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Ivan Fernandez-Val

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.

Working papers

  1. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2023. "Distribution regression with sample selection and UK wage decomposition," CeMMAP working papers 09/23, Institute for Fiscal Studies.

    Cited by:

    1. Onil Boussim, 2023. "Correcting Selection Bias in Standardized Test Comparisons," Papers 2309.10642, arXiv.org, revised Feb 2025.

  2. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis & Peracchi, Franco, 2022. "Selection and the Distribution of Female Hourly Wages in the U.S," IZA Discussion Papers 15028, Institute of Labor Economics (IZA).

    Cited by:

    1. Tromp, Nikolas, 2019. "The narrowing gender wage gap in South Korea," Journal of the Japanese and International Economies, Elsevier, vol. 53(C), pages 1-1.

  3. Ivan Fernandez-Val & Wayne Yuan Gao & Yuan Liao & Francis Vella, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," Papers 2202.04154, arXiv.org, revised Jan 2023.

    Cited by:

    1. Blaise Melly & Martina Pons, 2025. "Minimum Distance Estimation of Quantile Panel Data Models," Papers 2502.18242, arXiv.org.

  4. Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2021. "Low-rank approximations of nonseparable panel models," CeMMAP working papers CWP10/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    2. Anish Agarwal & Vasilis Syrgkanis, 2022. "Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime," Papers 2210.11003, arXiv.org.
    3. Ben Deaner & Chen-Wei Hsiang & Andrei Zeleneev, 2025. "Inferring Treatment Effects in Large Panels by Uncovering Latent Similarities," Papers 2503.20769, arXiv.org, revised Mar 2025.
    4. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    5. Anish Agarwal & Keegan Harris & Justin Whitehouse & Zhiwei Steven Wu, 2023. "Adaptive Principal Component Regression with Applications to Panel Data," Papers 2307.01357, arXiv.org, revised Aug 2024.
    6. Timothy B. Armstrong & Martin Weidner & Andrei Zeleneev, 2024. "Robust estimation and inference in panels with interactive fixed effects," CeMMAP working papers 28/24, Institute for Fiscal Studies.
    7. Anish Agarwal & Munther Dahleh & Devavrat Shah & Dennis Shen, 2021. "Causal Matrix Completion," Papers 2109.15154, arXiv.org.
    8. 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.
    9. Hugo Freeman, 2022. "Linear Multidimensional Regression with Interactive Fixed-Effects," Papers 2209.11691, arXiv.org, revised Mar 2025.

  5. Ivan Fernandez-Val & Franco Peracchi & Francis Vella & Aico van Vuuren, 2019. "Decomposing Changes in the Distribution of Real Hourly Wages in the U.S," CeMMAP working papers CWP61/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Bernd Fitzenberger & Jakob Lazzer, 2022. "Changing selection into full-time work and its effect on wage inequality in Germany," Empirical Economics, Springer, vol. 62(1), pages 247-277, January.

  6. Shuowen Chen & Victor Chernozhukov & Ivan Fernandez-Val, 2019. "Mastering Panel Metrics: Causal Impact of Democracy on Growth," CeMMAP working papers CWP33/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Arindrajit Dube & Daniele Girardi & Òscar Jordà & Alan M. Taylor, 2023. "A Local Projections Approach to Difference-in-Differences Event Studies," Working Paper Series 2023-12, Federal Reserve Bank of San Francisco.
    2. Mountford, Andrew, 2024. "Economic Growth Analysis When Balanced Growth Paths May Be Time Varying," MPRA Paper 119938, University Library of Munich, Germany.
    3. Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org.
    4. Christoph Morosoli & Peter Draper & Andreas Freytag & Sebastian Schuhmann, 2024. "Drivers of Inclusive Development: An Empirical Investigation," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 36(4), pages 987-1015, August.
    5. Fontanari, Claudia, 2024. "The role of wages in triggering innovation and productivity: A dynamic exploration for European economies," Economic Modelling, Elsevier, vol. 130(C).
    6. Victor Chernozhukov & Hiroyuki Kasaha & Paul Schrimpf, 2020. "Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S," Papers 2005.14168, arXiv.org, revised Oct 2020.
    7. Emanuele Amodio & Michele Battisti & Antonio Francesco Gravina & Andrea Mario Lavezzi & Giuseppe Maggio, 2023. "School‐age vaccination, school openings and Covid‐19 diffusion," Health Economics, John Wiley & Sons, Ltd., vol. 32(5), pages 1084-1100, May.
    8. Hryshko, Dmytro & Manovskii, Iourii, 2022. "How much consumption insurance in the U.S.?," Journal of Monetary Economics, Elsevier, vol. 130(C), pages 17-33.
    9. Andrew Chia, 2021. "Automatically Differentiable Random Coefficient Logistic Demand Estimation," Papers 2106.04636, arXiv.org.
    10. Ihsaan Bassier & Arindrajit Dube & Suresh Naidu, 2020. "Monopsony in Movers: The Elasticity of Labor Supply to Firm Wage Policies," NBER Working Papers 27755, National Bureau of Economic Research, Inc.

  7. Fernandez-Val , Ivan & van Vuuren, Aico & Vella, Francis, 2018. "Nonseparable Sample Selection Models with Censored Selection Rules," Working Papers in Economics 716, University of Gothenburg, Department of Economics.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.
    2. Matthias Westphal & Daniel A. Kamhöfer & Hendrik Schmitz, 2020. "Marginal College Wage Premiums under Selection into Employment," Working Papers CIE 133, Paderborn University, CIE Center for International Economics.
    3. Biewen, Martin & Fitzenberger, Bernd & Seckler, Matthias, 2020. "Counterfactual quantile decompositions with selection correction taking into account Huber/Melly (2015): An application to the German gender wage gap," Labour Economics, Elsevier, vol. 67(C).
    4. 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.
    5. Whitney K. Newey & Sami Stouli, 2018. "Control variables, discrete instruments, and identification of structural functions," CeMMAP working papers CWP55/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Fan Wu & Yi Xin, 2024. "Estimating Nonseparable Selection Models: A Functional Contraction Approach," Papers 2411.01799, arXiv.org, revised Feb 2025.

  8. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández-Val, 2018. "Generic Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," NBER Working Papers 24678, National Bureau of Economic Research, Inc.

    Cited by:

    1. Athey, Susan & Bergstrom, Katy & Hadad, Vitor & Jamison, Julian C. & Ozler, Berk & Parisotto, Luca & Sama, Julius Dohbit, 2021. "Shared Decision-Making: Can Improved Counseling Increase Willingness to Pay for Modern Contraceptives?," Research Papers 3987, Stanford University, Graduate School of Business.
    2. Jeffrey G. Shrader & Laura Bakkensen & Derek Lemoine, 2023. "Fatal Errors: The Mortality Value of Accurate Weather Forecasts," NBER Working Papers 31361, National Bureau of Economic Research, Inc.
    3. Jonas Hjort & Vinayak Iyer & Golvine de Rochambeau, 2020. "Informational Barriers to Market Access: Experimental Evidence from Liberian Firms," Working Papers hal-03389180, HAL.
    4. Odran Bonnet & Étienne Fize & Tristan Loisel & Lionel Wilner, 2024. "Compensating against fuel price inflation: Price subsidies or transfers?," PSE-Ecole d'économie de Paris (Postprint) hal-04799412, HAL.
    5. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    6. World Bank, 2021. "Promoting Women Entrepreneurs in Mexico Report," World Bank Publications - Reports 37323, The World Bank Group.
    7. Liu, Lin & Mukherjee, Rajarshi & Robins, James M., 2024. "Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators," Journal of Econometrics, Elsevier, vol. 240(2).
    8. Petru Crudu & Giacomo Pasini, 2023. "The Health Burden of Job Strain: Evidence from Europe," Working Papers 2023:19, Department of Economics, University of Venice "Ca' Foscari".
    9. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    10. Abhijit Banerjee & Esther Duflo & Amy Finkelstein & Lawrence F. Katz & Benjamin A. Olken & Anja Sautmann, 2020. "In Praise of Moderation: Suggestions for the Scope and Use of Pre-Analysis Plans for RCTs in Economics," NBER Working Papers 26993, National Bureau of Economic Research, Inc.
    11. Strittmatter, Anthony, 2019. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," GLO Discussion Paper Series 336, Global Labor Organization (GLO).
    12. Simon Briole & Marc Gurgand & Eric Maurin & Sandra Mcnally & Jenifer Ruiz-Valenzuela & Daniel Santin, 2024. "The Making of Civic Virtues: A School-Based Experiment in Three Countries," Working Papers halshs-04720970, HAL.
    13. Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022. "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers 22-059, ZEW - Leibniz Centre for European Economic Research.
    14. Simon Briole & Augustin Colette & Emmanuelle Lavaine, 2023. "The Heterogeneous Effects of Lockdown Policies on Air Pollution," Post-Print hal-04217143, HAL.
    15. Abhijit Banerjee & Emily Breza & Esther Duflo & Cynthia Kinnan, 2019. "Can Microfinance Unlock a Poverty Trap for Some Entrepreneurs?," NBER Working Papers 26346, National Bureau of Economic Research, Inc.
    16. Yingheng Zhang & Haojie Li & Gang Ren, 2025. "Data-driven exploration of heterogeneous gasoline price elasticities using generalized random forests," Transportation, Springer, vol. 52(1), pages 215-237, February.
    17. Chaisemartin, Clement de & Navarrete, Nicolas, 2019. "The direct and spillover effects of a mental health program for disruptive students," CAGE Online Working Paper Series 401, Competitive Advantage in the Global Economy (CAGE).
    18. De Neve, Jan-Emmanuel & Imbert, Clement & Spinnewijn, Johannes & Tsankova, Teodora & Luts, Maarten, 2019. "How to Improve Tax Compliance? Evidence from Population-wide Experiments in Belgium," The Warwick Economics Research Paper Series (TWERPS) 1194, University of Warwick, Department of Economics.
    19. Stefano Caria & Grant Gordon & Maximilian Kasy & Simon Quinn & Soha Shami & Alexander Teytelboym, 2020. "An Adaptive Targeted Field Experiment: Job Search Assistance for Refugees in Jordan," CESifo Working Paper Series 8535, CESifo.
    20. Sandrine Mesplé-Somps & Björn Nilsson, 2020. "Role models and migration intentions," Working Papers DT/2020/13, DIAL (Développement, Institutions et Mondialisation).
    21. Pedro Forquesato, 2022. "Who Benefits from Political Connections in Brazilian Municipalities," Papers 2204.09450, arXiv.org.
    22. Taiyo Fukai & Hidehiko Ichimura & Keisuke Kawata, 2021. "Describing the impacts of COVID-19 on the labor market in Japan until June 2020," The Japanese Economic Review, Springer, vol. 72(3), pages 439-470, July.
    23. Odran Bonnet & Étienne Fize & Tristan Loisel & Lionel Wilner, 2024. "Compensation against Fuel Inflation: Temporary Tax Rebates or Transfers?," CESifo Working Paper Series 10917, CESifo.
    24. Conner Mullally & Mayra Rivas & Travis McArthur, 2021. "Using Machine Learning to Estimate the Heterogeneous Effects of Livestock Transfers," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1058-1081, May.
    25. Benjamin A. Olken, 2020. "Banerjee, Duflo, Kremer, and the Rise of Modern Development Economics," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(3), pages 853-878, July.
    26. Maria Nareklishvili & Nicholas Polson & Vadim Sokolov, 2022. "Feature Selection for Personalized Policy Analysis," Papers 2301.00251, arXiv.org, revised Jul 2023.
    27. Devoto,Florencia & Emanuela Galasso & Kathleen G. Beegle & Stefanie Brodmann, 2024. "Women at Work : Evidence from a Randomized Experiment in Urban Djibouti," Policy Research Working Paper Series 10906, The World Bank.
    28. Kroczek, Martin & Kugler, Philipp, 2022. "Heterogeneous Effects of Monetary and Non-Monetary Job Characteristics on Job Attractiveness in Nursing," VfS Annual Conference 2022 (Basel): Big Data in Economics 264108, Verein für Socialpolitik / German Economic Association.
    29. Markus Eyting, 2020. "A Random Forest a Day Keeps the Doctor Away," Working Papers 2026, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    30. Ubfal,Diego Javier, 2024. "What Works in Supporting Women-Led Businesses ?," Policy Research Working Paper Series 10744, The World Bank.
    31. Daniel Jacob, 2021. "CATE meets ML," Digital Finance, Springer, vol. 3(2), pages 99-148, June.
    32. Ta-Wei Huang & Eva Ascarza, 2024. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals," Marketing Science, INFORMS, vol. 43(4), pages 863-884, July.
    33. Jeffrey Smith, 2022. "Treatment Effect Heterogeneity," Evaluation Review, , vol. 46(5), pages 652-677, October.
    34. David Glynn & John Giardina & Julia Hatamyar & Ankur Pandya & Marta Soares & Noemi Kreif, 2024. "Integrating decision modeling and machine learning to inform treatment stratification," Health Economics, John Wiley & Sons, Ltd., vol. 33(8), pages 1772-1792, August.
    35. Aparajithan Venkateswaran & Anirudh Sankar & Arun G. Chandrasekhar & Tyler H. McCormick, 2024. "Robustly estimating heterogeneity in factorial data using Rashomon Partitions," Papers 2404.02141, arXiv.org, revised Aug 2024.
    36. Dar, Manzoor H. & de Janvry, Alain & Emerick, Kyle & Kelley, Erin M. & Sadoulet, Elisabeth, 2019. "Endogenous Information Sharing and the Gains from Using Network Information to Maximize Technology Adoption," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt8qx7m4zq, Department of Agricultural & Resource Economics, UC Berkeley.
    37. Douglas Kiarelly Godoy de Araujo, 2023. "gingado: a machine learning library focused on economics and finance," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Data science in central banking: applications and tools, volume 59, Bank for International Settlements.
    38. Lily Davies & Mark Kattenberg & Benedikt Vogt, 2023. "Predicting Firm Exits with Machine Learning: Implications for Selection into COVID-19 Support and Productivity Growth," CPB Discussion Paper 444, CPB Netherlands Bureau for Economic Policy Analysis.
    39. Piasenti, Stefano & Valente, Marica & van Veldhuizen, Roel & Pfeifer, Gregor, 2023. "Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions," IZA Discussion Papers 16324, Institute of Labor Economics (IZA).
    40. David M. Ritzwoller & Joseph P. Romano, 2023. "Reproducible Aggregation of Sample-Split Statistics," Papers 2311.14204, arXiv.org, revised Nov 2024.
    41. Sendhil Mullainathan & Ashesh Rambachan, 2024. "From Predictive Algorithms to Automatic Generation of Anomalies," Papers 2404.10111, arXiv.org.
    42. Dorothee Weiffen & Ghassan Baliki & Tilman Brück, 2022. "Violent conflict moderates food security impacts of agricultural asset transfers in Syria: A heterogeneity analysis using machine learning," HiCN Working Papers 381, Households in Conflict Network.
    43. Francisco Gallego & Ofer Malamud & Cristian Pop-Eleches, 2017. "Parental Monitoring and Children's Internet Use: The Role of Information, Control, and Cues," NBER Working Papers 23982, National Bureau of Economic Research, Inc.
    44. Dmitry Arkhangelsky & Kazuharu Yanagimoto & Tom Zohar, 2024. "Using Event Studies as an Outcome in Causal Analysis," Papers 2403.19563, arXiv.org, revised Jan 2025.
    45. Emily Breza & Arun G. Chandrasekhar & Davide Viviano, 2025. "Generalizability with ignorance in mind: learning what we do (not) know for archetypes discovery," Papers 2501.13355, arXiv.org.
    46. Patrick Bajari & Zhihao Cen & Victor Chernozhukov & Manoj Manukonda & Jin Wang & Ramon Huerta & Junbo Li & Ling Leng & George Monokroussos & Suhas Vijaykunar & Shan Wan, 2023. "Hedonic prices and quality adjusted price indices powered by AI," CeMMAP working papers 08/23, Institute for Fiscal Studies.
    47. Yanqing Yang & Nan Zhang & Jinfeng Ge & Yan Xu, 2025. "Sino-US S and T Frictions and Transnational Knowledge Flows: Evidence from machine learning and cross-national patent data," Papers 2503.21822, arXiv.org.
    48. Simon Calmar Andersen & Louise Beuchert & Phillip Heiler & Helena Skyt Nielsen, 2023. "A Guide to Impact Evaluation under Sample Selection and Missing Data: Teacher's Aides and Adolescent Mental Health," Papers 2308.04963, arXiv.org.
    49. Rachel Cassidy & Menaal Fatima Ebrahim & Diego Javier Ubfal, 2024. "Testing the Promise of Digital Scaling : In-Person versus App-Based Training for Women Entrepreneurs," Policy Research Working Paper Series 10992, The World Bank.
    50. Minahil Asim & Ronak Jain & Vatsal Khandelwal, 2024. "Great expectations? Experimental evidence from schools in Pakistan," ECON - Working Papers 454, Department of Economics - University of Zurich.
    51. Kyle Myers & Wei Yang Tham, 2023. "Money, Time, and Grant Design," Papers 2312.06479, arXiv.org.
    52. Nathan Kallus, 2022. "Treatment Effect Risk: Bounds and Inference," Papers 2201.05893, arXiv.org, revised Jul 2022.
    53. Muller, Seán M., 2020. "The implications of a fundamental contradiction in advocating randomized trials for policy," World Development, Elsevier, vol. 127(C).
    54. Elek, Péter & Bíró, Anikó, 2021. "Regional differences in diabetes across Europe – regression and causal forest analyses," Economics & Human Biology, Elsevier, vol. 40(C).
    55. Sebastian Galiani & Brian Quistorff, 2022. "Assessing External Validity in Practice," NBER Working Papers 30398, National Bureau of Economic Research, Inc.
    56. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    57. Mark Kattenberg & Bas Scheer & Jurre Thiel, 2023. "Causal forests with fixed effects for treatment effect heterogeneity in difference-in-differences," CPB Discussion Paper 452, CPB Netherlands Bureau for Economic Policy Analysis.
    58. Robin Gubela & Artem Bequé & Stefan Lessmann & Fabian Gebert, 2019. "Conversion Uplift in E-Commerce: A Systematic Benchmark of Modeling Strategies," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 747-791, May.
    59. Martin Kroczek & Philipp Kugler, 2022. "Heterogeneous Effects of Monetary and Non-Monetary Job Characteristics on Job Attractiveness in Nursing," IAW Discussion Papers 139, Institut für Angewandte Wirtschaftsforschung (IAW).
    60. Vishalie Shah & Julia Hatamyar & Taufik Hidayat & Noemi Kreif, 2025. "Exploring the heterogeneous impacts of Indonesia's conditional cash transfer scheme (PKH) on maternal health care utilisation using instrumental causal forests," Papers 2501.12803, arXiv.org.
    61. Kretschmer, Sandra, 2024. "Carbon literacy – Can simple interventions help? Effect of information provision on emissions knowledge of private households," Energy Policy, Elsevier, vol. 188(C).
    62. Petru Crudu, 2023. "Long-term effects of early adverse labour market conditions: A Causal Machine Learning approach," Working Papers 2023:21, Department of Economics, University of Venice "Ca' Foscari".
    63. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    64. Phillip Heiler, 2022. "Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization," Papers 2209.04329, arXiv.org, revised Jul 2024.
    65. Mullally, Conner & Rivas, Mayra & McArthur, Travis, 2019. "Livestock Transfers Can Improve Child Health: Evidence from a Randomized Phase-In Design in Guatemala," SocArXiv c6zg5, Center for Open Science.
    66. Keshav Agrawal & Susan Athey & Ayush Kanodia & Emil Palikot, 2022. "Personalized Recommendations in EdTech: Evidence from a Randomized Controlled Trial," Papers 2208.13940, arXiv.org, revised Dec 2022.

  9. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis, 2018. "Decomposing Real Wage Changes in the United States," IZA Discussion Papers 12044, Institute of Labor Economics (IZA).

    Cited by:

    1. Sungwon Lee, 2020. "Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection," Working Papers 2012, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    2. Tromp, Nikolas, 2019. "The narrowing gender wage gap in South Korea," Journal of the Japanese and International Economies, Elsevier, vol. 53(C), pages 1-1.

  10. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2018. "Network and panel quantile effects via distribution regression," CeMMAP working papers CWP21/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2023. "Distributional Vector Autoregression: Eliciting Macro and Financial Dependence," Papers 2303.04994, arXiv.org.
    2. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    3. Alnafrah, Ibrahim & Belyaeva, Zhanna, 2024. "The nonlinear road to happiness: Making sense of ESGD impacts on well-being," Structural Change and Economic Dynamics, Elsevier, vol. 70(C), pages 365-381.
    4. Nathan Kallus & Miruna Oprescu, 2022. "Robust and Agnostic Learning of Conditional Distributional Treatment Effects," Papers 2205.11486, arXiv.org, revised Feb 2023.
    5. Andreas Dzemski, 2019. "An Empirical Model of Dyadic Link Formation in a Network with Unobserved Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 763-776, December.
    6. Céline Carrère & Monika Mrázová & J Peter Neary, 2020. "Gravity Without Apology: the Science of Elasticities, Distance and Trade," The Economic Journal, Royal Economic Society, vol. 130(628), pages 880-910.
    7. Alvarado, Rafael & Cuesta, Lizeth & Kumar, Pavan & Rehman, Abdul & Murshed, Muntasir & Işık, Cem & Vega, Nora & Ochoa-Moreno, Santiago & Tillaguango, Brayan, 2022. "Impact of natural resources on economic progress: Evidence for trading blocs in Latin America using non-linear econometric methods," Resources Policy, Elsevier, vol. 79(C).
    8. Maike Hohberg & Peter Pütz & Thomas Kneib, 2020. "Treatment effects beyond the mean using distributional regression: Methods and guidance," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-29, February.
    9. Neary, Peter & Carrère, Céline & Mrázová, Monika, 2020. "Gravity without Apologies: The Science of Elasticities, Distance, and Trade," CEPR Discussion Papers 14473, C.E.P.R. Discussion Papers.
    10. Wang, Yunyun & Oka, Tatsushi & Zhu, Dan, 2023. "Bivariate distribution regression with application to insurance data," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 215-232.
    11. Fernández-Val, Iván & Gao, Wayne Yuan & Liao, Yuan & Vella, Francis, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," IZA Discussion Papers 15236, Institute of Labor Economics (IZA).
    12. Vu, Dung Anh & Van Nguyen, Thinh & Nhu, Quang Minh & Tran, Tuyen Quang, 2024. "Does increased digital transformation promote a firm's financial performance? New insights from the quantile approach," Finance Research Letters, Elsevier, vol. 64(C).
    13. Tatsushi Oka & Shota Yasui & Yuta Hayakawa & Undral Byambadalai, 2024. "Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials," Papers 2407.14074, arXiv.org, revised Jan 2025.

  11. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Strittmatter, Anthony & Wunsch, Conny, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," IZA Discussion Papers 14128, Institute of Labor Economics (IZA).
    2. Dominik Wied, 2022. "Semiparametric Distribution Regression with Instruments and Monotonicity," Papers 2212.03704, arXiv.org.
    3. Miguel A. Delgado & Andr'es Garc'ia-Suaza & Pedro H. C. Sant'Anna, 2019. "Distribution Regression in Duration Analysis: an Application to Unemployment Spells," Papers 1904.06185, arXiv.org, revised Nov 2021.
    4. Liu, Ruixuan & Yu, Zhengfei, 2022. "Sample selection models with monotone control functions," Journal of Econometrics, Elsevier, vol. 226(2), pages 321-342.

  12. Victor Chernozhukov & Iv'n Fern'ndez-Val & Sukjin Han & Amanda E. Kowalski, 2018. "Censored Quantile Instrumental Variable Estimation with Stata," Cowles Foundation Discussion Papers 2120, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Sanna Nivakoski, 2020. "Wealth and the effect of subjective survival probability," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(2), pages 633-670, April.
    2. Abe Dunn, 2014. "Health Insurance and the Demand for Medical Care: Instrumental Variable Estimates Using Health Insurer Claims Data," BEA Working Papers 0107, Bureau of Economic Analysis.
    3. Kim, Young-Joo & Daly, Vincent, 2019. "The Education Gradient in Health: The Case of Obesity in the UK and US," Economics Discussion Papers 2019-4, School of Economics, Kingston University London.
    4. L. Benfratello & A. Bottasso & C. Piccardo, 2022. "R&D and export performance: exploring heterogeneity along the export intensity distribution," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(2), pages 189-232, June.
    5. Männasoo, Kadri, 2022. "Working hours and gender wage differentials: Evidence from the American Working Conditions Survey," Labour Economics, Elsevier, vol. 76(C).
    6. Sugimoto, Kota, 2021. "Ownership versus legal unbundling of electricity transmission network: Evidence from renewable energy investment in Germany," Energy Economics, Elsevier, vol. 99(C).
    7. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.

  13. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis, 2018. "Nonseparable Sample Selection Models with Censored Selection Rules: An Application to Wage Decompositions," IZA Discussion Papers 11294, Institute of Labor Economics (IZA).

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.
    2. Matthias Westphal & Daniel A. Kamhöfer & Hendrik Schmitz, 2020. "Marginal College Wage Premiums under Selection into Employment," Working Papers CIE 133, Paderborn University, CIE Center for International Economics.
    3. Biewen, Martin & Fitzenberger, Bernd & Seckler, Matthias, 2020. "Counterfactual quantile decompositions with selection correction taking into account Huber/Melly (2015): An application to the German gender wage gap," Labour Economics, Elsevier, vol. 67(C).
    4. Whitney K. Newey & Sami Stouli, 2018. "Control variables, discrete instruments, and identification of structural functions," CeMMAP working papers CWP55/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  14. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar Wüthrich, 2017. "Generic inference on quantile and quantile effect functions for discrete outcomes," CeMMAP working papers 23/17, Institute for Fiscal Studies.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Botha, Ferdi & de New, John P. & de New, Sonja C. & Ribar, David C. & Salamanca, Nicolás, 2020. "COVID-19 labour market shocks and their inequality implications for financial wellbeing," GLO Discussion Paper Series 661, Global Labor Organization (GLO).
    3. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.
    4. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2019. "Distributional conformal prediction," Papers 1909.07889, arXiv.org, revised Aug 2021.
    5. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
    6. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    8. Ferdi Botha & John P. de New, 2020. "COVID-19 infections, labour market shocks, and subjective well-being," Melbourne Institute Working Paper Series wp2020n14, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    9. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2023. "Distribution regression with sample selection and UK wage decomposition," CeMMAP working papers 09/23, Institute for Fiscal Studies.
    10. Valentina Corradi & Daniel Gutknecht, 2019. "Testing for Quantile Sample Selection," Papers 1907.07412, arXiv.org, revised Jan 2021.
    11. Lamarche, Carlos & Shi, Xuan & Young, Derek S., 2024. "Conditional Quantile Functions for Zero-Inflated Longitudinal Count Data," Econometrics and Statistics, Elsevier, vol. 31(C), pages 49-65.
    12. Tatsushi Oka & Shota Yasui & Yuta Hayakawa & Undral Byambadalai, 2024. "Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials," Papers 2407.14074, arXiv.org, revised Jan 2025.

  15. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers 61/17, Institute for Fiscal Studies.

    Cited by:

    1. Stephen Coussens & Jann Spiess, 2021. "Improving Inference from Simple Instruments through Compliance Estimation," Papers 2108.03726, arXiv.org.
    2. Daniel Lewis & Davide Melcangi & Laura Pilossoph, 2024. "Latent Heterogeneity in the Marginal Propensity to Consume," NBER Working Papers 32523, National Bureau of Economic Research, Inc.
    3. O'Neill, E. & Weeks, M., 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Cambridge Working Papers in Economics 1865, Faculty of Economics, University of Cambridge.
    4. Paul B. Ellickson & Wreetabrata Kar & James C. Reeder, 2023. "Estimating Marketing Component Effects: Double Machine Learning from Targeted Digital Promotions," Marketing Science, INFORMS, vol. 42(4), pages 704-728, July.
    5. Armand, Alex & Augsburg, Britta & Bancalari, Antonella & Ghatak, Maitreesh, 2023. "Public Service Delivery, Exclusion and Externalities: Theory and Experimental Evidence from India," CEPR Discussion Papers 18636, C.E.P.R. Discussion Papers.
    6. Knaus, Michael C., 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Economics Working Paper Series 2004, University of St. Gallen, School of Economics and Political Science.
    7. Matias D. Cattaneo & Max H. Farrell & Yingjie Feng, 2018. "Large Sample Properties of Partitioning-Based Series Estimators," Papers 1804.04916, arXiv.org, revised Jun 2019.
    8. Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kang, Miao & Kapadia, Sujit & Simsek, Özgür, 2020. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Bank of England working papers 848, Bank of England.
    9. Vira Semenova, 2020. "Generalized Lee Bounds," Papers 2008.12720, arXiv.org, revised May 2025.
    10. Alex Armand & Britta Augsburg & Antonella Bancalari, 2021. "Coordination and the poor maintenance trap: an experiment on public infrastructure in India," NOVAFRICA Working Paper Series wp2110, Universidade Nova de Lisboa, Nova School of Business and Economics, NOVAFRICA.
    11. Riccardo Di Francesco, 2024. "Aggregation Trees," Papers 2410.11408, arXiv.org.
    12. Eoghan O'Neill & Melvyn Weeks, 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Papers 1810.09179, arXiv.org, revised Oct 2019.

  16. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iv'an Fern'andez-Val, 2017. "Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Papers 1712.04802, arXiv.org, revised Oct 2023.

    Cited by:

    1. Bassi,Marina & Besbas,Bruno Azzedine & Dinarte Diaz,Lelys Ileana & Ravindran,Saravana & Reynoso,Ana Maria, 2024. "From Access to Achievement : The Primary School-Age Impacts of an At-Scale Preschool Construction Program in Highly Deprived Communities," Policy Research Working Paper Series 10814, The World Bank.
    2. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    3. Bertrand,Marianne & Crepon,Bruno Jacques Jean Philippe & Marguerie,Alicia Charlene & Premand,Patrick, 2021. "Do Workfare Programs Live Up to Their Promises ? Experimental Evidence from Côte d’Ivoire," Policy Research Working Paper Series 9611, The World Bank.
    4. Hoong, Ruru, 2021. "Self control and smartphone use: An experimental study of soft commitment devices," European Economic Review, Elsevier, vol. 140(C).
    5. Strittmatter, Anthony, 2019. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," GLO Discussion Paper Series 336, Global Labor Organization (GLO).
    6. Chaisemartin, Clement de & Navarrete, Nicolas, 2019. "The direct and spillover effects of a mental health program for disruptive students," CAGE Online Working Paper Series 401, Competitive Advantage in the Global Economy (CAGE).
    7. Lelys I. Dinarte Diaz & Saravana Ravindran & Manisha Shah & Shawn M. Powers & Helen Baker-Henningham, 2023. "Violent Discipline and Parental Behavior: Short- and Medium-term Effects of Virtual Parenting Support to Caregivers," NBER Working Papers 31338, National Bureau of Economic Research, Inc.
    8. Michael Vlassopoulos & Abu Siddique & Tabassum Rahman & Debayan Pakrashi & Asad Islam & Firoz Ahmed, 2021. "Improving Women's Mental Health During a Pandemic," Munich Papers in Political Economy 11, Munich School of Politics and Public Policy and the School of Management at the Technical University of Munich.
    9. Patrick Rehill, 2024. "How do applied researchers use the Causal Forest? A methodological review of a method," Papers 2404.13356, arXiv.org, revised Dec 2024.
    10. Andrew Baker & Brantly Callaway & Scott Cunningham & Andrew Goodman-Bacon & Pedro H. C. Sant'Anna, 2025. "Difference-in-Differences Designs: A Practitioner's Guide," Papers 2503.13323, arXiv.org.
    11. Christiansen, T. & Weeks, M., 2020. "Distributional Aspects of Microcredit Expansions," Cambridge Working Papers in Economics 20100, Faculty of Economics, University of Cambridge.
    12. Siddique, Abu & Islam, Asad & Mozumder, Tanvir Ahmed & Rahman, Tabassum & Shatil, Tanvir, 2022. "Forced Displacement, Mental Health, and Child Development: Evidence from the Rohingya Refugees," SocArXiv b4fc7, Center for Open Science.
    13. Dar, Manzoor H. & de Janvry, Alain & Emerick, Kyle & Kelley, Erin M. & Sadoulet, Elisabeth, 2019. "Endogenous Information Sharing and the Gains from Using Network Information to Maximize Technology Adoption," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt8qx7m4zq, Department of Agricultural & Resource Economics, UC Berkeley.
    14. Alejandro Sanchez-Becerra, 2023. "Robust inference for the treatment effect variance in experiments using machine learning," Papers 2306.03363, arXiv.org.
    15. Kayo MURAKAMI & Hideki SHIMADA & Yoshiaki USHIFUSA & Takanori IDA, 2020. "Heterogeneous Treatment Effects of Nudge and Rebate:Causal Machine Learning in a Field Experiment on Electricity Conservation," Discussion papers e-20-003, Graduate School of Economics , Kyoto University.
    16. Pramod Kumar Sur, 2021. "Understanding Vaccine Hesitancy: Empirical Evidence from India," Papers 2103.02909, arXiv.org, revised Feb 2023.
    17. Bruno Fava, 2024. "Predicting the Distribution of Treatment Effects: A Covariate-Adjustment Approach," Papers 2407.14635, arXiv.org, revised Oct 2024.
    18. Du, Tianyu & Kanodia, Ayush & Brunborg, Herman & Vafa, Keyon & Athey, Susan, 2024. "Labor-LLM: Language-Based Occupational Representations with Large Language Models," Research Papers 4188, Stanford University, Graduate School of Business.
    19. Carcillo, Stéphane & Valfort, Marie-Anne & Vergara Merino, Pedro, 2025. "Combating LGBTphobia in Schools: Evidence from a Field Experiment in France," IZA Discussion Papers 17683, Institute of Labor Economics (IZA).
    20. Girma, Sourafel & Paton, David, 2024. "Using double-debiased machine learning to estimate the impact of Covid-19 vaccination on mortality and staff absences in elderly care homes," European Economic Review, Elsevier, vol. 170(C).

  17. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.

    Cited by:

    1. Romuald Meango & Esther Mirjam Girsberger, 2023. "Just Ask Them Twice: Choice Probabilities and Identification of Ex ante returns and Willingness-To-Pay," Papers 2303.03009, arXiv.org, revised May 2025.
    2. Whitney K. Newey & Sami Stouli, 2025. "Identification of treatment effects under limited exogenous variation," CeMMAP working papers 06/25, Institute for Fiscal Studies.
    3. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    4. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.
    5. Christian Gische & Manuel C. Voelkle, 2022. "Beyond the Mean: A Flexible Framework for Studying Causal Effects Using Linear Models," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 868-901, September.
    6. Bruneel-Zupanc, Christophe Alain, 2021. "Discrete-Continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation," TSE Working Papers 21-1185, Toulouse School of Economics (TSE).
    7. Fernandez-Val , Ivan & van Vuuren, Aico & Vella, Francis, 2018. "Nonseparable Sample Selection Models with Censored Selection Rules," Working Papers in Economics 716, University of Gothenburg, Department of Economics.
    8. Dominik Wied, 2022. "Semiparametric Distribution Regression with Instruments and Monotonicity," Papers 2212.03704, arXiv.org.
    9. Tadao Hoshino, 2021. "Estimating a Continuous Treatment Model with Spillovers: A Control Function Approach," Papers 2112.15114, arXiv.org, revised Jan 2023.
    10. Jonas Meier, 2020. "Multivariate Distribution Regression," Diskussionsschriften dp2023, Universitaet Bern, Departement Volkswirtschaft.
    11. Romuald Meango, 2025. "Is the distribution of resolvable uncertainty Type I extreme value? A Test for Random Coefficient Models using Choice Probabilities," Papers 2503.13901, arXiv.org.
    12. Iv'an Fern'andez-Val & Franco Peracchi & Aico van Vuuren & Francis Vella, 2018. "Selection and the Distribution of Female Hourly Wages in the U.S," Papers 1901.00419, arXiv.org, revised Jan 2022.
    13. Meango, Romuald & Girsberger, Esther Mirjam, 2024. "Identification of Ex Ante Returns Using Elicited Choice Probabilities: An Application to Preferences for Public-Sector Jobs," IZA Discussion Papers 17174, Institute of Labor Economics (IZA).
    14. Whitney K. Newey & Sami Stouli, 2018. "Heterogenous coefficients, discrete instruments, and identification of treatment effects," CeMMAP working papers CWP66/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Richard Spady & Sami Stouli, 2020. "Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions," Papers 2011.06416, arXiv.org, revised Apr 2025.
    16. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.
    17. 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.
    18. Whitney K. Newey & Sami Stouli, 2018. "Control variables, discrete instruments, and identification of structural functions," CeMMAP working papers CWP55/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Iván Fernández‐Val & Aico van Vuuren & Francis Vella & Franco Peracchi, 2023. "Selection and the distribution of female real hourly wages in the United States," Quantitative Economics, Econometric Society, vol. 14(2), pages 571-607, May.
    20. Jayeeta Bhattacharya, 2020. "Quantile regression with generated dependent variable and covariates," Papers 2012.13614, arXiv.org.
    21. Romauld Méango, 2023. "Identification of ex ante returns using elicited choice probabilities," Economics Series Working Papers 1007, University of Oxford, Department of Economics.

  18. Victor Chernozhukov & Ivan Fernandez-Val & Tetsuya Kaji, 2017. "Extremal quantile regression: an overview," CeMMAP working papers 65/17, Institute for Fiscal Studies.

    Cited by:

    1. Xavier D’Haultfoeuille & Arnaud Maurel & Xiaoyun Qiu & Yichong Zhang, 2020. "Estimating selection models without an instrument with Stata," Stata Journal, StataCorp LLC, vol. 20(2), pages 297-308, June.
    2. Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    4. Matthew A Masten & Alexandre Poirier, 2023. "Choosing exogeneity assumptions in potential outcome models," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 327-349.
    5. Xavier D'Haultfoeuille & Arnaud Maurel & Yichong Zhang, 2014. "Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap," NBER Working Papers 20257, National Bureau of Economic Research, Inc.
    6. Matthias Fischer & Daniel Kraus & Marius Pfeuffer & Claudia Czado, 2017. "Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression," Risks, MDPI, vol. 5(3), pages 1-13, July.
    7. Yuya Sasaki & Yulong Wang, 2019. "Fixed-k Inference for Conditional Extremal Quantiles," Papers 1909.00294, arXiv.org, revised Jul 2020.
    8. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.
    9. Marian Vavra, 2023. "Bias-Correction in Time Series Quantile Regression Models," Working and Discussion Papers WP 3/2023, Research Department, National Bank of Slovakia.

  19. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers 33/17, Institute for Fiscal Studies.

    Cited by:

    1. Wang, Ao, 2020. "Identifying the Distribution of Random Coefficients in BLP Demand Models Using One Single Variation in Product Characteristics," The Warwick Economics Research Paper Series (TWERPS) 1304, University of Warwick, Department of Economics.
    2. Laurent Davezies & Xavier D’Haultfoeuille & Louise Laage, 2025. "Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models," Working Papers 2025-02, Center for Research in Economics and Statistics.
    3. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    4. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Discussion Paper 2022-009, Tilburg University, Center for Economic Research.
    5. Wang, Ao, 2023. "Sieve BLP: A semi-nonparametric model of demand for differentiated products," Journal of Econometrics, Elsevier, vol. 235(2), pages 325-351.

  20. Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers 42/17, Institute for Fiscal Studies.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    3. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2020. "Is there a euro effect in the drivers of US FDI? New evidence using Bayesian Model Averaging techniques," Working Papers 2020/25, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. Camarero, Mariam & Moliner, Sergi & Tamarit, Cecilio, 2024. "A Fresh Assessment of the Depth of the “Euro Effect" on US FDI," Single Market Economics Papers WP2024/18, Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs (European Commission), Chief Economist Team.
    5. Thierry Magnac & Sébastien Roux, 2021. "Heterogeneity and wage inequalities over the life cycle," Post-Print hal-04532017, HAL.
    6. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.
    7. Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2019. "Two-Step Estimation and Inference with Possibly Many Included Covariates," University of California at San Diego, Economics Working Paper Series qt86c7x315, Department of Economics, UC San Diego.
    8. Yugang He, 2024. "E-commerce and foreign direct investment: pioneering a new era of trade strategies," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    9. Martin Weidner & Thomas Zylkin, 2021. "Bias and consistency in three-way gravity models," CeMMAP working papers CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased Inference for Dynamic Nonlinear Panels with Multi-dimensional Heterogeneities," Papers 2305.03134, arXiv.org, revised Nov 2024.
    11. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    12. Birzhan Batkeyev & David R. DeRemer, 2022. "Mountains of Evidence: The Effects of Abnormal Air Pollution on Crime," Working Papers 2022/04, Nazarbayev University, Graduate School of Business.
    13. Gobillon, Laurent & Magnac, Thierry & Roux, Sébastien, 2022. "Lifecycle Wages and Human Capital Investments: Selection and Missing Data," CEPR Discussion Papers 16999, C.E.P.R. Discussion Papers.
    14. Yugang He, 2024. "Artificial intelligence and socioeconomic forces: transforming the landscape of religion," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    15. Yafei Wang & Zihan Zhao & Ming Xu & Zhixiong Tan & Jingwei Han & Lichen Zhang & Siying Chen, 2023. "Agriculture–Tourism Integration’s Impact on Agricultural Green Productivity in China," Agriculture, MDPI, vol. 13(10), pages 1-22, October.
    16. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org, revised Nov 2024.
    17. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2022. "A fresh assessment of the euro effect on outward US FDI," Working Papers 2209, Department of Applied Economics II, Universidad de Valencia.
    18. Quang Khai Nguyen, 2024. "How Does Financial Flexibility Strategy Impact on Risk Management Effectiveness?," SAGE Open, , vol. 14(2), pages 21582440241, May.
    19. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2020. "Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model," Working Papers 2007, Department of Applied Economics II, Universidad de Valencia.
    20. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    21. Soyoung Kim & Yuki Higuchi & Kei Kajisa & Yasuyuki Sawada, 2024. "Infrastructure and Structural Transformation: Evidence from Satellite, Administrative, and Multi-Generation Household Data in a Developing Country," CIRJE F-Series CIRJE-F-1237, CIRJE, Faculty of Economics, University of Tokyo.
    22. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    23. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    24. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    25. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    26. Bo E Honoré & Áureo de Paula, 2021. "Identification in simple binary outcome panel data models," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 78-93.
    27. Jochmans, Koen, 2024. "Modified-likelihood estimation of fixed-effect models for dyadic data," TSE Working Papers 24-1502, Toulouse School of Economics (TSE).
    28. Mariam Camarero & Laura Montolio & Cecilio Tamarit, 2022. "Explaining German outward FDI in the EU: a reassessment using Bayesian model averaging and GLM estimators," Empirical Economics, Springer, vol. 62(2), pages 487-511, February.
    29. Mingyang Li & Linlin Niu & Andrew Pua, 2020. "Market Pricing of Fundamentals at the Shanghai Stock Exchange: Evidence from a Dividend Discount Model with Adaptive Expectations," Working Papers 2020-12-30, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    30. Zhang, Huiming & Huang, Jiying & Wu, Kai & Wang, Shouyang & Nygaard, Christian & Qiu, Yueming, 2022. "Do political connections affect corporate poverty alleviation decisions? Evidence from China," China Economic Review, Elsevier, vol. 73(C).
    31. Paulo M.M. Rodrigues & Pedro Portugal & Anabela Carneiro, 2021. "The persistence of wages," Working Papers w202112, Banco de Portugal, Economics and Research Department.
    32. Okafor, Luke & Yan, Eric, 2022. "Covid-19 vaccines, rules, deaths, and tourism recovery," Annals of Tourism Research, Elsevier, vol. 95(C).
    33. Fernández-Val, Iván & Gao, Wayne Yuan & Liao, Yuan & Vella, Francis, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," IZA Discussion Papers 15236, Institute of Labor Economics (IZA).
    34. Yuki Takara & Shingo Takagi, 2023. "An empirical approach to measure unobserved cultural relations using music trade data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(2), pages 205-245, June.
    35. Bonaccolto-Töpfer, Marina & Castagnetti, Carolina & Prümer, Stephanie, 2022. "Understanding the public-private sector wage gap in Germany: New evidence from a Fixed Effects quantile Approach∗," Economic Modelling, Elsevier, vol. 116(C).
    36. Matthieu Crozet & Julian Hinz & Amrei Stammann & Joschka Wanner, 2021. "Worth the pain? Firms’ exporting behaviour to countries under sanctions," Post-Print hal-04150309, HAL.
    37. Abdulaziz Alsultan & Khaled Hussainey, 2024. "The Moderating Effect of Ownership Structure on the Relationship between Related Party Transactions and Earnings Quality: Evidence from Saudi Arabia," IJFS, MDPI, vol. 12(3), pages 1-25, June.
    38. Hatem Altaee, 2018. "Trade Openness and Economic Growth in the GCC Countries: A Panel Data Analysis Approach," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 11(3), pages 57-64, December.
    39. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    40. Iparraguirre José & Carena Bruno & Stratta Nicolás, 2023. "Trabajadores a tiempo completo en situación de pobreza en Argentina," Asociación Argentina de Economía Política: Working Papers 4661, Asociación Argentina de Economía Política.
    41. Camarero, Mariam & Moliner, Sergi & Tamarit, Cecilio, 2021. "Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging," Japan and the World Economy, Elsevier, vol. 57(C).
    42. 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.
    43. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.
    44. Liyuan Cui & Guanhao Feng & Yongmiao Hong, 2024. "Regularized Gmm For Time‐Varying Models With Applications To Asset Pricing," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(2), pages 851-883, May.
    45. Czarnowske, Daniel & Stammann, Amrei, 2022. "Latent unbalancedness in three-way gravity models," Economics Letters, Elsevier, vol. 220(C).
    46. Liu, Zhe & Zhu, Houle & Wilson, Jeffrey & Adams, Michelle & Walker, Tony R. & Xu, Yueying & Tang, Yu & Wang, Ziyu & Liu, Tongtong & Chen, Qinghua, 2024. "Achieving China's ‘double carbon goals’, an analysis of the potential and cost of carbon capture in the resource-based area: Northwestern China," Energy, Elsevier, vol. 292(C).

  21. Michael Lipsitz & Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val, 2017. "Quantreg.nonpar: an R package for performing nonparametric series quantile regression," CeMMAP working papers 29/17, Institute for Fiscal Studies.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Ivan Fernandez-Val, 2016. "Conditional quantile processes based on series or many regressors," CeMMAP working papers 46/16, Institute for Fiscal Studies.
    2. Bruneel-Zupanc, Christophe Alain, 2021. "Discrete-Continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation," TSE Working Papers 21-1185, Toulouse School of Economics (TSE).
    3. Clarke, Damian & Llorca-Jaña, Manuel & Pailañir, Daniel, 2021. "The Use of Quantile Methods in Economic History," IZA Discussion Papers 14659, Institute of Labor Economics (IZA).

  22. Mario Cruz-Gonzalez & Ivan Fernandez-Val & Martin Weidner, 2016. "probitfe and logitfe: Bias corrections for probit and logit models with two-way fixed effects," Papers 1610.07714, arXiv.org, revised Feb 2017.

    Cited by:

    1. Li, Xinyu & Wang, Huacheng & Li, Rong, 2023. "A hidden channel of “blood transfusion”: Internal capital market subsidies and zombie firms," The British Accounting Review, Elsevier, vol. 55(6).
    2. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.
    4. Dong, Siyuan & Wang, Na & Fan, Chengwei & Chen, Shi & Zhang, Lei, 2024. "E-commerce and rural women entrepreneurship ——Based on the quasi-natural experiment of “comprehensive demonstration policy” for E-commerce in rural areas," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 749-765.
    5. Réka Juhász & Claudia Steinwender, 2018. "Spinning the Web: The Impact of ICT on Trade in Intermediates and Technology Diffusion," NBER Working Papers 24590, National Bureau of Economic Research, Inc.
    6. David W. Hughes, 2021. "Estimating Nonlinear Network Data Models with Fixed Effects," Boston College Working Papers in Economics 1058, Boston College Department of Economics.
    7. Nakatani, Ryota, 2020. "Macroprudential Policy and the Probability of a Banking Crisis," MPRA Paper 101157, University Library of Munich, Germany.
    8. Carlos Pombo & Cristian Pinto-Gutierrez & Mauricio Jara-Betín, 2022. "Multiple large shareholder coalitions, institutional ownership and investment decisions: Evidence from cross-border deals in Latin America," Documentos CEDE 20333, Universidad de los Andes, Facultad de Economía, CEDE.
    9. Federici, Daniela & Parisi, Valentino & Ferrante, Francesco, 2020. "Heterogeneous firms, corporate taxes and export behavior: A firm-level investigation for Italy," Economic Modelling, Elsevier, vol. 88(C), pages 98-112.
    10. Julian Hinz & Amrei Stammann & Joschka Wanner, 2021. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," CEPA Discussion Papers 36, Center for Economic Policy Analysis.
    11. Thomas Hauner, 2020. "Aggregate wealth and its distribution as determinants of financial crises," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(3), pages 319-338, September.
    12. Ahmet Ihsan Kaya & Lutfi Erden & Ibrahim Ozkan, 2022. "Detecting capital flow surges in developing countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3510-3530, July.
    13. Jifeng Mu & Jonathan Z. Zhang, 2021. "Seller marketing capability, brand reputation, and consumer journeys on e-commerce platforms," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 994-1020, September.
    14. David Córcoles & Carmen Díaz-Mora & Rosario Gandoy & Ángela Triguero, 2023. "The role of servitization in international entrepreneurship: An analysis for Spanish manufacturing firms," Journal of International Entrepreneurship, Springer, vol. 21(2), pages 214-244, June.
    15. Troels Kristensen & Kim Rose-Olsen & Christian Volmar Skovsgaard, 2020. "Effects of Point-Of-Care Testing in General Practice for Type 2 Diabetes Patients on Ambulatory Visits and Hospitalizations," IJERPH, MDPI, vol. 17(17), pages 1-16, August.
    16. Juodis, Artūras & Karabiyik, Hande & Westerlund, Joakim, 2021. "On the robustness of the pooled CCE estimator," Journal of Econometrics, Elsevier, vol. 220(2), pages 325-348.
    17. Daniel Czarnowske & Amrei Stammann, 2019. "Fixed Effects Binary Choice Models: Estimation and Inference with Long Panels," Papers 1904.04217, arXiv.org, revised Oct 2020.
    18. Francesco Bartolucci & Claudia Pigini & Francesco Valentini, 2024. "MCMC conditional maximum likelihood for the two-way fixed-effects logit," Econometric Reviews, Taylor & Francis Journals, vol. 43(6), pages 379-404, July.
    19. Siranova, Maria & Tiruneh, Menbere Workie & Fisera, Boris, 2021. "Creating the illicit capital flows network in Europe – Do the net errors and omissions follow an economic pattern?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 955-973.
    20. Antonio C. David & Can Sever, 2024. "Electoral cycles in tax reforms," Empirical Economics, Springer, vol. 67(2), pages 495-529, August.
    21. K. Aleks Schaefer & Daniel P. Scheitrum & Steven van Winden, 2022. "Returns on investment to the British bovine tuberculosis control programme," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(2), pages 472-489, June.
    22. Neha Bhardwaj Upadhayay, 2020. "Uncovering the proliferation of contingent protection through channels of retaliation, gender and development assistance," Erudite Ph.D Dissertations, Erudite, number ph20-02 edited by Julie Lochard & Catherine Bros, April.
    23. Raf Van Gestel & Tobias Müller & Johan Bosmans, 2018. "Learning from failure in healthcare: Dynamic panel evidence of a physician shock effect," Health Economics, John Wiley & Sons, Ltd., vol. 27(9), pages 1340-1353, September.
    24. Valentina Raimondi & Margherita Scoppola, 2024. "Liberalising non‐tariff measures through regional trade agreements: The impact on multinational production," The World Economy, Wiley Blackwell, vol. 47(8), pages 3308-3338, August.
    25. Nicolae Stef, 2021. "Institutions and corporate financial distress in Central and Eastern Europe," European Journal of Law and Economics, Springer, vol. 52(1), pages 57-87, August.
    26. Cosima Obst, 2022. "Job Satisfaction and Training Investments," CEPA Discussion Papers 47, Center for Economic Policy Analysis.
    27. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    28. David Brady & Richard Carpiano & Michaela Curran, 2023. "A test of the predictive validity of relative versus absolute income for self-reported health and well-being in the United States," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(26), pages 775-808.
    29. Stojanovikj, Martin & Petrevski, Goran, 2019. "Adopting inflation targeting in emerging markets: exploring the factors behind the decision," MPRA Paper 115797, University Library of Munich, Germany, revised 18 Jun 2020.
    30. Elizabeth Blankespoor & Bradley E. Hendricks & Joseph Piotroski & Christina Synn, 2022. "Real-time revenue and firm disclosure," Review of Accounting Studies, Springer, vol. 27(3), pages 1079-1116, September.
    31. Zhonggang Yue & Chong Wang & Hui Hong, 2025. "Inclusive development of digital finance, family entrepreneurship and poverty reduction effect," International Entrepreneurship and Management Journal, Springer, vol. 21(1), pages 1-28, December.
    32. Marta F. Arroyabe & Martin Schumann, 2022. "On the Estimation of True State Dependence in the Persistence of Innovation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 850-893, August.
    33. Brady, David & Curran, Michaela & Carpiano, Richard M., 2023. "A test of the predictive validity of relative versus absolute income for self-reported health and well-being in the United States," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 48, pages 775-808.
    34. Jaworski, Taylor & Keay, Ian, 2022. "Globalization and the spread of industrialization in Canada, 1871–1891," Explorations in Economic History, Elsevier, vol. 86(C).
    35. Raf Van Gestel & Tobias Mueller & Johan Bosmans, 2018. "Learning from failure in healthcare: Dynamic panel evidence of a physician shock effect," Diskussionsschriften dp1809, Universitaet Bern, Departement Volkswirtschaft.
    36. Ryuki Kobayashi, 2023. "The effects of new technology on productivity: technological improvement and reallocation efficiency in the Japanese steelmaking industry," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-24, December.
    37. Alexander De Juan & Tim Wegenast, 2020. "Temperatures, food riots, and adaptation: A long-term historical analysis of England," Journal of Peace Research, Peace Research Institute Oslo, vol. 57(2), pages 265-280, March.
    38. Taylor Jaworski & Ian Keay, 2020. "Openness to Trade and the Spread of Industrialization: Evidence from Canada during the First Era of Globalization," NBER Working Papers 27716, National Bureau of Economic Research, Inc.
    39. Xiao, Han & Zheng, Xinye & Xie, Lunyu, 2022. "Promoting pro-poor growth through infrastructure investment: Evidence from the Targeted Poverty Alleviation program in China," China Economic Review, Elsevier, vol. 71(C).

  23. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.

    Cited by:

    1. Su, Miaomiao & Wang, Ruoyu & Wang, Qihua, 2022. "A two-stage optimal subsampling estimation for missing data problems with large-scale data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    2. Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
    3. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
    4. Shakeeb Khan & Xiaoying Lan & Elie Tamer & Qingsong Yao, 2021. "Estimating High Dimensional Monotone Index Models by Iterative Convex Optimization1," Papers 2110.04388, arXiv.org, revised Feb 2023.
    5. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Denis Fougère & Nicolas Jacquemet, 2019. "Causal Inference and Impact Evaluation," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 181-200.
    7. Rahul Singh, 2021. "Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension," Papers 2102.11076, arXiv.org, revised Jul 2024.
    8. Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," CEPR Discussion Papers 13430, C.E.P.R. Discussion Papers.
    9. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    10. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    11. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
    12. Berden, Carolien & Croes, R. & Kemp, R. & Mikkers, Misja & van der Noll, Rob & Shestalova, V. & Svitak, Jan, 2019. "Hospital Competition in the Netherlands : An Empirical Investigation," Other publications TiSEM e30db5a4-5c1c-450b-8f1d-6, Tilburg University, School of Economics and Management.
    13. Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
    14. Yusuke Narita & Kohei Yata, 2021. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Cowles Foundation Discussion Papers 2283, Cowles Foundation for Research in Economics, Yale University.
    15. Yamin Ahmad & Adam Check & Ming Chien Lo, 2024. "Unit Roots in Macroeconomic Time Series: A Comparison of Classical, Bayesian and Machine Learning Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2139-2173, June.
    16. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    17. Undral Byambadalai & Tatsushi Oka & Shota Yasui, 2024. "Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction," Papers 2407.16037, arXiv.org.
    18. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    19. Daisuke MIYAKAWA, 2019. "Shocks to Supply Chain Networks and Firm Dynamics: An Application of Double Machine Learning," Discussion papers 19100, Research Institute of Economy, Trade and Industry (RIETI).
    20. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2016. "Locally Robust Semiparametric Estimation," Papers 1608.00033, arXiv.org, revised Aug 2020.
    21. Daniel Brunstein & Georges Casamatta & Sauveur Giannoni, 2025. "Using machine learning to estimate the heterogeneous impact of Airbnb on house prices: Evidence from Corsica," Post-Print hal-04934630, HAL.
    22. Lihua Lei & Brad Ross, 2023. "Estimating Counterfactual Matrix Means with Short Panel Data," Papers 2312.07520, arXiv.org, revised May 2024.
    23. Yumou Qiu & Jing Tao & Xiao‐Hua Zhou, 2021. "Inference of heterogeneous treatment effects using observational data with high‐dimensional covariates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 1016-1043, November.
    24. Yue, Lili & Li, Gaorong & Lian, Heng & Wan, Xiang, 2019. "Regression adjustment for treatment effect with multicollinearity in high dimensions," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 17-35.
    25. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    26. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
    27. Mazzocchi, Mario & Capacci, Sara & Biondi, Beatrice, 2022. "Causal inference on the impact of nutrition policies using observational data," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 11(01), April.
    28. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Neng-Chieh Chang, 2018. "Semiparametric Difference-in-Differences with Potentially Many Control Variables," Papers 1812.10846, arXiv.org, revised Jan 2019.
    30. Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2018. "Inference in Linear Regression Models with Many Covariates and Heteroscedasticity," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1350-1361, July.
    31. Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2019. "Two-Step Estimation and Inference with Possibly Many Included Covariates," University of California at San Diego, Economics Working Paper Series qt86c7x315, Department of Economics, UC San Diego.
    32. Shi, Chengchun & Wan, Runzhe & Song, Ge & Luo, Shikai & Zhu, Hongtu & Song, Rui, 2023. "A multiagent reinforcement learning framework for off-policy evaluation in two-sided markets," LSE Research Online Documents on Economics 117174, London School of Economics and Political Science, LSE Library.
    33. Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
    34. Michael Pollmann, 2020. "Causal Inference for Spatial Treatments," Papers 2011.00373, arXiv.org, revised Jan 2023.
    35. Carvalho, Carlos & Masini, Ricardo & Medeiros, Marcelo C., 2018. "ArCo: An artificial counterfactual approach for high-dimensional panel time-series data," Journal of Econometrics, Elsevier, vol. 207(2), pages 352-380.
    36. Xiduo Chen & Xingdong Feng & Antonio F. Galvao & Yeheng Ge, 2025. "Treatment Effects Inference with High-Dimensional Instruments and Control Variables," Papers 2503.20149, arXiv.org.
    37. Neng-Chieh Chang, 2020. "The Mode Treatment Effect," Papers 2007.11606, arXiv.org.
    38. Marianne BLÉHAUT & Xavier D'HAULTFOEUILLE & Jérémy L'HOUR & Alexandre B. TSYBAKOV, 2020. "An alternative to synthetic control for models with many covariates under sparsity," Working Papers 2020-17, Center for Research in Economics and Statistics.
    39. Tymon Słoczyński & S. Derya Uysal & Jeffrey M. Wooldridge, 2025. "Abadie’s Kappa and Weighting Estimators of the Local Average Treatment Effect," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 43(1), pages 164-177, January.
    40. Knaus, Michael C. & Lechner, Michael & anthony.strittmatter@unisg.ch, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," Economics Working Paper Series 1817, University of St. Gallen, School of Economics and Political Science.
    41. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    42. Qizhao Chen & Vasilis Syrgkanis & Morgane Austern, 2022. "Debiased Machine Learning without Sample-Splitting for Stable Estimators," Papers 2206.01825, arXiv.org, revised Nov 2022.
    43. Zhengyuan Zhou & Susan Athey & Stefan Wager, 2018. "Offline Multi-Action Policy Learning: Generalization and Optimization," Papers 1810.04778, arXiv.org, revised Nov 2018.
    44. Ying-Ying Lee & Chu-An Liu, 2024. "Lee Bounds with a Continuous Treatment in Sample Selection," Papers 2411.04312, arXiv.org, revised Feb 2025.
    45. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    46. Hartley, Robert Paul & Lamarche, Carlos, 2017. "Behavioral Responses and Welfare Reform: Evidence from a Randomized Experiment," IZA Discussion Papers 10905, Institute of Labor Economics (IZA).
    47. Pedro H. C. Sant'Anna & Xiaojun Song, 2016. "Specification Tests for the Propensity Score," Papers 1611.06217, arXiv.org, revised Feb 2019.
    48. Tomasz Olma, 2021. "Nonparametric Estimation of Truncated Conditional Expectation Functions," Papers 2109.06150, arXiv.org.
    49. Entorf, Horst & Hou, Jia, 2018. "Financial Education for the Disadvantaged? A Review," IZA Discussion Papers 11515, Institute of Labor Economics (IZA).
    50. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    51. Jason Poulos & Shuxi Zeng, 2021. "RNN‐based counterfactual prediction, with an application to homestead policy and public schooling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1124-1139, August.
    52. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "Model Averaging and Double Machine Learning," Papers 2401.01645, arXiv.org, revised Sep 2024.
    53. Galbraith, John W. & Zinde-Walsh, Victoria, 2020. "Simple and reliable estimators of coefficients of interest in a model with high-dimensional confounding effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 609-632.
    54. Derya Uysal, 2023. "Abadie's kappa and weighting estimators of the local average treatment effect," Economics Virtual Symposium 2023 01, Stata Users Group.
    55. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2023. "Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 235(1), pages 166-179.
    56. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods," Papers 1803.09015, arXiv.org, revised Dec 2020.
    57. Kaido, Hiroaki & Wüthrich, Kaspar, 2021. "Decentralization estimators for instrumental variable quantile regression models," University of California at San Diego, Economics Working Paper Series qt362921wv, Department of Economics, UC San Diego.
    58. Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," PSE-Ecole d'économie de Paris (Postprint) hal-03098058, HAL.
    59. Luong, Hoa & Khedmati, Mehdi & Nguyen, Lan Anh & Nigmonov, Asror & Ovi, Nafisa Zabeen & Shams, Syed, 2023. "CEO-director ties and board gender diversity: US evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 40(C).
    60. Rahul Singh & Liyang Sun, 2024. "Double robustness for complier parameters and a semi-parametric test for complier characteristics," The Econometrics Journal, Royal Economic Society, vol. 27(1), pages 1-20.
    61. Herrera, Diego & Cunniff, Shannon & DuPont, Carolyn & Cohen, Benjamin & Gangi, Dakota & Kar, Devyani & Peyronnin Snider, Natalie & Rojas, Victor & Wyerman, Jim & Norriss, Jessie & Mountenot, Marshall, 2019. "Designing an environmental impact bond for wetland restoration in Louisiana," Ecosystem Services, Elsevier, vol. 35(C), pages 260-276.
    62. Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens, 2022. "ddml: Double/debiased machine learning in Stata," Swiss Stata Conference 2022 02, Stata Users Group.
    63. Hünermund Paul & Louw Beyers & Caspi Itamar, 2023. "Double machine learning and automated confounder selection: A cautionary tale," Journal of Causal Inference, De Gruyter, vol. 11(1), pages 1-12, January.
    64. Cerqua, Augusto & Letta, Marco, 2022. "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, vol. 92(C).
    65. Marica Valente, 2021. "Policy Evaluation of Waste Pricing Programs Using Heterogeneous Causal Effect Estimation," Discussion Papers of DIW Berlin 1980, DIW Berlin, German Institute for Economic Research.
    66. Barbara Felderer & Jannis Kueck & Martin Spindler, 2021. "Big Data meets Causal Survey Research: Understanding Nonresponse in the Recruitment of a Mixed-mode Online Panel," Papers 2102.08994, arXiv.org.
    67. Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2114, Department of Economics, University of Missouri.
    68. Biewen, Martin & Fitzenberger, Bernd & Seckler, Matthias, 2020. "Counterfactual quantile decompositions with selection correction taking into account Huber/Melly (2015): An application to the German gender wage gap," Labour Economics, Elsevier, vol. 67(C).
    69. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016. "Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk," Papers 1607.00286, arXiv.org, revised Oct 2019.
    70. Zhihao Zhao & Xinyu Zhang & Guohua Zou & Alan T. K. Wan & Geoffrey K. F. Tso, 2024. "Model averaging for estimating treatment effects," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(1), pages 73-92, February.
    71. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org, revised Nov 2024.
    72. Ana Fernandes & Martin Huber & Giannina Vaccaro, 2021. "Gender differences in wage expectations," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-24, June.
    73. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    74. Le-Yu Chen & Yu-Min Yen, 2021. "Estimations of the Local Conditional Tail Average Treatment Effect," Papers 2109.08793, arXiv.org, revised May 2024.
    75. Vira Semenova, 2023. "Debiased Machine Learning of Aggregated Intersection Bounds and Other Causal Parameters," Papers 2303.00982, arXiv.org, revised May 2025.
    76. Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
    77. Nathan Kallus & Miruna Oprescu, 2022. "Robust and Agnostic Learning of Conditional Distributional Treatment Effects," Papers 2205.11486, arXiv.org, revised Feb 2023.
    78. Narita, Yusuke & Yata, Kohei, 2022. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," CEI Working Paper Series 2021-05, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
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    80. T. Tony Cai & Zijian Guo & Yin Xia, 2023. "Statistical inference and large-scale multiple testing for high-dimensional regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(4), pages 1135-1171, December.
    81. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    82. Ravi B. Sojitra & Vasilis Syrgkanis, 2024. "Dynamic Local Average Treatment Effects," Papers 2405.01463, arXiv.org, revised May 2025.
    83. Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.
    84. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2017. "Weighted-average least squares estimation of generalized linear models," EIEF Working Papers Series 1711, Einaudi Institute for Economics and Finance (EIEF), revised Aug 2017.
    85. Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
    86. Michael Lechner & Jana Mareckova, 2024. "Comprehensive Causal Machine Learning," Papers 2405.10198, arXiv.org, revised Feb 2025.
    87. Jason Poulos & Andrea Albanese & Andrea Mercatanti & Fan Li, 2021. "Retrospective causal inference via matrix completion, with an evaluation of the effect of European integration on cross-border employment," Papers 2106.00788, arXiv.org.
    88. Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.
    89. Knaus, Michael C., 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Economics Working Paper Series 2004, University of St. Gallen, School of Economics and Political Science.
    90. Chen, Juan & Ma, Feng & Qiu, Xuemei & Li, Tao, 2023. "The role of categorical EPU indices in predicting stock-market returns," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 365-378.
    91. Qiu, Chen & Otsu, Taisuke, 2022. "Information theoretic approach to high dimensional multiplicative models: stochastic discount factor and treatment effect," LSE Research Online Documents on Economics 110494, London School of Economics and Political Science, LSE Library.
    92. Haitian Xie, 2020. "Efficient and Robust Estimation of the Generalized LATE Model," Papers 2001.06746, arXiv.org, revised Feb 2022.
    93. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    94. Karun Adusumilli & Friedrich Geiecke & Claudio Schilter, 2019. "Dynamically Optimal Treatment Allocation," Papers 1904.01047, arXiv.org, revised Nov 2024.
    95. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2024. "Reprint: Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 239(2).
    96. Johann Pfitzinger, 2021. "An Interpretable Neural Network for Parameter Inference," Papers 2106.05536, arXiv.org.
    97. Alejandro Sanchez-Becerra, 2023. "Robust inference for the treatment effect variance in experiments using machine learning," Papers 2306.03363, arXiv.org.
    98. Su, Miaomiao & Wang, Qihua, 2022. "A convex programming solution based debiased estimator for quantile with missing response and high-dimensional covariables," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    99. Chen Qiu & Taisuke Otsu, 2022. "Information theoretic approach to high‐dimensional multiplicative models: Stochastic discount factor and treatment effect," Quantitative Economics, Econometric Society, vol. 13(1), pages 63-94, January.
    100. Viviano, Davide & Bradic, Jelena, 2023. "Synthetic Learner: Model-free inference on treatments over time," Journal of Econometrics, Elsevier, vol. 234(2), pages 691-713.
    101. Ellington, Michael & Stamatogiannis, Michalis P. & Zheng, Yawen, 2022. "A study of cross-industry return predictability in the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    102. Joey Blumberg & Gary Thompson, 2022. "Nonparametric segmentation methods: Applications of unsupervised machine learning and revealed preference," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(3), pages 976-998, May.
    103. Narita, Yusuke & Yata, Kohei, 2022. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Discussion Paper Series 730, Institute of Economic Research, Hitotsubashi University.
    104. Zeyu Diao & Lili Yue & Fanrong Zhao & Gaorong Li, 2022. "High-Dimensional Regression Adjustment Estimation for Average Treatment Effect with Highly Correlated Covariates," Mathematics, MDPI, vol. 10(24), pages 1-18, December.
    105. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
    106. Zhengyu Zhang & Zequn Jin & Lihua Lin, 2024. "Identification and inference of outcome conditioned partial effects of general interventions," Papers 2407.16950, arXiv.org.
    107. Ai, Chunrong & Linton, Oliver & Zhang, Zheng, 2022. "Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models," Journal of Econometrics, Elsevier, vol. 228(1), pages 39-61.
    108. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly, 2022. "Fast algorithms for the quantile regression process," Empirical Economics, Springer, vol. 62(1), pages 7-33, January.
    109. Knaus, Michael C., 2018. "A Double Machine Learning Approach to Estimate the Effects of Musical Practice on Student's Skills," IZA Discussion Papers 11547, Institute of Labor Economics (IZA).
    110. Lucchetti, Riccardo & Pedini, Luca & Pigini, Claudia, 2022. "No such thing as the perfect match: Bayesian Model Averaging for treatment evaluation," Economic Modelling, Elsevier, vol. 107(C).
    111. Zemin Zheng & Jinchi Lv & Wei Lin, 2021. "Nonsparse Learning with Latent Variables," Operations Research, INFORMS, vol. 69(1), pages 346-359, January.
    112. Farbmacher, Helmut & Huber, Martin & Langen, Henrika & Spindler, Martin, 2020. "Causal mediation analysis with double machine learning," FSES Working Papers 515, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    113. Michael Lechner & Jana Mareckova, 2022. "Modified Causal Forest," Papers 2209.03744, arXiv.org.
    114. Zequn Jin & Lihua Lin & Zhengyu Zhang, 2022. "Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives," Papers 2211.07903, arXiv.org.
    115. Marina Bonaccolto-Töpfer & Giovanni Bonaccolto, 2023. "Gender wage inequality: new evidence from penalized expectile regression," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 21(3), pages 511-535, September.
    116. Whitney K. Newey & Sami Stouli, 2018. "Control variables, discrete instruments, and identification of structural functions," CeMMAP working papers CWP55/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    117. Vira Semenova, 2020. "Generalized Lee Bounds," Papers 2008.12720, arXiv.org, revised May 2025.
    118. David Cheng & Abhishek Chakrabortty & Ashwin N. Ananthakrishnan & Tianxi Cai, 2020. "Estimating average treatment effects with a double‐index propensity score," Biometrics, The International Biometric Society, vol. 76(3), pages 767-777, September.
    119. Nan Liu & Yanbo Liu & Yuya Sasaki, 2024. "Estimation and Inference for Causal Functions with Multiway Clustered Data," Papers 2409.06654, arXiv.org.
    120. Olivier Deschenes & Christopher Malloy & Gavin G. McDonald, 2023. "Causal Effects of Renewable Portfolio Standards on Renewable Investments and Generation: The Role of Heterogeneity and Dynamics," NBER Working Papers 31568, National Bureau of Economic Research, Inc.
    121. Nathan Kallus, 2022. "Treatment Effect Risk: Bounds and Inference," Papers 2201.05893, arXiv.org, revised Jul 2022.
    122. Agboola, Oluwagbenga David & Yu, Han, 2023. "Neighborhood-based cross fitting approach to treatment effects with high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 186(C).
    123. Dominick Bartelme & Andrei Levchenko & Ting Lan, 2019. "Specialization, Market Access and Medium-Term Growth," 2019 Meeting Papers 999, Society for Economic Dynamics.
    124. Guo, Lin & Zhang, Ben, 2019. "Mining structural influence to analyze relationships in social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 301-309.
    125. Philipp Bach & Victor Chernozhukov & Malte S. Kurz & Martin Spindler & Sven Klaassen, 2021. "DoubleML -- An Object-Oriented Implementation of Double Machine Learning in R," Papers 2103.09603, arXiv.org, revised Jun 2024.
    126. Li, Li & Shi, Pengfei & Fan, Qingliang & Zhong, Wei, 2024. "Causal effect estimation with censored outcome and covariate selection," Statistics & Probability Letters, Elsevier, vol. 204(C).
    127. Yuehao Bai & Jizhou Liu & Azeem M. Shaikh & Max Tabord-Meehan, 2023. "On the Efficiency of Finely Stratified Experiments," Papers 2307.15181, arXiv.org, revised Mar 2025.
    128. Rodney V. Fonseca & Aluísio Pinheiro, 2020. "Wavelet estimation of the dimensionality of curve time series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(5), pages 1175-1204, October.
    129. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
    130. Yuehao Bai & Liang Jiang & Joseph P. Romano & Azeem M. Shaikh & Yichong Zhang, 2023. "Covariate Adjustment in Experiments with Matched Pairs," Papers 2302.04380, arXiv.org, revised Oct 2023.
    131. Fan, Jianqing & Gong, Wenyan & Zhu, Ziwei, 2019. "Generalized high-dimensional trace regression via nuclear norm regularization," Journal of Econometrics, Elsevier, vol. 212(1), pages 177-202.
    132. Rao, Sandeep & Koirala, Santosh & Thapa, Chandra & Neupane, Suman, 2022. "When rain matters! Investments and value relevance," Journal of Corporate Finance, Elsevier, vol. 73(C).
    133. Victor Quintas-Martinez & Mohammad Taha Bahadori & Eduardo Santiago & Jeff Mu & Dominik Janzing & David Heckerman, 2024. "Multiply-Robust Causal Change Attribution," Papers 2404.08839, arXiv.org, revised Sep 2024.
    134. Yang Ning & Sida Peng & Jing Tao, 2020. "Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data," Papers 2009.03151, arXiv.org.
    135. Adel Javanmard & Jason D. Lee, 2020. "A flexible framework for hypothesis testing in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 685-718, July.
    136. Cerqua, Augusto & Letta, Marco, 2020. "Local economies amidst the COVID-19 crisis in Italy: a tale of diverging trajectories," MPRA Paper 104404, University Library of Munich, Germany.
    137. Geonwoo Kim & Suyong Song, 2024. "Double/Debiased CoCoLASSO of Treatment Effects with Mismeasured High-Dimensional Control Variables," Papers 2408.14671, arXiv.org.
    138. McNamara, Sarah, 2020. "Returns to higher education and dropouts: A double machine learning approach," ZEW Discussion Papers 20-084, ZEW - Leibniz Centre for European Economic Research.
    139. Ke Sun & Linglong Kong & Hongtu Zhu & Chengchun Shi, 2024. "ARMA-Design: Optimal Treatment Allocation Strategies for A/B Testing in Partially Observable Time Series Experiments," Papers 2408.05342, arXiv.org, revised Jan 2025.
    140. Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org, revised Apr 2024.
    141. Sandro Heiniger, 2024. "Data-driven model selection within the matrix completion method for causal panel data models," Papers 2402.01069, arXiv.org.
    142. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    143. Martin Wiegand, 2019. "Do early-ending conditional cash transfer programs crowd out school enrollment?," Tinbergen Institute Discussion Papers 19-053/V, Tinbergen Institute.
    144. Nathan Kallus, 2023. "Treatment Effect Risk: Bounds and Inference," Management Science, INFORMS, vol. 69(8), pages 4579-4590, August.
    145. Lucas Zhang, 2024. "Continuous difference-in-differences with double/debiased machine learning," Papers 2408.10509, arXiv.org, revised Mar 2025.
    146. Shinya Sugawara, 2022. "What composes desirable formal at-home elder care? An analysis for multiple service combinations," The Japanese Economic Review, Springer, vol. 73(2), pages 373-402, April.
    147. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Apr 2024.
    148. Zemin Zheng & Jie Zhang & Yang Li, 2022. "L 0 -Regularized Learning for High-Dimensional Additive Hazards Regression," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2762-2775, September.
    149. Khashayar Khosravi & Greg Lewis & Vasilis Syrgkanis, 2019. "Non-Parametric Inference Adaptive to Intrinsic Dimension," Papers 1901.03719, arXiv.org, revised Jun 2019.
    150. Jan Rabenseifner & Sven Klaassen & Jannis Kueck & Philipp Bach, 2025. "Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score Based Estimators," Papers 2503.17290, arXiv.org, revised Apr 2025.
    151. JoonHwan Cho & Thomas M. Russell, 2018. "Simple Inference on Functionals of Set-Identified Parameters Defined by Linear Moments," Papers 1810.03180, arXiv.org, revised May 2023.
    152. Xu, Wenfu & Tan, Zhiqiang, 2024. "High-dimensional model-assisted inference for treatment effects with multi-valued treatments," Journal of Econometrics, Elsevier, vol. 244(1).
    153. Sven Klaassen & Jannis Kueck & Martin Spindler, 2017. "Transformation Models in High-Dimensions," Papers 1712.07364, arXiv.org.

  24. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Ivan Fernandez-Val, 2016. "Conditional quantile processes based on series or many regressors," CeMMAP working papers 46/16, Institute for Fiscal Studies.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2014. "Valid post-selection inference in high-dimensional approximately sparse quantile regression models," CeMMAP working papers 53/14, Institute for Fiscal Studies.
    2. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2019. "On binscatter," Staff Reports 881, Federal Reserve Bank of New York.
    3. Zheng Fang & Andres Santos & Azeem Shaikh & Alexander Torgovitsky, 2020. "Inference for Large-Scale Linear Systems with Known Coefficients," Working Papers 2020-134, Becker Friedman Institute for Research In Economics.
    4. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "On the asymptotic theory for least squares series: pointwise and uniform results," CeMMAP working papers 73/13, Institute for Fiscal Studies.
    5. Petre Caraiani & Onur Polat & Rangan Gupta & Elie Bouri, 2025. "Climate Risks and Predictability of Financial Risks in the US Banking Sector," Working Papers 202507, University of Pretoria, Department of Economics.
    6. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers 40/15, Institute for Fiscal Studies.
    7. Shujie Ma & Oliver Linton & Jiti Gao, 2017. "Estimation and inference in semiparametric quantile factor models," Monash Econometrics and Business Statistics Working Papers 8/17, Monash University, Department of Econometrics and Business Statistics.
    8. Dimitrios Panagiotou, 2021. "Re-examining the leverage effect and gold’s safe haven properties with the utilization of the implied volatility of gold: a non-parametric quantile regression approach," SN Business & Economics, Springer, vol. 1(7), pages 1-18, July.
    9. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    10. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012. "Gaussian approximation of suprema of empirical processes," CeMMAP working papers CWP44/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Chernozhukov, Victor & Fernández-Val, Iván & Melly, Blaise & Wüthrich, Kaspar, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," University of California at San Diego, Economics Working Paper Series qt5zm6m9rq, Department of Economics, UC San Diego.
    12. Rangan Gupta & Syed Jawad Hussain Shahzad & Xin Sheng & Sowmya Subramaniam, 2020. "The Role of Oil and Risk Shocks in the High-Frequency Movements of the Term Structure of Interest Rates of the United States," Working Papers 202063, University of Pretoria, Department of Economics.
    13. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
    14. 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.
    15. Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Zhongjun Qu & Jungmo Yoon, 2011. "Nonparametric Estimation and Inference on Conditional Quantile Processes," Boston University - Department of Economics - Working Papers Series WP2011-059, Boston University - Department of Economics.
    17. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Ivan Fernandez-Val, 2016. "Conditional quantile processes based on series or many regressors," CeMMAP working papers 46/16, Institute for Fiscal Studies.
    18. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2024. "Bootstrap Inference for Panel Data Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 628-639, April.
    19. Torossian, Léonard & Picheny, Victor & Faivre, Robert & Garivier, Aurélien, 2020. "A review on quantile regression for stochastic computer experiments," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    20. Zheng Fang & Juwon Seo, 2021. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Econometrica, Econometric Society, vol. 89(5), pages 2439-2458, September.
    21. Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    22. Arellano, Manuel & Blundell, Richard & Bonhomme, Stephane, 2015. "Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework," IZA Discussion Papers 9344, Institute of Labor Economics (IZA).
    23. Matias D. Cattaneo & Yingjie Feng & Rocio Titiunik, 2019. "Prediction Intervals for Synthetic Control Methods," Papers 1912.07120, arXiv.org, revised Sep 2021.
    24. Victor Chernozhukov & Vira Semenova, 2018. "Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions," CeMMAP working papers CWP40/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. Qihui Chen, 2022. "Robust Estimation of Conditional Factor Models," Papers 2204.00801, arXiv.org, revised Apr 2022.
    26. Charlier, Isabelle & Paindaveine, Davy & Saracco, Jérôme, 2015. "Conditional quantile estimation based on optimal quantization: From theory to practice," Computational Statistics & Data Analysis, Elsevier, vol. 91(C), pages 20-39.
    27. Richard H. Spady & Sami Stouli, 2016. "Dual Regression," Bristol Economics Discussion Papers 16/669, School of Economics, University of Bristol, UK.
    28. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Kato, Kengo, 2015. "Some new asymptotic theory for least squares series: Pointwise and uniform results," Journal of Econometrics, Elsevier, vol. 186(2), pages 345-366.
    29. Chronopoulos, Ilias & Raftapostolos, Aristeidis & Kapetanios, George, 2023. "Forecasting Value-at-Risk using deep neural network quantile regression," Essex Finance Centre Working Papers 34837, University of Essex, Essex Business School.
    30. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney K. Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers 66/13, Institute for Fiscal Studies.
    31. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2019. "Best linear approximations to set identified functions: with an application to the gender wage gap," CeMMAP working papers 09/19, Institute for Fiscal Studies.
    32. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Robust inference in high-dimensional approximately sparse quantile regression models," CeMMAP working papers CWP70/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    33. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Christian Pierdzioch, 2021. "El Nino, La Nina, and the Forecastability of the Realized Variance of Heating Oil Price Movements," Working Papers 202138, University of Pretoria, Department of Economics.
    34. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, vol. 166(1), pages 127-137.
    35. Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers CWP51/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016. "Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk," Papers 1607.00286, arXiv.org, revised Oct 2019.
    37. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Uniform Post Selection Inference for LAD Regression and Other Z-estimation problems," Papers 1304.0282, arXiv.org, revised Oct 2020.
    38. Alexandre Belloni & Victor Chernozhukov, 2009. "L1-Penalized quantile regression in high-dimensional sparse models," CeMMAP working papers CWP10/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    39. Xi Chen & Victor Chernozhukov & Iv'an Fern'andez-Val & Scott Kostyshak & Ye Luo, 2018. "Shape-Enforcing Operators for Point and Interval Estimators," Papers 1809.01038, arXiv.org, revised Feb 2021.
    40. Rangan Gupta & Syed Jawad Hussain Shahzad & Xin Sheng & Sowmya Subramaniam, 2023. "The role of oil and risk shocks in the high‐frequency movements of the term structure of interest rates: Evidence from the U.S. Treasury market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1845-1857, April.
    41. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Uniform post selection inference for LAD regression models," CeMMAP working papers 24/13, Institute for Fiscal Studies.
    42. Feng, Xingdong & Liu, Qiaochu & Wang, Caixing, 2023. "A lack-of-fit test for quantile regression process models," Statistics & Probability Letters, Elsevier, vol. 192(C).
    43. Massimiliano Caporin & Petre Caraiani & Oguzhan Cepni & Rangan Gupta, 2024. "Predicting the Conditional Distribution of US Stock Market Systemic Stress: The Role of Climate Risks," Working Papers 202407, University of Pretoria, Department of Economics.
    44. Cattaneo, Matias D. & Jansson, Michael & Ma, Xinwei, 2024. "Local regression distribution estimators," Journal of Econometrics, Elsevier, vol. 240(2).
    45. Anqi Li & Shiko Maruyama, 2024. "Who suffered most in the pandemic? A distribution regression analysis of happiness in Japan," The Japanese Economic Review, Springer, vol. 75(4), pages 637-690, December.
    46. Ferreira,Francisco H. G. & Firpo,Sergio & Galvao,Antonio F., 2017. "Estimation and inference for actual and counterfactual growth incidence curves," Policy Research Working Paper Series 7933, The World Bank.
    47. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    48. Giovanni Bonaccolto & Massimiliano Caporin & Rangan Gupta, 2015. "The Dynamic Impact of Uncertainty in Causing and Forecasting the Distribution of Oil Returns and Risk," Working Papers 201564, University of Pretoria, Department of Economics.
    49. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2012. "Inference for best linear approximations to set identified functions," CeMMAP working papers 43/12, Institute for Fiscal Studies.
    50. Zheng Fang, 2021. "A Unifying Framework for Testing Shape Restrictions," Papers 2107.12494, arXiv.org, revised Aug 2021.
    51. Elie Bouri & Rangan Gupta & Clement Kweku Kyei & Sowmya Subramaniam, 2020. "High-Frequency Movements of the Term Structure of Interest Rates of the United States: The Role of Oil Market Uncertainty," Working Papers 202085, University of Pretoria, Department of Economics.
    52. Hao, Meiling & Lin, Yuanyuan & Shen, Guohao & Su, Wen, 2023. "Nonparametric inference on smoothed quantile regression process," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    53. Vira Semenova, 2020. "Generalized Lee Bounds," Papers 2008.12720, arXiv.org, revised May 2025.
    54. Tengyuan Liang, 2022. "Universal prediction band via semi‐definite programming," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1558-1580, September.
    55. Matias D. Cattaneo & Ricardo P. Masini & William G. Underwood, 2022. "Yurinskii's Coupling for Martingales," Papers 2210.00362, arXiv.org, revised Sep 2024.
    56. Karen X. Yan & Qi Li, 2018. "Nonparametric Estimation of a Conditional Quantile Function in a Fixed Effects Panel Data Model," JRFM, MDPI, vol. 11(3), pages 1-10, August.
    57. Shujie Ma & Oliver Linton & Jiti Gao, 2018. "Estimation in semiparametric quantile factor models," CeMMAP working papers CWP07/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    58. Mehmet Balcilar & Seyi Saint Akadiri & Rangan Gupta & Stephen M. Miller, 2017. "Partisan Conflict and Income Distribution in the United States: A Nonparametric Causality-in-Quantiles Approach," Working papers 2017-11, University of Connecticut, Department of Economics.
    59. Rangan Gupta & Damien Moodley, 2023. "Housing Search Activity and Quantiles-Based Predictability of Housing Price Movements in the United States," Working Papers 202335, University of Pretoria, Department of Economics.
    60. Mehmet Balcilar & Seyi Saint Akadiri & Rangan Gupta & Stephen M. Miller, 2019. "Partisan Conflict and Income Inequality in the United States: A Nonparametric Causality-in-Quantiles Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(1), pages 65-82, February.
    61. Gimenes, Nathalie & Guerre, Emmanuel, 2022. "Quantile regression methods for first-price auctions," Journal of Econometrics, Elsevier, vol. 226(2), pages 224-247.
    62. Lin, Fangzheng & Tang, Yanlin & Zhu, Zhongyi, 2020. "Weighted quantile regression in varying-coefficient model with longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
    63. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    64. Chen, Xirong & Li, Degui & Li, Qi & Li, Zheng, 2019. "Nonparametric estimation of conditional quantile functions in the presence of irrelevant covariates," Journal of Econometrics, Elsevier, vol. 212(2), pages 433-450.
    65. Holly Brannelly & Andrea Macrina & Gareth W. Peters, 2021. "Stochastic measure distortions induced by quantile processes for risk quantification and valuation," Papers 2201.02045, arXiv.org.
    66. 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.
    67. Erik Figueiredo & Luiz Lima & Georg Schaur, 2016. "The effect of the Euro on the bilateral trade distribution," Empirical Economics, Springer, vol. 50(1), pages 17-29, February.

  25. Victor Chernozhukov & Ivan Fernandez-Val & Ye Luo, 2015. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Papers 1512.05635, arXiv.org, revised May 2018.

    Cited by:

    1. Laub, Natalie & Boockmann, Bernhard & Kroczek, Martin, 2023. "Tightening Access to Early Retirement: Who Can Adapt?," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277625, Verein für Socialpolitik / German Economic Association.
    2. Daniel Goller, 2020. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Papers 2008.07165, arXiv.org.
    3. Matthew A. Masten & Alexandre Poirier & Muyang Ren, 2025. "A General Approach to Relaxing Unconfoundedness," Papers 2501.15400, arXiv.org.
    4. Strittmatter, Anthony & Wunsch, Conny, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," IZA Discussion Papers 14128, Institute of Labor Economics (IZA).
    5. Strittmatter, Anthony, 2019. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," GLO Discussion Paper Series 336, Global Labor Organization (GLO).
    6. Nora Bearth & Michael Lechner, 2024. "Causal Machine Learning for Moderation Effects," Papers 2401.08290, arXiv.org, revised Jan 2025.
    7. Florent Dubois & Christophe Muller, 2022. "Residential segregation matters to racial income gaps," Working Papers hal-03622711, HAL.
    8. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    9. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iv'an Fern'andez-Val, 2017. "Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Papers 1712.04802, arXiv.org, revised Oct 2023.
    10. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods," Papers 1803.09015, arXiv.org, revised Dec 2020.
    12. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers 33/17, Institute for Fiscal Studies.
    14. Cockx, Bart & Lechner, Michael & Bollens, Joost, 2023. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Labour Economics, Elsevier, vol. 80(C).
    15. Florent Dubois & Christophe Muller, 2020. "The Contribution of Residential Segregation to Racial Income Gaps: Evidence from South Africa," EconomiX Working Papers 2020-20, University of Paris Nanterre, EconomiX.
    16. Pullabhotla, Hemant K. & Souza, Mateus, 2022. "Air pollution from agricultural fires increases hypertension risk," Journal of Environmental Economics and Management, Elsevier, vol. 115(C).
    17. Bilancini, Ennio & Boncinelli, Leonardo & Di Paolo, Roberto & Menicagli, Dario & Pizziol, Veronica & Ricciardi, Emiliano & Serti, Francesco, 2022. "Prosocial behavior in emergencies: Evidence from blood donors recruitment and retention during the COVID-19 pandemic," Social Science & Medicine, Elsevier, vol. 314(C).
    18. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    19. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.
    20. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
    21. Diego Marino Fages, 2023. "Migration and trust: Evidence on assimilation from internal migrants," Discussion Papers 2023-08, Nottingham Interdisciplinary Centre for Economic and Political Research (NICEP).
    22. Victor Chernozhukov & Iván Fernández‐Val & Ye Luo, 2018. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Econometrica, Econometric Society, vol. 86(6), pages 1911-1938, November.
    23. Andrew Baker & Brantly Callaway & Scott Cunningham & Andrew Goodman-Bacon & Pedro H. C. Sant'Anna, 2025. "Difference-in-Differences Designs: A Practitioner's Guide," Papers 2503.13323, arXiv.org.
    24. Sallin, Aurelién, 2021. "Estimating returns to special education: combining machine learning and text analysis to address confounding," Economics Working Paper Series 2109, University of St. Gallen, School of Economics and Political Science.
    25. Kroczek, Martin & Kugler, Philipp, 2022. "Heterogeneous Effects of Monetary and Non-Monetary Job Characteristics on Job Attractiveness in Nursing," VfS Annual Conference 2022 (Basel): Big Data in Economics 264108, Verein für Socialpolitik / German Economic Association.
    26. Ricardo Masini & Marcelo Medeiros, 2025. "Balancing Flexibility and Interpretability: A Conditional Linear Model Estimation via Random Forest," Papers 2502.13438, arXiv.org.
    27. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    28. Michael Zimmert & Michael Lechner, 2019. "Nonparametric estimation of causal heterogeneity under high-dimensional confounding," Papers 1908.08779, arXiv.org.
    29. Florent Dubois & Christophe Muller, 2020. "The Contribution of Residential Segregation to Racial Income Gaps: Evidence from South Africa," AMSE Working Papers 2029, Aix-Marseille School of Economics, France.
    30. Daniel Jacob, 2019. "Group Average Treatment Effects for Observational Studies," Papers 1911.02688, arXiv.org, revised Mar 2020.
    31. Knaus, Michael C., 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Economics Working Paper Series 2004, University of St. Gallen, School of Economics and Political Science.
    32. Bin Xiong & Qi Sui, 2025. "The effect of digital economy on rural workforce occupation transformation ability: Evidence from China," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-15, December.
    33. Bernhard Boockmann & Martin Kroczek & Natalie Laub, 2023. "Tightening access to early retirement: who can adapt?," IAW Discussion Papers 142, Institut für Angewandte Wirtschaftsforschung (IAW).
    34. Kroczek, Martin & Kugler, Philipp, 2024. "Heterogeneous effects of monetary and non-monetary job characteristics on job attractiveness in nursing," Labour Economics, Elsevier, vol. 91(C).
    35. Zheng Fang, 2021. "A Unifying Framework for Testing Shape Restrictions," Papers 2107.12494, arXiv.org, revised Aug 2021.
    36. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," CESifo Working Paper Series 9037, CESifo.
    37. Chi Zhang & Xiangdan Piao & Shunsuke Managi, 2023. "Work Hour Mismatch on Life Evaluation: Full Heterogeneity and Individual- and Country-Level Characteristics of the Most and Least Affected Workers," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 170(2), pages 637-674, November.
    38. Posel, Dorrit & Oyenubi, Adeola, 2023. "Heterogeneous gender gaps in mental wellbeing: Do women with low economic status face the biggest gender gaps?," Social Science & Medicine, Elsevier, vol. 332(C).
    39. Olivier Deschenes & Christopher Malloy & Gavin G. McDonald, 2023. "Causal Effects of Renewable Portfolio Standards on Renewable Investments and Generation: The Role of Heterogeneity and Dynamics," NBER Working Papers 31568, National Bureau of Economic Research, Inc.
    40. Florent Dubois & Christophe Muller, 2022. "Residential segregation matters to racial income gaps: Evidence from South Africa," AMSE Working Papers 2205, Aix-Marseille School of Economics, France.
    41. Aur'elien Sallin, 2021. "Estimating returns to special education: combining machine learning and text analysis to address confounding," Papers 2110.08807, arXiv.org, revised Feb 2022.
    42. Martin Kroczek & Philipp Kugler, 2022. "Heterogeneous Effects of Monetary and Non-Monetary Job Characteristics on Job Attractiveness in Nursing," IAW Discussion Papers 139, Institut für Angewandte Wirtschaftsforschung (IAW).
    43. Yuri Fonseca & Marcelo Medeiros & Gabriel Vasconcelos & Alvaro Veiga, 2018. "BooST: Boosting Smooth Trees for Partial Effect Estimation in Nonlinear Regressions," Papers 1808.03698, arXiv.org, revised Jul 2020.
    44. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Causal Machine-Learning Approach," Papers 2103.10251, arXiv.org, revised Sep 2021.
    45. Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," Papers 2206.07845, arXiv.org.
    46. Lopez Garcia, Italo & Luoto, Jill E. & Aboud, Frances E. & Fernald, Lia C.H., 2023. "Group Meetings and Boosters to Sustain Early Impacts on Child Development: Experimental Evidence from Kenya," IZA Discussion Papers 16392, Institute of Labor Economics (IZA).
    47. Kai Feng & Han Hong, 2024. "Statistical Inference of Optimal Allocations I: Regularities and their Implications," Papers 2403.18248, arXiv.org, revised Apr 2024.
    48. Sookyo Jeong & Hongseok Namkoong, 2020. "Assessing External Validity Over Worst-case Subpopulations," Papers 2007.02411, arXiv.org, revised Feb 2022.

  26. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.

    Cited by:

    1. Wang, Peng & Wang, Xi, 2025. "Adjusted principal component estimation for binary factor model," MPRA Paper 123844, University Library of Munich, Germany.
    2. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    3. Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-rank approximations of nonseparable panel models," CeMMAP working papers CWP52/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    5. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2017. "Discretizing unobserved heterogeneity," IFS Working Papers W17/03, Institute for Fiscal Studies.
    6. David W. Hughes, 2021. "Estimating Nonlinear Network Data Models with Fixed Effects," Boston College Working Papers in Economics 1058, Boston College Department of Economics.
    7. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    8. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2022. "SONIC: SOcial Network analysis with Influencers and Communities," Journal of Econometrics, Elsevier, vol. 228(2), pages 177-220.
    9. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.
    10. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    11. Martin Weidner & Thomas Zylkin, 2021. "Bias and consistency in three-way gravity models," CeMMAP working papers CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org.
    13. Pigini, Claudia & Pionati, Alessandro & Valentini, Francesco, 2023. "Specification testing with grouped fixed effects," MPRA Paper 117821, University Library of Munich, Germany.
    14. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased Inference for Dynamic Nonlinear Panels with Multi-dimensional Heterogeneities," Papers 2305.03134, arXiv.org, revised Nov 2024.
    15. Hacioglu Hoke, Sinem & Kapetanios, George, 2017. "Common correlated effect cross-sectional dependence corrections for non-linear conditional mean panel models," Bank of England working papers 683, Bank of England.
    16. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    17. Jie Wei & Yonghui Zhang, 2022. "Panel Probit Models with Time‐Varying Individual Effects: Reestimating the Effects of Fertility on Female Labour Participation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 799-829, August.
    18. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    19. Francesco Bartolucci & Claudia Pigini & Francesco Valentini, 2024. "MCMC conditional maximum likelihood for the two-way fixed-effects logit," Econometric Reviews, Taylor & Francis Journals, vol. 43(6), pages 379-404, July.
    20. Zhou, Jin & Heckman, James J. & Liu, Bei & Lu, Mai, 2022. "The Impacts of a Prototypical Home Visiting Program on Child Skills," IZA Discussion Papers 15132, Institute of Labor Economics (IZA).
    21. Lena Boneva (Körber) & Oliver Linton, 2017. "A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance," CeMMAP working papers 02/17, Institute for Fiscal Studies.
    22. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
    23. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    24. Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
    25. Jia Chen Author-Name-First: Jia & Yongcheol Shin & Chaowen Zheng, 2023. "Dynamic Quantile Panel Data Models with Interactive Effects," Economics Discussion Papers em-dp2023-06, Department of Economics, University of Reading.
    26. Junhui Cai & Dan Yang & Ran Chen & Wu Zhu & Haipeng Shen & Linda Zhao, 2021. "Network regression and supervised centrality estimation," Papers 2111.12921, arXiv.org, revised Feb 2025.
    27. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    28. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    29. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    30. Bartolucci, Francesco & Pigini, Claudia, 2019. "Partial effects estimation for fixed-effects logit panel data models," MPRA Paper 92243, University Library of Munich, Germany.
    31. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    32. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    33. Danilo Leiva‐León & Gabriel Perez Quiros & Eyno Rots, 2024. "Real‐time weakness of the global economy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 813-832, August.
    34. 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.
    35. Susan Athey & Guido Imbens, 2025. "Identification of Average Treatment Effects in Nonparametric Panel Models," Papers 2503.19873, arXiv.org.
    36. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.
    37. Chen, Liang & Dolado, Juan José & Gonzalo, Jesús & Ramos Ramirez, Andrey David, 2013. "Revisiting Granger Causality of CO2 on Global Warming: a Quantile Factor Approach," DES - Working Papers. Statistics and Econometrics. WS 35531, Universidad Carlos III de Madrid. Departamento de Estadística.
    38. Wenqin Du & Bailey K. Fosdick & Wen Zhou, 2025. "Regression Modeling of the Count Relational Data with Exchangeable Dependencies," Papers 2502.11255, arXiv.org.
    39. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.
    40. Ting Fung Ma & Fangfang Wang & Jun Zhu, 2023. "On generalized latent factor modeling and inference for high‐dimensional binomial data," Biometrics, The International Biometric Society, vol. 79(3), pages 2311-2320, September.
    41. Hugo Freeman, 2022. "Linear Multidimensional Regression with Interactive Fixed-Effects," Papers 2209.11691, arXiv.org, revised Mar 2025.
    42. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.
    43. Iv'an Fern'andez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-Rank Approximations of Nonseparable Panel Models," Papers 2010.12439, arXiv.org, revised Mar 2021.

  27. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2014. "Program evaluation with high-dimensional data," CeMMAP working papers 33/14, Institute for Fiscal Studies.

    Cited by:

    1. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    2. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2014. "Valid post-selection inference in high-dimensional approximately sparse quantile regression models," CeMMAP working papers 53/14, Institute for Fiscal Studies.
    3. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2016. "Inference in High-Dimensional Panel Models With an Application to Gun Control," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 590-605, October.
    4. Victor Chernozhukov & Vira Semenova, 2018. "Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions," CeMMAP working papers CWP40/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
    6. Alexandre Belloni & Victor Chernozhukov & Lie Wang, 2013. "Pivotal estimation via square-root lasso in nonparametric regression," CeMMAP working papers CWP62/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," MPRA Paper 73622, University Library of Munich, Germany.
    8. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    9. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    10. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    11. Denis Chetverikov & . ., 2016. "On cross-validated Lasso," CeMMAP working papers CWP47/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Denis Chetverikov & . ., 2016. "On cross-validated Lasso," CeMMAP working papers 47/16, Institute for Fiscal Studies.
    13. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    14. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    15. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    16. Braverman, Mark & Chassang, Sylvain, 2022. "Data-driven incentive alignment in capitation schemes," Journal of Public Economics, Elsevier, vol. 207(C).
    17. Danquah, Michael & Iddrisu, Abdul Malik & Boakye, Ernest Owusu & Owusu, Solomon, 2021. "Do gender wage differences within households influence women's empowerment and welfare? Evidence from Ghana," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 916-932.
    18. Max H. Farrell, 2013. "Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations," Papers 1309.4686, arXiv.org, revised Feb 2018.
    19. Kasy Maximilian, 2019. "Uniformity and the Delta Method," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-19, January.
    20. Athey, Susan & Tibshirani, Julie & Wager, Stefan, 2017. "Generalized Random Forests," Research Papers 3575, Stanford University, Graduate School of Business.
    21. Thai T. Pham & Yuanyuan Shen, 2017. "A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform," Papers 1706.02795, arXiv.org.
    22. Matias D. Cattaneo & Michael Jansson, 2014. "Bootstrapping Kernel-Based Semiparametric Estimators," CREATES Research Papers 2014-25, Department of Economics and Business Economics, Aarhus University.
    23. Shao, Shuai & Xu, Le & Yang, Lili & Yu, Dianfan, 2024. "How do energy-saving policies improve environmental quality: Evidence from China’s Top 10,000 energy-consuming enterprises program," World Development, Elsevier, vol. 175(C).

  28. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.

    Cited by:

    1. Xuefeng Qian & Bifei Tian & W. Robert Reed & Ziruo Chen, 2018. "Searching for Profit-Shifting in China," Working Papers in Economics 18/08, University of Canterbury, Department of Economics and Finance.
    2. Xu, Shufang & Zhu, Ning & Copestake, James & Cai, Guiming & Peng, Xinman, 2024. "Is there a trade-off between MFls' financial efficiency and outreach in macroeconomic and institutional context?," International Review of Economics & Finance, Elsevier, vol. 94(C).
    3. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    4. Koen Jochmans, 2018. "Semiparametric Analysis of Network Formation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 705-713, October.
    5. Ramon Cobo-Reyes & Gabriel Katz & Simone Meraglia, 2017. "Endogenous Sanctioning Institutions and Migration Patterns: Experimental Evidence," Discussion Papers 1702, University of Exeter, Department of Economics.
    6. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    8. Yang Yang, 2023. "Hukou Identity and Economic Behaviours: A Social Identity Perspective," Erudite Ph.D Dissertations, Erudite, number ph23-02 edited by Catherine Bros & Julie Lochard, April.
    9. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2020. "Is there a euro effect in the drivers of US FDI? New evidence using Bayesian Model Averaging techniques," Working Papers 2020/25, Economics Department, Universitat Jaume I, Castellón (Spain).
    10. Presbitero, Andrea & Eberhardt, Markus, 2021. "Commodity Prices and Banking Crises," CEPR Discussion Papers 15959, C.E.P.R. Discussion Papers.
    11. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2022. "Discretizing Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 90(2), pages 625-643, March.
    12. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    13. Geert Dhaene & Martin Weidner, 2023. "Approximate functional differencing," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 14(3), pages 379-416, December.
    14. Geert Dhaene & Koen Jochmans, 2014. "Split-Panel Jackknife Estimation of Fixed-Effect Models," SciencePo Working papers Main hal-01070553, HAL.
    15. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.
    16. Jochmans, Koen, 2022. "Bias in instrumental-variable estimators of fixed-effect models for count data," Economics Letters, Elsevier, vol. 212(C).
    17. Larch, Mario & Yotov, Yoto V., 2016. "General equilibrium trade policy analysis with structural gravity," WTO Staff Working Papers ERSD-2016-08, World Trade Organization (WTO), Economic Research and Statistics Division.
    18. Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
    19. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2017. "Discretizing unobserved heterogeneity," IFS Working Papers W17/03, Institute for Fiscal Studies.
    20. Réka Juhász & Claudia Steinwender, 2018. "Spinning the Web: The Impact of ICT on Trade in Intermediates and Technology Diffusion," NBER Working Papers 24590, National Bureau of Economic Research, Inc.
    21. Francesca Marchetta & David E Sahn & Luca Tiberti, 2019. "The Role of Weather on Schooling and Work of Young Adults in Madagascar," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(4), pages 1203-1227.
    22. Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
    23. David W. Hughes, 2021. "Estimating Nonlinear Network Data Models with Fixed Effects," Boston College Working Papers in Economics 1058, Boston College Department of Economics.
    24. Müller, Karsten, 2019. "Electoral cycles in macroprudential regulation," ESRB Working Paper Series 106, European Systemic Risk Board.
    25. de Roure, Calebe & McLaren, Nick, 2019. "Liquidity transformation, collateral assets and counterparties," Bank of England working papers 830, Bank of England, revised 29 Jun 2020.
    26. Koen Jochmans, 2015. "Two-way models for gravity," SciencePo Working papers Main hal-01114776, HAL.
    27. Benedikt Heid & Mario Larch & Yoto V. Yoto, 2017. "Estimating the Effects of Non-discriminatory Trade Policies within Structural Gravity Models," CESifo Working Paper Series 6735, CESifo.
    28. Figueiredo, Octávio & Guimarães, Paulo & Woodward, Douglas, 2015. "Industry localization, distance decay, and knowledge spillovers: Following the patent paper trail," Journal of Urban Economics, Elsevier, vol. 89(C), pages 21-31.
    29. Otrachshenko, Vladimir & Nunes, Luis C., 2022. "Fire takes no vacation: impact of fires on tourism," Environment and Development Economics, Cambridge University Press, vol. 27(1), pages 86-101, February.
    30. Trebbi, Francesco & Canen, Nathan & Kendall, Chad, 2020. "Unbundling Polarization," CEPR Discussion Papers 14291, C.E.P.R. Discussion Papers.
    31. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    32. Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
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    173. Brantly Callaway & Tong Li & Irina Murtazashvili, 2021. "Distributional Effects with Two-Sided Measurement Error: An Application to Intergenerational Income Mobility," Papers 2107.09235, arXiv.org, revised Jun 2024.
    174. Hea‐Jung Hyun & Yong Joon Jang, 2022. "Technical regulation and trade: Export quality matters," The World Economy, Wiley Blackwell, vol. 45(5), pages 1447-1476, May.
    175. Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2025. "Grouped fixed effects regularization for binary choice models," Papers 2502.06446, arXiv.org.
    176. George Kapetanios & Laura Serlenga & Yongcheol Shin, 2024. "Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects," Advanced Studies in Theoretical and Applied Econometrics, in: Subal C. Kumbhakar & Robin C. Sickles & Hung-Jen Wang (ed.), Advances in Applied Econometrics, pages 147-195, Springer.
    177. Hyungsik Roger Roger Moon & Martin Weidner, 2014. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers 47/14, Institute for Fiscal Studies.
    178. 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.
    179. Zhian Yang & Pingzhang Lv & Shiqiang Sun, 2025. "The Impact of New Infrastructure Investment on the International Tourism Industry: Evidence from Provincial-Level Panel Data in China," Sustainability, MDPI, vol. 17(6), pages 1-19, March.
    180. Andres Sagner, 2020. "High Dimensional Quantile Factor Analysis," Working Papers Central Bank of Chile 886, Central Bank of Chile.
    181. Anna D’Ambrosio & Sandro Montresor, 2022. "The pro-export effect of subnational migration networks: new evidence from Spanish provinces," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 158(1), pages 53-107, February.
    182. Halil İbrahim KESKİN & Hakan ÖNDES, 2020. "Measuring the Efficiency of Selected European Football Clubs: DEA and Panel Tobit Model," Sosyoekonomi Journal, Sosyoekonomi Society, issue 28(43).
    183. Valentin Verdier, 2020. "Estimation and Inference for Linear Models with Two-Way Fixed Effects and Sparsely Matched Data," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 1-16, March.
    184. Das, Satya P. & Sant’Anna, Vinicios P., 2023. "Determinants of bilateral trade in manufacturing and services: A unified approach," Economic Modelling, Elsevier, vol. 123(C).
    185. Karyne B. Charbonneau, 2014. "Multiple Fixed Effects in Binary Response Panel Data Models," Staff Working Papers 14-17, Bank of Canada.
    186. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.
    187. Tamar Kricheli Katz & Tali Regev & Shay Lavie & Haggai Porat & Ronen Avraham, 2020. "Those who tan and those who don’t: A natural experiment on colorism," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-14, July.
    188. Alex Centeno, 2022. "A Structural Model for Detecting Communities in Networks," Papers 2209.08380, arXiv.org, revised Oct 2022.
    189. Raf Van Gestel & Tobias Mueller & Johan Bosmans, 2018. "Learning from failure in healthcare: Dynamic panel evidence of a physician shock effect," Diskussionsschriften dp1809, Universitaet Bern, Departement Volkswirtschaft.
    190. Bo E. Honoré & Martin Weidner, 2020. "Moment Conditions for Dynamic Panel Logit Models with Fixed Effects," CeMMAP working papers CWP38/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    191. Bauer, Gregory H., 2017. "International house price cycles, monetary policy and credit," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 88-114.
    192. Shuowen Chen, 2022. "Indirect Inference for Nonlinear Panel Models with Fixed Effects," Papers 2203.10683, arXiv.org, revised Apr 2022.
    193. Camarero, Mariam & Moliner, Sergi & Tamarit, Cecilio, 2021. "Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging," Japan and the World Economy, Elsevier, vol. 57(C).
    194. Sylvia Klosin, 2024. "Dynamic Biases of Static Panel Data Estimators," Papers 2410.16112, arXiv.org.
    195. Geert Dhaene & Martin Weidner, 2023. "Approximate Functional Differencing," Papers 2301.13736, arXiv.org, revised May 2023.
    196. Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
    197. Simon Hartmann & Rok Spruk, 2023. "The impact of unilateral BIT terminations on FDI: Quasi-experimental evidence from India," The Review of International Organizations, Springer, vol. 18(2), pages 259-296, April.
    198. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.
    199. Montfaucon, Angella Faith & Sato, Kiyotaka & Shrestha, Nagendra & Parsons, Craig, 2021. "Exchange rate pass-through and invoicing currency choice between fixed and floating exchange rate regimes: Evidence from Malawi’s transaction-level data," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 562-577.
    200. Mr. Markus Eberhardt & Mr. Andrea F Presbitero, 2018. "Commodity Price Movements and Banking Crises," IMF Working Papers 2018/153, International Monetary Fund.
    201. Ida Johnsson & Hyungsik Roger Moon, 2017. "Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach," Papers 1709.10024, arXiv.org, revised Jul 2019.

  29. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2013. "Evaluating the Role of Individual Specific Heterogeneity in the Relationship Between Subjective Health Assessments and Income," IZA Discussion Papers 7651, Institute of Labor Economics (IZA).

    Cited by:

    1. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2017. "Evaluating the role of income, state dependence and individual specific heterogeneity in the determination of subjective health assessments," Economics & Human Biology, Elsevier, vol. 25(C), pages 85-98.
    2. Lutz Bellmann & Olaf Hübler, 2022. "Personality traits, working conditions and health: an empirical analysis based on the German Linked Personnel Panel, 2013–2017," Review of Managerial Science, Springer, vol. 16(2), pages 283-318, February.
    3. Bellmann, Lutz & Hübler, Olaf, 2019. "Personal Attitudes, Job Characteristics and Health," IZA Discussion Papers 12597, Institute of Labor Economics (IZA).

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

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    3. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers 40/15, Institute for Fiscal Studies.
    4. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
    5. Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
    6. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers CWP12/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Linton, O. & Shiu, J-L., 2019. "Semiparametric Nonlinear Panel Data Models with Measurement Error," Cambridge Working Papers in Economics 1906, Faculty of Economics, University of Cambridge.
    9. Demian Pouzo & Zacharias Psaradakis & Martín Sola, 2021. "Maximum Likelihood Estimation in Markov Regime-Switching Models with Covariate-Dependent Transition Probabilities," Department of Economics Working Papers 2021_07, Universidad Torcuato Di Tella.
    10. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    11. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers 33/17, Institute for Fiscal Studies.
    12. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    13. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2016. "Maximum Likelihood Estimation in Possibly Misspeci ed Dynamic Models with Time-Inhomogeneous Markov Regimes," Department of Economics Working Papers 2016_04, Universidad Torcuato Di Tella.
    14. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    15. Čížek, Pavel & Lei, Jinghua, 2018. "Identification and estimation of nonseparable single-index models in panel data with correlated random effects," Journal of Econometrics, Elsevier, vol. 203(1), pages 113-128.
    16. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.
    17. Victor Chernozhukov & Iván Fernández‐Val & Ye Luo, 2018. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Econometrica, Econometric Society, vol. 86(6), pages 1911-1938, November.
    18. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    19. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
    20. Stefan Hoderlein & Hajo Holzmann & Maximilian Kasy & Alexander Meister, 2015. "Erratum regarding “Instrumental variables with unrestricted heterogeneity and continuous treatment”," Boston College Working Papers in Economics 896, Boston College Department of Economics, revised 01 Feb 2016.
    21. Laurent Davezies & Xavier D’Haultfoeuille & Louise Laage, 2025. "Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models," Working Papers 2025-02, Center for Research in Economics and Statistics.
    22. Irene Botosaru & Chris Muris & Krishna Pendakur, 2020. "Intertemporal Collective Household Models: Identification in Short Panels with Unobserved Heterogeneity in Resource Shares," Department of Economics Working Papers 2020-09, McMaster University.
    23. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    24. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Discussion Paper 2022-009, Tilburg University, Center for Economic Research.
    25. Ishihara, Takuya, 2020. "Identification and estimation of time-varying nonseparable panel data models without stayers," Journal of Econometrics, Elsevier, vol. 215(1), pages 184-208.
    26. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    27. D’Haultfœuille, Xavier & Hoderlein, Stefan & Sasaki, Yuya, 2023. "Nonparametric difference-in-differences in repeated cross-sections with continuous treatments," Journal of Econometrics, Elsevier, vol. 234(2), pages 664-690.
    28. Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.
    29. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.

  31. Ivan Fernandez-Val & Joonhwah Lee, 2012. "Panel Data Models with Nonadditive Unobserved Heterogeneity: Estimation and Inference," Papers 1206.2966, arXiv.org, revised Oct 2013.

    Cited by:

    1. Xiao, Jiaqi & Juodis, Arturas & Karavias, Yiannis & Sarafidis, Vasilis & Ditzen, Jan, 2022. "Improved Tests for Granger Non-Causality in Panel Data," MPRA Paper 114231, University Library of Munich, Germany.
    2. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    3. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    4. Koen Jochmans & Martin Weidner, 2019. "Inference on a distribution from noisy draws," CeMMAP working papers CWP44/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
    6. Koen Jochmans, 2015. "Two-way models for gravity," SciencePo Working papers Main hal-01114776, HAL.
    7. Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers 42/17, Institute for Fiscal Studies.
    8. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    10. Arturas Juodis & Yiannis Karavias & Vasilis Sarafidis, 2020. "A Homogeneous Approach to Testing for Granger Non-Causality in Heterogeneous Panels," Monash Econometrics and Business Statistics Working Papers 32/20, Monash University, Department of Econometrics and Business Statistics.
    11. Michael Bates & Seolah Kim, 2019. "Estimating the Price Elasticity of Gasoline Demand in Correlated Random Coefficient Models with Endogeneity," Working Papers 202021, University of California at Riverside, Department of Economics, revised Jul 2020.
    12. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.
    13. Santiago Pereda Fernández, 2016. "Copula-based random effects models for clustered data," Temi di discussione (Economic working papers) 1092, Bank of Italy, Economic Research and International Relations Area.
    14. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
    15. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    16. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    17. Iv'an Fern'andez-Val & Martin Weidner, 2017. "Fixed Effect Estimation of Large T Panel Data Models," Papers 1709.08980, arXiv.org, revised Mar 2018.
    18. Fernández-Val, Iván & Gao, Wayne Yuan & Liao, Yuan & Vella, Francis, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," IZA Discussion Papers 15236, Institute of Labor Economics (IZA).
    19. Valentin Verdier, 2020. "Average treatment effects for stayers with correlated random coefficient models of panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 917-939, November.
    20. Arturas Juodis & Yiannis Karavias, 2019. "Partially heterogeneous tests for Granger non-causality in panel data," Bank of Lithuania Working Paper Series 59, Bank of Lithuania.

  32. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile Regression with Censoring and Endogeneity," Papers 1104.4580, arXiv.org, revised Mar 2014.

    Cited by:

    1. German Blanco & Xuan Chen & Carlos A. Flores & Alfonso Flores-Lagunes, 2020. "Bounds on Average and Quantile Treatment Effects on Duration Outcomes Under Censoring, Selection, and Noncompliance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 901-920, October.
    2. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2009. "Inference on Counterfactual Distributions," Papers 0904.0951, arXiv.org, revised Sep 2013.
    3. Tatsushi Oka & Ken Yamada, 2023. "Heterogeneous Impact of the Minimum Wage: Implications for Changes in Between- and Within-Group Inequality," Journal of Human Resources, University of Wisconsin Press, vol. 58(1), pages 335-362.
    4. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    5. Sanna Nivakoski, 2020. "Wealth and the effect of subjective survival probability," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(2), pages 633-670, April.
    6. Evgeniy M. Ozhegov & Alina Ozhegova, 2020. "Regression tree model for prediction of demand with heterogeneity and censorship," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 489-500, April.
    7. Mendolia, Silvia & Paloyo, Alfredo R. & Walker, Ian, 2016. "Heterogeneous Effects of High School Peers on Educational Outcomes," IZA Discussion Papers 9795, Institute of Labor Economics (IZA).
    8. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers 48/17, Institute for Fiscal Studies.
    9. Chen, Songnian, 2018. "Sequential estimation of censored quantile regression models," Journal of Econometrics, Elsevier, vol. 207(1), pages 30-52.
    10. Chen, Songnian, 2019. "Quantile regression for duration models with time-varying regressors," Journal of Econometrics, Elsevier, vol. 209(1), pages 1-17.
    11. Yinchu Zhu, 2018. "Learning non-smooth models: instrumental variable quantile regressions and related problems," Papers 1805.06855, arXiv.org, revised Sep 2019.
    12. Gilles Crommen & Jad Beyhum & Ingrid Van Keilegom, 2024. "An instrumental variable approach under dependent censoring," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 33(2), pages 473-495, June.
    13. Justin Falk, 2023. "The Effects of Work Requirements on the Employment and Income of TANF Participants: Working Paper 2023-03," Working Papers 58867, Congressional Budget Office.
    14. Montes Rojas Gabriel & Alejo Javier & Galvao Antonio & Martínez-Iriarte Julián, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Asociación Argentina de Economía Política: Working Papers 4674, Asociación Argentina de Economía Política.
    15. Alina Ozhegova & Evgeniy M. Ozhegov, 2018. "Heterogeneity in demand for performances and seats in the theatre," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(3), pages 131-145, June.
    16. Victor Chernozhukov & Iv'n Fern'ndez-Val & Sukjin Han & Amanda E. Kowalski, 2018. "Censored Quantile Instrumental Variable Estimation with Stata," Cowles Foundation Discussion Papers 2120, Cowles Foundation for Research in Economics, Yale University.
    17. Manuel Arellano & Stéphane Bonhomme, 2017. "Sample Selection in Quantile Regression: A Survey," Working Papers wp2017_1702, CEMFI.
    18. Olga Miroshnichenko & Elena Iakovleva & Natalia Voronova, 2022. "Banking Sector Profitability: Does Household Income Matter?," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
    19. Yangyang Chen & Rui Ge & Henock Louis & Leon Zolotoy, 2019. "Stock liquidity and corporate tax avoidance," Review of Accounting Studies, Springer, vol. 24(1), pages 309-340, March.
    20. Erik Figueiredo & Luiz Renato Lima & Gianluca Orefice, 2016. "Migration and Regional Trade Agreements: A (New) Gravity Estimation," Review of International Economics, Wiley Blackwell, vol. 24(1), pages 99-125, February.
    21. Fernandez-Val , Ivan & van Vuuren, Aico & Vella, Francis, 2018. "Nonseparable Sample Selection Models with Censored Selection Rules," Working Papers in Economics 716, University of Gothenburg, Department of Economics.
    22. Chen, Songnian & Wang, Qian, 2023. "Quantile regression with censoring and sample selection," Journal of Econometrics, Elsevier, vol. 234(1), pages 205-226.
    23. James E. Payne & James W. Saunoris, 2020. "Corruption and Firm Tax Evasion in Transition Economies: Results from Censored Quantile Instrumental Variables Estimation," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 48(2), pages 195-206, June.
    24. Evgeniy M. Ozhegov & Daria Teterina, 2018. "The Ensemble Method For Censored Demand Prediction," HSE Working papers WP BRP 200/EC/2018, National Research University Higher School of Economics.
    25. Thomas Bassetti & Filippo Pavesi, 2015. "Electoral Contributions and the Cost of Unpopularity," "Marco Fanno" Working Papers 0195, Dipartimento di Scienze Economiche "Marco Fanno".
    26. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    27. Bertanha, Marinho & McCallum, Andrew H. & Seegert, Nathan, 2023. "Better bunching, nicer notching," Journal of Econometrics, Elsevier, vol. 237(2).
    28. Pourya Valizadeh & Shu Wen Ng, 2021. "Would A National Sugar‐Sweetened Beverage Tax in the United States Be Well Targeted?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 961-986, May.
    29. Kim, Young-Joo & Daly, Vincent, 2019. "The Education Gradient in Health: The Case of Obesity in the UK and US," Economics Discussion Papers 2019-4, School of Economics, Kingston University London.
    30. Alzuabi, Raslan & Brown, Sarah & Gray, Daniel & Harris, Mark N. & Spencer, Christopher, 2019. "Household Saving, Health, and Healthcare Utilisation in Japan," CEI Working Paper Series 2018-17, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    31. Amanda E. Kowalski, 2018. "Extrapolation using Selection and Moral Hazard Heterogeneity from within the Oregon Health Insurance Experiment," Cowles Foundation Discussion Papers 2135, Cowles Foundation for Research in Economics, Yale University.
    32. Brown, Sarah & Taylor, Karl, 2015. "Charitable Behaviour and the Big Five Personality Traits: Evidence from UK Panel Data," IZA Discussion Papers 9318, Institute of Labor Economics (IZA).
    33. Schmillen, Achim & Umkehrer, Matthias, 2013. "The scars of youth : effects of early-career unemployment on future unemployment experience," IAB-Discussion Paper 201306, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    34. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    35. Broberg, Thomas & Kazukauskas, Andrius, 2014. "Inefficiencies in residential use of energy - A critical overview of literature and energy efficiency policies in EU and Sweden," CERE Working Papers 2014:7, CERE - the Center for Environmental and Resource Economics.
    36. Victor Champonnois & Olivier Chanel & Costin Protopopescu, 2022. "Quantile Regression Analysis of Censored Data with Selection An Application to Willingness-to-Pay Data," AMSE Working Papers 2214, Aix-Marseille School of Economics, France.
    37. Jaeun Choi & A. James O'Malley, 2017. "Estimating the causal effect of treatment in observational studies with survival time end points and unmeasured confounding," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 159-185, January.
    38. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis, 2018. "Nonseparable Sample Selection Models with Censored Selection Rules: An Application to Wage Decompositions," IZA Discussion Papers 11294, Institute of Labor Economics (IZA).
    39. Affuso, Ermanno & Hite, Diane, 2013. "A model for sustainable land use in biofuel production: An application to the state of Alabama," Energy Economics, Elsevier, vol. 37(C), pages 29-39.
    40. L. Benfratello & A. Bottasso & C. Piccardo, 2022. "R&D and export performance: exploring heterogeneity along the export intensity distribution," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(2), pages 189-232, June.
    41. Abi Adams & Richard Blundell & Martin Browning & Ian Crawford, 2015. "Prices versus preferences: taste change and revealed preference," IFS Working Papers W15/11, Institute for Fiscal Studies.
    42. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    43. Männasoo, Kadri, 2022. "Working hours and gender wage differentials: Evidence from the American Working Conditions Survey," Labour Economics, Elsevier, vol. 76(C).
    44. Konstantinos Konstantaras & Vasilios Sogiakas, 2019. "Is stock liquidity transferred and upgraded in acquisitions? Evidence from liquidity synergies in US freeze-outs," Annals of Operations Research, Springer, vol. 282(1), pages 179-216, November.
    45. Jorge V Pérez-Rodríguez & Francisco Ledesma-Rodríguez, 2021. "Unconditional quantile regression and tourism expenditure: The case of the Canary Islands," Tourism Economics, , vol. 27(4), pages 626-648, June.
    46. Amanda E. Kowalski, 2016. "Doing More When You're Running LATE: Applying Marginal Treatment Effect Methods to Examine Treatment Effect Heterogeneity in Experiments," NBER Working Papers 22363, National Bureau of Economic Research, Inc.
    47. Bo Wei & Limin Peng & Mei‐Jie Zhang & Jason P. Fine, 2021. "Estimation of causal quantile effects with a binary instrumental variable and censored data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 559-578, July.
    48. Mukasa Adamon N. & Anthony M. Simpasa & Adeleke Oluwole Salami, 2017. "Working Paper 247 - Credit constraints and farm productivity: Micro-level evidence from smallholder farmers in Ethiopia," Working Paper Series 2356, African Development Bank.
    49. Victor Champonnois & Olivier Chanel & Costin Protopopescu, 2022. "Quantile Regression Analysis of Censored Data with Selection An Application to Willingness-to-Pay Data," Working Papers hal-03739861, HAL.
    50. Bucheli, José R. & Fontenla, Matías & Waddell, Benjamin James, 2019. "Return migration and violence," World Development, Elsevier, vol. 116(C), pages 113-124.
    51. Lima, Luiz Renato & Mesquita, Shirley & Wanamaker, Marianne, 2015. "Child labor and the wealth paradox: The role of altruistic parents," Economics Letters, Elsevier, vol. 130(C), pages 80-82.
    52. Sugimoto, Kota, 2021. "Ownership versus legal unbundling of electricity transmission network: Evidence from renewable energy investment in Germany," Energy Economics, Elsevier, vol. 99(C).
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    54. Virginie Vial & Julien Hanoteau, 2015. "Returns to Micro-Entrepreneurship in an Emerging Economy: A Quantile Study of Entrepreneurial Indonesian Households’ Welfare," Post-Print hal-01457392, HAL.
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  34. Joshua Angrist & Ivan Fernandez-Val, 2010. "ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework," NBER Working Papers 16566, National Bureau of Economic Research, Inc.

    Cited by:

    1. Hao Bo & Sebastian Galiani, 2019. "Assessing External Validity," NBER Working Papers 26422, National Bureau of Economic Research, Inc.
    2. Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Generalization error minimization: a new approach to model evaluation and selection with an application to penalized regression," Papers 1610.05448, arXiv.org.
    3. Wunsch, Conny & Strobl, Renate, 2018. "Identification of Causal Mechanisms Based on Between-Subject Double Randomization Designs," IZA Discussion Papers 11626, Institute of Labor Economics (IZA).
    4. Hunt Allcott, 2012. "Site Selection Bias in Program Evaluation," NBER Working Papers 18373, National Bureau of Economic Research, Inc.
    5. Sara Cools & Simen Markussen & Marte Strøm, 2017. "Children and Careers: How Family Size Affects Parents’ Labor Market Outcomes in the Long Run," Demography, Springer;Population Association of America (PAA), vol. 54(5), pages 1773-1793, October.
    6. Peter Hull, 2018. "Estimating Treatment Effects in Mover Designs," Papers 1804.06721, arXiv.org.
    7. Dehejia, Rajeev & Pop-Eleches, Cristian & Samii, Cyrus, 2015. "From Local to Global: External Validity in a Fertility Natural Experiment," IZA Discussion Papers 9300, Institute of Labor Economics (IZA).
    8. Dionissi Aliprantis, 2013. "Covariates and causal effects: the problem of context," Working Papers (Old Series) 1310, Federal Reserve Bank of Cleveland.
    9. Hans Fricke & Markus Frölich & Martin Huber & Michael Lechner, 2020. "Endogeneity and non‐response bias in treatment evaluation – nonparametric identification of causal effects by instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 481-504, August.
    10. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    11. Pritchett, Lant & Samji, Salimah & Hammer, Jeffrey, 2013. "It's All about MeE: Using Structured Experiential Learning ("e") to Crawl the Design Space," Working Paper Series rwp13-012, Harvard University, John F. Kennedy School of Government.
    12. Heng Chen & Geoffrey Dunbar & Q. Rallye Shen, 2020. "The Mode is the Message: Using Predata as Exclusion Restrictions to Evaluate Survey Design," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 341-357, Emerald Group Publishing Limited.
    13. Ethan Kaplan & Fernando Saltiel & Sergio Urzúa, 2023. "Voting for Democracy: Chile's Plebiscito and the Electoral Participation of a Generation," American Economic Journal: Economic Policy, American Economic Association, vol. 15(3), pages 438-464, August.
    14. James Bisbee & Rajeev Dehejia & Cristian Pop-Eleches & Cyrus Samii, 2015. "Local Instruments, Global Extrapolation: External Validity of the Labor Supply-Fertility Local Average Treatment Effect," NBER Working Papers 21663, National Bureau of Economic Research, Inc.
    15. Belchior, Carlos Alberto & Gonzaga, Gustavo & Ulyssea, Gabriel, 2023. "Unpacking Neighborhood Effects: Experimental Evidence from a Large-Scale Housing Program in Brazil," IZA Discussion Papers 16113, Institute of Labor Economics (IZA).
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    17. Daniel Aaronson & Rajeev Dehejia & Andrew Jordan & Cristian Pop-Eleches & Cyrus Samii & Karl Schulze, 2021. "The Effect of Fertility on Mothers’ Labor Supply over the Last Two Centuries [Semiparametric instrumental variables estimation of treatment response models]," The Economic Journal, Royal Economic Society, vol. 131(633), pages 1-32.
    18. de Luna, Xavier & Johansson, Per, 2012. "Testing for nonparametric identification of causal effects in the presence of a quasi-instrument," Working Paper Series 2012:14, IFAU - Institute for Evaluation of Labour Market and Education Policy.
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    23. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    24. Beatrice Baaba Tawiah, 2023. "The Effect of Children on Health," Working Papers Dissertations 103, Paderborn University, Faculty of Business Administration and Economics.
    25. Meager, Rachael, 2022. "Aggregating distributional treatment effects: a Bayesian hierarchical analysis of the microcredit literature," LSE Research Online Documents on Economics 115559, London School of Economics and Political Science, LSE Library.
    26. Sara Cools & Jon H. Fiva & Lars J. Kirkebøen, 2011. "Causal Effects of Paternity Leave on Children and Parents," CESifo Working Paper Series 3513, CESifo.
    27. Frölich, Markus & Melly, Blaise, 2008. "Identification of Treatment Effects on the Treated with One-Sided Non-Compliance," IZA Discussion Papers 3671, Institute of Labor Economics (IZA).
    28. Lina Zhang & David T. Frazier & Don S. Poskitt & Xueyan Zhao, 2021. "Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects," Monash Econometrics and Business Statistics Working Papers 21/21, Monash University, Department of Econometrics and Business Statistics.
    29. Brutscher, P-B., 2012. "Making Sense of Oil Stamp Saving Schemes," Cambridge Working Papers in Economics 1203, Faculty of Economics, University of Cambridge.
    30. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2015. "Going Beyond LATE: Bounding Average Treatment Effects of Job Corps Training," IZA Discussion Papers 9511, Institute of Labor Economics (IZA).
    31. Becker, Sascha O & Egger, Peter H & Von Ehrlich, Maximilian, 2012. "Absorptive Capacity and the Growth and Investment Effects of Regional Transfers: Regression Discontinuity Design with Heterogeneous Treatment Effects," CAGE Online Working Paper Series 89, Competitive Advantage in the Global Economy (CAGE).
    32. Christian N. Brinch & Magne Mogstad & Matthew Wiswall, 2012. "Beyond LATE with a discrete instrument. Heterogeneity in the quantity-quality interaction of children," Discussion Papers 703, Statistics Norway, Research Department.
    33. Meager, Rachael & Sturdy, Jennifer, 2017. "Aggregating Distributional Treatment Effects: A Bayesian Hierarchical Analysis of the Microcredit Literature," MetaArXiv 7tkvm, Center for Open Science.
    34. Angrist, Joshua & Rokkanen, Miikka, 2013. "Wanna Get Away? RD Identification Away from the Cutoff," IZA Discussion Papers 7429, Institute of Labor Economics (IZA).
    35. Daniel Fujiwara, 2013. "A General Method for Valuing Non-Market Goods Using Wellbeing Data: Three-Stage Wellbeing Valuation," CEP Discussion Papers dp1233, Centre for Economic Performance, LSE.

  35. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2009. "Inference on Counterfactual Distributions," Papers 0904.0951, arXiv.org, revised Sep 2013.

    Cited by:

    1. German Blanco & Xuan Chen & Carlos A. Flores & Alfonso Flores-Lagunes, 2020. "Bounds on Average and Quantile Treatment Effects on Duration Outcomes Under Censoring, Selection, and Noncompliance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 901-920, October.
    2. Brantly Callaway, 2020. "Bounds on Distributional Treatment Effect Parameters using Panel Data with an Application on Job Displacement," Papers 2008.08117, arXiv.org.
    3. Kolodziej, Ingo W.K. & García-Gómez, Pilar, 2019. "Saved by retirement: Beyond the mean effect on mental health," Social Science & Medicine, Elsevier, vol. 225(C), pages 85-97.
    4. René Böheim & Klemens Himpele & Helmut Mahringer & Christine Zulehner, 2013. "The distribution of the gender wage gap in Austria: evidence from matched employer-employee data and tax records [Eine Auswertung von Steuer- und Sozialversicherungsdaten zur Untersuchung der Verte," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 46(1), pages 19-34, March.
    5. Frölich, Markus & Melly, Blaise, 2008. "Quantile Treatment Effects in the Regression Discontinuity Design," IZA Discussion Papers 3638, Institute of Labor Economics (IZA).
    6. Marilena Furno, 2020. "Returns to Education and Gender Wage Gap Across Quantiles in Italy," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(2), pages 145-169, June.
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    280. Michael, Maria & Christofides, Louis N., 2020. "The impact of austerity measures on the public - private sector wage gap in Europe," Labour Economics, Elsevier, vol. 63(C).
    281. Mihaela-Cătălina Anastasiade-Guinand & Alina Matei & Yves Tillé, 2023. "Gender wage difference estimation at quantile levels using sample survey data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(4), pages 1392-1433, December.
    282. Andrew Goodman-Bacon & Jamein P. Cunningham, 2019. "Changes in Family Structure and Welfare Participation Since the 1960s: The Role of Legal Services," NBER Working Papers 26238, National Bureau of Economic Research, Inc.
    283. Kraft, Matthew A. & Brunner, Eric J. & Dougherty, Shaun M. & Schwegman, David J., 2020. "Teacher accountability reforms and the supply and quality of new teachers," Journal of Public Economics, Elsevier, vol. 188(C).
    284. Nigel Rice & María José Aragón, 2021. "Publicly funded hospital care: expenditure growth and its determinants," Working Papers 177cherp, Centre for Health Economics, University of York.
    285. Usamah F Alfarhan & Hossein Olya & Khaldoon Nusair, 2023. "How do prosperity and aspiration underlie leisure tourism expenditure patterns?," Tourism Economics, , vol. 29(3), pages 842-849, May.
    286. Biewen, Martin & Seckler, Matthias, 2017. "Changes in the German Wage Structure: Unions, Internationalization, Tasks, Firms, and Worker Characteristics," IZA Discussion Papers 10763, Institute of Labor Economics (IZA).
    287. VAN KERM Philippe & YU Seunghee & CHOE Chung, 2014. "Wage differentials between native, immigrant and cross-border workers: Evidence and model comparisons," LISER Working Paper Series 2014-05, Luxembourg Institute of Socio-Economic Research (LISER).
    288. Lai, Tsung-Chih & Su, Jiun-Hua, 2024. "Counterfactual copula," Economics Letters, Elsevier, vol. 241(C).
    289. Mustafizur Rahman & Md. Al-Hasan, 2019. "Male–Female Wage Gap and Informal Employment in Bangladesh: A Quantile Regression Approach," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 20(1), pages 106-123, March.
    290. Jessica Nisén & Johanna Tassot & Francesco Iacoella & Peter Eibich, 2022. "The effect of fertility timing on women’s earnings at midlife in the UK," MPIDR Working Papers WP-2022-021, Max Planck Institute for Demographic Research, Rostock, Germany.

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

    Cited by:

    1. Shiu, Ji-Liang & Hu, Yingyao, 2013. "Identification and estimation of nonlinear dynamic panel data models with unobserved covariates," Journal of Econometrics, Elsevier, vol. 175(2), pages 116-131.
    2. Martin Browning & Jesus M. Carro, 2009. "Dynamic binary outcome models with maximal heterogeneity," Economics Series Working Papers 426, University of Oxford, Department of Economics.
    3. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
    4. Ali Fakih, 2014. "Availability of Family-Friendly Work Practices and Implicit Wage Costs: New Evidence from Canada," CIRANO Working Papers 2014s-33, CIRANO.
    5. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2016. "Identification of panel data models with endogenous censoring," Journal of Econometrics, Elsevier, vol. 194(1), pages 57-75.
    6. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, vol. 166(1), pages 127-137.
    7. Andrei Markevich & Ekaterina Zhuravskaya, 2011. "M-form hierarchy with poorly-diversified divisions: A case of Khrushchev's reform in Soviet Russia," Post-Print halshs-00754499, HAL.
    8. Andrei Markevich & Ekaterina Zhuravskaya, 2009. "Career Concerns in a Political Hierarchy: A Case of Regional Leaders in Soviet Russia," Working Papers w0040, Center for Economic and Financial Research (CEFIR).
    9. Ali Fakih, 2014. "Vacation Leave, Work Hours And Wages: New Evidence From Linked Employer-Employee Data," CIRANO Papers 2014n-11a, CIRANO.
    10. 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.
    11. Manuel Arellano & Stéphane Bonhomme, 2012. "Identifying Distributional Characteristics in Random Coefficients Panel Data Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 987-1020.
    12. Hyland, Marie & Bertsch, Valentin, 2018. "The Role of Community Involvement Mechanisms in Reducing Resistance to Energy Infrastructure Development," Ecological Economics, Elsevier, vol. 146(C), pages 447-474.
    13. Lewbel, Arthur & Yang, Thomas Tao, 2016. "Identifying the average treatment effect in ordered treatment models without unconfoundedness," Journal of Econometrics, Elsevier, vol. 195(1), pages 1-22.
    14. Kyungchul Song, 2009. "Point Decisions for Interval-Identified Parameters," PIER Working Paper Archive 09-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    15. Philip Kostov & Julie Le Gallo, 2015. "Convergence: A Story of Quantiles and Spillovers," Kyklos, Wiley Blackwell, vol. 68(4), pages 552-576, November.
    16. 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.
    17. Valentin Bertsch & Hyland, Marie & Mahony, Michael, 2016. "What Drives People’s Opinions of Electricity Infrastructure? Empirical Evidence from Ireland," Papers WP545, Economic and Social Research Institute (ESRI).
    18. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    19. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    20. Ciani, Emanuele, 2012. "Informal adult care and caregivers' employment in Europe," Labour Economics, Elsevier, vol. 19(2), pages 155-164.

  37. Victor Chernozhukov & Ivan Fernandez-Val, 2009. "Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks," Papers 0912.5013, arXiv.org.

    Cited by:

    1. Xavier D’Haultfoeuille & Arnaud Maurel & Xiaoyun Qiu & Yichong Zhang, 2020. "Estimating selection models without an instrument with Stata," Stata Journal, StataCorp LLC, vol. 20(2), pages 297-308, June.
    2. Becker, Sascha O. & Hvide, Hans K., 2013. "Do entrepreneurs matter?," CEPR Discussion Papers 9295, C.E.P.R. Discussion Papers.
    3. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.
    4. Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2022. "Weighted-average quantile regression," Papers 2203.03032, arXiv.org.
    5. Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2016. "IV Quantile Regression for Group‐Level Treatments, With an Application to the Distributional Effects of Trade," Econometrica, Econometric Society, vol. 84, pages 809-833, March.
    6. Lee, Ji Hyung, 2016. "Predictive quantile regression with persistent covariates: IVX-QR approach," Journal of Econometrics, Elsevier, vol. 192(1), pages 105-118.
    7. Yuya Sasaki & Yulong Wang, 2020. "Testing Finite Moment Conditions for the Consistency and the Root-N Asymptotic Normality of the GMM and M Estimators," Papers 2006.02541, arXiv.org, revised Sep 2020.
    8. Daisuke Kurisu & Taisuke Otsu, 2021. "Nonparametric inference for extremal conditional quantiles," STICERD - Econometrics Paper Series 616, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    9. Florens, Jean-Pierre & Simar, Leopold & Van Keilegom, Ingrid, 2013. "Frontier estimation in nonparametric location-scale models," LIDAM Reprints ISBA 2013035, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Vladislav Morozov, 2022. "Inference on Extreme Quantiles of Unobserved Individual Heterogeneity," Papers 2210.08524, arXiv.org, revised Jun 2023.
    11. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    12. Oliver Himmler, 2009. "The Effects of School Competition on Academic Achievement and Grading Standards," CESifo Working Paper Series 2676, CESifo.
    13. Chernozhukov, Victor & Fernández-Val, Iván & Meier, Jonas & van Vuuren, Aico & Vella, Francis, 2025. "Conditional Rank-Rank Regression," IZA Discussion Papers 17591, Institute of Labor Economics (IZA).
    14. Habert white & Tae-Hwan Kim & Simone Manganelli, 2012. "VAR for VaR: Measuring Tail Dependence Using Multivariate Regression Quantiles," Working papers 2012rwp-45, Yonsei University, Yonsei Economics Research Institute.
    15. Yuya Sasaki & Yulong Wang, 2024. "Extreme Quantile Treatment Effects under Endogeneity: Evaluating Policy Effects for the Most Vulnerable Individuals," Papers 2409.03979, arXiv.org.
    16. Xavier D'Haultfoeuille & Arnaud Maurel & Yichong Zhang, 2014. "Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap," NBER Working Papers 20257, National Bureau of Economic Research, Inc.
    17. Julian Martinez-Iriarte & Gabriel Montes-Rojas & Yixiao Sun, 2022. "Unconditional Effects of General Policy Interventions," Papers 2201.02292, arXiv.org, revised Jul 2023.
    18. Calluzzo, Paul & Dong, Gang Nathan, 2015. "Has the financial system become safer after the crisis? The changing nature of financial institution risk," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 233-248.
    19. Marilena Furno & Francesco Caracciolo, 2020. "Multi-valued Double Robust quantile treatment effect," Empirical Economics, Springer, vol. 58(5), pages 2545-2571, May.
    20. Yulong Wang & Zhijie Xiao, 2020. "Estimation and Inference about Tail Features with Tail Censored Data," Boston College Working Papers in Economics 994, Boston College Department of Economics.
    21. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    22. Martina Pons, 2022. "The impact of air pollution on birthweight: evidence from grouped quantile regression," Empirical Economics, Springer, vol. 62(1), pages 279-296, January.
    23. David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.
    24. Michal Franta & Jan Vlcek, 2024. "Wage-Price Spirals: A Risk-Based Approach," Working Papers 2024/1, Czech National Bank.
    25. Daouia, Abdelaati & Stupfler, Gilles & Usseglio-Carleve, Antoine, 2022. "Inference for extremal regression with dependent heavy-tailed data," TSE Working Papers 22-1324, Toulouse School of Economics (TSE), revised 29 Aug 2023.
    26. Kurisu, Daisuke & Otsu, Taisuke, 2023. "Subsampling inference for nonparametric extremal conditional quantiles," LSE Research Online Documents on Economics 120365, London School of Economics and Political Science, LSE Library.
    27. Chavleishvili, Sulkhan & Manganelli, Simone, 2019. "Forecasting and stress testing with quantile vector autoregression," Working Paper Series 2330, European Central Bank.
    28. Yuya Sasaki & Yulong Wang, 2019. "Fixed-k Inference for Conditional Extremal Quantiles," Papers 1909.00294, arXiv.org, revised Jul 2020.
    29. Zhengyu Zhang & Zequn Jin & Lihua Lin, 2024. "Identification and inference of outcome conditioned partial effects of general interventions," Papers 2407.16950, arXiv.org.
    30. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly, 2022. "Fast algorithms for the quantile regression process," Empirical Economics, Springer, vol. 62(1), pages 7-33, January.
    31. Wei‐han Liu, 2020. "Are Gold and Government Bond Safe‐Haven Assets? An Extremal Quantile Regression Analysis," International Review of Finance, International Review of Finance Ltd., vol. 20(2), pages 451-483, June.
    32. Xiong, Qizhou, 2015. "Censored Fractional Response Model: Estimating Heterogeneous Relative Risk Aversion of European Households," IWH Discussion Papers 11/2015, Halle Institute for Economic Research (IWH).
    33. Aida Caldera Sánchez & Oliver Röhn, 2016. "How do policies influence GDP tail risks?," OECD Economics Department Working Papers 1339, OECD Publishing.
    34. Difang Huang & Jiti Gao & Tatsushi Oka, 2022. "Semiparametric Single-Index Estimation for Average Treatment Effects," Monash Econometrics and Business Statistics Working Papers 10/22, Monash University, Department of Econometrics and Business Statistics.
    35. Andres Sagner, 2020. "High Dimensional Quantile Factor Analysis," Working Papers Central Bank of Chile 886, Central Bank of Chile.
    36. Valentina Corradi & Daniel Gutknecht, 2019. "Testing for Quantile Sample Selection," Papers 1907.07412, arXiv.org, revised Jan 2021.
    37. Grimsby, Gjermund, 2018. "Partly risky, partly solid – Performance study of public innovation loans," Research Policy, Elsevier, vol. 47(7), pages 1344-1365.
    38. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    39. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    40. Maria Marino & Alessio Farcomeni, 2015. "Linear quantile regression models for longitudinal experiments: an overview," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 229-247, August.
    41. Takuma Yoshida, 2021. "Additive models for extremal quantile regression with Pareto-type distributions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(1), pages 103-134, March.
    42. He, Fengyang & Wang, Huixia Judy & Zhou, Yuejin, 2022. "Extremal quantile autoregression for heavy-tailed time series," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).

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

    Cited by:

    1. Ariel Pakes & Jack Porter, 2024. "Moment inequalities for multinomial choice with fixed effects," Quantitative Economics, Econometric Society, vol. 15(1), pages 1-25, January.
    2. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    3. Paulo M.M. Rodrigues & Matei Demetrescu, 2022. "Cross-Sectional Error Dependence in Panel Quantile Regressions," Working Papers w202213, Banco de Portugal, Economics and Research Department.
    4. Demetrescu, Matei & Hosseinkouchack, Mehdi & Rodrigues, Paulo M. M., 2023. "Tests of no cross-sectional error dependence in panel quantile regressions," Ruhr Economic Papers 1041, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Aguirregabiria, Victor & Carro, Jesus, 2021. "Identification of Average Marginal Effects in Fixed Effects Dynamic Discrete Choice Models," CEPR Discussion Papers 16354, C.E.P.R. Discussion Papers.
    6. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    8. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers 40/15, Institute for Fiscal Studies.
    9. Pauline Givord & Lionel Wilner, 2014. "When Does the Stepping‐Stone Work? Fixed‐Term Contracts Versus Temporary Agency Work in Changing Economic Conditions," Post-Print hal-04799379, HAL.
    10. Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-rank approximations of nonseparable panel models," CeMMAP working papers CWP52/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Geert Dhaene & Martin Weidner, 2023. "Approximate functional differencing," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 14(3), pages 379-416, December.
    12. Xavier d'Haultfoeuille & Roland Rathelot, 2011. "Measuring Segregation on Small Units : A Partial Identification Analysis," Working Papers 2011-18, Center for Research in Economics and Statistics.
    13. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    14. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    15. Jesus M. Carro & Alejandra Traferri, 2014. "State Dependence And Heterogeneity In Health Using A Bias‐Corrected Fixed‐Effects Estimator," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 181-207, March.
    16. Molinari, Francesca, 2020. "Microeconometrics with partial identification," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 355-486, Elsevier.
    17. Peter Hull, 2018. "Estimating Treatment Effects in Mover Designs," Papers 1804.06721, arXiv.org.
    18. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    19. Carro, Jesús M. & Pronkina, Elizaveta, 2021. "The heterogeneous effects of the Great Recession on informal care to the elderly," UC3M Working papers. Economics 33444, Universidad Carlos III de Madrid. Departamento de Economía.
    20. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
    21. Christopher Dobronyi & Jiaying Gu & Kyoo il Kim & Thomas M. Russell, 2021. "Identification of Dynamic Panel Logit Models with Fixed Effects," Papers 2104.04590, arXiv.org, revised Dec 2024.
    22. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
    23. Dmitry Arkhangelsky & Guido Imbens, 2018. "Fixed Effects and the Generalized Mundlak Estimator," Papers 1807.02099, arXiv.org, revised Aug 2023.
    24. St'ephane Bonhomme & Kevin Dano, 2023. "Functional Differencing in Networks," Papers 2307.11484, arXiv.org.
    25. Victor Aguirregabiria & Jiaying Gu & Yao Luo, 2018. "Sufficient Statistics for Unobserved Heterogeneity in Structural Dynamic Logit Models," Working Papers tecipa-603, University of Toronto, Department of Economics.
    26. Kevin Dano, 2023. "Transition Probabilities and Moment Restrictions in Dynamic Fixed Effects Logit Models," Papers 2303.00083, arXiv.org, revised Dec 2023.
    27. Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
    28. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2024. "Bootstrap Inference for Panel Data Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 628-639, April.
    29. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers CWP12/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Khan, S. & Ponomareva, M. & Tamer, E., 2023. "Identification of dynamic binary response models," Journal of Econometrics, Elsevier, vol. 237(1).
    31. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    32. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    33. Desire Kedagni & Kala Krishna & Rigissa Megalokonomou & Yingyan Zhao, 2019. "Does Class Size Matter? How, and at What Cost?," NBER Working Papers 25736, National Bureau of Economic Research, Inc.
    34. Linton, O. & Shiu, J-L., 2019. "Semiparametric Nonlinear Panel Data Models with Measurement Error," Cambridge Working Papers in Economics 1906, Faculty of Economics, University of Cambridge.
    35. Shu Yang & Yunshu Zhang, 2023. "Multiply robust matching estimators of average and quantile treatment effects," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 235-265, March.
    36. Clément de Chaisemartin & Xavier D'Haultfoeuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," NBER Working Papers 29691, National Bureau of Economic Research, Inc.
    37. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney K. Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers 66/13, Institute for Fiscal Studies.
    38. Laurent Davezies & Xavier D'Haultfœuille & Martin Mugnier, 2023. "Fixed‐effects binary choice models with three or more periods," Quantitative Economics, Econometric Society, vol. 14(3), pages 1105-1132, July.
    39. Laurent Davezies & Xavier D'Haultf{oe}uille & Louise Laage, 2021. "Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models," Papers 2105.00879, arXiv.org, revised Dec 2024.
    40. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    41. Natalia Lazzati & John K.‐H. Quah & Koji Shirai, 2025. "An ordinal approach to the empirical analysis of games with monotone best responses," Quantitative Economics, Econometric Society, vol. 16(1), pages 235-266, January.
    42. Andrew Chesher & Adam Rosen & Yuanqi Zhang, 2024. "Robust analysis of short panels," CeMMAP working papers 01/24, Institute for Fiscal Studies.
    43. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    44. Cavit Pakel & Martin Weidner, 2023. "Bounds on Average Effects in Discrete Choice Panel Data Models," Papers 2309.09299, arXiv.org, revised May 2024.
    45. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods," Papers 1803.09015, arXiv.org, revised Dec 2020.
    46. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    47. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2016. "Identification of panel data models with endogenous censoring," Journal of Econometrics, Elsevier, vol. 194(1), pages 57-75.
    48. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers 33/17, Institute for Fiscal Studies.
    49. Rachel Cassidy & Marije Groot Bruinderink & Wendy Janssens & Karlijn Morsink, 2020. "The Power to Protect: Household Bargaining and Female Condom Use," Tinbergen Institute Discussion Papers 20-058/VI, Tinbergen Institute.
    50. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    51. Desbordes, Rodolphe & Eberhardt, Markus, 2024. "Climate change and economic prosperity: Evidence from a flexible damage function," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    52. Michelle Marcus & Pedro H. C. Sant’Anna, 2021. "The Role of Parallel Trends in Event Study Settings: An Application to Environmental Economics," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 8(2), pages 235-275.
    53. 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.
    54. Douglas L. Miller & Na’ama Shenhav & Michel Z. Grosz, 2019. "Selection into Identification in Fixed Effects Models, with Application to Head Start," NBER Working Papers 26174, National Bureau of Economic Research, Inc.
    55. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    56. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.
    57. Wooldridge, Jeffrey M., 2019. "Correlated random effects models with unbalanced panels," Journal of Econometrics, Elsevier, vol. 211(1), pages 137-150.
    58. Čížek, Pavel & Lei, Jinghua, 2018. "Identification and estimation of nonseparable single-index models in panel data with correlated random effects," Journal of Econometrics, Elsevier, vol. 203(1), pages 113-128.
    59. Jinyong Hahn & David W. Hughes & Guido Kuersteiner & Whitney K. Newey, 2022. "Efficient Bias Correction for Cross-section and Panel Data," Papers 2207.09943, arXiv.org, revised Jan 2024.
    60. Michael Bates & Seolah Kim, 2019. "Estimating the Price Elasticity of Gasoline Demand in Correlated Random Coefficient Models with Endogeneity," Working Papers 202021, University of California at Riverside, Department of Economics, revised Jul 2020.
    61. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.
    62. Stéphane Bonhomme & Martin Weidner, 2020. "Minimizing Sensitivity to Model Misspecification," CeMMAP working papers CWP37/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    63. Ming Li, 2021. "Identification and Estimation in a Time-Varying Endogenous Random Coefficient Panel Data Model," Papers 2110.00982, arXiv.org, revised Nov 2024.
    64. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    65. Xin Liu, 2024. "A quantile-based nonadditive fixed effects model," Papers 2405.03826, arXiv.org.
    66. Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2020. "Bayesian Panel Quantile Regression for Binary Outcomes with Correlated Random Effects: An Application on Crime Recidivism in Canada," Papers 2001.09295, arXiv.org.
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    7. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "On the asymptotic theory for least squares series: pointwise and uniform results," CeMMAP working papers 73/13, Institute for Fiscal Studies.
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    175. Tonghui Yu & Liming Xiang & Huixia Judy Wang, 2021. "Quantile regression for survival data with covariates subject to detection limits," Biometrics, The International Biometric Society, vol. 77(2), pages 610-621, June.
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    178. 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.
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    180. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
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    Cited by:

    1. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    2. Pierre-Philippe Combes & Bruno Decreuse & Morgane Laouénan & Alain Trannoy, 2016. "Customer Discrimination and Employment Outcomes: Theory and Evidence from the French Labor Market," Journal of Labor Economics, University of Chicago Press, vol. 34(1), pages 107-160.
    3. Johannes S. Kunz & Kevin E. Staub & Rainer Winkelmann, 2019. "Predicting fixed effects in panel probit models," Monash Economics Working Papers 10-19, Monash University, Department of Economics.
    4. Jose Apesteguia & Ignacio Palacios-Huerta, 2008. "Psychological pressure in competitive environments: Evidence from a randomized natural experiment," Economics Working Papers 1116, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Shiu, Ji-Liang & Hu, Yingyao, 2013. "Identification and estimation of nonlinear dynamic panel data models with unobserved covariates," Journal of Econometrics, Elsevier, vol. 175(2), pages 116-131.
    6. Jess Benhabib & Alejandro Corvalan & Mark M. Spiegel, 2011. "Reestablishing the Income-Democracy Nexus," NBER Working Papers 16832, National Bureau of Economic Research, Inc.
    7. Rubén Segura-Cayuela & Josep M. Vilarrubia, 2008. "The effect of foreign service on trade volumes and trade partners," Working Papers 0808, Banco de España.
    8. Bazillier, Rémi & Hatte, Sophie & Vauday, Julien, 2017. "Are environmentally responsible firms less vulnerable when investing abroad? The role of reputation," Journal of Comparative Economics, Elsevier, vol. 45(3), pages 520-543.
    9. Felix Holub & Laura Hospido & Ulrich J. Wagner, 2020. "Urban air pollution and sick leaves: evidence from social security data," Working Papers 2041, Banco de España.
    10. Noth, Felix & Schüwer, Ulrich, 2017. "Natural disasters and bank stability: Evidence from the U.S. financial system," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168263, Verein für Socialpolitik / German Economic Association.
    11. Vivian Norambuena, 2015. "Sovereign Debt Default: Are Countries Trapped by Their Own Default History?," Working Papers wp416, University of Chile, Department of Economics.
    12. Rémi BAZILLIER & Sophie HATTE & Julien VAUDAY, 2016. "Is Reputation at Stake When Environmentally Responsible Multinationals Invest Abroad? An Empirical Investigation," LEO Working Papers / DR LEO 2315, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    13. John M. Clapp & Stephen L. Ross & Tingyu Zhou, 2019. "Retail Agglomeration and Competition Externalities: Evidence from Openings and Closings of Multiline Department Stores in the U.S," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 81-96, January.
    14. Hochguertel, Stefan & Ohlsson, Henry, 2011. "Wealth mobility and dynamics over entire individual working life cycles," Working Paper Series 1301, European Central Bank.
    15. Hospido, Laura, 2010. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," IZA Discussion Papers 4712, Institute of Labor Economics (IZA).
    16. Zareh Asatryan & Annika Havlik & Frank Streif, 2017. "Vetoing and inaugurating policy like others do: evidence on spatial interactions in voter initiatives," Public Choice, Springer, vol. 172(3), pages 525-544, September.
    17. Kajal Lahiri & Xian Li, 2020. "Smoking Behavior of Older Adults: A Panel Data Analysis Using HRS," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 495-523, September.
    18. Xiaoming Li, 2011. "Fixed Effects Estimation in Panel Nonlinear Fractional Response Models," Working papers 2011-11, University of Connecticut, Department of Economics.
    19. Grant, Darren, 2009. "Physician financial incentives and cesarean delivery: New conclusions from the healthcare cost and utilization project," Journal of Health Economics, Elsevier, vol. 28(1), pages 244-250, January.
    20. Rocha, Romero & Soares, Rodrigo R., 2009. "Evaluating the Impact of Community-Based Health Interventions: Evidence from Brazil's Family Health Program," IZA Discussion Papers 4119, Institute of Labor Economics (IZA).
    21. Bartolucci, Francesco & Nigro, Valentina, 2012. "Pseudo conditional maximum likelihood estimation of the dynamic logit model for binary panel data," Journal of Econometrics, Elsevier, vol. 170(1), pages 102-116.
    22. Blair Alexander & Robert Breunig, 2012. "A Monte Carlo Study of Bias Corrections for Panel Probit Models," CEPR Discussion Papers 662, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    23. Orcun Kaya, 2014. "Is perceived financial inadequacy persistent?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 636-654, December.
    24. Alison Preston & Robert E. Wright, 2020. "Exploring the gender difference in multiple job holding," Industrial Relations Journal, Wiley Blackwell, vol. 51(4), pages 301-328, July.
    25. Douglas L. Miller & Na’ama Shenhav & Michel Z. Grosz, 2019. "Selection into Identification in Fixed Effects Models, with Application to Head Start," NBER Working Papers 26174, National Bureau of Economic Research, Inc.
    26. Salvador Gil-Pareja, 2011. "Do nonreciprocal preference regimes increase exports?," ERSA conference papers ersa11p1561, European Regional Science Association.
    27. Sergei Guriev & Evgeny Yakovlev & Ekaterina Zhuravskaya, 2010. "Interest Group Politics in a Federation," Post-Print halshs-00754421, HAL.
    28. Sun, Yixiao & Kim, Min Seong, 2009. "k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models," University of California at San Diego, Economics Working Paper Series qt9gn6n5mr, Department of Economics, UC San Diego.
    29. Marco Grazzi & Nanditha Mathew & Daniele Moschella, 2017. "Efficiency, innovation, and imported inputs: determinants of export performance among Indian manufacturing firms," LEM Papers Series 2017/09, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    30. Yuliyan Mitkov & Ulrich Schüwer, 2021. "Unequal andunstable: income inequality and bank risk," ECONtribute Discussion Papers Series 012, University of Bonn and University of Cologne, Germany.
    31. Michael Anderson & Maximilian Auffhammer, 2011. "Pounds that Kill: The External Costs of Vehicle Weight," NBER Working Papers 17170, National Bureau of Economic Research, Inc.
    32. Carro, Jesús M. & Traferri, Alejandra, 2009. "Correcting the bias in the estimation of a dynamic ordered probit with fixed effects of self-assessed health status," UC3M Working papers. Economics we094021, Universidad Carlos III de Madrid. Departamento de Economía.
    33. Noth, Felix & Schüwer, Ulrich, 2018. "Natural disasters and bank stability: Evidence from the U.S. financial system," SAFE Working Paper Series 167, Leibniz Institute for Financial Research SAFE, revised 2018.
    34. Cerutti, Eugenio & Dagher, Jihad & Dell'Ariccia, Giovanni, 2017. "Housing finance and real-estate booms: A cross-country perspective," Journal of Housing Economics, Elsevier, vol. 38(C), pages 1-13.
    35. Fidrmuc, Jarko & Hainz, Christa, 2010. "Default rates in the loan market for SMEs: Evidence from Slovakia," Economic Systems, Elsevier, vol. 34(2), pages 133-147, June.
    36. Lambert, Claudia & Noth, Felix & Schüwer, Ulrich, 2014. "How do insured deposits affect bank risk? Evidence from the 2008 Emergency Economic Stabilization Act," SAFE Working Paper Series 38, Leibniz Institute for Financial Research SAFE, revised 2014.
    37. Buringh, Eltjo & Bosker, Maarten, 2010. "City seeds. Geography and the origins of the European city system," CEPR Discussion Papers 8066, C.E.P.R. Discussion Papers.
    38. Albarrán, Pedro & Carrasco, Raquel & Carro, Jesús M., 2015. "Estimation of Dynamic Nonlinear Random Effects Models with Unbalanced Panels," UC3M Working papers. Economics we1503, Universidad Carlos III de Madrid. Departamento de Economía.
    39. Sun, Ang & Yao, Yang, 2010. "Health shocks and children's school attainments in rural China," Economics of Education Review, Elsevier, vol. 29(3), pages 375-382, June.
    40. Andrew Adrian Yu Pua, 2015. "On IV estimation of a dynamic linear probability model with fixed effects," UvA-Econometrics Working Papers 15-01, Universiteit van Amsterdam, Dept. of Econometrics.
    41. Francesco Bartolucci & Valentina Nigro & Claudia Pigini, 2018. "Testing for state dependence in binary panel data with individual covariates by a modified quadratic exponential model," Econometric Reviews, Taylor & Francis Journals, vol. 37(1), pages 61-88, January.
    42. Tanika Chakraborty & Prabal K. De, 2011. "Mother's Autonomy and Child Welfare: A New Measure and Some New Evidence," Discussion Papers of DIW Berlin 1102, DIW Berlin, German Institute for Economic Research.
    43. Aysen Isaoglu, 2010. "Worker Reallocation across Occupations in Western Germany," SOEPpapers on Multidisciplinary Panel Data Research 319, DIW Berlin, The German Socio-Economic Panel (SOEP).
    44. 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.
    45. Jess Benhabib & Alejandro Corvalen & Mark M. Spiegel, 2014. "Modernization and Discrete Measures of Democracy," Working Paper Series 2014-1, Federal Reserve Bank of San Francisco.
    46. Yoshitsugu Kitazawa, 2013. "Exploration of dynamic fixed effects logit models from a traditional angle," Discussion Papers 60, Kyushu Sangyo University, Faculty of Economics.
    47. Pigini, Claudia & Bartolucci, Francesco, 2022. "Conditional inference for binary panel data models with predetermined covariates," Econometrics and Statistics, Elsevier, vol. 23(C), pages 83-104.
    48. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
    49. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2013. "Evaluating the Role of Individual Specific Heterogeneity in the Relationship Between Subjective Health Assessments and Income," IZA Discussion Papers 7651, Institute of Labor Economics (IZA).
    50. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    51. Ciani, Emanuele, 2012. "Informal adult care and caregivers' employment in Europe," Labour Economics, Elsevier, vol. 19(2), pages 155-164.
    52. Bartolucci, Francesco & Nigro, Valentina & Pigini, Claudia, 2013. "Testing for state dependence in binary panel data with individual covariates," MPRA Paper 48233, University Library of Munich, Germany.

  42. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Rearranging Edgeworth-Cornish-Fisher Expansions," Papers 0708.1627, arXiv.org, revised May 2013.

    Cited by:

    1. Candelon, Bertrand & Fuerst, Franz & Hasse, Jean-Baptiste, 2021. "Diversification Potential in Real Estate Portfolios," LIDAM Discussion Papers LFIN 2021001, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2019. "Posterior moments and quantiles for the normal location model with Laplace prior," EIEF Working Papers Series 1911, Einaudi Institute for Economics and Finance (EIEF), revised Jun 2019.
    3. Victor Chernozhukov & Pierre-André Chiappori & Marc Henry, 2010. "Introduction," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 42(2), pages 271-273, February.
    4. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Jean-Luc Prigent & Donald Keenan & Mahdi Mokrane, 2017. "Modified Sharpe Ratios in Real Estate Performance Measurement: Beyond the Standard Cornish Fisher Expansion," THEMA Working Papers 2017-20, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    5. Brenda Castillo-Brais & Ángel León & Juan Mora, 2022. "Estimating Value-at-Risk and Expected Shortfall: Do Polynomial Expansions Outperform Parametric Densities?," Mathematics, MDPI, vol. 10(22), pages 1-17, November.
    6. Stéphane Hamayon & Florence Legros & Pradat Yannick, 2016. "Non gaussian returns: which impact on default options retirement plans? [Distribution non gaussienne des rendements : quel impact sur les options par défaut des plans d'épargne retraite ?]," Working Papers hal-03003588, HAL.
    7. Karlygash Kurlbayeva & Samuel Malone, 2012. "The determinants of extreme commodity prices," OxCarre Working Papers 096, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    8. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Donald Keenan, 2015. "Cornish-Fisher Expansion for Commercial Real Estate Value at Risk," The Journal of Real Estate Finance and Economics, Springer, vol. 50(4), pages 439-464, May.
    9. Lee, Wing Yan & Li, Xiaolong & Liu, Fangda & Shi, Yifan & Yam, Sheung Chi Phillip, 2021. "A Fourier-cosine method for finite-time ruin probabilities," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 256-267.
    10. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy, 2022. "Proper use of the modified Sharpe ratios in performance measurement: rearranging the Cornish Fisher expansion," Annals of Operations Research, Springer, vol. 313(2), pages 691-712, June.
    11. Ghossoub, Mario, 2011. "Monotone equimeasurable rearrangements with non-additive probabilities," MPRA Paper 37629, University Library of Munich, Germany, revised 23 Mar 2012.
    12. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Didier Maillard, 2019. "Computation of the corrected Cornish–Fisher expansion using the response surface methodology: application to VaR and CVaR," Annals of Operations Research, Springer, vol. 281(1), pages 423-453, October.
    13. Liu, Nianqing & Vuong, Quang & Xu, Haiqing, 2017. "Rationalization and identification of binary games with correlated types," Journal of Econometrics, Elsevier, vol. 201(2), pages 249-268.
    14. Zang, Zhaoqi & Xu, Xiangdong & Yang, Chao & Chen, Anthony, 2018. "A closed-form estimation of the travel time percentile function for characterizing travel time reliability," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 228-247.
    15. Charles-Olivier Amedee-Manesme & Fabrice Barthélémy, 2012. "Cornish-Fisher expansion for real estate value at risk," ERES eres2012_044, European Real Estate Society (ERES).
    16. Carnero, M. Angeles & León, Angel & Ñíguez, Trino-Manuel, 2023. "Skewness in energy returns: estimation, testing and retain-->implications for tail risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 178-189.
    17. Donald Lien & Christopher Stroud & Keying Ye, 2013. "Comparing VaR Approximation Methods Which Use the First Four Moments as Inputs," Working Papers 0220mss, College of Business, University of Texas at San Antonio.

  43. Francis Vella & Ivan Fernandez-Val, 2007. "Bias Corrections for Two-Step Fixed Effects Panel Data Estimators," Boston University - Department of Economics - Working Papers Series WP2007-010, Boston University - Department of Economics.

    Cited by:

    1. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    2. Ramon Cobo-Reyes & Gabriel Katz & Simone Meraglia, 2017. "Endogenous Sanctioning Institutions and Migration Patterns: Experimental Evidence," Discussion Papers 1702, University of Exeter, Department of Economics.
    3. Alderighi, Marco & Gaggero, Alberto A. & Piga, Claudio A., 2015. "The effect of code-share agreements on the temporal profile of airline fares," Transportation Research Part A: Policy and Practice, Elsevier, vol. 79(C), pages 42-54.
    4. Panutat Satchachai & Peter Schmidt, 2010. "Estimates of technical inefficiency in stochastic frontier models with panel data: generalized panel jackknife estimation," Journal of Productivity Analysis, Springer, vol. 34(2), pages 83-97, October.
    5. Geert Dhaene & Koen Jochmans, 2014. "Split-Panel Jackknife Estimation of Fixed-Effect Models," SciencePo Working papers Main hal-01070553, HAL.
    6. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.
    7. Haruo Iwakura, 2014. "Deriving the Information Bounds for Nonlinear Panel Data Models with Fixed Effects," KIER Working Papers 886, Kyoto University, Institute of Economic Research.
    8. Elizabeth Schroeder, 2016. "Dynamic labor supply adjustment with bias correction," Empirical Economics, Springer, vol. 51(4), pages 1623-1640, December.
    9. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2017. "Evaluating the role of income, state dependence and individual specific heterogeneity in the determination of subjective health assessments," Economics & Human Biology, Elsevier, vol. 25(C), pages 85-98.
    10. Koen Jochmans, 2015. "Multiplicative-error models with sample selection," SciencePo Working papers Main hal-03392990, HAL.
    11. Simone Bertoli & Jesús Fernández-Huertas Moraga, 2015. "Visa Policies, Networks and the Cliff at the Border," CERDI Working papers halshs-01099863, HAL.
    12. Antonis Demos & Dimitra Kyriakopoulou, 2018. "Finite Sample Theory and Bias Correction of Maximum Likelihood Estimators in the EGARCH Model," DEOS Working Papers 1802, Athens University of Economics and Business.
    13. Ayden Higgins & Koen Jochmans, 2024. "Bootstrap Inference for Fixed‐Effect Models," Econometrica, Econometric Society, vol. 92(2), pages 411-427, March.
    14. Koen Jochmans & Vincenzo Verardi, 2022. "Instrumental‐variable estimation of exponential‐regression models with two‐way fixed effects with an application to gravity equations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1121-1137, September.
    15. Martin Weidner & Thomas Zylkin, 2021. "Bias and consistency in three-way gravity models," CeMMAP working papers CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Michael Beckmann & Thomas Cornelissen & Matthias Kräkel, 2015. "Self-Managed Working Time and Employee Effort: Theory and Evidence," SOEPpapers on Multidisciplinary Panel Data Research 768, DIW Berlin, The German Socio-Economic Panel (SOEP).
    17. Harrison Fell & Daniel T. Kaffine, 2018. "The Fall of Coal: Joint Impacts of Fuel Prices and Renewables on Generation and Emissions," American Economic Journal: Economic Policy, American Economic Association, vol. 10(2), pages 90-116, May.
    18. Georgios Marios Chrysanthou, 2008. "Estimating Union Wage Effects in Great Britain During 1991-2003," Discussion Papers 08/12, Department of Economics, University of York.
    19. Stelios Arvanitis & Antonis Demos, 2014. "A Class of Indirect Inference Estimators: Higher Order Asymptotics and Approximate Bias Correction (Revised)," DEOS Working Papers 1411, Athens University of Economics and Business, revised 23 Sep 2014.
    20. Michael J. Hicks & Michael LaFaive & Srikant Devaraj, 2016. "New Evidence on the Effect of Right-to-Work Laws on Productivity and Population Growth," Cato Journal, Cato Journal, Cato Institute, vol. 36(1), pages 101-120, Winter.
    21. Chih-Hai Yang & Meng-Wen Tsou, 2020. "Globalization and firm growth: does ownership matter?," Small Business Economics, Springer, vol. 55(4), pages 1019-1037, December.
    22. Almer, Christian & Laurent-Lucchetti, Jérémy & oechslin, Manuel, 2011. "Income shocks and social unrest: theory and evidence," MPRA Paper 34426, University Library of Munich, Germany.
    23. Michael Beckmann & Thomas Cornelissen, 2014. "Self-Managed Working Time and Employee Effort: Microeconometric Evidence," SOEPpapers on Multidisciplinary Panel Data Research 636, DIW Berlin, The German Socio-Economic Panel (SOEP).
    24. Sergi Jiménez-Martín & Majid M. Al-Sadoon, 2019. "Simple Methods for Consistent Estimation of Dynamic Panel Data Sample Selection Models," Working Papers 1069, Barcelona School of Economics.
    25. Sergi Jiménez-Martín & José María Labeaga, 2016. "Monte Carlo evidence on the estimation of AR(1) panel data sample selection models," Working Papers 2016-01, FEDEA.
    26. Paroma Sanyal & Linda R. Cohen, 2009. "Powering Progress: Restructuring, Competition, and R&D in the U.S. Electric Utility Industry," The Energy Journal, , vol. 30(2), pages 41-80, April.
    27. Naguib, Costanza, 2022. "Analytical bias correction for two-step fixed effects models with copula-distributed errors," Economics Letters, Elsevier, vol. 215(C).
    28. Chen, Mingli, 2016. "Estimation of Nonlinear Panel Models with Multiple Unobserved Effects," Economic Research Papers 269326, University of Warwick - Department of Economics.
    29. Harrison Fell & Daniel T. Kaffine, 2014. "A one-two punch: Joint effects of natural gas abundance and renewables on coal-fired power plants," Working Papers 2014-10, Colorado School of Mines, Division of Economics and Business.
    30. Yuki Takara, 2018. "Do cultural differences affect the trade of cultural goods? A study in trade of music," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 42(3), pages 393-417, August.
    31. Jochmans, K. & Verardi, V., 2019. "Instrumental-Variable Estimation of Gravity Equations," Cambridge Working Papers in Economics 1994, Faculty of Economics, University of Cambridge.
    32. Fell, Harrison & Kaffine, Daniel T., 2014. "A one-two punch: Joint eects of natural gas abundance and renewables on coal-red power plants," CEnREP Working Papers 340063, North Carolina State University, Department of Agricultural and Resource Economics.
    33. Dario Fauceglia & Andrea Lassmann & Anirudh Shingal & Martin Wermelinger, 2018. "Backward participation in global value chains and exchange rate driven adjustments of Swiss exports," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 154(3), pages 537-584, August.
    34. Aysen Isaoglu, 2010. "Worker Reallocation across Occupations in Western Germany," SOEPpapers on Multidisciplinary Panel Data Research 319, DIW Berlin, The German Socio-Economic Panel (SOEP).
    35. Chrysanthou, Georgios Marios, 2014. "Heterogeneity, Endogeneity, Measurement Error and Identification of the Union Wage Impact," QM&ET Working Papers 14-4, University of Alicante, D. Quantitative Methods and Economic Theory, revised 05 Nov 2014.
    36. 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.
    37. Kufenko, Vadmin & Prettner, Klaus, 2017. "You can't always get what you want? A Monte Carlo analysis of the bias and the efficiency of dynamic panel data estimators," ECON WPS - Working Papers in Economic Theory and Policy 07/2017, TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit.
    38. Christian Almer & Stefan Boes, 2012. "Climate (change) and conflict: resolving a puzzle of association and causation," Diskussionsschriften dp1203, Universitaet Bern, Departement Volkswirtschaft.
    39. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2013. "Evaluating the Role of Individual Specific Heterogeneity in the Relationship Between Subjective Health Assessments and Income," IZA Discussion Papers 7651, Institute of Labor Economics (IZA).

  44. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Improving Estimates of Monotone Functions by Rearrangement," Papers 0704.3686, arXiv.org, revised Nov 2010.

    Cited by:

    1. Daniel J. Henderson & Christopher F. Parmeter, 2009. "Imposing economic constraints in nonparametric regression: survey, implementation, and extension," Advances in Econometrics, in: Nonparametric Econometric Methods, pages 433-469, Emerald Group Publishing Limited.
    2. Holger Dette & Stanislav Volgushev, 2008. "Non‐crossing non‐parametric estimates of quantile curves," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(3), pages 609-627, July.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2008. "Improving Point and Interval Estimates of Monotone Functions by Rearrangement," Papers 0806.4730, arXiv.org, revised Nov 2008.
    4. Andrew Shephard, 2017. "Equilibrium Search And Tax Credit Reform," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(4), pages 1047-1088, November.
    5. Victor Chernozhukov & Iván Fernández-Val & Alfred Galichon, 2010. "Rearranging Edgeworth–Cornish–Fisher expansions," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 42(2), pages 419-435, February.
    6. Henderson, Daniel J. & List, John A. & Millimet, Daniel L. & Parmeter, Christopher F. & Price, Michael K., 2008. "Imposing Monotonicity Nonparametrically in First-Price Auctions," MPRA Paper 8769, University Library of Munich, Germany.
    7. Matthew J. Notowidigdo, 2011. "The Incidence of Local Labor Demand Shocks," NBER Working Papers 17167, National Bureau of Economic Research, Inc.
    8. Birke, Melanie & Bissantz, Nicolai, 2007. "Shape constrained estimators in inverse regression models with convolution-type operator," Technical Reports 2007,35, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    9. Birke, Melanie, 2008. "Shape constrained kernel density estimation," Technical Reports 2008,08, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  45. Ivan Fernandez-Val, 2005. "Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects," Boston University - Department of Economics - Working Papers Series WP2005-38, Boston University - Department of Economics.

    Cited by:

    1. Kruger, Diana I., 2007. "Coffee production effects on child labor and schooling in rural Brazil," Journal of Development Economics, Elsevier, vol. 82(2), pages 448-463, March.
    2. Haruo Iwakura, 2014. "Deriving the Information Bounds for Nonlinear Panel Data Models with Fixed Effects," KIER Working Papers 886, Kyoto University, Institute of Economic Research.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile and probability curves without crossing," CeMMAP working papers CWP10/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Hospido, Laura, 2010. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," IZA Discussion Papers 4712, Institute of Labor Economics (IZA).
    5. Fernández-Val, Iván & Vella, Francis, 2007. "Bias Corrections for Two-Step Fixed Effects Panel Data Estimators," IZA Discussion Papers 2690, Institute of Labor Economics (IZA).
    6. Inmaculada García & José Molina & María Navarro, 2007. "How Satisfied are Spouses with their Leisure Time? Evidence from Europe," Journal of Family and Economic Issues, Springer, vol. 28(4), pages 546-565, December.
    7. Martin Browning & Jesus Carro, 2006. "Heterogeneity and Microeconometrics Modelling," CAM Working Papers 2006-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    8. Manuel Arellano & Jinyong Hahn, 2005. "Understanding Bias in Nonlinear Panel Models: Some Recent Developments," Working Papers wp2005_0507, CEMFI.
    9. Nini, Greg & Smith, David C. & Sufi, Amir, 2009. "Creditor control rights and firm investment policy," Journal of Financial Economics, Elsevier, vol. 92(3), pages 400-420, June.

  46. Ivan Fernandez-Val, 2005. "Bias Correction in Panel Data Models with Individual Specific Parameters," Boston University - Department of Economics - Working Papers Series WP2005-041, Boston University - Department of Economics.

    Cited by:

    1. Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
    2. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
    3. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    4. Fernández-Val, Iván & Vella, Francis, 2007. "Bias Corrections for Two-Step Fixed Effects Panel Data Estimators," IZA Discussion Papers 2690, Institute of Labor Economics (IZA).
    5. Ivan Fernandez-Val, 2005. "Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects," Boston University - Department of Economics - Working Papers Series WP2005-38, Boston University - Department of Economics.
    6. Galvao, Antonio F. & Wang, Liang, 2015. "Efficient minimum distance estimator for quantile regression fixed effects panel data," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 1-26.

  47. Joshua Angrist & Victor Chernozhukov & Ivan Fernandez-Val, 2004. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," NBER Working Papers 10428, National Bureau of Economic Research, Inc.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2009. "Inference on Counterfactual Distributions," Papers 0904.0951, arXiv.org, revised Sep 2013.
    2. Tatsushi Oka & Ken Yamada, 2023. "Heterogeneous Impact of the Minimum Wage: Implications for Changes in Between- and Within-Group Inequality," Journal of Human Resources, University of Wisconsin Press, vol. 58(1), pages 335-362.
    3. Stefan Bache & Christian Dahl & Johannes Kristensen, 2013. "Headlights on tobacco road to low birthweight outcomes," Empirical Economics, Springer, vol. 44(3), pages 1593-1633, June.
    4. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "On the asymptotic theory for least squares series: pointwise and uniform results," CeMMAP working papers 73/13, Institute for Fiscal Studies.
    5. Patrick Kline & Andres Santos, 2013. "Sensitivity to missing data assumptions: Theory and an evaluation of the U.S. wage structure," Quantitative Economics, Econometric Society, vol. 4(2), pages 231-267, July.
    6. Paolo Frumento & Matteo Bottai & Iv'an Fern'andez-Val, 2020. "Parametric Modeling of Quantile Regression Coefficient Functions with Longitudinal Data," Papers 2006.00160, arXiv.org.
    7. Huber, Martin & Melly, Blaise, 2011. "Quantile Regression in the Presence of Sample Selection," Economics Working Paper Series 1109, University of St. Gallen, School of Economics and Political Science.
    8. Lee, Tae-Hwy & Ullah, Aman & Wang, He, 2018. "The second-order bias of quantile estimators," Economics Letters, Elsevier, vol. 173(C), pages 143-147.
    9. Olivier Bargain & Prudence Kwenda, 2014. "The Informal Sector Wage Gap: New Evidence Using Quantile Estimations on Panel Data," Post-Print hal-01474417, HAL.
    10. David M. Kaplan & Matt Goldman, 2016. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri.
    11. 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).
    12. Rahman, Mustafizur & Al-Hasan, Md., 2018. "Returns to Schooling in Bangladesh Revisited: An Instrumental Variable Quantile Regression Approach," Bangladesh Development Studies, Bangladesh Institute of Development Studies (BIDS), vol. 41(02), pages 27-42, June.
    13. Booth, Alison & Arulampalam, Wiji & Bryan, Mark L, 2004. "Are There Asymmetries in the Effects of Training on the Conditional Male Wage Distribution?," CEPR Discussion Papers 4289, C.E.P.R. Discussion Papers.
    14. Wan-Ni Lai & Claire Y. T. Chen & Edward W. Sun, 2022. "Risk factor extraction with quantile regression method," Annals of Operations Research, Springer, vol. 316(2), pages 1543-1572, September.
    15. Franco Peracchi & Andrei V. Tanase, 2008. "On estimating the conditional expected shortfall," CEIS Research Paper 122, Tor Vergata University, CEIS, revised 14 Jul 2008.
    16. Shabbar Jaffry & Yaseen Ghulam & Vyoma Shah, 2007. "Returns to Education in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 46(4), pages 833-852.
    17. Chernozhukov, Victor & Fernández-Val, Iván & Melly, Blaise & Wüthrich, Kaspar, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," University of California at San Diego, Economics Working Paper Series qt5zm6m9rq, Department of Economics, UC San Diego.
    18. Martinez-Sanchis, Elena & Mora, Juan & Kandemir, Ilker, 2012. "Counterfactual distributions of wages via quantile regression with endogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3212-3229.
    19. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
    20. Marilena Furno, 2011. "Goodness of Fit and Misspecification in Quantile Regressions," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 105-131, February.
    21. Suttles, Shellye & Babb, Angela & Knudsen, Daniel C., 2024. "Submitted and Denied: Understanding variation in case status across Supplemental Nutrition assistance program (SNAP) applications," Food Policy, Elsevier, vol. 123(C).
    22. Li, Ming-Yuan Leon, 2009. "Value or volume strategy?," Finance Research Letters, Elsevier, vol. 6(4), pages 210-218, December.
    23. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2023. "Out-of-sample tests for conditional quantile coverage an application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 236(2).
    24. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
    25. Machado, Jose A F & Santos Silva, Joao M C, 2008. "Quantiles for Fractions and Other Mixed Data," Economics Discussion Papers 3550, University of Essex, Department of Economics.
    26. Andini, Corrado, 2017. "Tertiary Education for All and Wage Inequality: Policy Insights from Quantile Regression," IZA Policy Papers 132, Institute of Labor Economics (IZA).
    27. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.
    28. Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
    29. Zhongjun Qu & Jungmo Yoon, 2011. "Nonparametric Estimation and Inference on Conditional Quantile Processes," Boston University - Department of Economics - Working Papers Series WP2011-059, Boston University - Department of Economics.
    30. Juan Carlos Escanciano & Carlos Velasco, 2008. "Specification Tests of Parametric Dynamic Conditional Quantiles," CAEPR Working Papers 2008-021, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    31. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Ivan Fernandez-Val, 2016. "Conditional quantile processes based on series or many regressors," CeMMAP working papers 46/16, Institute for Fiscal Studies.
    32. Pedro Isaac Chavez-Lopez & Tae-Hwy Lee, 2025. "Quantile-Covariance Three-Pass Regression Filter," Working Papers 202501, University of California at Riverside, Department of Economics.
    33. Montes Rojas Gabriel & Alejo Javier & Galvao Antonio & Martínez-Iriarte Julián, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Asociación Argentina de Economía Política: Working Papers 4674, Asociación Argentina de Economía Política.
    34. Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2022. "Weighted-average quantile regression," Papers 2203.03032, arXiv.org.
    35. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers CWP12/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Sasaki, Yuya, 2015. "What Do Quantile Regressions Identify For General Structural Functions?," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1102-1116, October.
    37. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile and probability curves without crossing," CeMMAP working papers CWP10/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    38. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    39. Manuel Arellano & Stéphane Bonhomme, 2015. "Quantile selection models: with an application to understanding changes in wage inequality," CeMMAP working papers CWP75/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    40. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 13/22, Monash University, Department of Econometrics and Business Statistics.
    41. Andy Feng & Georg Graetz, 2015. "Rise of the Machines: The Effects of Labor-Saving Innovations on Jobs and Wages," CEP Discussion Papers dp1330, Centre for Economic Performance, LSE.
    42. 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.
    43. Weifeng Jin, 2023. "Quantile Autoregression-based Non-causality Testing," Papers 2301.02937, arXiv.org.
    44. Escanciano, J.C. & Goh, S.C., 2014. "Specification analysis of linear quantile models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 495-507.
    45. Samantha Leorato & Franco Peracchi, 2015. "Comparing Distribution and Quantile Regression," EIEF Working Papers Series 1511, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    46. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    47. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    48. Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2016. "IV Quantile Regression for Group‐Level Treatments, With an Application to the Distributional Effects of Trade," Econometrica, Econometric Society, vol. 84, pages 809-833, March.
    49. Klaus Friesenbichler, 2014. "EU Accession, Domestic Market Competition and Total Factor Productivity. Firm Level Evidence," WIFO Working Papers 492, WIFO.
    50. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Kato, Kengo, 2015. "Some new asymptotic theory for least squares series: Pointwise and uniform results," Journal of Econometrics, Elsevier, vol. 186(2), pages 345-366.
    51. Mateut, Simona & Chevapatrakul, Thanaset, 2018. "Customer financing, bargaining power and trade credit uptake," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 147-162.
    52. 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.
    53. Arie Beresteanu, 2020. "Quantile Regression with Interval Data," Working Paper 6899, Department of Economics, University of Pittsburgh.
    54. Stacy, Brian, 2014. "Left with Bias? Quantile Regression with Measurement Error in Left Hand Side Variables," EconStor Preprints 104744, ZBW - Leibniz Information Centre for Economics.
    55. Boudarbat, Brahim & Lemieux, Thomas & Riddell, Craig, 2008. "The Evolution of the Returns to Human Capital in Canada, 1980-2006," Economics working papers craig_riddell-2008-15, Vancouver School of Economics, revised 22 Oct 2008.
    56. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    57. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    58. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference for high-dimensional sparse econometric models," CeMMAP working papers CWP41/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    59. Du, Zaichao & Escanciano, Juan Carlos & Zhu, Guangwei, 2023. "The case for CASE: Estimating heterogeneous systemic effects," Journal of Banking & Finance, Elsevier, vol. 157(C).
    60. Manuel Landajo & Javier De Andrés & Pedro Lorca, 2008. "Measuring firm performance by using linear and non‐parametric quantile regressions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(2), pages 227-250, April.
    61. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    62. Bernd Fitzenberger & Karsten Kohn & Alexander C. Lembcke, 2008. "Union Density and Varieties of Coverage: The Anatomy of Union Wage Effects in Germany," CEP Discussion Papers dp0859, Centre for Economic Performance, LSE.
    63. Ruosha Li & Limin Peng, 2017. "Assessing quantile prediction with censored quantile regression models," Biometrics, The International Biometric Society, vol. 73(2), pages 517-528, June.
    64. Pendakur, Krishna & Woodcock, Simon D., 2009. "Glass Ceilings or Glass Doors? Wage Disparity Within and Between Firms," IZA Discussion Papers 4626, Institute of Labor Economics (IZA).
    65. Adelino, Manuel & Dinc, I. Serdar, 2014. "Corporate distress and lobbying: Evidence from the Stimulus Act," Journal of Financial Economics, Elsevier, vol. 114(2), pages 256-272.
    66. Clément de Chaisemartin, 2012. "Fuzzy differences in differences," PSE Working Papers halshs-00671368, HAL.
    67. Leorato, Samantha & Peracchi, Franco & Tanase, Andrei V., 2012. "Asymptotically efficient estimation of the conditional expected shortfall," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 768-784.
    68. 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.
    69. Wang, Xichen & Duan, Xiaomei, 2024. "What leads some countries to experience larger decreases in foreign flows during low-flow episodes? Evidence from international portfolio flows," Journal of International Money and Finance, Elsevier, vol. 148(C).
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    209. Yu-Yen Ku & Tze-Yu Yen, 2016. "Heterogeneous Effect of Financial Leverage on Corporate Performance: A Quantile Regression Analysis of Taiwanese Companies," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-33, September.
    210. Schlüter, Tobias & Sievers, Sönke & Hartmann-Wendels, Thomas, 2012. "How can banks effectively stabilize their retail customers saving behavior? The impact of contractual rewards on saving persistence and cash flow volatility," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62057, Verein für Socialpolitik / German Economic Association.
    211. Andreas Behr & Ulrich Pötter, 2009. "Analysing Wage Differences between the USA and Germany Using Proportional Hazards Models," LABOUR, CEIS, vol. 23(2), pages 319-347, June.

  48. I. Fernandez-Val & J. Angrist & V. Chernozhukov, 2004. "Quantile Regression under Misspecification," Econometric Society 2004 North American Winter Meetings 198, Econometric Society.

    Cited by:

    1. Booth, Alison & Arulampalam, Wiji & Bryan, Mark L, 2004. "Are There Asymmetries in the Effects of Training on the Conditional Male Wage Distribution?," CEPR Discussion Papers 4289, C.E.P.R. Discussion Papers.
    2. Bernd Fitzenberger & Karsten Kohn & Alexander C. Lembcke, 2008. "Union Density and Varieties of Coverage: The Anatomy of Union Wage Effects in Germany," CEP Discussion Papers dp0859, Centre for Economic Performance, LSE.
    3. Taisuke Otsu, 2009. "RESET for quantile regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 381-391, August.
    4. Juergen Jung & Michael Makowsky, 2014. "The determinants of federal and state enforcement of workplace safety regulations: OSHA inspections 1990–2010," Journal of Regulatory Economics, Springer, vol. 45(1), pages 1-33, February.
    5. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, vol. 142(1), pages 379-398, January.

  49. Victor Chernozhukov & Ivan Fernandez-Val & Amanda E. Kowalski, "undated". "Censored Quantile Instrumental Variable Estimation via Control Functions," Boston University - Department of Economics - Working Papers Series wp2009-012, Boston University - Department of Economics.

    Cited by:

    1. Pravin K. Trivedi, 2010. "Keynote lecture: Estimation of count-data panel models," Mexican Stata Users' Group Meetings 2010 06, Stata Users Group.
    2. Diego Ubfal, 2013. "How General Are Time Preferences? Eliciting Good-Specific Discount Rates," Working Papers 473, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Kwak, Sungil, 2011. "The Impact of Taxes on Charitable Giving: Empirical Evidence from the Korean Labor and Income Panel Study," MPRA Paper 36845, University Library of Munich, Germany.

  50. V. Chernozhukov & Ivan Fernandez-Val, "undated". "Quantile and Average Effects in Nonseparable Panel Models," Boston University - Department of Economics - Working Papers Series wp2009-011, Boston University - Department of Economics.

    Cited by:

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

Articles

  1. Chernozhukov, Victor & Fernández-Val, Iván & Weidner, Martin, 2024. "Network and panel quantile effects via distribution regression," Journal of Econometrics, Elsevier, vol. 240(2).
    See citations under working paper version above.
  2. Fernández-Val, Ivan & van Vuuren, Aico & Vella, Francis, 2024. "Nonseparable sample selection models with censored selection rules," Journal of Econometrics, Elsevier, vol. 240(2).
    See citations under working paper version above.
  3. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly, 2022. "Fast algorithms for the quantile regression process," Empirical Economics, Springer, vol. 62(1), pages 7-33, January.

    Cited by:

    1. Cuesta, Lizeth & Ruiz, Yomara, 2021. "Efecto de la globalización sobre la desigualdad. Un estudio global para 104 países usando regresiones cuantílicas [Effect of globalization on inequality. A global study for 104 countries using quan," MPRA Paper 111022, University Library of Munich, Germany.
    2. Canavire Bacarreza, Gustavo J. & Rios-Avila, Fernando & Sacco-Capurro, Flavia, 2023. "Recovering Income Distribution in the Presence of Interval-Censored Data," IZA Discussion Papers 15921, Institute of Labor Economics (IZA).
    3. Wang, Xiuhua & Wang, Yipeng & Zhao, Yaxiong, 2022. "Financial permeation and rural poverty reduction Nexus: Further insights from counties in China," China Economic Review, Elsevier, vol. 76(C).
    4. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2023. "Expecting the unexpected: Stressed scenarios for economic growth," Working Papers 202314, University of California at Riverside, Department of Economics.
    5. Santiago Pereda-Fern'andez, 2024. "Fast Algorithms for Quantile Regression with Selection," Papers 2402.16693, arXiv.org.
    6. EunYi Chung & Mauricio Olivares, 2025. "Quantile‐Based Test for Heterogeneous Treatment Effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 3-17, January.
    7. Ana María Iregui-Bohórquez & María Teresa Ramírez-Giraldo & Ligia Alba Melo-Becerra & Jorge Leonardo Rodríguez-Arenas, 2025. "De la cobertura al desempeño: Explorando las brechas de género en el sistema educativo colombiano," Borradores de Economia 1301, Banco de la Republica de Colombia.
    8. Ignacio Garr'on & C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "International vulnerability of inflation," Papers 2410.20628, arXiv.org, revised Oct 2024.
    9. Garrón Vedia, Ignacio & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2024. "International vulnerability of inflation," DES - Working Papers. Statistics and Econometrics. WS 44814, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Rukundo, Emmanuel Nshakira & Schroeder, Sarah & Hisarciklilar, Mehtap & McKay, Andrew D., 2024. "Health insurance premium changes and labor supply: Evidence from a low-income country," Ruhr Economic Papers 1103, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    11. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2022. "Fast Inference for Quantile Regression with Tens of Millions of Observations," Papers 2209.14502, arXiv.org, revised Oct 2023.
    12. Borgen, Nicolai T. & Haupt, Andreas & Wiborg, Øyvind N., 2021. "Flexible and fast estimation of quantile treatment effects: The rqr and rqrplot commands," SocArXiv 4vquh, Center for Open Science.

  4. Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
    See citations under working paper version above.
  5. Paolo Frumento & Matteo Bottai & Iván Fernández-Val, 2021. "Parametric Modeling of Quantile Regression Coefficient Functions With Longitudinal Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(534), pages 783-797, April.

    Cited by:

    1. Viviana Carcaiso & Leonardo Grilli, 2023. "Quantile regression for count data: jittering versus regression coefficients modelling in the analysis of credits earned by university students after remote teaching," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(4), pages 1061-1082, October.
    2. Sottile, Gianluca & Frumento, Paolo, 2022. "Robust estimation and regression with parametric quantile functions," Computational Statistics & Data Analysis, Elsevier, vol. 171(C).
    3. Rong Jiang & Siu Kai Choy & Keming Yu, 2024. "Non‐crossing quantile double‐autoregression for the analysis of streaming time series data," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(4), pages 513-532, July.
    4. Gao, Suhao & Yu, Zhen, 2023. "Parametric expectile regression and its application for premium calculation," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 242-256.
    5. Hao, Meiling & Lin, Yuanyuan & Shen, Guohao & Su, Wen, 2023. "Nonparametric inference on smoothed quantile regression process," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    6. S. Ghasemzadeh & M. Ganjali & T. Baghfalaki, 2022. "Quantile regression via the EM algorithm for joint modeling of mixed discrete and continuous data based on Gaussian copula," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1181-1202, December.

  6. Hugo Freeman & Martin Weidner, 2021. "Low-rank approximations of nonseparable panel models," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 40-77.
    See citations under working paper version above.
  7. Victor Chernozhukov & Iván Fernández‐Val & Whitney Newey & Sami Stouli & Francis Vella, 2020. "Semiparametric estimation of structural functions in nonseparable triangular models," Quantitative Economics, Econometric Society, vol. 11(2), pages 503-533, May.
    See citations under working paper version above.
  8. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly & Kaspar Wüthrich, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 123-137, January.
    See citations under working paper version above.
  9. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Fernández-Val, Iván, 2019. "Conditional quantile processes based on series or many regressors," Journal of Econometrics, Elsevier, vol. 213(1), pages 4-29.
    See citations under working paper version above.
  10. Shuowen Chen & Victor Chernozhukov & Iván Fernández-Val, 2019. "Mastering Panel Metrics: Causal Impact of Democracy on Growth," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 77-82, May.
    See citations under working paper version above.
  11. Victor Chernozhukov & Ivan Fernández-Val & Sukjin Han & Amanda Kowalski, 2019. "Censored quantile instrumental-variable estimation with Stata," Stata Journal, StataCorp LLC, vol. 19(4), pages 768-781, December.
    See citations under working paper version above.
  12. Chernozhukov, Victor & Fernández-Val, Iván & Newey, Whitney K., 2019. "Nonseparable multinomial choice models in cross-section and panel data," Journal of Econometrics, Elsevier, vol. 211(1), pages 104-116.
    See citations under working paper version above.
  13. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
    See citations under working paper version above.
  14. Victor Chernozhukov & Iván Fernández‐Val & Ye Luo, 2018. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Econometrica, Econometric Society, vol. 86(6), pages 1911-1938, November.
    See citations under working paper version above.
  15. Mario Cruz-Gonzalez & Iván Fernández-Val & Martin Weidner, 2017. "Bias corrections for probit and logit models with two-way fixed effects," Stata Journal, StataCorp LLC, vol. 17(3), pages 517-545, September.
    See citations under working paper version above.
  16. A. Belloni & V. Chernozhukov & I. Fernández‐Val & C. Hansen, 2017. "Program Evaluation and Causal Inference With High‐Dimensional Data," Econometrica, Econometric Society, vol. 85, pages 233-298, January.
    See citations under working paper version above.
  17. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2017. "Evaluating the role of income, state dependence and individual specific heterogeneity in the determination of subjective health assessments," Economics & Human Biology, Elsevier, vol. 25(C), pages 85-98.

    Cited by:

    1. Chris Muris & Pedro Raposo & Sotiris Vandoros, 2020. "A dynamic ordered logit model with fixed effects," Papers 2008.05517, arXiv.org.
    2. Nesson, Erik T. & Robinson, Joshua J., 2019. "On the measurement of health and its effect on the measurement of health inequality," Economics & Human Biology, Elsevier, vol. 35(C), pages 207-221.
    3. Bo E. Honoré & Chris Muris & Martin Weidner, 2021. "Dynamic Ordered Panel Logit Models," Working Papers 2021-14, Princeton University. Economics Department..

  18. Fernández-Val, Iván & Weidner, Martin, 2016. "Individual and time effects in nonlinear panel models with large N, T," Journal of Econometrics, Elsevier, vol. 192(1), pages 291-312.
    See citations under working paper version above.
  19. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
    See citations under working paper version above.
  20. Chernozhukov, Victor & Fernández-Val, Iván & Hoderlein, Stefan & Holzmann, Hajo & Newey, Whitney, 2015. "Nonparametric identification in panels using quantiles," Journal of Econometrics, Elsevier, vol. 188(2), pages 378-392.
    See citations under working paper version above.
  21. Adam Ashcraft & Iván Fernández‐Val & Kevin Lang, 2013. "The Consequences of Teenage Childbearing: Consistent Estimates When Abortion Makes Miscarriage Non‐random," Economic Journal, Royal Economic Society, vol. 123, pages 875-905, September.

    Cited by:

    1. Gunes, Pinar Mine & Tsaneva, Magda, 2020. "The effects of teenage childbearing on education, physical health, and mental distress: evidence from Mexico," Journal of Demographic Economics, Cambridge University Press, vol. 86(2), pages 183-206, June.
    2. Grönqvist, Hans & Hall, Caroline, 2011. "Education policy and early fertility: Lessons from an expansion of upper secondary schooling," Working Paper Series, Center for Labor Studies 2011:20, Uppsala University, Department of Economics.
    3. Angelini, Viola & Mierau, Joachim, 2017. "Late-life Health Effects of Teenage Motherhood," Research Report 17002-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    4. Fletcher, Jason M. & Polos, Jessica, 2017. "Nonmarital and Teen Fertility," IZA Discussion Papers 10833, Institute of Labor Economics (IZA).
    5. Bütikofer, Aline & Coy, Deirdre & Doyle, Orla & Ginja, Rita, 2024. "The Consequences of Miscarriage on Parental Investments," CEPR Discussion Papers 18949, C.E.P.R. Discussion Papers.
    6. Matias Berthelon & Diana I. Kruger, 2017. "Does adolescent motherhood affect education and labor market outcomes of mothers? A study on young adult women in Chile during 1990–2013," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 62(2), pages 293-303, March.
    7. Christina J. Diaz & Jeremy E. Fiel, 2016. "The Effect(s) of Teen Pregnancy: Reconciling Theory, Methods, and Findings," Demography, Springer;Population Association of America (PAA), vol. 53(1), pages 85-116, February.
    8. Demir, Firat & Ghosh, Pallab & Liu, Zexuan, 2020. "Effects of motherhood timing, breastmilk substitutes and education on the duration of breastfeeding: Evidence from Egypt," World Development, Elsevier, vol. 133(C).
    9. Devon Gorry, 2019. "Heterogeneous Consequences of Teenage Childbearing," Demography, Springer;Population Association of America (PAA), vol. 56(6), pages 2147-2168, December.
    10. Andrea M. Kelly & Jason M. Lindo & Analisa Packham, 2019. "The Power of the IUD: Effects of Expanding Access to Contraception Through Title X Clinics," NBER Working Papers 25656, National Bureau of Economic Research, Inc.
    11. Nuevo-Chiquero, Ana, 2014. "The labor force effects of unplanned childbearing," Labour Economics, Elsevier, vol. 29(C), pages 91-101.
    12. Eva Rye Johansen & Helena Skyt Nielsen & Mette Verner, 2024. "Teenage mothers and the next generation: benefits of delay?," Review of Economics of the Household, Springer, vol. 22(2), pages 451-476, June.
    13. Cioffi, Camille C. & Schweer-Collins, Maria L. & Leve, Leslie D., 2022. "Pregnancy and miscarriage predict suicide attempts but not substance use among dual-systems involved female adolescents," Children and Youth Services Review, Elsevier, vol. 137(C).
    14. Simen Markussen & Marte Strøm, 2022. "Children and labor market outcomes: separating the effects of the first three children," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(1), pages 135-167, January.
    15. Melissa Schettini Kearney & Phillip B. Levine, 2011. "Income Inequality and Early Non-Marital Childbearing: An Economic Exploration of the "Culture of Despair"," NBER Working Papers 17157, National Bureau of Economic Research, Inc.
    16. Deza, Monica, 2019. "Graduated driver licensing and teen fertility," Economics & Human Biology, Elsevier, vol. 35(C), pages 51-62.
    17. Thiemo Fetzer & Oliver Pardo & Amar Shanghavi, 2013. "An Urban Legend?! Power Rationing, Fertility and its Effects on Mothers," CEP Discussion Papers dp1247, Centre for Economic Performance, LSE.
    18. Jones, Kelly M. & Pineda-Torres, Mayra, 2024. "TRAP’d Teens: Impacts of abortion provider regulations on fertility & education," Journal of Public Economics, Elsevier, vol. 234(C).
    19. Rachel Heath & A. Mushfiq Mobarak, 2014. "Manufacturing Growth and the Lives of Bangladeshi Women," NBER Working Papers 20383, National Bureau of Economic Research, Inc.
    20. Phillip B. Levine, 2014. "Teenage childbearing and labor market implications for women," IZA World of Labor, Institute of Labor Economics (IZA), pages 1-28, July.
    21. Melissa S. Kearney & Phillip B. Levine, 2012. "Why Is the Teen Birth Rate in the United States So High and Why Does It Matter?," Journal of Economic Perspectives, American Economic Association, vol. 26(2), pages 141-163, Spring.
    22. Nizalova, Olena Y. & Sliusarenko, Tamara & Shpak, Solomiya, 2016. "The motherhood wage penalty in times of transition," Journal of Comparative Economics, Elsevier, vol. 44(1), pages 56-75.
    23. Rodrigo Ceni & Cecilia Parada & Ivone Perazzo & Eliana Sena, 2020. "Birth Collapse and Long-Acting Reversible Contraceptive Policies," Documentos de Trabajo (working papers) 20-14, Instituto de Economía - IECON.
    24. Mølland, Eirin, 2016. "Benefits from delay? The effect of abortion availability on young women and their children," Labour Economics, Elsevier, vol. 43(C), pages 6-28.
    25. Hande Inanc & Ariella Spitzer & Brian Goesling, "undated". "Assessing the Benefits of the Success Sequence for Economic Self-Sufficiency and Family Stability," Mathematica Policy Research Reports c812f6cb5ece40df8265d7eaa, Mathematica Policy Research.
    26. Fetzer, Thiemo & Pardo, Oliver & Shanghavi, Amar, 2016. "More than an Urban Legend: The long-term socioeconomic effects of unplanned fertility shocks," CAGE Online Working Paper Series 284, Competitive Advantage in the Global Economy (CAGE).
    27. Rosenbaum, Philip, 2020. "Does early childbearing matter? New approach using Danish register data," Labour Economics, Elsevier, vol. 65(C).
    28. Lisa Schulkind & Danielle H. Sandler, 2019. "The Timing of Teenage Births: Estimating the Effect on High School Graduation and Later-Life Outcomes," Demography, Springer;Population Association of America (PAA), vol. 56(1), pages 345-365, February.
    29. Markussen, Simen & Strøm, Marte, 2015. "The Effects of Motherhood," Memorandum 19/2015, Oslo University, Department of Economics.
    30. Heiland, Frank & Korenman, Sanders & Smith, Rachel A., 2019. "Estimating the educational consequences of teenage childbearing: Identification, heterogeneous effects and the value of biological relationship information," Economics & Human Biology, Elsevier, vol. 33(C), pages 15-28.
    31. Steinhauer, Andreas & Bíró, Anikó & Dieterle, Steven, 2019. "Motherhood Timing and the Child Penalty: Bounding the Returns to Delay," CEPR Discussion Papers 13732, C.E.P.R. Discussion Papers.
    32. Dana Rotz & Brian Goesling & Hande Inanc & Gregory Chojnacki, "undated". "Economic Benefits of Delayed Sexual Activity," Mathematica Policy Research Reports 248b878cd4254142ac8c13102, Mathematica Policy Research.
    33. Devon Gorry, 2023. "Consequences of Teenage Childbearing on Child Outcomes in the United States," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(1), pages 225-254, January.
    34. Luca, Dara Lee & Stevens, Jack & Rotz, Dana & Goesling, Brian & Lutz, Robyn, 2021. "Evaluating teen options for preventing pregnancy: Impacts and mechanisms," Journal of Health Economics, Elsevier, vol. 77(C).
    35. Basu, Shubhashrita & Gorry, Devon, 2021. "Consequences of teenage childbearing on child health," Economics & Human Biology, Elsevier, vol. 42(C).
    36. Bahadır Dursun & Resul Cesur & Inas R. Kelly, 2022. "Mandatory Schooling of Girls Improved Their Children's Health: Evidence from Turkey's 1997 Education Reform," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(3), pages 824-858, June.
    37. Andrew Beauchamp, 2016. "Abortion Costs, Separation, and Non-marital Childbearing," Journal of Family and Economic Issues, Springer, vol. 37(2), pages 182-196, June.
    38. Pan, Zheng & Jiang, Xiandeng & Zhao, Ningru, 2021. "Does birth spacing affect female labor market participation? Evidence from urban China," China Economic Review, Elsevier, vol. 68(C).
    39. Jason Fletcher & Norma Padrón, 2016. "The effects of teenage childbearing on adult soft skills development," Journal of Population Economics, Springer;European Society for Population Economics, vol. 29(3), pages 883-910, July.
    40. Herrera Catalina & E. Sahn David, 2017. "Working Paper 281 - Early Childbearing, School Attainment and Cognitive Skills," Working Paper Series 2398, African Development Bank.
    41. Kevin Lang & Russell Weinstein, 2013. "The Consequences of Teenage Childbearing Before Roe v Wade," NBER Working Papers 19627, National Bureau of Economic Research, Inc.
    42. Philip Verwimp, 2016. "Secondary School as a Contraceptive: Quasi-Experimental Evidence from Burundi," Working Papers ECARES ECARES 2016-19, ULB -- Universite Libre de Bruxelles.
    43. Martin Foureaux Koppensteiner & Jesse Matheson, 2016. "Access to education and teenage childbearing," Discussion Papers in Economics 16/15, Division of Economics, School of Business, University of Leicester.
    44. Poh Lin Tan, 2017. "The impact of school entry laws on female education and teenage fertility," Journal of Population Economics, Springer;European Society for Population Economics, vol. 30(2), pages 503-536, April.
    45. Thiemo Fetzer & Oliver Pardo & Amar Shanghavi, 2018. "More than an urban legend: the short- and long-run effects of unplanned fertility shocks," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(4), pages 1125-1176, October.
    46. Martin Foureaux Koppensteiner & Jesse Matheson, 2016. "Access to Education and Teenage Pregnancy," CINCH Working Paper Series 1604, Universitaet Duisburg-Essen, Competent in Competition and Health, revised Aug 2016.
    47. Eva Rye Johansen & Helena Skyt Nielsen & Mette Verner, 2018. "Long-term Consequences of Early Parenthood," Economics Working Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    48. Guldi, Melanie, 2016. "Title IX and the education of teen mothers," Economics of Education Review, Elsevier, vol. 55(C), pages 103-116.
    49. Catalina Herrera Almanza & David E. Sahn, 2018. "Early Childbearing, School Attainment, and Cognitive Skills: Evidence From Madagascar," Demography, Springer;Population Association of America (PAA), vol. 55(2), pages 643-668, April.
    50. Berthelon, Matias & Kruger, Diana, 2014. "The Impact of Adolescent Motherhood on Education in Chile," IZA Discussion Papers 8072, Institute of Labor Economics (IZA).

  22. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    See citations under working paper version above.
  23. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
    See citations under working paper version above.
  24. Iván Fernández‐Val & Joonhwah Lee, 2013. "Panel data models with nonadditive unobserved heterogeneity: Estimation and inference," Quantitative Economics, Econometric Society, vol. 4(3), pages 453-481, November.
    See citations under working paper version above.
  25. Fernández-Val, Iván & Vella, Francis, 2011. "Bias corrections for two-step fixed effects panel data estimators," Journal of Econometrics, Elsevier, vol. 163(2), pages 144-162, August.
    See citations under working paper version above.
  26. Victor Chernozhukov & Iván Fernández-Val, 2011. "Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(2), pages 559-589.
    See citations under working paper version above.
  27. Victor Chernozhukov & Iván Fernández-Val & Alfred Galichon, 2010. "Rearranging Edgeworth–Cornish–Fisher expansions," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 42(2), pages 419-435, February.
    See citations under working paper version above.
  28. Victor Chernozhukov & Iv·n Fern·ndez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves Without Crossing," Econometrica, Econometric Society, vol. 78(3), pages 1093-1125, May.
    See citations under working paper version above.
  29. V. Chernozhukov & I. Fernández-Val & A. Galichon, 2009. "Improving point and interval estimators of monotone functions by rearrangement," Biometrika, Biometrika Trust, vol. 96(3), pages 559-575.
    See citations under working paper version above.
  30. Fernández-Val, Iván, 2009. "Fixed effects estimation of structural parameters and marginal effects in panel probit models," Journal of Econometrics, Elsevier, vol. 150(1), pages 71-85, May.
    See citations under working paper version above.
  31. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    See citations under working paper version above.
  32. Iván Fernández Val, 2003. "Household labor supply: evidence for Spain," Investigaciones Economicas, Fundación SEPI, vol. 27(2), pages 239-275, May.

    Cited by:

    1. Vela Espiago, Santiago, 2023. "Diferencias intrafamiliares en la oferta de trabajo: evidencia empírica para el caso de Reino Unido [Intrahousehold labor supply differences: Empirical evidence for the UK]," MPRA Paper 117342, University Library of Munich, Germany.
    2. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2014. "Comparing Labor Supply Elasticities in Europe and the United States: New Results," Post-Print hal-01463097, HAL.
    3. GholamReza Haddad, 2015. "Gender ratio, divorce rate, and intra-household collective decision process: evidence from iranian urban households labor supply with non-participation," Empirical Economics, Springer, vol. 48(4), pages 1365-1394, June.
    4. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2011. "Labor Supply Elasticities in Europe and the US," Working Papers 201114, School of Economics, University College Dublin.
    5. Pérez Mínguez, José Antonio, 2022. "Oferta laboral en Gran Bretaña: Un enfoque colectivo [Job supply in Great Britain: A collective approach]," MPRA Paper 112743, University Library of Munich, Germany.
    6. Ainhoa Herrarte & Julián Moral-Carcedo & Felipe Sáez, 2012. "The impact of childbirth on Spanish women’s decisions to leave the labor market," Review of Economics of the Household, Springer, vol. 10(3), pages 441-468, September.
    7. Tiago V. De V. Cavalcanti & José Tavares, 2011. "Women Prefer Larger Governments: Growth, Structural Transformation, And Government Size," Economic Inquiry, Western Economic Association International, vol. 49(1), pages 155-171, January.
    8. Laura Crespo, 2005. "Estimation And Testing Of Household Labour Supply Models: Evidence From Spain," Working Papers. Serie AD 2005-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    9. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2012. "Comparing Labor Supply Elasticities in Europe and the US: New Results," Working Papers halshs-00805736, HAL.

Software components

  1. Victor Chernozhukov & Ivan Fernandez-Val & Sukjin Han & Amanda Kowalski, 2012. "CQIV: Stata module to perform censored quantile instrumental variables regression," Statistical Software Components S457478, Boston College Department of Economics, revised 25 Sep 2019.

    Cited by:

    1. Melstrom, Richard T. & Jayasekera, Deshamithra H.W., 2016. "Two-Stage Estimation to Control for Unobservables in a Recreation Demand Model with Unvisited Sites," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236252, Agricultural and Applied Economics Association.
    2. Mendolia, Silvia & Paloyo, Alfredo R. & Walker, Ian, 2016. "Heterogeneous Effects of High School Peers on Educational Outcomes," IZA Discussion Papers 9795, Institute of Labor Economics (IZA).
    3. Gabrielle Fack & Camille Landais, 2016. "The effect of tax enforcement on tax elasticities: Evidence from charitable contributions in France," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01300122, HAL.
    4. Martin Falk & Eva Hagsten, 2014. "Output growth and prices of establishments in the Swedish lodging industry," ERSA conference papers ersa14p360, European Regional Science Association.
    5. Broberg, Thomas & Kazukauskas, Andrius, 2014. "Inefficiencies in residential use of energy - A critical overview of literature and energy efficiency policies in EU and Sweden," CERE Working Papers 2014:7, CERE - the Center for Environmental and Resource Economics.
    6. Sven Neelsen & Owen O'Donnell, 2017. "Progressive universalism? The impact of targeted coverage on health care access and expenditures in Peru," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 179-203, December.
    7. Kiran Krishnamurthy, Chandra & Kriström, Bengt, 2013. "Determinants of the price-premium for Green Energy: Evidence from an OECD cross-section," CERE Working Papers 2013:7, CERE - the Center for Environmental and Resource Economics, revised 30 Jun 2014.
    8. Michael J. Peel, 2014. "Addressing unobserved endogeneity bias in accounting studies: control and sensitivity methods by variable type," Accounting and Business Research, Taylor & Francis Journals, vol. 44(5), pages 545-571, October.

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