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Susanne Schennach

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. Cunha, Flavio & Heckman, James J. & Schennach, Susanne, 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," IZA Discussion Papers 4702, Institute of Labor Economics (IZA).

    Mentioned in:

    1. 非認知的スキル
      by hisakijapan in hkonoの日記 on 2011-04-15 01:23:01

Working papers

  1. Arthur Lewbel & Susanne M. Schennach & Linqi Zhang, 2020. "Identification of a Triangular Two Equation System Without Instruments," Boston College Working Papers in Economics 1022, Boston College Department of Economics, revised 15 Dec 2022.

    Cited by:

    1. Geert Mesters & Piotr Zwiernik, 2022. "Non-Independent Components Analysis," Working Papers 1358, Barcelona School of Economics.

  2. Florian Gunsilius & Susanne M. Schennach, 2019. "Independent nonlinear component analysis," CeMMAP working papers CWP46/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    2. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Florian Gunsilius, 2020. "Distributional synthetic controls," Papers 2001.06118, arXiv.org, revised Dec 2021.

  3. Susanne M. Schennach, 2015. "A bias bound approach to nonparametric inference," CeMMAP working papers 71/15, Institute for Fiscal Studies.

    Cited by:

    1. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    2. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    3. Timothy B. Armstrong & Michal Kolesar, 2014. "A Simple Adjustment for Bandwidth Snooping," Cowles Foundation Discussion Papers 1961R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2015.
    4. 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.
    5. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "Coverage Error Optimal Confidence Intervals for Local Polynomial Regression," Papers 1808.01398, arXiv.org, revised Jul 2021.
    6. Timothy B. Armstrong, 2018. "Adaptation Bounds for Confidence Bands under Self-Similarity," Cowles Foundation Discussion Papers 2146, Cowles Foundation for Research in Economics, Yale University.
    7. Timothy B. Armstrong & Michal Koles�r, 2016. "Optimal Inference in a Class of Regression Models," Cowles Foundation Discussion Papers 2043, Cowles Foundation for Research in Economics, Yale University.
    8. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 767-779, April.
    9. Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
    10. 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.
    11. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
    12. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.
    13. Harold D. Chiang & Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Linear programming approach to nonparametric inference under shape restrictions: with an application to regression kink designs," Papers 2102.06586, arXiv.org.

  4. Susanne M. Schennach & Daniel Wilhelm, 2014. "A simple parametric model selection test," CeMMAP working papers 10/14, Institute for Fiscal Studies.

    Cited by:

    1. Yves Breitmoser, 2021. "Controlling for presentation effects in choice," Quantitative Economics, Econometric Society, vol. 12(1), pages 251-281, January.
    2. de Castro, Luciano & Galvao, Antonio F. & Noussair, Charles N. & Qiao, Liang, 2022. "Do people maximize quantiles?," Games and Economic Behavior, Elsevier, vol. 132(C), pages 22-40.
    3. Senay Sokullu & Christine Valente, 2022. "Individual consumption in collective households: Identification using repeated observations with an application to PROGRESA," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 286-304, March.
    4. Hoshino, Tadao & Yanagi, Takahide, 2023. "Treatment effect models with strategic interaction in treatment decisions," Journal of Econometrics, Elsevier, vol. 236(2).
    5. Beggs, Alan, 2021. "Games with second-order expected utility," Games and Economic Behavior, Elsevier, vol. 130(C), pages 569-590.
    6. Isaiah Andrews & Toru Kitagawa & Adam McCloskey, 2018. "Inference on winners," CeMMAP working papers CWP73/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Yu‐Chin Hsu & Xiaoxia Shi, 2017. "Model‐selection tests for conditional moment restriction models," Econometrics Journal, Royal Economic Society, vol. 20(1), pages 52-85, February.
    8. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    9. Breitmoser, Yves, 2017. "Discrete Choice with Presentation Effects," Rationality and Competition Discussion Paper Series 35, CRC TRR 190 Rationality and Competition.
    10. Koriyama, Yukio & Ozkes, Ali I., 2021. "Inclusive cognitive hierarchy," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 458-480.
    11. Breitmoser, Yves & Schweighofer-Kodritsch, Sebastian, 2019. "Obviousness Around the Clock," Rationality and Competition Discussion Paper Series 151, CRC TRR 190 Rationality and Competition.
    12. Camilo García-Jimeno & Angel Iglesias & Pinar Yildirim, 2022. "Information Networks and Collective Action: Evidence from the Women's Temperance Crusade," American Economic Review, American Economic Association, vol. 112(1), pages 41-80, January.
    13. Isaiah Andrews & Toru Kitagawa & Adam McCloskey, 2020. "Inference after Estimation of Breaks," CeMMAP working papers CWP34/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Breitmoser, Yves, 2016. "Stochastic choice, systematic mistakes and preference estimation," MPRA Paper 72779, University Library of Munich, Germany.
    15. Piao Chen & Zhi‐Sheng Ye & Xun Xiao, 2019. "Pairwise model discrimination with applications in lifetime distributions and degradation processes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(8), pages 675-686, December.
    16. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2020. "Out of sample predictability in predictive regressions with many predictor candidates," UC3M Working papers. Economics 31554, Universidad Carlos III de Madrid. Departamento de Economía.
    17. Francesco Bravo, 2022. "Misspecified semiparametric model selection with weakly dependent observations," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 558-586, July.
    18. Jean-Yves Pitarakis, 2020. "A Novel Approach to Predictive Accuracy Testing in Nested Environments," Papers 2008.08387, arXiv.org, revised Oct 2023.
    19. Santiago Pereda-Fernández, 2021. "Copula-Based Random Effects Models for Clustered Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 575-588, March.
    20. 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.
    21. Breitmoser, Yves & Vorjohann, Pauline, 2022. "Fairness-based Altruism," Center for Mathematical Economics Working Papers 666, Center for Mathematical Economics, Bielefeld University.
    22. 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.
    23. Breitmoser, Yves & Vorjohann, Pauline, 2018. "Welfare-Based Altruism," Rationality and Competition Discussion Paper Series 89, CRC TRR 190 Rationality and Competition.
    24. Xiaoxia Shi, 2015. "A nondegenerate Vuong test," Quantitative Economics, Econometric Society, vol. 6(1), pages 85-121, March.
    25. 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.
    26. Yves Breitmoser & Sebastian Schweighofer-Kodritsch, 2022. "Obviousness around the clock," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 483-513, April.
    27. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  5. Susanne M. Schennach, 2013. "Long memory via networking," CeMMAP working papers 13/13, Institute for Fiscal Studies.

    Cited by:

    1. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," Journal of Econometrics, Elsevier, vol. 236(1).
    2. Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
    3. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    4. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    5. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.
    6. Jia Li & Peter C. B. Phillips & Shuping Shi & Jun Yu, 2022. "Weak Identification of Long Memory with Implications for Inference," Cowles Foundation Discussion Papers 2334, Cowles Foundation for Research in Economics, Yale University.
    7. Daron Acemoglu & Ufuk Akcigit & William Kerr, 2016. "Networks and the Macroeconomy: An Empirical Exploration," NBER Macroeconomics Annual, University of Chicago Press, vol. 30(1), pages 273-335.
    8. Chevillon, G. & Hecq, A.W. & Laurent, S.F.J.A., 2015. "Long memory through marginalization of large systems and hidden cross-section dependence," Research Memorandum 014, Maastricht University, Graduate School of Business and Economics (GSBE).
    9. Susanne M. Schennach, 2013. "Long memory via networking," CeMMAP working papers CWP13/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. John Barrdear, 2014. "Peering into the mist: social learning over an opaque observation network," Discussion Papers 1409, Centre for Macroeconomics (CFM).
    11. Hongwei Chuang, 2015. "Correlation Persistence in Financial Markets: A Network Theory Approach," DSSR Discussion Papers 33, Graduate School of Economics and Management, Tohoku University.
    12. Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.
    13. Tommaso Proietti & Federico Maddanu, 2021. "Modelling Cycles in Climate Series: the Fractional Sinusoidal Waveform Process," CEIS Research Paper 518, Tor Vergata University, CEIS, revised 19 Oct 2021.
    14. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," CREATES Research Papers 2019-02, Department of Economics and Business Economics, Aarhus University.
    15. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.
    16. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    17. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," Discussion Papers 19/01, University of Nottingham, Granger Centre for Time Series Econometrics.

  6. Susanne M. Schennach, 2013. "Entropic Latent Variable Integration via Simulation," CeMMAP working papers 32/13, Institute for Fiscal Studies.

    Cited by:

    1. Isaiah Andrews & Anna Mikusheva, 2016. "Conditional Inference With a Functional Nuisance Parameter," Econometrica, Econometric Society, vol. 84, pages 1571-1612, July.
    2. Bernstein, David H. & Parmeter, Christopher F. & Tsionas, Mike G., 2023. "On the performance of the United States nuclear power sector: A Bayesian approach," Energy Economics, Elsevier, vol. 125(C).
    3. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    4. Taisuke Otsu & Martin Pesendorfer & Yuya Sasaki & Yuya Takahashi, 2020. "Estimation of (static or dynamic) games under equilibrium multiplicity," STICERD - Econometrics Paper Series 611, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    5. Manuel A. Domínguez & Ignacio N. Lobato, 2020. "Specification testing with estimated variables," Econometric Reviews, Taylor & Francis Journals, vol. 39(5), pages 476-494, May.
    6. 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.
    7. Dongwoo Kim & Daniel Wilhelm, 2017. "Powerful t-Tests in the presence of nonclassical measurement error," CeMMAP working papers CWP57/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Komunjer, Ivana & Ragusa, Giuseppe, 2016. "Existence And Characterization Of Conditional Density Projections," Econometric Theory, Cambridge University Press, vol. 32(4), pages 947-987, August.
    9. 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.
    10. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.
    11. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.
    12. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.
    13. De Silva, Dakshina G. & Hubbard, Timothy P. & Schiller, Anita R. & Tsionas, Mike G., 2023. "Estimating outcomes in the presence of endogeneity and measurement error with an application to R&D," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 278-294.
    14. Victor H. Aguiar & Nail Kashaev, 2018. "Stochastic Revealed Preferences with Measurement Error," Papers 1810.05287, arXiv.org, revised Sep 2020.
    15. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers 40/15, Institute for Fiscal Studies.
    16. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    17. 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.
    18. Taisuke Otsu & Martin Pesendorfer, 2021. "Equilibrium multiplicity in dynamic games: testing and estimation," STICERD - Econometrics Paper Series 618, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    19. Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Taisuke Otsu & Martin Pesendorfer, 2023. "Equilibrium multiplicity in dynamic games: Testing and estimation," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 26-42.
    21. Stéphane Bonhomme & Martin Weidner, 2022. "Minimizing sensitivity to model misspecification," Quantitative Economics, Econometric Society, vol. 13(3), pages 907-954, July.
    22. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    23. Shuowen Chen, 2022. "Indirect Inference for Nonlinear Panel Models with Fixed Effects," Papers 2203.10683, arXiv.org, revised Apr 2022.
    24. Florian Gunsilius, 2019. "A path-sampling method to partially identify causal effects in instrumental variable models," Papers 1910.09502, arXiv.org, revised Jun 2020.
    25. Jun, Sung Jae & Pinkse, Joris, 2020. "Counterfactual prediction in complete information games: Point prediction under partial identification," Journal of Econometrics, Elsevier, vol. 216(2), pages 394-429.
    26. Gagliardini, Patrick & Gouriéroux, Christian, 2019. "Identification by Laplace transforms in nonlinear time series and panel models with unobserved stochastic dynamic effects," Journal of Econometrics, Elsevier, vol. 208(2), pages 613-637.
    27. 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.
    28. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.
    29. Isaiah Andrews & Anna Mikusheva, 2016. "Conditional Inference With a Functional Nuisance Parameter," Econometrica, Econometric Society, vol. 84(4), pages 1571-1612, July.
    30. Timothy Christensen & Benjamin Connault, 2023. "Counterfactual Sensitivity and Robustness," Econometrica, Econometric Society, vol. 91(1), pages 263-298, January.
    31. Florian Gunsilius & Susanne M. Schennach, 2019. "Independent nonlinear component analysis," CeMMAP working papers CWP46/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  7. Susanne M. Schennach, 2013. "Regressions with Berkson errors in covariates - A nonparametric approach," Papers 1308.2836, arXiv.org.

    Cited by:

    1. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    2. 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.
    3. Dubois, Pierre & Griffith, Rachel & O'Connell, Martin, 2017. "How well targeted are soda taxes?," CEPR Discussion Papers 12484, C.E.P.R. Discussion Papers.
    4. Pei Geng & Hira L. Koul, 2019. "Minimum distance model checking in Berkson measurement error models with validation data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 879-899, September.
    5. Chuanlong Xie & Lixing Zhu, 2018. "A minimum projected-distance test for parametric single-index Berkson models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 700-715, September.
    6. 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.
    7. Katharina Proksch & Nicolai Bissantz & Hajo Holzmann, 2022. "Simultaneous inference for Berkson errors-in-variables regression under fixed design," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 773-800, August.
    8. D’Haultfœuille, Xavier & Février, Philippe, 2015. "Identification of mixture models using support variations," Journal of Econometrics, Elsevier, vol. 189(1), pages 70-82.
    9. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    10. Sriya Iyer & Chander Velu & Melvyn Weeks, 2014. "Divine Competition: Religious Organisations and Service Provision in India," Cambridge Working Papers in Economics 1409, Faculty of Economics, University of Cambridge.
    11. Cornelis J. Potgieter & Rubin Wei & Victor Kipnis & Laurence S. Freedman & Raymond J. Carroll, 2016. "Moment reconstruction and moment‐adjusted imputation when exposure is generated by a complex, nonlinear random effects modeling process," Biometrics, The International Biometric Society, vol. 72(4), pages 1369-1377, December.

  8. Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers 46/13, Institute for Fiscal Studies.

    Cited by:

    1. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    2. Manuel Arellano & Stéphane Bonhomme, 2019. "Recovering Latent Variables by Matching," Working Papers wp2019_1914, CEMFI.
    3. Felt, Marie-Hélène, 2020. "On the identification of joint distributions using marginals and aggregates," Economics Letters, Elsevier, vol. 194(C).
    4. Hao Dong & Taisuke Otsu & Luke Taylor, 2022. "Nonparametric estimation of additive models with errors-in-variables," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1164-1204, November.
    5. Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022. "Estimation of varying coefficient models with measurement error," Journal of Econometrics, Elsevier, vol. 230(2), pages 388-415.
    6. Adusumilli, Karun & Kurisu, Daisies & Otsu, Taisuke & Whang, Yoon-Jae, 2020. "Inference on distribution functions under measurement error," LSE Research Online Documents on Economics 102692, London School of Economics and Political Science, LSE Library.
    7. Hao Dong & Daniel L. Millimet, 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," Departmental Working Papers 2013, Southern Methodist University, Department of Economics.
    8. Botosaru, Irene, 2023. "Time-varying unobserved heterogeneity in earnings shocks," Journal of Econometrics, Elsevier, vol. 235(2), pages 1378-1393.
    9. Ben-Moshe, Dan, 2018. "Identification Of Joint Distributions In Dependent Factor Models," Econometric Theory, Cambridge University Press, vol. 34(1), pages 134-165, February.
    10. Adusumilli, Karun & Kurisu, Daisuke & Otsu, Taisuke & Whang, Yoon-Jae, 2020. "Inference on distribution functions under measurement error," Journal of Econometrics, Elsevier, vol. 215(1), pages 131-164.
    11. Christian Gourieroux & Joann Jasiak, 2023. "Dynamic deconvolution and identification of independent autoregressive sources," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 151-180, March.
    12. Chen, Xiaohong & Linton, Oliver & Yi, Yanping, 2017. "Semiparametric identification of the bid–ask spread in extended Roll models," Journal of Econometrics, Elsevier, vol. 200(2), pages 312-325.
    13. Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.

  9. Susanne M. Schennach & Yingyao Hu, 2012. "Nonparametric identification and semiparametric estimation of classical measurement error models without side information," CeMMAP working papers 40/12, Institute for Fiscal Studies.

    Cited by:

    1. Hahn, Jinyong & Hausman, Jerry & Kim, Jeonghwan, 2021. "A small sigma approach to certain problems in errors-in-variables models," Economics Letters, Elsevier, vol. 208(C).
    2. Pierre‐André Chiappori & Ju Hyun Kim, 2017. "A note on identifying heterogeneous sharing rules," Quantitative Economics, Econometric Society, vol. 8(1), pages 201-218, March.
    3. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    4. Aurélie Bertrand & Ingrid Van Keilegom & Catherine Legrand, 2019. "Flexible parametric approach to classical measurement error variance estimation without auxiliary data," Biometrics, The International Biometric Society, vol. 75(1), pages 297-307, March.
    5. Layla Parast & Tanya P. Garcia & Ross L. Prentice & Raymond J. Carroll, 2022. "Robust methods to correct for measurement error when evaluating a surrogate marker," Biometrics, The International Biometric Society, vol. 78(1), pages 9-23, March.
    6. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    7. Erickson, Timothy & Jiang, Colin Huan & Whited, Toni M., 2014. "Minimum distance estimation of the errors-in-variables model using linear cumulant equations," Journal of Econometrics, Elsevier, vol. 183(2), pages 211-221.
    8. Arthur Lewbel, 2020. "Kotlarski with a Factor Loading," Boston College Working Papers in Economics 1001, Boston College Department of Economics, revised 15 Dec 2020.
    9. Susanne M. Schennach, 2013. "Entropic Latent Variable Integration via Simulation," CeMMAP working papers CWP32/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. 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).
    11. Andrew Chesher, 2017. "Understanding the effect of measurement error on quantile regressions," CeMMAP working papers CWP19/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Hu, Yingyao & Schennach, Susanne & Shiu, Ji-Liang, 2022. "Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 226(2), pages 269-294.
    13. Garcia, Tanya P. & Ma, Yanyuan, 2017. "Simultaneous treatment of unspecified heteroskedastic model error distribution and mismeasured covariates for restricted moment models," Journal of Econometrics, Elsevier, vol. 200(2), pages 194-206.
    14. Hao Dong & Yuya Sasaki, 2022. "Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving," Papers 2209.05914, arXiv.org.
    15. 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.
    16. 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.
    17. Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Average Derivative Estimation Under Measurement Error," Departmental Working Papers 1901, Southern Methodist University, Department of Economics.
    18. 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.
    19. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers 34/15, Institute for Fiscal Studies.
    20. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.
    21. Hong Li & Qifan Song & Jianxi Su, 2021. "Robust estimates of insurance misrepresentation through kernel quantile regression mixtures," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 625-663, September.
    22. Ben-Moshe, Dan, 2018. "Identification Of Joint Distributions In Dependent Factor Models," Econometric Theory, Cambridge University Press, vol. 34(1), pages 134-165, February.
    23. Hahn, Jinyong & Ridder, Geert, 2017. "Instrumental variable estimation of nonlinear models with nonclassical measurement error using control variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 238-250.
    24. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. Stefan Hoderlein & Bettina Siflinger & Joachim Winter, 2015. "Identification of structural models in the presence of measurement error due to rounding in survey responses," Boston College Working Papers in Economics 869, Boston College Department of Economics.
    26. Andrei Zeleneev & Kirill Evdokimov, 2023. "Simple estimation of semiparametric models with measurement errors," CeMMAP working papers 10/23, Institute for Fiscal Studies.
    27. Kirill S. Evdokimov & Andrei Zeleneev, 2023. "Simple Estimation of Semiparametric Models with Measurement Errors," Papers 2306.14311, arXiv.org, revised Mar 2024.
    28. Bertrand, Aurelie & Van Keilegom, Ingrid & Legrand, Catherine, 2017. "Flexible parametric approach to classical measurement error variance estimation without auxiliary data," LIDAM Discussion Papers ISBA 2017025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    29. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    30. Jingxuan Luo & Lili Yue & Gaorong Li, 2023. "Overview of High-Dimensional Measurement Error Regression Models," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
    31. 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.
    32. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers 03/15, Institute for Fiscal Studies.
    33. An, Yonghong & Hong, Shengjie & Zhang, Daiqiang, 2023. "A structural analysis of simple contracts," Journal of Econometrics, Elsevier, vol. 236(2).
    34. 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.
    35. Kirill Evdokimov & Andrei Zeleneev, 2024. "Simple estimation of semiparametric models with measurement errors," CeMMAP working papers 05/24, Institute for Fiscal Studies.
    36. Nikolay Gospodinov & Ivana Komunjer & Serena Ng, 2014. "Minimum Distance Estimation of Dynamic Models with Errors-In-Variables," FRB Atlanta Working Paper 2014-11, Federal Reserve Bank of Atlanta.
    37. 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.
    38. Tom Boot & Art=uras Juodis, 2023. "Uniform Inference in Linear Error-in-Variables Models: Divide-and-Conquer," Papers 2301.04439, arXiv.org.
    39. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers CWP03/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    40. Yingyao Hu & Jiaxiong Yao, 2019. "Illuminating Economic Growth," IMF Working Papers 2019/077, International Monetary Fund.

  10. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.

    Cited by:

    1. Pedro Carneiro & Michael Lokshin & Nithin Umapathi, 2017. "Average and Marginal Returns to Upper Secondary Schooling in Indonesia," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 16-36, January.
    2. José M.R. Murteira, 2018. "Copula-based Tests for Nonclassical Measurement Error – The Case of Fractional Random Variables," CeBER Working Papers 2018-13, Centre for Business and Economics Research (CeBER), University of Coimbra.
    3. Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2023. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1265-1303.
    4. Dongwoo Kim & Daniel Wilhelm, 2017. "Powerful t-Tests in the presence of nonclassical measurement error," CeMMAP working papers CWP57/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. von Gaudecker, Hans-Martin & Drerup, Tilman & Enke, Benjamin, 2015. "Measurement Error in Subjective Expectations and the Empirical Content of Economic Models," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112871, Verein für Socialpolitik / German Economic Association.
    6. Manuel Arellano & Stéphane Bonhomme, 2019. "Recovering Latent Variables by Matching," Working Papers wp2019_1914, CEMFI.
    7. 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.
    8. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
    9. Naoki Wakamori & Angelika Welte, 2012. "Why Do Shoppers Use Cash? Evidence from Shopping Diary Data," Staff Working Papers 12-24, Bank of Canada.
    10. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
    11. Boonsaeng, Tullaya & Carpio, Carlos E., 2015. "Data Collection Period and Food Demand System Estimation using Cross Sectional Data," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205576, Agricultural and Applied Economics Association.
    12. Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Ben-Moshe, Dan, 2018. "Identification Of Joint Distributions In Dependent Factor Models," Econometric Theory, Cambridge University Press, vol. 34(1), pages 134-165, February.
    14. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    15. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Stefan Hoderlein & Bettina Siflinger & Joachim Winter, 2015. "Identification of structural models in the presence of measurement error due to rounding in survey responses," Boston College Working Papers in Economics 869, Boston College Department of Economics.
    17. Giovanni Compiani & Yuichi Kitamura, 2016. "Using mixtures in econometric models: a brief review and some new results," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 95-127, October.
    18. Takahide Yanagi, 2014. "The Effect of Measurement Error in the Sharp Regression Discontinuity Design," KIER Working Papers 910, Kyoto University, Institute of Economic Research.
    19. Hu, Yingyao & Sasaki, Yuya, 2015. "Closed-form estimation of nonparametric models with non-classical measurement errors," Journal of Econometrics, Elsevier, vol. 185(2), pages 392-408.

  11. Flavio Cunha & James Heckman & Susanne M. Schennach, 2010. "Estimating the technology of cognitive and noncognitive skill formation," CeMMAP working papers CWP09/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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    1. Rosa, Leonardo & Martins, Marcelo & Carnoy, Martin, 2019. "Achievement gains from reconfiguring early schooling: The case of Brazil's primary education reform," Economics of Education Review, Elsevier, vol. 68(C), pages 1-12.
    2. Rossi, Federico, 2020. "Human Capital and Macro-Economic Development : A Review of the Evidence," The Warwick Economics Research Paper Series (TWERPS) 1246, University of Warwick, Department of Economics.
    3. Valerio Mendoza, Octasiano Miguel & Borsi, Mihály Tamás & Comim, Flavio, 2022. "Human capital dynamics in China: Evidence from a club convergence approach," Journal of Asian Economics, Elsevier, vol. 79(C).
    4. Achyuta Adhvaryu & Namrata Kala & Anant Nyshadham, 2018. "The Skills to Pay the Bills: Returns to On-the-job Soft Skills Training," NBER Working Papers 24313, National Bureau of Economic Research, Inc.
    5. Steven Lehrer, 2019. "How skills and parental valuation of education influence human capital acquisition and early labor market return to human capital in Canada," Working Paper 1416, Economics Department, Queen's University.
    6. Landerso, Rasmus & Heckman, James J., 2016. "The Scandinavian Fantasy: The Sources of Intergenerational Mobility in Denmark and the U.S," IZA Discussion Papers 10000, Institute of Labor Economics (IZA).
    7. Martin Schlotter, 2011. "Age at Preschool Entrance and Noncognitive Skills before School - An Instrumental Variable Approach," ifo Working Paper Series 112, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    8. Getik, Demid & Meier, Armando N., 2022. "Peer gender and mental health⁎," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 643-659.
    9. James J. Heckman & Tomas Jagelka & Tim Kautz, 2019. "Some Contributions of Economics to the Study of Personality," Working Papers 2019-069, Human Capital and Economic Opportunity Working Group.
    10. Doepke, M. & Tertilt, M., 2016. "Families in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1789-1891, Elsevier.
    11. Elizabeth M. Caucutt & Lance Lochner & Youngmin Park, 2015. "Correlation, Consumption, Confusion, or Constraints: Why do Poor Children Perform so Poorly?," NBER Working Papers 21023, National Bureau of Economic Research, Inc.
    12. Suzanne Bellue, 2024. "Why Don’t Poor Families Move? A Spatial Equilibrium Analysis of Parental Decisions with Social Learning," Working Papers 2024-07, Center for Research in Economics and Statistics.
    13. Tarek Azzam & Michael Bates & David Fairris, 2020. "Do Learning Communities Increase First Year College Retention? Testing Sample Selection and External Validity of Randomized Control Trials," Working Papers 202022, University of California at Riverside, Department of Economics, revised Jul 2020.
    14. Kelly Chen & Lars Osberg & Shelley Phipps, 2019. "Unequal opportunities and public policy: The impact of parental disability benefits on child postsecondary attendance," Canadian Journal of Economics, Canadian Economics Association, vol. 52(4), pages 1401-1432, November.
    15. James J. Heckman & Colleen P. Loughlin, 2021. "Are Student-Athletes Exploited?," NBER Working Papers 29072, National Bureau of Economic Research, Inc.
    16. Ismael Mourifie & Marc Henry & Romuald Meango, 2017. "Sharp bounds and testability of a Roy model of STEM major choices," Papers 1709.09284, arXiv.org, revised Nov 2019.
    17. Gizem Koşar & Cormac O'Dea, 2022. "Expectations Data in Structural Microeconomic Models," Staff Reports 1018, Federal Reserve Bank of New York.
    18. Valentina Conti & Joanna Kopinska, 2012. "The Role of Parental Cognitive Aging in the Intergenerational Mobility of Cognitive Abilities," CEIS Research Paper 219, Tor Vergata University, CEIS, revised 30 Jan 2012.
    19. Ravi Kanbur, 2020. "Inequality in a Global Perspective," Working Papers id:13083, eSocialSciences.
    20. Papageorge, Nicholas W. & Gershenson, Seth & Kang, Kyungmin, 2016. "Teacher Expectations Matter," IZA Discussion Papers 10165, Institute of Labor Economics (IZA).
    21. Sevim, Dilek & Baranov, Victoria & Bhalotra, Sonia R. & Maselko, Joanna & Biroli, Pietro, 2023. "Socioemotional Skills in Early Childhood: Evidence from a Maternal Psychosocial Intervention," IZA Discussion Papers 15925, Institute of Labor Economics (IZA).
    22. Tahir Andrabi & Jishnu Das & Asim Ijaz Khwaja & Tristan Zajonc, 2011. "Do Value-Added Estimates Add Value? Accounting for Learning Dynamics," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 29-54, July.
    23. Karthik Muralidharan & Abhijeet Singh & Alejandro J. Ganimian, 2019. "Disrupting Education? Experimental Evidence on Technology-Aided Instruction in India," American Economic Review, American Economic Association, vol. 109(4), pages 1426-1460, April.
    24. Ghazala Azmat & Katja Maria Kaufmann, 2021. "Formation of College Plans: Expected Returns, Preferences and Adjustment Process," Working Papers hal-03812823, HAL.
    25. Dercon, Stefan & Sánchez, Alan, 2012. "Undernutrition and Psychosocial Competencies: Evidence from Four Countries," CEPR Discussion Papers 9032, C.E.P.R. Discussion Papers.
    26. Agostinelli,Francesco & Avitabile,Ciro & Bobba,Matteo, 2021. "Enhancing Human Capital in Children : A Case Study on Scaling," Policy Research Working Paper Series 9647, The World Bank.
    27. Johannes Abeler & Armin Falk & Fabian Kosse, 2021. "Malleability of Preferences for Honesty," Working Papers 2021-021, Human Capital and Economic Opportunity Working Group.
    28. Jorge Calero & Rosario Ivano Scandurra, 2016. "Modelling adult skills in OECD countries," Working Papers 2016/17, Institut d'Economia de Barcelona (IEB).
    29. Thiel, Hendrik & Thomsen, Stephan L., 2009. "Noncognitive skills in economics: Models, measurement, and empirical evidence," ZEW Discussion Papers 09-076, ZEW - Leibniz Centre for European Economic Research.
    30. Jared N. Schachner & Robert J. Sampson, 2020. "Skill-Based Contextual Sorting: How Parental Cognition and Residential Mobility Produce Unequal Environments for Children," Demography, Springer;Population Association of America (PAA), vol. 57(2), pages 675-703, April.
    31. Hélène Le Forner, 2020. "Parents’ Separation: What Is The Effect On Parents’ and Children’s Time Investments?," Working Papers halshs-02937830, HAL.
    32. Sanz-de-Galdeano, Anna & Terskaya, Anastasia, 2019. "Sibling Differences in Educational Polygenic Scores: How Do Parents React?," IZA Discussion Papers 12375, Institute of Labor Economics (IZA).
    33. Elena Mattana & Juanna Joensen, 2016. "Student Aid, Academic Achievement, and Labor Market Behavior," 2016 Meeting Papers 1102, Society for Economic Dynamics.
    34. Palaash Bhargava & Daniel L. Chen & Matthias Sutter & Camille Terrier, 2023. "Homophily and Transmission of Behavioral Traits in Social Networks," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2023_02, Max Planck Institute for Research on Collective Goods.
    35. Anna-Elisabeth Thum, 2014. "Labor Market Integration of German Immigrants and Their Children: Does Personality Matter?," SOEPpapers on Multidisciplinary Panel Data Research 723, DIW Berlin, The German Socio-Economic Panel (SOEP).
    36. Charles Ka Yui Leung & Joe Cho Yiu Ng, 2018. "Macro Aspects of Housing," Globalization Institute Working Papers 340, Federal Reserve Bank of Dallas.
    37. García, Jorge Luis & Heckman, James J., 2022. "Parenting Promotes Social Mobility Within and Across Generations," IZA Discussion Papers 15672, Institute of Labor Economics (IZA).
    38. Yonghong An & Wang Le & Ruli Xiao, 2015. "Your American Dream is Not Mine! A New Approach to Estimating Intergenerational Mobility Elasticities," CAEPR Working Papers 2015-016, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    39. Falk, Armin & Kosse, Fabian & Schildberg-Hörisch, Hannah & Zimmermann, Florian, 2020. "Self-assessment: The role of the social environment," DICE Discussion Papers 339, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    40. Richard Akresh & Sonia Bhalotra & Marinella Leone & Una Osili, 2017. "Hunger Games: First and Second Generation Impacts of the Biafran War," HiCN Working Papers 254, Households in Conflict Network.
    41. Dinarte Diaz,Lelys Ileana & Egana-delSol,Pablo & Martinez A.,Claudia, 2022. "Socioemotional Skills Development in Highly Violent Contexts : Measurements and Impacts," Policy Research Working Paper Series 9957, The World Bank.
    42. Susanne Schennach & James Heckman & Flavio Cunha, 2007. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," 2007 Meeting Papers 973, Society for Economic Dynamics.
    43. Andrews, Rodney J. & Imberman, Scott A. & Lovenheim, Michael F., 2020. "Recruiting and supporting low-income, high-achieving students at flagship universities," Economics of Education Review, Elsevier, vol. 74(C).
    44. Ginja, Rita & Jans, Jenny & Karimi, Arizo, 2017. "Parental Investments in Early Life and Child Outcomes: Evidence from Swedish Parental Leave Rules," IZA Discussion Papers 11106, Institute of Labor Economics (IZA).
    45. Yann Algan & Elizabeth Beasley & Frank Vitaro & Richard Tremblay, 2014. "The Impact of Non-Cognitive Skills Training on Academic and Non-academic Trajectories: From Childhood to Early Adulthood," Sciences Po publications info:hdl:2441/6s39gt704s9, Sciences Po.
    46. Bhalotra, Sonia R. & Delavande, Adeline & Gilabert, Paulino Font & Maselko, Joanna, 2020. "Maternal Investments in Children: The Role of Expected Effort and Returns," IZA Discussion Papers 13056, Institute of Labor Economics (IZA).
    47. Deborah A. Cobb-Clark & Nicolás Salamanca & Anna Zhu, 2019. "Parenting style as an investment in human development," Journal of Population Economics, Springer;European Society for Population Economics, vol. 32(4), pages 1315-1352, October.
    48. Eric A. Hanushek & Lavinia Kinne & Philipp Lergetporer & Ludger Woessmann, 2020. "Culture and Student Achievement: The Intertwined Roles of Patience and Risk-Taking," NBER Working Papers 27484, National Bureau of Economic Research, Inc.
    49. Hendrik Jürges & Alexandra Schwarz & Sorel Cahan & Ziad Abdeen, 2019. "Child mental health and cognitive development: evidence from the West Bank," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(3), pages 423-442, August.
    50. Baert, Stijn & Picchio, Matteo, 2020. "A Signal of (Train)ability? Grade Repetition and Hiring Chances," GLO Discussion Paper Series 598, Global Labor Organization (GLO).
    51. Peter A. Savelyev & Kegon T. K. Tan, 2019. "Socioemotional Skills, Education, and Health-Related Outcomes of High-Ability Individuals," American Journal of Health Economics, University of Chicago Press, vol. 5(2), pages 250-280, Spring.
    52. Eriksson, Tor & Kristensen, Nicolai, 2010. "Wages or Fringes? Some Evidence on Trade-offs and Sorting," Working Papers 10-16, University of Aarhus, Aarhus School of Business, Department of Economics.
    53. Benjamin Faber & Rosa Sanchis-Guarner & Felix Weinhardt, 2015. "ICT and Education: Evidence from Student Home Addresses," NBER Working Papers 21306, National Bureau of Economic Research, Inc.
    54. Joseph Price & Luke P. Rodgers & Jocelyn S. Wikle, 2021. "Dinner timing and human capital investments in children," Review of Economics of the Household, Springer, vol. 19(4), pages 1047-1075, December.
    55. Britto, Diogo & Melo, Caique & Sampaio, Breno, 2022. "The Kids Aren't Alright: Parental Job Loss and Children's Outcomes Within and Beyond Schools," CEPR Discussion Papers 17562, C.E.P.R. Discussion Papers.
    56. Marc K. Chan & Kai Liu, 2018. "Life‐cycle and intergenerational effects of child care reforms," Quantitative Economics, Econometric Society, vol. 9(2), pages 659-706, July.
    57. Xiang Ao & Xuan Chen & Zhong Zhao, 2021. "Is Care by Grandparents or Parents Better for Children's Non-cognitive Skills? Evidence on Locus of Control from China," Working Papers 2021-010, Human Capital and Economic Opportunity Working Group.
    58. Timothy N. Bond & Kevin Lang, 2013. "The Evolution of the Black-White Test Score Gap in Grades K–3: The Fragility of Results," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1468-1479, December.
    59. Chao Fu & Nicolás Grau & Jorge Rivera, 2022. "Wandering astray: Teenagers' choices of schooling and crime," Quantitative Economics, Econometric Society, vol. 13(2), pages 387-424, May.
    60. Eric A. Hanushek & Babs Jacobs & Guido Schwerdt & Rolf van der Velden & Stan Vermeulen & Simon Wiederhold, 2021. "Where Do STEM Graduates Stem From? The Intergenerational Transmission of Comparative Skill Advantages," CESifo Working Paper Series 9388, CESifo.
    61. N. Luotonen & V. Puttonen & E. Rantapuska, 2022. "Ability, Educational Attainment, and Household Financial Distress," Journal of Consumer Policy, Springer, vol. 45(4), pages 655-672, December.
    62. Rasmussen, Astrid Würtz, 2010. "Increasing the length of parents' birth-related leave: The effect on children's long-term educational outcomes," Labour Economics, Elsevier, vol. 17(1), pages 91-100, January.
    63. Pietro Biroli & Titus Galama & Stephanie von Hinke & Hans van Kippersluis & Kevin Thom, 2022. "Economics and Econometrics of Gene-Environment Interplay," Bristol Economics Discussion Papers 22/759, School of Economics, University of Bristol, UK.
    64. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    65. Ye, Maoliang & Yi, Junjian, 2017. "Parental preferences, production technologies, and provision for progeny," Journal of Comparative Economics, Elsevier, vol. 45(2), pages 261-270.
    66. Zhang, Jing & Xu, Lixin Colin, 2016. "The long-run effects of treated water on education: The rural drinking water program in China," Journal of Development Economics, Elsevier, vol. 122(C), pages 1-15.
    67. Bratti, Massimiliano & Mendola, Mariapia, 2011. "Parental Health and Child Schooling," IZA Discussion Papers 5870, Institute of Labor Economics (IZA).
    68. Serap Sagir & Çağaçan Değer & Durdane Sirin Saracoglu, 2023. "The Growth Effects of Alternative Early Childhood Development Investment Policies in the Turkish Economy," ERC Working Papers 2304, ERC - Economic Research Center, Middle East Technical University, revised Nov 2023.
    69. Favara, Marta & Porter, Catherine & Woldehanna, Tassew, 2017. "Smarter through Social Protection? Evaluating the Impact of Ethiopia's Safety-Net on Child Cognitive Abilities," IZA Discussion Papers 10972, Institute of Labor Economics (IZA).
    70. Miroslav Verbič & Nela Kačmarčik-Maduna, 2018. "Child Well-being in Transition Countries as an Intergenerational Investment in the Development of Human Capital," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 11(4), pages 1077-1105, August.
    71. Sarah Cattan & Daniel A. Kamhöfer & Martin Karlsson & Therese Nilsson, 2017. "The short- and long-term effects of student absence: evidence from Sweden," IFS Working Papers W17/21, Institute for Fiscal Studies.
    72. Douglas Almond & Janet Currie & Valentina Duque, 2017. "Childhood Circumstances and Adult Outcomes: Act II," Working Papers 2017-082, Human Capital and Economic Opportunity Working Group.
    73. Hendrik Jürges & Sophie-Charlotte Meyer, 2020. "Cognitive ability and teen smoking," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(2), pages 287-296, March.
    74. Orazio Attanasio & Richard Blundell & Gabriella Conti & Giacomo Mason, 2018. "Inequality in Socio-emotional Skills: A Cross-Cohort Comparison," NBER Chapters, in: Inequality and Public Policy, Trans-Atlantic Public Economics Seminar 2018, National Bureau of Economic Research, Inc.
    75. Dionissi Aliprantis & Daniel R. Carroll, 2018. "Neighborhood dynamics and the distribution of opportunity," Quantitative Economics, Econometric Society, vol. 9(1), pages 247-303, March.
    76. Jacobs, Babs & van der Velden, Rolf, 2021. "Exploring the uncharted waters of educational mobility: The role of key skills," ROA Research Memorandum 006, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    77. Jin Zhou & James J. Heckman & Bei Liu & Mai Lu & Susan M. Chang & Sally Grantham-McGregor, 2022. "Comparing China REACH and the Jamaica Home Visiting Program," NBER Working Papers 30529, National Bureau of Economic Research, Inc.
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    79. Mounu Prem & Juan F. Vargas & Olga Namen, 2023. "The Human Capital Peace Dividend," Journal of Human Resources, University of Wisconsin Press, vol. 58(3), pages 962-1002.
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    1075. Assaad, Ragui & Aydemir, Abdurrahman B. & Dayioglu-Tayfur, Meltem & Kirdar, Murat Güray, 2023. "Wage Returns to Human Capital Resulting from an Extra Year of Primary School: Evidence from Egypt," IZA Discussion Papers 16037, Institute of Labor Economics (IZA).
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    1186. Juan Felipe Brando & Rafael J. Santos, 2015. "La Nina y los ninos: Effects of an Unexpected Winter on Early Life Human Capital and Family Responses," Documentos CEDE 13316, Universidad de los Andes, Facultad de Economía, CEDE.
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    1191. Jim Been & Anne C. Gielen & Marike Knoef & Gloria Moroni, 2022. "Prolonged worklife among grandfathers: Spillover effects on grandchildren's educational outcomes," Tinbergen Institute Discussion Papers 22-033/V, Tinbergen Institute.
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    1195. Eckstein, Zvi & Botticini, Maristella & Vaturi, Anat, 2018. "Child Care and Human Development: Insights from Jewish History in Central and Eastern Europe, 1500–1930," CEPR Discussion Papers 13178, C.E.P.R. Discussion Papers.
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    1199. Haelermans, Carla & Ghysels, Joris, 2019. "Effectively Involving Low-SES Parents in Human Capital Development: Evidence from a Field Experiment," Research Memorandum 025, Maastricht University, Graduate School of Business and Economics (GSBE).
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    1399. Biewen, Martin & Tapalaga, Madalina, 2017. "Life-cycle educational choices in a system with early tracking and ‘second chance’ options," Economics of Education Review, Elsevier, vol. 56(C), pages 80-94.
    1400. Araujo P., María Daniela & Quis, Johanna Sophie, 2021. "Teacher Effects in Germany: Evidence from Elementary School," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242457, Verein für Socialpolitik / German Economic Association.
    1401. Douglas Scott & Jennifer Lopez & Alan Sánchez & Jere Behrman, 2022. "The impact of the JUNTOS conditional cash transfer programme on foundational cognitive skills: Does age of enrollment matter?," PIER Working Paper Archive 22-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

  12. 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.

    Cited by:

    1. Bonhomme, Stphane & Robin, Jean-Marc, 2009. "Consistent noisy independent component analysis," Journal of Econometrics, Elsevier, vol. 149(1), pages 12-25, April.
    2. Andrea Neri & Roberta Zizza, 2010. "Income reporting behaviour in sample surveys," Temi di discussione (Economic working papers) 777, Bank of Italy, Economic Research and International Relations Area.

  13. Susanne Schennach & Halbert White & Karim Chalak, 2007. "Local Indirect Least Squares and Average Marginal Effects in Nonseparable Structural Systems," Boston College Working Papers in Economics 680, Boston College Department of Economics, revised 26 Dec 2009.

    Cited by:

    1. 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.
    2. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    3. 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.
    4. James J. Heckman, 2010. "Building Bridges between Structural and Program Evaluation Approaches to Evaluating Policy," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 356-398, June.
    5. Joeri Smits & Jeffrey S. Racine, 2013. "Testing Exclusion Restrictions in Nonseparable Triangular Models," Department of Economics Working Papers 2013-02, McMaster University.
    6. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    7. 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.
    8. Taylor, Luke & Otsu, Taisuke, 2016. "Estimation of nonseparable models with censored dependent variables and endogenous regressors," LSE Research Online Documents on Economics 68678, London School of Economics and Political Science, LSE Library.
    9. Hao Dong & Yuya Sasaki, 2022. "Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving," Papers 2209.05914, arXiv.org.
    10. 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.
    11. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
    12. Kasy, Maximilian, "undated". "Instrumental variables with unrestricted heterogeneity and continuous treatment - DON'T CITE! SEE ERRATUM BELOW," Working Paper 33257, Harvard University OpenScholar.
    13. Santos, Andres, 2011. "Instrumental variable methods for recovering continuous linear functionals," Journal of Econometrics, Elsevier, vol. 161(2), pages 129-146, April.
    14. 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.
    15. James J. Heckman & John Eric Humphries & Gregory Veramendi, 2018. "Returns to Education: The Causal Effects of Education on Earnings, Health, and Smoking," Journal of Political Economy, University of Chicago Press, vol. 126(S1), pages 197-246.
    16. Halbert White & Karim Chalak, 2013. "Identification and Identification Failure for Treatment Effects Using Structural Systems," Econometric Reviews, Taylor & Francis Journals, vol. 32(3), pages 273-317, November.
    17. Karim Chalak & Halbert White, 2007. "An Extended Class of Instrumental Variables for the Estimation of Causal Effects," Boston College Working Papers in Economics 692, Boston College Department of Economics, revised 30 Nov 2009.
    18. Florian Gunsilius, 2018. "Point-identification in multivariate nonseparable triangular models," Papers 1806.09680, arXiv.org.
    19. 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.
    20. 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.
    21. Lu, Xun & White, Halbert, 2014. "Testing for separability in structural equations," Journal of Econometrics, Elsevier, vol. 182(1), pages 14-26.
    22. 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.
    23. Roy Allen & John Rehbeck, 2020. "Hicksian complementarity and perturbed utility models," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 8(2), pages 245-261, October.

  14. Susanne M. Schennach, 2007. "Point estimation with exponentially tilted empirical likelihood," Papers 0708.1874, arXiv.org.

    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. Camponovo, Lorenzo & Otsu, Taisuke, 2014. "On Bartlett correctability of empirical likelihood in generalized power divergence family," LSE Research Online Documents on Economics 55597, London School of Economics and Political Science, LSE Library.
    3. Samer A. Kharroubi, 2018. "Posterior simulation via the exponentially tilted signed root log-likelihood ratio," Computational Statistics, Springer, vol. 33(1), pages 213-234, March.
    4. Lavergne, Pascal & Patilea, Valentin, 2013. "Smooth minimum distance estimation and testing with conditional estimating equations: Uniform in bandwidth theory," Journal of Econometrics, Elsevier, vol. 177(1), pages 47-59.
    5. 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.
    6. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
    7. Xiaohong Chen & Lars P. Hansen & Peter G. Hansen, 2020. "Robust Identification of Investor Beliefs," Cowles Foundation Discussion Papers 2236, Cowles Foundation for Research in Economics, Yale University.
    8. Jiang, Depeng & Zhao, Puying & Tang, Niansheng, 2016. "A propensity score adjustment method for regression models with nonignorable missing covariates," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 98-119.
    9. Sowell, Fallaw, 2009. "The empirical saddlepoint likelihood estimator applied to two-step GMM," MPRA Paper 15494, University Library of Munich, Germany, revised May 2009.
    10. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    11. Otsu, Taisuke, 2010. "On Bahadur efficiency of empirical likelihood," Journal of Econometrics, Elsevier, vol. 157(2), pages 248-256, August.
    12. Taisuke Otsu & Myung Hwan Seo & Yoon-Jae Whang, 2008. "Testing for Non-Nested Conditional Moment Restrictions Using Unconditional Empirical Likelihood," Cowles Foundation Discussion Papers 1660, Cowles Foundation for Research in Economics, Yale University.
    13. Bertille Antoine & Prosper Dovonon, 2020. "Robust Estimation with Exponentially Tilted Hellinger Distance," Discussion Papers dp20-02, Department of Economics, Simon Fraser University.
    14. 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.
    15. Yu‐Chin Hsu & Xiaoxia Shi, 2017. "Model‐selection tests for conditional moment restriction models," Econometrics Journal, Royal Economic Society, vol. 20(1), pages 52-85, February.
    16. Mehmet Caner, 2005. "Nearly Singular Design In Gmm And Generalized Empirical Likelihood Estimators," Econometrics 0509019, University Library of Munich, Germany.
    17. Jean-Pierre Florens & Anna Simoni, 2021. "Gaussian Processes and Bayesian Moment Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 482-492, March.
    18. Sanjay Chaudhuri & Malay Ghosh, 2011. "Empirical likelihood for small area estimation," Biometrika, Biometrika Trust, vol. 98(2), pages 473-480.
    19. De Silva, Dakshina G. & Hubbard, Timothy P. & Schiller, Anita R. & Tsionas, Mike G., 2023. "Estimating outcomes in the presence of endogeneity and measurement error with an application to R&D," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 278-294.
    20. 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.
    21. Bravo, Francesco & Chu, Ba & Jacho-Chavez, David, 2013. "Semiparametric estimation of moment condition models with weakly dependent data," MPRA Paper 79686, University Library of Munich, Germany, revised 2016.
    22. Sueishi, Naoya, 2013. "Identification problem of the exponential tilting estimator under misspecification," Economics Letters, Elsevier, vol. 118(3), pages 509-511.
    23. Alain Guay & Jean-Francois Lamarche, 2005. "The Information Content of Implied Probabilities to Detect Structural Change," Working Papers 0804, Brock University, Department of Economics, revised Oct 2008.
    24. Bedoui, Adel & Lazar, Nicole A., 2020. "Bayesian empirical likelihood for ridge and lasso regressions," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
    25. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    26. Chaussé, Pierre, 2010. "Computing Generalized Method of Moments and Generalized Empirical Likelihood with R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i11).
    27. Giuseppe Ragusa, 2011. "Minimum Divergence, Generalized Empirical Likelihoods, and Higher Order Expansions," Econometric Reviews, Taylor & Francis Journals, vol. 30(4), pages 406-456, August.
    28. Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
    29. Bruce E. Hansen & Seojeong Lee, 2021. "Inference for Iterated GMM Under Misspecification," Econometrica, Econometric Society, vol. 89(3), pages 1419-1447, May.
    30. Pierre Chaussé & Jin Liu & George Luta, 2016. "A Simulation-Based Comparison of Covariate Adjustment Methods for the Analysis of Randomized Controlled Trials," IJERPH, MDPI, vol. 13(4), pages 1-15, April.
    31. Gubhinder Kundhi & Paul Rilstone, 2015. "Saddlepoint expansions for GEL estimators," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 1-24, March.
    32. Hongtu Zhu & Haibo Zhou & Jiahua Chen & Yimei Li & Jeffrey Lieberman & Martin Styner, 2009. "Adjusted Exponentially Tilted Likelihood with Applications to Brain Morphology," Biometrics, The International Biometric Society, vol. 65(3), pages 919-927, September.
    33. Kirill Evdokimov & Yuichi Kitamura & Taisuke Otsu, 2014. "Robust estimation of moment condition models with weakly dependent data," STICERD - Econometrics Paper Series 579, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    34. Philip Kostov, 2013. "Empirical likelihood estimation of the spatial quantile regression," Journal of Geographical Systems, Springer, vol. 15(1), pages 51-69, January.
    35. 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.
    36. Halbert White & Karim Chalak, 2013. "Identification and Identification Failure for Treatment Effects Using Structural Systems," Econometric Reviews, Taylor & Francis Journals, vol. 32(3), pages 273-317, November.
    37. Francesco Bravo, 2022. "Misspecified semiparametric model selection with weakly dependent observations," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 558-586, July.
    38. Yuichi Kitamura & Taisuke Otsu & Kirill Evdokimov, 2013. "Robustness, Infinitesimal Neighborhoods, and Moment Restrictions," Econometrica, Econometric Society, vol. 81(3), pages 1185-1201, May.
    39. Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2015. "Nonparametric likelihood for volatility under high frequency data," STICERD - Econometrics Paper Series /2015/581, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    40. Lô, Serigne N. & Ronchetti, Elvezio, 2012. "Robust small sample accurate inference in moment condition models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3182-3197.
    41. Pierre Chaussé, 2011. "Generalized empirical likelihood for a continuum of moment conditions," Working Papers 1104, University of Waterloo, Department of Economics, revised Oct 2011.
    42. Ronchetti, Elvezio, 2020. "Accurate and robust inference," Econometrics and Statistics, Elsevier, vol. 14(C), pages 74-88.
    43. 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.
    44. Pierre Chausse & George Luta, 2017. "Casual Inference using Generalized Empirical Likelihood Methods," Working Papers 1707, University of Waterloo, Department of Economics, revised Dec 2017.
    45. Grendar, Marian & Judge, George G., 2006. "Large Deviations Theory and Empirical Estimator Choice," CUDARE Working Papers 25084, University of California, Berkeley, Department of Agricultural and Resource Economics.
    46. 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.
    47. 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.
    48. Dmitry Arkhangelsky & David Hirshberg, 2023. "Large-Sample Properties of the Synthetic Control Method under Selection on Unobservables," Papers 2311.13575, arXiv.org, revised Dec 2023.
    49. Israelov, Roni & Lugauer, Steven, 2011. "Combining empirical likelihood and generalized method of moments estimators: Asymptotics and higher order bias," Statistics & Probability Letters, Elsevier, vol. 81(9), pages 1339-1347, September.
    50. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.
    51. Tang, Niansheng & Yan, Xiaodong & Zhao, Puying, 2018. "Exponentially tilted likelihood inference on growing dimensional unconditional moment models," Journal of Econometrics, Elsevier, vol. 202(1), pages 57-74.
    52. Amor Keziou & Aida Toma, 2021. "A Robust Version of the Empirical Likelihood Estimator," Mathematics, MDPI, vol. 9(8), pages 1-19, April.
    53. 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.
    54. Hainmueller, Jens, 2012. "Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies," Political Analysis, Cambridge University Press, vol. 20(1), pages 25-46, January.
    55. Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.
    56. 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.
    57. Andreas Tryphonides, 2018. "Tilting Approximate Models," Papers 1805.10869, arXiv.org, revised Mar 2024.
    58. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
    59. A. Felipe & N. Martín & P. Miranda & L. Pardo, 2018. "Testing with Exponentially Tilted Empirical Likelihood," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1319-1358, December.
    60. 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.
    61. 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.
    62. 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.
    63. Canay, Ivan A. & Otsu, Taisuke, 2012. "Hodges–Lehmann optimality for testing moment conditions," Journal of Econometrics, Elsevier, vol. 171(1), pages 45-53.
    64. Chaudhuri, Saraswata & Renault, Eric, 2020. "Score tests in GMM: Why use implied probabilities?," Journal of Econometrics, Elsevier, vol. 219(2), pages 260-280.
    65. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    66. Alain Guay & Florian Pelgrin, 2007. "Using Implied Probabilities to Improve Estimation with Unconditional Moment Restrictions," Cahiers de recherche 0747, CIRPEE.
    67. Yang Shu, 2018. "Propensity Score Weighting for Causal Inference with Clustered Data," Journal of Causal Inference, De Gruyter, vol. 6(2), pages 1-19, September.

  15. Yingyao Hu & Susanne M. Schennach, 2006. "Identification and estimation of nonclassical nonlinear errors-in-variables models with continuous distributions using instruments," CeMMAP working papers CWP17/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Susanne Schennach & James Heckman & Flavio Cunha, 2007. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," 2007 Meeting Papers 973, Society for Economic Dynamics.
    2. 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).
    3. Gagliardini, Patrick & Scaillet, Olivier, 2012. "Tikhonov regularization for nonparametric instrumental variable estimators," Journal of Econometrics, Elsevier, vol. 167(1), pages 61-75.
    4. Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers 51/16, Institute for Fiscal Studies.
    5. Hoderlein, Stefan & Winter, Joachim, 2009. "Structural Measurement Errors in Nonseparable Models," Discussion Papers in Economics 9192, University of Munich, Department of Economics.
    6. Ji-Liang Shiu & Yingyao Hu, 2010. "Identification and Estimation of Nonlinear Dynamic Panel Data Models with Unobserved Covariates," Economics Working Paper Archive 557, The Johns Hopkins University,Department of Economics.
    7. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2018. "Nonparametric estimation in case of endogenous selection," Journal of Econometrics, Elsevier, vol. 202(2), pages 268-285.
    8. 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.
    9. Xavier d'Haultfoeuille, 2006. "On the Completeness Condition in Nonparametric Instrumental Problems," Working Papers 2006-32, Center for Research in Economics and Statistics.
    10. 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.
    11. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
    12. Yingyao Hu & Arthur Lewbel & Susanne M. Schennach, 2007. "Nonparametric identification of the classical errors-in-variables model without side information," CeMMAP working papers CWP14/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    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. D’Haultfœuille, Xavier & Février, Philippe, 2015. "Identification of mixture models using support variations," Journal of Econometrics, Elsevier, vol. 189(1), pages 70-82.
    15. Xiaohong Chen & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric Identification and Estimation of Nonclassical Errors-in-Variables Models Without Additional Information," Boston College Working Papers in Economics 676, Boston College Department of Economics.
    16. Sriya Iyer & Chander Velu & Melvyn Weeks, 2014. "Divine Competition: Religious Organisations and Service Provision in India," Cambridge Working Papers in Economics 1409, Faculty of Economics, University of Cambridge.
    17. El-Attar, Mayssun, 2009. "Could Education Promote the Israeli-Palestinian Peace Process?," IZA Discussion Papers 4447, Institute of Labor Economics (IZA).

  16. Susanne M. Schennach, 2004. "Instrumental Variable Estimation of Nonlinear Errors-in-Variables Models," Econometric Society 2004 North American Summer Meetings 602, Econometric Society.

    Cited by:

    1. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    2. Christoph Breunig, 2018. "Varying Random Coefficient Models," Papers 1804.03110, arXiv.org, revised Aug 2020.
    3. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    4. Luo, Guowang & Wu, Mixia & Pang, Zhen, 2022. "Estimation of spatial autoregressive models with covariate measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    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. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio Codina, 2017. "Estimating the production function for human capital: results from a randomized controlled trial in Colombia," IFS Working Papers W17/06, Institute for Fiscal Studies.
    7. 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).
    8. Weiming Yang & Yiping Yang, 2020. "Composite quantile regression estimation of linear error-in-variable models using instrumental variables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(1), pages 1-16, January.
    9. Ramalho Esmeralda A., 2010. "Covariate Measurement Error: Bias Reduction under Response-Based Sampling," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-34, September.
    10. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.
    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. Susanne M. Schennach, 2013. "Entropic Latent Variable Integration via Simulation," CeMMAP working papers CWP32/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio-Codina, 2015. "Estimating the Production Function for Human Capital: Results from a Randomized Control Trial in Colombia," Cowles Foundation Discussion Papers 1987, Cowles Foundation for Research in Economics, Yale University.
    15. 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.
    16. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Third Version," PIER Working Paper Archive 15-040, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 24 Nov 2015.
    17. Susanne M. Schennach & Halbert White & Karim Chalak, 2007. "Estimating average marginal effects in nonseparable structural systems," CeMMAP working papers CWP31/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. 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.
    19. Aman Ullah & Huansha Wang, 2013. "Parametric and Nonparametric Frequentist Model Selection and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-23, September.
    20. Biørn, Erik, 2017. "Identification and Method of Moments Estimation in Polynomial Measurement Error Models," Memorandum 01/2017, Oslo University, Department of Economics.
    21. Hao Dong & Taisuke Otsu & Luke Taylor, 2022. "Nonparametric estimation of additive models with errors-in-variables," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1164-1204, November.
    22. Xavier d'Haultfoeuille, 2006. "On the Completeness Condition in Nonparametric Instrumental Problems," Working Papers 2006-32, Center for Research in Economics and Statistics.
    23. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    24. Susanne M. Schennach, 2013. "Regressions with Berkson errors in covariates - a nonparametric approach," CeMMAP working papers 22/13, Institute for Fiscal Studies.
    25. 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.
    26. Battistin, Erich & Chesher, Andrew, 2014. "Treatment effect estimation with covariate measurement error," Journal of Econometrics, Elsevier, vol. 178(2), pages 707-715.
    27. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
    28. Aprajit Mahajan, 2006. "Identification and Estimation of Regression Models with Misclassification," Econometrica, Econometric Society, vol. 74(3), pages 631-665, May.
    29. Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Luis Quintero, "undated". "MCMC Approach to Classical Estimation with Overidentifying Restrictions," GSIA Working Papers 2013-E13, Carnegie Mellon University, Tepper School of Business.
    31. 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.
    32. 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.
    33. Breunig, Christoph, 2021. "Varying random coefficient models," Journal of Econometrics, Elsevier, vol. 221(2), pages 381-408.
    34. 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.
    35. Oliver Linton & Ji-Liang Shiu, 2018. "Semiparametric nonlinear panel data models with measurement error," CeMMAP working papers CWP09/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Ben-Moshe, Dan, 2018. "Identification Of Joint Distributions In Dependent Factor Models," Econometric Theory, Cambridge University Press, vol. 34(1), pages 134-165, February.
    37. 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.
    38. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    39. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    40. Deng, Ping & Hu, Yingyao, 2009. "Bounding the effect of a dichotomous regressor with arbitrary measurement errors," Economics Letters, Elsevier, vol. 105(3), pages 256-260, December.
    41. 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.
    42. Evdokimov, Kirill & White, Halbert, 2012. "Some Extensions Of A Lemma Of Kotlarski," Econometric Theory, Cambridge University Press, vol. 28(4), pages 925-932, August.
    43. D’Haultfœuille, Xavier & Février, Philippe, 2015. "Identification of mixture models using support variations," Journal of Econometrics, Elsevier, vol. 189(1), pages 70-82.
    44. 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.
    45. Yingyao Hu & Matthew Shum, 2008. "Nonparametric Identification of Dynamic Models with Unobserved State Variables," Economics Working Paper Archive 543, The Johns Hopkins University,Department of Economics.
    46. Christoph Breunig & Stephan Martin, 2020. "Nonclassical Measurement Error in the Outcome Variable," Papers 2009.12665, arXiv.org, revised May 2021.
    47. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    48. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(4), pages 1010-1043, August.
    49. Abito, Jose Miguel, 2019. "Estimating Production Functions with Fixed Effects," MPRA Paper 97825, University Library of Munich, Germany.
    50. Brantly Callaway & Tong Li & Irina Murtazashvili, 2021. "Nonlinear Approaches to Intergenerational Income Mobility allowing for Measurement Error," Papers 2107.09235, arXiv.org, revised Dec 2021.
    51. Bang-Qiang He & Xing-Jian Hong & Guo-Liang Fan, 2020. "Penalized empirical likelihood for partially linear errors-in-variables panel data models with fixed effects," Statistical Papers, Springer, vol. 61(6), pages 2351-2381, December.
    52. 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.
    53. Zhang, Jun & Feng, Zhenghui & Zhou, Bu, 2014. "A revisit to correlation analysis for distortion measurement error data," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 116-129.
    54. 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.
    55. Yingyao Hu & Susanne M. Schennach, 2006. "Identification and estimation of nonclassical nonlinear errors-in-variables models with continuous distributions using instruments," CeMMAP working papers CWP17/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    56. Wossen, Tesfamicheal & Abay, Kibrom A. & Abdoulaye, Tahirou, 2022. "Misperceiving and misreporting input quality: Implications for input use and productivity," Journal of Development Economics, Elsevier, vol. 157(C).
    57. Comte, F. & Lacour, C. & Rozenholc, Y., 2010. "Adaptive estimation of the dynamics of a discrete time stochastic volatility model," Journal of Econometrics, Elsevier, vol. 154(1), pages 59-73, January.

  17. Arthur Lewbel & Susanne M. Schennach, 2003. "A Simple Ordered Data Estimator For Inverse Density Weighted Functions," Boston College Working Papers in Economics 557, Boston College Department of Economics, revised 01 May 2005.

    Cited by:

    1. Yingying Dong & Arthur Lewbel & Thomas Tao Yang, 2012. "Comparing Features of Convenient Estimators for Binary Choice Models With Endogenous Regressors," Boston College Working Papers in Economics 789, Boston College Department of Economics, revised 15 May 2012.
    2. Yingying Dong & Arthur Lewbel, 2012. "A Simple Estimator for Binary Choice Models With Endogenous Regressors," Boston College Working Papers in Economics 807, Boston College Department of Economics.
    3. Mohnen, Pierre & Tiwari, Amaresh & Palm, Franz & Schim van der Loeff, Sybrand, 2007. "Financial Constraint and R&D Investment: Evidence from CIS," MERIT Working Papers 2007-011, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

Articles

  1. Hu, Yingyao & Schennach, Susanne & Shiu, Ji-Liang, 2022. "Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 226(2), pages 269-294.

    Cited by:

    1. Orville Mondal & Rui Wang, 2024. "Partial Identification of Binary Choice Models with Misreported Outcomes," Papers 2401.17137, arXiv.org.
    2. Loh, Isaac, 2023. "Genericity of the completeness condition with constrained instruments," Economics Letters, Elsevier, vol. 224(C).
    3. Diaz-Serrano, Luis & Nilsson, William, 2017. "The Reliability of Students' Earnings Expectations," IZA Discussion Papers 10700, Institute of Labor Economics (IZA).

  2. Susanne M Schennach, 2020. "A Bias Bound Approach to Non-parametric Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(5), pages 2439-2472.
    See citations under working paper version above.
  3. Schennach, Susanne M., 2019. "Convolution without independence," Journal of Econometrics, Elsevier, vol. 211(1), pages 308-318.
    See citations under working paper version above.
  4. Susanne M. Schennach, 2018. "Long Memory via Networking," Econometrica, Econometric Society, vol. 86(6), pages 2221-2248, November.
    See citations under working paper version above.
  5. Susanne M. Schennach & Daniel Wilhelm, 2017. "A Simple Parametric Model Selection Test," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1663-1674, October.
    See citations under working paper version above.
  6. Hu, Yingyao & Schennach, Susanne M. & Shiu, Ji-Liang, 2017. "Injectivity of a class of integral operators with compactly supported kernels," Journal of Econometrics, Elsevier, vol. 200(1), pages 48-58.

    Cited by:

    1. 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.
    2. Hu, Yingyao & Schennach, Susanne & Shiu, Ji-Liang, 2022. "Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 226(2), pages 269-294.
    3. Victor H. Aguiar & Nail Kashaev & Roy Allen, 2022. "Prices, Profits, Proxies, and Production," University of Western Ontario, Departmental Research Report Series 20226, University of Western Ontario, Department of Economics.
    4. Kenichi Nagasawa, 2018. "Treatment Effect Estimation with Noisy Conditioning Variables," Papers 1811.00667, arXiv.org, revised Sep 2022.
    5. 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.
    6. Botosaru, Irene, 2020. "Nonparametric analysis of a duration model with stochastic unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 217(1), pages 112-139.
    7. 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.

  7. Susanne M. Schennach, 2016. "Recent Advances in the Measurement Error Literature," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 341-377, October.

    Cited by:

    1. Hahn, Jinyong & Hausman, Jerry & Kim, Jeonghwan, 2021. "A small sigma approach to certain problems in errors-in-variables models," Economics Letters, Elsevier, vol. 208(C).
    2. Gilles E. Gignac & Elizabeth Ooi, 2022. "Measurement error in research on financial literacy: How much error is there and how does it influence effect size estimates?," Journal of Consumer Affairs, Wiley Blackwell, vol. 56(2), pages 938-956, June.
    3. Aurélie Bertrand & Ingrid Van Keilegom & Catherine Legrand, 2019. "Flexible parametric approach to classical measurement error variance estimation without auxiliary data," Biometrics, The International Biometric Society, vol. 75(1), pages 297-307, March.
    4. Aguiar, Victor H. & Serrano, Roberto, 2017. "Slutsky matrix norms: The size, classification, and comparative statics of bounded rationality," Journal of Economic Theory, Elsevier, vol. 172(C), pages 163-201.
    5. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    6. Erik Meijer & Edward Oczkowski & Tom Wansbeek, 2021. "How measurement error affects inference in linear regression," Empirical Economics, Springer, vol. 60(1), pages 131-155, January.
    7. Andrea Bastianin & Paolo Castelnovo & Massimo Florio, 2018. "Evaluating regulatory reform of network industries: a survey of empirical models based on categorical proxies," Papers 1810.03348, arXiv.org.
    8. Cheny, L.; & Clarke, P.M.; & Petrie, D.J.; & Staub, K.E.;, 2018. "The effects of self-assessed health: Dealing with and understanding misclassification bias," Health, Econometrics and Data Group (HEDG) Working Papers 18/26, HEDG, c/o Department of Economics, University of York.
    9. Murphy, Richard & Weinhardt, Felix, 2020. "Top of the class: the importance of ordinal rank," LSE Research Online Documents on Economics 105077, London School of Economics and Political Science, LSE Library.
    10. Hao Dong & Taisuke Otsu & Luke Taylor, 2021. "Bandwidth Selection for Nonparametric Regression with Errors-in-Variables," Departmental Working Papers 2104, Southern Methodist University, Department of Economics.
    11. Young Jun Lee & Daniel Wilhelm, 2020. "Testing for the presence of measurement error in Stata," Stata Journal, StataCorp LP, vol. 20(2), pages 382-404, June.
    12. Hu, Yingyao & Schennach, Susanne & Shiu, Ji-Liang, 2022. "Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 226(2), pages 269-294.
    13. Hu, Yingyao, 2021. "Identification of Causal Models with Unobservables: A Self-Report Approach," Economics Working Paper Archive 64330, The Johns Hopkins University,Department of Economics.
    14. 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.
    15. Hao Dong & Yuya Sasaki, 2022. "Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving," Papers 2209.05914, arXiv.org.
    16. Kyle L Marquardt, 2020. "How and how much does expert error matter? Implications for quantitative peace research," Journal of Peace Research, Peace Research Institute Oslo, vol. 57(6), pages 692-700, November.
    17. Peter A.G. van Bergeijk, 2017. "Making Data Measurement Errors Transparent: The Case of the IMF," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(3), pages 133-154, July.
    18. Carletto,Calogero & Dillon,Andrew S. & Zezza,Alberto, 2021. "Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage," Policy Research Working Paper Series 9745, The World Bank.
    19. Andrew Chesher & Adam Rosen, 2019. "Generalized Instrumental Variable Models, Methods, and Applications," CeMMAP working papers CWP41/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022. "Estimation of varying coefficient models with measurement error," Journal of Econometrics, Elsevier, vol. 230(2), pages 388-415.
    21. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
    22. Mohamed Doukali & Xiaojun Song & Abderrahim Taamouti, 2022. "Value-at Risk under Measurement Error," Working Papers 202209, University of Liverpool, Department of Economics.
    23. Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    24. Hao Dong & Daniel L. Millimet, 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," Departmental Working Papers 2013, Southern Methodist University, Department of Economics.
    25. Victor H. Aguiar & Nail Kashaev & Roy Allen, 2022. "Prices, Profits, Proxies, and Production," University of Western Ontario, Departmental Research Report Series 20226, University of Western Ontario, Department of Economics.
    26. Hong Li & Qifan Song & Jianxi Su, 2021. "Robust estimates of insurance misrepresentation through kernel quantile regression mixtures," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 625-663, September.
    27. Li, Siran & Zheng, Xunjie, 2020. "A generalization of Lemma 1 in Kotlarski (1967)," Statistics & Probability Letters, Elsevier, vol. 165(C).
    28. Naqib Ullah Khan & Peng Zhongyi & Heesup Han & Antonio Ariza-Montes, 2023. "Linking public leadership and public project success: the mediating role of team building," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    29. De Neve, Jan-Walter & Fink, Günther, 2018. "Children’s education and parental old age survival – Quasi-experimental evidence on the intergenerational effects of human capital investment," Journal of Health Economics, Elsevier, vol. 58(C), pages 76-89.
    30. Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Christian Gourieroux & Joann Jasiak, 2023. "Dynamic deconvolution and identification of independent autoregressive sources," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 151-180, March.
    32. Zhang, Han, 2021. "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv 453jk, Center for Open Science.
    33. Pablo Mitnik, 2018. "Estimating the Intergenerational Elasticity of Expected Income with Short-Run Income Measures: A Generalized Error-in-Variables Model," Working Papers 2018-045, Human Capital and Economic Opportunity Working Group.
    34. JoonHwan Cho & Yao Luo & Ruli Xiao, 2022. "Deconvolution from Two Order Statistics," Working Papers tecipa-739, University of Toronto, Department of Economics.
    35. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    36. Dong, Hao & Taylor, Luke, 2022. "Nonparametric Significance Testing In Measurement Error Models," Econometric Theory, Cambridge University Press, vol. 38(3), pages 454-496, June.
    37. 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.
    38. Bertrand, Aurelie & Van Keilegom, Ingrid & Legrand, Catherine, 2017. "Flexible parametric approach to classical measurement error variance estimation without auxiliary data," LIDAM Discussion Papers ISBA 2017025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    39. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    40. Marica Valente & Timm Gries & Lorenzo Trapani, 2023. "Informal employment from migration shocks," Working Papers 2023-09, Faculty of Economics and Statistics, Universität Innsbruck.
    41. 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.
    42. 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.
    43. Vitor Possebom, 2021. "Crime and Mismeasured Punishment: Marginal Treatment Effect with Misclassification," Papers 2106.00536, arXiv.org, revised Jul 2023.
    44. Martin T. Bohl & Nicole Branger & Mark Trede, 2019. "Measurement Errors in Index Trader Positions Data: Is the Price Pressure Hypothesis Still Invalid?," CQE Working Papers 8019, Center for Quantitative Economics (CQE), University of Muenster.
    45. Cunha, Flávio & Elo, Irma & Culhane, Jennifer, 2022. "Maternal subjective expectations about the technology of skill formation predict investments in children one year later," Journal of Econometrics, Elsevier, vol. 231(1), pages 3-32.
    46. Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
    47. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
    48. Flavio Cunha & Irma Elo & Jennifer Culhane, 2021. "Maternal Subjective Expectations about the Technology of Skill Formation Predict Investments in Children One Year Later," Working Papers 2021-018, Human Capital and Economic Opportunity Working Group.
    49. van Bergeijk, P.A.G., 2017. "Measurement error of global production," ISS Working Papers - General Series 632, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    50. Öberg, Stefan, 2021. "Treatment for natural experiments: How to improve causal estimates using conceptual definitions and substantive interpretations," SocArXiv pkyue, Center for Open Science.
    51. Tom Boot & Art=uras Juodis, 2023. "Uniform Inference in Linear Error-in-Variables Models: Divide-and-Conquer," Papers 2301.04439, arXiv.org.
    52. Andrea Bastianin & Paolo Castelnovo & Massimo Florio, 2017. "The Empirics of Regulatory Reforms Proxied by Categorical Variables: Recent Findings and Methodological Issues," ETA: Economic Theory and Applications 257877, Fondazione Eni Enrico Mattei (FEEM).
    53. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org.
    54. Eric Blankmeyer, 2018. "Measurement Errors as Bad Leverage Points," Papers 1807.02814, arXiv.org, revised Mar 2020.
    55. Dong, Hao & Millimet, Daniel L., 2023. "Embrace the Noise: It Is OK to Ignore Measurement Error in a Covariate, Sometimes," IZA Discussion Papers 16508, Institute of Labor Economics (IZA).

  8. Suyong Song & Susanne M. Schennach & Halbert White, 2015. "Estimating nonseparable models with mismeasured endogenous variables," Quantitative Economics, Econometric Society, vol. 6(3), pages 749-794, November.

    Cited by:

    1. 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.
    2. Denni Tommasi & Arthur Lewbel & Rossella Calvi, 2017. "LATE with Mismeasured or Misspecified Treatment: An application to Women's Empowerment in India," Working Papers ECARES ECARES 2017-27, ULB -- Universite Libre de Bruxelles.
    3. 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.
    4. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
    5. 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.
    6. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    7. 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.
    8. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.

  9. Susanne M. Schennach, 2014. "Entropic Latent Variable Integration via Simulation," Econometrica, Econometric Society, vol. 82(1), pages 345-385, January.
    See citations under working paper version above.
  10. S. M. Schennach & Yingyao Hu, 2013. "Nonparametric Identification and Semiparametric Estimation of Classical Measurement Error Models Without Side Information," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 177-186, March.
    See citations under working paper version above.
  11. 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.
    See citations under working paper version above.
  12. Flavio Cunha & James J. Heckman & Susanne M. Schennach, 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," Econometrica, Econometric Society, vol. 78(3), pages 883-931, May.
    See citations under working paper version above.
  13. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(4), pages 1010-1043, August.

    Cited by:

    1. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Childhood Intervention," IZA Discussion Papers 13101, Institute of Labor Economics (IZA).
    2. Sasaki, Yuya, 2015. "What Do Quantile Regressions Identify For General Structural Functions?," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1102-1116, October.
    3. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    4. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Child Intervention," CEPR Discussion Papers 14721, C.E.P.R. Discussion Papers.
    5. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.
    6. 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.
    7. Andrew Chesher, 2017. "Understanding the effect of measurement error on quantile regressions," CeMMAP working papers CWP19/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Gabriel Montes-Rojas, 2011. "Quantile Regression with Classical Additive Measurement Errors," Economics Bulletin, AccessEcon, vol. 31(4), pages 2863-2868.
    9. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.
    10. Galvao Jr, A. F. & Montes-Rojas, G., 2009. "Instrumental variables quantile regression for panel data with measurement errors," Working Papers 09/06, Department of Economics, City University London.
    11. Huixia Judy Wang & Leonard A. Stefanski & Zhongyi Zhu, 2012. "Corrected-loss estimation for quantile regression with covariate measurement errors," Biometrika, Biometrika Trust, vol. 99(2), pages 405-421.
    12. Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Schmidt, Christoph M. & Tauchmann, Harald, 2011. "Heterogeneity in the intergenerational transmission of alcohol consumption: A quantile regression approach," Journal of Health Economics, Elsevier, vol. 30(1), pages 33-42, January.
    14. Anil K. Bera & Antonio F. Galvao Jr. & Gabriel V. Montes-Rojas & Sung Y. Park, 2014. "Which Quantile is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression," World Scientific Book Chapters, in: Kaddour Hadri & William Mikhail (ed.), Econometric Methods and Their Applications in Finance, Macro and Related Fields, chapter 7, pages 167-199, World Scientific Publishing Co. Pte. Ltd..
    15. Wei, Ying & Carroll, Raymond J., 2009. "Quantile Regression With Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1129-1143.
    16. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    17. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Jerry Hausman & Haoyang Liu & Ye Luo & Christopher Palmer, 2021. "Errors in the Dependent Variable of Quantile Regression Models," Econometrica, Econometric Society, vol. 89(2), pages 849-873, March.
    19. Roger Koenker, 2017. "Quantile regression 40 years on," CeMMAP working papers CWP36/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Eren, Ozkan & Ozbeklik, Serkan, 2013. "The effect of noncognitive ability on the earnings of young men: A distributional analysis with measurement error correction," Labour Economics, Elsevier, vol. 24(C), pages 293-304.
    21. Wang, Le, 2011. "How Does Education Affect the Earnings Distribution in Urban China?," IZA Discussion Papers 6173, Institute of Labor Economics (IZA).
    22. Roger Koenker, 2017. "Quantile regression 40 years on," CeMMAP working papers 36/17, Institute for Fiscal Studies.
    23. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
    24. Bera Anil K. & Galvao Antonio F. & Montes-Rojas Gabriel V. & Park Sung Y., 2016. "Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 79-101, January.
    25. 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.

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    Cited by:

    1. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Childhood Intervention," IZA Discussion Papers 13101, Institute of Labor Economics (IZA).
    2. Papageorge, Nicholas W. & Gershenson, Seth & Kang, Kyungmin, 2016. "Teacher Expectations Matter," IZA Discussion Papers 10165, Institute of Labor Economics (IZA).
    3. Lorenzo Almada & Ian McCarthy & Rusty Tchernis, 2016. "What Can We Learn about the Effects of Food Stamps on Obesity in the Presence of Misreporting?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 997-1017.
    4. Susanne Schennach & James Heckman & Flavio Cunha, 2007. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," 2007 Meeting Papers 973, Society for Economic Dynamics.
    5. Stéphane Bonhomme & Koen Jochmans & Jean-Marc Robin, 2017. "Nonparametric estimation of non-exchangeable latent-variable models," SciencePo Working papers Main hal-03264006, HAL.
    6. Kemp, Gordon C.R. & Santos Silva, J.M.C., 2012. "Regression towards the mode," Journal of Econometrics, Elsevier, vol. 170(1), pages 92-101.
    7. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    8. Babii, Andrii & Florens, Jean-Pierre, 2020. "Is completeness necessary? Estimation in nonidentified linear models," TSE Working Papers 20-1091, Toulouse School of Economics (TSE).
    9. Battistin, Erich & De Nadai, Michele & Krishnan, Nandini, 2020. "The Insights and Illusions of Consumption Measurements," IZA Discussion Papers 13222, Institute of Labor Economics (IZA).
    10. Francis J. DiTraglia & Camilo Garcia-Jimeno, 2020. "Identifying the effect of a mis-classified, binary, endogenous regressor," Papers 2011.07272, arXiv.org.
    11. 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.
    12. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio Codina, 2017. "Estimating the production function for human capital: results from a randomized controlled trial in Colombia," IFS Working Papers W17/06, Institute for Fiscal Studies.
    13. 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.
    14. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Child Intervention," CEPR Discussion Papers 14721, C.E.P.R. Discussion Papers.
    15. Ekaterina Oparina & Sorawoot Srisuma, 2022. "Analyzing Subjective Well-Being Data with Misclassification," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 730-743, April.
    16. Chen Zhen & Justin L. Taylor & Mary K. Muth & Ephraim Leibtag, 2009. "Understanding Differences in Self-Reported Expenditures between Household Scanner Data and Diary Survey Data: A Comparison of Homescan and Consumer Expenditure Survey," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(3), pages 470-492, September.
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    18. Mittag, Nikolas, 2016. "Correcting for Misreporting of Government Benefits," IZA Discussion Papers 10266, Institute of Labor Economics (IZA).
    19. Ramalho Esmeralda A., 2010. "Covariate Measurement Error: Bias Reduction under Response-Based Sampling," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-34, September.
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    21. Manuel Arellano & Richard Blundell & Stéphane Bonhomme & Jack Light, 2024. "Heterogeneity of consumption responses to income shocks in the presence of nonlinear persistence," Post-Print hal-04536563, HAL.
    22. Rasmus Lentz & Suphanit Piyapromdee & Jean-Marc Robin, 2022. "The Anatomy of Sorting - Evidence from Danish Data," SciencePo Working papers Main hal-03869383, HAL.
    23. Jackson Bunting, 2022. "Continuous permanent unobserved heterogeneity in dynamic discrete choice models," Papers 2202.03960, arXiv.org, revised Feb 2024.
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    25. Benjamin Williams, 2018. "Identification of the Linear Factor Model," Working Papers 2018-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    26. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Second Version," PIER Working Paper Archive 15-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 11 Nov 2015.
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    28. Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers 51/16, Institute for Fiscal Studies.
    29. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
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    35. Andrew Chesher, 2017. "Understanding the effect of measurement error on quantile regressions," CeMMAP working papers CWP19/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio-Codina, 2015. "Estimating the Production Function for Human Capital: Results from a Randomized Control Trial in Colombia," Cowles Foundation Discussion Papers 1987, Cowles Foundation for Research in Economics, Yale University.
    37. 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.
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    42. Ji-Liang Shiu & Yingyao Hu, 2010. "Identification and Estimation of Nonlinear Dynamic Panel Data Models with Unobserved Covariates," Economics Working Paper Archive 557, The Johns Hopkins University,Department of Economics.
    43. 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.
    44. 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.
    45. Garcia, Tanya P. & Ma, Yanyuan, 2017. "Simultaneous treatment of unspecified heteroskedastic model error distribution and mismeasured covariates for restricted moment models," Journal of Econometrics, Elsevier, vol. 200(2), pages 194-206.
    46. Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2017. "Semiparametric Estimation Of Random Coefficients In Structural Economic Models," Post-Print hal-03089886, HAL.
    47. Carroll, Raymond J. & Delaigle, Aurore & Hall, Peter, 2009. "Nonparametric Prediction in Measurement Error Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 993-1003.
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    49. Delaigle, Aurore & Fan, Jianqing & Carroll, Raymond J., 2009. "A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 348-359.
    50. Sukjin Han & Sungwon Lee, 2018. "Estimation in a Generalization of Bivariate Probit Models with Dummy Endogenous Regressors," Papers 1808.05792, arXiv.org, revised Mar 2019.
    51. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Third Version," PIER Working Paper Archive 15-040, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 24 Nov 2015.
    52. DiTraglia, Francis J. & García-Jimeno, Camilo, 2019. "Identifying the effect of a mis-classified, binary, endogenous regressor," Journal of Econometrics, Elsevier, vol. 209(2), pages 376-390.
    53. Jane Cooley Fruehwirth & Salvador Navarro & Yuya Takahashi, 2011. "How The Timing of Grade Retention Affects Outcomes: Identification and Estimation of Time-Varying Treatment Effects," Working Papers 2011-015, Human Capital and Economic Opportunity Working Group.
    54. Yingyao Hu & Yi Xin, 2019. "Identi?cation and estimation of dynamic structural models with unobserved choices," CeMMAP working papers CWP35/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    55. 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.
    56. Hu, Yingyao & Schennach, Susanne M. & Shiu, Ji-Liang, 2017. "Injectivity of a class of integral operators with compactly supported kernels," Journal of Econometrics, Elsevier, vol. 200(1), pages 48-58.
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    60. Yingyao Hu & Ji-Liang Shiu, 2011. "Nonparametric identification using instrumental variables: sufficient conditions for completeness," CeMMAP working papers CWP25/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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    64. Suyong Song & Stephen Baek, 2021. "Body shape matters: Evidence from machine learning on body shape-income relationship," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-17, July.
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    66. Yao Luo, 2018. "Unobserved Heterogeneity in Auctions under Restricted Stochastic Dominance," Working Papers tecipa-606, University of Toronto, Department of Economics.
    67. Susanne M. Schennach & Yingyao Hu, 2012. "Nonparametric identification and semiparametric estimation of classical measurement error models without side information," CeMMAP working papers CWP40/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    68. You, Jing & Nie, Huihua, 2017. "Who determines Chinese firms' engagement in corruption: Themselves or neighbors?," China Economic Review, Elsevier, vol. 43(C), pages 29-46.
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    133. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Mar 2024.
    134. Abito, Jose Miguel, 2019. "Estimating Production Functions with Fixed Effects," MPRA Paper 97825, University Library of Munich, Germany.
    135. Zhang, Yinjunjie & Xu, Zhicheng Phil & Palma, Marco A., 2017. "Misclassification Errors of Subjective Well-being: A New Approach to Mapping Happiness," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258553, Agricultural and Applied Economics Association.
    136. Kenichi Nagasawa, 2018. "Treatment Effect Estimation with Noisy Conditioning Variables," Papers 1811.00667, arXiv.org, revised Sep 2022.
    137. Bollinger, Christopher R. & van Hasselt, Martijn, 2017. "Bayesian moment-based inference in a regression model with misclassification error," Journal of Econometrics, Elsevier, vol. 200(2), pages 282-294.
    138. Hu, Yingyao & Sasaki, Yuya, 2015. "Closed-form estimation of nonparametric models with non-classical measurement errors," Journal of Econometrics, Elsevier, vol. 185(2), pages 392-408.
    139. An, Yonghong, 2017. "Identification of first-price auctions with non-equilibrium beliefs: A measurement error approach," Journal of Econometrics, Elsevier, vol. 200(2), pages 326-343.
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    151. 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.
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    155. Christoph Breunig, 2015. "Testing Missing at Random using Instrumental Variables," SFB 649 Discussion Papers SFB649DP2015-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    156. Serafin J. Grundl & Yu Zhu, 2015. "Identification and Estimation of Risk Aversion in First Price Auctions With Unobserved Auction Heterogeneity," Finance and Economics Discussion Series 2015-89, Board of Governors of the Federal Reserve System (U.S.).
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    160. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers CWP03/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    161. Gutknecht, Daniel, 2011. "Nonclassical Measurement Error in a Nonlinear (Duration) Model," Economic Research Papers 270763, University of Warwick - Department of Economics.
    162. Yingyao Hu & Jiaxiong Yao, 2019. "Illuminating Economic Growth," IMF Working Papers 2019/077, International Monetary Fund.
    163. Escanciano, Juan Carlos, 2023. "Irregular identification of structural models with nonparametric unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 106-127.
    164. Hu, Yingyao & Yao, Jiaxiong, 2022. "Illuminating economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 359-378.
    165. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo Somaini & Daniel Waldinger, 2021. "Equilibrium Allocations Under Alternative Waitlist Designs: Evidence From Deceased Donor Kidneys," Econometrica, Econometric Society, vol. 89(1), pages 37-76, January.
    166. Christoph Breunig, 2017. "Testing Missing at Random using Instrumental Variables," SFB 649 Discussion Papers SFB649DP2017-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    167. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo J. Somaini & Daniel C. Waldinger, 2019. "Equilibrium Allocations under Alternative Waitlist Designs: Evidence from Deceased Donor Kidneys," NBER Working Papers 25607, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Nir Billfeld & Moshe Kim, 2019. "Semiparametric Wavelet-based JPEG IV Estimator for endogenously truncated data," Papers 1908.02166, arXiv.org.
    2. Federico Zincenko, 2019. "Testing for Risk Aversion in First-Price Sealed-Bid Auctions," Working Paper 6641, Department of Economics, University of Pittsburgh.
    3. Bontemps, Christophe & Nauges, Céline, 2014. "The impact of perceptions in averting-decision models: An application of the special regressor method to drinking water choices," TSE Working Papers 14-537, Toulouse School of Economics (TSE).
    4. Yingying Dong & Arthur Lewbel & Thomas Tao Yang, 2012. "Comparing Features of Convenient Estimators for Binary Choice Models With Endogenous Regressors," Boston College Working Papers in Economics 789, Boston College Department of Economics, revised 15 May 2012.
    5. Xuewen Lu & Heng Lian & Wanrong Liu, 2012. "Semiparametric estimation for inverse density weighted expectations when responses are missing at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 139-152.
    6. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    7. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2019. "Have Econometric Analyses of Happiness Data Been Futile? A Simple Truth about Happiness Scales," IZA Discussion Papers 12152, Institute of Labor Economics (IZA).
    8. Simona Mateut, 2018. "Subsidies, financial constraints and firm innovative activities in emerging economies," Small Business Economics, Springer, vol. 50(1), pages 131-162, January.
    9. David Jacho-Chávez, 2008. "k nearest-neighbor estimation of inverse density weighted expectations," Economics Bulletin, AccessEcon, vol. 3(48), pages 1-6.
    10. Denis Cogneau & Yannick Dupraz, 2014. "Questionable Inference on the Power of Pre-Colonial Institutions in Africa," Working Papers halshs-01018548, HAL.
    11. Yingying Dong & Arthur Lewbel, 2012. "A Simple Estimator for Binary Choice Models With Endogenous Regressors," Boston College Working Papers in Economics 807, Boston College Department of Economics.
    12. Arthur Lewbel, 2012. "An Overview of the Special Regressor Method," Boston College Working Papers in Economics 810, Boston College Department of Economics.
    13. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2022. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 672-686.
    14. Nir Billfeld & Moshe Kim, 2019. "Semiparametric correction for endogenous truncation bias with Vox Populi based participation decision," Papers 1902.06286, arXiv.org.
    15. Arthur Lewbel & Yingying Dong & Thomas Tao Yang, 2012. "Viewpoint: Comparing features of convenient estimators for binary choice models with endogenous regressors," Canadian Journal of Economics, Canadian Economics Association, vol. 45(3), pages 809-829, August.
    16. Yao, Becatien H. & Shanoyan, Aleksan & Schwab, Benjamin & Amanor-Boadu, Vincent, 2022. "Mobile money, transaction costs, and market participation: evidence from Côte d’Ivoire and Tanzania," Food Policy, Elsevier, vol. 112(C).
    17. Sasaki, Yuya & Ura, Takuya, 2023. "Estimation and inference for policy relevant treatment effects," Journal of Econometrics, Elsevier, vol. 234(2), pages 394-450.
    18. Mohnen, Pierre & Tiwari, Amaresh & Palm, Franz & Schim van der Loeff, Sybrand, 2007. "Financial Constraint and R&D Investment: Evidence from CIS," MERIT Working Papers 2007-011, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    19. Lewbel, Arthur, 2007. "Endogenous selection or treatment model estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 777-806, December.
    20. Escanciano, Juan Carlos & Jacho-Chávez, David T., 2012. "n-uniformly consistent density estimation in nonparametric regression models," Journal of Econometrics, Elsevier, vol. 167(2), pages 305-316.
    21. Joris Pinkse & Karl Schurter, 2020. "Estimates of derivatives of (log) densities and related objects," Papers 2006.01328, arXiv.org.
    22. Chu, Ba & Jacho-Chávez, David T., 2012. "k-NEAREST NEIGHBOR ESTIMATION OF INVERSE-DENSITY-WEIGHTED EXPECTATIONS WITH DEPENDENT DATA," Econometric Theory, Cambridge University Press, vol. 28(4), pages 769-803, August.
    23. Bontemps, Christophe & Nauges, Céline, 2017. "Endogenous Variables in Binary Choice Models: Some Insights for Practitioners," TSE Working Papers 17-855, Toulouse School of Economics (TSE).
    24. Stewart, Mark B., 2005. "A comparison of semiparametric estimators for the ordered response model," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 555-573, April.
    25. Stefano Iandolo & Anna Ferragina, 2021. "International activities and innovation: Evidence from Italy with a special regressor approach," The World Economy, Wiley Blackwell, vol. 44(11), pages 3300-3325, November.
    26. Hitomi, Kohtaro & Nishiyama, Yoshihiko & Okui, Ryo, 2008. "A Puzzling Phenomenon In Semiparametric Estimation Problems With Infinite-Dimensional Nuisance Parameters," Econometric Theory, Cambridge University Press, vol. 24(6), pages 1717-1728, December.
    27. Nicolas Moreau, 2018. "A SAS macro to perform Dong and Lewbel's "Simple Estimator for Binary Choice Models" (2015)," Working Papers hal-01691487, HAL.
    28. Marianna Succurro & Giuseppina Damiana Costanzo, 2019. "Ownership structure and firm patenting activity in Italy," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(2), pages 239-266, June.

  17. Susanne M. Schennach, 2005. "Bayesian exponentially tilted empirical likelihood," Biometrika, Biometrika Trust, vol. 92(1), pages 31-46, March.

    Cited by:

    1. Florian Gunsilius & Susanne M. Schennach, 2017. "A nonlinear principal component decomposition," CeMMAP working papers CWP16/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    3. Camponovo, Lorenzo & Otsu, Taisuke, 2014. "On Bartlett correctability of empirical likelihood in generalized power divergence family," LSE Research Online Documents on Economics 55597, London School of Economics and Political Science, LSE Library.
    4. Samer A. Kharroubi, 2018. "Posterior simulation via the exponentially tilted signed root log-likelihood ratio," Computational Statistics, Springer, vol. 33(1), pages 213-234, March.
    5. Bruce N. Lehmann, 2005. "The Role of Beliefs in Inference for Rational Expectations Models," NBER Working Papers 11758, National Bureau of Economic Research, Inc.
    6. Bernstein, David H. & Parmeter, Christopher F. & Tsionas, Mike G., 2023. "On the performance of the United States nuclear power sector: A Bayesian approach," Energy Economics, Elsevier, vol. 125(C).
    7. 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.
    8. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    9. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    10. Tsionas, Mike G. & Malikov, Emir & Kumbhakar, Subal C., 2019. "Endogenous Dynamic Efficiency in the Intertemporal Optimization Models of Firm Behavior," MPRA Paper 97780, University Library of Munich, Germany.
    11. Toru Kitagawa, 2011. "Inference and decision for set identified parameters using posterior lower and upper probabilities," CeMMAP working papers CWP16/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Alhamzawi, Rahim & Yu, Keming, 2013. "Conjugate priors and variable selection for Bayesian quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 209-219.
    13. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    14. Huigang Chen & Mr. Alin T Mirestean & Mr. Charalambos G Tsangarides, 2011. "Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model," IMF Working Papers 2011/230, International Monetary Fund.
    15. Kai-Tai Fang & Rahul Mukerjee, 2006. "Empirical-type likelihoods allowing posterior credible sets with frequentist validity: Higher-order asymptotics," Biometrika, Biometrika Trust, vol. 93(3), pages 723-733, September.
    16. Anisha Ghosh & Christian Julliard, 2008. "Can Rare Events Explain the Equity Premium Puzzle?," 2008 Meeting Papers 1090, Society for Economic Dynamics.
    17. Rubio-Ramírez, Juan Francisco & Schorfheide, Frank & Fernández-Villaverde, Jesús, 2015. "Solution and Estimation Methods for DSGE Models," CEPR Discussion Papers 11032, C.E.P.R. Discussion Papers.
    18. Giuseppe Ragusa, 2007. "Bayesian Likelihoods for Moment Condition Models," Working Papers 060714, University of California-Irvine, Department of Economics.
    19. Chawarat Rotejanaprasert & Andrew B. Lawson, 2018. "A Bayesian Quantile Modeling for Spatiotemporal Relative Risk: An Application to Adverse Risk Detection of Respiratory Diseases in South Carolina, USA," IJERPH, MDPI, vol. 15(9), pages 1-15, September.
    20. Jean-Pierre Florens & Anna Simoni, 2021. "Gaussian Processes and Bayesian Moment Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 482-492, March.
    21. Sanjay Chaudhuri & Malay Ghosh, 2011. "Empirical likelihood for small area estimation," Biometrika, Biometrika Trust, vol. 98(2), pages 473-480.
    22. De Silva, Dakshina G. & Hubbard, Timothy P. & Schiller, Anita R. & Tsionas, Mike G., 2023. "Estimating outcomes in the presence of endogeneity and measurement error with an application to R&D," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 278-294.
    23. Xu, Ke-Li, 2020. "Inference of local regression in the presence of nuisance parameters," Journal of Econometrics, Elsevier, vol. 218(2), pages 532-560.
    24. Jesús Fernández-Villaverde, 2010. "The econometrics of DSGE models," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 1(1), pages 3-49, March.
    25. Assaf, A. George & Tsionas, Mike & Kock, Florian & Josiassen, Alexander, 2021. "A Bayesian non-parametric stochastic frontier model," Annals of Tourism Research, Elsevier, vol. 87(C).
    26. Wu Wang & Zhongyi Zhu, 2017. "Conditional empirical likelihood for quantile regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 1-16, January.
    27. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    28. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    29. Rahul Mukerjee & Ling-Yau Chan, 2009. "Confidence intervals based on empirical statistics: existence of a probability matching prior and connection with frequentist Bartlett adjustability," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 271-282, August.
    30. Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
    31. Gallant, A. Ronald & Hong, Han & Leung, Michael P. & Li, Jessie, 2022. "Constrained estimation using penalization and MCMC," Journal of Econometrics, Elsevier, vol. 228(1), pages 85-106.
    32. Chang, In Hong & Mukerjee, Rahul, 2008. "Matching posterior and frequentist cumulative distribution functions with empirical-type likelihoods in the multiparameter case," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2793-2797, November.
    33. David M. Kaplan & Longhao Zhuo, 2018. "Frequentist size of Bayesian inequality tests," Working Papers 1802, Department of Economics, University of Missouri, revised 14 Jul 2019.
    34. Philip Kostov, 2013. "Empirical likelihood estimation of the spatial quantile regression," Journal of Geographical Systems, Springer, vol. 15(1), pages 51-69, January.
    35. 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.
    36. Tsionas, Mike & Patel, Pankaj C. & Guedes, Maria João, 2022. "Endogenous efficiency of the dynamic profit maximization in the intertemporal production models of venture behavior," International Journal of Production Economics, Elsevier, vol. 246(C).
    37. Anna Stelzer, 2023. "Monetary policy and the joint distribution of income and wealth: The heterogeneous case of the euro area," Papers 2304.14264, arXiv.org.
    38. van Hasselt, Martijn & Ferland, Timothy & Bray, Jeremy & Aldridge, Arnie, 2017. "Bayesian Estimation of the Complier Average Casual Effect," UNCG Economics Working Papers 17-14, University of North Carolina at Greensboro, Department of Economics.
    39. Lehmann, Bruce N., 2009. "The role of beliefs in inference for rational expectations models," Journal of Econometrics, Elsevier, vol. 150(2), pages 322-331, June.
    40. Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2015. "Nonparametric likelihood for volatility under high frequency data," STICERD - Econometrics Paper Series /2015/581, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    41. In Chang & Rahul Mukerjee, 2012. "On the approximate frequentist validity of the posterior quantiles of a parametric function: results based on empirical and related likelihoods," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 156-169, March.
    42. Lane F. Burgette & Jerome P. Reiter, 2012. "Modeling Adverse Birth Outcomes via Confirmatory Factor Quantile Regression," Biometrics, The International Biometric Society, vol. 68(1), pages 92-100, March.
    43. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2020. "Revealing forecaster's preferences: A Bayesian multivariate loss function approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 412-437, April.
    44. Raffaella Giacomini & Toru Kitagawa, 2018. "Robust Bayesian inference for set-identified models," CeMMAP working papers CWP61/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    45. Gallant, A. Ronald, 2022. "Nonparametric Bayes subject to overidentified moment conditions," Journal of Econometrics, Elsevier, vol. 228(1), pages 27-38.
    46. Kien C. Tran & Mike G. Tsionas, 2022. "Instrumental Variables Estimation without Outside Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 489-506, September.
    47. Tony Lancaster & Sung Jae Jun, 2010. "Bayesian quantile regression methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 287-307.
    48. Susanne M. Schennach, 2007. "Point estimation with exponentially tilted empirical likelihood," Papers 0708.1874, arXiv.org.
    49. 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.
    50. Bollinger, Christopher R. & van Hasselt, Martijn, 2017. "Bayesian moment-based inference in a regression model with misclassification error," Journal of Econometrics, Elsevier, vol. 200(2), pages 282-294.
    51. Grazian, Clara & Dalla Valle, Luciana & Liseo, Brunero, 2022. "Approximate Bayesian conditional copulas," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    52. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.
    53. Grendar, Marian & Judge, George G., 2009. "Maximum Empirical Likelihood: Empty Set Problem," CUDARE Working Papers 53402, University of California, Berkeley, Department of Agricultural and Resource Economics.
    54. Mr. Alin T Mirestean & Mr. Charalambos G Tsangarides & Huigang Chen, 2009. "Limited Information Bayesian Model Averaging for Dynamic Panels with Short Time Periods," IMF Working Papers 2009/074, International Monetary Fund.
    55. Tang, Niansheng & Yan, Xiaodong & Zhao, Puying, 2018. "Exponentially tilted likelihood inference on growing dimensional unconditional moment models," Journal of Econometrics, Elsevier, vol. 202(1), pages 57-74.
    56. Ventura, Laura & Cabras, Stefano & Racugno, Walter, 2009. "Prior Distributions From Pseudo-Likelihoods in the Presence of Nuisance Parameters," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 768-774.
    57. Tatiana Dmitrieva & Kristin McCullough & Nader Ebrahimi, 2021. "Improved approximate Bayesian computation methods via empirical likelihood," Computational Statistics, Springer, vol. 36(2), pages 1533-1552, June.
    58. Jianzhong Zhou & Kuaile Feng & Yi Liu & Chao Zhou & Feifei He & Guangbiao Liu & Zhongzheng He, 2020. "A Hydrologic Uncertainty Processor Using Linear Derivation in the Normal Quantile Transform Space," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(11), pages 3649-3665, September.
    59. Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.
    60. F. Giummolè & V. Mameli & E. Ruli & L. Ventura, 2019. "Objective Bayesian inference with proper scoring rules," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 728-755, September.
    61. 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.
    62. 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.
    63. Lin, Lu & Tan, Lin, 2008. "Proper Bayesian estimating equation based on Hilbert space method," Statistics & Probability Letters, Elsevier, vol. 78(9), pages 1119-1127, July.
    64. In Chang & Rahul Mukerjee, 2006. "Asymptotic Results on a General Class of Empirical Statistics: Power and Confidence Interval Properties," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(3), pages 427-440, September.
    65. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    66. In Hong Chang & Rahul Mukerjee, 2008. "Bayesian and frequentist confidence intervals arising from empirical-type likelihoods," Biometrika, Biometrika Trust, vol. 95(1), pages 139-147.
    67. Isaiah Andrews & Anna Mikusheva, 2022. "Optimal Decision Rules for Weak GMM," Econometrica, Econometric Society, vol. 90(2), pages 715-748, March.
    68. A. Ronald Gallant, 2020. "Complementary Bayesian method of moments strategies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 422-439, June.
    69. Sung Jae Jun & Tony Lancaster, 2006. "Bayesian quantile regression," CeMMAP working papers CWP05/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    70. Florian Gunsilius & Susanne M. Schennach, 2019. "Independent nonlinear component analysis," CeMMAP working papers CWP46/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  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.

    Cited by:

    1. Joaquín Jara, J. & Pérez, Patricio & Villalobos, Pablo, 2010. "Good deposits are not enough: Mining labor productivity analysis in the copper industry in Chile and Peru 1992-2009," Resources Policy, Elsevier, vol. 35(4), pages 247-256, December.
    2. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    3. Söderholm, Patrik & Sundqvist, Thomas, 2007. "Empirical challenges in the use of learning curves for assessing the economic prospects of renewable energy technologies," Renewable Energy, Elsevier, vol. 32(15), pages 2559-2578.
    4. Osmundsen, Petter & Roll, Kristin Helen & Tveteras, Ragnar, 2012. "Drilling speed—the relevance of experience," Energy Economics, Elsevier, vol. 34(3), pages 786-794.
    5. Ediger, Volkan Ş. & Berk, Istemi & Ersoy, Mücella, 2015. "An assessment of mining efficiency in Turkish lignite industry," Resources Policy, Elsevier, vol. 45(C), pages 44-51.

  19. Schennach, Susanne M., 2004. "Nonparametric Regression In The Presence Of Measurement Error," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1046-1093, December.

    Cited by:

    1. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    2. Susanne Schennach & James Heckman & Flavio Cunha, 2007. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," 2007 Meeting Papers 973, Society for Economic Dynamics.
    3. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    4. Delaigle, Aurore & Meister, Alexander, 2007. "Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1416-1426, December.
    5. 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.
    6. Ramalho Esmeralda A., 2010. "Covariate Measurement Error: Bias Reduction under Response-Based Sampling," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-34, September.
    7. Sophie DABO-NIANG & Christian FRANCQ & Jean-Michel ZAKOIAN, 2009. "Combining Nonparametric and Optimal Linear Time Series Predictions," Working Papers 2009-18, Center for Research in Economics and Statistics.
    8. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    9. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.
    10. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.
    11. Garcia, Tanya P. & Ma, Yanyuan, 2017. "Simultaneous treatment of unspecified heteroskedastic model error distribution and mismeasured covariates for restricted moment models," Journal of Econometrics, Elsevier, vol. 200(2), pages 194-206.
    12. Hao Dong & Yuya Sasaki, 2022. "Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving," Papers 2209.05914, arXiv.org.
    13. Susanne M. Schennach, 2015. "A bias bound approach to nonparametric inference," CeMMAP working papers CWP71/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Carroll, Raymond J. & Delaigle, Aurore & Hall, Peter, 2009. "Nonparametric Prediction in Measurement Error Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 993-1003.
    15. Delaigle, Aurore & Fan, Jianqing & Carroll, Raymond J., 2009. "A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 348-359.
    16. 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.
    17. 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.
    18. Susanne M. Schennach & Halbert White & Karim Chalak, 2007. "Estimating average marginal effects in nonseparable structural systems," CeMMAP working papers CWP31/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Stéphane Bonhomme & Jean-Marc Robin, 2010. "Generalized Non-Parametric Deconvolution with an Application to Earnings Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 491-533.
    20. Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    21. Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022. "Estimation of varying coefficient models with measurement error," Journal of Econometrics, Elsevier, vol. 230(2), pages 388-415.
    22. Staudenmayer, John & Ruppert, David & Buonaccorsi, John P., 2008. "Density Estimation in the Presence of Heteroscedastic Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 726-736, June.
    23. Mohamed Doukali & Xiaojun Song & Abderrahim Taamouti, 2022. "Value-at Risk under Measurement Error," Working Papers 202209, University of Liverpool, Department of Economics.
    24. Adusumilli, Karun & Kurisu, Daisies & Otsu, Taisuke & Whang, Yoon-Jae, 2020. "Inference on distribution functions under measurement error," LSE Research Online Documents on Economics 102692, London School of Economics and Political Science, LSE Library.
    25. 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.
    26. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. Irene Botosaru, 2017. "Identifying Distributions in a Panel Model with Heteroskedasticity: An Application to Earnings Volatility," Discussion Papers dp17-11, Department of Economics, Simon Fraser University.
    28. Adusumilli, Karun & Kurisu, Daisuke & Otsu, Taisuke & Whang, Yoon-Jae, 2020. "Inference on distribution functions under measurement error," Journal of Econometrics, Elsevier, vol. 215(1), pages 131-164.
    29. 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.
    30. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    31. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    32. Choo, Eugene & Eid, Jean, 2008. "Interregional Price Difference in the New Orleans Auctions Market for Slaves," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 486-509.
    33. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(4), pages 1010-1043, August.
    34. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers 37/13, Institute for Fiscal Studies.
    35. Hu, Yingyao & Sasaki, Yuya, 2015. "Closed-form estimation of nonparametric models with non-classical measurement errors," Journal of Econometrics, Elsevier, vol. 185(2), pages 392-408.
    36. Abhra Sarkar & Bani K. Mallick & Raymond J. Carroll, 2014. "Bayesian semiparametric regression in the presence of conditionally heteroscedastic measurement and regression errors," Biometrics, The International Biometric Society, vol. 70(4), pages 823-834, December.
    37. Daisuke Kurisu & Taisuke Otsu, 2021. "On linearization of nonparametric deconvolution estimators for repeated measurements model," STICERD - Econometrics Paper Series 615, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    38. Botosaru, Irene & Sasaki, Yuya, 2018. "Nonparametric heteroskedasticity in persistent panel processes: An application to earnings dynamics," Journal of Econometrics, Elsevier, vol. 203(2), pages 283-296.
    39. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
    40. Qiying Wang & Peter C.B. Phillips & Ioannis Kasparis, 2017. "Latent Variable Nonparametric Cointegrating Regression," Cowles Foundation Discussion Papers 2111, Cowles Foundation for Research in Economics, Yale University.
    41. Eric Blankmeyer, 2018. "Measurement Errors as Bad Leverage Points," Papers 1807.02814, arXiv.org, revised Mar 2020.
    42. Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," LSE Research Online Documents on Economics 112676, London School of Economics and Political Science, LSE Library.

  20. Schennach, Susanne M., 2004. "Exponential specifications and measurement error," Economics Letters, Elsevier, vol. 85(1), pages 85-91, October.

    Cited by:

    1. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    2. Reese, Simon & Li, Yushu, 2013. "Testing for Structural Breaks in the Presence of Data Perturbations: Impacts and Wavelet Based Improvements," Working Papers 2013:36, Lund University, Department of Economics.
    3. Ramazan Gencay & Nikola Gradojevic, 2009. "Errors-in-Variables Estimation with No Instruments," Working Paper series 30_09, Rimini Centre for Economic Analysis.

  21. Susanne M. Schennach, 2004. "Estimation of Nonlinear Models with Measurement Error," Econometrica, Econometric Society, vol. 72(1), pages 33-75, January.

    Cited by:

    1. Flavio Cunha & James Heckman, 2007. "The Evolution of Inequality, Heterogeneity and Uncertainty in Labor Earnings in the U.S. Economy," PIER Working Paper Archive 07-032, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. Hahn, Jinyong & Hausman, Jerry & Kim, Jeonghwan, 2021. "A small sigma approach to certain problems in errors-in-variables models," Economics Letters, Elsevier, vol. 208(C).
    3. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    4. Yonghong An & Wang Le & Ruli Xiao, 2015. "Your American Dream is Not Mine! A New Approach to Estimating Intergenerational Mobility Elasticities," CAEPR Working Papers 2015-016, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    5. Susanne Schennach & James Heckman & Flavio Cunha, 2007. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," 2007 Meeting Papers 973, Society for Economic Dynamics.
    6. Huijun Guo & Youming Liu, 2017. "Strong consistency of wavelet estimators for errors-in-variables regression model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 121-144, February.
    7. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    8. Margherita Comola & Marcel Fafchamps, 2016. "The Missing Transfers: Estimating Mis-reporting in Dyadic Data," PSE-Ecole d'économie de Paris (Postprint) hal-01306614, HAL.
    9. Delaigle, Aurore & Meister, Alexander, 2007. "Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1416-1426, December.
    10. 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.
    11. 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.
    12. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio Codina, 2017. "Estimating the production function for human capital: results from a randomized controlled trial in Colombia," IFS Working Papers W17/06, Institute for Fiscal Studies.
    13. 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).
    14. Chen Zhen & Justin L. Taylor & Mary K. Muth & Ephraim Leibtag, 2009. "Understanding Differences in Self-Reported Expenditures between Household Scanner Data and Diary Survey Data: A Comparison of Homescan and Consumer Expenditure Survey," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(3), pages 470-492, September.
    15. Flavio Cunha & Fatih Karahan & Ilton Soares, 2011. "Returns to Skills and the College Premium," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(s1), pages 39-86, August.
    16. Huijun Guo & Youming Liu, 2019. "Regression estimation under strong mixing data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(3), pages 553-576, June.
    17. 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.
    18. Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2023. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1265-1303.
    19. Mittag, Nikolas, 2016. "Correcting for Misreporting of Government Benefits," IZA Discussion Papers 10266, Institute of Labor Economics (IZA).
    20. Ramalho Esmeralda A., 2010. "Covariate Measurement Error: Bias Reduction under Response-Based Sampling," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-34, September.
    21. Chong Terence Tai-Leung & Chen Haiqiang & Wong Tsz-Nga & Yan Isabel Kit-Ming, 2018. "Estimation and inference of threshold regression models with measurement errors," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1-16, April.
    22. Martin Browning & Thomas Crossley, 2009. "Are two cheap, noisy measures better than one expensive, accurate one?," IFS Working Papers W09/01, Institute for Fiscal Studies.
    23. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.
    24. 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.
    25. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Second Version," PIER Working Paper Archive 15-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 11 Nov 2015.
    26. 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.
    27. Gabriel Montes-Rojas, 2011. "Quantile Regression with Classical Additive Measurement Errors," Economics Bulletin, AccessEcon, vol. 31(4), pages 2863-2868.
    28. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio-Codina, 2015. "Estimating the Production Function for Human Capital: Results from a Randomized Control Trial in Colombia," Cowles Foundation Discussion Papers 1987, Cowles Foundation for Research in Economics, Yale University.
    29. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.
    30. Hu, Yingyao & Schennach, Susanne & Shiu, Ji-Liang, 2022. "Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 226(2), pages 269-294.
    31. 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.
    32. Garcia, Tanya P. & Ma, Yanyuan, 2017. "Simultaneous treatment of unspecified heteroskedastic model error distribution and mismeasured covariates for restricted moment models," Journal of Econometrics, Elsevier, vol. 200(2), pages 194-206.
    33. Carroll, Raymond J. & Delaigle, Aurore & Hall, Peter, 2009. "Nonparametric Prediction in Measurement Error Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 993-1003.
    34. Delaigle, Aurore & Fan, Jianqing & Carroll, Raymond J., 2009. "A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 348-359.
    35. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Third Version," PIER Working Paper Archive 15-040, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 24 Nov 2015.
    36. 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.
    37. Jane Cooley Fruehwirth & Salvador Navarro & Yuya Takahashi, 2011. "How The Timing of Grade Retention Affects Outcomes: Identification and Estimation of Time-Varying Treatment Effects," Working Papers 2011-015, Human Capital and Economic Opportunity Working Group.
    38. Davezies, Laurent & D'Haultfoeuille, Xavier & Fougère, Denis, 2006. "Identification of Peer Effects Using Group Size Variation," IZA Discussion Papers 2324, Institute of Labor Economics (IZA).
    39. Cui, Hengjian & Hu, Tao, 2011. "On nonlinear regression estimator with denoised variables," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1137-1149, February.
    40. Xianzheng Huang & Haiming Zhou, 2017. "An alternative local polynomial estimator for the error-in-variables problem," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(2), pages 301-325, April.
    41. 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.
    42. Flávio Cunha, 2011. "Recent Developments in the Identification and Estimation of Production Functions of Skills," Fiscal Studies, Institute for Fiscal Studies, vol. 32(2), pages 297-316, June.
    43. 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.
    44. Susanne M. Schennach & Halbert White & Karim Chalak, 2007. "Estimating average marginal effects in nonseparable structural systems," CeMMAP working papers CWP31/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    45. Otsu, Taisuke & Taylor, Luke, 2020. "Specification testing for errors-in-variables models," LSE Research Online Documents on Economics 102690, London School of Economics and Political Science, LSE Library.
    46. Sule Alan & Martin Browning, 2010. "Estimating Intertemporal Allocation Parameters using Synthetic Residual Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(4), pages 1231-1261.
    47. Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Average Derivative Estimation Under Measurement Error," Departmental Working Papers 1901, Southern Methodist University, Department of Economics.
    48. Susanne M. Schennach & Yingyao Hu, 2012. "Nonparametric identification and semiparametric estimation of classical measurement error models without side information," CeMMAP working papers CWP40/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    49. Biørn, Erik, 2017. "Identification and Method of Moments Estimation in Polynomial Measurement Error Models," Memorandum 01/2017, Oslo University, Department of Economics.
    50. Carletto,Calogero & Dillon,Andrew S. & Zezza,Alberto, 2021. "Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage," Policy Research Working Paper Series 9745, The World Bank.
    51. Stéphane Bonhomme & Jean-Marc Robin, 2010. "Generalized Non-Parametric Deconvolution with an Application to Earnings Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 491-533.
    52. 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.
    53. 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.
    54. Xavier d'Haultfoeuille, 2006. "On the Completeness Condition in Nonparametric Instrumental Problems," Working Papers 2006-32, Center for Research in Economics and Statistics.
    55. Galvao Jr, A. F. & Montes-Rojas, G., 2009. "Instrumental variables quantile regression for panel data with measurement errors," Working Papers 09/06, Department of Economics, City University London.
    56. Susanne M. Schennach, 2013. "Regressions with Berkson errors in covariates - a nonparametric approach," CeMMAP working papers 22/13, Institute for Fiscal Studies.
    57. Susanne M Schennach, 2007. "Instrumental Variable Estimation of Nonlinear Errors-in-Variables Models," Econometrica, Econometric Society, vol. 75(1), pages 201-239, January.
    58. 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.
    59. Battistin, Erich & Chesher, Andrew, 2014. "Treatment effect estimation with covariate measurement error," Journal of Econometrics, Elsevier, vol. 178(2), pages 707-715.
    60. Christoph T. Weiss, 2012. "Persistent Attitudes and Behaviors," "Marco Fanno" Working Papers 0143, Dipartimento di Scienze Economiche "Marco Fanno".
    61. Aprajit Mahajan, 2006. "Identification and Estimation of Regression Models with Misclassification," Econometrica, Econometric Society, vol. 74(3), pages 631-665, May.
    62. Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    63. Yingyao Hu & Arthur Lewbel & Susanne M. Schennach, 2007. "Nonparametric identification of the classical errors-in-variables model without side information," CeMMAP working papers CWP14/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    64. Louis‐Philippe Morin, 2013. "Estimating the benefit of high school for university‐bound students: evidence of subject‐specific human capital accumulation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(2), pages 441-468, May.
    65. 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.
    66. El-Attar, Mayssun & Poschke, Markus, 2010. "Trust and the Choice Between Housing and Financial Assets: Evidence from Spanish Households," IZA Discussion Papers 5246, Institute of Labor Economics (IZA).
    67. Corrado, L. & Weeks, M., 2010. "Identification Strategies in Survey Response Using Vignettes," Cambridge Working Papers in Economics 1031, Faculty of Economics, University of Cambridge.
    68. 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.
    69. Zinde-Walsh, Victoria, 2008. "Kernel Estimation When Density May Not Exist," Econometric Theory, Cambridge University Press, vol. 24(3), pages 696-725, June.
    70. Ben-Moshe, Dan, 2018. "Identification Of Joint Distributions In Dependent Factor Models," Econometric Theory, Cambridge University Press, vol. 34(1), pages 134-165, February.
    71. 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.
    72. Pietro Biroli, 2017. "Health and Skill Formation in Early Childhood," CHILD Working Papers Series 52 JEL Classification: J2, Centre for Household, Income, Labour and Demographic Economics (CHILD) - CCA.
    73. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    74. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    75. Irene Botosaru, 2017. "Identifying Distributions in a Panel Model with Heteroskedasticity: An Application to Earnings Volatility," Discussion Papers dp17-11, Department of Economics, Simon Fraser University.
    76. Timothy Erickson & Toni M. Whited, 2006. "On the Accuracy of Different Measures of q," Financial Management, Financial Management Association International, vol. 35(3), pages 5-33, September.
    77. Deng, Ping & Hu, Yingyao, 2009. "Bounding the effect of a dichotomous regressor with arbitrary measurement errors," Economics Letters, Elsevier, vol. 105(3), pages 256-260, December.
    78. 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.
    79. 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.
    80. Mayssun El-Attar, 2013. "Trust, child care technology choice and female labor force participation," Review of Economics of the Household, Springer, vol. 11(4), pages 507-544, December.
    81. Evdokimov, Kirill & White, Halbert, 2012. "Some Extensions Of A Lemma Of Kotlarski," Econometric Theory, Cambridge University Press, vol. 28(4), pages 925-932, August.
    82. D’Haultfœuille, Xavier & Février, Philippe, 2015. "Identification of mixture models using support variations," Journal of Econometrics, Elsevier, vol. 189(1), pages 70-82.
    83. 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.
    84. Andrei Zeleneev & Kirill Evdokimov, 2023. "Simple estimation of semiparametric models with measurement errors," CeMMAP working papers 10/23, Institute for Fiscal Studies.
    85. Zhuan Pei & Yi Shen, 2016. "The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable," Working Papers 606, Princeton University, Department of Economics, Industrial Relations Section..
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    87. Comola, Margherita & Fafchamps, Marcel, 2014. "Estimating Mis-reporting in Dyadic Data: Are Transfers Mutually Beneficial?," IZA Discussion Papers 8664, Institute of Labor Economics (IZA).
    88. Yingyao Hu & Matthew Shum, 2008. "Nonparametric Identification of Dynamic Models with Unobserved State Variables," Economics Working Paper Archive 543, The Johns Hopkins University,Department of Economics.
    89. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    90. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(4), pages 1010-1043, August.
    91. Xiaohong Chen & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric Identification and Estimation of Nonclassical Errors-in-Variables Models Without Additional Information," Boston College Working Papers in Economics 676, Boston College Department of Economics.
    92. Hyeog Ug Kwon & Futoshi Narita & Machiko Narita, 2015. "Resource Reallocation and Zombie Lending in Japan in the 1990s," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(4), pages 709-732, October.
    93. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers 37/13, Institute for Fiscal Studies.
    94. Hu, Yingyao & Sasaki, Yuya, 2015. "Closed-form estimation of nonparametric models with non-classical measurement errors," Journal of Econometrics, Elsevier, vol. 185(2), pages 392-408.
    95. 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.
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