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Denis Nekipelov

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. Denis Nekipelov & Vira Semenova & Vasilis Syrgkanis, 2018. "Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models," Papers 1806.04823, arXiv.org, revised Sep 2021.

    Cited by:

    1. Khashayar Khosravi & Greg Lewis & Vasilis Syrgkanis, 2019. "Non-Parametric Inference Adaptive to Intrinsic Dimension," Papers 1901.03719, arXiv.org, revised Jun 2019.
    2. Sookyo Jeong & Hongseok Namkoong, 2020. "Assessing External Validity Over Worst-case Subpopulations," Papers 2007.02411, arXiv.org, revised Feb 2022.
    3. Dylan J. Foster & Vasilis Syrgkanis, 2019. "Orthogonal Statistical Learning," Papers 1901.09036, arXiv.org, revised Jun 2023.

  2. Sam Asher & Denis Nekipelov & Paul Novosad & Stephen P. Ryan, 2016. "Classification Trees for Heterogeneous Moment-Based Models," NBER Working Papers 22976, National Bureau of Economic Research, Inc.

    Cited by:

    1. Timmins, Christopher & Vissing, Ashley, 2022. "Environmental justice and Coasian bargaining: The role of race, ethnicity, and income in lease negotiations for shale gas," Journal of Environmental Economics and Management, Elsevier, vol. 114(C).
    2. Miller, Steve, 2020. "Causal forest estimation of heterogeneous and time-varying environmental policy effects," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    3. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    4. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    5. Daria Loginova & Stefan Mann, 2023. "Measuring stability and structural breaks: Applications in social sciences," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 302-320, April.

  3. Anna Kormilitsina & Denis Nekipelov, 2015. "Consistent Variance of the Laplace Type Estimators: Application to DSGE Models," Departmental Working Papers 1510, Southern Methodist University, Department of Economics.

    Cited by:

    1. Atsushi Inoue & Mototsugu Shintani, 2018. "Quasi‐Bayesian model selection," Quantitative Economics, Econometric Society, vol. 9(3), pages 1265-1297, November.
    2. Guerron-Quintana, Pablo & Inoue, Atsushi & Kilian, Lutz, 2017. "Impulse response matching estimators for DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 144-155.
    3. Rubio-Ramírez, Juan Francisco & Schorfheide, Frank & Fernández-Villaverde, Jesús, 2015. "Solution and Estimation Methods for DSGE Models," CEPR Discussion Papers 11032, C.E.P.R. Discussion Papers.

  4. Patrick Bajari & Victor Chernozhukov & Han Hong & Denis Nekipelov, 2015. "Identification and Efficient Semiparametric Estimation of a Dynamic Discrete Game," NBER Working Papers 21125, National Bureau of Economic Research, Inc.

    Cited by:

    1. Cook, Jonathan A. & Lin, C.-Y. Cynthia, 2015. "Wind Turbine Shutdowns and Upgrades in Denmark: Timing Decisions and the Impact of Government Policy," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 204960, Agricultural and Applied Economics Association.
    2. Jackson Bunting, 2022. "Continuous permanent unobserved heterogeneity in dynamic discrete choice models," Papers 2202.03960, arXiv.org, revised Feb 2024.
    3. Taiga Tsubota, 2021. "Identifying Dynamic Discrete Choice Models with Hyperbolic Discounting," Papers 2111.10721, arXiv.org, revised Oct 2024.
    4. Evgeny Yakovlev, 2016. "Demand for Alcohol Consumption and Implication for Mortality: Evidence from Russia," Working Papers w0221, Center for Economic and Financial Research (CEFIR).
    5. Jaap H. Abbring & Jeffrey R. Campbell & Jan Tilly & Nan Yang, 2018. "Very Simple Markov-Perfect Industry Dynamics: Empirics," Working Paper Series WP-2018-17, Federal Reserve Bank of Chicago.
    6. Abbring, Jaap & Daljord, Øystein, 2016. "Identifying the Discount Factor in Dynamic Discrete Choice Models," CEPR Discussion Papers 11133, C.E.P.R. Discussion Papers.
    7. Song Yao & Carl F. Mela, 2011. "A Dynamic Model of Sponsored Search Advertising," Marketing Science, INFORMS, vol. 30(3), pages 447-468, 05-06.
    8. Haitian Xie, 2020. "Efficient and Robust Estimation of the Generalized LATE Model," Papers 2001.06746, arXiv.org, revised Feb 2022.
    9. Abbring, Jaap & Campbell, J.R. & Tilly, J. & Yang, N., 2018. "Very Simple Markov-Perfect Industry Dynamics (revision of 2017-021) : Empirics," Other publications TiSEM 3a12f099-900b-44ac-b692-a, Tilburg University, School of Economics and Management.
    10. Zhaohui (Zoey) Jiang & Yan Huang & Damian R. Beil, 2022. "The Role of Feedback in Dynamic Crowdsourcing Contests: A Structural Empirical Analysis," Management Science, INFORMS, vol. 68(7), pages 4858-4877, July.
    11. A. Ronald Gallant & Han Hong & Ahmed Khwaja, 2018. "The Dynamic Spillovers of Entry: An Application to the Generic Drug Industry," Management Science, INFORMS, vol. 64(3), pages 1189-1211, March.
    12. Rojas Valdes, Ruben I. & Lin Lawell, C.-Y. Cynthia & Taylor, J. Edward, 2017. "The Dynamic Migration Game: A Structural Econometric Model and Application to Rural Mexico," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259184, Agricultural and Applied Economics Association.
    13. Lawell, Cynthia Lin & Yi, Fujin & Thome, Karen E, 2017. "The Effects of Subsidies and Mandates: A Dynamic Model of the Ethanol Industry," Institute of Transportation Studies, Working Paper Series qt73n0t4pv, Institute of Transportation Studies, UC Davis.
    14. Kheiravar, Khaled H, 2019. "Economic and Econometric Analyses of the World Petroleum Industry, Energy Subsidies, and Air Pollution," Institute of Transportation Studies, Working Paper Series qt3gj151w9, Institute of Transportation Studies, UC Davis.

  5. Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Demand Estimation with Machine Learning and Model Combination," NBER Working Papers 20955, National Bureau of Economic Research, Inc.

    Cited by:

    1. Krüger, Jens J. & Rhiel, Mathias, 2016. "Determinants of ICT infrastructure: A cross-country statistical analysis," Darmstadt Discussion Papers in Economics 228, Darmstadt University of Technology, Department of Law and Economics.
    2. 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.
    3. 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.
    4. Pierre Dodin & Jingyi Xiao & Yossiri Adulyasak & Neda Etebari Alamdari & Lea Gauthier & Philippe Grangier & Paul Lemaitre & William L. Hamilton, 2023. "Bombardier Aftermarket Demand Forecast with Machine Learning," Interfaces, INFORMS, vol. 53(6), pages 425-445, November.
    5. Erik Nelson & John Fitzgerald & Nathan Tefft, 2019. "The distributional impact of a green payment policy for organic fruit," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-25, February.
    6. Adam N. Smith & Jim E. Griffin, 2023. "Shrinkage priors for high-dimensional demand estimation," Quantitative Marketing and Economics (QME), Springer, vol. 21(1), pages 95-146, March.
    7. Pédussel Wu, Jennifer & Metzger, Martina & Neira, Ignacio Silva & Farroukh, Arafet, 2023. "What determines demand for digital community currencies? OurVillage in Cameroon," IPE Working Papers 209/2023, Berlin School of Economics and Law, Institute for International Political Economy (IPE).
    8. Evgeniy M. Ozhegov & Alina Ozhegova, 2017. "Regression Tree Model for Analysis of Demand with Heterogeneity and Censorship," HSE Working papers WP BRP 174/EC/2017, National Research University Higher School of Economics.
    9. Green, Gareth & Richards, Timothy, 2016. "Interpreting Results of Demand Estimation from Machine Learning Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236147, Agricultural and Applied Economics Association.
    10. Adam N. Smith & Peter E. Rossi & Greg M. Allenby, 2019. "Inference for Product Competition and Separable Demand," Marketing Science, INFORMS, vol. 38(4), pages 690-710, July.
    11. Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Machine Learning Methods for Demand Estimation," American Economic Review, American Economic Association, vol. 105(5), pages 481-485, May.
    12. Raval, Devesh & Rosenbaum, Ted & Wilson, Nathan E., 2021. "How do machine learning algorithms perform in predicting hospital choices? evidence from changing environments," Journal of Health Economics, Elsevier, vol. 78(C).

  6. Patrick Bajari & Chenghuan Sean Chu & Denis Nekipelov & Minjung Park, 2013. "A Dynamic Model of Subprime Mortgage Default: Estimation and Policy Implications," NBER Working Papers 18850, National Bureau of Economic Research, Inc.

    Cited by:

    1. Sauro Mocetti & Eliana Viviano, 2015. "Looking behind mortgage delinquencies," Temi di discussione (Economic working papers) 999, Bank of Italy, Economic Research and International Relations Area.
    2. Hanming Fang & You Suk Kim & Wenli Li, 2016. "The dynamics of subprime adjustable-rate mortgage default: a structural estimation," Working Papers 16-2, Federal Reserve Bank of Philadelphia.
    3. Hanming Fang & You Suk Kim & Wenli Li, 2015. "The Dynamics of Adjustable-Rate Subprime Mortgage Default: A Structural Estimation," PIER Working Paper Archive 15-041, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Dec 2015.
    4. Diego Avanzini & Juan Francisco Martínez & Víctor Pérez, 2016. "A micro-powered model of mortgage default risk for full recourse economies, with an application to the case of Chile," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Combining micro and macro data for financial stability analysis, volume 41, Bank for International Settlements.
    5. Thomas P. Boehm & Alan M. Schlottmann, 2017. "Mortgage Payment Problem Development and Recovery: A Joint Probability Model Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 55(4), pages 476-510, November.
    6. Wenli Li & Florian Oswald, 2014. "Recourse and residential mortgages: the case of Nevada," Working Papers 15-2, Federal Reserve Bank of Philadelphia.
    7. Seyed Morteza Emadi & Bradley R. Staats, 2020. "A Structural Estimation Approach to Study Agent Attrition," Management Science, INFORMS, vol. 66(9), pages 4071-4095, September.
    8. Richard Chamboko & Jorge Miguel Bravo, 2020. "A Multi-State Approach to Modelling Intermediate Events and Multiple Mortgage Loan Outcomes," Risks, MDPI, vol. 8(2), pages 1-29, June.

  7. Shakeeb Khan & Denis Nekipelov, 2013. "On Uniform Inference in Nonlinear Models with Endogeneity," Working Papers 13-16, Duke University, Department of Economics.

    Cited by:

    1. Timothy B. Armstrong & Michal Koles'ar, 2017. "Finite-Sample Optimal Estimation and Inference on Average Treatment Effects Under Unconfoundedness," Papers 1712.04594, arXiv.org, revised Jan 2021.
    2. Khan, Shakeeb & Nekipelov, Denis, 2024. "On uniform inference in nonlinear models with endogeneity," Journal of Econometrics, Elsevier, vol. 240(2).
    3. Christoph Rothe, 2017. "Robust Confidence Intervals for Average Treatment Effects Under Limited Overlap," Econometrica, Econometric Society, vol. 85, pages 645-660, March.
    4. D’Amour, Alexander & Ding, Peng & Feller, Avi & Lei, Lihua & Sekhon, Jasjeet, 2021. "Overlap in observational studies with high-dimensional covariates," Journal of Econometrics, Elsevier, vol. 221(2), pages 644-654.

  8. Tatiana V. Komarova & Denis Nekipelov & Evgeny Yakovlev, 2011. "Identification, data combination and the risk of disclosure," CeMMAP working papers CWP38/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Komarova, Tatiana & Nekipelov, Denis & Al Rafi, Ahnaf & Yakovlev, Evgeny, 2017. "K-anonymity: a note on the trade-off between data utility and data security," LSE Research Online Documents on Economics 85923, London School of Economics and Political Science, LSE Library.
    2. Tatiana Komarova & Denis Nekipelov, 2020. "Identification and Formal Privacy Guarantees," Papers 2006.14732, arXiv.org, revised May 2021.
    3. David Pacini, 2012. "Least Square Linear Prediction with Two-Sample Data," Bristol Economics Discussion Papers 12/631, School of Economics, University of Bristol, UK.

  9. Shakeeb Khan & Denis Nekipelov, 2011. "Information Structure and Statistical Information in Discrete Response Models," Working Papers 11-19, Duke University, Department of Economics.

    Cited by:

    1. Arthur Lewbel & Xun Tang, 2012. "Identification and Estimation of Games with Incomplete Information Using Excluded Regressors," Boston College Working Papers in Economics 808, Boston College Department of Economics, revised 05 Mar 2013.
    2. Hoshino, Tadao & Yanagi, Takahide, 2023. "Treatment effect models with strategic interaction in treatment decisions," Journal of Econometrics, Elsevier, vol. 236(2).
    3. Khan, Shakeeb & Maurel, Arnaud & Zhang, Yichong, 2020. "Informational Content of Factor Structures in Simultaneous Binary Response Models," IZA Discussion Papers 14008, Institute of Labor Economics (IZA).
    4. Kanaya, Shin & Taylor, Luke, 2020. "Type I and Type II Error Probabilities in the Courtroom," MPRA Paper 100217, University Library of Munich, Germany.
    5. Khan, Shakeeb & Nekipelov, Denis, 2024. "On uniform inference in nonlinear models with endogeneity," Journal of Econometrics, Elsevier, vol. 240(2).
    6. Shakeeb Khan & Denis Nekipelov, 2019. "On Uniform Inference in Nonlinear Models with Endogeneity," Boston College Working Papers in Economics 986, Boston College Department of Economics.
    7. Yingying Dong & Arthur Lewbel, 2012. "A Simple Estimator for Binary Choice Models With Endogenous Regressors," Boston College Working Papers in Economics 807, Boston College Department of Economics.
    8. Arthur Lewbel, 2012. "An Overview of the Special Regressor Method," Boston College Working Papers in Economics 810, Boston College Department of Economics.
    9. Juan Carlos Escanciano, 2020. "Irregular Identification of Structural Models with Nonparametric Unobserved Heterogeneity," Papers 2005.08611, arXiv.org.
    10. Tadao Hoshino, 2020. "A Pairwise Strategic Network Formation Model with Group Heterogeneity: With an Application to International Travel," Papers 2012.14886, arXiv.org, revised Feb 2021.
    11. M. T. Costa-Campi & N. Duch-Brown & Jose Garcia-Quevedo, 2024. "Drivers of Cooperation in Innovation by Energy Firms in Spain," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(12), pages 3387-3414, December.

  10. Patrick Bajari & Han Hong & John Krainer & Denis Nekipelov, 2006. "Estimating Static Models of Strategic Interaction," NBER Working Papers 12013, National Bureau of Economic Research, Inc.

    Cited by:

    1. Simon Quinn & Tom Gole, 2014. "Committees and Status Quo Bias: Structural Evidence from a Randomized Field Experiment," Economics Series Working Papers 733, University of Oxford, Department of Economics.
    2. Victor Aguirregabiria & Arvind Magesan, 2012. "Identification and estimation of dynamic games when players' beliefs are not in equilibrium," Working Papers tecipa-449, University of Toronto, Department of Economics.
    3. Dirk Bergemann & Stephen Morris, 2011. "Robust Predictions in Games with Incomplete Information," Cowles Foundation Discussion Papers 1821R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2011.
    4. Arthur Lewbel & Xun Tang, 2012. "Identification and Estimation of Games with Incomplete Information Using Excluded Regressors," Boston College Working Papers in Economics 808, Boston College Department of Economics, revised 05 Mar 2013.
    5. Drew Fudenberg, 2006. "Advancing Beyond Advances in Behavioral Economics," Journal of Economic Literature, American Economic Association, vol. 44(3), pages 694-711, September.
    6. Paul B. Ellickson & Sanjog Misra, 2011. "Structural Workshop Paper --Estimating Discrete Games," Marketing Science, INFORMS, vol. 30(6), pages 997-1010, November.
    7. Victor Aguirregabiria, 2009. "A Method for Implementing Counterfactual Experiments in Models with Multiple Equilibria," Working Papers tecipa-381, University of Toronto, Department of Economics.
    8. Ellickson, Paul & Misra, Sanjog, 2006. "Supermarket Pricing Strategies," Working Papers 06-02, Duke University, Department of Economics.
    9. Nicolai V. Kuminoff & V. Kerry Smith & Christopher Timmins, 2013. "The New Economics of Equilibrium Sorting and Policy Evaluation Using Housing Markets," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1007-1062, December.
    10. Victor Aguirregabiria, 2021. "Identification of firms’ beliefs in structural models of market competition," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(1), pages 5-33, February.
    11. Batarce, Marco & Ivaldi, Marc, 2014. "Urban travel demand model with endogenous congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 331-345.
    12. Mehmet Ali Soytaş & Damla Durak Uşar, 2017. "Role of Strategic Interactions in Corporate Sustainability Decisions: An Empirical Investigation," Ekonomi-tek - International Economics Journal, Turkish Economic Association, vol. 6(1), pages 17-46, January.
    13. Nicolai V. Kuminoff & V. Kerry Smith & Christopher Timmins, 2010. "The New Economics of Equilibrium Sorting and its Transformational Role for Policy Evaluation," NBER Working Papers 16349, National Bureau of Economic Research, Inc.
    14. Mitsukuni Nishida, 2018. "A Structural Analysis of Entry Order, Performance, and Geography: The Case of the Convenience-Store Industry in Japan," KIER Working Papers 993, Kyoto University, Institute of Economic Research.
    15. Paul Ellickson & Sanjog Misra, 2012. "Enriching interactions: Incorporating outcome data into static discrete games," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 1-26, March.
    16. Shiko Maruyama, 2009. "Estimating Sequential-move Games by a Recursive Conditioning Simulator," Discussion Papers 2009-01, School of Economics, The University of New South Wales.
    17. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    18. Victor Aguirregabiria & Jihye Jeon, 2020. "Firms’ Beliefs and Learning: Models, Identification, and Empirical Evidence," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(2), pages 203-235, March.
    19. Wang, Yafeng & Graham, Brett, 2009. "Generalized Maximum Entropy estimation of discrete sequential move games of perfect information," MPRA Paper 21331, University Library of Munich, Germany.
    20. Han Hong & Ahmed Khwaja & A. Ronald Gallant, 2008. "Estimating Dynamic Games of Complete Information with an Application to the Generic Pharmaceutical Industry," 2008 Meeting Papers 1050, Society for Economic Dynamics.
    21. Sanjog Misra, 2013. "Markov chain Monte Carlo for incomplete information discrete games," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 117-153, March.
    22. Hema Yoganarasimhan, 2016. "Estimation of Beauty Contest Auctions," Marketing Science, INFORMS, vol. 35(1), pages 27-54, January.
    23. Xiao, Ruli, 2018. "Identification and estimation of incomplete information games with multiple equilibria," Journal of Econometrics, Elsevier, vol. 203(2), pages 328-343.
    24. Haiqing Xu, 2010. "Social Interactions: A Game Theoretic Approach," Department of Economics Working Papers 130914, The University of Texas at Austin, Department of Economics.
    25. Thomas J. Holmes & Sanghoon Lee, 2009. "Economies of Density versus Natural Advantage: Crop Choice on the Back Forty," NBER Working Papers 14704, National Bureau of Economic Research, Inc.
    26. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    27. Xiaohong Chen & Jinyong Hahn, 2012. "Asymptotic efficiency of semiparametric two-step GMM," CeMMAP working papers CWP31/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. Mitsukuni Nishida, 2012. "Estimating a Model of Strategic Network Choice: The Convenience-Store Industry in Okinawa," Economics Working Paper Archive 594, The Johns Hopkins University,Department of Economics.
    29. Andrew Sweeting, 2008. "The Strategic Timing Incentives of Commercial Radio Stations: An Empirical Analysis Using Multiple Equilibria," NBER Working Papers 14506, National Bureau of Economic Research, Inc.
    30. Ron N. Borkovsky & Paul B. Ellickson & Brett R. Gordon & Victor Aguirregabiria & Gardete Pedro, 2014. "Multiplicity of Equilibria and Information Structures in Empirical Games: Challenges and Prospects," Working Papers tecipa-510, University of Toronto, Department of Economics.
    31. Leung, Michael P., 2015. "Two-step estimation of network-formation models with incomplete information," Journal of Econometrics, Elsevier, vol. 188(1), pages 182-195.
    32. Nianqing Liu & Quang Vuong & Haiqing Xu, 2012. "Rationalization and Identification of Discrete Games with Correlated Types," Department of Economics Working Papers 130915, The University of Texas at Austin, Department of Economics.
    33. Hou, Linke & Lv, Yuxia & Geng, Hao & Li, Feiyue, 2019. "To tell the truth or the perceived truth: Structural estimation of peer effects in China’s macroeconomic forecast," Economic Systems, Elsevier, vol. 43(2), pages 1-1.
    34. Sha Yang & Shijie Lu & Xianghua Lu, 2014. "Modeling Competition and Its Impact on Paid-Search Advertising," Marketing Science, INFORMS, vol. 33(1), pages 134-153, January.
    35. Yoon, Jangsu, 2024. "Identification and estimation of sequential games of incomplete information with multiple equilibria," Journal of Econometrics, Elsevier, vol. 238(2).
    36. Kojevnikov, Denis & Song, Kyungchul, 2023. "Econometric inference on a large Bayesian game with heterogeneous beliefs," Journal of Econometrics, Elsevier, vol. 237(1).
    37. Evgeny Yakovlev, 2016. "Demand for Alcohol Consumption and Implication for Mortality: Evidence from Russia," Working Papers w0221, Center for Economic and Financial Research (CEFIR).
    38. Jochmans, K., 2019. "Modified-Likelihood Estimation of Fixed-Effect Models for Dyadic Data," Cambridge Working Papers in Economics 1958, Faculty of Economics, University of Cambridge.
    39. Liu, Hong & Sun, Qi & Zhao, Zhong, 2013. "Social Learning and Health Insurance Enrollment: Evidence from China's New Cooperative Medical Scheme," IZA Discussion Papers 7251, Institute of Labor Economics (IZA).
    40. Áureo de Paula & Xun Tang, 2020. "Testable implications of multiple equilibria in discrete games with correlated types," CeMMAP working papers CWP56/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    41. Bryan S. Graham, 2019. "Network Data," Papers 1912.06346, arXiv.org.
    42. Haiqing Xu, "undated". "Estimation of Discrete Games with Correlated Types," Department of Economics Working Papers 130909, The University of Texas at Austin, Department of Economics.
    43. Aguirregabiria Victor & Xie Erhao, 2021. "Identification of Non-Equilibrium Beliefs in Games of Incomplete Information Using Experimental Data," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 1-26, January.
    44. Jinyang Zheng & Guopeng Yin & Yong Tan & Jianing Ding, 2024. "Does Help Help? An Empirical Analysis of Social Desirability Bias in Ratings," Information Systems Research, INFORMS, vol. 35(3), pages 1052-1073, September.
    45. Wang, Yafeng & Graham, Brett, 2010. "Identification and Estimation of a Discrete Game by Observing its Correlated Equilibria," MPRA Paper 45656, University Library of Munich, Germany, revised 16 May 2011.
    46. Victor Aguirregabiria & Pedro Mira, 2013. "Identification of Games of Incomplete Information with Multiple Equilibria and Common Unobserved Heterogeneity," Working Papers tecipa-474, University of Toronto, Department of Economics.
    47. Ting Zhu & Vishal Singh, 2009. "Spatial competition with endogenous location choices: An application to discount retailing," Quantitative Marketing and Economics (QME), Springer, vol. 7(1), pages 1-35, March.
    48. Giorgio Topa & Elizabeth Setren & Meta Brown, 2011. "Do Referrals Lead to Better Matches? Evidence from a Firm's Employee," 2011 Meeting Papers 711, Society for Economic Dynamics.
    49. Bernardo, Valeria & Borrell, Joan-Ramon & Perdiguero, Jordi, 2016. "Fast charging stations: Simulating entry and location in a game of strategic interaction," Energy Economics, Elsevier, vol. 60(C), pages 293-305.
    50. Itoh, Ryo & Nakajima, Kentaro, 2016. "Impact of supply chain network structure on FDI: Theory and evidence," HIT-REFINED Working Paper Series 49, Institute of Economic Research, Hitotsubashi University.
    51. Lin, Zhongjian & Tang, Xun & Yu, Ning Neil, 2021. "Uncovering heterogeneous social effects in binary choices," Journal of Econometrics, Elsevier, vol. 222(2), pages 959-973.
    52. Li, Shanjun & Liu, Yanyan & Deininger, Klaus, 2009. "How important are peer effects in group lending?: Estimating a static game of incomplete information," IFPRI discussion papers 940, International Food Policy Research Institute (IFPRI).
    53. Lambotte, Mathieu & Mathy, Sandrine & Risch, Anna & Treibich, Carole, 2023. "Disentangling peer effects in transportation mode choice: The example of active commuting," Journal of Environmental Economics and Management, Elsevier, vol. 121(C).
    54. Doraszelski, Ulrich & Kryukov, Yaroslav & Borkovsky, Ron N., 2008. "A User's Guide to Solving Dynamic Stochastic Games Using the Homotopy Method," CEPR Discussion Papers 6733, C.E.P.R. Discussion Papers.
    55. Wesley Hartmann & Puneet Manchanda & Harikesh Nair & Matthew Bothner & Peter Dodds & David Godes & Kartik Hosanagar & Catherine Tucker, 2008. "Modeling social interactions: Identification, empirical methods and policy implications," Marketing Letters, Springer, vol. 19(3), pages 287-304, December.
    56. Aradillas-Lopez, Andres, 2012. "Pairwise-difference estimation of incomplete information games," Journal of Econometrics, Elsevier, vol. 168(1), pages 120-140.
    57. Stohr, Tobias, 2013. "Intra-family migration decisions and elderly left behind," Kiel Working Papers 1858, Kiel Institute for the World Economy (IfW Kiel).
    58. Gautam, Sanghmitra, 2023. "Quantifying welfare effects in the presence of externalities: An ex-ante evaluation of sanitation interventions," Journal of Development Economics, Elsevier, vol. 164(C).
    59. William C. Horrace & Hyunseok Jung & Shane Sanders, 2022. "Network Competition and Team Chemistry in the NBA," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 35-49, January.
    60. Kojevnikov, Denis & Song, Kyungchul, 2023. "Econometric inference on a large bayesian game with heterogeneous beliefs," Other publications TiSEM aca0631e-4f8a-45c7-af3a-4, Tilburg University, School of Economics and Management.
    61. Baker, Matthew J. & George, Lisa M., 2024. "The news hour: Welfare estimation in the market for local television news," International Journal of Industrial Organization, Elsevier, vol. 94(C).
    62. Canta Chiara & Dubois Pierre, 2015. "Smoking within the Household: Spousal Peer Effects and Children’s Health Implications," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(4), pages 1939-1973, October.
    63. 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.
    64. Lin, Zhongjian & Hu, Yingyao, 2024. "Binary choice with misclassification and social interactions, with an application to peer effects in attitude," Journal of Econometrics, Elsevier, vol. 238(1).
    65. Xun Tang, 2009. "Binary Regressions with Bounded Median Dependence," PIER Working Paper Archive 09-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    66. Kline, Brendan, 2015. "Identification of complete information games," Journal of Econometrics, Elsevier, vol. 189(1), pages 117-131.
    67. Bart Bronnenberg & Jean Dubé & Carl Mela & Paulo Albuquerque & Tulin Erdem & Brett Gordon & Dominique Hanssens & Guenter Hitsch & Han Hong & Baohong Sun, 2008. "Measuring long-run marketing effects and their implications for long-run marketing decisions," Marketing Letters, Springer, vol. 19(3), pages 367-382, December.
    68. Navarro, Salvador & Takahashi, Yuya, 2012. "A Semiparametric Test of Agent's Information Sets for Games of Incomplete Information," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 432, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    69. Jason R. Blevins, 2014. "Structural Estimation of Sequential Games of Complete Information," Working Papers 14-01, Ohio State University, Department of Economics.
    70. Christian Cox, 2023. "Lobbying for government appropriations," RAND Journal of Economics, RAND Corporation, vol. 54(3), pages 443-483, September.
    71. John D. Singleton, 2019. "Incentives and the Supply of Effective Charter Schools," American Economic Review, American Economic Association, vol. 109(7), pages 2568-2612, July.
    72. Victor Aguirregabiria & Junichi Suzuki, 2015. "Empirical Games of Market Entry and Spatial Competition in Retail Industries," Working Papers tecipa-534, University of Toronto, Department of Economics.
    73. Luo, Yao & Xiao, Ping & Xiao, Ruli, 2022. "Identification of dynamic games with unobserved heterogeneity and multiple equilibria," Journal of Econometrics, Elsevier, vol. 226(2), pages 343-367.
    74. Alberto Bisin & Andrea Moro & Giorgio Topa, 2011. "The empirical content of models with multiple equilibria in economies with social interactions," Staff Reports 504, Federal Reserve Bank of New York.
    75. Xi Chen & Ralf van der Lans & Michael Trusov, 2021. "Efficient Estimation of Network Games of Incomplete Information: Application to Large Online Social Networks," Management Science, INFORMS, vol. 67(12), pages 7575-7598, December.
    76. Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    77. A. Yeşim Orhun, 2013. "Spatial differentiation in the supermarket industry: The role of common information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 3-37, March.
    78. Ryo Itoh & Kentaro Nakajima, 2021. "Do sourcing networks make firms global? Microlevel evidence from firm-to-firm transaction networks," The Japanese Economic Review, Springer, vol. 72(1), pages 65-96, January.
    79. Aristide Houndetoungan, 2024. "Count Data Models with Heterogeneous Peer Effects under Rational Expectations," Papers 2405.17290, arXiv.org.
    80. Wan, Yuanyuan & Xu, Haiqing, 2014. "Semiparametric identification of binary decision games of incomplete information with correlated private signals," Journal of Econometrics, Elsevier, vol. 182(2), pages 235-246.
    81. Antonio Merlo & Xun Tang, 2009. "Identification of Stochastic Sequential Bargaining Models," PIER Working Paper Archive 09-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    82. Antonio Merlo & Xun Tang, 2010. "Identification and Estimation of Stochastic Bargaining Models, Third Version," PIER Working Paper Archive 11-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 11 Mar 2011.
    83. Dennis Epple & Richard Romano & Sinan Sarpça & Holger Sieg & Melanie Zaber, 2017. "Market Power and Price Discrimination in the U.S. Market for Higher Education," Working Papers 2017-037, Human Capital and Economic Opportunity Working Group.
    84. Tang, Xun, 2010. "Estimating simultaneous games with incomplete information under median restrictions," Economics Letters, Elsevier, vol. 108(3), pages 273-276, September.
    85. Wang, Yafeng & Graham, Brett, 2010. "Simulation Based Estimation of Discrete Sequential Move Games of Perfect Information," MPRA Paper 23153, University Library of Munich, Germany.
    86. Bora Kim, 2020. "Analysis of Randomized Experiments with Network Interference and Noncompliance," Papers 2012.13710, arXiv.org.
    87. Nianqing Liu & Haiqing Xu, "undated". "Semiparametric Analysis of Binary Games of Incomplete Information," Department of Economics Working Papers 130911, The University of Texas at Austin, Department of Economics, revised Nov 2012.
    88. Marcoux, Mathieu, 2022. "Strategic interactions in mobile network investment with a new entrant and unobserved heterogeneity," International Journal of Industrial Organization, Elsevier, vol. 82(C).
    89. Emerson Melo, 2022. "On the uniqueness of quantal response equilibria and its application to network games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 74(3), pages 681-725, October.
    90. Alessandra Allocca, 2023. "“No Man is an Island”: An Empirical Study on Team Formation and Performance," Rationality and Competition Discussion Paper Series 389, CRC TRR 190 Rationality and Competition.
    91. Yanwei Jia & Jussi Keppo & Ville Satopää, 2023. "Herding in Probabilistic Forecasts," Management Science, INFORMS, vol. 69(5), pages 2713-2732, May.
    92. Denis Nekipelov & Vira Semenova & Vasilis Syrgkanis, 2018. "Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models," Papers 1806.04823, arXiv.org, revised Sep 2021.
    93. Shijie Lu & Sha Yang, 2017. "Investigating the Spillover Effect of Keyword Market Entry in Sponsored Search Advertising," Marketing Science, INFORMS, vol. 36(6), pages 976-998, November.
    94. Evgeny Yakovlev, 2012. "Peers and Alcohol: Evidence from Russia," Working Papers w0182, New Economic School (NES).
    95. Mian Dai & Xun Tang, 2013. "Regulation and Capacity Competition in Health Care: Evidence from Dialysis Markets," PIER Working Paper Archive 13-057, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    96. Marc Rysman & Timothy Simcoe & Yanfei Wang, 2020. "Differentiation Strategies in the Adoption of Environmental Standards: LEED from 2000 to 2014," Management Science, INFORMS, vol. 66(9), pages 4173-4192, September.
    97. Kyle Myers, 2020. "The Elasticity of Science," American Economic Journal: Applied Economics, American Economic Association, vol. 12(4), pages 103-134, October.
    98. Yuanyuan Wan & Haiqing Xu, 2010. "Semiparametric identification and estimation of binary discrete games of incomplete information with correlated private signals," Department of Economics Working Papers 130913, The University of Texas at Austin, Department of Economics.
    99. He, Yinghua, 2015. "Gaming the Boston School Choice Mechanism in Beijing," TSE Working Papers 15-551, Toulouse School of Economics (TSE), revised Sep 2017.
    100. Stephen Coate & Michael Conlin & Andrea Moro, 2004. "The Performance of the Pivotal-Voter Model in Small-Scale Elections: Evidence from Texas Liquor Referenda," NBER Working Papers 10797, National Bureau of Economic Research, Inc.
    101. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2018. "Nonparametric analysis of monotone choice," Discussion Paper Series 184, School of Economics, Kwansei Gakuin University.
    102. Jos'-Antonio Esp'n-S'nchez & 'lvaro Parra & Yuzhou Wang, 2018. "Equilibrium Uniqueness in Entry Games with Private Information," Cowles Foundation Discussion Papers 2126R, Cowles Foundation for Research in Economics, Yale University, revised May 2021.
    103. Yafeng Wang & Brett Graham, 2013. "Generalized Maximum Entropy Estimation of Discrete Sequential Move Games of Perfect Information," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    104. Sergio Aquino DeSouza, 2017. "A flexible nested logit model," Economics Bulletin, AccessEcon, vol. 37(4), pages 2854-2859.
    105. Yang, Chao & Lee, Lung-fei, 2017. "Social interactions under incomplete information with heterogeneous expectations," Journal of Econometrics, Elsevier, vol. 198(1), pages 65-83.
    106. Xun Tang, 2009. "Estimating Simultaneous Games with Incomplete Information under Median Restrictions," PIER Working Paper Archive 09-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    107. Erhao Xie, 2018. "Inference in Games Without Nash Equilibrium: An Application to Restaurants, Competition in Opening Hours," Staff Working Papers 18-60, Bank of Canada.
    108. Nazgul Jenish, 2015. "Strategic Interaction Model with Censored Strategies," Econometrics, MDPI, vol. 3(2), pages 1-31, June.
    109. Jos'-Antonio Esp'n-S'nchez & 'lvaro Parra, 2018. "Entry Games under Private Information," Cowles Foundation Discussion Papers 2126, Cowles Foundation for Research in Economics, Yale University.
    110. Holmes, Thomas J. & Sieg, Holger, 2015. "Structural Estimation in Urban Economics," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 69-114, Elsevier.
    111. Kenkel, Brenton & Signorino, Curtis, 2014. "Estimating Extensive Form Games in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(i08).
    112. Chen, Chia-Wen, 2014. "Estimating the foreclosure effect of exclusive dealing: Evidence from the entry of specialty beer producers," International Journal of Industrial Organization, Elsevier, vol. 37(C), pages 47-64.
    113. Sha Yang & Anindya Ghose, 2010. "Analyzing the Relationship Between Organic and Sponsored Search Advertising: Positive, Negative, or Zero Interdependence?," Marketing Science, INFORMS, vol. 29(4), pages 602-623, 07-08.
    114. Yang, Zhou, 2006. "Correlated Equilibrium and the Estimation of Static Discrete Games with Complete Information," MPRA Paper 79395, University Library of Munich, Germany.
    115. Chao Fu, 2014. "Equilibrium Tuition, Applications, Admissions, and Enrollment in the College Market," Journal of Political Economy, University of Chicago Press, vol. 122(2), pages 225-281.
    116. Arthur Lewbel & Xun Tang, 2010. "Identification and Estimation of Games with Incomplete Information Using Excluded Regressors, Second Version," PIER Working Paper Archive 12-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 20 Mar 2012.
    117. Koh, Paul S., 2023. "Stable outcomes and information in games: An empirical framework," Journal of Econometrics, Elsevier, vol. 237(1).
    118. Mehmet Ali Soytaş & Damla Durak Uşar & Meltem Denizel, 2022. "Estimation of the static corporate sustainability interactions," International Journal of Production Research, Taylor & Francis Journals, vol. 60(4), pages 1245-1264, February.
    119. Bryan S. Graham, 2019. "Network Data," CeMMAP working papers CWP71/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    120. Gillen, David & Hasheminia, Hamed & Jiang, Changmin, 2015. "Strategic considerations behind the network–regional airline tie ups – A theoretical and empirical study," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 93-111.
    121. Victor Chernozhukov & Denis Nekipelov & Vira Semenova & Vasilis Syrgkanis, 2018. "Plug-in regularized estimation of high dimensional parameters in nonlinear semiparametric models," CeMMAP working papers CWP41/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    122. Ron N. Borkovsky & Ulrich Doraszelski & Yaroslav Kryukov, "undated". "A User''s Guide to Solving Dynamic Stochastic Games Using the Homotopy Method," GSIA Working Papers 2009-E23, Carnegie Mellon University, Tepper School of Business.
    123. Che-Lin Su, 2014. "Estimating discrete-choice games of incomplete information: Simple static examples," Quantitative Marketing and Economics (QME), Springer, vol. 12(2), pages 167-207, June.
    124. Magnolfi, Lorenzo & Roncoroni, Camilla, 2020. "Estimation of Discrete Games with Weak Assumptions on Information," The Warwick Economics Research Paper Series (TWERPS) 1247, University of Warwick, Department of Economics.

  11. Akhmed Akhmedov & Evgenia Bessonova & Ivan Cherkashin & Irina Denisova & Elena Grishina & Denis Nekipelov, 2003. "WTO Accession and the Labor Market: Estimations for Russia," Working Papers w0040, Center for Economic and Financial Research (CEFIR).

    Cited by:

    1. Elena Vakulenko, 2013. "Labour Market Analysis using Time Series Models: Russia 1999-2011," Quaderni del Dipartimento di Economia, Finanza e Statistica 120/2013, Università di Perugia, Dipartimento Economia.
    2. Heinrich Hockmann & Michael Kopsidis, 2007. "What Kind of Technological Change for Russian Agriculture? The Transition Crisis of 1991-2005 from the Induced Innovation Theory Perspective," Post-Communist Economies, Taylor & Francis Journals, vol. 19(1), pages 35-52.

Articles

  1. Gentry, Matthew L. & Hubbard, Timothy P. & Nekipelov, Denis & Paarsch, Harry J., 2018. "Structural Econometrics of Auctions: A Review," Foundations and Trends(R) in Econometrics, now publishers, vol. 9(2-4), pages 79-302, April.

    Cited by:

    1. Weichselbaumer, Michael, 2024. "Competition after mergers near review thresholds," International Journal of Industrial Organization, Elsevier, vol. 94(C).
    2. Jun Ma & Vadim Marmer & Artyom Shneyerov & Pai Xu, 2019. "Monotonicity-Constrained Nonparametric Estimation and Inference for First-Price Auctions," Papers 1909.12974, arXiv.org.
    3. Ivaldi, Marc & Petrova, Milena & Urdanoz, Miguel, 2022. "Airline cooperation effects on airfare distribution: An auction-model-based approach," Transport Policy, Elsevier, vol. 115(C), pages 239-250.
    4. Sebastian Galiani & Juan Pantano, 2021. "Structural Models: Inception and Frontier," NBER Working Papers 28698, National Bureau of Economic Research, Inc.
    5. Enache, Andreea & Florens, Jean-Pierre & Sbai, Erwann, 2023. "A functional estimation approach to the first-price auction models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1564-1588.
    6. Myrna, Olena, 2023. "Competition in online land lease auctions in Ukraine: Reduced-form estimation," Land Use Policy, Elsevier, vol. 125(C).
    7. Dutra, Renato Cabral Dias & Carpio, Lucio Guido Tapia, 2021. "Biodiesel auctions in Brazil: Symmetry of bids and informational paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    8. Ivaldi, Marc & Petrova, Milena J & Urdanoz, Miguel, 2021. "Airline Cooperation Effects on Airfare Distribution: An Auction-model-based Approach," TSE Working Papers 21-1259, Toulouse School of Economics (TSE).
    9. Yoav Kolumbus & Joe Halpern & 'Eva Tardos, 2024. "Paying to Do Better: Games with Payments between Learning Agents," Papers 2405.20880, arXiv.org.

  2. Shakeeb Khan & Denis Nekipelov, 2018. "Information structure and statistical information in discrete response models," Quantitative Economics, Econometric Society, vol. 9(2), pages 995-1017, July.
    See citations under working paper version above.
  3. Robert F. Conrad & Bryce Hool & Denis Nekipelov, 2018. "The Role of Royalties in Resource Extraction Contracts," Land Economics, University of Wisconsin Press, vol. 94(3), pages 340-353.

    Cited by:

    1. Bertrand Laporte & Celine de Quatrebarbes & Yannick Bouterige, 2022. "Tax design and rent sharing in mining sector: Evidence from African gold‐producing countries," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(6), pages 1176-1196, August.
    2. Prest, Brian C. & Stock, James H., 2023. "Climate royalty surcharges," Journal of Environmental Economics and Management, Elsevier, vol. 120(C).
    3. Bertinelli, Luisito & Bourgain, Arnaud & Zanaj, Skerdilajda, 2022. "Taxes and declared profits: Evidence from gold mines in Africa," Resources Policy, Elsevier, vol. 78(C).

  4. Tatiana Komarova & Denis Nekipelov & Evgeny Yakovlev, 2018. "Identification, data combination, and the risk of disclosure," Quantitative Economics, Econometric Society, vol. 9(1), pages 395-440, March.
    See citations under working paper version above.
  5. Komarova, Tatiana & Nekipelov, Denis & Al Rafi , Ahnaf & Yakovlev, Evgeny, 2017. "K-anonymity: A note on the trade-off between data utility and data security," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 48, pages 44-62.

    Cited by:

    1. Tatiana Komarova & Denis Nekipelov, 2020. "Identification and Formal Privacy Guarantees," Papers 2006.14732, arXiv.org, revised May 2021.

  6. Patrick Bajari & Chenghuan Sean Chu & Denis Nekipelov & Minjung Park, 2016. "Identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action," Quantitative Marketing and Economics (QME), Springer, vol. 14(4), pages 271-323, December.

    Cited by:

    1. Murasawa, Yasutomo, 2023. "大学中退の逐次意思決定モデルの構造推定 [Structural estimation of a sequential decision model of college dropout]," MPRA Paper 118183, University Library of Munich, Germany.
    2. Yonghong An & Yingyao Hu & Ruli Xiao, 2018. "Dynamic decisions under subjective expectations: a structural analysis," CeMMAP working papers CWP11/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Myrto Kalouptsidi & Paul T. Scott & Eduardo Souza‐Rodrigues, 2021. "Identification of counterfactuals in dynamic discrete choice models," Quantitative Economics, Econometric Society, vol. 12(2), pages 351-403, May.
    4. Jay Lu & Yao Luo & Kota Saito & Yi Xin, 2024. "Did Harold Zuercher Have Time-Separable Preferences?," Papers 2406.07809, arXiv.org.
    5. Jason R. Blevins & Wei Shi & Donald R. Haurin & Stephanie Moulton, 2020. "A Dynamic Discrete Choice Model Of Reverse Mortgage Borrower Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1437-1477, November.
    6. Hu, Yingyao & Xin, Yi, 2024. "Identification and estimation of dynamic structural models with unobserved choices," Journal of Econometrics, Elsevier, vol. 242(2).
    7. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2021. "Linear IV regression estimators for structural dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 222(1), pages 778-804.
    8. Cheng Chou & Tim Derdenger & Vineet Kumar, 2019. "Linear Estimation of Aggregate Dynamic Discrete Demand for Durable Goods: Overcoming the Curse of Dimensionality," Marketing Science, INFORMS, vol. 38(5), pages 888-909, September.
    9. Sebastian Galiani & Juan Pantano, 2021. "Structural Models: Inception and Frontier," NBER Working Papers 28698, National Bureau of Economic Research, Inc.
    10. Kalouptsidi, Myrto & Souza-Rodrigues, Eduardo & Scott, Paul, 2017. "Identification of Counterfactuals in Dynamic Discrete Choice Models," CEPR Discussion Papers 12470, C.E.P.R. Discussion Papers.
    11. Jaap H. Abbring & Øystein Daljord, 2020. "Identifying the discount factor in dynamic discrete choice models," Quantitative Economics, Econometric Society, vol. 11(2), pages 471-501, May.
    12. Jaap H. Abbring & Øystein Daljord, 2020. "A Comment On “Estimating Dynamic Discrete Choice Models With Hyperbolic Discounting” By Hanming Fang And Yang Wang," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(2), pages 565-571, May.
    13. Øystein Daljord & Denis Nekipelov & Minjung Park, 2019. "Comments on “identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action”," Quantitative Marketing and Economics (QME), Springer, vol. 17(4), pages 439-449, December.
    14. Schiraldi, Pasquale & Levy, Matthew R., 2020. "Identification of intertemporal preferences in history-dependent dynamic discrete choice models," CEPR Discussion Papers 14447, C.E.P.R. Discussion Papers.
    15. Arcidiacono, Peter & Miller, Robert A., 2020. "Identifying dynamic discrete choice models off short panels," Journal of Econometrics, Elsevier, vol. 215(2), pages 473-485.
    16. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2018. "Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models," CEPR Discussion Papers 13240, C.E.P.R. Discussion Papers.
    17. Myrto Kalouptsidi & Paul T. Scott & Eduardo Souza-Rodrigues, 2018. "Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models," NBER Working Papers 25134, National Bureau of Economic Research, Inc.

  7. Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Machine Learning Methods for Demand Estimation," American Economic Review, American Economic Association, vol. 105(5), pages 481-485, May.

    Cited by:

    1. Gogolev, Stepan & Ozhegov, Evgeniy, 2023. "Asymmetric loss function in product-level sales forecasting: An empirical comparison," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 109-121.
    2. Federico Zincenko, 2023. "Nonparametric estimation of conditional densities by generalized random forests," Papers 2309.13251, arXiv.org, revised May 2024.
    3. Khudri, Md Mohsan & Hussey, Andrew, 2024. "Breastfeeding and Child Development Outcomes across Early Childhood and Adolescence: Doubly Robust Estimation with Machine Learning," IZA Discussion Papers 17080, Institute of Labor Economics (IZA).
    4. Luo, Ye & Spindler, Martin & Bach, Philipp, 2019. "Dynamic Pricing mit Künstlicher Intelligenz - Fallstudie aus dem Ride-Sharing-Markt," Marketing Review St.Gallen, Universität St.Gallen, Institut für Marketing und Customer Insight, vol. 36(5), pages 48-54.
    5. Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
    6. Md Jahidur Rahman & Hongtao Zhu, 2023. "Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(3), pages 3455-3486, September.
    7. Apostolos Ampountolas & Titus Nyarko Nde & Paresh Date & Corina Constantinescu, 2021. "A Machine Learning Approach for Micro-Credit Scoring," Risks, MDPI, vol. 9(3), pages 1-20, March.
    8. Koffi Dumor & Li Yao, 2019. "Estimating China’s Trade with Its Partner Countries within the Belt and Road Initiative Using Neural Network Analysis," Sustainability, MDPI, vol. 11(5), pages 1-22, March.
    9. Phoebe Koundouri & Barbara Hammer & Ulrike Kuhl & Alina Velias, 2022. "Behavioral and Neuroeconomics of Environmental Values," DEOS Working Papers 2227, Athens University of Economics and Business.
    10. Daniel Garcia & Juha Tolvanen & Alexander K. Wagner, 2022. "Demand Estimation Using Managerial Responses to Automated Price Recommendations," Management Science, INFORMS, vol. 68(11), pages 7918-7939, November.
    11. Zhu, Manhong & Schmitz, Andrew & Schmitz, Troy G., "undated". "What are the Culprits Causing Obesity? A Machine Learning Approach in Variable Selection and Parameter Coefficient Inference," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 261220, Agricultural and Applied Economics Association.
    12. Steven Lehrer & Tian Xie & Tao Zeng, 2021. "Does High-Frequency Social Media Data Improve Forecasts of Low-Frequency Consumer Confidence Measures? [Regression Models with Mixed Sampling Frequencies]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 910-933.
    13. Haoge Chang & Yusuke Narita & Kota Saito, 2022. "Approximating Choice Data by Discrete Choice Models," Papers 2205.01882, arXiv.org, revised Dec 2023.
    14. Amin, Modhurima Dey & Badruddoza, Syed & McCluskey, Jill J., 2021. "Predicting access to healthful food retailers with machine learning," Food Policy, Elsevier, vol. 99(C).
    15. Yanqing Yang & Xingcheng Xu & Jinfeng Ge & Yan Xu, 2024. "Machine Learning for Economic Forecasting: An Application to China's GDP Growth," Papers 2407.03595, arXiv.org.
    16. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2017. "Econom\'etrie et Machine Learning," Papers 1708.06992, arXiv.org, revised Mar 2018.
    17. Colin F. Camerer & Gideon Nave & Alec Smith, 2019. "Dynamic Unstructured Bargaining with Private Information: Theory, Experiment, and Outcome Prediction via Machine Learning," Management Science, INFORMS, vol. 65(4), pages 1867-1890, April.
    18. Koffi Dumor & Komlan Gbongli, 2021. "Trade impacts of the New Silk Road in Africa: Insight from Neural Networks Analysis," Theory Methodology Practice (TMP), Faculty of Economics, University of Miskolc, vol. 17(02), pages 13-26.
    19. Sule Birim & Ipek Kazancoglu & Sachin Kumar Mangla & Aysun Kahraman & Yigit Kazancoglu, 2024. "The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods," Annals of Operations Research, Springer, vol. 339(1), pages 131-161, August.
    20. Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2102, Department of Economics, University of Missouri.
    21. 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.
    22. Jorge Mejia & Shawn Mankad & Anandasivam Gopal, 2019. "A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections," Information Systems Research, INFORMS, vol. 30(4), pages 1363-1386, December.
    23. Halko, Marja-Liisa & Lappalainen, Olli & Sääksvuori, Lauri, 2021. "Do non-choice data reveal economic preferences? Evidence from biometric data and compensation-scheme choice," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 87-104.
    24. Shiguang Li & Yixiang Tian, 2023. "How Does Digital Transformation Affect Total Factor Productivity: Firm-Level Evidence from China," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    25. 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.
    26. Pedro M. Gardete & Carlos D. Santos, 2020. "No data? No problem! A Search-based Recommendation System with Cold Starts," Papers 2010.03455, arXiv.org.
    27. Abrell, Jan & Kosch, Mirjam & Rausch, Sebastian, 2021. "How effective is carbon pricing? A machine learning approach to policy evaluation," ZEW Discussion Papers 21-039, ZEW - Leibniz Centre for European Economic Research.
    28. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    29. Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
    30. Sun, Sizhong, 2022. "The demand for a COVID-19 vaccine," Economics & Human Biology, Elsevier, vol. 46(C).
    31. Sunghyeon Choi & Jin Hur, 2020. "An Ensemble Learner-Based Bagging Model Using Past Output Data for Photovoltaic Forecasting," Energies, MDPI, vol. 13(6), pages 1-16, March.
    32. Maria Ana Matias & Rita Santos & Panos Kasteridis & Katja Grasic & Anne Mason & Nigel Rice, 2022. "Approaches to projecting future healthcare demand," Working Papers 186cherp, Centre for Health Economics, University of York.
    33. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Économétrie & Machine Learning," Working Papers hal-01568851, HAL.
    34. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    35. Santiago Carbo-Valverde & Pedro Cuadros-Solas & Francisco Rodríguez-Fernández, 2020. "A machine learning approach to the digitalization of bank customers: Evidence from random and causal forests," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-39, October.
    36. Zhan Gao & Zhentao Shi, 2021. "Implementing Convex Optimization in R: Two Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1127-1135, December.
    37. Evgeniy M. Ozhegov & Alina Ozhegova, 2017. "Regression Tree Model for Analysis of Demand with Heterogeneity and Censorship," HSE Working papers WP BRP 174/EC/2017, National Research University Higher School of Economics.
    38. Louis R. Nemzer & Florence Neymotin, 2020. "Concierge care and patient reviews," Health Economics, John Wiley & Sons, Ltd., vol. 29(8), pages 913-922, August.
    39. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
    40. Daniele Guariso, 2018. "Terrorist Attacks and Immigration Rhetoric: A Natural Experiment on British MPs," Working Paper Series 1218, Department of Economics, University of Sussex Business School.
    41. Deimante Teresiene & Margarita Aleksynaite, 2020. "The Use of Technical Analysis in the US, European and Asian Stock Markets," Technium Social Sciences Journal, Technium Science, vol. 8(1), pages 302-318, June.
    42. Bonnet, Céline & Richards, Timothy J., 2016. "Models of Consumer Demand for Differentiated Products," TSE Working Papers 16-741, Toulouse School of Economics (TSE).
    43. Hanyao Gao & Gang Kou & Haiming Liang & Hengjie Zhang & Xiangrui Chao & Cong-Cong Li & Yucheng Dong, 2024. "Machine learning in business and finance: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-35, December.
    44. Merino Troncoso, Carlos, 2021. "Consumer Demand Estimation," MPRA Paper 105169, University Library of Munich, Germany.
    45. Badruddoza, Syed & Amin, Modhurima & McCluskey, Jill, 2019. "Assessing the Importance of an Attribute in a Demand SystemStructural Model versus Machine Learning," Working Papers 2019-5, School of Economic Sciences, Washington State University.
    46. Tatiana de Macedo Nogueira Lima, 2022. "Documento de Trabalho 03/2022 - Aprendizado de máquina e antitruste," Documentos de Trabalho 2022030, Conselho Administrativo de Defesa Econômica (Cade), Departamento de Estudos Econômicos.
    47. Marica Valente & Timm Gries & Lorenzo Trapani, 2023. "Informal employment from migration shocks," Working Papers 2023-09, Faculty of Economics and Statistics, Universität Innsbruck.
    48. Yongtong Shao & Tao Xiong & Minghao Li & Dermot Hayes & Wendong Zhang & Wei Xie, 2021. "China's Missing Pigs: Correcting China's Hog Inventory Data Using a Machine Learning Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1082-1098, May.
    49. Marc Bourreau & Yutec Sun, 2022. "Competition and Quality: Evidence from the Entry of Mobile Network Service," Working Papers 22-04, NET Institute.
    50. Frankel, Richard & Jennings, Jared & Lee, Joshua, 2016. "Using unstructured and qualitative disclosures to explain accruals," Journal of Accounting and Economics, Elsevier, vol. 62(2), pages 209-227.
    51. Jonathan Leslie, 2023. "?Seeing? the Future: Improving Macroeconomic Forecasts with Spatial Data and Recurrent Convolutional Neural Networks," CAEPR Working Papers 2023-003 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    52. Keaton Miller & Boyoung Seo, 2021. "The Effect of Cannabis Legalization on Substance Demand and Tax Revenues," National Tax Journal, University of Chicago Press, vol. 74(1), pages 107-145.
    53. Pollack, Adam B. & Kaufmann, Robert K., 2022. "Increasing storm risk, structural defense, and house prices in the Florida Keys," Ecological Economics, Elsevier, vol. 194(C).
    54. Uzma Mushtaque & Jennifer A. Pazour, 2020. "Random Utility Models with Cardinality Context Effects for Online Subscription Service Platforms," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(4), pages 276-290, August.
    55. Tsun Se Cheong & Guanghua Wan & David Kam Hung Chui, 2022. "Unveiling the Relationship between Economic Growth and Equality for Developing Countries," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 30(5), pages 1-28, September.
    56. Francesco Cusano & Giuseppe Marinelli & Stefano Piermattei, 2022. "Learning from revisions: an algorithm to detect errors in banks’ balance sheet statistical reporting," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4025-4059, December.
    57. Merino Troncoso, Carlos, 2023. "Introduction to Competition Economics," MPRA Paper 115999, University Library of Munich, Germany.
    58. Chengyan Gu, 2023. "Market segmentation and dynamic price discrimination in the U.S. airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(5), pages 338-361, October.
    59. Xueling Li & Xiaoyan Zhang & Yuan Liu & Yuanying Mi & Yong Chen, 2022. "The impact of artificial intelligence on users' entrepreneurial activities," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 597-608, May.
    60. Emrich Eike & Pierdzioch Christian, 2016. "Public Goods, Private Consumption, and Human Capital: Using Boosted Regression Trees to Model Volunteer Labour Supply," Review of Economics, De Gruyter, vol. 67(3), pages 263-283, December.
    61. Tzai-Shuen Chen, 2018. "Evaluating Conditional Cash Transfer Policies with Machine Learning Methods," Papers 1803.06401, arXiv.org.
    62. Richard Frankel & Jared Jennings & Joshua Lee, 2022. "Disclosure Sentiment: Machine Learning vs. Dictionary Methods," Management Science, INFORMS, vol. 68(7), pages 5514-5532, July.
    63. Raval, Devesh & Rosenbaum, Ted & Wilson, Nathan E., 2021. "How do machine learning algorithms perform in predicting hospital choices? evidence from changing environments," Journal of Health Economics, Elsevier, vol. 78(C).
    64. Embaye, Weldensie T. & Zereyesus, Yacob A., 2017. "Measuring the value of housing services in household surveys: an application of machine learning approach," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252851, Southern Agricultural Economics Association.
    65. Evgeny A. Antipov & Elena B. Pokryshevskaya, 2020. "Interpretable machine learning for demand modeling with high-dimensional data using Gradient Boosting Machines and Shapley values," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(5), pages 355-364, October.
    66. Zhang, Wenzhe & Liu, Guangqiang, 2023. "Digitalization and firm centralization: A quasi-natural experiment based on the “Broadband China” policy," Finance Research Letters, Elsevier, vol. 52(C).
    67. Rahman, Md Jahidur & Zhu, Hongtao, 2024. "Detecting accounting fraud in family firms: Evidence from machine learning approaches," Advances in accounting, Elsevier, vol. 64(C).
    68. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2020. "Deep Learning for Individual Heterogeneity: An Automatic Inference Framework," Papers 2010.14694, arXiv.org, revised Jul 2021.
    69. Haixiang Yao & Shenghao Xia & Hao Liu, 2024. "Return predictability via an long short‐term memory‐based cross‐section factor model: Evidence from Chinese stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1770-1794, September.
    70. Koffi Dumor & Li Yao & Jean-Paul Ainam & Edem Koffi Amouzou & Williams Ayivi, 2021. "Quantitative Dynamics Effects of Belt and Road Economies Trade Using Structural Gravity and Neural Networks," SAGE Open, , vol. 11(3), pages 21582440211, July.
    71. Wenjie Bi & Bing Wang & Haiying Liu, 2024. "Personalized Dynamic Pricing Based on Improved Thompson Sampling," Mathematics, MDPI, vol. 12(8), pages 1-14, April.

  8. Hong, Han & Mahajan, Aprajit & Nekipelov, Denis, 2015. "Extremum estimation and numerical derivatives," Journal of Econometrics, Elsevier, vol. 188(1), pages 250-263.

    Cited by:

    1. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers 45/13, Institute for Fiscal Studies.
    2. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2020. "Inference on Semiparametric Multinomial Response Models," Discussion Papers Series 627, School of Economics, University of Queensland, Australia.
    3. Xu, Ke-Li, 2020. "Inference of local regression in the presence of nuisance parameters," Journal of Econometrics, Elsevier, vol. 218(2), pages 532-560.
    4. Timothy B. Armstrong & Michal Kolesár, 2020. "Sensitivity Analysis using Approximate Moment Condition Models," Working Papers 2020-28, Princeton University. Economics Department..
    5. Bo E. Honoré & Luojia Hu, 2018. "Simpler bootstrap estimation of the asymptotic variance of U‐statistic‐based estimators," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-10, February.
    6. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    7. Kai Feng & Han Hong & Ke Tang & Jingyuan Wang, 2019. "Decision Making with Machine Learning and ROC Curves," Papers 1905.02810, arXiv.org.
    8. Fu Ouyang & Thomas Tao Yang, 2020. "Semiparametric Discrete Choice Models for Bundles," Discussion Papers Series 625, School of Economics, University of Queensland, Australia.
    9. Rabovic, R. & Cizek, P., 2020. "Estimation of Spatial Sample Selection Models: A Partial Maximum Likelihood Approach," Cambridge Working Papers in Economics 2012, Faculty of Economics, University of Cambridge.
    10. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2021. "Inference on semiparametric multinomial response models," Quantitative Economics, Econometric Society, vol. 12(3), pages 743-777, July.
    11. Luofeng Liao & Christian Kroer & Sergei Leonenkov & Okke Schrijvers & Liang Shi & Nicolas Stier-Moses & Congshan Zhang, 2024. "Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis," Papers 2402.07322, arXiv.org.
    12. Frazier, David T. & Oka, Tatsushi & Zhu, Dan, 2019. "Indirect inference with a non-smooth criterion function," Journal of Econometrics, Elsevier, vol. 212(2), pages 623-645.
    13. Hong, Han & Li, Jessie, 2018. "The numerical delta method," Journal of Econometrics, Elsevier, vol. 206(2), pages 379-394.
    14. Mario Martinoli & Raffaello Seri & Fulvio Corsi, 2024. "Generalized Optimization Algorithms for Complex Objective Functions," LEM Papers Series 2024/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    15. Adrian O’Hagan & Thomas Brendan Murphy & Luca Scrucca & Isobel Claire Gormley, 2019. "Investigation of parameter uncertainty in clustering using a Gaussian mixture model via jackknife, bootstrap and weighted likelihood bootstrap," Computational Statistics, Springer, vol. 34(4), pages 1779-1813, December.
    16. Rothe, Christoph & Wied, Dominik, 2020. "Estimating derivatives of function-valued parameters in a class of moment condition models," Journal of Econometrics, Elsevier, vol. 217(1), pages 1-19.

  9. Xiaohong Chen & Han Hong & Denis Nekipelov, 2011. "Nonlinear Models of Measurement Errors," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 901-937, December.

    Cited by:

    1. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Childhood Intervention," IZA Discussion Papers 13101, Institute of Labor Economics (IZA).
    2. Lorenzo Almada & Ian McCarthy & Rusty Tchernis, 2016. "What Can We Learn about the Effects of Food Stamps on Obesity in the Presence of Misreporting?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 997-1017.
    3. Kaspar W thrich, 2013. "Set Identification of Generalized Linear Predictors in the Presence of Non-Classical Measurement Errors," Diskussionsschriften dp1304, Universitaet Bern, Departement Volkswirtschaft.
    4. vom Lehn, Christian & Ellsworth, Cache & Kroff, Zachary, 2020. "Reconciling Occupational Mobility in the Current Population Survey," IZA Discussion Papers 13509, Institute of Labor Economics (IZA).
    5. Hossein Kavand & Marcel-Cristian Voia, 2016. "Estimation of Health Care Demand and its Implication on Income Effects of Individuals," Carleton Economic Papers 16-01, Carleton University, Department of Economics, revised 26 Jun 2017.
    6. Battistin, Erich & De Nadai, Michele & Krishnan, Nandini, 2020. "The Insights and Illusions of Consumption Measurements," IZA Discussion Papers 13222, Institute of Labor Economics (IZA).
    7. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Lv, Bingyang & Liu, Yongzheng & Li, Yan, 2020. "Fiscal incentives, competition, and investment in China," China Economic Review, Elsevier, vol. 59(C).
    9. Laurent Davezies & Thomas Le Barbanchon, 2014. "Regression Discontinuity Design with Continuous Measurement Error in the Running Variable," Working Papers 2014-27, Center for Research in Economics and Statistics.
    10. 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.
    11. Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
    12. Nicolas R. Ziebarth & Maike Schmitt & Martin Karlsson, 2014. "The Short-Term Population Health Effects of Weather and Pollution: Implications of Climate Change," SOEPpapers on Multidisciplinary Panel Data Research 646, DIW Berlin, The German Socio-Economic Panel (SOEP).
    13. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Second Version," PIER Working Paper Archive 15-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 11 Nov 2015.
    14. Dongwoo Kim & Daniel Wilhelm, 2017. "Powerful t-Tests in the presence of nonclassical measurement error," CeMMAP working papers CWP57/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Michele De Nadai & Arthur Lewbel, 2012. "Nonparametric Errors in Variables Models with Measurement Errors on both sides of the Equation," Boston College Working Papers in Economics 790, Boston College Department of Economics, revised 01 Jul 2013.
    16. Young Jun Lee & Daniel Wilhelm, 2020. "Testing for the presence of measurement error in Stata," Stata Journal, StataCorp LP, vol. 20(2), pages 382-404, June.
    17. Benjamin Williams, 2018. "Identification of a Nonseparable Model under Endogeneity using Binary Proxies for Unobserved Heterogeneity," Working Papers 2018-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    18. Kambayashi, Ryo & Kawaguchi, Daiji & Yamada, Ken, 2010. "The Minimum Wage in a Deflationary Economy: The Japanese Experience, 1994-2003," IZA Discussion Papers 4949, Institute of Labor Economics (IZA).
    19. Erich Battistin & Michele De Nadai & Daniela Vuri, 2014. "Counting Rotten Apples: Student Achievement and Score Manipulation in Italian Elementary Schools," CEIS Research Paper 329, Tor Vergata University, CEIS, revised 08 Sep 2014.
    20. Hu, Yingyao, 2021. "Identification of Causal Models with Unobservables: A Self-Report Approach," Economics Working Paper Archive 64330, The Johns Hopkins University,Department of Economics.
    21. Manuel Arellano & Stéphane Bonhomme, 2019. "Recovering Latent Variables by Matching," Working Papers wp2019_1914, CEMFI.
    22. Daniel Wilhelm, 2019. "Testing for the presence of measurement error," CeMMAP working papers CWP48/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Hao Dong & Yuya Sasaki, 2022. "Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving," Papers 2209.05914, arXiv.org.
    24. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Third Version," PIER Working Paper Archive 15-040, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 24 Nov 2015.
    25. Karun Adusumilli & Taisuke Otsu, 2015. "Nonparametric instrumental regression with errors in variables," STICERD - Econometrics Paper Series /2015/585, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    26. Tanya Byker & Italo A. Gutierrez, 2016. "Treatment Effects Using Inverse Probability Weighting and Contaminated Treatment Data An Application to the Evaluation of a Government Female Sterilization Campaign in Peru," Working Papers WR-1118-1, RAND Corporation.
    27. Nicolas R. Ziebarth, 2009. "Long-Term Absenteeism and Moral Hazard: Evidence from a Natural Experiment," Discussion Papers of DIW Berlin 888, DIW Berlin, German Institute for Economic Research.
    28. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2018. "Nonparametric estimation in case of endogenous selection," Journal of Econometrics, Elsevier, vol. 202(2), pages 268-285.
    29. Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Average Derivative Estimation Under Measurement Error," Departmental Working Papers 1901, Southern Methodist University, Department of Economics.
    30. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers 34/15, Institute for Fiscal Studies.
    31. Andrew Chesher & Adam Rosen, 2019. "Generalized Instrumental Variable Models, Methods, and Applications," CeMMAP working papers CWP41/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    32. Arun Advani & Bansi Malde, 2018. "Credibly Identifying Social Effects: Accounting For Network Formation And Measurement Error," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1016-1044, September.
    33. Makridis, Christos A. & Wang, Tao, 2024. "Learning from Friends in a Pandemic: Social networks and the macroeconomic response of consumption," European Economic Review, Elsevier, vol. 169(C).
    34. Battistin, Erich & Chesher, Andrew, 2014. "Treatment effect estimation with covariate measurement error," Journal of Econometrics, Elsevier, vol. 178(2), pages 707-715.
    35. Hachmi Ben Ameur & Fredj Jawadi & Abdoulkarim Idi Cheffou & Wael Louhichi, 2018. "Measurement errors in stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 287-306, March.
    36. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
    37. Hao Dong & Daniel L. Millimet, 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," Departmental Working Papers 2013, Southern Methodist University, Department of Economics.
    38. Botosaru, Irene, 2023. "Time-varying unobserved heterogeneity in earnings shocks," Journal of Econometrics, Elsevier, vol. 235(2), pages 1378-1393.
    39. Takeshi Yagihashi & Juan Du, 2020. "Intertemporal Elasticity of Substitution with Leisure Margin," Discussion papers ron322, Policy Research Institute, Ministry of Finance Japan.
    40. Battistin, Erich & De Nadai, Michele & Sianesi, Barbara, 2014. "Misreported schooling, multiple measures and returns to educational qualifications," Journal of Econometrics, Elsevier, vol. 181(2), pages 136-150.
    41. Louis‐Philippe Morin, 2013. "Estimating the benefit of high school for university‐bound students: evidence of subject‐specific human capital accumulation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(2), pages 441-468, May.
    42. Shiu, Ji-Liang, 2016. "Identification and estimation of endogenous selection models in the presence of misclassification errors," Economic Modelling, Elsevier, vol. 52(PB), pages 507-518.
    43. Lin, Zhongjian & Hu, Yingyao, 2024. "Binary choice with misclassification and social interactions, with an application to peer effects in attitude," Journal of Econometrics, Elsevier, vol. 238(1).
    44. Ashish Arora & Michelle Gittelman & Sarah Kaplan & John Lynch & Will Mitchell & Nicolaj Siggelkow & Chunmian Ge & Ke-Wei Huang & Ivan P. L. Png, 2016. "Engineer/scientist careers: Patents, online profiles, and misclassification bias," Strategic Management Journal, Wiley Blackwell, vol. 37(1), pages 232-253, January.
    45. Chalak, Karim, 2024. "Nonparametric Gini-Frisch bounds," Journal of Econometrics, Elsevier, vol. 238(1).
    46. Yao Luo & Ruli Xiao, 2022. "Identification of Auction Models Using Order Statistics," Papers 2205.12917, arXiv.org, revised Apr 2023.
    47. Florence Neymotin, 2014. "How Parental Involvement Affects Childhood Behavioral Outcomes," Journal of Family and Economic Issues, Springer, vol. 35(4), pages 433-451, December.
    48. Hahn, Jinyong & Ridder, Geert, 2017. "Instrumental variable estimation of nonlinear models with nonclassical measurement error using control variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 238-250.
    49. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    50. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    51. Ryo Kambayashi & Daiji Kawaguchi & Ken Yamada, 2012. "Minimum Wage in a Deflationary Economy: The Japanese Experience, 1994–2003," Working Papers 35-2012, Singapore Management University, School of Economics.
    52. Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    53. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.
    54. Andrei Zeleneev & Kirill Evdokimov, 2023. "Simple estimation of semiparametric models with measurement errors," CeMMAP working papers 10/23, Institute for Fiscal Studies.
    55. Giovanni Compiani & Yuichi Kitamura, 2016. "Using mixtures in econometric models: a brief review and some new results," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 95-127, October.
    56. Christoph Breunig & Stephan Martin, 2020. "Nonclassical Measurement Error in the Outcome Variable," Papers 2009.12665, arXiv.org, revised May 2021.
    57. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    58. Abito, Jose Miguel, 2019. "Estimating Production Functions with Fixed Effects," MPRA Paper 97825, University Library of Munich, Germany.
    59. Batarce, Marco, 2016. "Estimation of urban bus transit marginal cost without cost data," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 241-262.
    60. Liu, Yibin & Wu, Wenbin, 2017. "Closed-form estimation of a regression model with a mismeasured binary regressor and heteroskedasticity," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 202-206.
    61. Hu, Yingyao & Sasaki, Yuya, 2015. "Closed-form estimation of nonparametric models with non-classical measurement errors," Journal of Econometrics, Elsevier, vol. 185(2), pages 392-408.
    62. Chen, Xiaohong & Linton, Oliver & Yi, Yanping, 2017. "Semiparametric identification of the bid–ask spread in extended Roll models," Journal of Econometrics, Elsevier, vol. 200(2), pages 312-325.
    63. Diaz-Serrano, Luis & Nilsson, William, 2017. "The Reliability of Students' Earnings Expectations," IZA Discussion Papers 10700, Institute of Labor Economics (IZA).
    64. Lina Zhang, 2020. "Spillovers of Program Benefits with Missing Network Links," Papers 2009.09614, arXiv.org, revised Aug 2024.
    65. Meyer, Bruce D. & Mittag, Nikolas, 2017. "Misclassification in binary choice models," Journal of Econometrics, Elsevier, vol. 200(2), pages 295-311.
    66. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers 03/15, Institute for Fiscal Studies.
    67. Robert Grafstein, 2018. "The problem of polarization," Public Choice, Springer, vol. 176(1), pages 315-340, July.
    68. Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
    69. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
    70. Glennon, Dennis & Kiefer, Hua & Mayock, Tom, 2018. "Measurement error in residential property valuation: An application of forecast combination," Journal of Housing Economics, Elsevier, vol. 41(C), pages 1-29.
    71. Mwale, Martin Limbikani, 2023. "Do agricultural subsidies matter for women’s attitude towards intimate partner violence? Evidence from Malawi," Economic Modelling, Elsevier, vol. 128(C).
    72. Hjertstrand, Per, 2013. "A Simple Method to Account for Measurement Errors in Revealed Preference Tests," Working Paper Series 990, Research Institute of Industrial Economics.
    73. Federico Crudu, 2017. "Errors-in-Variables Models with Many Proxies," Department of Economics University of Siena 774, Department of Economics, University of Siena.
    74. Hao, Zhuang & Zhang, Xudong & Wang, Yuze, 2024. "Assessing the accuracy of self-reported health expenditure data: Evidence from two public surveys in China," Social Science & Medicine, Elsevier, vol. 356(C).
    75. Kim, Seonjin & Zhao, Zhibiao, 2014. "Specification test for Markov models with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 118-133.
    76. Arun Advani & Bansi Malde, 2014. "Empirical methods for networks data: social effects, network formation and measurement error," IFS Working Papers W14/34, Institute for Fiscal Studies.
    77. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers CWP03/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    78. Batarce, Marco, 2024. "Estimation of discrete choice models with error in variables: An application to revealed preference data with aggregate service level variables," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    79. Adeniyi, Isaac Adeola, 2020. "Bayesian Generalized Linear Mixed Effects Models Using Normal-Independent Distributions: Formulation and Applications," MPRA Paper 99165, University Library of Munich, Germany.
    80. Luo, Yao & Xiao, Ruli, 2023. "Identification of auction models using order statistics," Journal of Econometrics, Elsevier, vol. 236(1).
    81. Jaanika Meriküll & Tairi Rõõm, 2020. "Stress Tests of the Household Sector Using Microdata from Survey and Administrative Sources," International Journal of Central Banking, International Journal of Central Banking, vol. 16(2), pages 203-248, March.

  10. Han Hong & Denis Nekipelov, 2010. "Semiparametric efficiency in nonlinear LATE models," Quantitative Economics, Econometric Society, vol. 1(2), pages 279-304, November.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    2. Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    3. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2012. "Estimating Conditional Average Treatment Effects," CEU Working Papers 2012_16, Department of Economics, Central European University, revised 20 Jul 2012.
    4. Tymon S{l}oczy'nski, 2020. "When Should We (Not) Interpret Linear IV Estimands as LATE?," Papers 2011.06695, arXiv.org, revised Oct 2024.
    5. Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers 57/13, Institute for Fiscal Studies.
    6. Tymon Sloczynski & Derya Uysal & Jeffrey Wooldridge, 2023. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," Rationality and Competition Discussion Paper Series 424, CRC TRR 190 Rationality and Competition.
    7. Atila Abdulkadiroğlu & Joshua D. Angrist & Yusuke Narita & Parag A. Pathak, 2017. "Research Design Meets Market Design: Using Centralized Assignment for Impact Evaluation," Econometrica, Econometric Society, vol. 85, pages 1373-1432, September.
    8. Zhichao Jiang & Shu Yang & Peng Ding, 2022. "Multiply robust estimation of causal effects under principal ignorability," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1423-1445, September.
    9. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    10. George Gui & Harikesh Nair & Fengshi Niu, 2021. "Auction Throttling and Causal Inference of Online Advertising Effects," Papers 2112.15155, arXiv.org, revised Feb 2022.
    11. Haitian Xie, 2020. "Efficient and Robust Estimation of the Generalized LATE Model," Papers 2001.06746, arXiv.org, revised Feb 2022.
    12. Sloczynski, Tymon, 2021. "When Should We (Not) Interpret Linear IV Estimands as LATE?," IZA Discussion Papers 14349, Institute of Labor Economics (IZA).
    13. Ansel Jason & Hong Han & Jessie Li and, 2018. "OLS and 2SLS in Randomized and Conditionally Randomized Experiments," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 238(3-4), pages 243-293, July.
    14. Yumou Qiu & Jing Tao & Xiao‐Hua Zhou, 2021. "Inference of heterogeneous treatment effects using observational data with high‐dimensional covariates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 1016-1043, November.
    15. Yuehao Bai & Hongchang Guo & Azeem M. Shaikh & Max Tabord-Meehan, 2023. "Inference in Experiments with Matched Pairs and Imperfect Compliance," Papers 2307.13094, arXiv.org, revised Jun 2024.
    16. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.

  11. Bajari, Patrick & Hong, Han & Krainer, John & Nekipelov, Denis, 2010. "Estimating Static Models of Strategic Interactions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 469-482.
    See citations under working paper version above.

Chapters

  1. Tatiana Komarova & Denis Nekipelov & Evgeny Yakovlev, 2015. "Estimation of Treatment Effects from Combined Data: Identification versus Data Security," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 279-308, National Bureau of Economic Research, Inc.

    Cited by:

    1. Tatiana V. Komarova & Denis Nekipelov & Evgeny Yakovlev, 2011. "Identification, data combination and the risk of disclosure," CeMMAP working papers CWP38/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Amalia R. Miller & Catherine Tucker, 2017. "Frontiers of Health Policy: Digital Data and Personalized Medicine," Innovation Policy and the Economy, University of Chicago Press, vol. 17(1), pages 49-75.
    3. Komarova, Tatiana & Nekipelov, Denis & Al Rafi, Ahnaf & Yakovlev, Evgeny, 2017. "K-anonymity: a note on the trade-off between data utility and data security," LSE Research Online Documents on Economics 85923, London School of Economics and Political Science, LSE Library.
    4. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    5. Amalia R. Miller & Catherine Tucker, 2018. "Privacy Protection, Personalized Medicine, and Genetic Testing," Management Science, INFORMS, vol. 64(10), pages 4648-4668, October.
    6. Tatiana Komarova & Denis Nekipelov, 2020. "Identification and Formal Privacy Guarantees," Papers 2006.14732, arXiv.org, revised May 2021.

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