV estimation for weak and many instruments," CeMMAP working papers 41/15, Institute for Fiscal Studies.
    121. Florens, Jean-Pierre & Van Bellegem, Sébastien, 2015. "Instrumental variable estimation in functional linear models," Journal of Econometrics, Elsevier, vol. 186(2), pages 465-476.
    122. Matsushita, Yukitoshi & Otsu, Taisuke, 2023. "Second-order refinements for t-ratios with many instruments," LSE Research Online Documents on Economics 111065, London School of Economics and Political Science, LSE Library.
    123. Liu, Xiaodong, 2012. "On the consistency of the LIML estimator of a spatial autoregressive model with many instruments," Economics Letters, Elsevier, vol. 116(3), pages 472-475.
    124. Daniel A. Ackerberg & Paul J. Devereux, 2008. "Improved Jive Estimators for Overidentified Linear Models with and without Heteroskedasticity," Working Papers 200817, School of Economics, University College Dublin.
    125. Cássio Roberto de Andrade Alves & Márcio Laurini, 2023. "Estimating the Capital Asset Pricing Model with Many Instruments: A Bayesian Shrinkage Approach," Mathematics, MDPI, vol. 11(17), pages 1-20, September.
    126. Nshakira-Rukundo, Emmanuel & Mussa, Essa Chanie & Gerber, Nicolas & von Braun, Joachim, 2020. "Impact of voluntary community-based health insurance on child stunting: Evidence from rural Uganda," Social Science & Medicine, Elsevier, vol. 245(C).
    127. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    128. Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.
    129. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2010. "LASSO Methods for Gaussian Instrumental Variables Models," Papers 1012.1297, arXiv.org, revised Feb 2011.
    130. Boubacar Diallo, 2022. "Machine learning approaches to testing institutional hypotheses: the case of Acemoglu, Johnson, and Robinson (2001)," Empirical Economics, Springer, vol. 62(5), pages 2587-2600, May.
    131. Yiqi Lin & Frank Windmeijer & Xinyuan Song & Qingliang Fan, 2022. "On the instrumental variable estimation with many weak and invalid instruments," Papers 2207.03035, arXiv.org, revised Dec 2023.
    132. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    133. Joaquin Sanchez & Carmen Abril & Michael Haenlein, 2020. "Competitive spillover elasticities of electronic word of mouth: an application to the soft drink industry," Journal of the Academy of Marketing Science, Springer, vol. 48(2), pages 270-287, March.
    134. Stanislav Anatolyev, 2012. "Instrumental variables estimation and inference in the presence of many exogenous regressors," Working Papers w0162, Center for Economic and Financial Research (CEFIR).
    135. Okui, Ryo, 2011. "Instrumental variable estimation in the presence of many moment conditions," Journal of Econometrics, Elsevier, vol. 165(1), pages 70-86.
    136. Federico Nutarelli & Massimo Riccaboni & Andrea Morescalchi, 2021. "Product recalls, market size and innovation in the pharmaceutical industry," Papers 2111.15389, arXiv.org.
    137. Jesse Edgerton, 2011. "Estimating machinery supply elasticities using output price booms," Finance and Economics Discussion Series 2011-03, Board of Governors of the Federal Reserve System (U.S.).
    138. Joel L. Horowitz, 2018. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers CWP52/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    139. Herbst, Chris M., 2012. "The Impact of Non-Parental Child Care on Child Development: Evidence from the Summer Participation "Dip"," IZA Discussion Papers 7039, Institute of Labor Economics (IZA).
    140. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    141. Martins, Luis F. & Gabriel, Vasco J., 2014. "Linear instrumental variables model averaging estimation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 709-724.
    142. Nicolò Barbieri & Ugo Rizzo, 2023. "The impact of crime on firm entry," Journal of Regional Science, Wiley Blackwell, vol. 63(2), pages 446-469, March.
    143. Svenja G�rtner, 2016. "New Macroeconomic Evidence on Internal Migration in Sweden, 1967-2003," Regional Studies, Taylor & Francis Journals, vol. 50(1), pages 137-153, January.
    144. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    145. Wang, Wenjie, 2020. "On Bootstrap Validity for the Test of Overidentifying Restrictions with Many Instruments and Heteroskedasticity," MPRA Paper 104858, University Library of Munich, Germany.
    146. Antoine, Bertille & Boldea, Otilia, 2018. "Efficient estimation with time-varying information and the New Keynesian Phillips Curve," Journal of Econometrics, Elsevier, vol. 204(2), pages 268-300.
    147. Zhenhong Huang & Chen Wang & Jianfeng Yao, 2023. "Assessing the strength of many instruments with the first-stage F and Cragg-Donald statistics," Papers 2302.14423, arXiv.org.
    148. Bertille Antoine & Otilia Boldea, 2014. "Efficient Inference with Time-Varying Identification Strength," Discussion Papers dp14-03, Department of Economics, Simon Fraser University.
    149. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
    150. Anna Mikusheva & Liyang Sun, 2023. "Weak Identification with Many Instruments," Papers 2308.09535, arXiv.org, revised Jan 2024.
    151. Van Bellegem, Sébastien & Florens, Jean-Pierre, 2014. "Instrumental variable estimation in functional linear models," LIDAM Discussion Papers CORE 2014056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    152. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    153. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.
    154. Thomas Wiemann, 2023. "Optimal Categorical Instrumental Variables," Papers 2311.17021, arXiv.org.

  44. Whitney K. Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Maurice J. G. Bun & Frank Windmeijer, 2010. "The weak instrument problem of the system GMM estimator in dynamic panel data models," Econometrics Journal, Royal Economic Society, vol. 13(1), pages 95-126, February.
    2. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity," Departmental Working Papers 201118, Rutgers University, Department of Economics.
    3. Todd, Prono, 2010. "Simple GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 20034, University Library of Munich, Germany.
    4. Yoonseok Lee & Mehmet Caner & Xu Han, 2015. "Adaptive Elastic Net GMM Estimation with Many Invalid Moment Conditions: Simultaneous Model and Moment Selection," Center for Policy Research Working Papers 177, Center for Policy Research, Maxwell School, Syracuse University.
    5. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    6. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    7. Patrizia Ordine & Giuseppe Rose, 2008. "Local Banks Efficiency and Employment," LABOUR, CEIS, vol. 22(3), pages 469-493, September.
    8. Chao & Swanson & Hausman & Newey & Woutersen, 2010. "Asymptotic Distribution of JIVE in a Heteroskedastic IV Regression with Many Instruments," Economics Working Paper Archive 567, The Johns Hopkins University,Department of Economics.
    9. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    10. Frank Windmeijer, 2006. "GMM for panel count data models," CeMMAP working papers CWP21/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Stanislav Anatolyev, 2007. "Inference about predictive ability when there are many predictors," Working Papers w0096, New Economic School (NES).
    12. Yoonseok Lee & Ryo Okui, 2009. "A Specification Test for Instrumental Variables Regression with Many Instruments," Cowles Foundation Discussion Papers 1741, Cowles Foundation for Research in Economics, Yale University.
    13. Travaglini, Guido, 2010. "Dynamic Econometric Testing of Climate Change and of its Causes," MPRA Paper 23600, University Library of Munich, Germany.
    14. Enrica Croda & Ekaterini Kyriazidou & Iannis Polycarpou, 2011. "Intertemporal Labor Force Participation of Married Women in Germany: A Panel Data Analysis," Working Papers 2011_17, Department of Economics, University of Venice "Ca' Foscari".
    15. Yaya Li & Yongli Li & Yulin Zhao & Fang Wang, 2014. "Which factor dominates the industry evolution? A synergy analysis based on China's ICT industry," Papers 1403.4305, arXiv.org.
    16. Travaglini, Guido, 2010. "Supervised Principal Components and Factor Instrumental Variables. An Application to Violent CrimeTrends in the US, 1982-2005," MPRA Paper 22077, University Library of Munich, Germany.

  45. Guido W. Imbens & Whitney Newey & Geert Ridder, 2005. "Mean-square-error Calculations for Average Treatment Effects," IEPR Working Papers 05.34, Institute of Economic Policy Research (IEPR).

    Cited by:

    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Nonparametric Tests for Treatment Effect Heterogeneity," NBER Technical Working Papers 0324, National Bureau of Economic Research, Inc.
    2. de Brauw, Alan & Gilligan, Daniel O. & Hoddinott, John & Roy, Shalini, 2014. "The Impact of Bolsa Família on Women’s Decision-Making Power," World Development, Elsevier, vol. 59(C), pages 487-504.
    3. Busso, Matias & Kline, Patrick, 2008. "Do Local Economic Development Programs Work? Evidence from the Federal Empowerment Zone Program," Working Papers 36, Yale University, Department of Economics.
    4. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Chunrong Ai & Lukang Huang & Zheng Zhang, 2018. "A Simple and Efficient Estimation of the Average Treatment Effect in the Presence of Unmeasured Confounders," Papers 1807.05678, arXiv.org.
    6. Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.
    7. Yanchun Jin, 2016. "Nonparametric tests for the effect of treatment on conditional variance," KIER Working Papers 948, Kyoto University, Institute of Economic Research.
    8. Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
    9. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in Estimation of Average Treatment Effects by Changing the Estimand," Working Papers 0608, University of Miami, Department of Economics.
    10. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers 61/13, Institute for Fiscal Studies.
    11. Martin Huber & Michael Lechner & Conny Wunsch, 2010. "How to control for many covariates? Reliable estimators based on the propensity score," University of St. Gallen Department of Economics working paper series 2010 2010-30, Department of Economics, University of St. Gallen.
    12. Vera Chiodi & Gabriel Montes‐Rojas, 2022. "Mentoring as a dose treatment: Frequency matters—Evidence from a French mentoring programme," LABOUR, CEIS, vol. 36(2), pages 145-166, June.
    13. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    14. Michael Lechner & Blaise Melly, 2010. "Partial Idendification of Wage Effects of Training Programs," Working Papers 2010-8, Brown University, Department of Economics.
    15. de Brauw, Alan & Gilligan, Daniel O. & Hoddinott, John & Roy, Shalini, 2015. "The Impact of Bolsa Família on Schooling," World Development, Elsevier, vol. 70(C), pages 303-316.
    16. Cattaneo, Matias D., 2010. "Efficient semiparametric estimation of multi-valued treatment effects under ignorability," Journal of Econometrics, Elsevier, vol. 155(2), pages 138-154, April.
    17. de Brauw, Alan & Gilligan, Daniel O. & Hoddinott, John F. & Roy, Shalini, 2014. "The impact of Bolsa Família on schooling: Girls’ advantage increases and older children gain:," IFPRI discussion papers 1319, International Food Policy Research Institute (IFPRI).
    18. Lechner, Michael & Melly, Blaise, 2007. "Earnings Effects of Training Programs," CEPR Discussion Papers 6400, C.E.P.R. Discussion Papers.
    19. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
    20. Garbero, A., 2016. "IFAD RESEARCH SERIES 7 - Measuring IFAD’s impact: background paper to the IFAD9 Impact Assessment Initiative," IFAD Research Series 280045, International Fund for Agricultural Development (IFAD).
    21. Millimet, Daniel L. & Tchernis, Rusty, 2009. "On the Specification of Propensity Scores, With Applications to the Analysis of Trade Policies," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 397-415.
    22. Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 1053-1079.
    23. Alex Karagrigoriou & George-Jason Siouris & Despoina Skilogianni, 2019. "Adjusted Evaluation Measures for Asymmetrically Important Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 4(1), pages 41-66, June.
    24. Kwun Chuen Gary Chan & Sheung Chi Phillip Yam & Zheng Zhang, 2016. "Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 673-700, June.

  46. Whitney Newey & Guido Imbens, 2004. "Identification and Estimation of Triangular Simultaneous Equations Models without Additivity," Econometric Society 2004 North American Summer Meetings 594, Econometric Society.

    Cited by:

    1. Romuald Meango, 2023. "Identification of Ex Ante Returns Using Elicited Choice Probabilities," Papers 2303.03009, arXiv.org.
    2. Victor Aguirregabiria, 2006. "Another Look at the Identification of Dynamic Discrete Decision Processes: With an Application to Retirement Behavior," 2006 Meeting Papers 169, Society for Economic Dynamics.
    3. Heckman, James J., 2010. "The Assumptions Underlying Evaluation Estimators," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(2), December.
    4. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile regression with censoring and endogeneity," CeMMAP working papers CWP20/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    6. Depalo, D.;, 2019. "Explaining the causal effect of adherence to medication on cholesterol through the marginal patient," Health, Econometrics and Data Group (HEDG) Working Papers 19/13, HEDG, c/o Department of Economics, University of York.
    7. Rahul Singh, 2021. "Debiased Kernel Methods," Papers 2102.11076, arXiv.org, revised Mar 2021.
    8. Gauthier Tshiswaka-Kashalala & Steven F. Koch, 2015. "The Demand for Reproductive Health Care," Working Papers 533, Economic Research Southern Africa.
    9. Michela Bia & Martin Huber & Luk'av{s} Laff'ers, 2020. "Double machine learning for sample selection models," Papers 2012.00745, arXiv.org, revised Jul 2021.
    10. Stefan Hoderlein & Yuya Sasaki, 2013. "Outcome Conditioned Treatment Effects," Boston College Working Papers in Economics 840, Boston College Department of Economics.
    11. Centorrino, Samuele & Pérez-Urdiales, María, 2023. "Maximum likelihood estimation of stochastic frontier models with endogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 82-105.
    12. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    13. Eric Gautier & Stefan Soderlein, 2011. "Estimating the Distribution of Treatment Effects," Working Papers 2011-25, Center for Research in Economics and Statistics.
    14. Hoderlein, Stefan & Winter, Joachim, 2010. "Structural measurement errors in nonseparable models," Munich Reprints in Economics 19445, University of Munich, Department of Economics.
    15. Yu-Chin Hsu & Ta-Cheng Huang & Haiqing Xu, 2018. "Testing for Unobserved Heterogeneous Treatment Effects with Observational Data," Papers 1803.07514, arXiv.org, revised Aug 2021.
    16. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
    17. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.
    18. Karim Chalak & Halbert White, 2011. "Viewpoint: An extended class of instrumental variables for the estimation of causal effects," Canadian Journal of Economics, Canadian Economics Association, vol. 44(1), pages 1-51, February.
    19. Lingjie Ma & Roger Koenker, 2004. "Quantile regression methods for recursive structural equation models," CeMMAP working papers CWP01/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Andrew Chesher & Adam M. Rosen, 2013. "What Do Instrumental Variable Models Deliver with Discrete Dependent Variables?," American Economic Review, American Economic Association, vol. 103(3), pages 557-562, May.
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    Cited by:

    1. Smith, Richard J., 2007. "Efficient information theoretic inference for conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 138(2), pages 430-460, June.
    2. Whitney K. Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers CWP03/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Parente, Paulo M.D.C. & Smith, Richard J., 2011. "Gel Methods For Nonsmooth Moment Indicators," Econometric Theory, Cambridge University Press, vol. 27(1), pages 74-113, February.
    5. Richard Smith, 2005. "Local GEL methods for conditional moment restrictions," CeMMAP working papers CWP15/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M., 2007. "Worst-case estimation for econometric models with unobservable components," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3330-3354, April.

  50. Donald, Stephen G. & Whitney Newey, 1999. "Choosing the Number of Instruments," Working papers 99-05, Massachusetts Institute of Technology (MIT), Department of Economics.

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    Cited by:

    1. Aktas, Nihat & de Bodt, Eric & Roll, Richard, 2013. "Learning from repetitive acquisitions: Evidence from the time between deals," Journal of Financial Economics, Elsevier, vol. 108(1), pages 99-117.
    2. Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
    3. Frumento, Paolo & Bottai, Matteo, 2017. "An estimating equation for censored and truncated quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 53-63.
    4. Chen, Songnian & Zhou, Xianbo, 2012. "Semiparametric estimation of a truncated regression model," Journal of Econometrics, Elsevier, vol. 167(2), pages 297-304.
    5. Jonsson, Robert, 2008. "When does Heckman’s two-step procedure for censored data work and when does it not?," Research Reports 2008:2, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    6. Myoung-jae Lee & Maria Karlsson, 2015. "Trimmed and winsorized semiparametric estimator for left-truncated and right-censored regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(4), pages 485-495, May.
    7. Karlsson, Maria & Laitila, Thomas, 2008. "A semiparametric regression estimator under left truncation and right censoring," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2567-2571, November.

  52. Whitney Newey, 1999. "Flexible Simulated Moment Estimation of Nonlinear Errors-in-Variables Models," Working papers 99-02, Massachusetts Institute of Technology (MIT), Department of Economics.

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    1. Rulon D. Pope & Jeffrey T. LaFrance & Richard E. Just, 2007. "Imperfect Price Deflation in Production Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(3), pages 738-754.
    2. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    3. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    4. D’Haultfœuille, Xavier & Février, Philippe, 2015. "Identification of mixture models using support variations," Journal of Econometrics, Elsevier, vol. 189(1), pages 70-82.
    5. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.
    6. De Agostini, Paola, 2014. "The effect of food prices and household income on the British diet," ISER Working Paper Series 2014-10, Institute for Social and Economic Research.
    7. Luo, Guowang & Wu, Mixia & Pang, Zhen, 2022. "Estimation of spatial autoregressive models with covariate measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    8. Qing Li, 2014. "Identifiability of mean-reverting measurement error with instrumental variable," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(2), pages 118-129, May.
    9. Yingyao Hu & Geert Ridder, 2005. "Estimation of Nonlinear Models with Mismeasured Regressors Using Marginal Information," IEPR Working Papers 05.39, Institute of Economic Policy Research (IEPR).
    10. De Nadai, Michele & Lewbel, Arthur, 2016. "Nonparametric errors in variables models with measurement errors on both sides of the equation," Journal of Econometrics, Elsevier, vol. 191(1), pages 19-32.
    11. Alan Beggs & Kathryn Graddy, 2005. "Testing for Reference Dependence: An Application to the Art Market," Economics Series Working Papers 228, University of Oxford, Department of Economics.
    12. Timothy Erickson & Toni M. Whited, 2006. "On the Accuracy of Different Measures of Q," Financial Management, Financial Management Association, vol. 35(3), Autumn.
    13. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.
    14. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(4), pages 1010-1043, August.
    15. Kneip, Alois & Simar, Leopold & Van Keilegom, Ingrid, 2015. "Frontier estimation in the presence of measurement error with unknown variance," LIDAM Reprints ISBA 2015004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. Mochen Yang & Edward McFowland III & Gordon Burtch & Gediminas Adomavicius, 2020. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," Papers 2012.10790, arXiv.org.
    17. Susanne M. Schennach, 2013. "Regressions with Berkson errors in covariates - A nonparametric approach," Papers 1308.2836, arXiv.org.
    18. Stoker, Thomas M. & Berndt, Ernst R. & Denny Ellerman, A. & Schennach, Susanne M., 2005. "Panel data analysis of U.S. coal productivity," Journal of Econometrics, Elsevier, vol. 127(2), pages 131-164, August.
    19. Jean‐Jacques Forneron, 2023. "A Sieve‐SMM Estimator for Dynamic Models," Econometrica, Econometric Society, vol. 91(3), pages 943-977, May.
    20. Karun Adusumilli & Taisuke Otsu, 2015. "Nonparametric instrumental regression with errors in variables," STICERD - Econometrics Paper Series /2015/585, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    21. Anish Agarwal & Rahul Singh, 2021. "Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy," Papers 2107.02780, arXiv.org, revised Feb 2024.
    22. Biørn, Erik, 2017. "Identification and Method of Moments Estimation in Polynomial Measurement Error Models," Memorandum 01/2017, Oslo University, Department of Economics.
    23. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
    24. Richard E. Just & Rulon D. Pope, 2012. "Cost Function Estimation with Proportional Errors in Variables," International Econometric Review (IER), Econometric Research Association, vol. 4(2), pages 59-81, September.
    25. Xi CHEN, 2012. "Estimation of the CES Production Function with Biased Technical Change: A Control Function Approach," Working Papers of BETA 2012-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    26. Dennis Epple & Brett Gordon & Holger Sieg, 2010. "A New Approach to Estimating the Production Function for Housing," American Economic Review, American Economic Association, vol. 100(3), pages 905-924, June.
    27. Susanne M. Schennach & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric identification of the classical errors-in-variables model without side information," Boston College Working Papers in Economics 674, Boston College Department of Economics.
    28. Xiaohong Chen & Yingyao Hu, 2006. "Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors," Cowles Foundation Discussion Papers 1590, Cowles Foundation for Research in Economics, Yale University.
    29. Hu, Yingyao & Shiu, Ji-Liang & Woutersen, Tiemen, 2016. "Identification in nonseparable models with measurement errors and endogeneity," Economics Letters, Elsevier, vol. 144(C), pages 33-36.
    30. ZINDE-WALSH, Victoria, 2007. "Errors-in-Variables Models : A Generalized Functions Approach," Cahiers de recherche 14-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    31. Ramazan Gencay & Nikola Gradojevic, 2009. "Errors-in-Variables Estimation with No Instruments," Working Paper series 30_09, Rimini Centre for Economic Analysis.
    32. Shiu, Ji-Liang, 2016. "Identification and estimation of endogenous selection models in the presence of misclassification errors," Economic Modelling, Elsevier, vol. 52(PB), pages 507-518.
    33. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
    34. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    35. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    36. Geert Ridder & Yingyao Hu, 2004. "Estimation of Nonlinear Models with Measurement Error Using Marginal Information," Econometric Society 2004 North American Summer Meetings 21, Econometric Society.
    37. Schennach, Susanne M., 2004. "Exponential specifications and measurement error," Economics Letters, Elsevier, vol. 85(1), pages 85-91, October.
    38. Xiaohong Chen & Han Hong & Denis Nekipelov, 2011. "Nonlinear Models of Measurement Errors," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 901-937, December.
    39. Edgerton, David & Jochumzen, Peter, 2003. "Estimation in Binary Choice Models with Measurement Errors," Working Papers 2003:4, Lund University, Department of Economics, revised 07 Jul 2003.
    40. Han Hong, 2010. "Comment for identification and estimation of nonlinear models using two samples with nonclassical measurement errors, by Carroll, Chen and Hu," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 405-408.

  53. Soren Blomquist & Whitney Newey, 1999. "Nonparametric Estimation with Nonlinear Budget Sets," Working papers 99-03, Massachusetts Institute of Technology (MIT), Department of Economics.

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    1. van Soest, Arthur & Das, Marcel & Gong, Xiaodong, 2000. "A Structural Labour Supply Model with Nonparametric Preferences," IZA Discussion Papers 211, Institute of Labor Economics (IZA).
    2. van Soest, Arthur & Das, Marcel & Gong, Xiaodong, 2002. "A structural labour supply model with flexible preferences," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 345-374, March.
    3. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2018. "A discrete/continuous choice model on a nonconvex budget set," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 89-113, February.
    4. Olivier Bargain & Andreas Peichl, 2016. "Own-wage labor supply elasticities: variation across time and estimation methods," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-31, December.
    5. Richard Blundell & Thomas MaCurdy, 1998. "Labour supply: a review of alternative approaches," IFS Working Papers W98/18, Institute for Fiscal Studies.
    6. Blomquist, Sören & Selin, Håkan, 2010. "Hourly wage rate and taxable labor income responsiveness to changes in marginal tax rates," Journal of Public Economics, Elsevier, vol. 94(11-12), pages 878-889, December.
    7. Panayiota Lyssiotou & Elena Savva, 2021. "Labor supply responses to income tax free and bracket expansions," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 49(7), pages 1225-1239, November.
    8. Bessho, Shun-ichiro & Hayashi, Masayoshi, 2011. "Labor supply response and preferences specification: Estimates for prime-age males in Japan," Journal of Asian Economics, Elsevier, vol. 22(5), pages 398-411, October.
    9. Thomas Aronsson & James R. Walker, 2010. "Labor Supply, Tax Base and Public Policy in Sweden," NBER Chapters, in: Reforming the Welfare State: Recovery and Beyond in Sweden, pages 127-158, National Bureau of Economic Research, Inc.
    10. Dalton, Christina M., 2014. "Estimating demand elasticities using nonlinear pricing," International Journal of Industrial Organization, Elsevier, vol. 37(C), pages 178-191.
    11. Olivier Bargain, 2004. "On modeling household labor supply with taxation," DELTA Working Papers 2004-14, DELTA (Ecole normale supérieure).
    12. Gan, Li & Ju, Gaosheng & Zhu, Xi, 2015. "Nonparametric estimation of structural labor supply and exact welfare change under nonconvex piecewise-linear budget sets," Journal of Econometrics, Elsevier, vol. 188(2), pages 526-544.
    13. Panos Pashardes & Alexandros Polycarpou, 2015. "A backward-bending and forward-falling semi-log model of labour supply," University of Cyprus Working Papers in Economics 03-2015, University of Cyprus Department of Economics.
    14. Olivier Bargain & Andreas Peichl, 2013. "Steady-State Labor Supply Elasticities: An International Comparison," Working Papers halshs-00805744, HAL.
    15. Magali Beffy & Richard Blundell & Antoine Bozio & Guy Laroque & Maxime Tô, 2019. "Labour supply and taxation with restricted choices," PSE-Ecole d'économie de Paris (Postprint) halshs-01883898, HAL.
    16. Leora Friedberg, 1999. "The Labor Supply Effects of the Social Security Earnings Test," NBER Working Papers 7200, National Bureau of Economic Research, Inc.
    17. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    18. Koji Miyawaki & Yasuhiro Omori, 2007. "Duality-Based Analysis of Residential Gas Demand under Decreasing Block Rate Pricing," CIRJE F-Series CIRJE-F-506, CIRJE, Faculty of Economics, University of Tokyo.
    19. Liang, Che-Yuan, 2018. "Taxes and Household Labor Supply: Estimating Distributional Effects of Nonlinear Prices on Multidimensional Choice," Working Paper Series 2018:2, Uppsala University, Department of Economics.
    20. Sören Blomquist & Laurent Simula, 2019. "Marginal deadweight loss when the income tax is nonlinear," Post-Print halshs-01644460, HAL.
    21. Anil Kumar & Che-Yuan Liang, 2016. "Estimating Taxable Income Responses with Elasticity Heterogeneity," Working Papers 1611, Federal Reserve Bank of Dallas.
    22. Engelhardt, Gary V. & Kumar, Anil, 2007. "Employer matching and 401(k) saving: Evidence from the health and retirement study," Journal of Public Economics, Elsevier, vol. 91(10), pages 1920-1943, November.
    23. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    24. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.
    25. Anil Kumar & Che-Yuan Liang, 2015. "Declining female labor supply elasticities in the U.S. and implications for tax policy: evidence from panel data," Working Papers 1501, Federal Reserve Bank of Dallas.
    26. John K. Dagsvik & Steinar Strøm, 2004. "Sectoral Labor Supply, Choice Restrictions and Functional Form," Discussion Papers 388, Statistics Norway, Research Department.
    27. Abby Alpert & David Powell, 2020. "Estimating Intensive And Extensive Tax Responsiveness," Economic Inquiry, Western Economic Association International, vol. 58(4), pages 1855-1873, October.
    28. Amanda E. Kowalski, 2012. "Estimating the Tradeoff Between Risk Protection and Moral Hazard with a Nonlinear Budget Set Model of Health Insurance," NBER Working Papers 18108, National Bureau of Economic Research, Inc.
    29. Reiss, Peter C. & White, Matthew W., 2002. "Household Electricity Demand, Revisited," Research Papers 1830, Stanford University, Graduate School of Business.
    30. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2012. "Comparing Labor Supply Elasticities in Europe and the US: New Results," Working Papers halshs-00805736, HAL.
    31. Daniel Wilhelm, 2019. "Testing for the presence of measurement error," CeMMAP working papers CWP48/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    32. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    33. Liang, Che-Yuan, 2009. "Nonparametric Structural Estimation of Labor Supply in the Presence of Censoring," Working Paper Series 2009:8, Uppsala University, Department of Economics.
    34. Aaberge, Rolf & Colombino, Ugo, 2018. "Structural Labour Supply Models and Microsimulation," IZA Discussion Papers 11562, Institute of Labor Economics (IZA).
    35. Michiel Evers & Ruud Mooij & Daniel Vuuren, 2008. "The Wage Elasticity of Labour Supply: A Synthesis of Empirical Estimates," De Economist, Springer, vol. 156(1), pages 25-43, March.
    36. Bargain, Olivier & Peichl, Andreas, 2013. "Steady-State Labor Supply Elasticities: A Survey," IZA Discussion Papers 7698, Institute of Labor Economics (IZA).
    37. Das, M., 2003. "Identification and sequential estimation of panel data models with insufficient exclusion restrictions," Journal of Econometrics, Elsevier, vol. 114(2), pages 297-328, June.
    38. Liwen, Chen & Zeng, Xiangquan & Yumei, Yang, 2011. "Rural Labor Absorption Efficiency in Urban Areas under Different Urbanization Patterns and Industrial Structures: The Case of China," IZA Discussion Papers 6189, Institute of Labor Economics (IZA).
    39. Bastani, Spencer & Selin, Håkan, 2011. "Bunching and Non-Bunching at Kink Points of the Swedish Tax schedule," Working Paper Series, Center for Fiscal Studies 2011:12, Uppsala University, Department of Economics.
    40. David Powell & Dana Goldman, 2016. "Disentangling Moral Hazard and Adverse Selection in Private Health Insurance," NBER Working Papers 21858, National Bureau of Economic Research, Inc.
    41. Anil Kumar, 2012. "Nonparametric estimation of the impact of taxes on female labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 415-439, April.
    42. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    43. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2010. "Discrete/Continuous Choice Model of the Residential Gas Demand on the Nonconvex Budget Set," CIRJE F-Series CIRJE-F-770, CIRJE, Faculty of Economics, University of Tokyo.
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    Cited by:

    1. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999, Cowles Foundation for Research in Economics, Yale University.
    2. Xiaohong Chen & Jinyong Hahn & Zhipeng Liao, 2012. "Asymptotic Efficiency of Semiparametric Two-step GMM," Cowles Foundation Discussion Papers 1880, Cowles Foundation for Research in Economics, Yale University.
    3. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    4. Xiaohong Chen & Demian Pouzo & James L. Powell, 2019. "Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions," Papers 1902.10100, arXiv.org.

  55. Whitney Newey, 1999. "Two Step Series Estimation of Sample Selection Models," Working papers 99-04, Massachusetts Institute of Technology (MIT), Department of Economics.

    Cited by:

    1. Giulia BETTIN & Riccardo LUCCHETTI & Alberto ZAZZARO, 2011. "Endogeneity and sample selection in a model for remittances," Working Papers 361, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    2. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile regression with censoring and endogeneity," CeMMAP working papers CWP20/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Huber, Martin & Melly, Blaise, 2011. "Quantile Regression in the Presence of Sample Selection," Economics Working Paper Series 1109, University of St. Gallen, School of Economics and Political Science.
    4. Matsushita, Yukitoshi & Otsu, Taisuke, 2020. "Likelihood inference on semiparametric models with generated regressors," LSE Research Online Documents on Economics 102696, London School of Economics and Political Science, LSE Library.
    5. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999, Cowles Foundation for Research in Economics, Yale University.
    6. Black, Dan A. & Joo, Joonhwi & LaLonde, Robert & Smith, Jeffrey A. & Taylor, Evan J., 2022. "Simple Tests for Selection: Learning More from Instrumental Variables," Labour Economics, Elsevier, vol. 79(C).
    7. Jörg Schwiebert, 2015. "Estimation and interpretation of a Heckman selection model with endogenous covariates," Empirical Economics, Springer, vol. 49(2), pages 675-703, September.
    8. Nir Billfeld & Moshe Kim, 2019. "Semiparametric Wavelet-based JPEG IV Estimator for endogenously truncated data," Papers 1908.02166, arXiv.org.
    9. Christian Dustmann & Joseph-Simon Görlach, 2014. "Selective Outmigration and the Estimation of Immigrants' Earnings Profiles," CESifo Working Paper Series 4617, CESifo.
    10. Aysit Tansel & Halil Ibrahim Keskin & Zeynel Abidin Ozdemir, 2018. "Public Versus Private Sector Wage Gap in Egypt: Evidence from Quantile Regression on Panel Data," Working Papers 1265, Economic Research Forum, revised 10 Dec 2018.
    11. Martin Huber & Giovanni Mellace, 2015. "Sharp Bounds on Causal Effects under Sample Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 129-151, February.
    12. Anastasia Semykina & Jeffrey M. Woodridge, 2010. "Estimating Panel Data Models in the Presence of Endogeneity and Selection," Working Papers wp2010_10_01, Department of Economics, Florida State University.
    13. Koen Jochmans, 2015. "Multiplicative-error models with sample selection," SciencePo Working papers Main hal-03392990, HAL.
    14. Jacopo Mazza & Hans van Ophem, 2020. "Educational Choice, Initial Wage and Wage Growth," Tinbergen Institute Discussion Papers 20-030/III, Tinbergen Institute.
    15. Manuel A. Domínguez & Ignacio N. Lobato, 2020. "Specification testing with estimated variables," Econometric Reviews, Taylor & Francis Journals, vol. 39(5), pages 476-494, May.
    16. Ibáñez, Ana María & Muñoz, Juan Carlos & Verwimp, Philip, 2013. "Abandoning Coffee under the Threat of Violence and the Presence of Illicit Crops. Evidence from Colombia," Documentos CEDE Series 161356, Universidad de Los Andes, Economics Department.
    17. Schwiebert, Jörg, 2012. "Semiparametric Estimation of a Sample Selection Model in the Presence of Endogeneity," Hannover Economic Papers (HEP) dp-504, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    18. Cristina Cattaneo, 2012. "Migrants’ international transfers and educational expenditure," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 20(1), pages 163-193, January.
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    20. Kossova, Elena & Potanin, Bogdan, 2022. "Estimation of Gaussian multinomial endogenous switching model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 67, pages 121-143.
    21. Puja Vasudeva Dutta, 2006. "Returns to Education: New Evidence for India, 1983-1999," Education Economics, Taylor & Francis Journals, vol. 14(4), pages 431-451.
    22. Xiaohong Chen & Jinyong Hahn & Zhipeng Liao, 2012. "Asymptotic Efficiency of Semiparametric Two-step GMM," Cowles Foundation Discussion Papers 1880, Cowles Foundation for Research in Economics, Yale University.
    23. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    24. Martin Huber, 2014. "Treatment Evaluation in the Presence of Sample Selection," Econometric Reviews, Taylor & Francis Journals, vol. 33(8), pages 869-905, November.
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    27. D’Haultfœuille, Xavier & Maurel, Arnaud, 2013. "Inference on an extended Roy model, with an application to schooling decisions in France," Journal of Econometrics, Elsevier, vol. 174(2), pages 95-106.
    28. Alfonso Miranda & Yu Zhu, 2013. "The Causal Effect of Deficiency at English on Female Immigrants’ Labour Market Outcomes in the UK," Studies in Economics 1301, School of Economics, University of Kent.
    29. Samuel Bazzi & Masyhur Hilmy & Benjamin Marx, 2020. "Religion, Education, and Development," SciencePo Working papers Main hal-03873758, HAL.
    30. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    31. Pham, T. Hung & Reilly, Barry, 2007. "Ethnic Wage Inequality in Vietnam: Empirical Evidence from 2002," MPRA Paper 6477, University Library of Munich, Germany.
    32. Giuseppe De Luca & Franco Peracchi, 2007. "A sample selection model for unit and item nonresponse in cross-sectional surveys," CEIS Research Paper 95, Tor Vergata University, CEIS.
    33. Giulia Bettin & Riccardo Lucchetti & Claudia Pigini, 2016. "State dependence and unobserved heterogeneity in a double hurdle model for remittances: evidence from immigrants to Germany," Mo.Fi.R. Working Papers 127, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    34. Martin Huber & Giovanni Mellace, 2014. "Testing exclusion restrictions and additive separability in sample selection models," Empirical Economics, Springer, vol. 47(1), pages 75-92, August.
    35. Magnus Söderberg & Miguel Santolino, 2012. "Modelling appellate courts' responses in motor injury disputes," Post-Print hal-00869780, HAL.
    36. Schwiebert, Jörg, 2012. "Semiparametric Estimation of a Binary Choice Model with Sample Selection," Hannover Economic Papers (HEP) dp-505, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    37. D’Haultfœuille, Xavier & Maurel, Arnaud & Zhang, Yichong, 2018. "Extremal quantile regressions for selection models and the black–white wage gap," Journal of Econometrics, Elsevier, vol. 203(1), pages 129-142.
    38. Karol Wyszynski & Giampiero Marra, 2018. "Sample selection models for count data in R," Computational Statistics, Springer, vol. 33(3), pages 1385-1412, September.
    39. Koumenta, Maria & Pagliero, Mario & Rostam-Afschar, Davud, 2020. "Occupational licensing and the gender wage gap," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    40. Hoffmann, Vivian & Rao, Vijayendra & Surendra, Vaishnavi & Datta, Upamanyu, 2021. "Relief from usury: Impact of a self-help group lending program in rural India," Journal of Development Economics, Elsevier, vol. 148(C).
    41. Xiaohong Chen & Demian Pouzo & James L. Powell, 2019. "Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions," Papers 1902.10100, arXiv.org.
    42. Zhewen Pan, 2023. "On semiparametric estimation of the intercept of the sample selection model: a kernel approach," Papers 2302.05089, arXiv.org.
    43. D'Haultfoeuille, Xavier & Maurel, Arnaud, 2009. "Inference on a Generalized Roy Model, with an Application to Schooling Decisions in France," IZA Discussion Papers 4606, Institute of Labor Economics (IZA).
    44. Abby Alpert & David Powell, 2020. "Estimating Intensive And Extensive Tax Responsiveness," Economic Inquiry, Western Economic Association International, vol. 58(4), pages 1855-1873, October.
    45. Wiemann, Paul F.V. & Klein, Nadja & Kneib, Thomas, 2022. "Correcting for sample selection bias in Bayesian distributional regression models," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    46. Giulia Bettin & Riccardo Lucchetti, 2012. "Intertemporal Remittance Behaviour by Immigrants in Germany," SOEPpapers on Multidisciplinary Panel Data Research 505, DIW Berlin, The German Socio-Economic Panel (SOEP).
    47. Alfonso Miranda & Sophia Rabe-Hesketh & John W. McDonald, 2012. "Reducing bias due to missing values of the response variable by joint modeling with an auxiliary variable," DoQSS Working Papers 12-05, Quantitative Social Science - UCL Social Research Institute, University College London.
    48. Abby Alpert & David Powell, 2014. "Estimating Intensive and Extensive Tax Responsiveness Do Older Workers Respond to Income Taxes?," Working Papers WR-987-1, RAND Corporation.
    49. Joonhwi Joo & Ali Hortacsu, 2016. "Semiparametric estimation of CES demand system with observed and unobserved product characteristics," 2016 Meeting Papers 36, Society for Economic Dynamics.
    50. ASANO Hirokatsu, 2008. "Econometric Analysis of Irreversible Investment with Financial Constraints: Comparison of Parametric and Semiparametric Estimations," Discussion papers 08032, Research Institute of Economy, Trade and Industry (RIETI).
    51. Mark Borgschulte & Paco Martorell, 2018. "Paying to Avoid Recession: Using Reenlistment to Estimate the Cost of Unemployment," American Economic Journal: Applied Economics, American Economic Association, vol. 10(3), pages 101-127, July.
    52. Hussinger, Katrin, 2003. "R&D and Subsidies at the Firm Level: An Application of Parametric and Semi-Parametric Two-Step Selection Models," ZEW Discussion Papers 03-63, ZEW - Leibniz Centre for European Economic Research.
    53. Asma Hyder & Barry Reilly, 2005. "The Public and Private Sector Pay Gap in Pakistan: A Quantile Regression Analysis," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 44(3), pages 271-306.
    54. Adelchi Azzalini & Hyoung-Moon Kim & Hea-Jung Kim, 2019. "Sample selection models for discrete and other non-Gaussian response variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(1), pages 27-56, March.
    55. Jinyong Hahn & Geert Ridder, 2010. "The Asymptotic Variance of Semi-parametric Estimators with Generated Regressors," Textos para discussão 575, Department of Economics PUC-Rio (Brazil).
    56. Schwiebert, Jörg, 2012. "Revisiting the Composition of the Female Workforce - A Heckman Selection Model with Endogeneity," Hannover Economic Papers (HEP) dp-502, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    57. S. I. Dolgikh & B. S. Potanin, 2023. "The Impact of Public Administration on the Efficiency of Russian Firms," Studies on Russian Economic Development, Springer, vol. 34(1), pages 59-67, February.
    58. David Powell & Seth A. Seabury, 2014. "Medical Care Spending and Labor Market Outcomes Evidence from Workers' Compensation Reforms," Working Papers WR-1028-1, RAND Corporation.
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    61. Juan Carlos Escanciano & Lin Zhu, 2015. "A Simple Data-Driven Estimator for the Semiparametric Sample Selection Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 734-762, December.
    62. Burn, Ian & Kettler, Kyle, 2019. "The more you know, the better you’re paid? Evidence from pay secrecy bans for managers," Labour Economics, Elsevier, vol. 59(C), pages 92-109.
    63. Wojtyś, Małgorzata & Marra, Giampiero & Radice, Rosalba, 2018. "Copula based generalized additive models for location, scale and shape with non-random sample selection," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 1-14.
    64. Shakeeb Khan & Denis Nekipelov, 2019. "On Uniform Inference in Nonlinear Models with Endogeneity," Boston College Working Papers in Economics 986, Boston College Department of Economics.
    65. Escribano, Álvaro & Wang, Dandan, 2021. "Mixed random forest, cointegration, and forecasting gasoline prices," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1442-1462.
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    68. David Benatia & Raphael Godefroy & Joshua Lewis, 2020. "Estimating COVID-19 Prevalence in the United States: A Sample Selection Model Approach," Cahiers de recherche 08-2020, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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    71. Xavier D’Haultfoeuille & Arnaud Maurel & Xiaoyun Qiu & Yichong Zhang, 2020. "Estimating selection models without an instrument with Stata," Stata Journal, StataCorp LP, vol. 20(2), pages 297-308, June.
    72. Abby Alpert & David Powell, 2012. "Tax Elasticity of Labor Earnings for Older Individuals," Working Papers wp272, University of Michigan, Michigan Retirement Research Center.
    73. Basani, Marcello & Isham, Jonathan & Reilly, Barry, 2008. "The Determinants of Water Connection and Water Consumption: Empirical Evidence from a Cambodian Household Survey," World Development, Elsevier, vol. 36(5), pages 953-968, May.
    74. Dogan, Osman & Taspinar, Suleyman, 2016. "Bayesian Inference in Spatial Sample Selection Models," MPRA Paper 82829, University Library of Munich, Germany.
    75. Joo, Joonhwi & LaLonde, Robert J., 2014. "Testing for Selection Bias," IZA Discussion Papers 8455, Institute of Labor Economics (IZA).
    76. Domenico Depalo & Santiago Pereda-Fernández, 2020. "Consistent estimates of the public/private wage gap," Empirical Economics, Springer, vol. 58(6), pages 2937-2947, June.
    77. George-Levi Gayle & Christelle Viauroux, "undated". "Root-N Consistent Semiparametric Estimators of a Dynamic Panel Sample Selection Model," GSIA Working Papers 2004-E62, Carnegie Mellon University, Tepper School of Business.
    78. Huber, Martin & Mellace, Giovanni, 2011. "Testing instrument validity in sample selection models," Economics Working Paper Series 1145, University of St. Gallen, School of Economics and Political Science.
    79. Jacopo Mazza, 2012. "Does Risk Matter? A Semi-parametric Model for Educational Choices in the Presence of Uncertainty," Economics Discussion Paper Series 1225, Economics, The University of Manchester.
    80. Lee, Ji Hyung & Park, Byoung G., 2023. "Nonparametric identification and estimation of the extended Roy model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1087-1113.
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    Cited by:

    1. Rahul Singh, 2021. "Debiased Kernel Methods," Papers 2102.11076, arXiv.org, revised Mar 2021.
    2. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
    3. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    4. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Dec 2017.
    5. Kotlyarova, Yulia & Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2021. "Rates of expansions for functional estimators," LSE Research Online Documents on Economics 113436, London School of Economics and Political Science, LSE Library.
    6. Guy Tchuente, 2019. "Weak Identification and Estimation of Social Interaction Models," Papers 1902.06143, arXiv.org.
    7. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Apr 2024.
    8. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
    9. Neng-Chieh Chang, 2018. "Semiparametric Difference-in-Differences with Potentially Many Control Variables," Papers 1812.10846, arXiv.org, revised Jan 2019.
    10. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
    11. Qizhao Chen & Vasilis Syrgkanis & Morgane Austern, 2022. "Debiased Machine Learning without Sample-Splitting for Stable Estimators," Papers 2206.01825, arXiv.org, revised Nov 2022.
    12. Agboola, Oluwagbenga David & Yu, Han, 2023. "Neighborhood-based cross fitting approach to treatment effects with high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 186(C).
    13. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. David Bruns-Smith & Oliver Dukes & Avi Feller & Elizabeth L. Ogburn, 2023. "Augmented balancing weights as linear regression," Papers 2304.14545, arXiv.org, revised Aug 2023.
    15. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.

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    Cited by:

    1. van Soest, Arthur & Das, Marcel & Gong, Xiaodong, 2000. "A Structural Labour Supply Model with Nonparametric Preferences," IZA Discussion Papers 211, Institute of Labor Economics (IZA).
    2. van Soest, Arthur & Das, Marcel & Gong, Xiaodong, 2002. "A structural labour supply model with flexible preferences," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 345-374, March.
    3. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2018. "A discrete/continuous choice model on a nonconvex budget set," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 89-113, February.
    4. Olivier Bargain & Andreas Peichl, 2016. "Own-wage labor supply elasticities: variation across time and estimation methods," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-31, December.
    5. Richard Blundell & Thomas MaCurdy, 1998. "Labour supply: a review of alternative approaches," IFS Working Papers W98/18, Institute for Fiscal Studies.
    6. Blomquist, Sören & Selin, Håkan, 2010. "Hourly wage rate and taxable labor income responsiveness to changes in marginal tax rates," Journal of Public Economics, Elsevier, vol. 94(11-12), pages 878-889, December.
    7. Panayiota Lyssiotou & Elena Savva, 2021. "Labor supply responses to income tax free and bracket expansions," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 49(7), pages 1225-1239, November.
    8. Bessho, Shun-ichiro & Hayashi, Masayoshi, 2011. "Labor supply response and preferences specification: Estimates for prime-age males in Japan," Journal of Asian Economics, Elsevier, vol. 22(5), pages 398-411, October.
    9. Thomas Aronsson & James R. Walker, 2010. "Labor Supply, Tax Base and Public Policy in Sweden," NBER Chapters, in: Reforming the Welfare State: Recovery and Beyond in Sweden, pages 127-158, National Bureau of Economic Research, Inc.
    10. Dalton, Christina M., 2014. "Estimating demand elasticities using nonlinear pricing," International Journal of Industrial Organization, Elsevier, vol. 37(C), pages 178-191.
    11. Olivier Bargain, 2004. "On modeling household labor supply with taxation," DELTA Working Papers 2004-14, DELTA (Ecole normale supérieure).
    12. Gan, Li & Ju, Gaosheng & Zhu, Xi, 2015. "Nonparametric estimation of structural labor supply and exact welfare change under nonconvex piecewise-linear budget sets," Journal of Econometrics, Elsevier, vol. 188(2), pages 526-544.
    13. Panos Pashardes & Alexandros Polycarpou, 2015. "A backward-bending and forward-falling semi-log model of labour supply," University of Cyprus Working Papers in Economics 03-2015, University of Cyprus Department of Economics.
    14. Olivier Bargain & Andreas Peichl, 2013. "Steady-State Labor Supply Elasticities: An International Comparison," Working Papers halshs-00805744, HAL.
    15. Magali Beffy & Richard Blundell & Antoine Bozio & Guy Laroque & Maxime Tô, 2019. "Labour supply and taxation with restricted choices," PSE-Ecole d'économie de Paris (Postprint) halshs-01883898, HAL.
    16. Leora Friedberg, 1999. "The Labor Supply Effects of the Social Security Earnings Test," NBER Working Papers 7200, National Bureau of Economic Research, Inc.
    17. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    18. Koji Miyawaki & Yasuhiro Omori, 2007. "Duality-Based Analysis of Residential Gas Demand under Decreasing Block Rate Pricing," CIRJE F-Series CIRJE-F-506, CIRJE, Faculty of Economics, University of Tokyo.
    19. Liang, Che-Yuan, 2018. "Taxes and Household Labor Supply: Estimating Distributional Effects of Nonlinear Prices on Multidimensional Choice," Working Paper Series 2018:2, Uppsala University, Department of Economics.
    20. Sören Blomquist & Laurent Simula, 2019. "Marginal deadweight loss when the income tax is nonlinear," Post-Print halshs-01644460, HAL.
    21. Anil Kumar & Che-Yuan Liang, 2016. "Estimating Taxable Income Responses with Elasticity Heterogeneity," Working Papers 1611, Federal Reserve Bank of Dallas.
    22. Engelhardt, Gary V. & Kumar, Anil, 2007. "Employer matching and 401(k) saving: Evidence from the health and retirement study," Journal of Public Economics, Elsevier, vol. 91(10), pages 1920-1943, November.
    23. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    24. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.
    25. Anil Kumar & Che-Yuan Liang, 2015. "Declining female labor supply elasticities in the U.S. and implications for tax policy: evidence from panel data," Working Papers 1501, Federal Reserve Bank of Dallas.
    26. John K. Dagsvik & Steinar Strøm, 2004. "Sectoral Labor Supply, Choice Restrictions and Functional Form," Discussion Papers 388, Statistics Norway, Research Department.
    27. Abby Alpert & David Powell, 2020. "Estimating Intensive And Extensive Tax Responsiveness," Economic Inquiry, Western Economic Association International, vol. 58(4), pages 1855-1873, October.
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    29. Reiss, Peter C. & White, Matthew W., 2002. "Household Electricity Demand, Revisited," Research Papers 1830, Stanford University, Graduate School of Business.
    30. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2012. "Comparing Labor Supply Elasticities in Europe and the US: New Results," Working Papers halshs-00805736, HAL.
    31. Daniel Wilhelm, 2019. "Testing for the presence of measurement error," CeMMAP working papers CWP48/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    32. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    33. Liang, Che-Yuan, 2009. "Nonparametric Structural Estimation of Labor Supply in the Presence of Censoring," Working Paper Series 2009:8, Uppsala University, Department of Economics.
    34. Aaberge, Rolf & Colombino, Ugo, 2018. "Structural Labour Supply Models and Microsimulation," IZA Discussion Papers 11562, Institute of Labor Economics (IZA).
    35. Michiel Evers & Ruud Mooij & Daniel Vuuren, 2008. "The Wage Elasticity of Labour Supply: A Synthesis of Empirical Estimates," De Economist, Springer, vol. 156(1), pages 25-43, March.
    36. Bargain, Olivier & Peichl, Andreas, 2013. "Steady-State Labor Supply Elasticities: A Survey," IZA Discussion Papers 7698, Institute of Labor Economics (IZA).
    37. Das, M., 2003. "Identification and sequential estimation of panel data models with insufficient exclusion restrictions," Journal of Econometrics, Elsevier, vol. 114(2), pages 297-328, June.
    38. Liwen, Chen & Zeng, Xiangquan & Yumei, Yang, 2011. "Rural Labor Absorption Efficiency in Urban Areas under Different Urbanization Patterns and Industrial Structures: The Case of China," IZA Discussion Papers 6189, Institute of Labor Economics (IZA).
    39. Bastani, Spencer & Selin, Håkan, 2011. "Bunching and Non-Bunching at Kink Points of the Swedish Tax schedule," Working Paper Series, Center for Fiscal Studies 2011:12, Uppsala University, Department of Economics.
    40. David Powell & Dana Goldman, 2016. "Disentangling Moral Hazard and Adverse Selection in Private Health Insurance," NBER Working Papers 21858, National Bureau of Economic Research, Inc.
    41. Anil Kumar, 2012. "Nonparametric estimation of the impact of taxes on female labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 415-439, April.
    42. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    43. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2010. "Discrete/Continuous Choice Model of the Residential Gas Demand on the Nonconvex Budget Set," CIRJE F-Series CIRJE-F-770, CIRJE, Faculty of Economics, University of Tokyo.
    44. Francoise Forges & Enrico Minelli, 2006. "Afriat's Theorem for General Budget Sets," Working Papers ubs0609, University of Brescia, Department of Economics.
    45. Michiel Evers & Ruud A. De Mooij & Daniel J. Van Vuuren, 2005. "What Explains the Variation in Estimates of Labour Supply Elasticities?," CESifo Working Paper Series 1633, CESifo.
    46. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2014. "Comparing Labor Supply Elasticities in Europe and the United States: New Results," Post-Print hal-01463097, HAL.
    47. Charles F. Manski, 2014. "Identification of income–leisure preferences and evaluation of income tax policy," Quantitative Economics, Econometric Society, vol. 5, pages 145-174, March.
    48. Sören Blomquist, 2023. "Evaluating the Discrete Choice and BN Methods to Estimate Labor Supply Functions," CESifo Working Paper Series 10827, CESifo.
    49. Christophe Muller, 2003. "Female Activity Choice In A Dual Context: An Integrated Model For Formal And Informal Sectors In Cameroon," Working Papers. Serie AD 2003-39, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    50. Kumar, Anil & Liang, Che-Yuan, 2015. "The Taxable Income Elasticity: A Structural Differencing Approach," Working Paper Series, Center for Fiscal Studies 2015:1, Uppsala University, Department of Economics.
    51. Rolf Aaberge & Ugo Colombino, 2014. "Labour Supply Models," Contributions to Economic Analysis, in: Handbook of Microsimulation Modelling, volume 127, pages 167-221, Emerald Group Publishing Limited.
    52. Gary V. Engelhardt & Anil Kumar, 2008. "The elasticity of intertemporal substitution: new evidence from 401(k) participation," Working Papers 0812, Federal Reserve Bank of Dallas.
    53. Charles F. Manski, 2012. "Identification of Preferences and Evaluation of Income Tax Policy," NBER Working Papers 17755, National Bureau of Economic Research, Inc.
    54. Abaluck, Jason & Gruber, Jonathan & Swanson, Ashley, 2018. "Prescription drug use under Medicare Part D: A linear model of nonlinear budget sets," Journal of Public Economics, Elsevier, vol. 164(C), pages 106-138.
    55. Pablo Vidueira & José M. Díaz-Puente & María Rivera, 2014. "Socioeconomic Impact Assessment in Ex Ante Evaluations," Evaluation Review, , vol. 38(4), pages 309-335, August.
    56. Liang, Che-Yuan, 2014. "Distribution-Free Structural Estimation with Nonlinear Budget Sets," Working Paper Series, Center for Fiscal Studies 2014:4, Uppsala University, Department of Economics.
    57. Peter C. Reiss & Matthew W. White, 2001. "Household Electricity Demand, Revisited," NBER Working Papers 8687, National Bureau of Economic Research, Inc.
    58. White, Matthew W. & Reiss, Peter C., 2001. "Household Electricity Demand, Revisited," Research Papers 1715, Stanford University, Graduate School of Business.
    59. Kumar, Anil, 2008. "Labor supply, deadweight loss and tax reform act of 1986: A nonparametric evaluation using panel data," Journal of Public Economics, Elsevier, vol. 92(1-2), pages 236-253, February.

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    Cited by:

    1. Fang, Hongsheng & Bao, Yuxin & Zhang, Jun, 2017. "Asymmetric reform bonus: The impact of VAT pilot expansion on China's corporate total tax burden," China Economic Review, Elsevier, vol. 46(S), pages 17-34.
    2. Carneiro, Fernando Moraes & Turnovsky, Stephen J. & Tourinho, Octavio Augusto Fontes, 2022. "Economic growth and inequality tradeoffs under progressive taxation," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    3. Blomquist, Sören & Selin, Håkan, 2010. "Hourly wage rate and taxable labor income responsiveness to changes in marginal tax rates," Journal of Public Economics, Elsevier, vol. 94(11-12), pages 878-889, December.
    4. Bessho, Shun-ichiro & Hayashi, Masayoshi, 2011. "Labor supply response and preferences specification: Estimates for prime-age males in Japan," Journal of Asian Economics, Elsevier, vol. 22(5), pages 398-411, October.
    5. Thomas Aronsson & James R. Walker, 2010. "Labor Supply, Tax Base and Public Policy in Sweden," NBER Chapters, in: Reforming the Welfare State: Recovery and Beyond in Sweden, pages 127-158, National Bureau of Economic Research, Inc.
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    7. Michael Keane, 2010. "Labor Supply and Taxes: A Survey," Working Paper Series 160, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
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    1. Bryan S. Graham & Fengshi Niu & James L. Powell, 2019. "Kernel density estimation for undirected dyadic data," CeMMAP working papers CWP39/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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    4. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
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    7. Gayle, Wayne-Roy, 2013. "Identification and N-consistent estimation of a nonlinear panel data model with correlated unobserved effects," Journal of Econometrics, Elsevier, vol. 175(2), pages 71-83.
    8. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Cherchye, Laurens & Demuynck, Thomas & De Rock, Bram, 2013. "The empirical content of Cournot competition," Journal of Economic Theory, Elsevier, vol. 148(4), pages 1552-1581.
    10. Cattaneo, Matias D & Crump, Richard K & Jansson, Michael, 2014. "Small Bandwidth Asymptotics For Density-Weighted Average Derivatives," Department of Economics, Working Paper Series qt3jd237cg, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
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    6. Richard Blundell & Thomas MaCurdy, 1998. "Labour supply: a review of alternative approaches," IFS Working Papers W98/18, Institute for Fiscal Studies.
    7. Fábio Veras Soares, 2015. "Do Informal Workers Queue for Formal Jobs in Brazil?," Discussion Papers 0130, Instituto de Pesquisa Econômica Aplicada - IPEA.
    8. Huffman, Wallace E. & El-Osta, Hisham, 1997. "Off-Farm Work Participation, Off-Farm Labor Supply and On-Farm Labor Demand of U.S. Farm Operators," ISU General Staff Papers 199712010800001290, Iowa State University, Department of Economics.
    9. Soonae Park & Byung-Yeon Kim & Wonchang Jang & Kyung-Min Nam, 2014. "Imperfect information and labor market bias against small and medium-sized enterprises: a Korean case," Small Business Economics, Springer, vol. 43(3), pages 725-741, October.
    10. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
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    12. Morduch, Jonathan J. & Stern, Hal S., 1997. "Using mixture models to detect sex bias in health outcomes in Bangladesh," Journal of Econometrics, Elsevier, vol. 77(1), pages 259-276, March.
    13. Kaitlin Anderson & Gema Zamarro & Jennifer Steele & Trey Miller, 2021. "Comparing Performance of Methods to Deal With Differential Attrition in Randomized Experimental Evaluations," Evaluation Review, , vol. 45(1-2), pages 70-104, February.
    14. Ibáñez, Ana María & Muñoz, Juan Carlos & Verwimp, Philip, 2013. "Abandoning Coffee under the Threat of Violence and the Presence of Illicit Crops. Evidence from Colombia," Documentos CEDE Series 161356, Universidad de Los Andes, Economics Department.
    15. Huffman, Sonya Kostova, 1999. "Changes of household consumption behavior during the transition from centrally-planned to market-oriented economy," ISU General Staff Papers 1999010108000013568, Iowa State University, Department of Economics.
    16. Francis Teal & Marcella Vigneri, 2004. "Production changes in ghana cocoa farming households under market reforms," CSAE Working Paper Series 2004-16, Centre for the Study of African Economies, University of Oxford.
    17. Tim Liao, 1995. "The nonrandom selection of don't knows in binary and ordinal responses: Corrections with the bivariate probit model with sample selection," Quality & Quantity: International Journal of Methodology, Springer, vol. 29(1), pages 87-110, February.
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    19. Dimitrios Bakas & Theodore Panagiotidis & Gianluigi Pelloni, 2023. "Labor Reallocation and Unemployment Fluctuations: A Tale of Two Tails," Working Paper series 23-07, Rimini Centre for Economic Analysis.
    20. Richard Blundell & Frank Windmeijer, 2000. "Identifying demand for health resources using waiting times information," IFS Working Papers W00/03, Institute for Fiscal Studies.
    21. Atak, Alev & Linton, Oliver B. & Xiao, Zhijie, 2010. "A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom," MPRA Paper 22079, University Library of Munich, Germany.
    22. Hiau Joo Kee, 2005. "Glass Ceiling or Sticky Floor? Exploring the Australian Gender Pay Gap using Quantile Regression and Counterfactual Decomposition Methods," CEPR Discussion Papers 487, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    23. Günter Hitsch & Ali Hortaçsu & Dan Ariely, 2010. "What makes you click?—Mate preferences in online dating," Quantitative Marketing and Economics (QME), Springer, vol. 8(4), pages 393-427, December.
    24. Joseph E. Zveglich Jr. & Yana van der Meulen Rodgers & William M. Rodgers III, 1997. "The Persistence of Gender Earnings Inequality in Taiwan, 1978–1992," ILR Review, Cornell University, ILR School, vol. 50(4), pages 594-609, July.
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    5. Nyström, Kristina, 2005. "Interdependencies in the Dynamics of Firm Entry and Exit," Working Paper Series in Economics and Institutions of Innovation 28, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
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  76. Douglas Holtz-Eakin & Whitney Newey & Harvey S. Rosen, 1987. "Wages and Hours: Estimating Vector Autoregressions with Panel Data," Working Papers 602, Princeton University, Department of Economics, Industrial Relations Section..

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    1. Donadelli, Michael & Ferranna, Licia & Gufler, Ivan & Paradiso, Antonio, 2021. "Using past epidemics to estimate the macroeconomic implications of COVID-19: A bad idea!," Structural Change and Economic Dynamics, Elsevier, vol. 57(C), pages 214-224.
    2. António Afonso & Michael G. Arghyrou & María Dolores Gadea & Alexandros Kontonikas, 2017. ""Whatever it takes" to resolve the European sovereign debt crisis? Bond pricing regime switches and monetary policy effects," Working Papers REM 2017/02, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    3. Smajlbegovic, Esad, 2015. "Regional Economic Activity and Stock Returns," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112854, Verein für Socialpolitik / German Economic Association.
    4. Aaron Tornell & Frank Westermann & Lorenza Martinez, 2004. "The Positive Link Between Financial Liberalization, Growth and Crises," NBER Working Papers 10293, National Bureau of Economic Research, Inc.
    5. Zuzana Rakovska & Dominika Ehrenbergerova & Martin Hodula, 2020. "The Power of Sentiment: Irrational Beliefs of Households and Consumer Loan Dynamics," Working Papers 2020/10, Czech National Bank.
    6. Qazi Haque & Leandro M. Magnusson, 2020. "Identification robust empirical evidence on the Euler equation in open economies," CAMA Working Papers 2020-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Klaus Grobys & Topi Huhta-Halkola, 2019. "Combining value and momentum: evidence from the Nordic equity market," Applied Economics, Taylor & Francis Journals, vol. 51(26), pages 2872-2884, June.
    8. Franklin G. Mixon & Chandini Sankaran, 2019. "Men in Grey Suits: Shark Activity and Congestion of the Surfing Commons," Sustainability, MDPI, vol. 11(11), pages 1-15, June.
    9. El-Shazly Alaa, 2005. "Imperfect Information and Credit Rationing Equilibrium: Evidence from Egypt," Review of Middle East Economics and Finance, De Gruyter, vol. 3(2), pages 59-72, August.
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    12. Andrew M. McKenzie & Bingrong Jiang & Harjanto Djunaidi & Linwood A. Hoffman & Eric J. Wailes, 2002. "Unbiasedness and Market Efficiency Tests of the U.S. Rice Futures Market," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 24(2), pages 474-493.
    13. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    14. Neuenkirch, Matthias & Siklos, Pierre L., 2013. "What's in a second opinion? Shadowing the ECB and the Bank of England," European Journal of Political Economy, Elsevier, vol. 32(C), pages 135-148.
    15. Babalos, Vassilios & Caporale, Guglielmo Maria & Philippas, Nikolaos, 2015. "Gender, style diversity, and their effect on fund performance," Research in International Business and Finance, Elsevier, vol. 35(C), pages 57-74.
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    6925. Jungshik Hur & Cedric Mbanga Luma, 2017. "Aggregate idiosyncratic volatility, dynamic aspects of loss aversion, and narrow framing," Review of Quantitative Finance and Accounting, Springer, vol. 49(2), pages 407-433, August.
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    6928. Driessen, Joost & Laeven, Luc, 2007. "International portfolio diversification benefits: Cross-country evidence from a local perspective," Journal of Banking & Finance, Elsevier, vol. 31(6), pages 1693-1712, June.
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    6931. Hu, Jianfeng, 2014. "Does option trading convey stock price information?," Journal of Financial Economics, Elsevier, vol. 111(3), pages 625-645.
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    7339. Simon Fritzsch & Maike Timphus & Gregor Weiss, 2021. "Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?," Papers 2109.10946, arXiv.org.
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    Cited by:

    1. Calzolari, Giorgio, 1992. "Stima delle equazioni simultanee non-lineari: una rassegna [Estimation of nonlinear simultaneous equations: a survey]," MPRA Paper 24123, University Library of Munich, Germany, revised 1992.
    2. Brueckner,Markus & Lederman,Daniel, 2018. "Inequality and economic growth : the role of initial income," Policy Research Working Paper Series 8467, The World Bank.
    3. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Post-Print hal-03072119, HAL.
    4. So Im, Kyung & Ahn, Seung C. & Schmidt, Peter & Wooldridge, Jeffrey M., 1999. "Efficient estimation of panel data models with strictly exogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 93(1), pages 177-201, November.
    5. Hala Abou-Ali & Yasmine M. Abdelfattah, 2011. "Integrated Paradigm for Sustainable Development: A Panel Data Study," Working Papers 646, Economic Research Forum, revised 10 Jan 2011.
    6. Fackler, Paul L., 1988. "Vector Autoregressive Techniques for Structural Analysis," Department of Economics and Business - Archive 259427, North Carolina State University, Department of Economics.
    7. Panizza, Ugo & Presbitero, Andrea F., 2012. "Public debt and economic growth: Is there a causal effect?," POLIS Working Papers 168, Institute of Public Policy and Public Choice - POLIS.
    8. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.
    9. Bernard Fortin & Nadia Joubert & Guy Lacroix, 2002. "Fiscalité, effets de voisinage et offre de travail au noir," Post-Print halshs-00178184, HAL.
    10. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
    11. Arnab Bhattacharjee & Chris Jensen-Butler, 2011. "Estimation of the Spatial Weights Matrix under Structural Constraints," Dundee Discussion Papers in Economics 254, Economic Studies, University of Dundee.
    12. Jacoby, Hanan G. & Mansuri, Ghazala, 2007. "Watta satta : bride exchange and women's welfare in rural Pakistan," Policy Research Working Paper Series 4126, The World Bank.
    13. Jingwen Zhang & Yifang Chen & Amandeep Singh, 2022. "Causal Bandits: Online Decision-Making in Endogenous Settings," Papers 2211.08649, arXiv.org, revised Feb 2023.
    14. Bhattacharjee, A. & Holly, S., 2010. "Understanding Interactions in Social Networks and Committees," Cambridge Working Papers in Economics 1003, Faculty of Economics, University of Cambridge.
    15. Biørn, Erik, 2017. "Identification, Instruments, Omitted Variables, and Rudimentary Models: Fallacies in the ‘Experimental Approach’ to Econometrics," Memorandum 13/2017, Oslo University, Department of Economics.
    16. Calzolari, Giorgio & Sampoli, Letizia, 1989. "Instrumental variables interpretations of FIML and nonlinear FIML," MPRA Paper 29024, University Library of Munich, Germany.
    17. Sofien Tiba & Mohamed Frikha, 2020. "Sustainability Challenge in the Agenda of African Countries: Evidence from Simultaneous Equations Models," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(3), pages 1270-1294, September.
    18. Prabuddha De & Yu (Jeffrey) Hu & Mohammad S. Rahman, 2010. "Technology Usage and Online Sales: An Empirical Study," Management Science, INFORMS, vol. 56(11), pages 1930-1945, November.
    19. Taghizadeh Hesary Farhad & Naoyuki Yoshino, 2013. "Empirical Analysis of Oil Price Determination Based on Market Quality Theory," Keio/Kyoto Joint Global COE Discussion Paper Series 2012-044, Keio/Kyoto Joint Global COE Program.
    20. Robert G. King & Mark W. Watson, 1997. "Testing long-run neutrality," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 69-101.
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    22. Hartley, Peter R. & Whitt Jr, Joseph A., 2003. "Macroeconomic fluctuations: Demand or supply, permanent or temporary?," European Economic Review, Elsevier, vol. 47(1), pages 61-94, February.
    23. Markus Brueckner, 2022. "Estimating Causal Effects of Monetary Policy for a Small Open Economy: Econometric Model and Estimation Framework," ANU Working Papers in Economics and Econometrics 2022-689, Australian National University, College of Business and Economics, School of Economics.
    24. Gori, Filippo, 2018. "Dissecting the ‘doom loop’: the bank-sovereign credit risk nexus during the US debt ceiling crisis," MPRA Paper 87994, University Library of Munich, Germany.
    25. Kevin Williams, 2023. "Does trade shape educational decisions? The role of initial schooling," Economic Change and Restructuring, Springer, vol. 56(5), pages 3631-3663, October.
    26. Hausman, Jerry A., 2003. "Triangular structural model specification and estimation with application to causality," Journal of Econometrics, Elsevier, vol. 112(1), pages 107-113, January.
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    30. Steven Lehrer & Weili Ding, 2004. "Estimating Dynamic Treatment Effects from Project STAR," Econometric Society 2004 North American Summer Meetings 252, Econometric Society.

Articles

  1. Sören Blomquist & Whitney K. Newey & Anil Kumar & Che-Yuan Liang, 2021. "On Bunching and Identification of the Taxable Income Elasticity," Journal of Political Economy, University of Chicago Press, vol. 129(8), pages 2320-2343.
    See citations under working paper version above.
  2. Newey, Whitney & Stouli, Sami, 2021. "Control variables, discrete instruments, and identification of structural functions," Journal of Econometrics, Elsevier, vol. 222(1), pages 73-88.
    See citations under working paper version above.
  3. Victor Chernozhukov & Iván Fernández‐Val & Whitney Newey & Sami Stouli & Francis Vella, 2020. "Semiparametric estimation of structural functions in nonseparable triangular models," Quantitative Economics, Econometric Society, vol. 11(2), pages 503-533, May.
    See citations under working paper version above.
  4. Drew Fudenberg & Whitney Newey & Philipp Strack & Tomasz Strzalecki, 2020. "Testing the drift-diffusion model," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(52), pages 33141-33148, December.
    See citations under working paper version above.
  5. Chernozhukov, Victor & Fernández-Val, Iván & Newey, Whitney K., 2019. "Nonseparable multinomial choice models in cross-section and panel data," Journal of Econometrics, Elsevier, vol. 211(1), pages 104-116.
    See citations under working paper version above.
  6. Cattaneo, Matias D. & Jansson, Michael & Newey, Whitney K., 2018. "Alternative Asymptotics And The Partially Linear Model With Many Regressors," Econometric Theory, Cambridge University Press, vol. 34(2), pages 277-301, April.
    See citations under working paper version above.
  7. Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2018. "Inference in Linear Regression Models with Many Covariates and Heteroscedasticity," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1350-1361, July.
    See citations under working paper version above.
  8. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    See citations under working paper version above.
  9. Jerry A. Hausman & Whitney K. Newey, 2017. "Nonparametric Welfare Analysis," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 521-546, September.

    Cited by:

    1. Richard Blundell & Joel Horowitz & Matthias Parey, 2022. "Estimation of a Heterogeneous Demand Function with Berkson Errors," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 877-889, December.
    2. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    3. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    4. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    5. Richard Blundell & Joel L. Horowitz & Matthias Parey, 2018. "Estimation of a nonseparable heterogenous demand function with shape restrictions and Berkson errors," CeMMAP working papers CWP67/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Sarantis Tsiaplias, 2017. "The Welfare Implications of Unobserved Heterogeneity," Melbourne Institute Working Paper Series wp2017n21, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    7. Matias D. Cattaneo & Xinwei Ma & Yusufcan Masatlioglu & Elchin Suleymanov, 2020. "A Random Attention Model," Journal of Political Economy, University of Chicago Press, vol. 128(7), pages 2796-2836.
    8. Victor Chernozhukov & Iván Fernández‐Val & Ye Luo, 2018. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Econometrica, Econometric Society, vol. 86(6), pages 1911-1938, November.
    9. Karun Adusumilli & Taisuke Otsu & Chen Qiu, 2020. "Reweighted nonparametric likelihood inference for linear functionals," STICERD - Econometrics Paper Series 614, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    10. KANEKO Shinji & KAWATA Keisuke & YIN Ting, 2019. "Estimating Family Preference for Home Elderly-care Services: Large-scale Conjoint Survey Experiment in Japan," Discussion papers 19092, Research Institute of Economy, Trade and Industry (RIETI).
    11. Adusumilli, Karun & Otsu, Taisuke & Qiu, Chen, 2023. "Reweighted nonparametric likelihood inference for linear functionals," LSE Research Online Documents on Economics 120198, London School of Economics and Political Science, LSE Library.

  10. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey, 2017. "Double/Debiased/Neyman Machine Learning of Treatment Effects," American Economic Review, American Economic Association, vol. 107(5), pages 261-265, May.

    Cited by:

    1. Delprato, Marcos & Frola, Alessia & Antequera, Germán, 2022. "Indigenous and non-Indigenous proficiency gaps for out-of-school and in-school populations: A machine learning approach," International Journal of Educational Development, Elsevier, vol. 93(C).
    2. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    3. Xiong, Ruoxuan & Koenecke, Allison & Powell, Michael & Shen, Zhu & Vogelstein, Joshua T. & Athey, Susan, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Research Papers 3990, Stanford University, Graduate School of Business.
    4. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Tinbergen Institute Discussion Papers 21-001/V, Tinbergen Institute.
    5. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    6. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    7. Maximilian Maurice Gail & Phil-Adrian Klotz, 2021. "The Impact of the Agency Model on E-book Prices: Evidence from the UK," MAGKS Papers on Economics 202111, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    8. Oliver Hines & Stijn Vansteelandt & Karla Diaz-Ordaz, 2021. "Robust Inference for Mediated Effects in Partially Linear Models," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 595-618, June.
    9. Jong Hee Park & Byung Koo Kim, 2020. "Why your neighbor matters: Positions in preferential trade agreement networks and export growth in global value chains," Economics and Politics, Wiley Blackwell, vol. 32(3), pages 381-410, November.
    10. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    11. Vira Semenova, 2017. "Debiased Machine Learning of Set-Identified Linear Models," Papers 1712.10024, arXiv.org, revised Dec 2022.
    12. Ziwei Cong & Jia Liu & Puneet Manchanda, 2021. "The Role of "Live" in Livestreaming Markets: Evidence Using Orthogonal Random Forest," Papers 2107.01629, arXiv.org, revised Sep 2022.
    13. Amit Sharma & Emre Kiciman, 2020. "DoWhy: An End-to-End Library for Causal Inference," Papers 2011.04216, arXiv.org.
    14. Feng, Sanying & Kong, Kaidi & Kong, Yinfei & Li, Gaorong & Wang, Zhaoliang, 2022. "Statistical inference of heterogeneous treatment effect based on single-index model," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    15. Miquel Oliu-Barton & Bary S R Pradelski & Nicolas Woloszko & Lionel Guetta-Jeanrenaud & Philippe Aghion & Patrick Artus & Arnaud Fontanet & Philippe Martin & Guntram B Wolff, 2022. "The Effect of COVID Certificates on Vaccine Uptake, Health Outcomes, and the Economy," Post-Print hal-03813557, HAL.
    16. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Inference on weighted average value function in high-dimensional state space," Papers 1908.09173, arXiv.org.
    17. Waverly Wei & Maya Petersen & Mark J van der Laan & Zeyu Zheng & Chong Wu & Jingshen Wang, 2023. "Efficient targeted learning of heterogeneous treatment effects for multiple subgroups," Biometrics, The International Biometric Society, vol. 79(3), pages 1934-1946, September.
    18. Jinyong Hahn & Jerry Hausman, 2021. "Problems with the Control Variable Approach in Achieving Unbiased Estimates in Nonlinear Models in the Presence of Many Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 39-58, December.
    19. Sven Klaassen & Jannis Kuck & Martin Spindler & Victor Chernozhukov, 2018. "Uniform Inference in High-Dimensional Gaussian Graphical Models," Papers 1808.10532, arXiv.org, revised Dec 2018.
    20. Wang, Hongning & Ma, Sanjun, 2022. "Preventing crimes against public health with artificial intelligence and machine learning capabilities," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    21. Yong Bian & Xiqian Wang & Qin Zhang, 2023. "How Does China's Household Portfolio Selection Vary with Financial Inclusion?," Papers 2311.01206, arXiv.org.
    22. Betts,Alexander Milton Stedman & Stierna,Maria Flinder & Omata,Naohiko & Sterck,Olivier Christian Brigitte, 2022. "Social Cohesion and Refugee-Host Interactions : Evidence from East Africa," Policy Research Working Paper Series 9917, The World Bank.
    23. Monica Andini & Emanuele Ciani & Guido de Blasio & Alessio D'Ignazio & Viola Salvestrini, 2017. "Targeting policy-compliers with machine learning: an application to a tax rebate programme in Italy," Temi di discussione (Economic working papers) 1158, Bank of Italy, Economic Research and International Relations Area.
    24. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
    25. Bobonis, Gustavo & Gertler, Paul & Gonzalez-Navarro, Marco & Nichter, Simeon, 2023. "Does Combating Corruption Reduce Clientelism?," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt13k514pd, Department of Agricultural & Resource Economics, UC Berkeley.
    26. Jules Gazeaud & Nausheen Khan & Eric Mvukiyehe & Olivier Sterck, 2023. "With or without him? Experimental evidence on cash grants and gender-sensitive trainings in Tunisia," Post-Print hal-04364356, HAL.
    27. Sven Klaassen & Jannis Kueck & Martin Spindler, 2017. "Transformation Models in High-Dimensions," Papers 1712.07364, arXiv.org.
    28. Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
    29. Jikai Jin & Vasilis Syrgkanis, 2024. "Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation," Papers 2402.14264, arXiv.org, revised Mar 2024.
    30. Francesco Decarolis & Cristina Giorgiantonio, 2020. "Corruption red flags in public procurement: new evidence from Italian calls for tenders," Questioni di Economia e Finanza (Occasional Papers) 544, Bank of Italy, Economic Research and International Relations Area.
    31. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Source Condition Double Robust Inference on Functionals of Inverse Problems," Papers 2307.13793, arXiv.org.
    32. Vira Semenova, 2018. "Machine Learning for Dynamic Discrete Choice," Papers 1808.02569, arXiv.org, revised Nov 2018.
    33. Carl Bonander & Mikael Svensson, 2021. "Using causal forests to assess heterogeneity in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1818-1832, August.
    34. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    35. Huber, Martin & Wüthrich, Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," University of California at San Diego, Economics Working Paper Series qt4j29d8sc, Department of Economics, UC San Diego.
    36. Valente, Marica, 2023. "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    37. Maria Cuellar & Edward H. Kennedy, 2020. "A non‐parametric projection‐based estimator for the probability of causation, with application to water sanitation in Kenya," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1793-1818, October.
    38. Laura Derksen & Jason Kerwin & Natalia Ordaz Reynoso & Olivier Sterck, 2021. "Appointments: A More Effective Commitment Device for Health Behaviors," Papers 2110.06876, arXiv.org.
    39. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Papers 2101.00878, arXiv.org.
    40. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    41. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    42. Zhen Li & Jie Chen & Eric Laber & Fang Liu & Richard Baumgartner, 2023. "Optimal Treatment Regimes: A Review and Empirical Comparison," International Statistical Review, International Statistical Institute, vol. 91(3), pages 427-463, December.
    43. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    44. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    45. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    46. Wang, Xiqian & Bian, Yong & Zhang, Qin, 2023. "The effect of cooking fuel choice on the elderly’s well-being: Evidence from two non-parametric methods," Energy Economics, Elsevier, vol. 125(C).
    47. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Economica, London School of Economics and Political Science, vol. 89(354), pages 362-376, April.
    48. Heiler, Phillip & Kazak, Ekaterina, 2021. "Valid inference for treatment effect parameters under irregular identification and many extreme propensity scores," Journal of Econometrics, Elsevier, vol. 222(2), pages 1083-1108.
    49. Pradhi Aggarwal & Alec Brandon & Ariel Goldszmidt & Justin Holz & John List & Ian Muir & Gregory Sun & Thomas Yu, 2022. "High-frequency location data shows that race affects the likelihood of being stopped and fined for speeding," Natural Field Experiments 00764, The Field Experiments Website.
    50. Songul Cinaroglu, 2020. "Modelling unbalanced catastrophic health expenditure data by using machine‐learning methods," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 168-181, October.
    51. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    52. Matt Goldman & Brian Quistorff, 2018. "Pricing Engine: Estimating Causal Impacts in Real World Business Settings," Papers 1806.03285, arXiv.org, revised Jun 2018.
    53. Nikolaos Ignatiadis & Wolfgang Huber, 2021. "Covariate powered cross‐weighted multiple testing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 720-751, September.
    54. Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018. "Orthogonal Random Forest for Causal Inference," Papers 1806.03467, arXiv.org, revised Sep 2019.
    55. Gareth Liu-Evans & Shalini Mitra, 2023. "Formal sector enforcement and welfare," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(3), pages 706-728, June.
    56. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    57. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
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    59. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    60. Fernando Delbianco & Fernando Tohmé, 2023. "Individualized Conformal," Working Papers 247, Red Nacional de Investigadores en Economía (RedNIE).
    61. Sander Gerritsen & Mark Kattenberg & Sonny Kuijpers, 2019. "The impact of age at arrival on education and mental health," CPB Discussion Paper 389, CPB Netherlands Bureau for Economic Policy Analysis.
    62. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised Nov 2023.
    63. Fukuyama, Hirofumi & Tsionas, Mike & Tan, Yong, 2023. "Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: Application to the Chinese banking industry," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1360-1373.
    64. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    65. Mark Kattenberg & Bas Scheer & Jurre Thiel, 2023. "Causal forests with fixed effects for treatment effect heterogeneity in difference-in-differences," CPB Discussion Paper 452, CPB Netherlands Bureau for Economic Policy Analysis.
    66. Jonas Metzger, 2022. "Adversarial Estimators," Papers 2204.10495, arXiv.org, revised Jun 2022.
    67. Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.
    68. Dongcheng Zhang & Kunpeng Zhang, 2020. "Weighting-Based Treatment Effect Estimation via Distribution Learning," Papers 2012.13805, arXiv.org, revised May 2023.
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    73. Heigle, Julia & Pfeiffer, Friedhelm, 2019. "An analysis of selected labor market outcomes of college dropouts in Germany: A machine learning estimation approach. Research report," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 222378, September.
    74. Stephan Martin, 2022. "Estimation of Conditional Random Coefficient Models using Machine Learning Techniques," Papers 2201.08366, arXiv.org.
    75. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    76. Falco J. Bargagli Stoffi & Kenneth De Beckker & Joana E. Maldonado & Kristof De Witte, 2021. "Assessing Sensitivity of Machine Learning Predictions.A Novel Toolbox with an Application to Financial Literacy," Papers 2102.04382, arXiv.org.
    77. Ashkan Ertefaie & Nima S. Hejazi & Mark J. van der Laan, 2023. "Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso," Biometrics, The International Biometric Society, vol. 79(2), pages 1029-1041, June.
    78. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    79. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations," Papers 1910.09004, arXiv.org, revised Aug 2020.
    80. Betts, Alexander & Flinder Stierna, Maria & Omata, Naohiko & Sterck, Olivier, 2023. "Refugees welcome? Inter-group interaction and host community attitude formation," World Development, Elsevier, vol. 161(C).
    81. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
    82. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    83. Johannes Jakubik & Stefan Feuerriegel, 2022. "Data‐driven allocation of development aid toward sustainable development goals: Evidence from HIV/AIDS," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2739-2756, June.

  11. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    See citations under working paper version above.
  12. Chernozhukov, Victor & Fernández-Val, Iván & Hoderlein, Stefan & Holzmann, Hajo & Newey, Whitney, 2015. "Nonparametric identification in panels using quantiles," Journal of Econometrics, Elsevier, vol. 188(2), pages 378-392.
    See citations under working paper version above.
  13. Chao, John C. & Hausman, Jerry A. & Newey, Whitney K. & Swanson, Norman R. & Woutersen, Tiemen, 2014. "Testing overidentifying restrictions with many instruments and heteroskedasticity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 15-21.
    See citations under working paper version above.
  14. Xiaohong Chen & Victor Chernozhukov & Sokbae Lee & Whitney K. Newey, 2014. "Local Identification of Nonparametric and Semiparametric Models," Econometrica, Econometric Society, vol. 82(2), pages 785-809, March.
    See citations under working paper version above.
  15. Whitney K. Newey, 2013. "Nonparametric Instrumental Variables Estimation," American Economic Review, American Economic Association, vol. 103(3), pages 550-556, May.

    Cited by:

    1. Rodrigo Adao & Arnaud Costinot & Dave Donaldson, 2017. "Nonparametric Counterfactual Predictions in Neoclassical Models of International Trade," American Economic Review, American Economic Association, vol. 107(3), pages 633-689, March.
    2. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Xue, Melanie Meng, 2018. "High-Value Work and the Rise of Women: The Cotton Revolution and Gender Equality in China," MPRA Paper 91100, University Library of Munich, Germany.
    4. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    5. Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Papers 1411.1144, arXiv.org, revised Mar 2015.
    6. Liu, Chu-An & Tao, Jing, 2016. "Model selection and model averaging in nonparametric instrumental variables models," MPRA Paper 69492, University Library of Munich, Germany.
    7. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    8. Xiaohong Chen & Timothy M. Christensen, 2015. "Optimal sup-norm rates, adaptivity and inference in nonparametric instrumental variables estimation," CeMMAP working papers 32/15, Institute for Fiscal Studies.
    9. Martin Emil Jakobsen & Jonas Peters, 2020. "Distributional robustness of K-class estimators and the PULSE," Papers 2005.03353, arXiv.org, revised Mar 2022.
    10. Susan Athey & Julie Tibshirani & Stefan Wager, 2016. "Generalized Random Forests," Papers 1610.01271, arXiv.org, revised Apr 2018.
    11. Carlos Felipe Balcázar & Lidia Ceriani & Sergio Olivieri & Marco Ranzani, 2017. "Rent‐Imputation for Welfare Measurement: A Review of Methodologies and Empirical Findings," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(4), pages 881-898, December.
    12. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Source Condition Double Robust Inference on Functionals of Inverse Problems," Papers 2307.13793, arXiv.org.
    13. Loh, Isaac, 2023. "Genericity of the completeness condition with constrained instruments," Economics Letters, Elsevier, vol. 224(C).
    14. Evgeniy Ozhegov, 2015. "Identification in a class of nonparametric simultaneous equation models with sample selection (in Russian)," Quantile, Quantile, issue 13, pages 15-23, May.
    15. Evgeniy M. Ozhegov, 2014. "The Underwriting, Choice And Performance Of Government-Insured Mortgages In Russia," HSE Working papers WP BRP 31/FE/2014, National Research University Higher School of Economics.
    16. Xiaohong Chen & Timothy M. Christensen, 2015. "Optimal sup-norm rates, adaptivity and inference in nonparametric instrumental variables estimation," CeMMAP working papers CWP32/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Alyssa Carlson, 2021. "Relaxing Conditional Independence in an Endogenous Binary Response Model," Working Papers 2113, Department of Economics, University of Missouri.
    18. Christiane Hinerasky, 2014. "Advances in Training Evaluation - Psychological, Educational, Economic, and Econometric Perspectives on the Kirkpatrick Model," Working Papers Dissertations 14, Paderborn University, Faculty of Business Administration and Economics.
    19. Hoshino, Tadao, 2022. "Sieve IV estimation of cross-sectional interaction models with nonparametric endogenous effect," Journal of Econometrics, Elsevier, vol. 229(2), pages 263-275.
    20. Guy Tchuente, 2016. "Estimation of social interaction models using regularization," Studies in Economics 1607, School of Economics, University of Kent.
    21. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    22. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers 37/13, Institute for Fiscal Studies.
    23. Alina Buzanakova & Evgeniy M. Ozhegov, 2016. "Demand for performing arts: the effect of unobserved quality on price elasticity," ACEI Working Paper Series AWP-05-2016, Association for Cultural Economics International, revised Jun 2016.
    24. Claire-Océane Chevallier, 2017. "Empirical Investigation of the Effect of Bank Long Term Debt on Loans and Output in the Euro-zone," DEM Discussion Paper Series 17-04, Department of Economics at the University of Luxembourg.
    25. Guy Tchuente, 2019. "Weak Identification and Estimation of Social Interaction Models," Papers 1902.06143, arXiv.org.
    26. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    27. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness," Papers 2302.05404, arXiv.org.
    28. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers 48/13, Institute for Fiscal Studies.
    29. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers CWP48/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Anupriya, & Graham, Daniel J. & Bansal, Prateek & Hörcher, Daniel & Anderson, Richard, 2023. "Optimal congestion control strategies for near-capacity urban metros: Informing intervention via fundamental diagrams," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    31. Sourabh Balgi & Adel Daoud & Jose M. Pe~na & Geoffrey T. Wodtke & Jesse Zhou, 2024. "Deep Learning With DAGs," Papers 2401.06864, arXiv.org.
    32. Yingying Dong & Michal Kolesár, 2023. "When Can We Ignore Measurement Error in the Running Variable?," Working Papers 2022-13, Princeton University. Economics Department..
    33. Anupriya, & Bansal, Prateek & Graham, Daniel J., 2023. "Congestion in cities: Can road capacity expansions provide a solution?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    34. Dieterle, Steven G. & Snell, Andy, 2016. "A simple diagnostic to investigate instrument validity and heterogeneous effects when using a single instrument," Labour Economics, Elsevier, vol. 42(C), pages 76-86.
    35. Kaukin, Andrey (Каукин, Андрей), 2018. "Diagnosis of the Growth Model of the Russian Air Transportation Market: Bottlenecks and Directions of Development [Диагностика Модели Роста Российского Рынка Авиаперевозок: Узкие Места И Направлени," Working Papers 061830, Russian Presidential Academy of National Economy and Public Administration.
    36. Yingying Dong & Michal Kolesár, 2023. "When can we ignore measurement error in the running variable?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 735-750, August.

  16. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
    See citations under working paper version above.
  17. Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen & John C. Chao & Norman R. Swanson, 2012. "Instrumental variable estimation with heteroskedasticity and many instruments," Quantitative Economics, Econometric Society, vol. 3(2), pages 211-255, July.
    See citations under working paper version above.
  18. Chao, John C. & Swanson, Norman R. & Hausman, Jerry A. & Newey, Whitney K. & Woutersen, Tiemen, 2012. "Asymptotic Distribution Of Jive In A Heteroskedastic Iv Regression With Many Instruments," Econometric Theory, Cambridge University Press, vol. 28(1), pages 42-86, February.
    See citations under working paper version above.
  19. Hausman, Jerry & Lewis, Randall & Menzel, Konrad & Newey, Whitney, 2011. "Properties of the CUE estimator and a modification with moments," Journal of Econometrics, Elsevier, vol. 165(1), pages 45-57.

    Cited by:

    1. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
    2. Meijer, Erik & Spierdijk, Laura & Wansbeek, Tom, 2017. "Consistent estimation of linear panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 169-180.
    3. Naoto Kunitomo & Michael McAleer & Yoshihiko Nishiyama, 2010. "Moment Restriction-based Econometric Methods: An Overview," KIER Working Papers 734, Kyoto University, Institute of Economic Research.
    4. Stéphane Bonhomme & Martin Weidner, 2020. "Minimizing Sensitivity to Model Misspecification," CeMMAP working papers CWP37/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Pierre Chausse, 2017. "Regularized Empirical Likelihood as a Solution to the No Moment," Working Papers 1708, University of Waterloo, Department of Economics, revised Nov 2017.
    6. Stéphane Bonhomme & Martin Weidner, 2022. "Minimizing sensitivity to model misspecification," Quantitative Economics, Econometric Society, vol. 13(3), pages 907-954, July.
    7. Myung Hwan Seo & Yongcheol Shin, 2014. "Dynamic Panels with Threshold Effect and Endogeneity," STICERD - Econometrics Paper Series 577, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    8. Marine Carrasco & Guy Tchuente, 2015. "Efficient estimation with many weak instruments using regularization techniques," Studies in Economics 1517, School of Economics, University of Kent.
    9. Andreas Tryphonides, 2017. "Conditional moment restrictions and the role of density information in estimated structural models," SFB 649 Discussion Papers SFB649DP2017-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Rachida Ouysse, 2014. "On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models," Computational Statistics, Springer, vol. 29(1), pages 233-261, February.
    11. Dakyung Seong, 2022. "Binary response model with many weak instruments," Papers 2201.04811, arXiv.org, revised May 2023.
    12. Chaudhuri, Saraswata & Renault, Eric, 2020. "Score tests in GMM: Why use implied probabilities?," Journal of Econometrics, Elsevier, vol. 219(2), pages 260-280.

  20. Hansen, Christian & McDonald, James B. & Newey, Whitney K., 2010. "Instrumental Variables Estimation With Flexible Distributions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 13-25.
    See citations under working paper version above.
  21. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2009. "Choosing instrumental variables in conditional moment restriction models," Journal of Econometrics, Elsevier, vol. 152(1), pages 28-36, September.

    Cited by:

    1. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    2. Nguyen, Canh Phuc & Doytch, Nadia, 2022. "The impact of ICT patents on economic growth: An international evidence," Telecommunications Policy, Elsevier, vol. 46(5).
    3. Sentana, Enrique & Peñaranda, Francisco, 2007. "Duality in Mean-Variance Frontiers with Conditioning Information," CEPR Discussion Papers 6566, C.E.P.R. Discussion Papers.
    4. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    5. Hao Hao & Bai Huang & Tae-Hwy Lee, 2022. "Model Averaging Estimation of Panel Data Models with Many Instruments and Boosting," Working Papers 202212, University of California at Riverside, Department of Economics.
    6. Liu, Chu-An & Tao, Jing, 2016. "Model selection and model averaging in nonparametric instrumental variables models," MPRA Paper 69492, University Library of Munich, Germany.
    7. Varvara Isyuk, 2014. "Resuming bank lending in the aftermath of the Capital Purchase Program," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01093414, HAL.
    8. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    9. Parente, Paulo M.D.C. & Smith, Richard J., 2017. "Tests of additional conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 200(1), pages 1-16.
    10. Shantanu Gupta & Zachary C. Lipton & David Childers, 2021. "Efficient Online Estimation of Causal Effects by Deciding What to Observe," Papers 2108.09265, arXiv.org, revised Oct 2021.
    11. Varvara Isyuk, 2014. "Resuming bank lending in the aftermath of the Capital Purchase Program," Post-Print halshs-01093414, HAL.
    12. Sébastien Mary & Avraham Stoler, 2021. "Does agricultural trade liberalization increase obesity in developing countries?," Review of Development Economics, Wiley Blackwell, vol. 25(3), pages 1326-1350, August.
    13. Richard Ashley & Christopher Parmeter, 2015. "Sensitivity analysis for inference in 2SLS/GMM estimation with possibly flawed instruments," Empirical Economics, Springer, vol. 49(4), pages 1153-1171, December.
    14. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 14-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Dec 2014.
    15. Yves G. Berger, 2023. "Unconditional empirical likelihood approach for analytic use of public survey data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 383-410, March.
    16. Mary, Sebastien & Shaw, Kelsey & Colen, Liesbeth & Gomez y Paloma, Sergio, 2020. "Does agricultural aid reduce child stunting?," World Development, Elsevier, vol. 130(C).
    17. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    18. Victor Chernozhukov & Iv'an Fern'andez-Val & Chen Huang & Weining Wang, 2024. "Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models," Papers 2402.00584, arXiv.org, revised Apr 2024.
    19. Kuersteiner, Guido M., 2012. "Kernel-weighted GMM estimators for linear time series models," Journal of Econometrics, Elsevier, vol. 170(2), pages 399-421.
    20. Kun Xu & Yanyuan Ma & Liqun Wang, 2015. "Instrument Assisted Regression for Errors in Variables Models with Binary Response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 104-117, March.
    21. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    22. Berger, Yves G. & Patilea, Valentin, 2022. "A semi-parametric empirical likelihood approach for conditional estimating equations under endogenous selection," Econometrics and Statistics, Elsevier, vol. 24(C), pages 151-163.
    23. Stefan Boes, 2010. "Count Data Models with Correlated Unobserved Heterogeneity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(3), pages 382-402, September.
    24. Shakil, Golam Saroare & Marsh, Thomas L., 2021. "One Instrument to Rule Them All?," 2021 Annual Meeting, August 1-3, Austin, Texas 314047, Agricultural and Applied Economics Association.
    25. DiTraglia, Francis J., 2016. "Using invalid instruments on purpose: Focused moment selection and averaging for GMM," Journal of Econometrics, Elsevier, vol. 195(2), pages 187-208.
    26. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    27. Sébastien Mary & Kelsey Shaw & Sergio Gomez y Paloma, 2019. "Does the sectoral composition of growth affect child stunting reductions?," Development Policy Review, Overseas Development Institute, vol. 37(2), pages 225-244, March.
    28. Nguyen, Canh Phuc & Nguyen, Binh Quang, 2023. "Environmental foe or friend: The influence of the shadow economy on forest land," Land Use Policy, Elsevier, vol. 124(C).
    29. Sébastien Mary, 2019. "Hungry for free trade? Food trade and extreme hunger in developing countries," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(2), pages 461-477, April.
    30. Jonathan Chassot & Michael Creel, 2023. "Constructing Efficient Simulated Moments Using Temporal Convolutional Networks," Working Papers 1412, Barcelona School of Economics.
    31. Creel, Michael, 2017. "Neural nets for indirect inference," Econometrics and Statistics, Elsevier, vol. 2(C), pages 36-49.
    32. Varvara Isyuk, 2014. "Resuming bank lending in the aftermath of the Capital Purchase Program," Documents de travail du Centre d'Economie de la Sorbonne 14062, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    33. Michael Creel, 2016. "Neural Nets for Indirect Inference," UFAE and IAE Working Papers 960.16, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 18 Jul 2016.
    34. Nguyen, Canh Phuc, 2021. "Gender equality and economic complexity," Economic Systems, Elsevier, vol. 45(4).
    35. Michael Creel, 2021. "Inference Using Simulated Neural Moments," Econometrics, MDPI, vol. 9(4), pages 1-15, September.
    36. Canay, Ivan A., 2010. "Simultaneous selection and weighting of moments in GMM using a trapezoidal kernel," Journal of Econometrics, Elsevier, vol. 156(2), pages 284-303, June.
    37. Hristache, Marian & Patilea, Valentin, 2021. "Equivalent models for observables under the assumption of missing at random," Econometrics and Statistics, Elsevier, vol. 20(C), pages 153-165.
    38. Francis DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 15-027, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 10 Aug 2015.
    39. Sébastien Mary, 2018. "How Much Does Economic Growth Contribute to Child Stunting Reductions?," Economies, MDPI, vol. 6(4), pages 1-18, October.
    40. Cho, Hyunkeun, 2016. "The analysis of multivariate longitudinal data using multivariate marginal models," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 481-491.
    41. Christopher Conlon & Jeff Gortmaker, 2020. "Best practices for differentiated products demand estimation with PyBLP," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 1108-1161, December.
    42. Mary, Sébastien, 2018. "Does Agricultural (Food) Trade Openness Reduce Child Stunting?," 2018 Annual Meeting, August 5-7, Washington, D.C. 274282, Agricultural and Applied Economics Association.
    43. Enrico De Monte & Anne-Laure Levet, 2019. "Productivity Dynamics in French Woodworking Industries," Working Papers of BETA 2019-45, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    44. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

  22. Whitney K. Newey & Frank Windmeijer, 2009. "Generalized Method of Moments With Many Weak Moment Conditions," Econometrica, Econometric Society, vol. 77(3), pages 687-719, May.

    Cited by:

    1. Simon Freyaldenhoven & Christian Hansen & Jesse M. Shapiro, 2019. "Pre-event Trends in the Panel Event-Study Design," American Economic Review, American Economic Association, vol. 109(9), pages 3307-3338, September.
    2. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
    3. Gründler, Klaus & Scheuermeyer, Philipp, 2018. "Growth effects of inequality and redistribution: What are the transmission channels?," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 293-313.
    4. Brahim Gaies & Khaled Guesmi & St'ephane Goutte, 2019. "FDI, banking crisis and growth: direct and spill over effects," Papers 1904.04911, arXiv.org.
    5. Andrew Shephard & Xu Cheng & Alejándro Sanchez-Becerra, 2023. "How to weight in moments matchings: A new approach and applications to earnings dynamics," CeMMAP working papers 13/23, Institute for Fiscal Studies.
    6. Drew Fudenberg & Whitney K. Newey & Philipp Strack & Tomasz Strzalecki, 2019. "Testing the Drift-Diffusion Model," Papers 1908.05824, arXiv.org.
    7. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
    8. Böhm, Michael Johannes & Gaudecker, Hans-Martin von & Schran, Felix, 2019. "Occupation Growth, Skill Prices, and Wage Inequality," IZA Discussion Papers 12647, Institute of Labor Economics (IZA).
    9. Hayakawa, K. & Pesaran, M.H., 2012. "Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Models," Cambridge Working Papers in Economics 1224, Faculty of Economics, University of Cambridge.
    10. Frank Windmeijer, 2018. "Testing Over- and Underidentification in Linear Models, with Applications to Dynamic Panel Data and Asset-Pricing Models," Bristol Economics Discussion Papers 18/696, School of Economics, University of Bristol, UK.
    11. Sosson Tadadjeu & Henri Njangang & Simplice A. Asongu & Brice Kamguia, 2021. "Natural resources, child mortality and governance quality in African countries," Working Papers 21/027, European Xtramile Centre of African Studies (EXCAS).
    12. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    13. Richard A. Ashley & Xiaojin Sun, 2016. "Subset-Continuous-Updating GMM Estimators for Dynamic Panel Data Models," Econometrics, MDPI, vol. 4(4), pages 1-13, November.
    14. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
    15. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Ratto, Marco, 2018. "Identification Versus Misspecification in New Keynesian Monetary Policy Models," Working Paper Series 362, Sveriges Riksbank (Central Bank of Sweden).
    16. Prono, Todd, 2015. "Market proxies as factors in linear asset pricing models: Still living with the roll critique," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 36-53.
    17. Fan, Yanqin & Han, Fang & Li, Wei & Zhou, Xiao-Hua, 2020. "On rank estimators in increasing dimensions," Journal of Econometrics, Elsevier, vol. 214(2), pages 379-412.
    18. Peter C. B. Phillips, 2022. "An Econometrician amongst Statisticians: T. W. Anderson," Cowles Foundation Discussion Papers 2333, Cowles Foundation for Research in Economics, Yale University.
    19. Alexander Chudik & M. Hashem Pesaran, 2017. "An Augmented Anderson-Hsiao Estimator for Dynamic Short-T Panels," Globalization Institute Working Papers 327, Federal Reserve Bank of Dallas, revised 27 Mar 2021.
    20. McAdam, Peter & Willman, Alpo, 2011. "Technology, utilization and inflation: what drives the New Keynesian Phillips Curve?," Working Paper Series 1369, European Central Bank.
    21. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    22. Andrew Chia, 2021. "Automatically Differentiable Random Coefficient Logistic Demand Estimation," Papers 2106.04636, arXiv.org.
    23. Todd, Prono, 2009. "Simple, Skewness-Based GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 30994, University Library of Munich, Germany, revised 30 Jul 2011.
    24. Stanislav Anatolyev & Anna Mikusheva, 2018. "Factor models with many assets: strong factors, weak factors, and the two-pass procedure," Papers 1807.04094, arXiv.org, revised Apr 2019.
    25. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP04/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Jungbin Hwang & Byunghoon Kang & Seojeong Lee, 2019. "A Doubly Corrected Robust Variance Estimator for Linear GMM," Discussion Papers 2019-08, School of Economics, The University of New South Wales.
    27. Colacito, Riccardo & Hoffmann, Bridget & Phan, Toan, 2016. "Temperature and Growth: A Panel Analysis of the United States," IDB Publications (Working Papers) 7654, Inter-American Development Bank.
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    69. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    70. Schennach, Susanne & White, Halbert & Chalak, Karim, 2012. "Local indirect least squares and average marginal effects in nonseparable structural systems," Journal of Econometrics, Elsevier, vol. 166(2), pages 282-302.
    71. Andrews, Donald W.K., 2017. "Examples of L2-complete and boundedly-complete distributions," Journal of Econometrics, Elsevier, vol. 199(2), pages 213-220.
    72. Chiappori, Pierre-Andre & Komunjer, Ivana, 2008. "Correct Specification and Identification of Nonparametric Transformation Models," University of California at San Diego, Economics Working Paper Series qt4v12m2rg, Department of Economics, UC San Diego.
    73. Andrew Chesher, 2008. "Instrumental variable models for discrete outcomes," CeMMAP working papers CWP30/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    74. An, Yonghong & Hu, Yingyao & Liu, Pengfei, 2018. "Estimating heterogeneous contributing strategies in threshold public goods provision: A structural analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 124-146.
    75. Kaspar W thrich, 2014. "A Comparison of two Quantile Models with Endogeneity," Diskussionsschriften dp1408, Universitaet Bern, Departement Volkswirtschaft.
    76. Yingying DONG & Ying-Ying LEE & Michael GOU, 2019. "Regression Discontinuity Designs with a Continuous Treatment," Discussion papers 19058, Research Institute of Economy, Trade and Industry (RIETI).
    77. Jin Li & Ye Luo & Xiaowei Zhang, 2021. "Causal Reinforcement Learning: An Instrumental Variable Approach," Papers 2103.04021, arXiv.org, revised Sep 2022.
    78. Liao, Yuan & Jiang, Wenxin, 2011. "Posterior consistency of nonparametric conditional moment restricted models," MPRA Paper 38700, University Library of Munich, Germany.
    79. Fève, Frédérique & Florens, Jean-Pierre, 2014. "Iterative algorithm for non parametric estimation of the instrumental variables quantiles," Economics Letters, Elsevier, vol. 123(3), pages 300-304.
    80. Christos Kollias & Suzanna Maria Paleologou & Panayiotis Tzeremes & Nickolaos Tzeremes, 2018. "The demand for military spending in Latin American countries," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 27(1), pages 1-17, December.
    81. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(4), pages 1010-1043, August.
    82. Pierre-Andre Chiappori & Ivana Komunjer & Dennis Kristensen, 2011. "Nonparametric Identification and Estimation of Transformation Models," CAM Working Papers 2011-01, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    83. Caetano, Carolina & Rothe, Christoph & Yıldız, Neşe, 2016. "A discontinuity test for identification in triangular nonseparable models," Journal of Econometrics, Elsevier, vol. 193(1), pages 113-122.
    84. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    85. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    86. Horowitz, Joel L., 2014. "Adaptive nonparametric instrumental variables estimation: Empirical choice of the regularization parameter," Journal of Econometrics, Elsevier, vol. 180(2), pages 158-173.
    87. Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Apr 2023.
    88. Joachim Freyberger & Joel L. Horowitz, 2013. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers CWP31/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    89. Jinyong Hahn & Geert Ridder, 2011. "Conditional Moment Restrictions and Triangular Simultaneous Equations," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 683-689, May.
    90. Giovanni Forchini, 2014. "A General Result on Observational Equivalence in a Class of Nonparametric Structural Equations Models," School of Economics Discussion Papers 0114, School of Economics, University of Surrey.
    91. Arthur Lewbel, 2018. "The Identification Zoo - Meanings of Identification in Econometrics," Boston College Working Papers in Economics 957, Boston College Department of Economics, revised 14 Dec 2019.
    92. Maximilian Kasy, 2014. "Instrumental Variables with Unrestricted Heterogeneity and Continuous Treatment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(4), pages 1614-1636.
    93. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    94. Halbert White & Karim Chalak, 2008. "Identifying Structural Effects in Nonseparable Systems Using Covariates," Boston College Working Papers in Economics 734, Boston College Department of Economics.
    95. Rothe, Christoph, 2010. "Identification of unconditional partial effects in nonseparable models," Economics Letters, Elsevier, vol. 109(3), pages 171-174, December.

  28. Whitney K. Newey, 2007. "NONPARAMETRIC CONTINUOUS/DISCRETE CHOICE MODELS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1429-1439, November.

    Cited by:

    1. Martin Huber & Giovanni Mellace, 2014. "Testing exclusion restrictions and additive separability in sample selection models," Empirical Economics, Springer, vol. 47(1), pages 75-92, August.
    2. Huber, Martin & Solovyeva, Anna, 2018. "Direct and indirect effects under sample selection and outcome attrition," FSES Working Papers 496, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    3. Escanciano, Juan Carlos & Jacho-Chávez, David T. & Lewbel, Arthur, 2014. "Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 426-443.
    4. Martin Huber, 2012. "Identification of Average Treatment Effects in Social Experiments Under Alternative Forms of Attrition," Journal of Educational and Behavioral Statistics, , vol. 37(3), pages 443-474, June.
    5. Heng Chen & Geoffrey Dunbar & Q. Rallye Shen, 2020. "The Mode is the Message: Using Predata as Exclusion Restrictions to Evaluate Survey Design," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 341-357, Emerald Group Publishing Limited.
    6. Huber, Martin & Solovyeva, Anna, 2018. "On the sensitivity of wage gap decompositions," FSES Working Papers 497, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    7. Mathieu David & Joaquín Alonso-Montesinos & Josselin Le Gal La Salle & Philippe Lauret, 2023. "Probabilistic Solar Forecasts as a Binary Event Using a Sky Camera," Energies, MDPI, vol. 16(20), pages 1-18, October.
    8. Viauroux, Christelle, 2011. "Pricing urban congestion: A structural random utility model with traffic anticipation," European Economic Review, Elsevier, vol. 55(7), pages 877-902.
    9. Iván Fernández‐Val & Aico van Vuuren & Francis Vella & Franco Peracchi, 2023. "Selection and the distribution of female real hourly wages in the United States," Quantitative Economics, Econometric Society, vol. 14(2), pages 571-607, May.
    10. Helmers, Christian & Rogers, Mark, 2011. "Does patenting help high-tech start-ups?," Research Policy, Elsevier, vol. 40(7), pages 1016-1027, September.
    11. Tatsuya Abe, 2022. "Welfare Effects of Fuel Tax and Feebate Policies in the Japanese New Car Market," ISER Discussion Paper 1183, Institute of Social and Economic Research, Osaka University.
    12. Roger Klein & Chan Shen & Francis Vella, 2014. "Semiiparametric Selection Models with Binary Outcomes," Departmental Working Papers 201403, Rutgers University, Department of Economics.
    13. Rothe, Christoph, 2009. "Semiparametric estimation of binary response models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 153(1), pages 51-64, November.
    14. Tatsuya Abe, 2022. "Welfare Effects of Fuel Tax and Feebate Policies in the Japanese New Car Market," Working Papers e172, Tokyo Center for Economic Research.

  29. Jinyong Hahn & Whitney Newey, 2004. "Jackknife and Analytical Bias Reduction for Nonlinear Panel Models," Econometrica, Econometric Society, vol. 72(4), pages 1295-1319, July.
    See citations under working paper version above.
  30. Whitney K. Newey, 2004. "Efficient Semiparametric Estimation via Moment Restrictions," Econometrica, Econometric Society, vol. 72(6), pages 1877-1897, November.

    Cited by:

    1. Kaplan, David M. & Sun, Yixiao, 2012. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," University of California at San Diego, Economics Working Paper Series qt888657tp, Department of Economics, UC San Diego.
    2. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    3. Huybrechts F. Bindele & Ash Abebe & Karlene N. Meyer, 2018. "General rank-based estimation for regression single index models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1115-1146, October.
    4. Chen, Songnian & Zhou, Xianbo, 2012. "Semiparametric estimation of a truncated regression model," Journal of Econometrics, Elsevier, vol. 167(2), pages 297-304.
    5. Manuel Arellano & Stéphane Bonhomme, 2009. "Identifying distributional characteristics in random coefficients panel data models," CeMMAP working papers CWP22/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Yingye Zheng & Tianxi Cai & Ziding Feng, 2006. "Application of the Time-Dependent ROC Curves for Prognostic Accuracy with Multiple Biomarkers," Biometrics, The International Biometric Society, vol. 62(1), pages 279-287, March.
    7. Xiaohong Chen & Jinyong Hahn, 2012. "Asymptotic efficiency of semiparametric two-step GMM," CeMMAP working papers CWP31/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    9. Chunrong Ai & Xiaohong Chen, 2009. "Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," CeMMAP working papers CWP28/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Bustamante, M. Cecilia, 2016. "How Do Frictions Affect Corporate Investment? A Structural Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(6), pages 1863-1895, December.
    11. Hans Fricke & Markus Frölich & Martin Huber & Michael Lechner, 2020. "Endogeneity and non‐response bias in treatment evaluation – nonparametric identification of causal effects by instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 481-504, August.
    12. Donkers, Bas & Schafgans, Marcia M. A., 2005. "A method of moments estimator for semiparametric index models," LSE Research Online Documents on Economics 6815, London School of Economics and Political Science, LSE Library.
    13. Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2012. "Optimal inference for instrumental variables regression with non-Gaussian errors," Journal of Econometrics, Elsevier, vol. 167(1), pages 1-15.
    14. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
    15. Xiaohong Chen & David T. Jacho-Chávez & Oliver Linton, 2009. "An Alternative Way of ComputingEfficient Instrumental VariableEstimators," STICERD - Econometrics Paper Series 536, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    16. Aradillas-López, Andrés, 2021. "Computing semiparametric efficiency bounds in discrete choice models with strategic-interactions and rational expectations," Journal of Econometrics, Elsevier, vol. 221(1), pages 25-42.
    17. Chen, Songnian, 2010. "Root-N-consistent estimation of fixed-effect panel data transformation models with censoring," Journal of Econometrics, Elsevier, vol. 159(1), pages 222-234, November.
    18. Hui Li & Xiaogang Duan & Guosheng Yin, 2016. "Generalized Method of Moments for Additive Hazards Model with Clustered Dental Survival Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1124-1139, December.
    19. Li, Cheng & Jiang, Wenxin, 2016. "On oracle property and asymptotic validity of Bayesian generalized method of moments," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 132-147.
    20. Frumento, Paolo & Bottai, Matteo, 2017. "An estimating equation for censored and truncated quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 53-63.
    21. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
    22. Hristache, Marian & Patilea, Valentin, 2021. "Equivalent models for observables under the assumption of missing at random," Econometrics and Statistics, Elsevier, vol. 20(C), pages 153-165.
    23. Marcelo Moreira, 2008. "A Maximum Likelihood Method for the Incidental Parameter Problem," NBER Working Papers 13787, National Bureau of Economic Research, Inc.

  31. Whitney K. Newey & Fushing Hsieh & James M. Robins, 2004. "Twicing Kernels and a Small Bias Property of Semiparametric Estimators," Econometrica, Econometric Society, vol. 72(3), pages 947-962, May.

    Cited by:

    1. Matias D. Cattaneo & Max H. Farrell & Michael Jansson & Ricardo Masini, 2022. "Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators," Papers 2301.00277, arXiv.org, revised Feb 2024.
    2. Yifei Sun & Chiung-Yu Huang & Mei-Cheng Wang, 2017. "Nonparametric Benefit–Risk Assessment Using Marker Process in the Presence of a Terminal Event," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 826-836, April.
    3. Xiaohong Chen & Demian Pouzo, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," CeMMAP working papers CWP20/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Cattaneo, Matias D & Crump, Richard K & Jansson, Michael, 2014. "Small Bandwidth Asymptotics For Density-Weighted Average Derivatives," Department of Economics, Working Paper Series qt3jd237cg, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    5. Michael Jansson & Demian Pouzo, 2019. "Towards a general large sample theory for regularized estimators," CeMMAP working papers CWP63/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
    7. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    8. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference In Differences," NBER Working Papers 25532, National Bureau of Economic Research, Inc.
    9. Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2010. "Robust Data-Driven Inference for Density-Weighted Average Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1070-1083.
    10. Nilsson, William, 2019. "Estimating nonlinear intergenerational income mobility with correlation curves," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-20.
    11. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    12. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Dec 2017.
    13. Roger Klein & Francis Vella, 2005. "Estimating a class of triangular simultaneous equations models without exclusion restrictions," CeMMAP working papers CWP08/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Ravi Kumar & Shahin Boluki & Karl Isler & Jonas Rauch & Darius Walczak, 2022. "Machine Learning based Framework for Robust Price-Sensitivity Estimation with Application to Airline Pricing," Papers 2205.01875, arXiv.org, revised Dec 2022.
    15. Kotlyarova, Yulia & Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2021. "Rates of expansions for functional estimators," LSE Research Online Documents on Economics 113436, London School of Economics and Political Science, LSE Library.
    16. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    17. S. Darolles & Y. Fan & J. P. Florens & E. Renault, 2011. "Nonparametric Instrumental Regression," Econometrica, Econometric Society, vol. 79(5), pages 1541-1565, September.
    18. Rothe, Christoph & Firpo, Sergio, 2013. "Semiparametric Estimation and Inference Using Doubly Robust Moment Conditions," IZA Discussion Papers 7564, Institute of Labor Economics (IZA).
    19. Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
    20. Matias D. Cattaneo & Michael Jansson, 2014. "Bootstrapping Kernel-Based Semiparametric Estimators," CREATES Research Papers 2014-25, Department of Economics and Business Economics, Aarhus University.
    21. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Apr 2024.
    22. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile Regression with Censoring and Endogeneity," Cowles Foundation Discussion Papers 1797, Cowles Foundation for Research in Economics, Yale University.
    23. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
    24. Dennis Kristensen & Bernard Salanié, 2010. "Higher Order Improvements for Approximate Estimators," CAM Working Papers 2010-04, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    25. Matias Cattaneo & Michael Jansson & Whitney K. Newey, 2015. "Alternative asymptotics and the partially linear model with many regressors," CeMMAP working papers 36/15, Institute for Fiscal Studies.
    26. Sviták, Jan & Tichem, Jan & Haasbeek, Stefan, 2021. "Price effects of search advertising restrictions," International Journal of Industrial Organization, Elsevier, vol. 77(C).
    27. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. Dennis Kristensen, 2004. "Estimation in Two Classes of Semiparametric Diffusion Models," FMG Discussion Papers dp500, Financial Markets Group.
    29. Elia Lapenta, 2022. "A Bootstrap Specification Test for Semiparametric Models with Generated Regressors," Papers 2212.11112, arXiv.org, revised Oct 2023.
    30. Matsushita, Yukitoshi & Otsu, Taisuke, 2020. "Likelihood inference on semiparametric models with generated regressors," LSE Research Online Documents on Economics 102696, London School of Economics and Political Science, LSE Library.
    31. Rahul Singh, 2021. "Debiased Kernel Methods," Papers 2102.11076, arXiv.org, revised Mar 2021.
    32. Klein, Roger & Shen, Chan & Vella, Francis, 2015. "Estimation of marginal effects in semiparametric selection models with binary outcomes," Journal of Econometrics, Elsevier, vol. 185(1), pages 82-94.
    33. Bravo, Francesco & Escanciano, Juan Carlos & Van Keilegom, Ingrid, 2015. "Wilks' Phenomenon in Two-Step Semiparametric Empirical Likelihood Inference," LIDAM Discussion Papers ISBA 2015016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    34. Elia Lapenta & Pascal Lavergne, 2022. "Encompassing Tests for Nonparametric Regressions," Papers 2203.06685, arXiv.org, revised Oct 2023.
    35. Chan Shen & Roger Klein, 2017. "Recursive Differencing: Bias Reduction with Regular Kernels," Departmental Working Papers 201701, Rutgers University, Department of Economics.
    36. Anish Agarwal & Rahul Singh, 2021. "Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy," Papers 2107.02780, arXiv.org, revised Feb 2024.
    37. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
    38. Kristensen, Dennis, 2004. "Estimation of partial differential equations with applications in finance," LSE Research Online Documents on Economics 24738, London School of Economics and Political Science, LSE Library.
    39. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2021. "A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees," Papers 2105.15197, arXiv.org, revised Oct 2022.
    40. Neng-Chieh Chang, 2018. "Semiparametric Difference-in-Differences with Potentially Many Control Variables," Papers 1812.10846, arXiv.org, revised Jan 2019.
    41. Qizhao Chen & Vasilis Syrgkanis & Morgane Austern, 2022. "Debiased Machine Learning without Sample-Splitting for Stable Estimators," Papers 2206.01825, arXiv.org, revised Nov 2022.
    42. Roger Klein & Chan Shen & Francis Vella, 2014. "Semiiparametric Selection Models with Binary Outcomes," Departmental Working Papers 201403, Rutgers University, Department of Economics.
    43. Robins, James M. & Li, Lingling & Tchetgen, Eric Tchetgen & van der Vaart, Aad, 2016. "Asymptotic normality of quadratic estimators," Stochastic Processes and their Applications, Elsevier, vol. 126(12), pages 3733-3759.
    44. Lapenta, Elia & Lavergne, Pascal, 2022. "Encompassing Tests for Nonparametric Regressions," TSE Working Papers 22-1332, Toulouse School of Economics (TSE).
    45. Chan Shen, 2019. "Recursive Differencing for Estimating Semiparametric Models," Departmental Working Papers 201903, Rutgers University, Department of Economics.
    46. Agboola, Oluwagbenga David & Yu, Han, 2023. "Neighborhood-based cross fitting approach to treatment effects with high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 186(C).
    47. Lee, Jiyon, 2015. "A semiparametric single index model with heterogeneous impacts on an unobserved variable," Journal of Econometrics, Elsevier, vol. 184(1), pages 13-36.
    48. Yulia Kotlyarova & Victoria Zinde-Walsh, 2006. "Robust Kernel Estimator For Densities Of Unknown," Departmental Working Papers 2005-05, McGill University, Department of Economics.
    49. David Bruns-Smith & Oliver Dukes & Avi Feller & Elizabeth L. Ogburn, 2023. "Augmented balancing weights as linear regression," Papers 2304.14545, arXiv.org, revised Aug 2023.
    50. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    51. Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects," Papers 2112.14249, arXiv.org, revised Mar 2024.

  32. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    See citations under working paper version above.
  33. Mitali Das & Whitney K. Newey & Francis Vella, 2003. "Nonparametric Estimation of Sample Selection Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(1), pages 33-58.

    Cited by:

    1. Giulia BETTIN & Riccardo LUCCHETTI & Alberto ZAZZARO, 2011. "Endogeneity and sample selection in a model for remittances," Working Papers 361, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    2. Huber, Martin & Melly, Blaise, 2011. "Quantile Regression in the Presence of Sample Selection," Economics Working Paper Series 1109, University of St. Gallen, School of Economics and Political Science.
    3. Langella, Monica & Manning, Alan, 2016. "Diversity and neighbourhood satisfaction," LSE Research Online Documents on Economics 69041, London School of Economics and Political Science, LSE Library.
    4. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    5. Mündler, Marc-Andreas & Becker, Sascha O., 2006. "Margins of multinational labor substitution," Discussion Paper Series 1: Economic Studies 2006,24, Deutsche Bundesbank.
    6. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    7. Martin Huber & Giovanni Mellace, 2015. "Sharp Bounds on Causal Effects under Sample Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 129-151, February.
    8. Cezar, Rafael, 2011. "Newtoning financial development with heterogeneous firms," Conference papers 332064, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    9. Santos Silva, Joao & Tenreyro, Silvana, 2009. "Trading partners and trading volumes: implementing the Helpman-Melitz-Rubinstein model empirically," LSE Research Online Documents on Economics 25505, London School of Economics and Political Science, LSE Library.
    10. Giuseppe Migali & Ian Walker, 2011. "Estimates of the causal effects of education on earnings over the lifecycle with cohort effects and endogenous education," Working Papers 2248796, Lancaster University Management School, Economics Department.
    11. Schwiebert, Jörg, 2012. "Semiparametric Estimation of a Sample Selection Model in the Presence of Endogeneity," Hannover Economic Papers (HEP) dp-504, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    12. Giuseppe De Luca & Franco Peracchi, 2010. "Estimating Engel curves under unit and item nonresponse," EIEF Working Papers Series 1004, Einaudi Institute for Economics and Finance (EIEF), revised Nov 2010.
    13. Teresa D. Harrison & Daniel J. Henderson & Deniz Ozabaci & Christopher A. Laincz, 2023. "Does one size fit all in the non‐profit donation production function?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 373-402, April.
    14. Calomiris, Charles W. & Chen, Sophia, 2022. "The spread of deposit insurance and the global rise in bank asset risk since the 1970s," Journal of Financial Intermediation, Elsevier, vol. 49(C).
    15. Naércio Aquino Menezes Filho & Marc-Andreas Muendler & Garey Ramey, 2006. "The Structure of Worker Compensation in Brazil, with a Comparison to France and the United States," CESifo Working Paper Series 1643, CESifo.
    16. David S. Lee, 2002. "Trimming for Bounds on Treatment Effects with Missing Outcomes," NBER Technical Working Papers 0277, National Bureau of Economic Research, Inc.
    17. D’Haultfœuille, Xavier & Maurel, Arnaud, 2013. "Inference on an extended Roy model, with an application to schooling decisions in France," Journal of Econometrics, Elsevier, vol. 174(2), pages 95-106.
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    159. Lin, Zhongjian & Vella, Francis, 2021. "Selection and Endogenous Treatment Models with Social Interactions: An Application to the Impact of Exercise on Self-Esteem," IZA Discussion Papers 14167, Institute of Labor Economics (IZA).
    160. Kyungchul Song, 2009. "Two-Step Extremum Estimation with Estimated Single-Indices," PIER Working Paper Archive 09-012, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
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    163. Hamermesh, Daniel S. & Donald, Stephen G., 2008. "The effect of college curriculum on earnings: An affinity identifier for non-ignorable non-response bias," Journal of Econometrics, Elsevier, vol. 144(2), pages 479-491, June.
    164. Doyle, Joseph J., 2007. "Can't buy me love? Subsidizing the care of related children," Journal of Public Economics, Elsevier, vol. 91(1-2), pages 281-304, February.
    165. Jaime Ruiz-Tagle & Francis Vella, 2010. "Borrowing Constraints and Credit Demand," Working Papers Central Bank of Chile 578, Central Bank of Chile.
    166. Bailey, Michael & Hopkins, Daniel J. & Rogers, Todd, 2013. "Unresponsive and Unpersuaded: The Unintended Consequences of Voter Persuasion Efforts," Working Paper Series rwp13-034, Harvard University, John F. Kennedy School of Government.
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    Cited by:

    1. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers 14/17, Institute for Fiscal Studies.
    2. Senay Sokullu, 2012. "Nonparametric Estimation of Semiparametric Transformation Models," Bristol Economics Discussion Papers 12/625, School of Economics, University of Bristol, UK.
    3. Huber, Martin & Melly, Blaise, 2011. "Quantile Regression in the Presence of Sample Selection," Economics Working Paper Series 1109, University of St. Gallen, School of Economics and Political Science.
    4. Maican, Florin & Orth, Matilda, 2008. "Productivity Dynamics and the Role of “Big-Box” Entrants in Retailing," Working Papers in Economics 328, University of Gothenburg, Department of Economics.
    5. Yevgeniy Kovchegov & Nese Yildiz, 2014. "Orthogonal Polynomials for Seminonparametric Instrumental Variables Model," Papers 1409.1620, arXiv.org.
    6. Cui, Liyuan & Hong, Yongmiao & Li, Yingxing, 2021. "Solving Euler equations via two-stage nonparametric penalized splines," Journal of Econometrics, Elsevier, vol. 222(2), pages 1024-1056.
    7. Fève, Frédérique & Florens, Jean-Pierre, 2014. "Non parametric analysis of panel data models with endogenous variables," Journal of Econometrics, Elsevier, vol. 181(2), pages 151-164.
    8. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    9. Horowitz, Joel L. & Lee, Sokbae, 2009. "Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative," Journal of Econometrics, Elsevier, vol. 152(2), pages 141-152, October.
    10. Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2022. "Nonparametric Identification of Random Coefficients in Endogenous and Heterogeneous Aggregate Demand Models," Papers 2201.06140, arXiv.org.
    11. Susanne Schennach & James Heckman & Flavio Cunha, 2007. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," 2007 Meeting Papers 973, Society for Economic Dynamics.
    12. Xiaohong Chen & Demian Pouzo, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," CeMMAP working papers CWP20/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Daniel Wilhelm & Denis Chetverikov & Dongwoo Kim, 2017. "Nonparametric instrumental variable estimation," CeMMAP working papers CWP47/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Gayle, Wayne-Roy, 2013. "Identification and N-consistent estimation of a nonlinear panel data model with correlated unobserved effects," Journal of Econometrics, Elsevier, vol. 175(2), pages 71-83.
    15. Joel L. Horowitz & Sokbae (Simon) Lee, 2010. "Uniform confidence bands for functions estimated nonparametrically with instrumental variables," CeMMAP working papers CWP19/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Dunker, Fabian & Hoderlein, Stefan & Kaido, Hiroaki, 2014. "Nonparametric Identification of Endogenous and Heterogeneous Aggregate Demand Models: Complements, Bundles and the Market Level," Economics Series 307, Institute for Advanced Studies.
    17. Christoph Breunig, 2018. "Varying Random Coefficient Models," Papers 1804.03110, arXiv.org, revised Aug 2020.
    18. Tatiana V. Komarova, 2013. "Extremum sieve estimation in k -out-of- n systems," CeMMAP working papers 47/13, Institute for Fiscal Studies.
    19. Ai, Chunrong & Chen, Xiaohong, 2007. "Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables," Journal of Econometrics, Elsevier, vol. 141(1), pages 5-43, November.
    20. Michael Jansson & Demian Pouzo, 2019. "Towards a general large sample theory for regularized estimators," CeMMAP working papers CWP63/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2018.
    22. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    23. Dubois, Pierre & Nauges, Celine, 2007. "Identifying the Effect of Unobserved Quality and Expert Reviews in the Pricing of Experience Goods: Empirical Application on Bordeaux Wine," Working Papers 37320, American Association of Wine Economists.
    24. Bruneel-Zupanc, Christophe Alain, 2021. "Discrete-Continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation," TSE Working Papers 21-1185, Toulouse School of Economics (TSE).
    25. Andrew Chesher, 2003. "Nonparametric identification under discrete variation," CeMMAP working papers CWP19/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Zheng Fang & Juwon Seo, 2021. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Econometrica, Econometric Society, vol. 89(5), pages 2439-2458, September.
    27. Antonio Merlo & Áureo de Paula, 2015. "Identification and estimation of preference distributions when voters are ideological," CeMMAP working papers CWP50/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. Markus Frölich, 2008. "Parametric and Nonparametric Regression in the Presence of Endogenous Control Variables," International Statistical Review, International Statistical Institute, vol. 76(2), pages 214-227, August.
    29. Rodrigo Adao & Arnaud Costinot & Dave Donaldson, 2017. "Nonparametric Counterfactual Predictions in Neoclassical Models of International Trade," American Economic Review, American Economic Association, vol. 107(3), pages 633-689, March.
    30. Yevgeniy Kovchegov & Nese Yildiz, 2012. "Identification via completeness for discrete covariates and orthogonal polynomials," Koç University-TUSIAD Economic Research Forum Working Papers 1203, Koc University-TUSIAD Economic Research Forum.
    31. Yonghong An & Yingyao Hu, 2009. "Well-posedness of measurement error models for self-reported data," CeMMAP working papers CWP35/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    32. Babii, Andrii & Florens, Jean-Pierre, 2020. "Is completeness necessary? Estimation in nonidentified linear models," TSE Working Papers 20-1091, Toulouse School of Economics (TSE).
    33. Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," CeMMAP working papers CWP13/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    34. Battistin, Erich & De Nadai, Michele & Krishnan, Nandini, 2020. "The Insights and Illusions of Consumption Measurements," IZA Discussion Papers 13222, Institute of Labor Economics (IZA).
    35. Babii, Andrii, 2020. "Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models," Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
    36. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    37. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.
    38. Richard Blundell & Joel Horowitz & Matthias Parey, 2022. "Estimation of a Heterogeneous Demand Function with Berkson Errors," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 877-889, December.
    39. Laurent Davezies & Thomas Le Barbanchon, 2014. "Regression Discontinuity Design with Continuous Measurement Error in the Running Variable," Working Papers 2014-27, Center for Research in Economics and Statistics.
    40. Riccardo Della Vecchia & Debabrota Basu, 2023. "Online Instrumental Variable Regression: Regret Analysis and Bandit Feedback," Working Papers hal-03831210, HAL.
    41. Dominick Bartelme & Arnaud Costinot & Dave Donaldson & Andres Rodriguez-Clare, "undated". "The Textbook Case for Industrial Policy: Theory Meets Data," Working Papers 675, Research Seminar in International Economics, University of Michigan.
    42. Xiaohong Chen & Demian Pouzo, 2012. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Econometrica, Econometric Society, vol. 80(1), pages 277-321, January.
    43. James J. Heckman & Rodrigo Pinto, 2013. "Causal Analysis after Haavelmo," Working Papers 2013-008, Human Capital and Economic Opportunity Working Group.
    44. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2019. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," NBER Working Papers 25827, National Bureau of Economic Research, Inc.
    45. Daniel P. Miller, 2014. "Subcontracting and competitive bidding on incomplete procurement contracts," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 705-746, December.
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    47. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    48. Xiaohong Chen & Timothy Christensen, 2013. "Optimal Uniform Convergence Rates for Sieve Nonparametric Instrumental Variables Regression," Papers 1311.0412, arXiv.org.
    49. Yu Zhu, 2020. "Inference in nonparametric/semiparametric moment equality models with shape restrictions," Quantitative Economics, Econometric Society, vol. 11(2), pages 609-636, May.
    50. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    51. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    52. Dalderop, Jeroen, 2023. "Semiparametric estimation of latent variable asset pricing models," Journal of Econometrics, Elsevier, vol. 236(1).
    53. Areosa, Waldyr Dutra & McAleer, Michael & Medeiros, Marcelo C., 2011. "Moment-based estimation of smooth transition regression models with endogenous variables," Journal of Econometrics, Elsevier, vol. 165(1), pages 100-111.
    54. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    55. Richard Blundell & Joel L. Horowitz, 2004. "A nonparametric test of exogeneity," CeMMAP working papers CWP15/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    56. Xiaohong Chen & Victor Chernozhukov & Sokbae (Simon) Lee & Whitney K. Newey, 2011. "Local identification of nonparametric and semiparametric models," CeMMAP working papers 17/11, Institute for Fiscal Studies.
    57. Chen, Qihui, 2021. "Robust and optimal estimation for partially linear instrumental variables models with partial identification," Journal of Econometrics, Elsevier, vol. 221(2), pages 368-380.
    58. Santiago Pereda Fernández, 2019. "Identification and estimation of triangular models with a binary treatment," Temi di discussione (Economic working papers) 1210, Bank of Italy, Economic Research and International Relations Area.
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    63. Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Papers 1411.1144, arXiv.org, revised Mar 2015.
    64. Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Mar 2021.
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    76. Cohen, Michael & Shaw, Philip & Chen, Tao, 2008. "Nonparametric Instrumental Variable Estimation in Practice," Research Reports 149936, University of Connecticut, Food Marketing Policy Center.
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    97. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.
    98. Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," CeMMAP working papers 38/14, Institute for Fiscal Studies.
    99. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.
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    107. Victor Chernozhukov & Christian Hansen, 2013. "Quantile models with endogeneity," CeMMAP working papers CWP25/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    108. Senay Sokullu, 2012. "Nonparametric Analysis of Two-Sided Markets," Bristol Economics Discussion Papers 12/628, School of Economics, University of Bristol, UK.
    109. Hong, Shengjie, 2017. "Inference in semiparametric conditional moment models with partial identification," Journal of Econometrics, Elsevier, vol. 196(1), pages 156-179.
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    111. Yingyao Hu & Arthur Lewbel, 2008. "Identifying the returns to lying when the truth is unobserved," CeMMAP working papers CWP06/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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    116. Guohua Feng & Jiti Gao & Bin Peng & Xiaohui Zhang, 2015. "A Varying-Coefficient Panel Data Model with Fixed Effects: Theory and an Application to U.S. Commercial Banks," Monash Econometrics and Business Statistics Working Papers 9/15, Monash University, Department of Econometrics and Business Statistics.
    117. Chaohua Dong & Jiti Gao, 2014. "Specification Testing in Structural Nonparametric Cointegration," Monash Econometrics and Business Statistics Working Papers 2/14, Monash University, Department of Econometrics and Business Statistics.
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    63. Zhipeng Liao & Xiaoxia Shi, 2020. "A nondegenerate Vuong test and post selection confidence intervals for semi/nonparametric models," Quantitative Economics, Econometric Society, vol. 11(3), pages 983-1017, July.
    64. Pierre Chausse & George Luta, 2017. "Casual Inference using Generalized Empirical Likelihood Methods," Working Papers 1707, University of Waterloo, Department of Economics, revised Dec 2017.
    65. Krikamol Muandet & Wittawat Jitkrittum & Jonas Kubler, 2020. "Kernel Conditional Moment Test via Maximum Moment Restriction," Papers 2002.09225, arXiv.org, revised Jun 2020.
    66. Ying Sheng & Yifei Sun & Chiung‐Yu Huang & Mi‐Ok Kim, 2022. "Synthesizing external aggregated information in the presence of population heterogeneity: A penalized empirical likelihood approach," Biometrics, The International Biometric Society, vol. 78(2), pages 679-690, June.
    67. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
    68. Pascal Lavergne & Valentin Patilea, 2006. "Breaking the Curse of Dimensionality in Nonparametric Testing," Working Papers 2006-24, Center for Research in Economics and Statistics.
    69. Lu, Zhentong & Shi, Xiaoxia & Tao, Jing, 2023. "Semi-nonparametric estimation of random coefficients logit model for aggregate demand," Journal of Econometrics, Elsevier, vol. 235(2), pages 2245-2265.
    70. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2009. "Choosing instrumental variables in conditional moment restriction models," Journal of Econometrics, Elsevier, vol. 152(1), pages 28-36, September.
    71. Fan, Jianqing & Liao, Yuan, 2012. "Endogeneity in ultrahigh dimension," MPRA Paper 38698, University Library of Munich, Germany.
    72. Marine Carrasco & Mohamed Doukali, 2022. "Testing overidentifying restrictions with many instruments and heteroscedasticity using regularised jackknife IV [Specification testing in models with many instruments]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 71-97.
    73. Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021. "Efficient Estimation in NPIV Models: A Comparison of Various Neural Networks-Based Estimators," Papers 2110.06763, arXiv.org, revised Oct 2022.
    74. Yoonseok Lee & Ryo Okui, 2009. "A Specification Test for Instrumental Variables Regression with Many Instruments," Cowles Foundation Discussion Papers 1741, Cowles Foundation for Research in Economics, Yale University.
    75. Dovonon, Prosper, 2008. "Large sample properties of the three-step euclidean likelihood estimators under model misspecification," MPRA Paper 40025, University Library of Munich, Germany, revised 16 May 2010.
    76. Xiaohong Chen & David Jacho-Chávez & Oliver Linton, 2012. "Averaging of moment condition estimators," CeMMAP working papers CWP26/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    77. Ivan Korolev, 2018. "A Consistent Heteroskedasticity Robust LM Type Specification Test for Semiparametric Models," Papers 1810.07620, arXiv.org, revised Nov 2019.
    78. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2018. "Rate Optimal Specification Test When the Number of Instruments is Large," KIER Working Papers 986, Kyoto University, Institute of Economic Research.
    79. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    80. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.
    81. Richard Smith, 2005. "Local GEL methods for conditional moment restrictions," CeMMAP working papers CWP15/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    82. Demian Pouzo, 2014. "Bootstrap Consistency for Quadratic Forms of Sample Averages with Increasing Dimension," Papers 1411.2701, arXiv.org, revised Aug 2015.
    83. Nishihat, Masaya & Otsu, Taisuke, 2020. "Conditional GMM estimation for gravity models," LSE Research Online Documents on Economics 105083, London School of Economics and Political Science, LSE Library.
    84. Lewbel, Arthur, 2007. "A local generalized method of moments estimator," Economics Letters, Elsevier, vol. 94(1), pages 124-128, January.
    85. Ivan Korolev, 2019. "A Consistent LM Type Specification Test for Semiparametric Panel Data Models," Papers 1909.05649, arXiv.org.
    86. Gupta, A, 2015. "Nonparametric specification testing via the trinity of tests," Economics Discussion Papers 23824, University of Essex, Department of Economics.
    87. Jin, Fei & Lee, Lung-fei, 2019. "GEL estimation and tests of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 208(2), pages 585-612.
    88. Joel L. Horowitz, 2004. "Testing a parametric model against a nonparametric alternative with identification through instrumental variables," CeMMAP working papers 14/04, Institute for Fiscal Studies.
    89. Matthew Backus & Christopher Conlon & Michael Sinkinson, 2021. "Common Ownership and Competition in the Ready-to-Eat Cereal Industry," NBER Working Papers 28350, National Bureau of Economic Research, Inc.
    90. Paulo Parente & Richard Smith, 2012. "Exogeneity in semiparametric moment condition models," CeMMAP working papers 30/12, Institute for Fiscal Studies.
    91. Stefan Boes, 2007. "Count Data Models with Unobserved Heterogeneity: An Empirical Likelihood Approach," SOI - Working Papers 0704, Socioeconomic Institute - University of Zurich.

  36. Brian Boyer & James McDonald & Whitney Newey, 2003. "A Comparison of Partially Adaptive and Reweighted Least Squares Estimation," Econometric Reviews, Taylor & Francis Journals, vol. 22(2), pages 115-134.

    Cited by:

    1. Usta, Ilhan & Kantar, Yeliz Mert, 2011. "On the performance of the flexible maximum entropy distributions within partially adaptive estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2172-2182, June.
    2. Steven Caudill & James Long, 2010. "Do former athletes make better managers? Evidence from a partially adaptive grouped-data regression model," Empirical Economics, Springer, vol. 39(1), pages 275-290, August.
    3. James B. McDonald & Richard A. Michelfelder & Panayiotis Theodossiou, 2009. "Robust Regression Estimation Methods and Intercept Bias: A Capital Asset Pricing Model Application," Multinational Finance Journal, Multinational Finance Journal, vol. 13(3-4), pages 293-321, September.
    4. James Mcdonald & Richard Michelfelder & Panayiotis Theodossiou, 2010. "Robust estimation with flexible parametric distributions: estimation of utility stock betas," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 375-387.
    5. Hansen, James V. & McDonald, James B. & Turley, Robert S., 2006. "Partially adaptive robust estimation of regression models and applications," European Journal of Operational Research, Elsevier, vol. 170(1), pages 132-143, April.

  37. Soren Blomquist & Whitney Newey, 2002. "Nonparametric Estimation with Nonlinear Budget Sets," Econometrica, Econometric Society, vol. 70(6), pages 2455-2480, November.
    See citations under working paper version above.
  38. Brown, Bryan W & Newey, Whitney K, 2002. "Generalized Method of Moments, Efficient Bootstrapping, and Improved Inference," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 507-517, October.

    Cited by:

    1. Seojeong Lee, 2014. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for GEL Estimators," Discussion Papers 2014-02, School of Economics, The University of New South Wales.
    2. Ming‐Yueh Huang & Chiung‐Yu Huang, 2023. "Improved semiparametric estimation of the proportional rate model with recurrent event data," Biometrics, The International Biometric Society, vol. 79(3), pages 1686-1700, September.
    3. Arvanitis, Stelios & Post, Thierry & Potì, Valerio & Karabati, Selcuk, 2021. "Nonparametric tests for Optimal Predictive Ability," International Journal of Forecasting, Elsevier, vol. 37(2), pages 881-898.
    4. Marcel Schroder, 2013. "Should developing countries undervalue their currencies?," Departmental Working Papers 2013-12, The Australian National University, Arndt-Corden Department of Economics.
    5. Jason Allen & Allan Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Staff Working Papers 08-18, Bank of Canada.
    6. João Madeira & Nuno Palma, 2018. "Measuring Monetary Policy Deviations from the Taylor Rule," Economics Discussion Paper Series 1803, Economics, The University of Manchester.
    7. Todd, Prono, 2009. "Simple, Skewness-Based GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 30994, University Library of Munich, Germany, revised 30 Jul 2011.
    8. Davide La Vecchia & Alban Moor & O. Scaillet, 2020. "A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data," Swiss Finance Institute Research Paper Series 20-01, Swiss Finance Institute.
    9. Russell Davidson & Jean-Yves Duclos, 2006. "Testing for Restricted Stochastic Dominance," Cahiers de recherche 0609, CIRPEE.
    10. Wang, Xuexin, 2016. "A New Class of Tests for Overidentifying Restrictions in Moment Condition Models," MPRA Paper 69004, University Library of Munich, Germany.
    11. Giuseppe Ragusa, 2007. "Bayesian Likelihoods for Moment Condition Models," Working Papers 060714, University of California-Irvine, Department of Economics.
    12. Parente, Paulo M.D.C. & Smith, Richard J., 2011. "Gel Methods For Nonsmooth Moment Indicators," Econometric Theory, Cambridge University Press, vol. 27(1), pages 74-113, February.
    13. Matias D. Cattaneo & Michael Jansson, 2014. "Bootstrapping Kernel-Based Semiparametric Estimators," CREATES Research Papers 2014-25, Department of Economics and Business Economics, Aarhus University.
    14. Chen, Song Xi & Cui, Hengjian, 2007. "On the second-order properties of empirical likelihood with moment restrictions," Journal of Econometrics, Elsevier, vol. 141(2), pages 492-516, December.
    15. Dovonon, Prosper & Gonçalves, Sílvia, 2017. "Bootstrapping the GMM overidentification test under first-order underidentification," Journal of Econometrics, Elsevier, vol. 201(1), pages 43-71.
    16. Pedro Portugal & João Ejarque, 2007. "Labor Adjustment Costs in a Panel of Establishments: A Structural Approach," Working Papers w200716, Banco de Portugal, Economics and Research Department.
    17. Giuseppe Ragusa, 2011. "Minimum Divergence, Generalized Empirical Likelihoods, and Higher Order Expansions," Econometric Reviews, Taylor & Francis Journals, vol. 30(4), pages 406-456, August.
    18. Almeida, Caio & Garcia, René, 2012. "Assessing misspecified asset pricing models with empirical likelihood estimators," Journal of Econometrics, Elsevier, vol. 170(2), pages 519-537.
    19. Camponovo, Lorenzo & Otsu, Taisuke, 2015. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 60185, London School of Economics and Political Science, LSE Library.
    20. Wong, Heung & Liu, Feng & Chen, Min & Ip, Wai Cheung, 2009. "Empirical likelihood based diagnostics for heteroscedasticity in partial linear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3466-3477, July.
    21. Joshua Angrist & Ivan Fernandez-Val, 2010. "ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework," NBER Working Papers 16566, National Bureau of Economic Research, Inc.
    22. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    23. Matias D. Cattaneo & Michael Jansson, 2018. "Kernel†Based Semiparametric Estimators: Small Bandwidth Asymptotics and Bootstrap Consistency," Econometrica, Econometric Society, vol. 86(3), pages 955-995, May.
    24. Yuichi Kitamura, 2020. "A Comment on: “On the Informativeness of Descriptive Statistics for Structural Estimates” by Isaiah Andrews, Matthew Gentzkow, and Jesse M. Shapiro," Econometrica, Econometric Society, vol. 88(6), pages 2265-2269, November.
    25. Nicky L. Grant & Richard J. Smith, 2018. "GEL-based inference with unconditional moment inequality restrictions," CeMMAP working papers 23/18, Institute for Fiscal Studies.
    26. Hahn, Jinyong & Newey, Whitney K. & Smith, Richard J., 2014. "Neglected heterogeneity in moment condition models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 86-100.
    27. Yamagata, Takashi, 2008. "A joint serial correlation test for linear panel data models," Journal of Econometrics, Elsevier, vol. 146(1), pages 135-145, September.
    28. Richard Smith, 2004. "GEL Criteria for Moment Condition Models," CeMMAP working papers CWP19/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Richard Smith, 2005. "Efficient information theoretic inference for conditional moment restrictions," CeMMAP working papers CWP14/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Martyn Andrews & Obbey Elamin & Alastair R. Hall & Kostas Kyriakoulis & Matthew Sutton, 2014. "Inference in the Presence of Redundant Moment Conditions and the Impact of Government Health Expenditure on Health Outcomes in England," Economics Discussion Paper Series 1401, Economics, The University of Manchester.
    31. Russell Davidson, 2010. "Innis Lecture: Inference on income distributions," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 43(4), pages 1122-1148, November.
    32. Guggenberger, Patrik & Ramalho, Joaquim J.S. & Smith, Richard J., 2012. "GEL statistics under weak identification," Journal of Econometrics, Elsevier, vol. 170(2), pages 331-349.
    33. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    34. Rulon D. Pope & Jeffrey T. LaFrance & Richard E. Just, 2007. "Imperfect Price Deflation in Production Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(3), pages 738-754.
    35. Giurcanu, Mihai C., 2012. "Bootstrapping in non-regular smooth function models," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 78-93.
    36. Chen, Ruxin & Tabri, Rami V., 2019. "Jackknife Empirical Likelihood for Inequality Constraints on Regular Functionals," Working Papers 2019-07, University of Sydney, School of Economics, revised Sep 2019.
    37. Seojeong Lee, 2015. "A Consistent Variance Estimator for 2SLS When Instruments Identify Different LATEs," Discussion Papers 2015-01, School of Economics, The University of New South Wales.
    38. Todd, Prono, 2010. "Simple GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 20034, University Library of Munich, Germany.
    39. Martyn Andrews & Obbey Elamin & Alastair R. Hall & Kostas Kyriakoulis & Matthew Sutton, 2017. "Inference in the presence of redundant moment conditions and the impact of government health expenditure on health outcomes in England," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 23-41, March.
    40. Saraswata Chaudhuri & Eric Renault, 2015. "Shrinkage of Variance for Minimum Distance Based Tests," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 328-351, March.
    41. Seojeong Lee, 2013. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Method of Moments Estimators," Discussion Papers 2013-09, School of Economics, The University of New South Wales.
    42. Jing Cheng & Dylan S. Small, 2021. "Semiparametric models and inference for the effect of a treatment when the outcome is nonnegative with clumping at zero," Biometrics, The International Biometric Society, vol. 77(4), pages 1187-1201, December.
    43. Susanne M. Schennach, 2007. "Point estimation with exponentially tilted empirical likelihood," Papers 0708.1874, arXiv.org.
    44. Francesco Bravo & Federico Crudu, 2012. "Efficient bootstrap with weakly dependent processes," Discussion Papers 12/08, Department of Economics, University of York.
    45. Mihai Giurcanu & Brett Presnell, 2018. "Bootstrap inference for misspecified moment condition models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(3), pages 605-630, June.
    46. Schröder, Marcel, 2013. "Should developing countries undervalue their currencies?," Journal of Development Economics, Elsevier, vol. 105(C), pages 140-151.
    47. Nicky L. Grant & Richard J. Smith, 2018. "GEL-based inference with unconditional moment inequality restrictions," CeMMAP working papers CWP23/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    48. Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021. "Efficient Estimation in NPIV Models: A Comparison of Various Neural Networks-Based Estimators," Papers 2110.06763, arXiv.org, revised Oct 2022.
    49. Russell Davidson, 2007. "Bootstrapping econometric models (in Russian)," Quantile, Quantile, issue 3, pages 13-36, September.
    50. Gad Allon & Awi Federgruen & Margaret Pierson, 2011. "How Much Is a Reduction of Your Customers' Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods," Manufacturing & Service Operations Management, INFORMS, vol. 13(4), pages 489-507, October.
    51. Jungbin Hwang & Gonzalo Valdés, 2020. "Finite-sample Corrected Inference for Two-step GMM in Time Series," Working papers 2020-02, University of Connecticut, Department of Economics.
    52. Dovonon, Prosper, 2008. "Large sample properties of the three-step euclidean likelihood estimators under model misspecification," MPRA Paper 40025, University Library of Munich, Germany, revised 16 May 2010.
    53. Stanislav Anatolyev, 2007. "The basics of bootstrapping (in Russian)," Quantile, Quantile, issue 3, pages 1-12, September.
    54. Ramalho, Joaquim J.S., 2006. "Bootstrap bias-adjusted GMM estimators," Economics Letters, Elsevier, vol. 92(1), pages 149-155, July.
    55. Richard Smith, 2005. "Local GEL methods for conditional moment restrictions," CeMMAP working papers CWP15/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    56. Firmin Doko Tchatoka & Robert Garrard & Virginie Masson, 2017. "Testing for Stochastic Dominance in Social Networks," School of Economics and Public Policy Working Papers 2017-02, University of Adelaide, School of Economics and Public Policy.
    57. Verma Vivek & Nath Dilip C., 2019. "Characterization Of The Sum Of Binomial Random Variables Under Ranked Set Sampling," Statistics in Transition New Series, Polish Statistical Association, vol. 20(3), pages 1-29, September.
    58. Joachim Inkmann, 2010. "Estimating Firm Size Elasticities of Product and Process R&D," Economica, London School of Economics and Political Science, vol. 77(306), pages 384-402, April.
    59. Canay, Ivan A., 2010. "Simultaneous selection and weighting of moments in GMM using a trapezoidal kernel," Journal of Econometrics, Elsevier, vol. 156(2), pages 284-303, June.
    60. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
    61. Paulo M.D.C. Parente & Richard J. Smith, 2018. "Generalised Empirical Likelihood Kernel Block Bootstrapping," Working Papers REM 2018/55, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    62. Nicky L. Grant & Richard J. Smith, 2018. "GEL-Based Inference from Unconditional Moment Inequality Restrictions," Economics Discussion Paper Series 1802, Economics, The University of Manchester.
    63. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2018. "Portfolio optimization based on stochastic dominance and empirical likelihood," Journal of Econometrics, Elsevier, vol. 206(1), pages 167-186.
    64. Canay, Ivan A., 2010. "EL inference for partially identified models: Large deviations optimality and bootstrap validity," Journal of Econometrics, Elsevier, vol. 156(2), pages 408-425, June.
    65. Ramalho Joaquim J.S., 2005. "Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-20, March.
    66. Tabri, Rami V., 2015. "Empirical Likelihood for Robust Poverty Comparisons," Working Papers 2015-02, University of Sydney, School of Economics, revised May 2015.
    67. Tenglong Li & Jordan Lawson, 2021. "A generalized bootstrap procedure of the standard error and confidence interval estimation for inverse probability of treatment weighting," Papers 2109.00171, arXiv.org.
    68. Hwang, Jungbin & Valdés, Gonzalo, 2023. "Finite-sample corrected inference for two-step GMM in time series," Journal of Econometrics, Elsevier, vol. 234(1), pages 327-352.
    69. Mihai C. Giurcanu, 2017. "Oracle M-Estimation for Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 479-504, May.
    70. Chen, Ruxin & Tabri, Rami V., 2021. "Jackknife empirical likelihood for inequality constraints on regular functionals," Journal of Econometrics, Elsevier, vol. 221(1), pages 68-77.

  39. Blomquist, Soren & Eklof, Matias & Newey, Whitney, 2001. "Tax reform evaluation using non-parametric methods: Sweden 1980-1991," Journal of Public Economics, Elsevier, vol. 79(3), pages 543-568, March.
    See citations under working paper version above.
  40. Newey, Whitney K., 2001. "Conditional Moment Restrictions In Censored And Truncated Regression Models," Econometric Theory, Cambridge University Press, vol. 17(5), pages 863-888, October.
    See citations under working paper version above.
  41. Whitney K. Newey, 2001. "Flexible Simulated Moment Estimation Of Nonlinear Errors-In-Variables Models," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 616-627, November.
    See citations under working paper version above.
  42. Donald, Stephen G & Newey, Whitney K, 2001. "Choosing the Number of Instruments," Econometrica, Econometric Society, vol. 69(5), pages 1161-1191, September.
    See citations under working paper version above.
  43. Donald, Stephen G. & Newey, Whitney K., 2000. "A jackknife interpretation of the continuous updating estimator," Economics Letters, Elsevier, vol. 67(3), pages 239-243, June.

    Cited by:

    1. Favero, Carlo A. & Consolo, Agostino, 2009. "Monetary Policy Inertia: More a Fiction than a fact?," CEPR Discussion Papers 7341, C.E.P.R. Discussion Papers.
    2. Patrik Guggenberger, 2005. "Monte-carlo evidence suggesting a no moment problem of the continuous updating estimator," Economics Bulletin, AccessEcon, vol. 3(13), pages 1-6.
    3. Richard A. Ashley & Xiaojin Sun, 2016. "Subset-Continuous-Updating GMM Estimators for Dynamic Panel Data Models," Econometrics, MDPI, vol. 4(4), pages 1-13, November.
    4. Whitney K. Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    6. Andrew Chia, 2021. "Automatically Differentiable Random Coefficient Logistic Demand Estimation," Papers 2106.04636, arXiv.org.
    7. Todd, Prono, 2009. "Simple, Skewness-Based GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 30994, University Library of Munich, Germany, revised 30 Jul 2011.
    8. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    9. Fan, Yanqin & Gentry, Matthew & Li, Tong, 2011. "A new class of asymptotically efficient estimators for moment condition models," Journal of Econometrics, Elsevier, vol. 162(2), pages 268-277, June.
    10. Frank Kleibergen, 2004. "Expansions of GMM statistics that indicate their properties under weak and/or many instruments and the bootstrap," Econometric Society 2004 North American Summer Meetings 408, Econometric Society.
    11. Hausman, Jerry & Lewis, Randall & Menzel, Konrad & Newey, Whitney, 2011. "Properties of the CUE estimator and a modification with moments," Journal of Econometrics, Elsevier, vol. 165(1), pages 45-57.
    12. Nikolay Gospodinov & Taisuke Otsu, 2008. "Local GMM Estimation of Time Series Models with Conditional Moment Restrictions," Working Papers 08010, Concordia University, Department of Economics.
    13. Michael Creel & Dennis Kristensen, "undated". "Indirect Likelihood Inference," Working Papers 558, Barcelona School of Economics.
    14. Bekker, Paul A. & Crudu, Federico, 2012. "Symmetric Jackknife Instrumental Variable Estimation," MPRA Paper 37853, University Library of Munich, Germany.
    15. Hertrich, Markus & Nathan, Daniel, 2022. "Foreign exchange interventions and their impact on expectations: Evidence from the USD/ILS options market," Discussion Papers 20/2022, Deutsche Bundesbank.
    16. Joaquim Ramalho, 2003. "Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables," Economics Working Papers 9_2003, University of Évora, Department of Economics (Portugal).
    17. Alastair R. Hall, 2013. "Generalized Method of Moments," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 14, pages 313-333, Edward Elgar Publishing.
    18. Tom Boot & Johannes W. Ligtenberg, 2023. "Identification- and many instrument-robust inference via invariant moment conditions," Papers 2303.07822, arXiv.org, revised Sep 2023.
    19. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.
    20. Joachim Inkmann, 2010. "Estimating Firm Size Elasticities of Product and Process R&D," Economica, London School of Economics and Political Science, vol. 77(306), pages 384-402, April.
    21. Prosper Donovon & Alastair R. Hall, 2015. "GMM and Indirect Inference: An appraisal of their connections and new results on their properties under second order identification," Economics Discussion Paper Series 1505, Economics, The University of Manchester.
    22. Hwang, Jungbin & Valdés, Gonzalo, 2023. "Finite-sample corrected inference for two-step GMM in time series," Journal of Econometrics, Elsevier, vol. 234(1), pages 327-352.

  44. Whitney K. Newey & James L. Powell & Francis Vella, 1999. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Econometrica, Econometric Society, vol. 67(3), pages 565-604, May.
    See citations under working paper version above.
  45. Newey, Whitney K., 1999. "Consistency of two-step sample selection estimators despite misspecification of distribution," Economics Letters, Elsevier, vol. 63(2), pages 129-132, May.

    Cited by:

    1. Astrid Grasdal, 2001. "The performance of sample selection estimators to control for attrition bias," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 385-398, July.
    2. Gerlach, Knut & Hübler, Olaf, 2008. "Employment Adjustments on the Internal and External Labour Market: An Empirical Study with Personnel Records of a German Company," ZEW Discussion Papers 08-133, ZEW - Leibniz Centre for European Economic Research.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    5. Nicolai Fink Simonsen & Anne Sophie Oxholm & Søren Rud Kristensen & Luigi Siciliani, 2020. "What explains differences in waiting times for health care across socioeconomic status?," Health Economics, John Wiley & Sons, Ltd., vol. 29(12), pages 1764-1785, December.
    6. Ken Yamada, 2009. "Labor Supply Responses to the 1990s Japanese Tax Reforms," Working Papers 12-2009, Singapore Management University, School of Economics.
    7. Domenico Depalo & Santiago Pereda-Fernández, 2020. "Consistent estimates of the public/private wage gap," Empirical Economics, Springer, vol. 58(6), pages 2937-2947, June.
    8. Fernández-Sainz, Ana I. & Rodríguez-Póo, Juan M., 2010. "An Empirical Investigation of Parametric and Semiparametric Estimation Methods in Sample Selection Models = Investigación empírica de métodos de estimación paramétricos y semiparamétricos de modelos d," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 10(1), pages 99-120, December.
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    22. Miguel Santolino & Catalina Bolancé & Manuela Alcañiz, 2011. "Factors affecting hospital admission and recovery stay duration of in-patient motor victims in Spain," IREA Working Papers 201119, University of Barcelona, Research Institute of Applied Economics, revised Oct 2011.
    23. Denis Y. Orlov & Evgeniy M. Ozhegov, 2016. "Do sequel movies really earn more than non-sequels? Evidence from the US box office," ACEI Working Paper Series AWP-03-2016, Association for Cultural Economics International, revised Apr 2016.
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    1. Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," CeMMAP working papers CWP13/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Whitney K. Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Inkmann, Joachim, 2000. "Finite Sample Properties of One-step, Two-step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," CoFE Discussion Papers 00/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. Lorenzo Camponovo & Taisuke Otsu, 2017. "Relative error accurate statistic based on nonparametric likelihood," STICERD - Econometrics Paper Series 593, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    5. Hill, Jonathan B. & Prokhorov, Artem, 2016. "GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference," Journal of Econometrics, Elsevier, vol. 190(1), pages 18-45.
    6. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    7. Fan, Yanqin & Gentry, Matthew & Li, Tong, 2011. "A new class of asymptotically efficient estimators for moment condition models," Journal of Econometrics, Elsevier, vol. 162(2), pages 268-277, June.
    8. Patrik Buggenberger & Richard Smith, 2003. "Generalized empirical likelihood estimators and tests under partial, weak and strong identification," CeMMAP working papers CWP08/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Frank Kleibergen, 2004. "Expansions of GMM statistics that indicate their properties under weak and/or many instruments and the bootstrap," Econometric Society 2004 North American Summer Meetings 408, Econometric Society.
    10. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers CWP03/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Shane M. Sherlund, 2004. "Quasi Empirical Likelihood Estimation of Moment Condition Models," Econometric Society 2004 North American Summer Meetings 507, Econometric Society.
    12. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2021. "Relative error accurate statistic based on nonparametric likelihood," LSE Research Online Documents on Economics 107521, London School of Economics and Political Science, LSE Library.
    13. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
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    19. Gagliardini, Patrick & Ronchetti, Diego, 2013. "Semi-parametric estimation of American option prices," Journal of Econometrics, Elsevier, vol. 173(1), pages 57-82.
    20. Severini, Thomas A. & Tripathi, Gautam, 2001. "A simplified approach to computing efficiency bounds in semiparametric models," Journal of Econometrics, Elsevier, vol. 102(1), pages 23-66, May.
    21. Peter Woehrmann & Willi Semmler & Martin Lettau, "undated". "Nonparametric Estimation of the Time-varying Sharpe Ratio in Dynamic Asset Pricing Models," IEW - Working Papers 225, Institute for Empirical Research in Economics - University of Zurich.
    22. Arthur Lewbel & Daniel McFadden & Oliver Linton, 1997. "Estimating Features of a Distribution from Binomial Data," Boston College Working Papers in Economics 442, Boston College Department of Economics, revised 01 Jul 2010.
    23. Aeberhard, William H. & Cantoni, Eva & Heritier, Stephane, 2017. "Saddlepoint tests for accurate and robust inference on overdispersed count data," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 162-175.
    24. Inkmann, J., 2005. "Inverse Probability Weighted Generalised Empirical Likelihood Estimators : Firm Size and R&D Revisited," Other publications TiSEM c39cff1f-16c1-4446-a83f-c, Tilburg University, School of Economics and Management.
    25. Zhou, Ling & Lin, Huazhen & Chen, Kani & Liang, Hua, 2019. "Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models," Journal of Econometrics, Elsevier, vol. 213(2), pages 593-607.
    26. Hahn, Jinyong & Newey, Whitney K. & Smith, Richard J., 2014. "Neglected heterogeneity in moment condition models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 86-100.
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    31. Whitney K. Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    32. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
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    34. Joachim Inkmann, 2010. "Estimating Firm Size Elasticities of Product and Process R&D," Economica, London School of Economics and Political Science, vol. 77(306), pages 384-402, April.
    35. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers 48/13, Institute for Fiscal Studies.
    36. Alain Guay & Florian Pelgrin, 2016. "Using Implied Probabilities to Improve the Estimation of Unconditional Moment Restrictions for Weakly Dependent Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 344-372, March.
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  47. Whitney K. Newey & Douglas G. Steigerwald, 1997. "Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models," Econometrica, Econometric Society, vol. 65(3), pages 587-600, May.

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    1. Kim, Suk-Joong & Sheen, Jeffrey, 1998. "International Linkages and Macroeconomic News Effects on Interest Rate Volatility - Australia and the US'," Working Papers 11, University of Sydney, School of Economics.
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    3. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
    4. Li, Muyi & Li, Wai Keung & Li, Guodong, 2015. "A new hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 189(2), pages 428-436.
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    6. Hafner, C.M. & Rombouts, J.V.K., 2004. "Estimation of temporally aggregated multivariate GARCH models," Econometric Institute Research Papers EI 2004-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    8. Claude Diebolt & Mohamed Chikhi, 2021. "Testing The Weak Form Efficiency Of The French Etf Market With Lstar-Anlstgarch Approach Using A Semiparametric Estimation," Working Papers 09-21, Association Française de Cliométrie (AFC).
    9. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    10. Laïb Naâmane & Lemdani Mohamed & Ould Saïd Elias, 2013. "A functional conditional symmetry test for a GARCH-SM model: Power asymptotic properties," Statistics & Risk Modeling, De Gruyter, vol. 30(1), pages 75-104, March.
    11. Lüders, Erik & Schröder, Michael, 2004. "Modeling Asset Returns: A Comparison of Theoretical and Empirical Models," ZEW Discussion Papers 04-19, ZEW - Leibniz Centre for European Economic Research.
    12. Carluccio Bianchi & Alessandro Carta & Dean Fantazzini & Maria Elena De Giuli & Mario A. Maggi, 2009. "A Copula-VAR-X Approach for Industrial Production Modelling and Forecasting," Quaderni di Dipartimento 105, University of Pavia, Department of Economics and Quantitative Methods.
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    15. Colavecchio, Roberta & Funke, Michael, 2006. "Volatility transmissions between renminbi and Asia-Pacific on-shore and off-shore U.S. dollar futures," BOFIT Discussion Papers 16/2006, Bank of Finland Institute for Emerging Economies (BOFIT).
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    283. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2023. "Distribution regression with sample selection and UK wage decomposition," CeMMAP working papers 09/23, Institute for Fiscal Studies.
    284. Jerry Hausman & Whitney K. Newey, 2014. "Individual Heterogeneity and Average Welfare," CeMMAP working papers 42/14, Institute for Fiscal Studies.
    285. Matias D. Cattaneo & Fang Han & Zhexiao Lin, 2023. "On Rosenbaum's Rank-based Matching Estimator," Papers 2312.07683, arXiv.org, revised Jan 2024.
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    Cited by:

    1. Zheng Fang & Juwon Seo, 2021. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Econometrica, Econometric Society, vol. 89(5), pages 2439-2458, September.
    2. Galbraith, John W. & Zinde-Walsh, Victoria, 2020. "Simple and reliable estimators of coefficients of interest in a model with high-dimensional confounding effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 609-632.
    3. Liu, Yan & Zhang, Sanguo & Ma, Shuangge & Zhang, Qingzhao, 2020. "Tests for regression coefficients in high dimensional partially linear models," Statistics & Probability Letters, Elsevier, vol. 163(C).
    4. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    5. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2012. "Inference on treatment effects after selection amongst high-dimensional controls," CeMMAP working papers CWP10/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Khan, Shakeeb & Maurel, Arnaud & Zhang, Yichong, 2020. "Informational Content of Factor Structures in Simultaneous Binary Response Models," IZA Discussion Papers 14008, Institute of Labor Economics (IZA).
    7. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    8. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    9. Qi Li & Aman Ullha, 1998. "Estimating partially linear panel data models with one-way error components," Econometric Reviews, Taylor & Francis Journals, vol. 17(2), pages 145-166.
    10. Cattaneo, Matias D & Jansson, Michael & Newey, Whitney K, 2018. "Inference in Linear Regression Models with Many Covariates and Heteroscedasticity," Department of Economics, Working Paper Series qt6rp7p9gs, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    11. Cui, Xia & Zhao, Weihua & Lian, Heng & Liang, Hua, 2019. "Pursuit of dynamic structure in quantile additive models with longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 130(C), pages 42-60.
    12. Holland, Ashley D., 2017. "Penalized spline estimation in the partially linear model," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 211-235.
    13. Li, Lingling & Tchetgen Tchetgen, Eric & van der Vaart, Aad & Robins, James M., 2011. "Higher order inference on a treatment effect under low regularity conditions," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 821-828, July.
    14. You, Jinhong & Zhou, Xian, 2006. "Statistical inference in a panel data semiparametric regression model with serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 844-873, April.
    15. Hengjian, Cui & Rongcai, Li, 1998. "On Parameter Estimation for Semi-linear Errors-in-Variables Models," Journal of Multivariate Analysis, Elsevier, vol. 64(1), pages 1-24, January.
    16. Matias Cattaneo & Michael Jansson & Whitney K. Newey, 2015. "Alternative asymptotics and the partially linear model with many regressors," CeMMAP working papers 36/15, Institute for Fiscal Studies.
    17. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Yang Ning & Sida Peng & Jing Tao, 2020. "Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data," Papers 2009.03151, arXiv.org.
    19. You, Jinhong & Zhou, Xian & Chen, Gemai, 2005. "Jackknifing in partially linear regression models with serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 92(2), pages 386-404, February.
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    21. Wang, Wenjie, 2021. "Bootstrap Inference for Partially Linear Model with Many Regressors," MPRA Paper 106391, University Library of Munich, Germany.
    22. Naoya Sueishi & Arihiro Yoshimura, 2017. "Focused Information Criterion for Series Estimation in Partially Linear Models," The Japanese Economic Review, Springer, vol. 68(3), pages 352-363, September.
    23. You, Jinhong & Sun, Xiaoqian & Pang, Wan-kai & Leung, Ping-kei, 2002. "Jackknifing type weighted least squares estimators in partially linear regression models," Statistics & Probability Letters, Elsevier, vol. 60(1), pages 17-31, November.
    24. Liang, Han-Ying & Fan, Guo-Liang, 2009. "Berry-Esseen type bounds of estimators in a semiparametric model with linear process errors," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 1-15, January.
    25. Ruoyao Shi, 2022. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202211, University of California at Riverside, Department of Economics.
    26. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    27. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    28. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
    29. You, Jinhong & Chen, Gemai, 2006. "Estimation of a semiparametric varying-coefficient partially linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 324-341, February.
    30. Matthew Backus & Sida Peng, 2019. "On Testing Continuity and the Detection of Failures," NBER Working Papers 26016, National Bureau of Economic Research, Inc.
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    32. Lai, Peng & Meng, Jie & Lian, Heng, 2015. "Polynomial spline approach for variable selection and estimation in varying coefficient models for time series data," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 21-27.
    33. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.

  54. Newey, Whitney K, 1994. "The Asymptotic Variance of Semiparametric Estimators," Econometrica, Econometric Society, vol. 62(6), pages 1349-1382, November.
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  55. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
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    Cited by:

    1. Alberto Abadie, 2000. "Semiparametric Estimation of Instrumental Variable Models for Causal Effects," NBER Technical Working Papers 0260, National Bureau of Economic Research, Inc.

  57. Newey, Whitney K & Stoker, Thomas M, 1993. "Efficiency of Weighted Average Derivative Estimators and Index Models," Econometrica, Econometric Society, vol. 61(5), pages 1199-1223, September.

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    1. Hiroaki Kaido, 2014. "Asymptotically efficient estimation of weighted average derivatives with an interval censored variable," CeMMAP working papers 03/14, Institute for Fiscal Studies.
    2. Marcia M Schafgans & Victoria Zinde-Walshyz, 2008. "Smoothness Adaptive AverageDerivative Estimation," STICERD - Econometrics Paper Series 529, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Cattaneo, Matias D & Crump, Richard K & Jansson, Michael, 2014. "Small Bandwidth Asymptotics For Density-Weighted Average Derivatives," Department of Economics, Working Paper Series qt3jd237cg, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    4. Ai, Chunrong & Chen, Xiaohong, 2007. "Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables," Journal of Econometrics, Elsevier, vol. 141(1), pages 5-43, November.
    5. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2018.
    6. SCHAFGANS, Marcia M.A. & ZINDE-WALSH, Victoria, 2007. "Robust Average Derivative Estimation," Cahiers de recherche 12-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    7. Pedro Carneiro & James Heckman & Edward Vytlacil, 2009. "Evaluating marginal policy changes and the average effect of treatment for individuals at the margin," CeMMAP working papers CWP21/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Lu, Xuewen & Burke, M.D., 2005. "Censored multiple regression by the method of average derivatives," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 182-205, July.
    9. Wanrong Liu & Xuewen Lu, 2011. "Empirical likelihood for density-weighted average derivatives," Statistical Papers, Springer, vol. 52(2), pages 391-412, May.
    10. Jérôme Foncel & Marian Hristache & Valentin Patilea, 2004. "Semiparametric Single-index Poisson Regression Model with Unobserved Heterogeneity," Working Papers 2004-04, Center for Research in Economics and Statistics.
    11. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    12. Chunrong Ai & Xiaohong Chen, 2009. "Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," CeMMAP working papers CWP28/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Andrew Chesher, 2005. "Identification with excess heterogeneity," CeMMAP working papers CWP19/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Li, Cong & Wang, Yanfei, 2016. "Gradient-based bandwidth selection for estimating average derivatives," Economics Letters, Elsevier, vol. 140(C), pages 19-22.
    15. Chen, Xiaohong & Pouzo, Demian & Powell, James L., 2019. "Penalized sieve GEL for weighted average derivatives of nonparametric quantile IV regressions," Journal of Econometrics, Elsevier, vol. 213(1), pages 30-53.
    16. Lu, Xun & White, Habert, 2015. "Testing For Treatment Dependence Of Effects Of A Continuous Treatment," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1016-1053, October.
    17. Severini, Thomas A. & Tripathi, Gautam, 2001. "A simplified approach to computing efficiency bounds in semiparametric models," Journal of Econometrics, Elsevier, vol. 102(1), pages 23-66, May.
    18. Donkers, Bas & Schafgans, Marcia M. A., 2005. "A method of moments estimator for semiparametric index models," LSE Research Online Documents on Economics 6815, London School of Economics and Political Science, LSE Library.
    19. Chesher, Andrew, 2009. "Excess heterogeneity, endogeneity and index restrictions," Journal of Econometrics, Elsevier, vol. 152(1), pages 37-45, September.
    20. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    21. Aprajit Mahajan, 2006. "Identification and Estimation of Regression Models with Misclassification," Econometrica, Econometric Society, vol. 74(3), pages 631-665, May.
    22. Matsushita, Yukitoshi & Otsu, Taisuke, 2018. "Likelihood inference on semiparametric models: average derivative and treatment effect," LSE Research Online Documents on Economics 85870, London School of Economics and Political Science, LSE Library.
    23. Härdle, Wolfgang & Müller, Marlene, 1997. "Multivariate and semiparametric kernel regression," SFB 373 Discussion Papers 1997,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    24. Kun Chen & Yanyuan Ma, 2017. "Analysis of Double Single Index Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 1-20, March.
    25. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Discussion Paper 2022-009, Tilburg University, Center for Economic Research.
    26. Lu, Xuewen & Cheng, Tsung-Lin, 2007. "Randomly censored partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1895-1922, November.
    27. Subbotin, Viktor, 2008. "Essays on the econometric theory of rank regressions," MPRA Paper 14086, University Library of Munich, Germany.
    28. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    29. Cizek, P. & Lei, J., 2013. "Identification and Estimation of Nonseparable Single-Index Models in Panel Data with Correlated Random Effects," Other publications TiSEM 73e394eb-6799-4c79-af23-8, Tilburg University, School of Economics and Management.
    30. Juan Carlos Escanciano & Kyungchul Song, 2007. "Asymptotically Optimal Tests for Single-Index Restrictions with a Focus on Average Partial Effects," PIER Working Paper Archive 07-005, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    31. Chen, Songnian & Khan, Shakeeb, 2000. "Estimating censored regression models in the presence of nonparametric multiplicative heteroskedasticity," Journal of Econometrics, Elsevier, vol. 98(2), pages 283-316, October.
    32. Das, M., 2005. "Instrumental variables estimators of nonparametric models with discrete endogenous regressors," Journal of Econometrics, Elsevier, vol. 124(2), pages 335-361, February.
    33. Bryan S. Graham & Guido W. Imbens & Geert Ridder, 2010. "Measuring the Effects of Segregation in the Presence of Social Spillovers: A Nonparametric Approach," NBER Working Papers 16499, National Bureau of Economic Research, Inc.
    34. Catalina Bolancé & Ricardo Cao & Montserrat Guillen, 2018. "“Flexible maximum conditional likelihood estimation for single-index models to predict accident severity with telematics data”," IREA Working Papers 201829, University of Barcelona, Research Institute of Applied Economics, revised Dec 2018.
    35. Coppejans, Mark, 2001. "Estimation of the binary response model using a mixture of distributions estimator (MOD)," Journal of Econometrics, Elsevier, vol. 102(2), pages 231-269, June.
    36. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," Journal of Econometrics, Elsevier, vol. 157(1), pages 151-164, July.
    37. Ping Yu & Peter C.B. Phillips, 2014. "Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 1966, Cowles Foundation for Research in Economics, Yale University.
    38. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    39. Christou, Eliana & Akritas, Michael G., 2016. "Single index quantile regression for heteroscedastic data," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 169-182.
    40. Cai, Zongwu & Juhl, Ted & Yang, Bingduo, 2015. "Functional index coefficient models with variable selection," Journal of Econometrics, Elsevier, vol. 189(2), pages 272-284.
    41. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    42. Victor Chernozhukov & Vira Semenova, 2018. "Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions," CeMMAP working papers CWP40/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    43. Yuya Sasaki & Takuya Ura, 2018. "Estimation and Inference for Policy Relevant Treatment Effects," Papers 1805.11503, arXiv.org, revised Jul 2020.
    44. Hennessy, David A., 2006. "Multi-Output Firm Under Price Uncertainty," Staff General Research Papers Archive 12408, Iowa State University, Department of Economics.
    45. Banerjee, Anurag, 2007. "A method of estimating the average derivative," Journal of Econometrics, Elsevier, vol. 136(1), pages 65-88, January.
    46. Delecroix, Michel & Härdle, Wolfgang & Hristache, Marian, 2003. "Efficient estimation in conditional single-index regression," Journal of Multivariate Analysis, Elsevier, vol. 86(2), pages 213-226, August.
    47. Escanciano, Juan Carlos & Song, Kyungchul, 2010. "Testing single-index restrictions with a focus on average derivatives," Journal of Econometrics, Elsevier, vol. 156(2), pages 377-391, June.
    48. Nishiyama, Y., 2004. "Minimum normal approximation error bandwidth selection for averaged derivatives," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(1), pages 53-61.
    49. Marian Hristache, 2002. "Are Efficient Estimators in Single-Index Models Really Efficient? A Computational Discussion," Computational Statistics, Springer, vol. 17(4), pages 453-464, December.
    50. Chen, Tao & Parker, Thomas, 2014. "Semiparametric efficiency for partially linear single-index regression models," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 376-386.
    51. Chin-Shang Li & Minggen Lu, 2018. "A lack-of-fit test for generalized linear models via single-index techniques," Computational Statistics, Springer, vol. 33(2), pages 731-756, June.

  58. Hausman, Jerry A. & Newey, Whitney K. & Ichimura, Hidehiko & Powell, James L., 1991. "Identification and estimation of polynomial errors-in-variables models," Journal of Econometrics, Elsevier, vol. 50(3), pages 273-295, December.

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    1. Laurence C. Baker, 1995. "HMOs and Fee-For-Service Health Care Expenditures: Evidence from Medicare," NBER Working Papers 5360, National Bureau of Economic Research, Inc.
    2. Christoph Breunig, 2018. "Varying Random Coefficient Models," Papers 1804.03110, arXiv.org, revised Aug 2020.
    3. Giuseppe De Luca & Franco Peracchi, 2010. "Estimating Engel curves under unit and item nonresponse," EIEF Working Papers Series 1004, Einaudi Institute for Economics and Finance (EIEF), revised Nov 2010.
    4. Battistin, Erich & De Nadai, Michele & Krishnan, Nandini, 2020. "The Insights and Illusions of Consumption Measurements," IZA Discussion Papers 13222, Institute of Labor Economics (IZA).
    5. Qing Li, 2014. "Identifiability of mean-reverting measurement error with instrumental variable," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(2), pages 118-129, May.
    6. Yingyao Hu & Geert Ridder, 2005. "Estimation of Nonlinear Models with Mismeasured Regressors Using Marginal Information," IEPR Working Papers 05.39, Institute of Economic Policy Research (IEPR).
    7. Shigeru Iwata, 2001. "Recentered And Rescaled Instrumental Variable Estimation Of Tobit And Probit Models With Errors In Variables," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 319-335.
    8. Dalderop, Jeroen, 2023. "Semiparametric estimation of latent variable asset pricing models," Journal of Econometrics, Elsevier, vol. 236(1).
    9. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    10. Xiaodong Gong & Arthur van Soest & Ping Zhang, 2005. "The effects of the gender of children on expenditure patterns in rural China: a semiparametric analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 509-527, May.
    11. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.
    12. Michele De Nadai & Arthur Lewbel, 2012. "Nonparametric Errors in Variables Models with Measurement Errors on both sides of the Equation," Boston College Working Papers in Economics 790, Boston College Department of Economics, revised 01 Jul 2013.
    13. Zapata, Hector O. & Sulgham, Anil K., 2006. "A Semiparametric Approach to Estimate Engel curves using the US Micro Data," 2006 Annual meeting, July 23-26, Long Beach, CA 21092, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Denni Tommasi & Lina Zhang, 2020. "Bounding Program Benefits When Participation is Misreported," Monash Econometrics and Business Statistics Working Papers 24/20, Monash University, Department of Econometrics and Business Statistics.
    15. Martin Browning & Sule Alan & Orazio Attanasio, 2006. "Estimating Euler Equations with Noisy Data: Two Exact GMM Estimators," Economics Series Working Papers 283, University of Oxford, Department of Economics.
    16. Gong, X. & van Soest, A.H.O. & Zhang, P., 2000. "Sexual Bias and Household Consumption : A Semiparametic Analysis of Engel curves in Rural China," Discussion Paper 2000-45, Tilburg University, Center for Economic Research.
    17. Tey, (John) Yeong-Sheng & Shamsudin, Mad Nasir & Mohamed, Zainalabidin & Abdullah, Amin Mahir & Radam, Alias, 2009. "Evidence of Engel curves in food away from home: A study of Malaysia," MPRA Paper 14833, University Library of Munich, Germany.
    18. Hennessy, Christopher A. & Levy, Amnon & Whited, Toni M., 2007. "Testing Q theory with financing frictions," Journal of Financial Economics, Elsevier, vol. 83(3), pages 691-717, March.
    19. Raymond Carroll & Xiaohong Chen & Yingyao Hu, 2010. "Identification and estimation of nonlinear models using two samples with nonclassical measurement errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 419-423.
    20. Lance Lochner & Youngki Shin, 2014. "Understanding Earnings Dynamics: Identifying and Estimating the Changing Roles of Unobserved Ability, Permanent and Transitory Shocks," NBER Working Papers 20068, National Bureau of Economic Research, Inc.
    21. Orley Ashenfelter & Cecilia Rouse, 1998. "Income, Schooling, and Ability: Evidence from a New Sample of Identical Twins," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(1), pages 253-284.
    22. Ben-Moshe, Dan & D’Haultfœuille, Xavier & Lewbel, Arthur, 2017. "Identification of additive and polynomial models of mismeasured regressors without instruments," Journal of Econometrics, Elsevier, vol. 200(2), pages 207-222.
    23. Candelaria, Luis E. & Ura, Takuya, 2020. "Identification and Inference of Network Formation Games with Misclassified Links," The Warwick Economics Research Paper Series (TWERPS) 1258, University of Warwick, Department of Economics.
    24. Biørn, Erik, 2017. "Identification and Method of Moments Estimation in Polynomial Measurement Error Models," Memorandum 01/2017, Oslo University, Department of Economics.
    25. Aucejo, Esteban & Coate, Patrick & Cooley Fruehwirth, Jane & Kelly, Sean & Mozenter, Zachary, 2018. "Teacher Effectiveness and Classroom Composition," CEPR Discussion Papers 13166, C.E.P.R. Discussion Papers.
    26. Dennis Epple & Brett Gordon & Holger Sieg, 2010. "A New Approach to Estimating the Production Function for Housing," American Economic Review, American Economic Association, vol. 100(3), pages 905-924, June.
    27. Xiaohong Chen & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric Identification of Regression Models Containing a Misclassified Dichotomous Regressor Without Instruments," Boston College Working Papers in Economics 675, Boston College Department of Economics.
    28. Mitali Das, 2000. "Instrumental Variables Estimation of Nonparametric Models with Discrete Endogenous Regressors," Econometric Society World Congress 2000 Contributed Papers 1008, Econometric Society.
    29. Shrabani Mukherjee & Subhadri Sankar Mallik & Debdulal Thakur, 2019. "Tracking Financial Inclusion in India: A Study of SHG Initiatives," Indian Journal of Human Development, , vol. 13(1), pages 32-46, April.
    30. Xiaohong Chen & Yingyao Hu, 2006. "Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors," Cowles Foundation Discussion Papers 1590, Cowles Foundation for Research in Economics, Yale University.
    31. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
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    5. Ashenfelter, O. & Harmon, C. & Oosterbeek, H., 1999. "A Review of Estimates of the Schooling/ Earnings Relationship, with tests for Publication Bias," Papers 99/20, College Dublin, Department of Political Economy-.
    6. Robert Stefko & Beata Gavurova & Miroslav Kelemen & Martin Rigelsky & Viera Ivankova, 2021. "Relationships between Renewable Energy and the Prevalence of Morbidity in the Countries of the European Union: A Panel Regression Approach," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    7. Robert LaLonde, 2004. "Should We Teach Old Dogs New Tricks? The Impact of Community College Retraining on Older Displaced Workers," Working Papers 0412, Harris School of Public Policy Studies, University of Chicago.
    8. Stephanie Riegg Cellini & Latika Chaudhary, 2012. "The Labor Market Returns to a For-Profit College Education," NBER Working Papers 18343, National Bureau of Economic Research, Inc.
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    10. Louis Jacobson & Robert J. Lalonde & Daniel Sullivan, 2005. "The Impact of Community College Retraining on Older Displaced Workers: Should We Teach Old Dogs New Tricks?," ILR Review, Cornell University, ILR School, vol. 58(3), pages 398-415, April.
    11. Beata Gavurova & Jaroslav Belas & Katarina Zvarikova & Martin Rigelsky & Viera Ivankova, 2021. "The Effect of Education and R&D on Tourism Spending in OECD Countries: An Empirical Study," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(58), pages 806-806, August.
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    1. Lingjie Ma & Roger Koenker, 2004. "Quantile regression methods for recursive structural equation models," CeMMAP working papers CWP01/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    3. Kaplan, David M. & Sun, Yixiao, 2012. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," University of California at San Diego, Economics Working Paper Series qt888657tp, Department of Economics, UC San Diego.
    4. Habert white & Tae-Hwan Kim & Simone Manganelli, 2012. "VAR for VaR: Measuring Tail Dependence Using Multivariate Regression Quantiles," Working papers 2012rwp-45, Yonsei University, Yonsei Economics Research Institute.
    5. Andrew Chesher, 2001. "Exogenous impact and conditional quantile functions," CeMMAP working papers 01/01, Institute for Fiscal Studies.
    6. Cinthya G. Caamal Olvera, 2017. "Decreasing returns to schooling in Mexico," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 32(1), pages 27-63.
    7. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    8. Stéphane Girard & Gilles Claude Stupfler & Antoine Usseglio-Carleve, 2021. "Extreme Conditional Expectile Estimation in Heavy-Tailed Heteroscedastic Regression Models," Post-Print hal-03306230, HAL.
    9. Chesher, Andrew, 2007. "Instrumental values," Journal of Econometrics, Elsevier, vol. 139(1), pages 15-34, July.
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    40. Sun, Y., 2003. "Square Root N - Consistent Semiparametric Estimation of Partially Linear Quantile Regression Models," Working Papers 2003-11, University of Guelph, Department of Economics and Finance.
    41. Lingjie Ma & Roger Koenker, 2004. "Quantile regression methods for recursive structural equation models," CeMMAP working papers 01/04, Institute for Fiscal Studies.
    42. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
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    44. Shengfang Tang & Zongwu Cai & Ying Fang & Ming Lin, 2020. "A New Quantile Treatment Effect Model for Studying Smoking Effect on Birth Weight During Mother's Pregnancy," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202003, University of Kansas, Department of Economics, revised Feb 2020.

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    1. Lee, Lung-fei, 1995. "Semiparametric maximum likelihood estimation of polychotomous and sequential choice models," Journal of Econometrics, Elsevier, vol. 65(2), pages 381-428, February.
    2. Chen, Songnian, 1997. "Semiparametric estimation of the Type-3 Tobit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 1-34, September.
    3. Linton, Oliver, 1996. "Edgeworth Approximation for MINPIN Estimators in Semiparametric Regression Models," Econometric Theory, Cambridge University Press, vol. 12(1), pages 30-60, March.
    4. Rich Benjamin & Moodie Erica E. M. & A. Stephens David, 2016. "Influence Re-weighted G-Estimation," The International Journal of Biostatistics, De Gruyter, vol. 12(1), pages 157-177, May.
    5. Xiaohong Chen & Demian Pouzo, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," CeMMAP working papers CWP20/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Lv, Xiaofeng & Li, Rui & Fang, Zheng, 2017. "Efficient semiparametric estimation for Gini inequality treatment effects," Economics Letters, Elsevier, vol. 154(C), pages 96-100.
    7. Michael Jansson & Demian Pouzo, 2019. "Towards a general large sample theory for regularized estimators," CeMMAP working papers CWP63/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
    9. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2018.
    10. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    11. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    12. Mogstad, Magne & Wiswall, Matthew, 2010. "Linearity in Instrumental Variables Estimation: Problems and Solutions," IZA Discussion Papers 5216, Institute of Labor Economics (IZA).
    13. Franklin, Simon, 2020. "Enabled to work: The impact of government housing on slum dwellers in South Africa," Journal of Urban Economics, Elsevier, vol. 118(C).
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    1. Linton, Oliver, 1996. "Edgeworth Approximation for MINPIN Estimators in Semiparametric Regression Models," Econometric Theory, Cambridge University Press, vol. 12(1), pages 30-60, March.
    2. Zhengyu Zhang & Pingfang Zhu, 2010. "A More Efficient Best Spatial Three-stage Least Squares Estimator for Spatial Autoregressive Models," Annals of Economics and Finance, Society for AEF, vol. 11(1), pages 155-184, May.
    3. Delis, Manthos & Savva, Christos & Theodossiou, Panayiotis, 2020. "A Coronavirus Asset Pricing Model: The Role of Skewness," MPRA Paper 100877, University Library of Munich, Germany.
    4. Thanasis Stengos & Ximing Wu, 2005. "Partially Adaptive Estimation via Maximum Entropy Densities," University of Cyprus Working Papers in Economics 6-2005, University of Cyprus Department of Economics.
    5. Wai Mun Fong, 1997. "Robust beta estimation: Some empirical evidence," Review of Financial Economics, John Wiley & Sons, vol. 6(2), pages 167-186.
    6. Ao Yuan & Jan G. De Gooijer, 2007. "Semiparametric Regression with Kernel Error Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 841-869, December.
    7. Arslan, Olcay, 2004. "Family of multivariate generalized t distributions," Journal of Multivariate Analysis, Elsevier, vol. 89(2), pages 329-337, May.
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    9. West, Kenneth D, 2001. "On Optimal Instrumental Variables Estimation of Stationary Time Series Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1043-1050, November.
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    11. Tao Chen & Gautam Tripathi, 2013. "Testing conditional symmetry without smoothing," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 273-313, June.
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    15. Thanasis Stengos & Yiguo Sun, 2005. "The Absolute Health Income Hypothesis Revisited : A Semiparametric Quantile Regression Approach," University of Cyprus Working Papers in Economics 7-2005, University of Cyprus Department of Economics.
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    26. Peter M Robinson, 2007. "Efficient Estimation of the SemiparametricSpatial Autoregressive Model," STICERD - Econometrics Paper Series 515, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    27. James Mcdonald & Richard Michelfelder & Panayiotis Theodossiou, 2010. "Robust estimation with flexible parametric distributions: estimation of utility stock betas," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 375-387.
    28. Im, Kyung So & Schmidt, Peter, 2008. "More efficient estimation under non-normality when higher moments do not depend on the regressors, using residual augmented least squares," Journal of Econometrics, Elsevier, vol. 144(1), pages 219-233, May.
    29. Linton, Oliver, 2000. "Edgeworth approximations for semiparametric instrumental variable estimators and test statistics," LSE Research Online Documents on Economics 2156, London School of Economics and Political Science, LSE Library.
    30. Peter Robinson, 2006. "Efficient estimation of the semiparametric spatial autoregressive model," CeMMAP working papers CWP08/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Tao Chen & Gautam Tripathi, 2014. "A simple consistent test of conditional symmetry in symmetrically trimmed tobit models," DEM Discussion Paper Series 14-04, Department of Economics at the University of Luxembourg.
    32. Alicia Pérez Alonso, 2006. "A Bootstrap Approach To Test The Conditional Symmetry In Time Series Models," Working Papers. Serie AD 2006-18, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    33. James B. McDonald & Daniel B. Walton & Bryan Chia, 2020. "Distributional Assumptions and the Estimation of Contingent Valuation Models," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 431-460, August.
    34. Bai, Jushan & Ng, Serena, 2001. "A consistent test for conditional symmetry in time series models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 225-258, July.
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    37. Ramirez, Octavio A. & Misra, Sukant K. & Nelson, Jeannie, 2002. "Estimation Of Efficient Regression Models For Applied Agricultural Economics Research," 2002 Annual meeting, July 28-31, Long Beach, CA 19904, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    38. Victor Korolev, 2023. "Analytic and Asymptotic Properties of the Generalized Student and Generalized Lomax Distributions," Mathematics, MDPI, vol. 11(13), pages 1-27, June.
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    44. Peter M Robinson, 2009. "Developments in the Analysis of Spatial Data," STICERD - Econometrics Paper Series 531, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    45. Peter M Robinson, 2004. "Efficiency Improvements in Inference on Stationary and Nonstationary Fractional Time Series," STICERD - Econometrics Paper Series 480, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    46. Robinson, Peter & Taylor, Luke, 2017. "Adaptive estimation in multiple time series with independent component errors," LSE Research Online Documents on Economics 68345, London School of Economics and Political Science, LSE Library.
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    50. Robinson, P.M., 2010. "Efficient estimation of the semiparametric spatial autoregressive model," Journal of Econometrics, Elsevier, vol. 157(1), pages 6-17, July.
    51. Joseph Ngatchou-Wandji & Michel Harel, 2013. "A Cramér-von Mises test for symmetry of the error distribution in asymptotically stationary stochastic models," Statistical Inference for Stochastic Processes, Springer, vol. 16(3), pages 207-236, October.
    52. Eric Auerbach, 2019. "Identification and Estimation of a Partially Linear Regression Model using Network Data," Papers 1903.09679, arXiv.org, revised Jun 2021.
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    54. Ivanović, Blagoje & Milošević, Bojana & Obradović, Marko, 2020. "Comparison of symmetry tests against some skew-symmetric alternatives in i.i.d. and non-i.i.d. setting," Computational Statistics & Data Analysis, Elsevier, vol. 151(C).
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    56. H. He & W. Wang & J. Hu & R. Gallop & P. Crits-Christoph & Y. Xia, 2015. "Distribution-free inference of zero-inflated binomial data for longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(10), pages 2203-2219, October.
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    61. Robinson, Peter, 2008. "Developments in the analysis of spatial data," LSE Research Online Documents on Economics 25473, London School of Economics and Political Science, LSE Library.
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    1. Thomas Bittmann & Jens‐Peter Loy & Sven Anders, 2020. "Product differentiation and cost pass‐through: industry‐wide versus firm‐specific cost shocks," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(4), pages 1184-1209, October.
    2. Altunbas, Yener & Binici, Mahir & Gambacorta, Leonardo, 2018. "Macroprudential policy and bank risk," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 203-220.
    3. Blanka Škrabić Perić & Petar Sorić, 2018. "A Note on the “Economic Policy Uncertainty Index”," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(2), pages 505-526, June.
    4. Cosimo Magazzino, 2014. "A Panel VAR Approach of the Relationship among Economic Growth, CO2 Emissions, and Energy Use in the ASEAN-6 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 4(4), pages 546-553.
    5. Marra, Alessandro & Colantonio, Emiliano, 2021. "The path to renewable energy consumption in the European Union through drivers and barriers: A panel vector autoregressive approach," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    6. Maria Bernadete Sarmiento Gutierrez & Mario Jorge Cardoso de Mendonça & Adolfo Sachsida & Paulo Roberto Amorim Loureiro, 2004. "Inequality And Criminality Revisited: Further Evidence From Brazil," Anais do XXXII Encontro Nacional de Economia [Proceedings of the 32nd Brazilian Economics Meeting] 149, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    7. Kim, Younoh, 2015. "The dynamics of health and its determinants among the elderly in developing countries," Economics & Human Biology, Elsevier, vol. 19(C), pages 1-12.
    8. Isiaka Akande Raifu & Terver Theophilus Kumeka & Alarudeen Aminu, 2021. "Reaction of stock market returns to COVID-19 pandemic and lockdown policy: evidence from Nigerian firms stock returns," Future Business Journal, Springer, vol. 7(1), pages 1-16, December.
    9. Alfonso Mendoza-Velázquez & Luis Carlos Ortuño-Barba & Luis David Conde-Cortés, 2022. "Corporate governance and firm performance in hybrid model countries," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 21(1), pages 32-58, February.
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    11. Salotti, Simone & Marattin, Luigi, 2009. "On the usefulness of government spending in the EU area," MPRA Paper 19476, University Library of Munich, Germany.
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    14. Kazuhiko Hayakawa, 2007. "A Simple Efficient Instrumental Variable Estimator in Panel AR(p) Models," Hi-Stat Discussion Paper Series d07-213, Institute of Economic Research, Hitotsubashi University.
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    17. Jan Babecký & Tomáš Havránek & Jakub Mateju & Marek Rusnák & Katerina Šmídková & Borek Vašícek, 2012. "Banking, Debt, and Currency Crises: Early Warning Indicators for Developed Countries," Working Papers IES 2012/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2012.
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    21. Nguyen Van Bon, 2019. "The Role Of Institutional Quality In The Relationship Between Fdi And Economic Growth In Vietnam: Empirical Evidence From Provincial Data," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(03), pages 601-623, June.
    22. Sabien (S.) Dobbelaere & Jacques Mairesse, 2017. "Comparing micro-evidence on rent sharing from two different econometric models," Tinbergen Institute Discussion Papers 17-112/V, Tinbergen Institute.
    23. Tori, Daniele & Onaran, Özlem, 2017. "Financialisation and Physical Investment: A global race to the bottom in accumulation?," Greenwich Papers in Political Economy 20981, University of Greenwich, Greenwich Political Economy Research Centre.
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    26. Jessica M. Mc Lay & Roy Lay-Yee & Barry J. Milne & Peter Davis, 2015. "Regression-Style Models for Parameter Estimation in Dynamic Microsimulation: An Empirical Performance Assessment," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 83-127.
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    31. Matthieu Darracq Paries, 2018. "Financial frictions and monetary policy conduct," Erudite Ph.D Dissertations, Erudite, number ph18-01 edited by Ferhat Mihoubi, February.
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    42. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
    43. L. Arturo Bernal Ponce & Ricardo Pérez Navarro & Mauricio Ramírez Grajeda, 2020. "Causality between Chinese investment in Latin America and the governance indicators," Competition and Regulation in Network Industries, , vol. 21(1), pages 6-17, March.
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    45. Luca VOTA, 2022. "Employment Impact Of Firms' Innovation: What Is The Role Of Regional Institutions? Evidence From Italy," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(2), pages 11-24, June.
    46. Thomas Goda, Santiago Sánchez, 2022. "Export Market Size Matters: The effect of the market size of export destinations on manufacturing growth," Documentos de Trabajo de Valor Público 20531, Universidad EAFIT.
    47. Morris A. Davis & Jonas D. M. Fisher & Toni M. Whited, 2014. "Macroeconomic Implications of Agglomeration," Econometrica, Econometric Society, vol. 82(2), pages 731-764, March.
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    50. Ouyang, Yusi & Shimeles, Abebe & Thorbecke, Erik, 2018. "Revisiting Cross-Country Poverty Convergence in the Developing World with a Special Focus on Sub-Saharan Africa," IZA Discussion Papers 11388, Institute of Labor Economics (IZA).
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    58. Ross Levine & Norman Loayza & Thorsten Beck, 2002. "Financial Intermediation and Growth: Causality and Causes," Central Banking, Analysis, and Economic Policies Book Series, in: Leonardo Hernández & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.),Banking, Financial Integration, and International Crises, edition 1, volume 3, chapter 2, pages 031-084, Central Bank of Chile.
    59. Stefan Dercon, 2003. "Growth and Shocks: evidence from rural Ethiopia," CSAE Working Paper Series 2003-12, Centre for the Study of African Economies, University of Oxford.
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    120. Guanglei Hong & Fan Yang & Xu Qin, 2021. "Did you conduct a sensitivity analysis? A new weighting‐based approach for evaluations of the average treatment effect for the treated," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 227-254, January.
    121. Jinyong Hahn & Jerry Hausman & Josh Lustig, 2017. "Specification test on mixed logit models," CeMMAP working papers 58/17, Institute for Fiscal Studies.
    122. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    123. Joachim Inkmann, 2010. "Estimating Firm Size Elasticities of Product and Process R&D," Economica, London School of Economics and Political Science, vol. 77(306), pages 384-402, April.
    124. Sakaguchi, Shosei, 2016. "Estimation of time-varying average treatment effects using panel data when unobserved fixed effects affect potential outcomes differently," Economics Letters, Elsevier, vol. 146(C), pages 82-84.
    125. Brück, Florian & Fermanian, Jean-David & Min, Aleksey, 2023. "A corrected Clarke test for model selection and beyond," Journal of Econometrics, Elsevier, vol. 235(1), pages 105-132.
    126. Jaumandreu, Jordi & Lorences, Joaquin, 2002. "Modelling price competition across many markets (An application to the Spanish loans market)," European Economic Review, Elsevier, vol. 46(1), pages 93-115, January.
    127. Kathleen McGarry, 1995. "Factors Determining Participation of the Elderly in SSI," NBER Working Papers 5250, National Bureau of Economic Research, Inc.
    128. Glaeser, Edward L. & Gyourko, Joseph & Morales, Eduardo & Nathanson, Charles G., 2014. "Housing dynamics: An urban approach," Journal of Urban Economics, Elsevier, vol. 81(C), pages 45-56.
    129. Keunkwan Ryu, 2001. "Maximum Likelihood Estimation and Specification Test of the Proportional Hazard Model Using Grouped Durations," ISER Discussion Paper 0552, Institute of Social and Economic Research, Osaka University.
    130. Olivier De Groote & Guido Pepermans & Frank Verboven, 2015. "Heterogeneity in the adoption of photovoltaic systems in Flanders," Working Papers of Department of Economics, Leuven 511914, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    131. Vella, Francis & Gregory, R. G., 1996. "Selection bias and human capital investment: Estimating the rates of return to education for young males," Labour Economics, Elsevier, vol. 3(2), pages 197-219, September.
    132. Jessie Handbury, 2019. "Are Poor Cities Cheap for Everyone? Non-Homotheticity and the Cost of Living Across U.S. Cities," NBER Working Papers 26574, National Bureau of Economic Research, Inc.
    133. Amaresh K Tiwari, 2018. "Panel Data Binary Response Model In A Triangular System," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 110, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    134. Subramanian Balachander & Yan Liu & Axel Stock, 2009. "An Empirical Analysis of Scarcity Strategies in the Automobile Industry," Management Science, INFORMS, vol. 55(10), pages 1623-1637, October.
    135. Athanasakou, Vasiliki & Ferreira, Daniel & Goh, Lisa, 2022. "Changes in CEO stock option grants: A look at the numbers," Journal of Corporate Finance, Elsevier, vol. 75(C).
    136. Amaresh K Tiwari, 2021. "A Control Function Approach to Estimate Panel Data Binary Response Model," Papers 2102.12927, arXiv.org, revised Sep 2021.
    137. Sydney C. Ludvigson & Sai Ma & Serena Ng, 2015. "Uncertainty and Business Cycles: Exogenous Impulse or Endogenous Response?," NBER Working Papers 21803, National Bureau of Economic Research, Inc.
    138. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    139. Brachet, Tanguy, 2008. "Maternal Smoking, Misclassification, and Infant Health," MPRA Paper 21466, University Library of Munich, Germany.
    140. Chih-Hai Yang, 2018. "Exports and innovation: the role of heterogeneity in exports," Empirical Economics, Springer, vol. 55(3), pages 1065-1087, November.
    141. Prokhorov, Artem & Schmidt, Peter, 2009. "GMM redundancy results for general missing data problems," Journal of Econometrics, Elsevier, vol. 151(1), pages 47-55, July.
    142. Holden, Stein T. & Fisher, Monica & Katengeza, Samson P. & Thierfelder, Christian, 2018. "Can lead farmers reveal the adoption potential of conservation agriculture? The case of Malawi," Land Use Policy, Elsevier, vol. 76(C), pages 113-123.

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    Cited by:

    1. Sumitro Banerjee & David A. Soberman, 2013. "Product development capability and marketing strategy for new durable products," ESMT Research Working Papers ESMT-13-01, ESMT European School of Management and Technology.
    2. Jonathan B. Berk Richard C. Green and Vasant Naik., 1998. "Valuation and Return Dynamics of New Ventures," Research Program in Finance Working Papers RPF-284, University of California at Berkeley.
    3. Pindyck, Robert S, 1991. "Irreversibility, Uncertainty, and Investment," Journal of Economic Literature, American Economic Association, vol. 29(3), pages 1110-1148, September.
    4. Garner, Jacqueline L. & Nam, Jouahn & Ottoo, Richard E., 2002. "Determinants of corporate growth opportunities of emerging firms," Journal of Economics and Business, Elsevier, vol. 54(1), pages 73-93.
    5. Kort, Peter M. & Murto, Pauli & Pawlina, Grzegorz, 2010. "Uncertainty and stepwise investment," European Journal of Operational Research, Elsevier, vol. 202(1), pages 196-203, April.
    6. Melstrom, Richard T. & Salau, Kehinde Rilwan & Shanafelt, David W., 2019. "The Optimal Timing of Reintroducing Captive Populations Into the Wild," Ecological Economics, Elsevier, vol. 156(C), pages 174-184.
    7. Lind, Robert C, 1995. "Intergenerational equity, discounting, and the role of cost-benefit analysis in evaluating global climate policy," Energy Policy, Elsevier, vol. 23(4-5), pages 379-389.
    8. Saman Majd & Robert S. Pindyck, 1985. "Time to Build, Option Value, and Investment Decisions," NBER Working Papers 1654, National Bureau of Economic Research, Inc.
    9. Pindyck, Robert S., 1993. "Investments of uncertain cost," Journal of Financial Economics, Elsevier, vol. 34(1), pages 53-76, August.
    10. Viju, Crina & Kerr, William A. & Nolan, James F., 2006. "Subsidization of the Biofuel Industry: Security vs. Clean Air?," 2006 Annual meeting, July 23-26, Long Beach, CA 21321, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. Li, Yong & James, Barclay & Madhavan, Ravi & Mahoney, Joseph T., 2006. "Real Options: Taking Stock and Looking Ahead," Working Papers 06-0114, University of Illinois at Urbana-Champaign, College of Business.
    12. Deeney, Peter & Cummins, Mark & Heintz, Katharina & Pryce, Mary T., 2021. "A real options based decision support tool for R&D investment: Application to CO2 recycling technology," European Journal of Operational Research, Elsevier, vol. 289(2), pages 696-711.
    13. Viju, Crina & Kerr, William A., 2010. "Is The Subsidy For Biofuels The Way To Go?," 14th ICABR Conference, June 16-18, 2010, Ravello, Italy 188117, International Consortium on Applied Bioeconomy Research (ICABR).
    14. Céline Bérard & Marie Perez, 2014. "Alliance Dynamics through Real Options: The Case of an Alliance between Competing Pharmaceutical Companies," Post-Print hal-04010373, HAL.
    15. Kolstad, Charles D., 2000. "Energy and Depletable Resources: Economics and Policy, 1973-1998," Journal of Environmental Economics and Management, Elsevier, vol. 39(3), pages 282-305, May.
    16. Bérard, Céline & Perez, Marie, 2014. "Alliance dynamics through real options: The case of an alliance between competing pharmaceutical companies," European Management Journal, Elsevier, vol. 32(2), pages 337-349.
    17. Viju, Crina & Kerr, William A., 2013. "Taking an option on the future: Subsidizing biofuels for energy security or reducing global warming," Energy Policy, Elsevier, vol. 56(C), pages 543-548.
    18. Schimmelpfennig, David, 1995. "The option value of renewable energy: The case of climate change," Energy Economics, Elsevier, vol. 17(4), pages 311-317, October.
    19. Lin, Yuanfang & Pazgal, Amit & Soberman, David A., 2021. "Who is the winner in an industry of innovation?," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 50-69.
    20. Banerjee, Sumitro & Soberman, David A., 2013. "Product development capability and marketing strategy for new durable products," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 276-291.
    21. Ottoo, Richard E., 1998. "Valuation of Internal Growth Opportunities: The Case of a Biotechnology Company," The Quarterly Review of Economics and Finance, Elsevier, vol. 38(3, Part 2), pages 615-633.

Chapters

  1. Newey, Whitney K. & McFadden, Daniel, 1986. "Large sample estimation and hypothesis testing," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 36, pages 2111-2245, Elsevier.

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    1. Güell, Maia & Hu, Luojia, 2003. "Estimating the Probability of Leaving Unemployment Using Uncompleted Spells from Repeated Cross-Section Data," CEPR Discussion Papers 3957, C.E.P.R. Discussion Papers.
    2. Guido W. Imbens & Judith K. Hellerstein, 1996. "Imposing Moment Restrictions from Auxiliary Data by Weighting," NBER Technical Working Papers 0202, National Bureau of Economic Research, Inc.
    3. Atsushi Inoue & Lutz Kilian & Fatma Burcu Kiraz, 2009. "Do Actions Speak Louder Than Words? Household Expectations of Inflation Based on Micro Consumption Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1331-1363, October.
    4. Mariacristina De Nardi & Eric French & John Bailey Jones, 2006. "Differential Mortality, Uncertain Medical Expenses, and the Saving of Elderly Singles," NBER Working Papers 12554, National Bureau of Economic Research, Inc.
    5. Chen, Xiaohong & Linton, Oliver & Van Keilegom, Ingrid, 2003. "Estimation of semiparametric models when the criterion function is not smooth," LSE Research Online Documents on Economics 2167, London School of Economics and Political Science, LSE Library.
    6. Jeremy Tobacman & David Laibson & Andrea Repetto, 2007. "Estimating Discount Functions with Consumption Choices over the Lifecycle," Economics Series Working Papers 341, University of Oxford, Department of Economics.
    7. DUFOUR, Jean-Marie & PELLETIER, Denis & RENAULT, Éric, 2003. "Short Run and Long Run Causality in Time Series : Inference," Cahiers de recherche 14-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    8. Schnedler, Wendelin, 2003. "What You Always Wanted to Know About Censoring But Never Dared to Ask – Parameter Estimation for Censored Random Vectors," IZA Discussion Papers 837, Institute of Labor Economics (IZA).
    9. Richard Harris & Qian Cher Li, 2007. "Learning-by-Exporting? Firm-Level Evidence for UK Manufacturing and Services Sectors," Working Papers 2007_22, Business School - Economics, University of Glasgow.
    10. Horowitz, Shira & Mauch, Brandon & Sowell, Fallaw, 2014. "Forecasting residential air conditioning loads," Applied Energy, Elsevier, vol. 132(C), pages 47-55.
    11. Clemente De Lucia & Mara Meacci, 2005. "Does job security matter for consumption? An analysis on Italian microdata," ISAE Working Papers 54, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    12. Murray Leibbrandt & James Levinsohn & Justin McCrary, 2005. "Incomes in South Africa Since the Fall of Apartheid," NBER Working Papers 11384, National Bureau of Economic Research, Inc.
    13. Van den Berg, Gerard & van Vuuren, Aico, 2003. "The Effect of Search Frictions on Wages," CEPR Discussion Papers 3979, C.E.P.R. Discussion Papers.
    14. Shakeeb Khan & Arthur Lewbel, 2002. "Weighted and Two Stage Least Squares Estimation of Semiparametric Truncated Regression Models," Boston College Working Papers in Economics 525, Boston College Department of Economics, revised 04 Sep 2006.
    15. Albuquerque, Rui & Marques, Luis & de Francisco, Eva, 2006. "Marketwide Private Information in Stocks: Forecasting Currency Returns," CEPR Discussion Papers 5604, C.E.P.R. Discussion Papers.
    16. Roger Klein & Francis Vella, 2009. "A semiparametric model for binary response and continuous outcomes under index heteroscedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 735-762.
    17. Eric French & John BaileyJones, 2007. "The Effects of Health Insurance and Self-Insurance on Retirement Behavior," Working Papers wp170, University of Michigan, Michigan Retirement Research Center.
    18. Carrasco, Marine & Florens, Jean-Pierre, 2014. "On The Asymptotic Efficiency Of Gmm," Econometric Theory, Cambridge University Press, vol. 30(2), pages 372-406, April.
    19. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.
    20. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Sara G. Castellanos & Marco A. Oviedo, 2004. "Optimal Bidding in the Mexican Treasury Securities Primary Auctions: Results from a Structural Econometrics Approach," Levine's Working Paper Archive 122247000000000118, David K. Levine.
    22. Arimura, Toshi H. & Li, Shanjun & Newell, Richard G. & Palmer, Karen, 2011. "Cost-Effectiveness of Electricity Energy Efficiency Programs," RFF Working Paper Series dp-09-48-rev, Resources for the Future.
    23. Inkmann, Joachim, 2000. "Finite Sample Properties of One-step, Two-step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," CoFE Discussion Papers 00/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    24. Alastair R. Hall & Fernanda P. M. Peixe, 2003. "A Consistent Method for the Selection of Relevant Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 22(3), pages 269-287, January.
    25. Marszalec, Daniel, 2017. "The impact of auction choice on revenue in treasury bill auctions – An empirical evaluation," International Journal of Industrial Organization, Elsevier, vol. 53(C), pages 215-239.
    26. Giulio Bottazzi & Angelo Secchi, 2006. "Maximum Likelihood Estimation of the Symmetric and Asymmetric Exponential Power Distribution," LEM Papers Series 2006/19, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    27. Alastair R. Hall & Atsushi Inoue & James M Nason & Barbara Rossi, 2009. "Information Criteria for Impulse Response Function Matching Estimation of DSGE Models," Centre for Growth and Business Cycle Research Discussion Paper Series 127, Economics, The University of Manchester.
    28. Manganelli, Simone, 2006. "A new theory of forecasting," Working Paper Series 584, European Central Bank.
    29. Roger Klein & Francis Vella, 2005. "Estimating a class of triangular simultaneous equations models without exclusion restrictions," CeMMAP working papers CWP08/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Pasquale Della Corte & Lucio Sarno & Daniel L. Thornton, 2007. "The expectation hypothesis of the term structure of very short-term rates: statistical tests and economic value," Working Papers 2006-061, Federal Reserve Bank of St. Louis.
    31. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Discussion Paper 2004-56, Tilburg University, Center for Economic Research.
    32. Richard Paap & Frank Kleibergen, 2004. "Generalized Reduced Rank Tests using the Singular Value Decomposition," Econometric Society 2004 Australasian Meetings 195, Econometric Society.
    33. Sophocles Mavroeidis, 2006. "Testing the New Keynesian Phillips Curve Without Assuming Identification," Working Papers 2006-13, Brown University, Department of Economics.
    34. Chrisopher J. Bennett & Brennan S. Thompson, 2012. "Moving the Goalposts: Subjective Performance Benchmarks and the Aumann-Serrano Measure of Riskiness," Working Papers 057, Ryerson University, Department of Economics, revised Oct 2014.
    35. Bo E. Honore & Arthur Lewbel, 1998. "Semiparametric Binary Choice Panel Data Models without Strictly Exogeneous Regressors," Boston College Working Papers in Economics 455, Boston College Department of Economics, revised 22 Sep 2001.
    36. Hussinger, Katrin, 2003. "R&D and Subsidies at the Firm Level: An Application of Parametric and Semi-Parametric Two-Step Selection Models," ZEW Discussion Papers 03-63, ZEW - Leibniz Centre for European Economic Research.
    37. Mehmet Caner, 2005. "Higher Order Expansions in GMM with Nearly Weak and Many Nearly Weak Instruments," Working Paper 209, Department of Economics, University of Pittsburgh, revised Jan 2005.
    38. Frank Kleibergen, 2004. "Expansions of GMM statistics that indicate their properties under weak and/or many instruments and the bootstrap," Econometric Society 2004 North American Summer Meetings 408, Econometric Society.
    39. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
    40. Robert M. de Jong & Tiemen Woutersen, 2007. "Dynamic time series binary choice," Economics Working Paper Archive 538, The Johns Hopkins University,Department of Economics.
    41. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers CWP03/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    42. Luc Behaghel & Bruno Crépon & Marc Gurgand & Thomas Le Barbanchon, 2015. "Please Call Again: Correcting Nonresponse Bias in Treatment Effect Models," PSE-Ecole d'économie de Paris (Postprint) halshs-01245539, HAL.
    43. Härdle, Wolfgang Karl & Ritov, Ya’acov & Wang, Weining, 2015. "Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 129-145.
    44. Jean-Yves Pitarakis, 2003. "Least Squares Estimation and Tests of Breaks in Mean and Variance under Misspecification," Econometrics 0312004, University Library of Munich, Germany.
    45. Eric French & John Bailey Jones, 2002. "On the distribution and dynamics of health costs," Working Paper Series WP-02-21, Federal Reserve Bank of Chicago.
    46. Alberto Abadie, 2000. "Semiparametric Estimation of Instrumental Variable Models for Causal Effects," NBER Technical Working Papers 0260, National Bureau of Economic Research, Inc.
    47. Hærnes, Erik & Jia, Zhiyang & Strøm, Steinar, 2005. "Retirement in Non-Cooperative and Cooperative Families," Memorandum 15/2006, Oslo University, Department of Economics.
    48. Shane M. Sherlund, 2004. "Quasi Empirical Likelihood Estimation of Moment Condition Models," Econometric Society 2004 North American Summer Meetings 507, Econometric Society.
    49. Haroon Mumtaz & Konstantinos Theodoridis, 2017. "Fiscal Policy Shocks and Stock Prices in the United States," Working Papers 817, Queen Mary University of London, School of Economics and Finance.
    50. Justin McCrary & Heather Royer, 2006. "The Effect of Female Education on Fertility and Infant Health: Evidence from School Entry Policies Using Exact Date of Birth," NBER Working Papers 12329, National Bureau of Economic Research, Inc.
    51. Manganelli, Simone, 2007. "Asset allocation by penalized least squares," Working Paper Series 723, European Central Bank.
    52. Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers 0319, Econometric Society.
    53. Andrew Ang & Monika Piazzesi & Min Wei, 2004. "What Does the Yield Curve Tell us about GDP Growth?," NBER Working Papers 10672, National Bureau of Economic Research, Inc.
    54. Parra-Alvarez, Juan Carlos & Posch, Olaf & Wang, Mu-Chun, 2020. "Estimation of heterogeneous agent models: A likelihood approach," Discussion Papers 42/2020, Deutsche Bundesbank.
    55. Hugo Kruiniger, 2002. "On the estimation of panel regression models with fixed effects," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C6-2, International Conferences on Panel Data.
    56. Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," Harvard Institute of Economic Research Working Papers 1736, Harvard - Institute of Economic Research.
    57. Steven Berry & Alon Eizenberg & Joel Waldfogel, 2016. "Optimal product variety in radio markets," RAND Journal of Economics, RAND Corporation, vol. 47(3), pages 463-497, August.
    58. Jean-Marie Dufour & Alain Trognon & Purevdorj Tuvaandorj, 2015. "Invariant tests based on M-estimators, estimating functions, and the generalized method of moments," CIRANO Working Papers 2015s-27, CIRANO.
    59. Haiqing Xu, "undated". "Estimation of Discrete Games with Correlated Types," Department of Economics Working Papers 130909, The University of Texas at Austin, Department of Economics.
    60. Francisco Peñaranda & Enrique Sentana, 2008. "Spanning tests in return and stochastic discount factor mean-variance frontiers: A unifying approach," Economics Working Papers 1101, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2010.
    61. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.
    62. Audrino, Francesco & Trojani, Fabio, 2011. "A General Multivariate Threshold GARCH Model With Dynamic Conditional Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 138-149.
    63. Alastair R. Hall & Atsushi Inoue, 2005. "The Large Sample Behaviour of the Generalized Method of Moments Estimator in Misspecified Models," Econometrics 0505002, University Library of Munich, Germany.
    64. S. Chandra & Masanobu Taniguchi, 2001. "Estimating Functions for Nonlinear Time Series Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 125-141, March.
    65. Smith, Richard J., 2005. "Automatic Positive Semidefinite Hac Covariance Matrix And Gmm Estimation," Econometric Theory, Cambridge University Press, vol. 21(1), pages 158-170, February.
    66. James D. Hamilton & Seth Pruitt & Scott Borger, 2011. "Estimating the Market-Perceived Monetary Policy Rule," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 1-28, July.
    67. Laura Dumitrescu & Wei Qian & J. N. K. Rao, 2021. "Inference for longitudinal data from complex sampling surveys: An approach based on quadratic inference functions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 246-274, March.
    68. Arie Beresteanu & Francesca Molinari, 2008. "Asymptotic Properties for a Class of Partially Identified Models," Econometrica, Econometric Society, vol. 76(4), pages 763-814, July.
    69. Riccardo DiCecio & Edward Nelson, 2007. "An estimated DSGE model for the United Kingdom," Review, Federal Reserve Bank of St. Louis, vol. 89(Jul), pages 215-232.
    70. Matteo M. Pelagatti & Stefania Rondena, 2005. "Dynamic Conditional Correlation with Elliptical Distributions," Econometrics 0503007, University Library of Munich, Germany.
    71. Markus Frölich, 2006. "Statistical Treatment Choice: An Application to Active Labour Market Programmes," University of St. Gallen Department of Economics working paper series 2006 2006-14, Department of Economics, University of St. Gallen.
    72. Jeffrey M. Wooldridge, 2002. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," CeMMAP working papers CWP18/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    73. Susanne M Schennach, 2007. "Instrumental Variable Estimation of Nonlinear Errors-in-Variables Models," Econometrica, Econometric Society, vol. 75(1), pages 201-239, January.
    74. Hyungsik Roger Moon & Peter C. B. Phillips, 2004. "GMM Estimation of Autoregressive Roots Near Unity with Panel Data," Econometrica, Econometric Society, vol. 72(2), pages 467-522, March.
    75. Òscar Jordà & Sharon Kozicki, 2007. "Estimation and Inference by the Method of Projection Minimum Distance," Staff Working Papers 07-56, Bank of Canada.
    76. MEDDAHI, Nour & RENAULT, Éric, 1998. "Quadratic M-Estimators for ARCH-Type Processes," Cahiers de recherche 9814, Universite de Montreal, Departement de sciences economiques.
    77. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Other publications TiSEM 93fe16c1-9f21-4dab-9b73-4, Tilburg University, School of Economics and Management.
    78. Wolfgang Karl Härdle & Ya'acov Ritov & Weining Wang, 2013. "Tie the straps: uniform bootstrap confidence bands for bounded influence curve estimators," SFB 649 Discussion Papers SFB649DP2013-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    79. Farshid Vahid & Pushkar Maitra, 2005. "The Effect of Household Characteristics on Living Standards in South Africa 1993 - 98: A Quantile Regression Analysis with Sample Attrition," ANU Working Papers in Economics and Econometrics 2005-452, Australian National University, College of Business and Economics, School of Economics.
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    84. Jeffrey M. Wooldridge, 2001. "Applications of Generalized Method of Moments Estimation," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 87-100, Fall.
    85. Juan Carlos Parra‐Alvarez & Olaf Posch & Mu‐Chun Wang, 2023. "Estimation of Heterogeneous Agent Models: A Likelihood Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 304-330, April.
    86. Rong Tang & Yun Yang, 2022. "Bayesian inference for risk minimization via exponentially tilted empirical likelihood," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1257-1286, September.
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    93. Thorsten Vogel, 2006. "Reassessing Intergenerational Mobility in Germany and the United States: The Impact of Differences in Lifecycle Earnings Patterns," SFB 649 Discussion Papers SFB649DP2006-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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    97. Söehnke Bartram & Stephen Taylor & Yaw-Huei Wang, 2004. "The Euro and European Financial Market Integration," Money Macro and Finance (MMF) Research Group Conference 2004 49, Money Macro and Finance Research Group, revised 13 Oct 2004.
    98. Arthur Lewbel, 2002. "Ordered Response Threshold Estimation," Boston College Working Papers in Economics 535, Boston College Department of Economics, revised 29 Oct 2003.
    99. Kenneth Bollen & Stanislav Kolenikov & Shawn Bauldry, 2014. "Model-Implied Instrumental Variable—Generalized Method of Moments (MIIV-GMM) Estimators for Latent Variable Models," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 20-50, January.
    100. Onur Başer & Joseph C. Gardiner & Cathy J. Bradley & Hüseyin Yüce & Charles Given, 2006. "Longitudinal analysis of censored medical cost data," Health Economics, John Wiley & Sons, Ltd., vol. 15(5), pages 513-525, May.
    101. Jürgen Maurer & André Meier, 2008. "Smooth it Like the “Joneses?†Estimating Peer-Group Effects in Intertemporal Consumption Choice," MEA discussion paper series 08167, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    102. An, Yonghong & Hu, Yingyao & Shum, Matthew, 2010. "Estimating first-price auctions with an unknown number of bidders: A misclassification approach," Journal of Econometrics, Elsevier, vol. 157(2), pages 328-341, August.
    103. Lewbel, Arthur, 2007. "Endogenous selection or treatment model estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 777-806, December.
    104. Arthur Lewbel, 2000. "Asymptotic Trimming for Bounded Density Plug-in Estimators," Boston College Working Papers in Economics 479, Boston College Department of Economics, revised 30 Oct 2000.
    105. Hiroyuki Kasahara & Katsumi Shimotsu, 2006. "Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices," University of Western Ontario, Departmental Research Report Series 20065, University of Western Ontario, Department of Economics.
    106. Sergio Pastorello & Valentin Patilea & Eric Renault, 2003. "Iterative and Recursive Estimation in Structural Non-Adaptive Models," CIRANO Working Papers 2003s-08, CIRANO.
    107. Ivan Fernandez-Val, 2005. "Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects," Boston University - Department of Economics - Working Papers Series WP2005-38, Boston University - Department of Economics.
    108. van Akkeren, Marco & Judge, George & Mittelhammer, Ron, 2002. "Generalized moment based estimation and inference," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 127-148, March.
    109. Carlos A. Flores, 2007. "Estimation of Dose-Response Functions and Optimal Doses with a Continuous Treatment," Working Papers 0707, University of Miami, Department of Economics.
    110. Farshid Vahid & Pushkar Maitra, 2006. "The effect of household characteristics on living standards in South Africa 1993-1998: a quantile regression analysis with sample attrition," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 999-1018.
    111. Lechner, Michael & Laisney, François, 2002. "Almost Consistent Estimation of Panel Probit Models with 'Small' Fixed Effects," ZEW Discussion Papers 02-64, ZEW - Leibniz Centre for European Economic Research.
    112. Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
    113. Richard Smith, 2005. "Weak instruments and empirical likelihood: a discussion of the papers by DWK Andrews and JH Stock and Y Kitamura," CeMMAP working papers CWP13/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    114. Gad Allon & Michael Beenstock & Steven Hackman & Ury Passy & Alex Shapiro, 2005. "Nonparametric estimation of concave production technologies by entropic methods," Econometrics 0512003, University Library of Munich, Germany.
    115. Whitney K. Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    116. Schorfheide, Frank & Moon, Hyungsik Roger, 2006. "Boosting Your Instruments: Estimation with Overidentifying Inequality Moment Conditions," CEPR Discussion Papers 5605, C.E.P.R. Discussion Papers.
    117. Giovanni Forchini & Grant Hillier, 2005. "Ill-conditioned problems, Fisher information and weak instruments," CeMMAP working papers CWP04/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    118. David S. Lee, 2005. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," NBER Working Papers 11721, National Bureau of Economic Research, Inc.
    119. Robert Moffit, 2007. "Estimating Marginal Treatment Effects in Heterogeneous Populations," Economics Working Paper Archive 539, The Johns Hopkins University,Department of Economics.
    120. Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July.
    121. André Faria & Philip R. Lane & Paolo Mauro & Gian Maria Milesi-Ferretti, 2007. "The Shifting Composition of External Liabilities," The Institute for International Integration Studies Discussion Paper Series iiisdp190, IIIS.
    122. Wilke, Ralf A., 2003. "Semiparametric Estimation of Regression Functions Under Shape Invariance Restrictions," ZEW Discussion Papers 03-64, ZEW - Leibniz Centre for European Economic Research.
    123. Filippeli, Thomai & Harrison, Richard & Theodoridis, Konstantinos, 2018. "DSGE-based Priors for BVARs & Quasi-Bayesian DSGE Estimation," Cardiff Economics Working Papers E2018/5, Cardiff University, Cardiff Business School, Economics Section.
    124. Arthur Lewbel, 2005. "Simple Endogenous Binary Choice and Selection Panel Model Estimators," Boston College Working Papers in Economics 613, Boston College Department of Economics, revised 04 Sep 2006.
    125. Jürgen Maurer & André Meier, 2005. "Do the "Joneses" really matter? Peer-group versus correlated effects in intertemporal consumption choice," IFS Working Papers W05/15, Institute for Fiscal Studies.
    126. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    127. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition and stratification," CeMMAP working papers CWP11/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    128. Markus Pannenberg & Martin Spieß, 2007. "GEE Estimation of a Two-Equation Panel Data Model: An Analysis of Wage Dynamics and the Incidence of Profit-Sharing in West Germany," Discussion Papers of DIW Berlin 663, DIW Berlin, German Institute for Economic Research.
    129. Pierre Azoulay & Waverly Ding & Toby Stuart, 2006. "The Impact of Academic Patenting on the Rate, Quality, and Direction of (Public) Research Output," NBER Working Papers 11917, National Bureau of Economic Research, Inc.
    130. Peter C.B. Phillips & Jun Yu, 2005. "A Two-Stage Realized Volatility Approach to the Estimation for Diffusion Processes from Discrete Observations," Cowles Foundation Discussion Papers 1523, Cowles Foundation for Research in Economics, Yale University.
    131. Esmerelda A. Ramalho & Richard Smith, 2003. "Discrete choice non-response," CeMMAP working papers CWP07/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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Books

  1. Blundell,Richard & Newey,Whitney & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521692106.

    Cited by:

    1. Bosetti, Valentina & Maffezzoli, Marco, 2013. "Taxing Carbon under Market Incompleteness," Climate Change and Sustainable Development 158665, Fondazione Eni Enrico Mattei (FEEM).
    2. Andres Aradillas-Lopez & Adam Rosen, 2013. "Inference in ordered response games with complete information," CeMMAP working papers 33/13, Institute for Fiscal Studies.
    3. Christopher P. Chambers & Federico Echenique & Nicolas Lambert, 2019. "Recovering Preferences from Finite Data," Papers 1909.05457, arXiv.org, revised Oct 2020.
    4. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," SciencePo Working papers Main hal-01073733, HAL.
    5. Chang, Jinyuan & Chen, Song Xi & Chen, Xiaohong, 2014. "High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data," MPRA Paper 59640, University Library of Munich, Germany.
    6. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2022. "Discretizing Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 90(2), pages 625-643, March.
    7. Stefan Hoderlein & Yuya Sasaki, 2013. "Outcome Conditioned Treatment Effects," Boston College Working Papers in Economics 840, Boston College Department of Economics.
    8. Van Biesebroeck, Johannes & Grant, Iris, 2019. "Entry decisions and asymmetric competition between non-profit and for-profit homes in the long-term care market," CEPR Discussion Papers 14005, C.E.P.R. Discussion Papers.
    9. Kiviet, Jan F. & Niemczyk, Jerzy, 2012. "Comparing the asymptotic and empirical (un)conditional distributions of OLS and IV in a linear static simultaneous equation," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3567-3586.
    10. Andrea Attar & Thomas Mariotti & François Salanié, 2020. "The Social Costs of Side Trading," Working Papers hal-02538295, HAL.
    11. Valentina Corradi & Antonio Mele & Walter Distaso, 2008. "Macroeconomic Determinants of Stock Market Returns, Volatility and Volatility Risk-Premia," FMG Discussion Papers dp616, Financial Markets Group.
    12. Sheng-Pin Hsueh & Wei-Ming Lee, 2012. "A revisit to the relationship between patents and R&D using empirical likelihood estimation," Economics Bulletin, AccessEcon, vol. 32(2), pages 1208-1214.
    13. Marmer, Vadim & Otsu, Taisuke, 2008. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Microeconomics.ca working papers vadim_marmer-2008-13, Vancouver School of Economics, revised 25 Jul 2011.
    14. Andrew Chesher, 2007. "Endogeneity and discrete outcomes," CeMMAP working papers CWP05/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
    16. Nguezet, Paul Martin Dontsop & Diagne, Aliou & Okoruwa, Victor Olusegun & Ojehomon, Vivian, 2011. "Impact of Improved Rice Technology (NERICA varieties) on Income and Poverty among Rice Farming Households in Nigeria: A Local Average Treatment Effect (LATE) Approach," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 50(3), pages 1-25.
    17. Xu, Ke-Li, 2010. "Reweighted Functional Estimation Of Diffusion Models," Econometric Theory, Cambridge University Press, vol. 26(2), pages 541-563, April.
    18. Almut E. D. Veraart & Luitgard A. M. Veraart, 2009. "Stochastic volatility and stochastic leverage," CREATES Research Papers 2009-20, Department of Economics and Business Economics, Aarhus University.
    19. Vetter, Mathias & Podolskij, Mark, 2006. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," Technical Reports 2006,51, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    20. Dubois, Pierre & Griffith, Rachel & O'Connell, Martin, 2022. "The Use of Scanner Data for Economics Research," TSE Working Papers 22-1286, Toulouse School of Economics (TSE).
    21. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, Department of Economics and Business Economics, Aarhus University.
    22. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers 45/13, Institute for Fiscal Studies.
    23. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    24. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    25. Jeremy T. Fox & David H. Hsu & Chenyu Yang, 2012. "Unobserved Heterogeneity in Matching Games with an Application to Venture Capital," NBER Working Papers 18168, National Bureau of Economic Research, Inc.
    26. Vianney Dequiedt & David Martimort, 2015. "Vertical Contracting with Informational Opportunism," PSE - Labex "OSE-Ouvrir la Science Economique" halshs-01273256, HAL.
    27. Richard Blundell & Joel Horowitz & Matthias Parey, 2022. "Estimation of a Heterogeneous Demand Function with Berkson Errors," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 877-889, December.
    28. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    29. Ralph Stinebrickner & Todd R. Stinebrickner, 2013. "A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout," NBER Working Papers 19165, National Bureau of Economic Research, Inc.
    30. Francis X. Diebold & Georg Strasser, 2013. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(4), pages 1304-1337.
    31. Firmin Doko Tchatoka, 2014. "Specification Tests with Weak and Invalid Instruments," School of Economics and Public Policy Working Papers 2014-05, University of Adelaide, School of Economics and Public Policy.
    32. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
    33. Lee, Yoonseok & Phillips, Peter C.B., 2015. "Model selection in the presence of incidental parameters," Journal of Econometrics, Elsevier, vol. 188(2), pages 474-489.
    34. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    36. Kalnina, Ilze & Linton, Oliver, 2007. "Inference about realized volatility using infill subsampling," LSE Research Online Documents on Economics 4411, London School of Economics and Political Science, LSE Library.
    37. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
    38. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016. "Intraday volatility interaction between the crude oil and equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
    39. John Bailey Jones & Minhee Kim & Byoung G. Park, 2020. "The Wage Penalty for Married Women of Career Interruptions: Evidence from the 1970s and the 1990s," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 783-807, August.
    40. Antoni Calvo-Armengol & Eleonora Patacchini & Yves Zenou, 2008. "Peer Effects and Social Networks in Education," RF Berlin - CReAM Discussion Paper Series 0814, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    41. James M. Nason & Gregor W. Smith, 2005. "Identifying the New Keynesian Phillips curve," FRB Atlanta Working Paper 2005-01, Federal Reserve Bank of Atlanta.
    42. Manuel Arellano, 2007. "Comments on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 23-27, May.
    43. Almut Veraart, 2011. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(3), pages 253-291, September.
    44. Justin Yifu Lin & Pengfei Zhang, 2007. "Development Strategy and Economic Institutions in Less Developed Countries," CID Working Papers 17, Center for International Development at Harvard University.
    45. Koen Jochmans, 2011. "Identification in Bivariate binary-choice Models with elliptical innovations," SciencePo Working papers Main hal-01069483, HAL.
    46. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    47. Itai Sher & Kyoo il Kim, 2012. "Identification of Demand Models of Multiple Purchases," Working Papers 2012-2, University of Minnesota, Department of Economics.
    48. Carro, Jesús M. & Traferri, Alejandra, 2011. "State dependence and heterogeneity in health using a bias corrected fixed effects estimator," UC3M Working papers. Economics we1118, Universidad Carlos III de Madrid. Departamento de Economía.
    49. Laura Hospido, 2007. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," Working Papers wp2007_0717, CEMFI.
    50. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    51. Hovhannisyan, Vardges & Urutyan, Vardan, 2017. "A Structural Model of Pre-committed Demand: The Case of Food Demand in China," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258200, Agricultural and Applied Economics Association.
    52. Jinyong Hahn & Ruoyao Shi, 2021. "Breusch and Pagan’s (1980) Test Revisited," Working Papers 202110, University of California at Riverside, Department of Economics.
    53. Donna Feir & Thomas Lemieux & Vadim Marmer, 2016. "Weak Identification in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 185-196, April.
    54. Markus Haavio and Kaisa Kotakorpi, 2012. "Sin Licenses Revisited," Discussion Papers 75, Aboa Centre for Economics.
    55. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    56. Peter C. B. Phillips & Jun Yu, 2009. "Information Loss in Volatility Measurement with Flat Price Trading," Global COE Hi-Stat Discussion Paper Series gd08-039, Institute of Economic Research, Hitotsubashi University.
    57. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    58. Chesher, Andrew, 2013. "Semiparametric Structural Models Of Binary Response: Shape Restrictions And Partial Identification," Econometric Theory, Cambridge University Press, vol. 29(2), pages 231-266, April.
    59. Cecilia Mancini & Vanessa Mattiussi & Roberto Reno', 2012. "Spot Volatility Estimation Using Delta Sequences," Working Papers - Mathematical Economics 2012-10, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    60. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    61. Taisuke Otsu & Chen Qiu, 2018. "Information theoretic approach to high dimensional multiplicative models: Stochastic discount factor and treatment effect," STICERD - Econometrics Paper Series 595, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    62. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk — realised semivariance," CREATES Research Papers 2008-42, Department of Economics and Business Economics, Aarhus University.
    63. Ali Mehrabani & Aman Ullah, 2020. "Improved Average Estimation in Seemingly Unrelated Regressions," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    64. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
    65. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    66. Heejoon Han & Myung D. Park, 2013. "Comparison of Realized Measure and Implied Volatility in Forecasting Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 522-533, September.
    67. Bertille Antoine & Prosper Dovonon, 2020. "Robust Estimation with Exponentially Tilted Hellinger Distance," Discussion Papers dp20-02, Department of Economics, Simon Fraser University.
    68. Alain Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2008. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," BIS Working Papers 249, Bank for International Settlements.
    69. Javier Álvarez & Manuel Arellano, 2004. "Robust Likelihood Estimation of Dynamic Panel Data Models," Working Papers wp2004_0421, CEMFI.
    70. Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014. "Fact or friction: Jumps at ultra high frequency," Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
    71. John M Maheu & Thomas H McCurdy, 2008. "Do high-frequency measures of volatility improve forecasts of return distributions?," Working Papers tecipa-324, University of Toronto, Department of Economics.
    72. Bo E. Honor√ & Daniel Kaufmann & Sarah Lein, 2012. "Asymmetries in Price-Setting Behavior: New Microeconometric Evidence from Switzerland," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44, pages 211-236, December.
    73. Cheuk Yin Ho, 2016. "Better Health With More Friends: The Role of Social Capital in Producing Health," Health Economics, John Wiley & Sons, Ltd., vol. 25(1), pages 91-100, January.
    74. Waterson, Michael & Toivanen, Otto, 2011. "Retail Chain Expansion: The Early Years of McDonalds in Great Britain," CEPR Discussion Papers 8534, C.E.P.R. Discussion Papers.
    75. Michael Salinger & Pauline Ippolito & Joel Schrag, 2007. "Economics at the FTC: Pharmaceutical Patent Dispute Settlements and Behavioral Economics," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 31(2), pages 85-105, September.
    76. Osafo-Kwaako, Philip & Robinson, James A., 2013. "Political centralization in pre-colonial Africa," Journal of Comparative Economics, Elsevier, vol. 41(1), pages 6-21.
    77. Bontemps, Christian & Kumar, Rohit, 2018. "A Geometric Approach to Inference in Set-Identified Entry Games," TSE Working Papers 18-943, Toulouse School of Economics (TSE), revised Mar 2019.
    78. Weinschenk, Philipp, 2012. "Increasing workload in a stochastic environment," Economics Letters, Elsevier, vol. 115(2), pages 286-288.
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    80. Kline, Brendan & Tamer, Elie, 2012. "Bounds for best response functions in binary games," Journal of Econometrics, Elsevier, vol. 166(1), pages 92-105.
    81. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
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    83. Christiano A. Coelho & João Manoel Pinho de Mello & Leonardo Rezende, 2007. "Are Public Banks pro-Competitive? Evidence from Concentrated Local Markets in Brazil," Textos para discussão 551, Department of Economics PUC-Rio (Brazil), revised Sep 2007.
    84. Rhodes, Andrew & Zhou, Jidong, 2022. "Personalized Pricing and Competition," MPRA Paper 112988, University Library of Munich, Germany.
    85. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
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    87. Hoderlein, Stefan & Winter, Joachim, 2009. "Structural Measurement Errors in Nonseparable Models," Discussion Papers in Economics 9192, University of Munich, Department of Economics.
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    89. Diebold, Francis X. & Strasser, Georg H., 2008. "On the correlation structure of microstructure noise in theory and practice," CFS Working Paper Series 2008/32, Center for Financial Studies (CFS).
    90. Wang, Xuexin, 2016. "A New Class of Tests for Overidentifying Restrictions in Moment Condition Models," MPRA Paper 69004, University Library of Munich, Germany.
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    32. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
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    35. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
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    37. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
    38. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016. "Intraday volatility interaction between the crude oil and equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
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    44. Justin Yifu Lin & Pengfei Zhang, 2007. "Development Strategy and Economic Institutions in Less Developed Countries," CID Working Papers 17, Center for International Development at Harvard University.
    45. Koen Jochmans, 2011. "Identification in Bivariate binary-choice Models with elliptical innovations," SciencePo Working papers Main hal-01069483, HAL.
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    50. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    51. Hovhannisyan, Vardges & Urutyan, Vardan, 2017. "A Structural Model of Pre-committed Demand: The Case of Food Demand in China," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258200, Agricultural and Applied Economics Association.
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    260. Gervas Huxley & Mike W. Peacey, 2016. "Self-control at College," Bristol Economics Discussion Papers 16/675, School of Economics, University of Bristol, UK.
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    3. Christopher P. Chambers & Federico Echenique & Nicolas Lambert, 2019. "Recovering Preferences from Finite Data," Papers 1909.05457, arXiv.org, revised Oct 2020.
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    5. Chang, Jinyuan & Chen, Song Xi & Chen, Xiaohong, 2014. "High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data," MPRA Paper 59640, University Library of Munich, Germany.
    6. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2022. "Discretizing Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 90(2), pages 625-643, March.
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    8. Van Biesebroeck, Johannes & Grant, Iris, 2019. "Entry decisions and asymmetric competition between non-profit and for-profit homes in the long-term care market," CEPR Discussion Papers 14005, C.E.P.R. Discussion Papers.
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    11. Valentina Corradi & Antonio Mele & Walter Distaso, 2008. "Macroeconomic Determinants of Stock Market Returns, Volatility and Volatility Risk-Premia," FMG Discussion Papers dp616, Financial Markets Group.
    12. Sheng-Pin Hsueh & Wei-Ming Lee, 2012. "A revisit to the relationship between patents and R&D using empirical likelihood estimation," Economics Bulletin, AccessEcon, vol. 32(2), pages 1208-1214.
    13. Marmer, Vadim & Otsu, Taisuke, 2008. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Microeconomics.ca working papers vadim_marmer-2008-13, Vancouver School of Economics, revised 25 Jul 2011.
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    24. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
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    26. Vianney Dequiedt & David Martimort, 2015. "Vertical Contracting with Informational Opportunism," PSE - Labex "OSE-Ouvrir la Science Economique" halshs-01273256, HAL.
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    35. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
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    37. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
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    3. Christopher P. Chambers & Federico Echenique & Nicolas Lambert, 2019. "Recovering Preferences from Finite Data," Papers 1909.05457, arXiv.org, revised Oct 2020.
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    6. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2022. "Discretizing Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 90(2), pages 625-643, March.
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    8. Van Biesebroeck, Johannes & Grant, Iris, 2019. "Entry decisions and asymmetric competition between non-profit and for-profit homes in the long-term care market," CEPR Discussion Papers 14005, C.E.P.R. Discussion Papers.
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    11. Valentina Corradi & Antonio Mele & Walter Distaso, 2008. "Macroeconomic Determinants of Stock Market Returns, Volatility and Volatility Risk-Premia," FMG Discussion Papers dp616, Financial Markets Group.
    12. Sheng-Pin Hsueh & Wei-Ming Lee, 2012. "A revisit to the relationship between patents and R&D using empirical likelihood estimation," Economics Bulletin, AccessEcon, vol. 32(2), pages 1208-1214.
    13. Marmer, Vadim & Otsu, Taisuke, 2008. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Microeconomics.ca working papers vadim_marmer-2008-13, Vancouver School of Economics, revised 25 Jul 2011.
    14. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
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    16. Nguezet, Paul Martin Dontsop & Diagne, Aliou & Okoruwa, Victor Olusegun & Ojehomon, Vivian, 2011. "Impact of Improved Rice Technology (NERICA varieties) on Income and Poverty among Rice Farming Households in Nigeria: A Local Average Treatment Effect (LATE) Approach," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 50(3), pages 1-25.
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    19. Vetter, Mathias & Podolskij, Mark, 2006. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," Technical Reports 2006,51, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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    23. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    24. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    25. Jeremy T. Fox & David H. Hsu & Chenyu Yang, 2012. "Unobserved Heterogeneity in Matching Games with an Application to Venture Capital," NBER Working Papers 18168, National Bureau of Economic Research, Inc.
    26. Vianney Dequiedt & David Martimort, 2015. "Vertical Contracting with Informational Opportunism," PSE - Labex "OSE-Ouvrir la Science Economique" halshs-01273256, HAL.
    27. Richard Blundell & Joel Horowitz & Matthias Parey, 2022. "Estimation of a Heterogeneous Demand Function with Berkson Errors," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 877-889, December.
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    35. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    36. Kalnina, Ilze & Linton, Oliver, 2007. "Inference about realized volatility using infill subsampling," LSE Research Online Documents on Economics 4411, London School of Economics and Political Science, LSE Library.
    37. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
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    44. Justin Yifu Lin & Pengfei Zhang, 2007. "Development Strategy and Economic Institutions in Less Developed Countries," CID Working Papers 17, Center for International Development at Harvard University.
    45. Koen Jochmans, 2011. "Identification in Bivariate binary-choice Models with elliptical innovations," SciencePo Working papers Main hal-01069483, HAL.
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    47. Itai Sher & Kyoo il Kim, 2012. "Identification of Demand Models of Multiple Purchases," Working Papers 2012-2, University of Minnesota, Department of Economics.
    48. Carro, Jesús M. & Traferri, Alejandra, 2011. "State dependence and heterogeneity in health using a bias corrected fixed effects estimator," UC3M Working papers. Economics we1118, Universidad Carlos III de Madrid. Departamento de Economía.
    49. Laura Hospido, 2007. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," Working Papers wp2007_0717, CEMFI.
    50. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    51. Hovhannisyan, Vardges & Urutyan, Vardan, 2017. "A Structural Model of Pre-committed Demand: The Case of Food Demand in China," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258200, Agricultural and Applied Economics Association.
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    24. Hitoshi Matsushima, 2011. "Price-Based Combinatorial Auction: Connectedness and Representative Valuations," CIRJE F-Series CIRJE-F-806, CIRJE, Faculty of Economics, University of Tokyo.
    25. Antonio Merlo & Vincenzo Galasso & Massimiliano Landi & Andrea Mattozzi, 2008. "The Labor Market of Italian Politicians," Working Papers 15-2008, Singapore Management University, School of Economics, revised Oct 2008.
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    27. Elie Tamer & Federico Ciliberto, 2004. "Market Structure and Multiple Equilibria in Airline Markets," 2004 Meeting Papers 52, Society for Economic Dynamics.
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