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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. 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.

  2. 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. Anish Agarwal & Vasilis Syrgkanis, 2022. "Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime," Papers 2210.11003, arXiv.org.
    2. Anish Agarwal & Munther Dahleh & Devavrat Shah & Dennis Shen, 2021. "Causal Matrix Completion," Papers 2109.15154, arXiv.org.
    3. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    4. 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.
    5. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    6. 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.
    7. Hugo Freeman, 2022. "Linear Multidimensional Regression with Interactive Fixed-Effects," Papers 2209.11691, arXiv.org, revised Mar 2025.

  3. 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.

  4. 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. 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.
    2. Hryshko, Dmytro & Manovskii, Iourii, 2022. "How much consumption insurance in the U.S.?," Journal of Monetary Economics, Elsevier, vol. 130(C), pages 17-33.
    3. Victor Chernozhukov & Hiroyuki Kasahara & Paul Schrimpf, 2020. "Causal impact of masks, policies, behavior on early COVID-19 pandemic in the U.S," CeMMAP working papers CWP24/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Taylor, Alan M. & Dube, Arindrajit & Girardi, Daniele & Jordà , Òscar, 2023. "A Local Projections Approach to Difference-in-Differences Event Studies," CEPR Discussion Papers 18141, C.E.P.R. Discussion Papers.
    5. Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org.
    6. Mountford, Andrew, 2022. "Economic Growth Analysis When Balanced Growth Paths May Be Time Varying," MPRA Paper 114249, University Library of Munich, Germany.
    7. Andrew Chia, 2021. "Automatically Differentiable Random Coefficient Logistic Demand Estimation," Papers 2106.04636, arXiv.org.
    8. Christoph Doerffel & Peter Draper & Andreas Freytag & Sebastian Schuhmann, 2021. "Drivers of Inclusive Development: An Empirical Investigation," Jena Economics Research Papers 2021-015, Friedrich-Schiller-University Jena.
    9. 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.
    10. Fontanari, Claudia, 2024. "The role of wages in triggering innovation and productivity: A dynamic exploration for European economies," Economic Modelling, Elsevier, vol. 130(C).

  5. 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. 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.
    2. 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).

  6. 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. 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.
    2. Peter Neary & Céline Carrère & Monika Mrázová, 2020. "Gravity without Apology: The Science of Elasticities, Distance, and Trade," Economics Series Working Papers 904, University of Oxford, Department of Economics.
    3. 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).
    4. 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).
    5. 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.
    6. 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.
    7. 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.
    8. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2022. "Bivariate Distribution Regression with Application to Insurance Data," Papers 2203.12228, arXiv.org, revised Sep 2023.
    9. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2023. "Distributional Vector Autoregression: Eliciting Macro and Financial Dependence," Papers 2303.04994, arXiv.org.
    10. Nathan Kallus & Miruna Oprescu, 2022. "Robust and Agnostic Learning of Conditional Distributional Treatment Effects," Papers 2205.11486, arXiv.org, revised Feb 2023.
    11. 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).
    12. 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.
    13. 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.

  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 CWP48/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Westphal, Matthias & Kamhöfer, Daniel A. & Schmitz, Hendrik, 2020. "Marginal college wage premiums under selection into employment," Ruhr Economic Papers 855, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. 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.
    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.
    5. 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).
    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 & 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. Wunsch, Conny & Strittmatter, Anthony, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," CEPR Discussion Papers 15840, C.E.P.R. Discussion Papers.
    2. Liu, Ruixuan & Yu, Zhengfei, 2022. "Sample selection models with monotone control functions," Journal of Econometrics, Elsevier, vol. 226(2), pages 321-342.
    3. Dominik Wied, 2022. "Semiparametric Distribution Regression with Instruments and Monotonicity," Papers 2212.03704, arXiv.org.
    4. Miguel A Delgado & Andrés García-Suaza & Pedro H C Sant’Anna, 2022. "Distribution regression in duration analysis: an application to unemployment spells [Lecture notes in statistics: Proceedings]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 675-698.

  9. 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. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. 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.
    3. De Neve, Jan-Emmanuel & Imbert, Clement & Spinnewijn, Johannes & Tsankova, Teodora & Luts, Maarten, 2020. "How to Improve Tax Compliance? Evidence from Population-wide Experiments in Belgium," CAGE Online Working Paper Series 458, Competitive Advantage in the Global Economy (CAGE).
    4. Daniel Jacob, 2021. "CATE meets ML," Digital Finance, Springer, vol. 3(2), pages 99-148, June.
    5. Odran Bonnet & Etienne Fize & Tristan Loisel & Lionel Wilner, 2024. "Compensation against fuel inflation: Temporary tax rebates or transfers?," Working Papers 2024-05, Center for Research in Economics and Statistics.
    6. 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.
    7. Abhijit Banerjee & Emily Breza & Esther Duflo & Cynthia Kinnan, 2019. "Can Microfinance Unlock a Poverty Trap for Some Entrepreneurs?," Discussion Papers Series, Department of Economics, Tufts University 0832, Department of Economics, Tufts University.
    8. Sendhil Mullainathan & Ashesh Rambachan, 2024. "From Predictive Algorithms to Automatic Generation of Anomalies," Papers 2404.10111, arXiv.org.
    9. 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.
    10. Stefano Piasenti & Marica Valente & Roel van Veldhuizen & Gregor Pfeifer & Gregor-Gabriel Pfeifer, 2023. "Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions," CESifo Working Paper Series 10572, CESifo.
    11. Elek, Péter & Bíró, Anikó, 2021. "Regional differences in diabetes across Europe – regression and causal forest analyses," Economics & Human Biology, Elsevier, vol. 40(C).
    12. 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".
    13. 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.
    14. 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.
    15. Pedro Forquesato, 2022. "Who Benefits from Political Connections in Brazilian Municipalities," Papers 2204.09450, arXiv.org.
    16. 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.
    17. 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.
    18. Ubfal, Diego, 2024. "What Works in Supporting Women-Led Businesses?," IZA Discussion Papers 16950, Institute of Labor Economics (IZA).
    19. Jeffrey G. Shrader & Laura Bakkensen & Derek Lemoine, 2023. "Fatal Errors: The Mortality Value of Accurate Weather Forecasts," Working Papers 23-30, Center for Economic Studies, U.S. Census Bureau.
    20. Strittmatter, Anthony, 2019. "What is the Value Added by using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203499, Verein für Socialpolitik / German Economic Association.
    21. Sandrine Mesplé-Somps and & Björn Nilsson, 2020. "Role models and migration intentions," Working Paper 519bfbde-8d2e-4e86-bd62-0, Agence française de développement.
    22. 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.
    23. A. 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," CSAE Working Paper Series 2020-20, Centre for the Study of African Economies, University of Oxford.
    24. 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.
    25. Simon Briole & Augustin Colette & Emmanuelle Lavaine, 2023. "The Heterogeneous Effects of Lockdown Policies on Air Pollution," Post-Print hal-04217143, HAL.
    26. 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.
    27. Jeffrey Smith, 2022. "Treatment Effect Heterogeneity," Evaluation Review, , vol. 46(5), pages 652-677, October.
    28. Odran Bonnet & Étienne Fize & Tristan Loisel & Lionel Wilner, 2024. "Compensating against fuel price inflation: Price subsidies or transfers?," Institut des Politiques Publiques hal-04799412, HAL.
    29. David M. Ritzwoller & Joseph P. Romano, 2023. "Reproducible Aggregation of Sample-Split Statistics," Papers 2311.14204, arXiv.org, revised Nov 2024.
    30. Nathan Kallus, 2022. "Treatment Effect Risk: Bounds and Inference," Papers 2201.05893, arXiv.org, revised Jul 2022.
    31. Jonas Hjort & Vinayak Iyer & Golvine de Rochambeau, 2020. "Informational Barriers to Market Access: Experimental Evidence from Liberian Firms," SciencePo Working papers hal-03389180, HAL.
    32. Sebastian Galiani & Brian Quistorff, 2022. "Assessing External Validity in Practice," NBER Working Papers 30398, National Bureau of Economic Research, Inc.
    33. 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.
    34. 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.
    35. World Bank, 2021. "Promoting Women Entrepreneurs in Mexico Report," World Bank Publications - Reports 37323, The World Bank Group.
    36. 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).
    37. 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).
    38. Otis, Nicholas G. & Clarke, Rowan Philip & Delecourt, Solene & Holtz, David & Koning, Rembrand, 2023. "The Uneven Impact of Generative AI on Entrepreneurial Performance," OSF Preprints hdjpk_v1, Center for Open Science.
    39. 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.
    40. 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.
    41. 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.
    42. Dmitry Arkhangelsky & Kazuharu Yanagimoto & Tom Zohar, 2024. "Using Event Studies as an Outcome in Causal Analysis," Papers 2403.19563, arXiv.org, revised Jan 2025.
    43. 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.
    44. Gallego, Francisco A. & Malamud, Ofer & Pop-Eleches, Cristian, 2020. "Parental monitoring and children's internet use: The role of information, control, and cues," Journal of Public Economics, Elsevier, vol. 188(C).
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. Odran Bonnet & Étienne Fize & Tristan Loisel & Lionel Wilner, 2024. "Compensating against fuel price inflation: Price subsidies or transfers?," Post-Print hal-04799412, HAL.
    50. 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.
    51. Muller, Seán M., 2020. "The implications of a fundamental contradiction in advocating randomized trials for policy," World Development, Elsevier, vol. 127(C).
    52. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    53. 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).
    54. 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.
    55. Bonnet, Odran & Fize, Étienne & Loisel, Tristan & Wilner, Lionel, 2025. "Compensating against fuel price inflation: Price subsidies or transfers?," Journal of Environmental Economics and Management, Elsevier, vol. 129(C).
    56. 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.
    57. 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.
    58. 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.
    59. 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.
    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. 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".
    62. 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.
    63. Maria Nareklishvili & Nicholas Polson & Vadim Sokolov, 2022. "Feature Selection for Personalized Policy Analysis," Papers 2301.00251, arXiv.org, revised Jul 2023.
    64. 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.
    65. Kyle Myers & Wei Yang Tham, 2023. "Money, Time, and Grant Design," Papers 2312.06479, arXiv.org.
    66. 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).

  10. Victor Chernozhukov & Iván Fernández-Val & Sukjin Han & Amanda Kowalski, 2018. "Censored Quantile Instrumental Variable Estimation with Stata," NBER Working Papers 24232, National Bureau of Economic Research, Inc.

    Cited by:

    1. 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.
    2. Männasoo, Kadri, 2022. "Working hours and gender wage differentials: Evidence from the American Working Conditions Survey," Labour Economics, Elsevier, vol. 76(C).
    3. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.
    4. Dunn, Abe, 2016. "Health insurance and the demand for medical care: Instrumental variable estimates using health insurer claims data," Journal of Health Economics, Elsevier, vol. 48(C), pages 74-88.
    5. 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.
    6. 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.
    7. Sugimoto, Kota, 2021. "Ownership versus legal unbundling of electricity transmission network: Evidence from renewable energy investment in Germany," Energy Economics, Elsevier, vol. 99(C).

  11. 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 CWP48/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Westphal, Matthias & Kamhöfer, Daniel A. & Schmitz, Hendrik, 2020. "Marginal college wage premiums under selection into employment," Ruhr Economic Papers 855, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. 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.
    4. 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).

  12. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers CWP33/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Wang, Ao, 2023. "Sieve BLP: A semi-nonparametric model of demand for differentiated products," Journal of Econometrics, Elsevier, vol. 235(2), pages 325-351.
    2. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    3. 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.
    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, 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.

  13. Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP42/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Thierry Magnac & Sébastien Roux, 2021. "Heterogeneity and wage inequalities over the life cycle," Post-Print hal-04532017, HAL.
    2. 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.
    3. 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.
    4. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    5. 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.
    6. Carneiro, Anabela & Portugal, Pedro & Raposo, Pedro & Rodrigues, Paulo M.M., 2023. "The persistence of wages," Journal of Econometrics, Elsevier, vol. 233(2), pages 596-611.
    7. 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).
    8. 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.
    9. 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.
    10. Czarnowske, Daniel & Stammann, Amrei, 2022. "Latent unbalancedness in three-way gravity models," Economics Letters, Elsevier, vol. 220(C).
    11. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    12. 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).
    13. 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.
    14. Koen Jochmans, 2023. "Modified-likelihood estimation of fixed-effect models for dyadic data," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 14(3), pages 417-433, December.
    15. 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.
    16. 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.
    17. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.
    23. 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).
    24. 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.
    25. Yugang He, 2024. "Artificial intelligence and socioeconomic forces: transforming the landscape of religion," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    26. 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.
    27. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org, revised Nov 2024.
    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. 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.
    30. 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.
    31. 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).
    32. Matthieu Crozet & Julian Hinz & Amrei Stammann & Joschka Wanner, 2021. "Worth the pain? Firms’ exporting behaviour to countries under sanctions," Post-Print hal-04150309, HAL.
    33. Nguyen, Quang Khai, 2024. "How Does Financial Flexibility Strategy Impact on Risk Management Effectiveness?," MPRA Paper 121162, University Library of Munich, Germany.
    34. Bo E. Honoré & Áureo de Paula, 2021. "Identification in simple binary outcome panel data models," CeMMAP working papers CWP14/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    40. 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).
    41. Okafor, Luke & Yan, Eric, 2022. "Covid-19 vaccines, rules, deaths, and tourism recovery," Annals of Tourism Research, Elsevier, vol. 95(C).
    42. 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.
    43. 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.
    44. 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.
    45. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.
    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).

  14. 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.

    Cited by:

    1. Vira Semenova, 2020. "Generalized Lee Bounds," Papers 2008.12720, arXiv.org, revised Feb 2023.
    2. Alex Armand & Britta Augsburg & Antonella Bancalari & Maitreesh Ghatak, 2023. "Public service delivery, exclusion and externalities: theory and experimental evidence from India," NOVAFRICA Working Paper Series wp2303, Universidade Nova de Lisboa, Nova School of Business and Economics, NOVAFRICA.
    3. Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kapadia, Sujit & Şimşek, Özgür, 2021. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Working Paper Series 2614, European Central Bank.
    4. 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.
    5. Daniel J. Lewis & Davide Melcangi & Laura Pilossoph, 2019. "Latent Heterogeneity in the Marginal Propensity to Consume," Staff Reports 902, Federal Reserve Bank of New York.
    6. Michael C Knaus, 2022. "Double machine learning-based programme evaluation under unconfoundedness [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 602-627.
    7. 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.
    8. Alex Armand & Britta Augsburg & Antonella Bancalari, 2021. "Coordination and the poor maintenance trap: an experiment on public infrastructure in India," IFS Working Papers W21/16, Institute for Fiscal Studies.
    9. 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.
    10. Riccardo Di Francesco, 2024. "Aggregation Trees," Papers 2410.11408, arXiv.org.
    11. Stephen Coussens & Jann Spiess, 2021. "Improving Inference from Simple Instruments through Compliance Estimation," Papers 2108.03726, arXiv.org.
    12. 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.

  15. Michael Lipsitz & Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val, 2017. "Quantreg.nonpar: an R package for performing nonparametric series quantile regression," CeMMAP working papers CWP29/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. 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).
    2. 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).
    3. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Iv'an Fern'andez-Val, 2011. "Conditional Quantile Processes based on Series or Many Regressors," Papers 1105.6154, arXiv.org, revised Aug 2018.

  16. Victor Chernozhukov & Ivan Fernandez-Val & Tetsuya Kaji, 2017. "Extremal quantile regression: an overview," CeMMAP working papers CWP65/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. 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".
    2. Matthew A. Masten & Alexandre Poirier, 2022. "Choosing Exogeneity Assumptions in Potential Outcome Models," Papers 2205.02288, arXiv.org.
    3. Yuya Sasaki & Yulong Wang, 2022. "Fixed-k Inference for Conditional Extremal Quantiles," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 829-837, April.
    4. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.
    5. 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.
    6. Marian Vavra, 2023. "Bias-Correction in Time Series Quantile Regression Models," Working and Discussion Papers WP 3/2023, Research Department, National Bank of Slovakia.
    7. D'Haultfoeuille, Xavier & Maurel, Arnaud & Zhang, Yichong, 2014. "Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap," IZA Discussion Papers 8256, Institute of Labor Economics (IZA).
    8. Xavier D'Haultfoeuille & Arnaud Maurel & Xiaoyun Qiu & Yichong Zhang, 2019. "Estimating Selection Models without Instrument with Stata," NBER Working Papers 25823, National Bureau of Economic Research, Inc.
    9. 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.

  17. 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. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. 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.
    3. Alejandro Sanchez-Becerra, 2023. "Robust inference for the treatment effect variance in experiments using machine learning," Papers 2306.03363, arXiv.org.
    4. Vlassopoulos, Michael & Siddique, Abu & Rahman, Tabassum & Pakrashi, Debayan & Islam, Asadul & Ahmed, Firoz, 2021. "Improving Women's Mental Health during a Pandemic," IZA Discussion Papers 14786, Institute of Labor Economics (IZA).
    5. Marianne Bertrand & Bruno Crépon & Alicia Marguerie & Patrick Premand, 2021. "Do Workfare Programs Live Up to Their Promises? Experimental Evidence from Cote D’Ivoire," NBER Working Papers 28664, National Bureau of Economic Research, Inc.
    6. Strittmatter, Anthony, 2019. "What is the Value Added by using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203499, Verein für Socialpolitik / German Economic Association.
    7. Islam, Asadul & Mozumder, Tanvir Ahmed & Rahman, Tabassum & Shatil, Tanvir & Siddique, Abu, 2024. "Forced Displacement, Mental Health, and Child Development: Evidence from the Rohingya Refugees," IZA Discussion Papers 16961, Institute of Labor Economics (IZA).
    8. 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).
    9. Bruno Fava, 2024. "Predicting the Distribution of Treatment Effects: A Covariate-Adjustment Approach," Papers 2407.14635, arXiv.org, revised Oct 2024.
    10. 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).
    11. Christiansen, T. & Weeks, M., 2020. "Distributional Aspects of Microcredit Expansions," Cambridge Working Papers in Economics 20100, Faculty of Economics, University of Cambridge.
    12. 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.
    13. 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.
    14. 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).
    15. Hoong, Ruru, 2021. "Self control and smartphone use: An experimental study of soft commitment devices," European Economic Review, Elsevier, vol. 140(C).
    16. 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.
    17. Pramod Kumar Sur, 2021. "Understanding Vaccine Hesitancy: Empirical Evidence from India," Papers 2103.02909, arXiv.org, revised Feb 2023.

  18. Victor Chernozhukov & Iván Fernández-Val & Whitney Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models," Bristol Economics Discussion Papers 17/690, School of Economics, University of Bristol, UK.

    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 Feb 2025.
    2. 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 CWP48/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. 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).
    4. 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.
    5. 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.
    6. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.
    7. 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.
    8. Jayeeta Bhattacharya, 2020. "Quantile regression with generated dependent variable and covariates," Papers 2012.13614, arXiv.org.
    9. 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.
    10. 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.
    11. 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.
    12. Dominik Wied, 2022. "Semiparametric Distribution Regression with Instruments and Monotonicity," Papers 2212.03704, arXiv.org.
    13. Jonas Meier, 2020. "Multivariate Distribution Regression," Diskussionsschriften dp2023, Universitaet Bern, Departement Volkswirtschaft.
    14. Whitney K. Newey & Sami Stouli, 2018. "Identification of Treatment Effects under Limited Exogenous Variation," Papers 1811.09837, arXiv.org, revised Jan 2025.
    15. Richard Spady & Sami Stouli, 2020. "Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions," Papers 2011.06416, arXiv.org.
    16. Romauld Méango, 2023. "Identification of ex ante returns using elicited choice probabilities," Economics Series Working Papers 1007, University of Oxford, Department of Economics.
    17. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    18. Tadao Hoshino, 2021. "Estimating a Continuous Treatment Model with Spillovers: A Control Function Approach," Papers 2112.15114, arXiv.org, revised Jan 2023.
    19. 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).
    20. 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.

  19. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers CWP13/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," CEPR Discussion Papers 13430, C.E.P.R. Discussion Papers.
    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    8. Ying-Ying Lee & Chu-An Liu, 2024. "Lee Bounds with a Continuous Treatment in Sample Selection," Papers 2411.04312, arXiv.org, revised Feb 2025.
    9. 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.
    10. 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).
    11. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    12. Vira Semenova, 2023. "Aggregated Intersection Bounds and Aggregated Minimax Values," Papers 2303.00982, arXiv.org, revised Jun 2024.
    13. 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.
    14. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
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    6. 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.
    7. 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.
    8. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Nakatani, Ryota, 2020. "Macroprudential Policy and the Probability of a Banking Crisis," MPRA Paper 101157, University Library of Munich, Germany.
    14. 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.
    15. Hinz, Julian & Stammann, Amrei & Wanner, Joschka, 2019. "Persistent zeros: The extensive margin of trade," Kiel Working Papers 2139, Kiel Institute for the World Economy (IfW Kiel).
    16. 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.
    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. David W. Hughes, 2022. "Estimating Nonlinear Network Data Models with Fixed Effects," Papers 2203.15603, arXiv.org, revised Mar 2023.
    19. 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.
    20. 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).
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. Cosima Obst, 2022. "Job Satisfaction and Training Investments," CEPA Discussion Papers 47, Center for Economic Policy Analysis.
    31. 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.
    32. Jaworski, Taylor & Keay, Ian, 2022. "Globalization and the spread of industrialization in Canada, 1871–1891," Explorations in Economic History, Elsevier, vol. 86(C).
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. 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.

  21. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar W thrich, 2016. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Diskussionsschriften dp1607, Universitaet Bern, Departement Volkswirtschaft.

    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 CWP48/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. 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.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. 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.
    5. Valentina Corradi & Daniel Gutknecht, 2019. "Testing for Quantile Sample Selection," Papers 1907.07412, arXiv.org, revised Jan 2021.
    6. 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.
    7. 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.
    8. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    9. 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.
    10. Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "Distributional conformal prediction," University of California at San Diego, Economics Working Paper Series qt2zs6m5p5, Department of Economics, UC San Diego.
    11. Ferdi Botha & John P. de New & Sonja C. de New & David C. Ribar & Nicolás Salamanca, 2020. "COVID-19 labour market shocks and their inequality implications for financial wellbeing," Melbourne Institute Working Paper Series wp2020n15, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    12. 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.

  22. Victor Chernozhukov & Ivan Fernandez-Val & Ye Luo, 2015. "The sorted effects method: discovering heterogeneous effects beyond their averages," CeMMAP working papers CWP74/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. 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.
    2. 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).
    3. 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).
    4. 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.
    5. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    6. Wunsch, Conny & Strittmatter, Anthony, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," CEPR Discussion Papers 15840, C.E.P.R. Discussion Papers.
    7. Sookyo Jeong & Hongseok Namkoong, 2020. "Assessing External Validity Over Worst-case Subpopulations," Papers 2007.02411, arXiv.org, revised Feb 2022.
    8. Daniel Goller, 2023. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Annals of Operations Research, Springer, vol. 325(1), pages 649-679, June.
    9. Nora Bearth & Michael Lechner, 2024. "Causal Machine Learning for Moderation Effects," Papers 2401.08290, arXiv.org, revised Jan 2025.
    10. 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.
    11. Strittmatter, Anthony, 2019. "What is the Value Added by using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203499, Verein für Socialpolitik / German Economic Association.
    12. 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).
    13. 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).
    14. 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.
    15. 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.
    16. Michael Zimmert & Michael Lechner, 2019. "Nonparametric estimation of causal heterogeneity under high-dimensional confounding," Papers 1908.08779, arXiv.org.
    17. Daniel Jacob, 2019. "Group Average Treatment Effects for Observational Studies," Papers 1911.02688, arXiv.org, revised Mar 2020.
    18. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    19. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández-Val, 2023. "Fischer-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Working Papers hal-04238425, HAL.
    20. 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.
    21. 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.
    22. Michael C Knaus, 2022. "Double machine learning-based programme evaluation under unconfoundedness [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 602-627.
    23. 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".
    24. Pullabhotla, Hemant K. & Souza, Mateus, 2022. "Air pollution from agricultural fires increases hypertension risk," Journal of Environmental Economics and Management, Elsevier, vol. 115(C).
    25. 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.
    26. Victor Chernozhukov & Ivan Fernandez-Val & Ye Luo, 2015. "The sorted effects method: discovering heterogeneous effects beyond their averages," CeMMAP working papers CWP74/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. 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.
    28. 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.
    29. Kai Feng & Han Hong, 2024. "Statistical Inference of Optimal Allocations I: Regularities and their Implications," Papers 2403.18248, arXiv.org, revised Apr 2024.
    30. Matthew A. Masten & Alexandre Poirier & Muyang Ren, 2025. "A General Approach to Relaxing Unconfoundedness," Papers 2501.15400, arXiv.org.
    31. 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.
    32. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods," Papers 1803.09015, arXiv.org, revised Dec 2020.
    33. 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.
    34. Florent Dubois & Christophe Muller, 2022. "Residential segregation matters to racial income gaps," Working Papers hal-03622711, HAL.
    35. 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.
    36. 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).
    37. Zheng Fang, 2021. "A Unifying Framework for Testing Shape Restrictions," Papers 2107.12494, arXiv.org, revised Aug 2021.
    38. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," CESifo Working Paper Series 9037, CESifo.
    39. 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).
    40. 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).
    41. Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," Papers 2206.07845, arXiv.org.
    42. 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.
    43. 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).
    44. Bernhard Boockmann & Martin Kroczek & Natalie Laub, 2023. "Tightening access to early retirement: who can adapt?," IAW Discussion Papers 142, Institut für Angewandte Wirtschaftsforschung (IAW).

  23. 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. 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. 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.
    3. 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.
    4. 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.
    5. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
    6. 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.
    7. Dolado, Juan J & Chen, Liang & Gonzalo, Jesus, 2018. "Quantile Factor Models," CEPR Discussion Papers 12716, C.E.P.R. Discussion Papers.
    8. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2017. "Discretizing unobserved heterogeneity," IFS Working Papers W17/03, Institute for Fiscal Studies.
    9. 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.
    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. Boneva, L. & Linton, O., 2017. "A Discrete Choice Model For Large Heterogeneous Panels with Interactive Fixed Effects with an Application to the Determinants of Corporate Bond Issuance," Cambridge Working Papers in Economics 1703, Faculty of Economics, University of Cambridge.
    12. Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2023. "Specification testing with grouped fixed effects," Papers 2310.01950, arXiv.org.
    13. Bartolucci, Francesco & Pigini, Claudia, 2019. "Partial effects estimation for fixed-effects logit panel data models," MPRA Paper 92243, University Library of Munich, Germany.
    14. Bin Ping & Liangju Su & Yanrong Yang & Joakim Westerlund, 2023. "Interactive-effects panel-data models with general factors and regressors," French Stata Users' Group Meetings 2023 14, Stata Users Group.
    15. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.
    16. 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.
    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. 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).
    19. 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.
    20. David W. Hughes, 2022. "Estimating Nonlinear Network Data Models with Fixed Effects," Papers 2203.15603, arXiv.org, revised Mar 2023.
    21. 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.
    22. Cheng, T. & Dong, C. & Gao, J. & Linton, O., 2022. "GMM Estimation for High-Dimensional Panel Data Models," Cambridge Working Papers in Economics 2245, Faculty of Economics, University of Cambridge.
    23. 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.
    24. 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.
    25. Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org.
    26. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    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. 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.
    30. Chen, Liang & 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    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. 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.
    40. Hugo Freeman, 2022. "Linear Multidimensional Regression with Interactive Fixed-Effects," Papers 2209.11691, arXiv.org, revised Mar 2025.

  24. 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. 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.
    2. Bellmann, Lutz & Hübler, Olaf, 2019. "Personal Attitudes, Job Characteristics and Health," IZA Discussion Papers 12597, Institute of Labor Economics (IZA).
    3. 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.

  25. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney K. Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers CWP66/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. 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.
    2. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    3. 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.
    4. 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.
    5. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2022. "Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities," Econometrica, Econometric Society, vol. 90(4), pages 1681-1710, July.
    6. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    7. 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.
    8. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile Regression with Panel Data," NBER Working Papers 21034, National Bureau of Economic Research, Inc.
    9. Oliver Linton & Ji-Liang Shiu, 2018. "Semiparametric nonlinear panel data models with measurement error," CeMMAP working papers CWP09/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Cizek, P. & Lei, J., 2013. "Identification and Estimation of Nonseparable Single-Index Models in Panel Data with Correlated Random Effects," Other publications TiSEM 73e394eb-6799-4c79-af23-8, Tilburg University, School of Economics and Management.
    11. 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.
    12. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    14. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    15. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    16. 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.
    17. 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.
    18. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
    19. 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.
    20. 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.
    21. Victor Chernozhukov & Ivan Fernandez-Val & Ye Luo, 2015. "The sorted effects method: discovering heterogeneous effects beyond their averages," CeMMAP working papers CWP74/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. Irene Botosaru & Chris Muris & Krishna Pendakur, 2020. "Intertemporal Collective Household Models: Identification in Short Panels with Unobserved Heterogeneity in Resource Shares," CeMMAP working papers CWP26/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. 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.
    24. 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.
    25. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Discussion Paper 2022-009, Tilburg University, Center for Economic Research.
    26. 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.
    27. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.
    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.

  26. Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP57/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
    2. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    3. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Papers 1611.09420, arXiv.org, revised Dec 2016.
    4. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in High Dimensional Panel Models with an Application to Gun Control," Papers 1411.6507, arXiv.org.
    5. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    6. Susan Athey & Julie Tibshirani & Stefan Wager, 2016. "Generalized Random Forests," Papers 1610.01271, arXiv.org, revised Apr 2018.
    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. Max H. Farrell, 2013. "Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations," Papers 1309.4686, arXiv.org, revised Feb 2018.
    9. Kasy Maximilian, 2019. "Uniformity and the Delta Method," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-19, January.
    10. 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).
    11. 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.
    12. Denis Chetverikov & . ., 2016. "On cross-validated Lasso," CeMMAP working papers CWP47/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. 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.
    14. 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.
    15. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    16. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    17. Alexandre Belloni & Victor Chernozhukov & Lie Wang, 2013. "Pivotal estimation via square-root lasso in nonparametric regression," CeMMAP working papers 62/13, Institute for Fiscal Studies.
    18. Matias D. Cattaneo & Michael Jansson, 2014. "Bootstrapping Kernel-Based Semiparametric Estimators," CREATES Research Papers 2014-25, Department of Economics and Business Economics, Aarhus University.
    19. Michael Danquah & Abdul Malik Iddrisu & Ernest Owusu Boakye & Solomon Owusu, 2021. "Do gender wage differences within households influence women's empowerment and welfare?: Evidence from Ghana," WIDER Working Paper Series wp-2021-40, World Institute for Development Economic Research (UNU-WIDER).
    20. 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.
    21. Denis Chetverikov & . ., 2016. "On cross-validated Lasso," CeMMAP working papers 47/16, Institute for Fiscal Studies.
    22. Braverman, Mark & Chassang, Sylvain, 2022. "Data-driven incentive alignment in capitation schemes," Journal of Public Economics, Elsevier, vol. 207(C).
    23. 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.

  27. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and time effects in nonlinear panel models with large N, T," CeMMAP working papers CWP60/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    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. 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. 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.
    4. 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.
    5. 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.
    6. Steven Yamarik & Mariya Mileva, 2023. "Cultural institutes: Networks and determinants," The World Economy, Wiley Blackwell, vol. 46(4), pages 1119-1143, April.
    7. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. 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.
    9. Hyungsik Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers CWP63/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Massenot, Baptiste & Pettinicchi, Yuri, 2018. "Can households see into the future? Survey evidence from the Netherlands," SAFE Working Paper Series 233, Leibniz Institute for Financial Research SAFE.
    11. Koen Jochmans, 2022. "Bias in instrumental-variable estimators of fixed-effect models for count data," Post-Print hal-03699836, HAL.
    12. 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.
    13. Lucciano Villacorta, 2016. "Estimating Country Heterogeneity in Capital - Labor Substitution Using Panel Data," Working Papers Central Bank of Chile 788, Central Bank of Chile.
    14. Larch, Mario & Wanner, Joschka & Yotov, Yoto & Zylkin, Thomas, 2017. "The Currency Union Effect: A PPML Re-assessment with High-Dimensional Fixed Effects," School of Economics Working Paper Series 2017-7, LeBow College of Business, Drexel University.
    15. 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.
    16. Áureo de Paula, 2020. "Econometric Models of Network Formation," CeMMAP working papers CWP4/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. 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.
    19. Dolado, Juan J & Chen, Liang & Gonzalo, Jesus, 2018. "Quantile Factor Models," CEPR Discussion Papers 12716, C.E.P.R. Discussion Papers.
    20. Gindo Tampubolon, 2023. "Climate justice for persons with disability: Few harmed much, fewer still harmed too much," WIDER Working Paper Series wp-2023-2, World Institute for Development Economic Research (UNU-WIDER).
    21. Carneiro, Anabela & Portugal, Pedro & Raposo, Pedro & Rodrigues, Paulo M.M., 2023. "The persistence of wages," Journal of Econometrics, Elsevier, vol. 233(2), pages 596-611.
    22. 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).
    23. Markus Leibrecht & Johann Scharler, 2021. "Veto players, market discipline, and structural fiscal consolidations," Public Choice, Springer, vol. 188(3), pages 361-384, September.
    24. Torben G. Andersen & Nicola Fusari & Viktor Todorov & Rasmus T. Varneskov, 2018. "Unified Inference for Nonlinear Factor Models from Panels with Fixed and Large Time Span," CREATES Research Papers 2018-03, Department of Economics and Business Economics, Aarhus University.
    25. 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).
    26. 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).
    27. Karyne B. Charbonneau, 2014. "Multiple Fixed Effects in Binary Response Panel Data Models," Staff Working Papers 14-17, Bank of Canada.
    28. 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.
    29. Alex Centeno, 2022. "A Structural Model for Detecting Communities in Networks," Papers 2209.08380, arXiv.org, revised Oct 2022.
    30. George Kapetanios & Laura Serlenga & Yongcheol Shin, 2023. "Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects," Empirical Economics, Springer, vol. 64(6), pages 2611-2659, June.
    31. Ohyun Kwon & Jangsu Yoon & Yoto V. Yotov, 2022. "A Generalized Poisson-Pseudo Maximum Likelihood Estimator," CESifo Working Paper Series 10145, CESifo.
    32. 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.
    33. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    34. 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.
    35. 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).
    36. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2017. "Discretizing unobserved heterogeneity," IFS Working Papers W17/03, Institute for Fiscal Studies.
    37. 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.
    38. Larch, Mario & Yotov, Yoto, 2016. "General Equilibrium Trade Policy Analysis with Structural Gravity," School of Economics Working Paper Series 2016-9, LeBow College of Business, Drexel University.
    39. Ming Li & Zhentao Shi & Yapeng Zheng, 2024. "Estimation and Inference in Dyadic Network Formation Models with Nontransferable Utilities," Papers 2410.23852, arXiv.org.
    40. 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.
    41. Sinem Hacıoğlu Hoke & George Kapetanios, 2021. "Common correlated effect cross‐sectional dependence corrections for nonlinear conditional mean panel models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 125-150, January.
    42. Octávio Figueiredo & Paulo Guimarães & Douglas Woodward, 2014. "Industry Localization, Distance Decay, and Knowledge Spillovers: Following the Patent Paper Trail," FEP Working Papers 521, Universidade do Porto, Faculdade de Economia do Porto.
    43. J. M. C. Santos Silva & Silvana Tenreyro, 2022. "The Log of Gravity at 15," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 21(3), pages 423-437, September.
    44. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
    45. Waidelich, Paul & Steffen, Bjarne, 2024. "Renewable energy financing by state investment banks: Evidence from OECD countries," Energy Economics, Elsevier, vol. 132(C).
    46. Koen Jochmans, 2023. "Bootstrap inference for fixed-effect models," French Stata Users' Group Meetings 2023 21, Stata Users Group.
    47. 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.
    48. James Lake & Maia K. Linask, 2015. "Could tariffs be pro-cyclcial?," Departmental Working Papers 1502, Southern Methodist University, Department of Economics.
    49. 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.
    50. 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.
    51. Egger, Peter & Staub, Kevin E, 2015. "GLM estimation of trade gravity models with fixed effects," CEPR Discussion Papers 10428, C.E.P.R. Discussion Papers.
    52. David J. Kuenzel, 2020. "Non-tariff Measures: What’s Tariffs Got to Do with It?," Wesleyan Economics Working Papers 2020-006, Wesleyan University, Department of Economics.
    53. Fonseca, Luís & Nikalexi, Katerina & Papaioannou, Elias, 2023. "The Globalization of Corporate Control," CEPR Discussion Papers 17861, C.E.P.R. Discussion Papers.
    54. Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2020. "Machine Learning Panel Data Regressions with Heavy-tailed Dependent Data: Theory and Application," Papers 2008.03600, arXiv.org, revised Nov 2021.
    55. Martin Schumann & Thomas A. Severini & Gautam Tripathi, 2017. "Integrated Likelihood Based Inference for Nonlinear Panel Data Models with Unobserved Effects," DEM Discussion Paper Series 17-01, Department of Economics at the University of Luxembourg.
    56. 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.
    57. Auer, Daniel & Meierrieks, Daniel, 2021. "Merchants of death: Arms imports and terrorism," European Economic Review, Elsevier, vol. 137(C).
    58. Matthias Breuer & Harm H. Schütt, 2023. "Accounting for uncertainty: an application of Bayesian methods to accruals models," Review of Accounting Studies, Springer, vol. 28(2), pages 726-768, June.
    59. 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.
    60. Juliana Araujo & Povilas Lastauskas & Chris Papageorgiou, 2015. "Evolution of Bilateral Capital Flows to Developing Countries at Intensive and Extensive Margins," Cambridge Working Papers in Economics 1502, Faculty of Economics, University of Cambridge.
    61. 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.
    62. Áureo de Paula, 2016. "Econometrics of network models," CeMMAP working papers CWP06/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    63. Lukas Buchheim & Sebastian Link, 2017. "The Effect of Disaggregate Information on the Expectation Formation of Firms," CESifo Working Paper Series 6768, CESifo.
    64. 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.
    65. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    66. Rafaela Dezidério dos Santos Rocha & Márcio Laurini, 2023. "Factor Sufficiency in Asset Pricing: An Application for the Brazilian Market," IJFS, MDPI, vol. 11(4), pages 1-31, December.
    67. Javier Mejia, 2018. "Social Networks and Entrepreneurship. Evidence from a Historical Episode of Industrialization," Documentos CEDE 16380, Universidad de los Andes, Facultad de Economía, CEDE.
    68. 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.
    69. Lazarov, Vladimir & Hinterschweiger, Marc, 2018. "Determinants of distress in the UK owner-occupier and buy-to-let mortgage markets," Bank of England working papers 760, Bank of England.
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    71. 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.
    72. Christophe Bell'ego & David Benatia & Louis Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Papers 2203.11820, arXiv.org.
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    74. Blanco-Oliver, Antonio, 2021. "Banking reforms and bank efficiency: Evidence for the collapse of Spanish savings banks," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 334-347.
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    2. Olga Miroshnichenko & Elena Iakovleva & Natalia Voronova, 2022. "Banking Sector Profitability: Does Household Income Matter?," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
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    4. 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.
    5. Javier Alejo & Antonio F. Galvao & Julian Martinez-Iriarte & Gabriel Montes-Rojas, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Papers 2301.07241, arXiv.org, revised Dec 2023.
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    8. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2012. "Inference on counterfactual distributions," CeMMAP working papers 05/12, Institute for Fiscal Studies.
    9. 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.
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    20. 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.
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    43. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2022. "Unconditional quantile regression with high‐dimensional data," Quantitative Economics, Econometric Society, vol. 13(3), pages 955-978, July.
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    46. Viola, Alessandra Pasqualina & Klotzle, Marcelo Cabus & Pinto, Antonio Carlos Figueiredo & da Silveira Barbedo, Claudio Henrique, 2019. "Foreign exchange interventions in Brazil and their impact on volatility: A quantile regression approach," Research in International Business and Finance, Elsevier, vol. 47(C), pages 251-263.
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    51. 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.
    52. 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.
    53. 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.
    54. 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.
    55. Raslan Alzuabi & Sarah Brown & Daniel Gray & Mark N Harris & Christopher Spencer, 2022. "Household saving, health, and healthcare utilization in Japan [Stature, obesity, and portfolio choice]," Oxford Economic Papers, Oxford University Press, vol. 74(2), pages 473-497.
    56. 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.
    57. Leon Zolotoy & Don O’Sullivan & Geoffrey P. Martin & Robert M. Wiseman, 2021. "Stakeholder Agency Relationships: CEO Stock Options and Corporate Tax Avoidance," Journal of Management Studies, Wiley Blackwell, vol. 58(3), pages 782-814, May.
    58. Jad Beyhum & Lorenzo Tedesco & Ingrid Van Keilegom, 2022. "Instrumental variable quantile regression under random right censoring," Papers 2209.01429, arXiv.org, revised Feb 2023.
    59. Jad Beyhum & Jean-Pierre Florens & Ingrid Van Keilegom, 2021. "A nonparametric instrumental approach to endogeneity in competing risks models," Papers 2105.00946, arXiv.org.
    60. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    61. 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.
    62. 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.
    63. Manuel Arellano & Stéphane Bonhomme, 2017. "Sample Selection in Quantile Regression: A Survey," Working Papers wp2017_1702, CEMFI.
    64. 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.
    65. 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).
    66. 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].
    67. 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).
    68. Thomas Bassetti & Filippo Pavesi, 2015. "Electoral Contributions and the Cost of Unpopularity," Working Papers 05/2015, University of Verona, Department of Economics.
    69. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Model Averaging for High Dimensional Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202302, University of Kansas, Department of Economics, revised Jan 2023.
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    74. Aziz N. Berdiev & James W. Saunoris, 2023. "The case for independence: Does central bank independence curb the spread of the underground economy?," Kyklos, Wiley Blackwell, vol. 76(3), pages 407-435, August.
    75. Amanda E. Kowalski, 2016. "Doing More When You're Running LATE: Applying Marginal Treatment Effect Methods to Examine Treatment Effect Heterogeneity in Experiments for the Young and Privately Insured"," Cowles Foundation Discussion Papers 2045, Cowles Foundation for Research in Economics, Yale University.
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    79. J Doran & G Ryan, 2016. "The effectiveness of R&D and external interaction for innovation: Insights from quantile regression," Economic Issues Journal Articles, Economic Issues, vol. 21(1), pages 47-65, March.
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  29. Victor Chernozhukov & Ivan Fernandez-Val, 2011. "Inference for extremal conditional quantile models, with an application to market and birthweight risks," CeMMAP working papers CWP40/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Becker, Sascha O. & Hvide, Hans K., 2013. "Do entrepreneurs matter?," CEPR Discussion Papers 9295, C.E.P.R. Discussion Papers.
    2. Yuya Sasaki & Yulong Wang, 2024. "Extreme Quantile Treatment Effects under Endogeneity: Evaluating Policy Effects for the Most Vulnerable Individuals," Papers 2409.03979, arXiv.org.
    3. 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.
    4. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    5. Wang, Yulong & Xiao, Zhijie, 2022. "Estimation and inference about tail features with tail censored data," Journal of Econometrics, Elsevier, vol. 230(2), pages 363-387.
    6. Martínez-Iriarte, Julián & Montes-Rojas, Gabriel & Sun, Yixiao, 2024. "Unconditional effects of general policy interventions," Journal of Econometrics, Elsevier, vol. 238(2).
    7. Valentina Corradi & Daniel Gutknecht, 2019. "Testing for Quantile Sample Selection," Papers 1907.07412, arXiv.org, revised Jan 2021.
    8. Yuya Sasaki & Yulong Wang, 2022. "Fixed-k Inference for Conditional Extremal Quantiles," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 829-837, April.
    9. 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.
    10. Lee, JiHyung, 2015. "Predictive quantile regression with persistent covariates: IVX-QR approach," MPRA Paper 65150, University Library of Munich, Germany.
    11. Michal Franta & Jan Vlcek, 2024. "Wage-Price Spirals: A Risk-Based Approach," Working Papers 2024/1, Czech National Bank.
    12. Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly, 2019. "Fast Algorithms for the Quantile Regression Process," Papers 1909.05782, arXiv.org, revised Apr 2020.
    13. 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.
    14. 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.
    15. 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.
    16. Andres Sagner, 2020. "High Dimensional Quantile Factor Analysis," Working Papers Central Bank of Chile 886, Central Bank of Chile.
    17. D'Haultfoeuille, Xavier & Maurel, Arnaud & Zhang, Yichong, 2014. "Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap," IZA Discussion Papers 8256, Institute of Labor Economics (IZA).
    18. Grimsby, Gjermund, 2018. "Partly risky, partly solid – Performance study of public innovation loans," Research Policy, Elsevier, vol. 47(7), pages 1344-1365.
    19. 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).
    20. Oliver Himmler, 2009. "The Effects of School Competition on Academic Achievement and Grading Standards," CESifo Working Paper Series 2676, CESifo.
    21. Xavier D'Haultfoeuille & Arnaud Maurel & Xiaoyun Qiu & Yichong Zhang, 2019. "Estimating Selection Models without Instrument with Stata," NBER Working Papers 25823, National Bureau of Economic Research, Inc.
    22. Victor Chernozhukov & Iv'an Fern'andez-Val & Jonas Meier & Aico van Vuuren & Francis Vella, 2024. "Conditional Rank-Rank Regression," Papers 2407.06387, arXiv.org, revised Mar 2025.
    23. Sulkhan Chavleishvili & Simone Manganelli, 2024. "Forecasting and stress testing with quantile vector autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 66-85, January.
    24. Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2015. "IV Quantile Regression for Group-level Treatments, with an Application to the Distributional Effects of Trade," NBER Working Papers 21033, National Bureau of Economic Research, Inc.
    25. He, Fengyang & Wang, Huixia Judy & Zhou, Yuejin, 2022. "Extremal quantile autoregression for heavy-tailed time series," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
    26. 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.
    27. 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.
    28. 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.
    29. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    30. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.
    31. Vladislav Morozov, 2022. "Inference on Extreme Quantiles of Unobserved Individual Heterogeneity," Papers 2210.08524, arXiv.org, revised Jun 2023.
    32. Marilena Furno & Francesco Caracciolo, 2020. "Multi-valued Double Robust quantile treatment effect," Empirical Economics, Springer, vol. 58(5), pages 2545-2571, May.
    33. 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.
    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. 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.
    36. 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.
    37. Zhengyu Zhang & Zequn Jin & Lihua Lin, 2024. "Identification and inference of outcome conditioned partial effects of general interventions," Papers 2407.16950, arXiv.org.
    38. Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2022. "Weighted-average quantile regression," Papers 2203.03032, arXiv.org.
    39. David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.
    40. 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).
    41. Aida Caldera Sánchez & Oliver Röhn, 2016. "How do policies influence GDP tail risks?," OECD Economics Department Working Papers 1339, OECD Publishing.
    42. 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.

  30. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val, 2011. "Conditional quantile processes based on series or many regressors," CeMMAP working papers CWP19/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
    2. 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.
    3. 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".
    4. 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.
    5. 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.
    6. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012. "Some New Asymptotic Theory for Least Squares Series: Pointwise and Uniform Results," Papers 1212.0442, arXiv.org, revised Jun 2015.
    7. 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.
    8. 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.
    9. Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers 51/16, Institute for Fiscal Studies.
    10. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2024. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 1026-1040, July.
    11. Hao, Meiling & Lin, Yuanyuan & Shen, Guohao & Su, Wen, 2023. "Nonparametric inference on smoothed quantile regression process," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    12. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar Wüthrich, 2017. "Generic inference on quantile and quantile effect functions for discrete outcomes," CeMMAP working papers CWP23/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2012. "Inference for best linear approximations to set identified functions," CeMMAP working papers CWP43/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
    15. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    16. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Iv'an Fern'andez-Val, 2011. "Conditional Quantile Processes based on Series or Many Regressors," Papers 1105.6154, arXiv.org, revised Aug 2018.
    17. Zheng Fang & Andres Santos & Azeem M. Shaikh & Alexander Torgovitsky, 2020. "Inference for Large-Scale Linear Systems with Known Coefficients," Papers 2009.08568, arXiv.org, revised Sep 2021.
    18. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
    19. Vira Semenova, 2020. "Generalized Lee Bounds," Papers 2008.12720, arXiv.org, revised Feb 2023.
    20. Matias D. Cattaneo & Ricardo P. Masini & William G. Underwood, 2022. "Yurinskii's Coupling for Martingales," Papers 2210.00362, arXiv.org, revised Sep 2024.
    21. 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.
    22. 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.
    23. Richard Spady & Sami Stouli, 2016. "Dual regression," CeMMAP working papers 04/16, Institute for Fiscal Studies.
    24. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Uniform post selection inference for LAD regression and other z-estimation problems," CeMMAP working papers 74/13, Institute for Fiscal Studies.
    25. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2019. "On binscatter," Staff Reports 881, Federal Reserve Bank of New York.
    26. 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.
    27. 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).
    28. 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.
    29. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. 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.
    31. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Uniform post selection inference for LAD regression models," CeMMAP working papers 24/13, Institute for Fiscal Studies.
    32. Feng, Xingdong & Liu, Qiaochu & Wang, Caixing, 2023. "A lack-of-fit test for quantile regression process models," Statistics & Probability Letters, Elsevier, vol. 192(C).
    33. 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 CWP09/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    34. 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.
    35. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2017. "Quantile graphical models: prediction and conditional independence with applications to systemic risk," CeMMAP working papers 54/17, Institute for Fiscal Studies.
    36. Matias D. Cattaneo & Yingjie Feng & Rocio Titiunik, 2021. "Prediction Intervals for Synthetic Control Methods," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1865-1880, October.
    37. 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.
    38. 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.
    39. 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.
    40. Qihui Chen, 2022. "Robust Estimation of Conditional Factor Models," Papers 2204.00801, arXiv.org, revised Apr 2022.
    41. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2016. "Gaussian approximation of suprema of empirical processes," CeMMAP working papers CWP41/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    42. 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.
    43. 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.
    44. Ferreira, Francisco H. G. & Firpo, Sergio & Galvao, Antonio F., 2017. "Estimation and Inference for Actual and Counterfactual Growth Incidence Curves," IZA Discussion Papers 10473, Institute of Labor Economics (IZA).
    45. 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.
    46. 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.
    47. 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.
    48. 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.
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    50. 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.
    51. Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2021. "Local regression distribution estimators," Department of Economics, Working Paper Series qt7416d3x8, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
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    62. 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.
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    1. Hao Bo & Sebastian Galiani, 2019. "Assessing External Validity," NBER Working Papers 26422, National Bureau of Economic Research, Inc.
    2. 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.
    3. Han, Sukjin & Yang, Shenshen, 2024. "A computational approach to identification of treatment effects for policy evaluation," Journal of Econometrics, Elsevier, vol. 240(1).
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    5. Lina Zhang & David T. Frazier & D. S. Poskitt & Xueyan Zhao, 2020. "Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects," Papers 2009.02642, arXiv.org, revised Sep 2022.
    6. 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).
    7. 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.
    8. 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.
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    13. Meager, Rachael & Sturdy, Jennifer, 2017. "Aggregating Distributional Treatment Effects: A Bayesian Hierarchical Analysis of the Microcredit Literature," MetaArXiv 7tkvm, Center for Open Science.
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    24. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
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    26. Dionissi Aliprantis, 2013. "Covariates and causal effects: the problem of context," Working Papers (Old Series) 1310, Federal Reserve Bank of Cleveland.
    27. 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.
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    30. 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.
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    32. Beatrice Baaba Tawiah, 2023. "The Effect of Children on Health," Working Papers Dissertations 103, Paderborn University, Faculty of Business Administration and Economics.
    33. Fujiwara, Daniel, 2013. "A general method for valuing non-market goods using wellbeing data: three-stage wellbeing valuation," LSE Research Online Documents on Economics 51577, London School of Economics and Political Science, LSE Library.
    34. Brutscher, P-B., 2012. "Making Sense of Oil Stamp Saving Schemes," Cambridge Working Papers in Economics 1203, Faculty of Economics, University of Cambridge.
    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.

  32. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves without Crossing," SciencePo Working papers Main hal-01052958, HAL.

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    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 Feb 2025.
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    3. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    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 CWP48/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    6. 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.
    7. 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".
    8. 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.
    9. Christian Manuel Posso Suárez, 2008. "Desigualdad salarial en Colombia 1984-2005: cambios en la composición del mercado laboral y retornos a la educación post-secundaria," Borradores de Economia 5003, Banco de la Republica.
    10. 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.
    11. David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
    12. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012. "Some New Asymptotic Theory for Least Squares Series: Pointwise and Uniform Results," Papers 1212.0442, arXiv.org, revised Jun 2015.
    13. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
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    16. Sohag, Kazi & Kliestik, Tomas & Shams, S.M. Riad & Mariev, Oleg & Davidson, Natalia, 2022. "Capital market deepening, Governor’s characteristics and Russian regional enterprises: A big data analysis," Journal of Business Research, Elsevier, vol. 149(C), pages 340-352.
    17. Clément de Chaisemartin & Xavier d'Haultfoeuille, 2014. "Fuzzy Changes-in-Changes," Working Papers 2014-18, Center for Research in Economics and Statistics.
    18. Gail Pacheco & Bill Cochrane, 2015. "Decomposing the temporary-permanent wage gap in New Zealand," Working Papers 2015-07, Auckland University of Technology, Department of Economics.
    19. Manuel Arellano & Richard Blundell & Stéphane Bonhomme & Jack Light, 2024. "Heterogeneity of consumption responses to income shocks in the presence of nonlinear persistence," Post-Print hal-04536563, HAL.
    20. Matthew Masten & Alexandre Poirier, 2017. "Inference on breakdown frontiers," CeMMAP working papers 20/17, Institute for Fiscal Studies.
    21. 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.
    22. Ruhose, Jens & Parey, Matthias & Waldinger, Fabian & Netz, Nicolai, 2015. "The Selection of High-Skilled Migrants," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113148, Verein für Socialpolitik / German Economic Association.
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    25. Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    26. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2012. "Inference on counterfactual distributions," CeMMAP working papers 05/12, Institute for Fiscal Studies.
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    42. Florent Dubois, 2017. "The Sources of Segregation," AMSE Working Papers 1720, Aix-Marseille School of Economics, France.
    43. Gabriel Montes-Rojas & Lucas Siga & Ram Mainali, 2017. "Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(3), pages 245-255, September.
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    46. Ritter, Joseph A. & West, Kristine L., 2014. "Field of Study and Earnings Inequality among the Highly Educated: 1993-2010," Miscellaneous Publications 195683, University of Minnesota, Department of Applied Economics.
    47. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile Regression with Censoring and Endogeneity," Cowles Foundation Discussion Papers 1797, Cowles Foundation for Research in Economics, Yale University.
    48. 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.
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    4. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    5. 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.
    6. 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.
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    12. 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.
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  35. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2008. "Improving point and interval estimates of monotone functions by rearrangement," CeMMAP working papers CWP17/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Wu, Ximing & Sickles, Robin, 2018. "Semiparametric estimation under shape constraints," Econometrics and Statistics, Elsevier, vol. 6(C), pages 74-89.
    2. Tae-Hwy Lee & Weiping Yang, 2014. "Granger-Causality in Quantiles between Financial Markets: Using Copula Approach," Working Papers 201406, University of California at Riverside, Department of Economics.
    3. Sokbae Lee & Ryo Okui & Yoon†Jae Whang, 2017. "Doubly robust uniform confidence band for the conditional average treatment effect function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1207-1225, November.
    4. Joel L. Horowitz & Sokbae (Simon) Lee, 2010. "Uniform confidence bands for functions estimated nonparametrically with instrumental variables," CeMMAP working papers CWP19/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Stéphane Bonhomme & Koen Jochmans & Jean-Marc Robin, 2017. "Nonparametric estimation of non-exchangeable latent-variable models," SciencePo Working papers Main hal-03264006, HAL.
    6. Amy Finkelstein & Erzo F.P. Luttmer & Matthew J. Notowidigdo, 2008. "What Good Is Wealth Without Health? The Effect of Health on the Marginal Utility of Consumption," NBER Working Papers 14089, National Bureau of Economic Research, Inc.
    7. José F. Tudón M., 2019. "Perception, utility, and evolution," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 7(2), pages 191-208, December.
    8. 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.
    9. Joel L. Horowitz & Sokbae (Simon) Lee, 2015. "Nonparametric estimation and inference under shape restrictions," CeMMAP working papers CWP67/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Jun Ma & Vadim Marmer & Artyom Shneyerov & Pai Xu, 2019. "Monotonicity-Constrained Nonparametric Estimation and Inference for First-Price Auctions," Papers 1909.12974, arXiv.org.
    11. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2012. "Inference on counterfactual distributions," CeMMAP working papers 05/12, Institute for Fiscal Studies.
    12. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    13. Koen Jochmans & Stéphane Bonhomme & Jean-Marc Robin, 2015. "Nonparametric estimation of finite mixtures from repeated measurements," SciencePo Working papers Main hal-03568247, HAL.
    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 CWP23/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile And Probability Curves Without Crossing," Boston University - Department of Economics - Working Papers Series WP2007-011, Boston University - Department of Economics.
    16. Marc Henry & Koen Jochmans & Bernard Salanié, 2014. "Inference on Mixtures Under Tail Restrictions," SciencePo Working papers hal-01053810, HAL.
    17. Rodrigues, T. & Dortet-Bernadet, J.-L. & Fan, Y., 2019. "Simultaneous fitting of Bayesian penalised quantile splines," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 93-109.
    18. Philippe Van Kerm & Seunghee Yu & Chung Choe, 2016. "Decomposing quantile wage gaps: a conditional likelihood approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(4), pages 507-527, August.
    19. Florent Dubois, 2017. "The Sources of Segregation," AMSE Working Papers 1720, Aix-Marseille School of Economics, France.
    20. Gabriel Montes-Rojas & Lucas Siga & Ram Mainali, 2017. "Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(3), pages 245-255, September.
    21. 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.
    22. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    23. Henderson, Daniel J. & List, John A. & Millimet, Daniel L. & Parmeter, Christopher F. & Price, Michael K., 2012. "Empirical implementation of nonparametric first-price auction models," Journal of Econometrics, Elsevier, vol. 168(1), pages 17-28.
    24. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Iv'an Fern'andez-Val, 2011. "Conditional Quantile Processes based on Series or Many Regressors," Papers 1105.6154, arXiv.org, revised Aug 2018.
    25. Marc Henry & Romuald Meango & Ismael Mourifie, 2020. "Role models and revealed gender-specific costs of STEM in an extended Roy model of major choice," Papers 2005.09095, arXiv.org, revised Aug 2023.
    26. Trabs, Mathias, 2011. "Calibration of self-decomposable Lévy models," SFB 649 Discussion Papers 2011-073, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    27. Koen Jochmans, 2013. "Pairwise-comparison estimation with nonparametric controls," SciencePo Working papers hal-00973068, HAL.
    28. Tatiana Komarova & Javier Hidalgo, 2019. "Testing nonparametric shape restrictions," Papers 1909.01675, arXiv.org, revised Jun 2020.
    29. David H. Autor & Susan N. Houseman & Sari Pekkala Kerr, 2012. "The Effect of Work First Job Placements on the Distribution of Earnings: An Instrumental Variable Quantile Regression Approach," NBER Working Papers 17972, National Bureau of Economic Research, Inc.
    30. Ghossoub, Mario, 2011. "Monotone equimeasurable rearrangements with non-additive probabilities," MPRA Paper 37629, University Library of Munich, Germany, revised 23 Mar 2012.
    31. Avdulaj Krenar & Barunik Jozef, 2017. "A semiparametric nonlinear quantile regression model for financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 81-97, February.
    32. Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "Distributional conformal prediction," University of California at San Diego, Economics Working Paper Series qt2zs6m5p5, Department of Economics, UC San Diego.
    33. Isaiah Andrews & Jesse M. Shapiro, 2021. "A Model of Scientific Communication," Econometrica, Econometric Society, vol. 89(5), pages 2117-2142, September.
    34. Kroft, Kory & Lange, Fabian & Notowidigdo, Matthew J., 2012. "Duration Dependence and Labor Market Conditions: Theory and Evidence from a Field Experiment," CLSSRN working papers clsrn_admin-2012-21, Vancouver School of Economics, revised 28 Sep 2012.
    35. 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.
    36. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2022. "Bivariate Distribution Regression with Application to Insurance Data," Papers 2203.12228, arXiv.org, revised Sep 2023.
    37. 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.
    38. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2023. "Distributional Vector Autoregression: Eliciting Macro and Financial Dependence," Papers 2303.04994, arXiv.org.
    39. Victor Chernozhukov & Ivan Fernandez-Val & Ye Luo, 2015. "The sorted effects method: discovering heterogeneous effects beyond their averages," CeMMAP working papers CWP74/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    40. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2023. "Constrained Conditional Moment Restriction Models," Econometrica, Econometric Society, vol. 91(2), pages 709-736, March.
    41. Anatolyev, Stanislav & Baruník, Jozef, 2019. "Forecasting dynamic return distributions based on ordered binary choice," International Journal of Forecasting, Elsevier, vol. 35(3), pages 823-835.
    42. Bradley Larsen, 2014. "The Efficiency of Real-World Bargaining: Evidence from Wholesale Used-Auto Auctions," NBER Working Papers 20431, National Bureau of Economic Research, Inc.
    43. Lee, Tae-Hwy & Tu, Yundong & Ullah, Aman, 2014. "Nonparametric and semiparametric regressions subject to monotonicity constraints: Estimation and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 196-210.
    44. Catania, Leopoldo & Luati, Alessandra, 2023. "Semiparametric modeling of multiple quantiles," Journal of Econometrics, Elsevier, vol. 237(2).
    45. Fan, Zengyan & Lian, Heng, 2018. "Quantile regression for additive coefficient models in high dimensions," Journal of Multivariate Analysis, Elsevier, vol. 164(C), pages 54-64.
    46. Heuchenne, Cédric & Jacquemain, Alexandre, 2022. "Inference for monotone single-index conditional means: A Lorenz regression approach," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    47. Santiago Acerenza & Vitor Possebom & Pedro H. C. Sant'Anna, 2023. "Was Javert right to be suspicious? Unpacking treatment effect heterogeneity of alternative sentences on time-to-recidivism in Brazil," Papers 2311.13969, arXiv.org, revised Jan 2025.
    48. Senay Sokullu, 2012. "Nonparametric Analysis of Two-Sided Markets," Bristol Economics Discussion Papers 12/628, School of Economics, University of Bristol, UK.
    49. Ilaria Lucrezia Amerise, 2013. "Weighted Non-Crossing Quantile Regressions," Working Papers 201308, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    50. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    51. Denis Chetverikov & Daniel Wilhelm, 2016. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers 48/16, Institute for Fiscal Studies.
    52. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2024. "Inflation Target at Risk: A Time-varying Parameter Distributional Regression," Papers 2403.12456, arXiv.org.
    53. Thomas R. Covert & Richard L. Sweeney, 2023. "Relinquishing Riches: Auctions versus Informal Negotiations in Texas Oil and Gas Leasing," American Economic Review, American Economic Association, vol. 113(3), pages 628-663, March.
    54. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Didier Maillard, 2017. "Computation of the Corrected Cornish-Fisher Expansion using the Response Surface Methodology: Application to V aR and CV aR," THEMA Working Papers 2017-21, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    55. Yijian Huang, 2017. "Restoration of Monotonicity Respecting in Dynamic Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 613-622, April.
    56. Schaumburg, Julia, 2012. "Predicting extreme value at risk: Nonparametric quantile regression with refinements from extreme value theory," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4081-4096.
    57. Tibor Szendrei & Arnab Bhattacharjee & Mark E. Schaffer, 2024. "Fused LASSO as Non-Crossing Quantile Regression," Papers 2403.14036, arXiv.org, revised Aug 2024.
    58. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
    59. Gwennaëlle Mabon, 2017. "Adaptive Deconvolution on the Non-negative Real Line," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 707-740, September.
    60. Marc Henry & Romuald Meango & Ismael Mourifié, 2020. "Revealing Gender-Specific Costs of STEM in an Extended Roy Model of Major Choice," Working Papers 2020-035, Human Capital and Economic Opportunity Working Group.
    61. Patrick Link & Miltiadis Poursanidis & Jochen Schmid & Rebekka Zache & Martin Kurnatowski & Uwe Teicher & Steffen Ihlenfeldt, 2022. "Capturing and incorporating expert knowledge into machine learning models for quality prediction in manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 33(7), pages 2129-2142, October.
    62. Lian, Heng & Meng, Jie & Fan, Zengyan, 2015. "Simultaneous estimation of linear conditional quantiles with penalized splines," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 1-21.
    63. Lee, Ji Hyung & Park, Byoung G., 2023. "Nonparametric identification and estimation of the extended Roy model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1087-1113.
    64. Elodie Brunel & Fabienne Comte & Valentine Genon-Catalot, 2016. "Nonparametric density and survival function estimation in the multiplicative censoring model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 570-590, September.

  36. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney K. Newey, 2008. "Identification and estimation of marginal effects in nonlinear panel models," CeMMAP working papers CWP25/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Martin Browning & Jesus M. Carro, 2009. "Dynamic binary outcome models with maximal heterogeneity," Economics Series Working Papers 426, University of Oxford, Department of Economics.
    2. Ali Fakih, 2014. "Vacation Leave, Work Hours and Wages: New Evidence from Linked Employer-Employee Data," CIRANO Working Papers 2014s-40, CIRANO.
    3. 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.
    4. Ji-Liang Shiu & Yingyao Hu, 2010. "Identification and Estimation of Nonlinear Dynamic Panel Data Models with Unobserved Covariates," Economics Working Paper Archive 557, The Johns Hopkins University,Department of Economics.
    5. Ciani, Emanuele, 2012. "Informal adult care and caregivers' employment in Europe," Labour Economics, Elsevier, vol. 19(2), pages 155-164.
    6. 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.
    7. Philip Kostov & Julie Le Gallo, 2015. "Convergence: A Story of Quantiles and Spillovers," Post-Print hal-01868567, HAL.
    8. 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.
    9. Shakeeb Khan & Maria Ponomareva & Elie Tamer, 2011. "Identification of Panel Data Models with Endogenous Censoring," Working Papers 11-07, Duke University, Department of Economics.
    10. 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.
    11. 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).
    12. 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).
    13. Adam Rosen, 2009. "Set identification via quantile restrictions in short panels," CeMMAP working papers CWP26/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.

  37. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Improving Estimates Of Monotone Functions By Rearrangement," Boston University - Department of Economics - Working Papers Series WP2007-012, Boston University - Department of Economics.

    Cited by:

    1. 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.
    2. Henderson, Daniel J. & Parmeter, Christopher F., 2009. "Imposing Economic Constraints in Nonparametric Regression: Survey, Implementation and Extension," IZA Discussion Papers 4103, Institute of Labor Economics (IZA).
    3. Matthew J. Notowidigdo, 2011. "The Incidence of Local Labor Demand Shocks," NBER Working Papers 17167, National Bureau of Economic Research, Inc.
    4. 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.
    5. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2010. "Rearranging Edgeworth-Cornish-Fisher Expansions," Post-Print hal-03588300, HAL.
    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. 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.
    8. Andrew Shephard, 2011. "Equilibrium Search and Tax Credit Reform," Working Papers 1336, Princeton University, Department of Economics, Center for Economic Policy Studies..
    9. Birke, Melanie, 2008. "Shape constrained kernel density estimation," Technical Reports 2008,08, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  38. Ivan Fernandez-Val, 2007. "Fixed Effects Estimation of Structural Parameters and Marginal Effects in Panel Probit Models," Boston University - Department of Economics - Working Papers Series WP2007-009, 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. Vivian Norambuena, 2015. "Sovereign Debt Default: Are Countries Trapped by Their Own Default History?," Working Papers wp416, University of Chile, Department of Economics.
    3. Darren Grant, 2008. "Physician Financial Incentives and Cesarean Delivery: New Conclusions from the Healthcare Cost and Utilization Project," Working Papers 0801, Sam Houston State University, Department of Economics and International Business.
    4. 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.
    5. 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.
    6. Michael Anderson & Maximilian Auffhammer, 2011. "Pounds that Kill: The External Costs of Vehicle Weight," NBER Working Papers 17170, National Bureau of Economic Research, Inc.
    7. 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.
    8. Albarrán, Pedro, 2015. "Estimation of Dynamic Nonlinear Random Effects Models with Unbalanced Panels," UC3M Working papers. Economics we1503, Universidad Carlos III de Madrid. Departamento de Economía.
    9. Ji-Liang Shiu & Yingyao Hu, 2010. "Identification and Estimation of Nonlinear Dynamic Panel Data Models with Unobserved Covariates," Economics Working Paper Archive 557, The Johns Hopkins University,Department of Economics.
    10. 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.
    11. 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).
    12. 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.
    13. Chakraborty, Tanika & De, Prabal K., 2011. "Mother's Autonomy and Child Welfare: A New Measure and Some New Evidence," IZA Discussion Papers 5438, Institute of Labor Economics (IZA).
    14. Ciani, Emanuele, 2012. "Informal adult care and caregivers' employment in Europe," Labour Economics, Elsevier, vol. 19(2), pages 155-164.
    15. 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.
    16. 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.
    17. 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.
    18. Hochguertel, Stefan & Ohlsson, Henry, 2011. "Wealth mobility and dynamics over entire individual working life cycles," Working Paper Series 1301, European Central Bank.
    19. Hospido, Laura, 2010. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," IZA Discussion Papers 4712, Institute of Labor Economics (IZA).
    20. 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.
    21. 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.
    22. 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.
    23. Mr. Eugenio M Cerutti & Jihad Dagher & Mr. Giovanni Dell'Ariccia, 2015. "Housing Finance and Real-Estate Booms: A Cross-Country Perspective," IMF Staff Discussion Notes 2015/012, International Monetary Fund.
    24. 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.
    25. Salvador Gil-Pareja, 2011. "Do nonreciprocal preference regimes increase exports?," ERSA conference papers ersa11p1561, European Regional Science Association.
    26. Felix Holub & Laura Hospido & Ulrich J. Wagner, 2020. "Urban Air Pollution and Sick Leaves: Evidence From Social Security Data," CRC TR 224 Discussion Paper Series crctr224_2020_241, University of Bonn and University of Mannheim, Germany.
    27. 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.
    28. Jarko Fidrmuc & Christa Hainz, 2009. "Default Rates in the Loan Market for SMEs: Evidence from Slovakia," ifo Working Paper Series 72, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    29. Guriev, Sergei & Zhuravskaya, Ekaterina & Yakovlev, Evgeny, 2008. "Interest Group Politics in a Federation," CEPR Discussion Papers 6671, C.E.P.R. Discussion Papers.
    30. 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.
    31. Rubén Segura-Cayuela & Josep M. Vilarrubia, 2008. "The effect of foreign service on trade volumes and trade partners," Working Papers 0808, Banco de España.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. Romero Rocha & Rodrigo R. Soares, 2010. "Evaluating the impact of community‐based health interventions: evidence from Brazil's Family Health Program," Health Economics, John Wiley & Sons, Ltd., vol. 19(S1), pages 126-158, September.
    37. Kunz, J.S.; & Staub, K.E.; & Winkelmann, R.;, 2018. "Predicting fixed effects in panel probit models," Health, Econometrics and Data Group (HEDG) Working Papers 18/23, HEDG, c/o Department of Economics, University of York.
    38. Xiaoming Li, 2011. "Fixed Effects Estimation in Panel Nonlinear Fractional Response Models," Working papers 2011-11, University of Connecticut, Department of Economics.
    39. Jess Benhabib & Alejandro Corvalen & Mark M. Spiegel, 2011. "Reestablishing the income-democracy nexus," Working Paper Series 2011-09, Federal Reserve Bank of San Francisco.
    40. 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.
    41. 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).
    42. 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.
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    128. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    129. Catania, Leopoldo & Luati, Alessandra, 2023. "Semiparametric modeling of multiple quantiles," Journal of Econometrics, Elsevier, vol. 237(2).
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    176. Gah-Yi Ban & Cynthia Rudin, 2019. "The Big Data Newsvendor: Practical Insights from Machine Learning," Operations Research, INFORMS, vol. 67(1), pages 90-108, January.
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    178. Berrisch, Jonathan & Ziel, Florian, 2024. "Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1568-1586.
    179. Liwen Zhang & Huixia Judy Wang & Zhongyi Zhu, 2017. "Composite change point estimation for bent line quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 145-168, February.
    180. J. David López-Salido & Francesca Loria, 2020. "Inflation at Risk," Finance and Economics Discussion Series 2020-013, Board of Governors of the Federal Reserve System (U.S.).
    181. Yingying DONG & Ying-Ying LEE & Michael GOU, 2019. "Regression Discontinuity Designs with a Continuous Treatment," Discussion papers 19058, Research Institute of Economy, Trade and Industry (RIETI).
    182. 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).
    183. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    184. Wolf, Elias, 2023. "Estimating Growth at Risk with Skewed Stochastic Volatility Models," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277696, Verein für Socialpolitik / German Economic Association.
    185. Storti, Giuseppe & Wang, Chao, 2022. "Nonparametric expected shortfall forecasting incorporating weighted quantiles," International Journal of Forecasting, Elsevier, vol. 38(1), pages 224-239.
    186. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    187. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Non-crossing convex quantile regression," Economics Letters, Elsevier, vol. 233(C).
    188. Castagnetti, Carolina & Giorgetti, Maria Letizia, 2019. "Understanding the gender wage-gap differential between the public and private sectors in Italy: A quantile approach," Economic Modelling, Elsevier, vol. 78(C), pages 240-261.
    189. Zhongjun Qu & Jungmo Yoon, 2015. "Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs," Boston University - Department of Economics - Working Papers Series wp2015-009, Boston University - Department of Economics.
    190. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
    191. Le, Trung H., 2021. "International portfolio allocation: The role of conditional higher moments," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 33-57.
    192. Berrisch, Jonathan & Ziel, Florian, 2023. "CRPS learning," Journal of Econometrics, Elsevier, vol. 237(2).
    193. Lee, Ji Hyung & Park, Byoung G., 2023. "Nonparametric identification and estimation of the extended Roy model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1087-1113.
    194. Karthik Sriram & R. V. Ramamoorthi & Pulak Ghosh, 2016. "On Bayesian Quantile Regression Using a Pseudo-joint Asymmetric Laplace Likelihood," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(1), pages 87-104, February.
    195. Diego Chicana & Rafael Nivin, 2021. "Evaluating Growth-at-Risk as a tool for monitoring macro-financial risks in the Peruvian economy," IHEID Working Papers 07-2021, Economics Section, The Graduate Institute of International Studies.
    196. Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
    197. 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.
    198. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    199. 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.
    200. Holger Dette, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 437-441, September.
    201. Souhaib Ben Taieb & Raphael Huser & Rob J. Hyndman & Marc G. Genton, 2015. "Probabilistic time series forecasting with boosted additive models: an application to smart meter data," Monash Econometrics and Business Statistics Working Papers 12/15, Monash University, Department of Econometrics and Business Statistics.
    202. Claudia Noack, 2021. "Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption," Papers 2106.06421, arXiv.org.

  40. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Rearranging Edgeworth-Cornish-Fisher expansions," CeMMAP working papers CWP19/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. 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.
    2. Charles-Olivier Amedee-Manesme & Fabrice Barthélémy, 2012. "Cornish-Fisher expansion for real estate value at risk," ERES eres2012_044, European Real Estate Society (ERES).
    3. 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.
    4. 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.
    5. Ghossoub, Mario, 2011. "Monotone equimeasurable rearrangements with non-additive probabilities," MPRA Paper 37629, University Library of Munich, Germany, revised 23 Mar 2012.
    6. 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.
    7. 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.
    8. Fabrice Barthélémy, 2014. "Cornish-Fisher Expansion for Commercial Real Estate Value at Risk," THEMA Working Papers 2014-29, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    9. Candelon, Bertrand & Fuerst, Franz & Hasse, Jean-Baptiste, 2021. "Diversification potential in real estate portfolios," International Economics, Elsevier, vol. 166(C), pages 126-139.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Didier Maillard, 2017. "Computation of the Corrected Cornish-Fisher Expansion using the Response Surface Methodology: Application to V aR and CV aR," THEMA Working Papers 2017-21, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    16. 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.
    17. 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.

  41. 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).

    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. Koen Jochmans, 2015. "Multiplicative-error models with sample selection," SciencePo Working papers Main hal-03392990, HAL.
    3. 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.
    4. 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).
    5. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Simone BERTOLI & Jesús FERNÁNDEZ-HUERTAS MORAGA, 2014. "Visa Policies, Networks and the Cliff at the Border," Working Papers 201427, CERDI.
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. Koen Jochmans, 2023. "Bootstrap inference for fixed-effect models," French Stata Users' Group Meetings 2023 21, Stata Users Group.
    12. 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.
    13. 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.
    14. 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.
    15. Georgios Marios Chrysanthou, 2008. "Estimating Union Wage Effects in Great Britain During 1991-2003," Discussion Papers 08/12, Department of Economics, University of York.
    16. Koen Jochmans & Vincenzo Verardi, 2022. "Instrumental-Variable Estimation Of Exponential Regression Models With Two-Way Fixed Effects With An Application To Gravity Equations," Post-Print hal-03818773, HAL.
    17. Demos Antonis & Kyriakopoulou Dimitra, 2019. "Finite-Sample Theory and Bias Correction of Maximum Likelihood Estimators in the EGARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 11(1), pages 1-20, January.
    18. Marco Alderighi & Alberto A. Gaggero & Claudio A. Piga, 2014. "The effect of code-share agreements on the temporal profile of airline fares," Working Paper series 27_14, Rimini Centre for Economic Analysis.
    19. Ivan Fernandez-Val & Martin Weidner, 2014. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 32/14, Institute for Fiscal Studies.
    20. Stelios Arvanitis & Antonis Demos, 2015. "A class of indirect inference estimators: higher‐order asymptotics and approximate bias correction," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 200-241, June.
    21. Majid M. Al-Sadoon & Sergi Jiménez-Martín & Jose M. Labeaga, 2019. "Simple methods for consistent estimation of dynamic panel data sample selection models," Economics Working Papers 1631, Department of Economics and Business, Universitat Pompeu Fabra.
    22. Chen, Mingli, 2016. "Estimation of Nonlinear Panel Models with Multiple Unobserved Effects," The Warwick Economics Research Paper Series (TWERPS) 1120, University of Warwick, Department of Economics.
    23. 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.
    24. Cobo-Reyes, Ramón & Katz, Gabriel & Meraglia, Simone, 2019. "Endogenous sanctioning institutions and migration patterns: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 575-606.
    25. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and time effects in nonlinear panel models with large N, T," CeMMAP working papers 60/13, Institute for Fiscal Studies.
    26. Almer, Christian & Laurent-Lucchetti, Jérémy & oechslin, Manuel, 2011. "Income shocks and social unrest: theory and evidence," MPRA Paper 34426, University Library of Munich, Germany.
    27. Jochmans, K. & Verardi, V., 2019. "Instrumental-Variable Estimation of Gravity Equations," Cambridge Working Papers in Economics 1994, Faculty of Economics, University of Cambridge.
    28. 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.
    29. 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).
    30. 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).
    31. Ivan Fernandez-Val & Martin Weidner, 2015. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 17/15, Institute for Fiscal Studies.
    32. 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.
    33. 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.
    34. 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.
    35. Elizabeth Schroeder, 2016. "Dynamic labor supply adjustment with bias correction," Empirical Economics, Springer, vol. 51(4), pages 1623-1640, December.
    36. 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.
    37. 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.
    38. Naguib, Costanza, 2022. "Analytical bias correction for two-step fixed effects models with copula-distributed errors," Economics Letters, Elsevier, vol. 215(C).
    39. 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.
    40. 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.
    41. Christian Almer & Stefan Boes, 2012. "Climate (change) and conflict: resolving a puzzle of association and causation," Diskussionsschriften dp1203, Universitaet Bern, Departement Volkswirtschaft.

  42. 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. Martin Browning & Jesus Carro, 2006. "Heterogeneity and Microeconometrics Modelling," CAM Working Papers 2006-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    2. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile And Probability Curves Without Crossing," Boston University - Department of Economics - Working Papers Series WP2007-011, Boston University - Department of Economics.
    3. Hospido, Laura, 2010. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," IZA Discussion Papers 4712, Institute of Labor Economics (IZA).
    4. 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.
    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. 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.
    7. Manuel Arellano & Jinyong Hahn, 2005. "Understanding Bias in Nonlinear Panel Models: Some Recent Developments," Working Papers wp2005_0507, CEMFI.
    8. 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.
    9. 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.

  43. 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. 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. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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.

  44. 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. 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.
    2. Lee, Tae-Hwy & Ullah, Aman & Wang, He, 2018. "The second-order bias of quantile estimators," Economics Letters, Elsevier, vol. 173(C), pages 143-147.
    3. 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).
    4. 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.
    5. Andini, Corrado, 2017. "Tertiary Education for All and Wage Inequality: Policy Insights from Quantile Regression," IZA Policy Papers 132, Institute of Labor Economics (IZA).
    6. 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.
    7. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    8. 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.
    9. 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.
    10. Javier Alejo & Antonio F. Galvao & Julian Martinez-Iriarte & Gabriel Montes-Rojas, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Papers 2301.07241, arXiv.org, revised Dec 2023.
    11. 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.
    12. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012. "Some New Asymptotic Theory for Least Squares Series: Pointwise and Uniform Results," Papers 1212.0442, arXiv.org, revised Jun 2015.
    13. Du, Zaichao & Escanciano, Juan Carlos & Zhu, Guangwei, 2023. "The case for CASE: Estimating heterogeneous systemic effects," Journal of Banking & Finance, Elsevier, vol. 157(C).
    14. 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.
    15. 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.
    16. 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.
    17. Bargain, Olivier B. & Melly, Blaise, 2008. "Public Sector Pay Gap in France: New Evidence Using Panel Data," IZA Discussion Papers 3427, Institute of Labor Economics (IZA).
    18. George J. Borjas & Rachel M. Friedberg, 2009. "Recent Trends in the Earnings of New Immigrants to the United States," NBER Working Papers 15406, National Bureau of Economic Research, Inc.
    19. Clément de Chaisemartin & Xavier d'Haultfoeuille, 2014. "Fuzzy Changes-in-Changes," Working Papers 2014-18, Center for Research in Economics and Statistics.
    20. 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.
    21. Gindling,T. H. & Hasnain,Zahid & Newhouse,David Locke & Shi,Rong, 2019. "Are Public Sector Workers in Developing Countries Overpaid ? Evidence from a New Global Data Set," Policy Research Working Paper Series 8754, The World Bank.
    22. Natalya Presman & Tanya Suhoy, 2024. "How have government housing programs affected developers' bids in Israel Land Authority land tenders?," Bank of Israel Working Papers 2024.08, Bank of Israel.
    23. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2012. "Inference on counterfactual distributions," CeMMAP working papers 05/12, Institute for Fiscal Studies.
    24. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    25. Marco LILLA, 2008. "Income Inequality and Education from ECHP data," Working Papers 311, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    26. Domenico Depalo & Raffaella Giordano, 2011. "The public-private pay gap: a robust quantile approach," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 70(1), pages 25-64, January.
    27. Guillaume Carlier & Victor Chernozhukov & Alfred Galichon, 2014. "Vector quantile regression," CeMMAP working papers 48/14, Institute for Fiscal Studies.
    28. Michal Franta, 2023. "The Application of Multiple-Output Quantile Regression on the US Financial Cycle," Working Papers 2023/2, Czech National Bank.
    29. Simona Mateut & Thanaset Chevapatrakul, 2017. "Customer financing, bargaining power and trade credit uptake," Discussion Papers 2017/04, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    30. Samantha Leorato & Franco Peracchi, 2015. "Shape Regressions," EIEF Working Papers Series 1506, Einaudi Institute for Economics and Finance (EIEF), revised Jul 2015.
    31. Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.
    32. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    33. Feng, Andy & Graetz, Georg, 2015. "Rise of the Machines: The Effects of Labor-Saving Innovations on Jobs and Wages," IZA Discussion Papers 8836, Institute of Labor Economics (IZA).
    34. Chunbei Wang & Le Wang, 2011. "Language Skills and the Earnings Distribution Among Child Immigrants," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 50(2), pages 297-322, April.
    35. Andrew Chesher, 2017. "Understanding the effect of measurement error on quantile regressions," CeMMAP working papers CWP19/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Alexandre Belloni & Victor Chernozhukov, 2011. "High Dimensional Sparse Econometric Models: An Introduction," Papers 1106.5242, arXiv.org, revised Sep 2011.
    37. Ion Zgreaban, Irina, 2013. "Education in Romania - How much is it Worth?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 149-163, March.
    38. David M. Kaplan & Matt Goldman, 2013. "IDEAL Quantile Inference via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1315, Department of Economics, University of Missouri.
    39. Fong, Wai Mun, 2013. "Footprints in the market: Hedge funds and the carry trade," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 41-59.
    40. Tjeerd de Vries, 2021. "A Tale of Two Tails: A Model-free Approach to Estimating Disaster Risk Premia and Testing Asset Pricing Models," Papers 2105.08208, arXiv.org, revised Oct 2023.
    41. Junho Lee & Ying Sun & Huixia Judy Wang, 2021. "Spatial cluster detection with threshold quantile regression," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    42. Clément de Chaisemartin, 2012. "Fuzzy differences in differences," Working Papers halshs-00671368, HAL.
    43. Parker, Thomas, 2019. "Asymptotic inference for the constrained quantile regression process," Journal of Econometrics, Elsevier, vol. 213(1), pages 174-189.
    44. Dolado, Juan J & Chen, Liang & Gonzalo, Jesus, 2018. "Quantile Factor Models," CEPR Discussion Papers 12716, C.E.P.R. Discussion Papers.
    45. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar Wüthrich, 2017. "Generic inference on quantile and quantile effect functions for discrete outcomes," CeMMAP working papers CWP23/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    46. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile And Probability Curves Without Crossing," Boston University - Department of Economics - Working Papers Series WP2007-011, Boston University - Department of Economics.
    47. Grimpe, Christoph & Kaiser, Ulrich & Sofka, Wolfgang, 2018. "Innovating for the Better? The Role of Advocacy Group Work Experience for Employee Pay," IZA Discussion Papers 11649, Institute of Labor Economics (IZA).
    48. Evangelia Papapetrou & Pinelopi Tsalaporta, 2017. "Inter-Industry Wage Differentials in Greece: Evidence from Quantile Regression Analysis," International Economic Journal, Taylor & Francis Journals, vol. 31(1), pages 51-67, January.
    49. J. Carlos Escanciano & Carlos Velasco, 2010. "Specification tests of parametric dynamic conditional quantiles," Post-Print hal-00732534, HAL.
    50. Franco Peracchi & Andrei V. Tanase, 2008. "On estimating the conditional expected shortfall," CEIS Research Paper 122, Tor Vergata University, CEIS, revised 14 Jul 2008.
    51. 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.
    52. Marilena Furno, 2011. "Goodness of Fit and Misspecification in Quantile Regressions," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 105-131, February.
    53. Li, Ming-Yuan Leon, 2009. "Value or volume strategy?," Finance Research Letters, Elsevier, vol. 6(4), pages 210-218, December.
    54. Wiji Arulampalam & Alison Booth & Mark L. Bryan, 2006. "Are there Asymmetries in the Effects of Training on the Conditional Male Wage Distribution?," CEPR Discussion Papers 523, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    55. Arie Beresteanu, 2020. "Quantile Regression with Interval Data," Working Paper 6899, Department of Economics, University of Pittsburgh.
    56. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Iv'an Fern'andez-Val, 2011. "Conditional Quantile Processes based on Series or Many Regressors," Papers 1105.6154, arXiv.org, revised Aug 2018.
    57. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Quantile Random-Coefficient Regression with Interactive Fixed Effects: Heterogeneous Group-Level Policy Evaluation," Papers 2208.03632, arXiv.org, revised Nov 2024.
    58. Bruce E. Hansen & Seojeong Lee, 2021. "Inference for Iterated GMM Under Misspecification," Econometrica, Econometric Society, vol. 89(3), pages 1419-1447, May.
    59. Boudarbat, Brahim & Lemieux, Thomas & Riddell, W. Craig, 2010. "The Evolution of the Returns to Human Capital in Canada, 1980-2005," CLSSRN working papers clsrn_admin-2010-2, Vancouver School of Economics, revised 30 Jan 2010.
    60. Lembcke, Alexander C. & Kohn, Karsten & Fitzenberger, Bernd, 2008. "Union Density and Varieties of Coverage: The Anatomy of Union Wage Effects in Germany," ZEW Discussion Papers 08-012, ZEW - Leibniz Centre for European Economic Research.
    61. Le-Yu Chen & Yu-Min Yen, 2021. "Estimations of the Local Conditional Tail Average Treatment Effect," Papers 2109.08793, arXiv.org, revised May 2024.
    62. Ying-Ying Lee, 2015. "Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification," Econometrics, MDPI, vol. 4(1), pages 1, December.
    63. 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.
    64. Zishu Zhan & Yang Li & Yuhong Yang & Cunjie Lin, 2023. "Model averaging for semiparametric varying coefficient quantile regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(4), pages 649-681, August.
    65. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
    66. Jun, Sung Jae, 2009. "Local structural quantile effects in a model with a nonseparable control variable," Journal of Econometrics, Elsevier, vol. 151(1), pages 82-97, July.
    67. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.
    68. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
    69. Zequn Jin & Lihua Lin & Zhengyu Zhang, 2022. "Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives," Papers 2211.07903, arXiv.org.
    70. Machado, José A.F. & Santos Silva, J.M.C. & Wei, Kehai, 2016. "Quantiles, corners, and the extensive margin of trade," European Economic Review, Elsevier, vol. 89(C), pages 73-84.
    71. Furno, Marilena, 2013. "Quantile regression and structural change in the Italian wage equation," Economic Modelling, Elsevier, vol. 30(C), pages 420-434.
    72. Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly, 2019. "Fast Algorithms for the Quantile Regression Process," Papers 1909.05782, arXiv.org, revised Apr 2020.
    73. Jurecková, Jana & Picek, Jan & Saleh, A.K.Md. Ehsanes, 2010. "Rank tests and regression rank score tests in measurement error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3108-3120, December.
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    80. 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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    82. Olivier Bargain & Prudence Kwenda, 2010. "Is Informality Bad? - Evidence from Brazil, Mexico and South Africa," Working Papers 201003, School of Economics, University College Dublin.
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    85. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2013. "Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes," SOEPpapers on Multidisciplinary Panel Data Research 572, DIW Berlin, The German Socio-Economic Panel (SOEP).
    86. Jerry Hausman & Haoyang Liu & Ye Luo & Christopher Palmer, 2021. "Errors in the Dependent Variable of Quantile Regression Models," Econometrica, Econometric Society, vol. 89(2), pages 849-873, March.
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    89. 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.
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    91. 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).
    92. Liang, Che-Yuan, 2018. "Taxes and Household Labor Supply: Estimating Distributional Effects of Nonlinear Prices on Multidimensional Choice," Working Paper Series 2018:2, Uppsala University, Department of Economics.
    93. Wang, Le, 2011. "How Does Education Affect the Earnings Distribution in Urban China?," IZA Discussion Papers 6173, Institute of Labor Economics (IZA).
    94. Katarzyna Burzynska & Olle Berggren, 2015. "The Impact of Social Beliefs on Microfinance Performance," Journal of International Development, John Wiley & Sons, Ltd., vol. 27(7), pages 1074-1097, October.
    95. Tatsushi Oka & Ken Yamada, 2019. "Heterogeneous Impact of the Minimum Wage: Implications for Changes in Between- and Within-group Inequality," Papers 1903.03925, arXiv.org, revised Jul 2019.
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    107. DePaula, Guilherme, 2020. "The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
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    124. Sherrilyn Billger & Carlos Lamarche, 2015. "A panel data quantile regression analysis of the immigrant earnings distribution in the United Kingdom and United States," Empirical Economics, Springer, vol. 49(2), pages 705-750, September.
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    176. 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.
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    178. Weifeng Jin, 2023. "Quantile Autoregression-based Non-causality Testing," Papers 2301.02937, arXiv.org.
    179. 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.
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    183. Kato, Kengo, 2009. "Asymptotics for argmin processes: Convexity arguments," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1816-1829, September.
    184. Akanksha Negi, 2020. "Doubly weighted M-estimation for nonrandom assignment and missing outcomes," Papers 2011.11485, arXiv.org.
    185. L. Leoncini & F. Rentocchini, 2010. "Counteracting cocaine production. An analysis based on a novel dataset," Working Papers 693, Dipartimento Scienze Economiche, Universita' di Bologna.
    186. Wolfgang Sofka & Christoph Grimpe & Ulrich Kaiser, 2022. "Understanding the unwritten rules of the game: Government work experience and salary premiums in foreign MNC subsidiaries," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 53(6), pages 1110-1132, August.
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    198. 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.
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  45. 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. Wiji Arulampalam & Alison Booth & Mark L. Bryan, 2006. "Are there Asymmetries in the Effects of Training on the Conditional Male Wage Distribution?," CEPR Discussion Papers 523, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    2. Lembcke, Alexander C. & Kohn, Karsten & Fitzenberger, Bernd, 2008. "Union Density and Varieties of Coverage: The Anatomy of Union Wage Effects in Germany," ZEW Discussion Papers 08-012, ZEW - Leibniz Centre for European Economic Research.
    3. 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.
    4. 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.
    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.

  46. Iván Fernández-Val & Joonhwan Lee, "undated". "Panel Data Models with Nonadditive Unobserved Heterogeneity: Estimation and Inference," Boston University - Department of Economics - Working Papers Series wp2010-001, 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. Ivan Fernandez-Val & Martin Weidner, 2018. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP22/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    4. Xiao, Jiaqi & Juodis, Arturas & Karavias, Yiannis & Sarafidis, Vasilis, 2021. "Improved Tests for Granger Non-Causality in Panel Data," MPRA Paper 107180, University Library of Munich, Germany.
    5. 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).
    6. Torben G. Andersen & Nicola Fusari & Viktor Todorov & Rasmus T. Varneskov, 2018. "Unified Inference for Nonlinear Factor Models from Panels with Fixed and Large Time Span," CREATES Research Papers 2018-03, Department of Economics and Business Economics, Aarhus University.
    7. Santiago Pereda-Fernández, 2021. "Copula-Based Random Effects Models for Clustered Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 575-588, March.
    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. Jochmans, Koen & Weidner, Martin, 2021. "Inference On A Distribution From Noisy Draws," TSE Working Papers 21-1275, Toulouse School of Economics (TSE).
    10. Michael Bates & Seolah Kim, 2019. "Estimating the Price Elasticity of Gasoline Demand in Correlated Random Coefficient Models with Endogeneity," Working Papers 202021, University of California at Riverside, Department of Economics, revised Jul 2020.
    11. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    12. Ivan Fernandez-Val & Martin Weidner, 2014. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 32/14, Institute for Fiscal Studies.
    13. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    14. Juodis, Arturas & Karavias, Yiannis & Sarafidis, Vasilis, 2020. "A Homogeneous Approach to Testing for Granger Non-Causality in Heterogeneous Panels," MPRA Paper 102992, University Library of Munich, Germany.
    15. Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
    16. Koen Jochmans, 2017. "Two-Way Models for Gravity," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 478-485, July.
    17. Ivan Fernandez-Val & Martin Weidner, 2015. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 17/15, Institute for Fiscal Studies.
    18. 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.
    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.
    21. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.

  47. 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. 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.
    2. 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.
    3. Pravin K. Trivedi, 2010. "Keynote lecture: Estimation of count-data panel models," Mexican Stata Users' Group Meetings 2010 06, Stata Users Group.

  48. 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. 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.
    3. 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.
    4. David Powell, 2010. "Unconditional Quantile Treatment Effects in the Presence of Covariates," Working Papers WR-816, RAND Corporation.
    5. 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.
    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. Adam Rosen, 2009. "Set identification via quantile restrictions in short panels," CeMMAP working papers CWP26/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    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. 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. 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.
    3. 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.
    4. Ignacio Garr'on & C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "International vulnerability of inflation," Papers 2410.20628, arXiv.org, revised Oct 2024.
    5. Santiago Pereda-Fern'andez, 2024. "Fast Algorithms for Quantile Regression with Selection," Papers 2402.16693, arXiv.org.
    6. 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.
    7. 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.
    8. 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).
    9. Fernando Rios-Avila & Gustavo Canavire-Bacarreza & Flavia Sacco-Capurro, 2024. "Recovering income distribution in the presence of interval-censored data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 22(4), pages 1039-1060, December.
    10. Garrón Vedia, Ignacio & Rodríguez Caballero, Carlos Vladimir, 2024. "International vulnerability of inflation," DES - Working Papers. Statistics and Econometrics. WS 44814, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. 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.
    12. Borgen, Nicolai T. & Haupt, Andreas & Wiborg, Øyvind N., 2021. "A New Framework for Estimation of Unconditional Quantile Treatment Effects: The Residualized Quantile Regression (RQR) Model," SocArXiv 42gcb_v1, Center for Open Science.

  2. 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. Hao, Meiling & Lin, Yuanyuan & Shen, Guohao & Su, Wen, 2023. "Nonparametric inference on smoothed quantile regression process," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    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. 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. 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.

  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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," Department of Economics Working Papers 2020-14, McMaster University.
    2. Bo E. Honor'e & Chris Muris & Martin Weidner, 2021. "Dynamic Ordered Panel Logit Models," Papers 2107.03253, arXiv.org, revised Apr 2024.
    3. 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.

  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  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. Grönqvist, Hans & Hall, Caroline, 2013. "Education policy and early fertility: Lessons from an expansion of upper secondary schooling," Economics of Education Review, Elsevier, vol. 37(C), pages 13-33.
    2. 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.
    3. 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.
    4. 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.
    5. Rachel Heath & A. Mushfiq Mobarak, 2014. "Manufacturing Growth and the Lives of Bangladeshi Women," NBER Working Papers 20383, National Bureau of Economic Research, Inc.
    6. 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.
    7. 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.
    8. 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).
    9. 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.
    10. Bütikofer, Aline & Coy, Deirdre & Doyle, Orla & Ginja, Rita, 2024. "The Consequences of Miscarriage on Parental Investments," IZA Discussion Papers 16858, Institute of Labor Economics (IZA).
    11. Kevin Lang Jr. & Russell Weinstein Jr., 2015. "The Consequences of Teenage Childbearing before Roe v. Wade," American Economic Journal: Applied Economics, American Economic Association, vol. 7(4), pages 169-197, October.
    12. Berthelon, Matias & Kruger, Diana, 2014. "The Impact of Adolescent Motherhood on Education in Chile," IZA Discussion Papers 8072, Institute of Labor Economics (IZA).
    13. 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.
    14. 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.
    15. Basu, Shubhashrita & Gorry, Devon, 2021. "Consequences of teenage childbearing on child health," Economics & Human Biology, Elsevier, vol. 42(C).
    16. Andrew Beauchamp, 2012. "Abortion Costs, Separation and Non-Marital Childbearing," Boston College Working Papers in Economics 812, Boston College Department of Economics.
    17. 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).
    18. 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.
    19. Kelly, Andrea & Lindo, Jason M. & Packham, Analisa, 2020. "The power of the IUD: Effects of expanding access to contraception through Title X clinics," Journal of Public Economics, Elsevier, vol. 192(C).
    20. Danielle H. Sandler & Lisa Schulkind, 2016. "The Timing of Teenage Births: Estimating the Effect on High School Graduation and Later Life Outcomes," Working Papers 16-39, Center for Economic Studies, U.S. Census Bureau.
    21. Herrera Catalina & E. Sahn David, 2017. "Working Paper 281 - Early Childbearing, School Attainment and Cognitive Skills," Working Paper Series 2398, African Development Bank.
    22. 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.
    23. 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.
    24. Fletcher, Jason M. & Polos, Jessica, 2017. "Nonmarital and Teen Fertility," IZA Discussion Papers 10833, Institute of Labor Economics (IZA).
    25. 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.
    26. 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.
    27. 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.
    28. Guldi, Melanie, 2016. "Title IX and the education of teen mothers," Economics of Education Review, Elsevier, vol. 55(C), pages 103-116.
    29. 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.
    30. 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).
    31. Devon Gorry, 2019. "Heterogeneous Consequences of Teenage Childbearing," Demography, Springer;Population Association of America (PAA), vol. 56(6), pages 2147-2168, December.
    32. 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.
    33. Rosenbaum, Philip, 2020. "Does early childbearing matter? New approach using Danish register data," Labour Economics, Elsevier, vol. 65(C).
    34. 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.
    35. 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).
    36. Melissa Schettini Kearney & Phillip B. Levine, 2012. "Why is the Teen Birth Rate in the United States so High and Why Does it Matter?," NBER Working Papers 17965, National Bureau of Economic Research, Inc.
    37. Philip Verwimp, 2016. "Secondary School as a Contraceptive: Quasi-Experimental Evidence from Burundi," Working Papers ECARES ECARES 2016-19, ULB -- Universite Libre de Bruxelles.
    38. 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).
    39. Deza, Monica, 2019. "Graduated driver licensing and teen fertility," Economics & Human Biology, Elsevier, vol. 35(C), pages 51-62.
    40. 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).
    41. 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.
    42. Nuevo-Chiquero, Ana, 2014. "The labor force effects of unplanned childbearing," Labour Economics, Elsevier, vol. 29(C), pages 91-101.
    43. 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.
    44. Markussen, Simen & Strøm, Marte, 2015. "The Effects of Motherhood," Memorandum 19/2015, Oslo University, Department of Economics.
    45. Dana Rotz & Brian Goesling & Hande Inanc & Gregory Chojnacki, "undated". "Economic Benefits of Delayed Sexual Activity," Mathematica Policy Research Reports 248b878cd4254142ac8c13102, Mathematica Policy Research.
    46. 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).
    47. 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.
    48. 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.
    49. 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.
    50. 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.

  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. Iván Fernández Val, 2003. "Household labor supply: evidence for Spain," Investigaciones Economicas, Fundación SEPI, vol. 27(2), pages 239-275, May.

    Cited by:

    1. Peichl, Andreas & Bargain, Olivier & Orsini, Kristian, 2011. "Labor supply elasticities in Europe and the US," EUROMOD Working Papers EM1/11, EUROMOD at the Institute for Social and Economic Research.
    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. 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.
    4. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2012. "Comparing Labor Supply Elasticities in Europe and the US: New Results," Working Papers halshs-00805736, HAL.
    5. 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.
    6. 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.
    7. 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.
    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. 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.

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. Mendolia, Silvia & Paloyo, Alfredo R. & Walker, Ian, 2016. "Heterogeneous effects of high school peers on educational outcomes," Ruhr Economic Papers 612, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    2. Fack, Gabrielle & Landais, Camille, 2016. "The effect of tax enforcement on tax elasticities: evidence from charitable contributions in France," LSE Research Online Documents on Economics 64578, London School of Economics and Political Science, LSE Library.
    3. Richard T. Melstrom & Deshamithra H. W. Jayasekera, 2017. "Two-Stage Estimation to Control for Unobservables in a Recreation Demand Model with Unvisited Sites," Land Economics, University of Wisconsin Press, vol. 93(2), pages 328-341.
    4. 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.
    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. 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.
    7. Martin Falk & Eva Hagsten, 2014. "Output growth and prices of establishments in the Swedish lodging industry," ERSA conference papers ersa14p360, European Regional Science Association.
    8. 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.

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