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Bootstrap inference of matching estimators for average treatment effects

Citations

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Cited by:

  1. Zhexiao Lin & Peng Ding & Fang Han, 2023. "Estimation Based on Nearest Neighbor Matching: From Density Ratio to Average Treatment Effect," Econometrica, Econometric Society, vol. 91(6), pages 2187-2217, November.
  2. Mahmud, Minhaj & Sawada, Yasuyuki & Seki, Mai & Takakura, Kazuma, 2025. "Self-learning at the right level, COVID-19, school closure, and non-cognitive abilities," Economics of Education Review, Elsevier, vol. 107(C).
  3. Shu Yang & Yunshu Zhang, 2023. "Multiply robust matching estimators of average and quantile treatment effects," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 235-265, March.
  4. García, Gustavo Antonio & Ramírez-Hassan, Andrés & Saravia, Estefanía & Vargas, Raquel & Duque, Juan Fernando & Londoño, Daniel, 2022. "Impacto de las intervenciones físicas en el transporte público en Medellín (Colombia) como herramientas para reducir la exclusión social," IDB Publications (Working Papers) 12014, Inter-American Development Bank.
  5. Matthew Blackwell & Anton Strezhnev, 2022. "Telescope matching for reducing model dependence in the estimation of the effects of time‐varying treatments: An application to negative advertising," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 377-399, January.
  6. D’Arcangelo, Filippo Maria & Pavan, Giulia & Calligaris, Sara, "undated". "The Impact of the European Carbon Market on Firm Productivity: Evidence from Italian Manufacturing Firms," FEEM Working Papers 324170, Fondazione Eni Enrico Mattei (FEEM).
  7. Cristina Bernini & Augusto Cerqua, 2020. "Are eco‐labels good for the local economy?," Papers in Regional Science, Wiley Blackwell, vol. 99(3), pages 645-661, June.
  8. Weiss, Amanda, 2024. "How Much Should We Trust Modern Difference-in-Differences Estimates?," OSF Preprints bqmws, Center for Open Science.
  9. Walsh, Christopher & Jentsch, Carsten, 2025. "Nearest neighbor matching: M-out-of-N bootstrapping without bias correction vs. the naive bootstrap," Econometrics and Statistics, Elsevier, vol. 36(C), pages 81-89.
  10. Taisuke Otsu & Mengshan Xu, 2022. "Isotonic propensity score matching," STICERD - Econometrics Paper Series 623, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  11. Bernini, Cristina & Cerqua, Augusto, 2019. "Do sustainability policies finance local economies?," MPRA Paper 91882, University Library of Munich, Germany.
  12. Huber, Martin & Camponovo, Lorenzo & Bodory, Hugo & Lechner, Michael, 2016. "A wild bootstrap algorithm for propensity score matching estimators," FSES Working Papers 470, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  13. Cerqua, A. & Ferrante, C. & Letta, M., 2021. "Electoral Earthquake: Natural Disasters and the Geography of Discontent," GLO Discussion Paper Series 790, Global Labor Organization (GLO).
  14. Eli Ben‐Michael & Avi Feller & Jesse Rothstein, 2022. "Synthetic controls with staggered adoption," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 351-381, April.
  15. Bodory, Hugo & Camponovo, Lorenzo & Huber, Martin & Lechner, Michael, 2024. "Nonparametric bootstrap for propensity score matching estimators," Statistics & Probability Letters, Elsevier, vol. 208(C).
  16. Shu Yang & Jae Kwang Kim, 2020. "Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 839-861, September.
  17. Wagner, Gary A. & Rork, Jonathan C., 2023. "Does state tax reciprocity affect interstate commuting? Evidence from a natural experiment," Regional Science and Urban Economics, Elsevier, vol. 102(C).
  18. Giovanni Baiocchetti & Cecilia Castaldo & Ilan Noy & Federico Zampollo, 2025. "The Adverse Impacts of Disasters In-Name-Only," CESifo Working Paper Series 11681, CESifo.
  19. Ziming Lin & Fang Han, 2024. "On the consistency of bootstrap for matching estimators," Papers 2410.23525, arXiv.org, revised Nov 2024.
  20. Ferman, Bruno, 2021. "Matching estimators with few treated and many control observations," Journal of Econometrics, Elsevier, vol. 225(2), pages 295-307.
  21. Andr'es Ram'irez-Hassan & Raquel Vargas-Correa & Gustavo Garc'ia & Daniel Londo~no, 2020. "Optimal selection of the number of control units in kNN algorithm to estimate average treatment effects," Papers 2008.06564, arXiv.org.
  22. Hugo Bodory & Lorenzo Camponovo & Martin Huber & Michael Lechner, 2020. "The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 183-200, January.
  23. Kara E Rudolph & Nicholas T Williams & Floriana Milazzo & Atheendar Venkataramani & Rourke O’Brien, 2023. "Has the opening of Amazon fulfillment centers affected demand for disability insurance?," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-13, November.
  24. Filippo Maria D’Arcangelo & Giulia Pavan & Sara Calligaris, 2022. "The Impact of the European Carbon Market on Firm Productivity: Evidence from Italian Manufacturing Firms," Working Papers 2022.24, Fondazione Eni Enrico Mattei.
  25. Cerqua, Augusto & Ferrante, Chiara & Letta, Marco, 2023. "Electoral earthquake: Local shocks and authoritarian voting," European Economic Review, Elsevier, vol. 156(C).
  26. Mengshan Xu & Taisuke Otsu, 2022. "Isotonic propensity score matching," Papers 2207.08868, arXiv.org, revised Jan 2025.
  27. repec:osf:osfxxx:bqmws_v1 is not listed on IDEAS
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