Yuya Sasaki
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
- Yukun Ma & Pedro H. C. Sant'Anna & Yuya Sasaki & Takuya Ura, 2023.
"Doubly Robust Estimators with Weak Overlap,"
Papers
2304.08974, arXiv.org, revised Apr 2023.
Cited by:
- Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
- Ruonan Xu, 2023. "Difference-in-Differences with Interference," Papers 2306.12003, arXiv.org, revised Feb 2024.
- Ji Hyung Lee & Yuya Sasaki & Alexis Akira Toda & Yulong Wang, 2022.
"Capital and Labor Income Pareto Exponents in the United States, 1916-2019,"
Papers
2206.04257, arXiv.org.
Cited by:
- Harmenberg, Karl, 2020.
"A Simple Theory of Pareto Earnings,"
Working Papers
21-2020, Copenhagen Business School, Department of Economics.
- Harmenberg, Karl, 2024. "A simple theory of Pareto-distributed earnings," Economics Letters, Elsevier, vol. 234(C).
- Ji Hyung Lee & Yuya Sasaki & Alexis Akira Toda & Yulong Wang, 2022.
"Tuning Parameter-Free Nonparametric Density Estimation from Tabulated Summary Data,"
Papers
2204.05480, arXiv.org, revised May 2023.
- Lee, Ji Hyung & Sasaki, Yuya & Toda, Alexis Akira & Wang, Yulong, 2024. "Tuning parameter-free nonparametric density estimation from tabulated summary data," Journal of Econometrics, Elsevier, vol. 238(1).
- Harmenberg, Karl, 2020.
"A Simple Theory of Pareto Earnings,"
Working Papers
21-2020, Copenhagen Business School, Department of Economics.
- Yuya Sasaki & Yulong Wang, 2022.
"Non-Robustness of the Cluster-Robust Inference: with a Proposal of a New Robust Method,"
Papers
2210.16991, arXiv.org, revised Dec 2022.
Cited by:
- Harold D. Chiang & Yuya Sasaki & Yulong Wang, 2023. "On the Inconsistency of Cluster-Robust Inference and How Subsampling Can Fix It," Papers 2308.10138, arXiv.org, revised Mar 2024.
- Harold D Chiang & Bruce E Hansen & Yuya Sasaki, 2022.
"Standard errors for two-way clustering with serially correlated time effects,"
Papers
2201.11304, arXiv.org, revised Dec 2023.
Cited by:
- Kaicheng Chen & Timothy J. Vogelsang, 2023. "Fixed-b Asymptotics for Panel Models with Two-Way Clustering," Papers 2309.08707, arXiv.org, revised May 2024.
- Xavier D'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2021.
"Nonparametric Difference-in-Differences in Repeated Cross-Sections with Continuous Treatments,"
Papers
2104.14458, arXiv.org, revised May 2022.
- 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.
Cited by:
- Clément de Chaisemartin & Xavier d'Haultfoeuille & Félix Pasquier & Gonzalo Vazquez-Bare, 2022.
"Difference-in-Differences Estimators for Treatments Continuously Distributed at Every Period,"
SciencePo Working papers Main
hal-03873926, HAL.
- Clément de Chaisemartin & Xavier d'Haultfoeuille & Félix Pasquier & Gonzalo Vazquez-Bare, 2022. "Difference-in-Differences Estimators for Treatments Continuously Distributed at Every Period," Working Papers hal-03873926, HAL.
- Cl'ement de Chaisemartin & Xavier D'Haultfoeuille & F'elix Pasquier & Gonzalo Vazquez-Bare, 2022. "Difference-in-Differences Estimators for Treatments Continuously Distributed at Every Period," Papers 2201.06898, arXiv.org, revised Dec 2023.
- Yan Zhao & Ehsan Elahi & Zainab Khalid & Xuegang Sun & Fang Sun, 2023. "Environmental, Social and Governance Performance: Analysis of CEO Power and Corporate Risk," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
- Carolina Caetano & Gregorio Caetano & Hao Fe & Eric R. Nielsen, 2021. "A Dummy Test of Identification in Models with Bunching," Finance and Economics Discussion Series 2021-068, Board of Governors of the Federal Reserve System (U.S.).
- Shun Yiu & Rob Seamans & Manav Raj & Ted Liu, 2024. "Strategic Responses to Technological Change: Evidence from ChatGPT and Upwork," Papers 2403.15262, arXiv.org, revised Apr 2024.
- Yuya Sasaki & Takuya Ura, 2021.
"Slow Movers in Panel Data,"
Papers
2110.12041, arXiv.org.
Cited by:
- M. Hashem Pesaran & Liying Yang, 2023.
"Trimmed Mean Group Estimation of Average Treatment Effects in Ultra Short T Panels under Correlated Heterogeneity,"
CESifo Working Paper Series
10725, CESifo.
- M. Hashem Pesaran & Liying Yang, 2023. "Trimmed Mean Group Estimation of Average Treatment Effects in Ultra Short T Panels under Correlated Heterogeneity," Papers 2310.11680, arXiv.org.
- Pesaran, M. H. & Yang, L., 2023. "Trimmed Mean Group Estimation of Average Treatment Effects in Ultra Short T Panels under Correlated Heterogeneity," Cambridge Working Papers in Economics 2364, Faculty of Economics, University of Cambridge.
- M. Hashem Pesaran & Liying Yang, 2023.
"Trimmed Mean Group Estimation of Average Treatment Effects in Ultra Short T Panels under Correlated Heterogeneity,"
CESifo Working Paper Series
10725, CESifo.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki & Takuya Ura, 2021.
"Linear programming approach to nonparametric inference under shape restrictions: with an application to regression kink designs,"
Papers
2102.06586, arXiv.org.
Cited by:
- Villamizar-Villegas, Mauricio & Pinzón-Puerto, Freddy A. & Ruiz-Sánchez, María Alejandra, 2020.
"A Comprehensive History of Regression Discontinuity Designs: An Empirical Survey of the last 60 Years,"
Working papers
38, Red Investigadores de Economía.
- Mauricio Villamizar‐Villegas & Freddy A. Pinzon‐Puerto & Maria Alejandra Ruiz‐Sanchez, 2022. "A comprehensive history of regression discontinuity designs: An empirical survey of the last 60 years," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1130-1178, September.
- Mauricio Villamizar-Villegas & Freddy A. Pinzón-Puerto & María Alejandra Ruiz-Sánchez, 2020. "A Comprehensive History of Regression Discontinuity Designs: An Empirical Survey of the last 60 Years," Borradores de Economia 1112, Banco de la Republica de Colombia.
- Zheng Fang, 2021. "A Unifying Framework for Testing Shape Restrictions," Papers 2107.12494, arXiv.org, revised Aug 2021.
- Villamizar-Villegas, Mauricio & Pinzón-Puerto, Freddy A. & Ruiz-Sánchez, María Alejandra, 2020.
"A Comprehensive History of Regression Discontinuity Designs: An Empirical Survey of the last 60 Years,"
Working papers
38, Red Investigadores de Economía.
- Yuya Sasaki & Takuya Ura, 2020.
"Welfare Analysis via Marginal Treatment Effects,"
Papers
2012.07624, arXiv.org.
Cited by:
- Yan Liu, 2022. "Policy Learning under Endogeneity Using Instrumental Variables," Papers 2206.09883, arXiv.org, revised Mar 2024.
- Toru Kitagawa & Hugo Lopez & Jeff Rowley, 2022. "Stochastic Treatment Choice with Empirical Welfare Updating," Papers 2211.01537, arXiv.org, revised Feb 2023.
- Yu-Chang Chen & Haitian Xie, 2022. "Personalized Subsidy Rules," Papers 2202.13545, arXiv.org, revised Mar 2022.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki, 2020.
"Inference for high-dimensional exchangeable arrays,"
Papers
2009.05150, arXiv.org, revised Jul 2021.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki, 2023. "Inference for High-Dimensional Exchangeable Arrays," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(543), pages 1595-1605, July.
Cited by:
- Harold D Chiang & Bruce E Hansen & Yuya Sasaki, 2022. "Standard errors for two-way clustering with serially correlated time effects," Papers 2201.11304, arXiv.org, revised Dec 2023.
- Victor Chernozhukov & Denis Chetverikov & Kengo Kato & Yuta Koike, 2022. "High-dimensional Data Bootstrap," Papers 2205.09691, arXiv.org.
- Harold D Chiang & Yukitoshi Matsushita & Taisuke Otsu, 2021. "Multiway empirical likelihood," STICERD - Econometrics Paper Series 617, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Harold D Chiang & Yukitoshi Matsushita & Taisuke Otsu, 2021. "Multiway empirical likelihood," Papers 2108.04852, arXiv.org, revised Dec 2023.
- Harold D. Chiang & Jiatong Li & Yuya Sasaki, 2021. "Algorithmic subsampling under multiway clustering," Papers 2103.00557, arXiv.org, revised Oct 2022.
- Lu, Zhentong & Shi, Xiaoxia & Tao, Jing, 2023. "Semi-nonparametric estimation of random coefficients logit model for aggregate demand," Journal of Econometrics, Elsevier, vol. 235(2), pages 2245-2265.
- Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020.
"Unconditional Quantile Regression with High Dimensional Data,"
Papers
2007.13659, arXiv.org, revised Feb 2022.
- 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.
Cited by:
- Zequn Jin & Lihua Lin & Zhengyu Zhang, 2022. "Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives," Papers 2211.07903, arXiv.org.
- Hui-Ching Chuang & Jau-er Chen, 2023. "Exploring Industry-Distress Effects on Loan Recovery: A Double Machine Learning Approach for Quantiles," Econometrics, MDPI, vol. 11(1), pages 1-20, February.
- Taisuke Otsu & Martin Pesendorfer & Yuya Sasaki & Yuya Takahashi, 2020.
"Estimation of (static or dynamic) games under equilibrium multiplicity,"
STICERD - Econometrics Paper Series
611, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Taisuke Otsu & Martin Pesendorfer & Yuya Sasaki & Yuya Takahashi, 2022. "Estimation Of (Static Or Dynamic) Games Under Equilibrium Multiplicity," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1165-1188, August.
- Otsu, Taisuke & Pesendorfer, Martin & Sasaki, Yuya & Takahashi, Yuya, 2022. "Estimation of (static or dynamic) games under equilibrium multiplicity," LSE Research Online Documents on Economics 112785, London School of Economics and Political Science, LSE Library.
- Pesendorfer, Martin & Otsu, Taisuke & Sasaki, Yuya & Takahashi, Yuya, 2020. "Estimation of (static or dynamic) games under equilibrium multiplicity," CEPR Discussion Papers 14342, C.E.P.R. Discussion Papers.
Cited by:
- Sasaki, Yuya & Takahashi, Yuya & Xin, Yi & Hu, Yingyao, 2023. "Dynamic discrete choice models with incomplete data: Sharp identification," Journal of Econometrics, Elsevier, vol. 236(1).
- Yuya Sasaki & Yulong Wang, 2019.
"Fixed-k Inference for Conditional Extremal Quantiles,"
Papers
1909.00294, arXiv.org, revised Jul 2020.
- 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.
Cited by:
- Nicolau, João & Rodrigues, Paulo M.M. & Stoykov, Marian Z., 2023.
"Tail index estimation in the presence of covariates: Stock returns’ tail risk dynamics,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 2266-2284.
- Paulo M.M. Rodrigues & João Nicolau, 2023. "Tail index estimation in the presence of covariates: Stock returns’ tail risk dynamics," Working Papers w202306, Banco de Portugal, Economics and Research Department.
- Yuya Sasaki & Yulong Wang, 2024.
"Extreme Changes in Changes,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 812-824, April.
- Yuya Sasaki & Yulong Wang, 2022. "Extreme Changes in Changes," Papers 2211.14870, arXiv.org, revised May 2023.
- Harold D. Chiang & Kengo Kato & Yukun Ma & Yuya Sasaki, 2019.
"Multiway Cluster Robust Double/Debiased Machine Learning,"
Papers
1909.03489, arXiv.org, revised Mar 2020.
- Harold D. Chiang & Kengo Kato & Yukun Ma & Yuya Sasaki, 2022. "Multiway Cluster Robust Double/Debiased Machine Learning," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1046-1056, June.
Cited by:
- Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org, revised Apr 2024.
- James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2022.
"Cluster-Robust Inference: A Guide to Empirical Practice,"
Working Paper
1456, Economics Department, Queen's University.
- James MacKinnon & Morten Ørregaard Nielsen, 2022. "Cluster-Robust Inference: A Guide to Empirical Practice," CREATES Research Papers 2022-08, Department of Economics and Business Economics, Aarhus University.
- Matthew D. Webb & James MacKinnon & Morten Nielsen, 2021. "Cluster–robust inference: A guide to empirical practice," Economics Virtual Symposium 2021 6, Stata Users Group.
- MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Cluster-robust inference: A guide to empirical practice," Journal of Econometrics, Elsevier, vol. 232(2), pages 272-299.
- James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2022. "Cluster-Robust Inference: A Guide to Empirical Practice," Papers 2205.03285, arXiv.org.
- Philipp Bach & Victor Chernozhukov & Malte S. Kurz & Martin Spindler, 2021. "DoubleML -- An Object-Oriented Implementation of Double Machine Learning in Python," Papers 2104.03220, arXiv.org, revised Dec 2021.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki, 2023.
"Inference for High-Dimensional Exchangeable Arrays,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(543), pages 1595-1605, July.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki, 2020. "Inference for high-dimensional exchangeable arrays," Papers 2009.05150, arXiv.org, revised Jul 2021.
- Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
- Harold D. Chiang & Jiatong Li & Yuya Sasaki, 2021. "Algorithmic subsampling under multiway clustering," Papers 2103.00557, arXiv.org, revised Oct 2022.
- Davide Viviano & Jelena Bradic, 2020. "Fair Policy Targeting," Papers 2005.12395, arXiv.org, revised Jun 2022.
- Bryan S. Graham & Fengshi Niu & James L. Powell, 2021.
"Minimax Risk and Uniform Convergence Rates for Nonparametric Dyadic Regression,"
NBER Working Papers
28548, National Bureau of Economic Research, Inc.
- Bryan S. Graham & Fengshi Niu & James L. Powell, 2020. "Minimax Risk and Uniform Convergence Rates for Nonparametric Dyadic Regression," Papers 2012.08444, arXiv.org, revised Mar 2021.
- Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019.
"Post-Selection Inference in Three-Dimensional Panel Data,"
Papers
1904.00211, arXiv.org, revised Apr 2019.
- Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
Cited by:
- 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.
- Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
- Harold D. Chiang & Yuya Sasaki, 2019.
"Lasso under Multi-way Clustering: Estimation and Post-selection Inference,"
Papers
1905.02107, arXiv.org, revised Aug 2019.
Cited by:
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2019. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Papers 1912.06307, arXiv.org, revised Feb 2021.
- Harold D. Chiang & Kengo Kato & Yukun Ma & Yuya Sasaki, 2022.
"Multiway Cluster Robust Double/Debiased Machine Learning,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1046-1056, June.
- Harold D. Chiang & Kengo Kato & Yukun Ma & Yuya Sasaki, 2019. "Multiway Cluster Robust Double/Debiased Machine Learning," Papers 1909.03489, arXiv.org, revised Mar 2020.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki, 2023.
"Inference for High-Dimensional Exchangeable Arrays,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(543), pages 1595-1605, July.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki, 2020. "Inference for high-dimensional exchangeable arrays," Papers 2009.05150, arXiv.org, revised Jul 2021.
- Kengo Kato & Yuya Sasaki & Takuya Ura, 2018.
"Inference based on Kotlarski's Identity,"
Papers
1808.09375, arXiv.org, revised Sep 2019.
Cited by:
- Li, Siran & Zheng, Xunjie, 2020. "A generalization of Lemma 1 in Kotlarski (1967)," Statistics & Probability Letters, Elsevier, vol. 165(C).
- Adusumilli, Karun & Kurisu, Daisuke & Otsu, Taisuke & Whang, Yoon-Jae, 2020.
"Inference on distribution functions under measurement error,"
Journal of Econometrics, Elsevier, vol. 215(1), pages 131-164.
- Karun Adusumilli & Taisuke Otsu & Yoon-Jae Whang, 2017. "Inference on distribution functions under measurement error," STICERD - Econometrics Paper Series 594, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Karun Adusumilli & Taisuke Otsu & Yoon-Jae Whang, "undated". "Inference On Distribution Functions Under Measurement Error," Working Paper Series no108, Institute of Economic Research, Seoul National University.
- William Morrison & Dmitry Taubinsky, 2019.
"Rules of Thumb and Attention Elasticities: Evidence from Under- and Overreaction to Taxes,"
NBER Working Papers
26180, National Bureau of Economic Research, Inc.
- William Morrison & Dmitry Taubinsky, 2023. "Rules of Thumb and Attention Elasticities: Evidence from Under- and Overreaction to Taxes," The Review of Economics and Statistics, MIT Press, vol. 105(5), pages 1110-1127, September.
- Adusumilli, Karun & Kurisu, Daisies & Otsu, Taisuke & Whang, Yoon-Jae, 2020. "Inference on distribution functions under measurement error," LSE Research Online Documents on Economics 102692, London School of Economics and Political Science, LSE Library.
- Tong Li & Yuya Sasaki, 2017.
"Constructive Identification of Heterogeneous Elasticities in the Cobb-Douglas Production Function,"
Papers
1711.10031, arXiv.org.
Cited by:
- Victor H. Aguiar & Nail Kashaev & Roy Allen, 2022.
"Prices, Profits, Proxies, and Production,"
University of Western Ontario, Departmental Research Report Series
20226, University of Western Ontario, Department of Economics.
- Aguiar, Victor H. & Kashaev, Nail & Allen, Roy, 2023. "Prices, profits, proxies, and production," Journal of Econometrics, Elsevier, vol. 235(2), pages 666-693.
- Victor H. Aguiar & Roy Allen & Nail Kashaev, 2020. "Prices, Profits, Proxies, and Production," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20202, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
- Victor H. Aguiar & Nail Kashaev & Roy Allen, 2018. "Prices, Profits, Proxies, and Production," Papers 1810.04697, arXiv.org, revised Jun 2022.
- Hiroyuki Kasahara & Paul Schrimpf & Michio Suzuki, 2023.
"Identification and Estimation of Production Function with Unobserved Heterogeneity,"
Papers
2305.12067, arXiv.org.
- Paul Schrimpf & Michio Suzuki & Hiroyuki Kasahara, 2015. "Identification and Estimation of Production Function with Unobserved Heterogeneity," 2015 Meeting Papers 924, Society for Economic Dynamics.
- Hiroyuki Kasahara & Paul Schrimpf & CMichio Suzuki, 2023. "Identification and Estimation of Production Function with Unobserved Heterogeneity," TUPD Discussion Papers 38, Graduate School of Economics and Management, Tohoku University.
- Ming Li, 2021. "A Time-Varying Endogenous Random Coefficient Model with an Application to Production Functions," Papers 2110.00982, arXiv.org.
- Yu Hao & Hiroyuki Kasahara, 2022. "Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data," Papers 2210.02824, arXiv.org, revised Jun 2023.
- Victor H. Aguiar & Nail Kashaev & Roy Allen, 2022.
"Prices, Profits, Proxies, and Production,"
University of Western Ontario, Departmental Research Report Series
20226, University of Western Ontario, Department of Economics.
- Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013.
"Nonlinear difference-in-differences in repeated cross sections with continuous treatments,"
CeMMAP working papers
40/13, Institute for Fiscal Studies.
- Xavier D'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear Difference-in-Differences in Repeated Cross Sections with Continuous Treatments," Boston College Working Papers in Economics 839, Boston College Department of Economics.
- Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers CWP40/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Cited by:
- Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
- Clément de Chaisemartin & Xavier d'Haultfoeuille, 2014.
"Fuzzy Changes-in-Changes,"
Working Papers
2014-18, Center for Research in Economics and Statistics.
- de Chaisemartin, Clement & D'Haultfoeuille, Xavier, 2014. "Fuzzy Changes-in Changes," CAGE Online Working Paper Series 184, Competitive Advantage in the Global Economy (CAGE).
- de Chaisemartin, Clement & D'Haultfoeuille, Xavier, 2015. "Fuzzy Differences-in-Differences," The Warwick Economics Research Paper Series (TWERPS) 1065, University of Warwick, Department of Economics.
- Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.
- 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.
- Clément de Chaisemartin, 2012.
"Fuzzy differences in differences,"
Working Papers
halshs-00671368, HAL.
- Clément de Chaisemartin, 2011. "Fuzzy Differences in Differences," Working Papers 2011-10, Center for Research in Economics and Statistics.
- Clément de Chaisemartin, 2012. "Fuzzy differences in differences," PSE Working Papers halshs-00671368, HAL.
- Clément de Chaisemartin & Xavier d'Haultfoeuille, 2015. "Fuzzy differences-in-differences," CeMMAP working papers 69/15, Institute for Fiscal Studies.
- C de Chaisemartin & X D’HaultfŒuille, 2018. "Fuzzy Differences-in-Differences," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 999-1028.
- Clément de Chaisemartin & Xavier d'Haultfoeuille, 2015. "Fuzzy differences-in-differences," CeMMAP working papers CWP69/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- de Chaisemartin, Clement & D'Haultfoeuille, Xavier, 2015. "Fuzzy Differences-in-Differences," The Warwick Economics Research Paper Series (TWERPS) 1065, University of Warwick, Department of Economics.
- Clément de CHAISEMARTIN, 2010. "Fuzzy Differences in Differences," Working Papers 2010-08, Center for Research in Economics and Statistics.
- de Chaisemartin, Clement & D'Haultfoeuille, Xavier, "undated". "Fuzzy Differences-in-Differences," Economic Research Papers 270218, University of Warwick - Department of Economics.
- 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.
- Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers 31/17, Institute for Fiscal Studies.
- 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.
- Michela Tincani, 2017. "Heterogeneous Peer Effects and Rank Concerns: Theory and Evidence," Working Papers 2017-006, Human Capital and Economic Opportunity Working Group.
- Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
- Carolina Caetano & Juan Carlos Escaniano, 2015. "Identifying Multiple Marginal Effects with a Single Binary Instrument or by Regression Discontinuity," CAEPR Working Papers 2015-009, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
- Michela Maria Tincani, 2017. "Heterogeneous Peer Effects and Rank Concerns: Theory and Evidence," CESifo Working Paper Series 6331, CESifo.
- Florian Gunsilius, 2018. "Point-identification in multivariate nonseparable triangular models," Papers 1806.09680, arXiv.org.
- Stefan Hoderlein & Yuya Sasaki, 2013.
"Outcome conditioned treatment effects,"
CeMMAP working papers
39/13, Institute for Fiscal Studies.
- Stefan Hoderlein & Yuya Sasaki, 2013. "Outcome Conditioned Treatment Effects," Boston College Working Papers in Economics 840, Boston College Department of Economics.
- Stefan Hoderlein & Yuya Sasaki, 2013. "Outcome conditioned treatment effects," CeMMAP working papers CWP39/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Cited by:
- Xavier D'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013.
"Nonlinear Difference-in-Differences in Repeated Cross Sections with Continuous Treatments,"
Boston College Working Papers in Economics
839, Boston College Department of Economics.
- Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers 40/13, Institute for Fiscal Studies.
- Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers CWP40/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Kasy, Maximilian, "undated". "Instrumental variables with unrestricted heterogeneity and continuous treatment - DON'T CITE! SEE ERRATUM BELOW," Working Paper 33257, Harvard University OpenScholar.
- 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.
- Maximilian Kasy, 2014. "Instrumental Variables with Unrestricted Heterogeneity and Continuous Treatment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(4), pages 1614-1636.
Articles
- D’Haultfœuille, Xavier & Hoderlein, Stefan & Sasaki, Yuya, 2024.
"Testing and relaxing the exclusion restriction in the control function approach,"
Journal of Econometrics, Elsevier, vol. 240(2).
Cited by:
- Soonwoo Kwon & Jonathan Roth, 2024. "Testing Mechanisms," Papers 2404.11739, arXiv.org.
- 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.
See citations under working paper version above.
- Xavier D'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2021. "Nonparametric Difference-in-Differences in Repeated Cross-Sections with Continuous Treatments," Papers 2104.14458, arXiv.org, revised May 2022.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki, 2023.
"Inference for High-Dimensional Exchangeable Arrays,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(543), pages 1595-1605, July.
See citations under working paper version above.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki, 2020. "Inference for high-dimensional exchangeable arrays," Papers 2009.05150, arXiv.org, revised Jul 2021.
- Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023.
"Post-Selection Inference In Three-Dimensional Panel Data,"
Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
See citations under working paper version above.
- Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.
- Yuya Sasaki & Yulong Wang, 2023.
"Diagnostic Testing of Finite Moment Conditions for the Consistency and Root-N Asymptotic Normality of the GMM and M Estimators,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 339-348, April.
Cited by:
- Jean-Jacques Forneron, 2023. "Occasionally Misspecified," Papers 2312.05342, arXiv.org.
- Harold D. Chiang & Kengo Kato & Yukun Ma & Yuya Sasaki, 2022.
"Multiway Cluster Robust Double/Debiased Machine Learning,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1046-1056, June.
See citations under working paper version above.
- Harold D. Chiang & Kengo Kato & Yukun Ma & Yuya Sasaki, 2019. "Multiway Cluster Robust Double/Debiased Machine Learning," Papers 1909.03489, arXiv.org, revised Mar 2020.
- Taisuke Otsu & Martin Pesendorfer & Yuya Sasaki & Yuya Takahashi, 2022.
"Estimation Of (Static Or Dynamic) Games Under Equilibrium Multiplicity,"
International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1165-1188, August.
See citations under working paper version above.
- Taisuke Otsu & Martin Pesendorfer & Yuya Sasaki & Yuya Takahashi, 2020. "Estimation of (static or dynamic) games under equilibrium multiplicity," STICERD - Econometrics Paper Series 611, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Otsu, Taisuke & Pesendorfer, Martin & Sasaki, Yuya & Takahashi, Yuya, 2022. "Estimation of (static or dynamic) games under equilibrium multiplicity," LSE Research Online Documents on Economics 112785, London School of Economics and Political Science, LSE Library.
- Pesendorfer, Martin & Otsu, Taisuke & Sasaki, Yuya & Takahashi, Yuya, 2020. "Estimation of (static or dynamic) games under equilibrium multiplicity," CEPR Discussion Papers 14342, C.E.P.R. Discussion Papers.
- Sasaki, Yuya & Ura, Takuya, 2022.
"Estimation And Inference For Moments Of Ratios With Robustness Against Large Trimming Bias,"
Econometric Theory, Cambridge University Press, vol. 38(1), pages 66-112, February.
Cited by:
- 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.
- Yukun Ma & Pedro H. C. Sant'Anna & Yuya Sasaki & Takuya Ura, 2023. "Doubly Robust Estimators with Weak Overlap," Papers 2304.08974, arXiv.org, revised Apr 2023.
- 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.
See citations under working paper version above.
- Yuya Sasaki & Yulong Wang, 2019. "Fixed-k Inference for Conditional Extremal Quantiles," Papers 1909.00294, arXiv.org, revised Jul 2020.
- 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.
See citations under working paper version above.
- Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
- Kengo Kato & Yuya Sasaki & Takuya Ura, 2021.
"Robust inference in deconvolution,"
Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
Cited by:
- 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.
- Hao Dong & Yuya Sasaki, 2022. "Estimation of average derivatives of latent regressors: with an application to inference on buffer-stock saving," Departmental Working Papers 2204, Southern Methodist University, Department of Economics.
- JoonHwan Cho & Yao Luo & Ruli Xiao, 2024. "Deconvolution from two order statistics," Papers 2403.17777, arXiv.org.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Linear programming approach to nonparametric inference under shape restrictions: with an application to regression kink designs," Papers 2102.06586, arXiv.org.
- Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
- JoonHwan Cho & Yao Luo & Ruli Xiao, 2022. "Deconvolution from Two Order Statistics," Working Papers tecipa-739, University of Toronto, Department of Economics.
- Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," LSE Research Online Documents on Economics 112676, London School of Economics and Political Science, LSE Library.
- 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.
- Chen, Heng & Chiang, Harold D. & Sasaki, Yuya, 2020.
"Quantile Treatment Effects In Regression Kink Designs,"
Econometric Theory, Cambridge University Press, vol. 36(6), pages 1167-1191, December.
Cited by:
- Matias D. Cattaneo & Rocio Titiunik, 2021.
"Regression Discontinuity Designs,"
Papers
2108.09400, arXiv.org, revised Feb 2022.
- Matias D. Cattaneo & Rocio Titiunik & Gonzalo Vazquez-Bare, 2019. "The Regression Discontinuity Design," Papers 1906.04242, arXiv.org, revised Jun 2020.
- Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Linear programming approach to nonparametric inference under shape restrictions: with an application to regression kink designs," Papers 2102.06586, arXiv.org.
- Matias D. Cattaneo & Rocio Titiunik, 2021.
"Regression Discontinuity Designs,"
Papers
2108.09400, arXiv.org, revised Feb 2022.
- Hu, Yingyao & Huang, Guofang & Sasaki, Yuya, 2020.
"Estimating production functions with robustness against errors in the proxy variables,"
Journal of Econometrics, Elsevier, vol. 215(2), pages 375-398.
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- Guofang Huang & Yingyao Hu, 2011. "Estimating Production Functions with Robustness Against Errors in the Proxy Variables," Economics Working Paper Archive 583, The Johns Hopkins University,Department of Economics.
Cited by:
- Bournakis, Ioannis & Tsionas, Mike G., 2023. "A Non-Parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," MPRA Paper 118100, University Library of Munich, Germany.
- Manuel Arellano & Stéphane Bonhomme, 2016.
"Nonlinear panel data methods for dynamic heterogeneous agent models,"
CeMMAP working papers
51/16, Institute for Fiscal Studies.
- Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers CWP51/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 471-496, September.
- Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2017_1703, CEMFI.
- Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2016_1607, CEMFI.
- Hu, Yingyao & Huang, Guofang & Sasaki, Yuya, 2020.
"Estimating production functions with robustness against errors in the proxy variables,"
Journal of Econometrics, Elsevier, vol. 215(2), pages 375-398.
- Guofang Huang & Yingyao Hu, 2011. "Estimating Production Functions with Robustness Against Errors in the Proxy Variables," Economics Working Paper Archive 583, The Johns Hopkins University,Department of Economics.
- Guofang Huang & Yingyao Hu, 2011. "Estimating production functions with robustness against errors in the proxy variables," CeMMAP working papers CWP35/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Li, Tong & Sasaki, Yuya, 2024. "Identification of heterogeneous elasticities in gross-output production functions," Journal of Econometrics, Elsevier, vol. 238(2).
- Chen Yeh & Claudia Macaluso & Brad Hershbein, 2022.
"Monopsony in the US Labor Market,"
American Economic Review, American Economic Association, vol. 112(7), pages 2099-2138, July.
- Chen Yeh & Claudia Macaluso & Brah J. Hershbein, 2022. "Monopsony in the U.S. Labor Market," Upjohn Working Papers 22-364, W.E. Upjohn Institute for Employment Research.
- Kim, Kyoo il & Petrin, Amil & Song, Suyong, 2016. "Estimating production functions with control functions when capital is measured with error," Journal of Econometrics, Elsevier, vol. 190(2), pages 267-279.
- Chen, Hanxue & Wang, Shuhong & Song, Malin, 2021. "Global Environmental Value Chain Embeddedness and Enterprise Production Efficiency Improvement," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 278-290.
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- Ainagul T. Mamyralieva & Aziza B. Karbekova & Gulchehra B. Abdyrahmanova, 2022. "Analysis of the economic sectors? sustainability of the Kyrgyz Republic," RIVISTA DI STUDI SULLA SOSTENIBILITA', FrancoAngeli Editore, vol. 0(2), pages 185-204.
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- Mike G. Tsionas & Subal C. Kumbhakar, 2023. "Proxy variable estimation of productivity and efficiency," Southern Economic Journal, John Wiley & Sons, vol. 89(3), pages 885-923, January.
- Tong Li & Yuya Sasaki, 2017. "Constructive Identification of Heterogeneous Elasticities in the Cobb-Douglas Production Function," Papers 1711.10031, arXiv.org.
- Alvaro Aguirre & Matias Tapia & Lucciano Villacorta, 2021. "Production, Investment and Wealth Dynamics under Financial Frictions: An Empirical Investigation of the Selffinancing Channel," Working Papers Central Bank of Chile 904, Central Bank of Chile.
- Abito, Jose Miguel, 2019. "Estimating Production Functions with Fixed Effects," MPRA Paper 97825, University Library of Munich, Germany.
- Mike G. Tsionas & Subal C. Kumbhakar, 2023. "Productivity and Performance: A GMM approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 331-344, April.
- Dibyendu Maiti & Chiranjib Neogi, 2020. "Endogeneity Corrected Stochastic Frontier with Market Imperfections," Working papers 313, Centre for Development Economics, Delhi School of Economics.
- Yingyao Hu & Robert Moffitt & Yuya Sasaki, 2019.
"Semiparametric estimation of the canonical permanent‐transitory model of earnings dynamics,"
Quantitative Economics, Econometric Society, vol. 10(4), pages 1495-1536, November.
Cited by:
- Manuel Arellano & Stéphane Bonhomme, 2019.
"Recovering Latent Variables by Matching,"
Working Papers
wp2019_1914, CEMFI.
- Manuel Arellano & Stéphane Bonhomme, 2020. "Recovering Latent Variables by Matching," CeMMAP working papers CWP2/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Manuel Arellano & Stephane Bonhomme, 2019. "Recovering Latent Variables by Matching," Papers 1912.13081, arXiv.org.
- Manuel Arellano & Stéphane Bonhomme, 2023. "Recovering Latent Variables by Matching," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(541), pages 693-706, January.
- 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.
- Hao Dong & Yuya Sasaki, 2022. "Estimation of average derivatives of latent regressors: with an application to inference on buffer-stock saving," Departmental Working Papers 2204, Southern Methodist University, Department of Economics.
- 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).
- Ivan Fernandez-Val & Wayne Yuan Gao & Yuan Liao & Francis Vella, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," Papers 2202.04154, arXiv.org, revised Jan 2023.
- Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
- Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
- Costanza Naguib, 2022. "Financial Turmoil and Earnings Mobility," Diskussionsschriften dp2208, Universitaet Bern, Departement Volkswirtschaft.
- Joseph G. Altonji & Disa M. Hynsjö & Ivan Vidangos, 2022.
"Individual Earnings and Family Income: Dynamics and Distribution,"
NBER Working Papers
30095, National Bureau of Economic Research, Inc.
- Joseph Altonji & Disa Hynsjo & Ivan Vidangos, 2023. "Individual Earnings and Family Income: Dynamics and Distribution," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 225-250, July.
- Silvia Sarpietro & Yuya Sasaki & Yulong Wang, 2022. "Non-Existent Moments of Earnings Growth," Papers 2203.08014, arXiv.org, revised Feb 2024.
- Costanza Naguib, 2022. "Did earnings mobility change after minimum wage introduction? Evidence from parametric and semi‐nonparametric methods in Germany," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1379-1402, November.
- Kartik B. Athreya & Grey Gordon & John Bailey Jones & Urvi Neelakantan, 2021. "Incarceration, Earnings, and Race," Working Paper 21-11`, Federal Reserve Bank of Richmond.
- Manuel Arellano & Stéphane Bonhomme, 2019.
"Recovering Latent Variables by Matching,"
Working Papers
wp2019_1914, CEMFI.
- Chiang, Harold D. & Sasaki, Yuya, 2019.
"Causal inference by quantile regression kink designs,"
Journal of Econometrics, Elsevier, vol. 210(2), pages 405-433.
Cited by:
- Matias D. Cattaneo & Rocio Titiunik, 2021.
"Regression Discontinuity Designs,"
Papers
2108.09400, arXiv.org, revised Feb 2022.
- Matias D. Cattaneo & Rocio Titiunik & Gonzalo Vazquez-Bare, 2019. "The Regression Discontinuity Design," Papers 1906.04242, arXiv.org, revised Jun 2020.
- Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
- Chiang, Harold D. & Hsu, Yu-Chin & Sasaki, Yuya, 2019. "Robust uniform inference for quantile treatment effects in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 211(2), pages 589-618.
- Caner, Mehmet, 2023.
"Generalized linear models with structured sparsity estimators,"
Journal of Econometrics, Elsevier, vol. 236(2).
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- Mehmet Caner & Kfir Eliaz, 2021. "Shoiuld Humans Lie to Machines: The Incentive Compatibility of Lasso and General Weighted Lasso," Papers 2101.01144, arXiv.org, revised Sep 2021.
- Harold D. Chiang & Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Linear programming approach to nonparametric inference under shape restrictions: with an application to regression kink designs," Papers 2102.06586, arXiv.org.
- Haitian Xie, 2022. "Nonlinear and Nonseparable Structural Functions in Fuzzy Regression Discontinuity Designs," Papers 2204.08168, arXiv.org, revised Jul 2022.
- Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
- Matias D. Cattaneo & Rocio Titiunik, 2021.
"Regression Discontinuity Designs,"
Papers
2108.09400, arXiv.org, revised Feb 2022.
- Kato, Kengo & Sasaki, Yuya, 2019.
"Uniform confidence bands for nonparametric errors-in-variables regression,"
Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
Cited by:
- Hao Dong & Taisuke Otsu & Luke Taylor, 2021.
"Bandwidth Selection for Nonparametric Regression with Errors-in-Variables,"
Departmental Working Papers
2104, Southern Methodist University, Department of Economics.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2023. "Bandwidth selection for nonparametric regression with errors-in-variables," Econometric Reviews, Taylor & Francis Journals, vol. 42(4), pages 393-419, April.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2022. "Bandwidth selection for nonparametric regression with errors-in-variables," STICERD - Econometrics Paper Series 620, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- 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.
- Hao Dong & Yuya Sasaki, 2022. "Estimation of average derivatives of latent regressors: with an application to inference on buffer-stock saving," Departmental Working Papers 2204, Southern Methodist University, Department of Economics.
- Jun Ma & Vadim Marmer & Zhengfei Yu, 2021.
"Inference on Individual Treatment Effects in Nonseparable Triangular Models,"
Papers
2107.05559, arXiv.org, revised Feb 2023.
- Ma, Jun & Marmer, Vadim & Yu, Zhengfei, 2023. "Inference on individual treatment effects in nonseparable triangular models," Journal of Econometrics, Elsevier, vol. 235(2), pages 2096-2124.
- Hao Dong & Daniel L. Millimet, 2020.
"Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions,"
JRFM, MDPI, vol. 13(11), pages 1-24, November.
- 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.
- Dong, Hao & Millimet, Daniel L., 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," IZA Discussion Papers 13893, Institute of Labor Economics (IZA).
- Katharina Proksch & Nicolai Bissantz & Hajo Holzmann, 2022. "Simultaneous inference for Berkson errors-in-variables regression under fixed design," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 773-800, August.
- Dong, Hao & Taylor, Luke, 2022.
"Nonparametric Significance Testing In Measurement Error Models,"
Econometric Theory, Cambridge University Press, vol. 38(3), pages 454-496, June.
- Hao Dong & Luke Taylor, 2020. "Nonparametric Significance Testing in Measurement Error Models," Departmental Working Papers 2003, Southern Methodist University, Department of Economics.
- Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
- Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
- Ma, Jun & Marmer, Vadim & Shneyerov, Artyom, 2019.
"Inference for first-price auctions with Guerre, Perrigne, and Vuong’s estimator,"
Journal of Econometrics, Elsevier, vol. 211(2), pages 507-538.
- Ma, Jun & Marmer, Vadim & Shneyerov, Artyom, 2016. "Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's estimator," Microeconomics.ca working papers vadim_marmer-2016-4, Vancouver School of Economics, revised 19 Jan 2019.
- Jun Ma & Vadim Marmer & Artyom Shneyerov, 2019. "Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's Estimator," Papers 1903.06401, arXiv.org.
- Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," LSE Research Online Documents on Economics 112676, London School of Economics and Political Science, LSE Library.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2021.
"Bandwidth Selection for Nonparametric Regression with Errors-in-Variables,"
Departmental Working Papers
2104, Southern Methodist University, Department of Economics.
- Chiang, Harold D. & Hsu, Yu-Chin & Sasaki, Yuya, 2019.
"Robust uniform inference for quantile treatment effects in regression discontinuity designs,"
Journal of Econometrics, Elsevier, vol. 211(2), pages 589-618.
Cited by:
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021.
"Testing identifying assumptions in fuzzy regression discontinuity designs,"
CeMMAP working papers
CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifie & Yuanyuan Wan, 2018. "Testing Identifying Assumptions In Fuzzy Regression Discontinuity Designs," Working Papers tecipa-623, University of Toronto, Department of Economics.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2019. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP10/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2018. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP50/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Matias D. Cattaneo & Rocio Titiunik, 2021.
"Regression Discontinuity Designs,"
Papers
2108.09400, arXiv.org, revised Feb 2022.
- Matias D. Cattaneo & Rocio Titiunik & Gonzalo Vazquez-Bare, 2019. "The Regression Discontinuity Design," Papers 1906.04242, arXiv.org, revised Jun 2020.
- Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
- He, Yang & Bartalotti, Otávio, 2020.
"Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals,"
ISU General Staff Papers
202005010700001071, Iowa State University, Department of Economics.
- He, Yang & Bartalotti, Otávio, 2019. "Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals," ISU General Staff Papers 201903010800001071, Iowa State University, Department of Economics.
- Yang He & Otávio Bartalotti, 2020. "Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals [Using Maimonides’ rule to estimate the effect of class size on scholastic achievemen," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 211-231.
- He, Yang & Bartalotti, Otávio, 2019. "Wild Bootstrap for Fuzzy Regression Discontinuity Designs: Obtaining Robust Bias-Corrected Confidence Intervals," IZA Discussion Papers 12801, Institute of Labor Economics (IZA).
- Villamizar-Villegas, Mauricio & Pinzón-Puerto, Freddy A. & Ruiz-Sánchez, María Alejandra, 2020.
"A Comprehensive History of Regression Discontinuity Designs: An Empirical Survey of the last 60 Years,"
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- Mauricio Villamizar-Villegas & Freddy A. Pinzón-Puerto & María Alejandra Ruiz-Sánchez, 2020. "A Comprehensive History of Regression Discontinuity Designs: An Empirical Survey of the last 60 Years," Borradores de Economia 1112, Banco de la Republica de Colombia.
- Jun Ma & Zhengfei Yu, 2020. "Empirical Likelihood Covariate Adjustment for Regression Discontinuity Designs," Papers 2008.09263, arXiv.org, revised May 2022.
- 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).
- Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021.
"Testing identifying assumptions in fuzzy regression discontinuity designs,"
CeMMAP working papers
CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Kato, Kengo & Sasaki, Yuya, 2018.
"Uniform confidence bands in deconvolution with unknown error distribution,"
Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
Cited by:
- Babii, Andrii, 2020.
"Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models,"
Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
- Andrii Babii, 2016. "Honest Confidence Sets in Nonparametric IV Regression and Other Ill-Posed Models," Papers 1611.03015, arXiv.org, revised Dec 2020.
- Babii, Andrii, 2017. "Honest confidence sets in nonparametric IV regression and other ill-posed models," TSE Working Papers 17-803, Toulouse School of Economics (TSE).
- Hao Dong & Taisuke Otsu & Luke Taylor, 2021.
"Bandwidth Selection for Nonparametric Regression with Errors-in-Variables,"
Departmental Working Papers
2104, Southern Methodist University, Department of Economics.
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- Hao Dong & Taisuke Otsu & Luke Taylor, 2022. "Bandwidth selection for nonparametric regression with errors-in-variables," STICERD - Econometrics Paper Series 620, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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"Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving,"
Papers
2209.05914, arXiv.org.
- Hao Dong & Yuya Sasaki, 2022. "Estimation of average derivatives of latent regressors: with an application to inference on buffer-stock saving," Departmental Working Papers 2204, Southern Methodist University, Department of Economics.
- Hao Dong & Daniel L. Millimet, 2020.
"Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions,"
JRFM, MDPI, vol. 13(11), pages 1-24, November.
- 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.
- Dong, Hao & Millimet, Daniel L., 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," IZA Discussion Papers 13893, Institute of Labor Economics (IZA).
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2021.
"Average Derivative Estimation Under Measurement Error,"
Econometric Theory, Cambridge University Press, vol. 37(5), pages 1004-1033, October.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Average Derivative Estimation Under Measurement Error," Departmental Working Papers 1901, Southern Methodist University, Department of Economics.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Average derivative estimation under measurement error," STICERD - Econometrics Paper Series 602, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2020. "Average derivative estimation under measurement error," LSE Research Online Documents on Economics 106489, London School of Economics and Political Science, LSE Library.
- Adusumilli, Karun & Kurisu, Daisuke & Otsu, Taisuke & Whang, Yoon-Jae, 2020.
"Inference on distribution functions under measurement error,"
Journal of Econometrics, Elsevier, vol. 215(1), pages 131-164.
- Karun Adusumilli & Taisuke Otsu & Yoon-Jae Whang, 2017. "Inference on distribution functions under measurement error," STICERD - Econometrics Paper Series 594, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Karun Adusumilli & Taisuke Otsu & Yoon-Jae Whang, "undated". "Inference On Distribution Functions Under Measurement Error," Working Paper Series no108, Institute of Economic Research, Seoul National University.
- Katharina Proksch & Nicolai Bissantz & Hajo Holzmann, 2022. "Simultaneous inference for Berkson errors-in-variables regression under fixed design," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 773-800, August.
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"Nonparametric Significance Testing In Measurement Error Models,"
Econometric Theory, Cambridge University Press, vol. 38(3), pages 454-496, June.
- Hao Dong & Luke Taylor, 2020. "Nonparametric Significance Testing in Measurement Error Models," Departmental Working Papers 2003, Southern Methodist University, Department of Economics.
- Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
- Kengo Kato & Yuya Sasaki & Takuya Ura, 2018. "Inference based on Kotlarski's Identity," Papers 1808.09375, arXiv.org, revised Sep 2019.
- Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
- Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
- Ma, Jun & Marmer, Vadim & Shneyerov, Artyom, 2019.
"Inference for first-price auctions with Guerre, Perrigne, and Vuong’s estimator,"
Journal of Econometrics, Elsevier, vol. 211(2), pages 507-538.
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- Jun Ma & Vadim Marmer & Artyom Shneyerov, 2019. "Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's Estimator," Papers 1903.06401, arXiv.org.
- Adusumilli, Karun & Kurisu, Daisies & Otsu, Taisuke & Whang, Yoon-Jae, 2020. "Inference on distribution functions under measurement error," LSE Research Online Documents on Economics 102692, London School of Economics and Political Science, LSE Library.
- Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," LSE Research Online Documents on Economics 112676, London School of Economics and Political Science, LSE Library.
- Babii, Andrii, 2020.
"Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models,"
Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
- Botosaru, Irene & Sasaki, Yuya, 2018.
"Nonparametric heteroskedasticity in persistent panel processes: An application to earnings dynamics,"
Journal of Econometrics, Elsevier, vol. 203(2), pages 283-296.
Cited by:
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"Recovering Latent Variables by Matching,"
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wp2019_1914, CEMFI.
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- Manuel Arellano & Stephane Bonhomme, 2019. "Recovering Latent Variables by Matching," Papers 1912.13081, arXiv.org.
- Manuel Arellano & Stéphane Bonhomme, 2023. "Recovering Latent Variables by Matching," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(541), pages 693-706, January.
- Botosaru, Irene, 2023. "Time-varying unobserved heterogeneity in earnings shocks," Journal of Econometrics, Elsevier, vol. 235(2), pages 1378-1393.
- Irene Botosaru, 2017. "Identifying Distributions in a Panel Model with Heteroskedasticity: An Application to Earnings Volatility," Discussion Papers dp17-11, Department of Economics, Simon Fraser University.
- Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
- 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).
- Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2016. "Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework," Working Papers wp2016_1606, CEMFI.
- Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2015. "Earnings and consumption dynamics: a nonlinear panel data framework," IFS Working Papers W15/24, Institute for Fiscal Studies.
- Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2015. "Earnings and consumption dynamics: a nonlinear panel data framework," CeMMAP working papers CWP53/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2015. "Earnings and consumption dynamics: a nonlinear panel data framework," CeMMAP working papers 53/15, Institute for Fiscal Studies.
- Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2015. "Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework," Working Papers wp2015_1506, CEMFI.
- Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2017. "Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework," Econometrica, Econometric Society, vol. 85, pages 693-734, May.
- Ryo Okui & Takahide Yanagi, 2014.
"Panel Data Analysis with Heterogeneous Dynamics,"
KIER Working Papers
906, Kyoto University, Institute of Economic Research.
- Ryo Okui & Takahide Yanagi, 2018. "Panel Data Analysis with Heterogeneous Dynamics," Papers 1803.09452, arXiv.org, revised Jan 2019.
- Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
- Dan Ben-Moshe, 2023. "Identifying an Earnings Process With Dependent Contemporaneous Income Shocks," Papers 2303.08460, arXiv.org, revised May 2023.
- Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
- Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
- Ben-Moshe, Dan, 2023. "Identifying an earnings process with dependent contemporaneous income shocks," Economics Letters, Elsevier, vol. 230(C).
- Silvia Sarpietro & Yuya Sasaki & Yulong Wang, 2022. "Non-Existent Moments of Earnings Growth," Papers 2203.08014, arXiv.org, revised Feb 2024.
- Manuel Arellano & Stéphane Bonhomme, 2019.
"Recovering Latent Variables by Matching,"
Working Papers
wp2019_1914, CEMFI.
- Hu, Yingyao & Sasaki, Yuya, 2018.
"Closed-Form Identification Of Dynamic Discrete Choice Models With Proxies For Unobserved State Variables,"
Econometric Theory, Cambridge University Press, vol. 34(1), pages 166-185, February.
Cited by:
- Schneider, Ulrich, 2019. "Identification of Time Preferences in Dynamic Discrete Choice Models: Exploiting Choice Restrictions," MPRA Paper 102137, University Library of Munich, Germany, revised 29 Jul 2020.
- Sasaki, Yuya & Takahashi, Yuya & Xin, Yi & Hu, Yingyao, 2023. "Dynamic discrete choice models with incomplete data: Sharp identification," Journal of Econometrics, Elsevier, vol. 236(1).
- Kato, Ryutah & Sasaki, Yuya, 2017.
"On Using Linear Quantile Regressions For Causal Inference,"
Econometric Theory, Cambridge University Press, vol. 33(3), pages 664-690, June.
Cited by:
- Tymon S{l}oczy'nski, 2018. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," Papers 1810.01576, arXiv.org, revised May 2020.
- Arie Beresteanu, 2020.
"Quantile Regression with Interval Data,"
Working Paper
6899, Department of Economics, University of Pittsburgh.
- Arie Beresteanu, 2016. "Quantile Regression with Interval Data," Working Paper 5991, Department of Economics, University of Pittsburgh.
- Tymon Sloczynski, 2018.
"A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands,"
Working Papers
125, Brandeis University, Department of Economics and International Business School.
- Sloczynski, Tymon, 2018. "A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands," IZA Discussion Papers 11866, Institute of Labor Economics (IZA).
- Chiang, Harold D. & Sasaki, Yuya, 2019. "Causal inference by quantile regression kink designs," Journal of Econometrics, Elsevier, vol. 210(2), pages 405-433.
- Sasaki, Yuya & Xin, Yi, 2017.
"Unequal spacing in dynamic panel data: Identification and estimation,"
Journal of Econometrics, Elsevier, vol. 196(2), pages 320-330.
Cited by:
- Montes-Rojas Gabriel & Sosa-Escudero Walter & Zincenko Federico, 2020. "Level-Based Estimation of Dynamic Panel Models," Journal of Econometric Methods, De Gruyter, vol. 9(1), pages 1-23, January.
- Lynda Khalaf & Maral Kichian & Charles Saunders & Marcel Voia, 2021.
"Dynamic panels with MIDAS covariates: Nonlinearity, estimation and fit,"
Post-Print
hal-03528880, HAL.
- Khalaf, Lynda & Kichian, Maral & Saunders, Charles J. & Voia, Marcel, 2021. "Dynamic panels with MIDAS covariates: Nonlinearity, estimation and fit," Journal of Econometrics, Elsevier, vol. 220(2), pages 589-605.
- Steele, Fiona & Grundy, Emily, 2021. "Random effects dynamic panel models for unequally-spaced multivariate categorical repeated measures: an application to child-parent exchanges of support," LSE Research Online Documents on Economics 106255, London School of Economics and Political Science, LSE Library.
- Chen, Maolong & Myers, Robert J. & Hu, Chaoran, 2020. "Estimating dynamic binary choice models using irregularly spaced panel data," Economics Letters, Elsevier, vol. 192(C).
- Chen, Weihao & Cizek, Pavel, 2023. "Bias-Corrected Instrumental Variable Estimation in Linear Dynamic Panel Data Models," Other publications TiSEM 9bf2c16c-522f-4223-8037-c, Tilburg University, School of Economics and Management.
- Zhang, Xiaoge & Chen, Maolong, 2023. "Indirect inference approach to estimating dynamic panel data models with irregular spacing," Economics Letters, Elsevier, vol. 226(C).
- Chen, Weihao & Cizek, Pavel, 2023. "Bias-Corrected Instrumental Variable Estimation in Linear Dynamic Panel Data Models," Discussion Paper 2023-028, Tilburg University, Center for Economic Research.
- Fiona Steele & Emily Grundy, 2021. "Random effects dynamic panel models for unequally spaced multivariate categorical repeated measures: an application to child–parent exchanges of support," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 3-23, January.
- Hu, Yingyao & Sasaki, Yuya, 2017.
"Identification Of Paired Nonseparable Measurement Error Models,"
Econometric Theory, Cambridge University Press, vol. 33(4), pages 955-979, August.
Cited by:
- Emmanuel Guerre & Yao Luo, 2019. "Nonparametric Identification of First-Price Auction with Unobserved Competition: A Density Discontinuity Framework," Papers 1908.05476, arXiv.org, revised Jan 2022.
- Yao Luo & Ruli Xiao, 2022.
"Identification of Auction Models Using Order Statistics,"
Papers
2205.12917, arXiv.org, revised Apr 2023.
- Yao Luo & Ruli Xiao, 2019. "Identification of Auction Models Using Order Statistics," Working Papers tecipa-630, University of Toronto, Department of Economics.
- Cheng Chou & Ruoyao Shi, 2021. "What time use surveys can (and cannot) tell us about labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 917-937, November.
- 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.
- 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.
- Grundl, Serafin & Zhu, Yu, 2024. "Two results on auctions with endogenous entry," Economics Letters, Elsevier, vol. 234(C).
- Serafin J. Grundl & Yu Zhu, 2015.
"Identification and Estimation of Risk Aversion in First Price Auctions With Unobserved Auction Heterogeneity,"
Finance and Economics Discussion Series
2015-89, Board of Governors of the Federal Reserve System (U.S.).
- Serafin Grundl & Yu Zhu, 2016. "Identification and Estimation of Risk Aversion in First-Price Auctions with Unobserved Auction Heterogeneity," Staff Working Papers 16-23, Bank of Canada.
- Grundl, Serafin & Zhu, Yu, 2019. "Identification and estimation of risk aversion in first-price auctions with unobserved auction heterogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 363-378.
- Dongwoo Kim & Daniel Wilhelm, 2017.
"Powerful t-Tests in the presence of nonclassical measurement error,"
CeMMAP working papers
57/17, Institute for Fiscal Studies.
- Dongwoo Kim & Daniel Wilhelm, 2023. "Powerful t-tests in the presence of nonclassical measurement error," IFS Working Papers WCWP22/23, Institute for Fiscal Studies.
- Dongwoo Kim & Daniel Wilhelm, 2023. "Powerful t-tests in the presence of nonclassical measurement error," CeMMAP working papers 22/23, Institute for Fiscal Studies.
- Dongwoo Kim & Daniel Wilhelm, 2021. "Powerful t-tests in the presence of nonclassical measurement error," CeMMAP working papers CWP18/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- 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.
- Mavroeidis, Sophocles & Sasaki, Yuya & Welch, Ivo, 2015.
"Estimation of heterogeneous autoregressive parameters with short panel data,"
Journal of Econometrics, Elsevier, vol. 188(1), pages 219-235.
Cited by:
- Mario Crucini & Nam Vu, 2021.
"Did the American Recovery and Reinvestment Act Help Counties Most Affected by the Great Recession?,"
Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 42, pages 264-282, October.
- Mario Crucini & Nam Vu, 2020. "Code and data files for "Did the American Recovery and Reinvestment Act Help Counties Most Affected by the Great Recession?"," Computer Codes 19-343, Review of Economic Dynamics.
- Mario Crucini & Nam Vu, 2020. "Online Appendix to "Did the American Recovery and Reinvestment Act Help Counties Most Affected by the Great Recession?"," Online Appendices 19-343, Review of Economic Dynamics.
- Mario J. Crucini & Nam T. Vu, 2017. "Did the American Recovery and Reinvestment Act Help Counties Most Affected by the Great Recession?," NBER Working Papers 24093, National Bureau of Economic Research, Inc.
- Mario J Crucini & Nam T Vu, 2019. "Did the American recovery and reinvestment act help counties most affected by the great recession?," CAMA Working Papers 2019-57, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Ryo Okui & Takahide Yanagi, 2018.
"Kernel Estimation for Panel Data with Heterogeneous Dynamics,"
Papers
1802.08825, arXiv.org, revised May 2019.
- Ryo Okui & Takahide Yanagi, 2020. "Kernel estimation for panel data with heterogeneous dynamics [Econometric tools for analyzing market outcomes]," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 156-175.
- M. Hashem Pesaran & Liying Yang, 2023.
"Heterogeneous Autoregressions in Short T Panel Data Models,"
CESifo Working Paper Series
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- Pesaran, M. H. & Yang, L., 2023. "Heterogeneous Autoregressions in Short T Panel Data Models," Cambridge Working Papers in Economics 2342, Faculty of Economics, University of Cambridge.
- M. Hashem Pesaran & Liying Yang, 2023. "Heterogeneous Autoregressions in Short T Panel Data Models," Papers 2306.05299, arXiv.org, revised Apr 2024.
- Ryo Okui & Takahide Yanagi, 2014.
"Panel Data Analysis with Heterogeneous Dynamics,"
KIER Working Papers
906, Kyoto University, Institute of Economic Research.
- Ryo Okui & Takahide Yanagi, 2018. "Panel Data Analysis with Heterogeneous Dynamics," Papers 1803.09452, arXiv.org, revised Jan 2019.
- Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
- Durand, Robert B. & Greene, William H. & Harris, Mark N. & Khoo, Joye, 2022. "Heterogeneity in speed of adjustment using finite mixture models," Economic Modelling, Elsevier, vol. 107(C).
- Zhang, Yue-Jun & Liu, Zhao & Qin, Chang-Xiong & Tan, Tai-De, 2017. "The direct and indirect CO2 rebound effect for private cars in China," Energy Policy, Elsevier, vol. 100(C), pages 149-161.
- Mario Crucini & Nam Vu, 2021.
"Did the American Recovery and Reinvestment Act Help Counties Most Affected by the Great Recession?,"
Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 42, pages 264-282, October.
- Sasaki, Yuya, 2015.
"What Do Quantile Regressions Identify For General Structural Functions?,"
Econometric Theory, Cambridge University Press, vol. 31(5), pages 1102-1116, October.
Cited by:
- 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.
- 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.
- Victor Chernozhukov & Iv'an Fern'andez-Val & Whitney Newey, 2017. "Nonseparable Multinomial Choice Models in Cross-Section and Panel Data," Papers 1706.08418, arXiv.org, revised May 2018.
- 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.
- Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022.
"Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects,"
Papers
2208.03632, arXiv.org, revised Apr 2023.
- 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.
- Ying-Ying Lee, 2015. "Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification," Econometrics, MDPI, vol. 4(1), pages 1-14, December.
- Creemers, Sarah & Peeters, Ludo & Quiroz Castillo, Juan Luis & Vancauteren, Mark & Voordeckers, Wim, 2023. "Family firms and the labor productivity controversy: A distributional analysis of varying labor productivity gaps," Journal of Family Business Strategy, Elsevier, vol. 14(2).
- Chiang, Harold D. & Sasaki, Yuya, 2019. "Causal inference by quantile regression kink designs," Journal of Econometrics, Elsevier, vol. 210(2), pages 405-433.
- 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.
- Victor Chernozhukov & Ivan Fernandez-Val & Ye Luo, 2015. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Papers 1512.05635, arXiv.org, revised May 2018.
- Victor Chernozhukov & Ivan Fernandez-Val & Ye Luo, 2015. "The sorted effects method: discovering heterogeneous effects beyond their averages," CeMMAP working papers 74/15, Institute for Fiscal Studies.
- 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.
- Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
- Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017.
"Non-separable Models with High-dimensional Data,"
Economics and Statistics Working Papers
15-2017, Singapore Management University, School of Economics.
- Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
- Chalak, Karim, 2019. "A note on the robustness of quantile treatment effect estimands," Economics Letters, Elsevier, vol. 185(C).
- David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.
- 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.
- Sasaki, Yuya, 2015.
"Heterogeneity and selection in dynamic panel data,"
Journal of Econometrics, Elsevier, vol. 188(1), pages 236-249.
Cited by:
- Sergi Jiménez-Martín & José M. Labeaga & Majid al Sadoon, 2020.
"Consistent estimation of panel data sample selection models,"
Working Papers
2020-06, FEDEA.
- Baltagi, Badi H. & Jimenez-Martin, Sergi & Labeaga, José M. & al Sadoon, Majid, 2023. "Consistent Estimation of Panel Data Sample Selection Models," IZA Discussion Papers 16594, Institute of Labor Economics (IZA).
- Xavier D'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013.
"Nonlinear Difference-in-Differences in Repeated Cross Sections with Continuous Treatments,"
Boston College Working Papers in Economics
839, Boston College Department of Economics.
- Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers 40/13, Institute for Fiscal Studies.
- Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers CWP40/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Sukjin Han, 2018.
"Identification in Nonparametric Models for Dynamic Treatment Effects,"
Papers
1805.09397, arXiv.org, revised Jan 2019.
- Han, Sukjin, 2021. "Identification in nonparametric models for dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 132-147.
- 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.
- Kenichi Nagasawa, 2018. "Treatment Effect Estimation with Noisy Conditioning Variables," Papers 1811.00667, arXiv.org, revised Sep 2022.
- 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.
- 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.
- Majid M. Al-Sadoon & Sergi Jiménez-Martín & José M Labeaga, 2019. "Simple Methods for Consistent Estimation of Dynamic Panel Data Sample Selection Models," Working Papers 1069, Barcelona School of Economics.
- 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.
- 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.
- Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
- Oliver Cassagneau-Francis & Robert Gary-Bobo & Julie Pernaudet & Jean-Marc Robin, 2022.
"A Nonparametric Finite Mixture Approach to Difference-in-Difference Estimation, with an Application to On-the-job Training and Wages,"
SciencePo Working papers Main
hal-03869547, HAL.
- Oliver Cassagneau-Francis & Robert Gary-Bobo & Julie Pernaudet & Jean-Marc Robin, 2022. "A Nonparametric Finite Mixture Approach to Difference-in-Difference Estimation, with an Application to On-the-job Training and Wages," Working Papers hal-03869547, HAL.
- Oliver Cassagneau-Francis & Robert Gary-Bobo & Julie Pernaudet & Jean-Marc Robin, 2022. "A Nonparametric Finite Mixture Approach to Difference-in-Difference Estimation, with an Application to On-the-job Training and Wages," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03869547, HAL.
- Chirok Han & Goeun Lee, 2017. "Efficient Estimation of Linear Panel Data Models with Sample Selection and Fixed Effects," Discussion Paper Series 1707, Institute of Economic Research, Korea University.
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