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Practical procedures to deal with common support problems in matching estimation

Citations

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Cited by:

  1. Lechner, Michael, 2018. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," IZA Discussion Papers 12040, Institute of Labor Economics (IZA).
  2. Andrea Albanese & Lorenzo Cappellari & Marco Leonardi, 2021. "The effects of youth labour market reforms: evidence from Italian apprenticeships," Oxford Economic Papers, Oxford University Press, vol. 73(1), pages 98-121.
  3. Pohlan, Laura, 2019. "Unemployment and social exclusion," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 273-299.
  4. Michael C. Knaus & Steffen Otterbach, 2019. "Work Hour Mismatch And Job Mobility: Adjustment Channels And Resolution Rates," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 227-242, January.
  5. Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
  6. Weltin, Meike & Hüttel, Silke, 2019. "Farm eco-efficiency: Can sustainable intensification make the difference?," FORLand Working Papers 10 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
  7. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany's programmes for long term unemployed," Labour Economics, Elsevier, vol. 65(C).
  8. Michael C Knaus & Michael Lechner & Anthony Strittmatter, 2021. "Machine learning estimation of heterogeneous causal effects: Empirical Monte Carlo evidence," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 134-161.
  9. Tübbicke Stefan, 2022. "Entropy Balancing for Continuous Treatments," Journal of Econometric Methods, De Gruyter, vol. 11(1), pages 71-89, January.
  10. Marco Caliendo & Stefan Tübbicke, 2020. "New evidence on long-term effects of start-up subsidies: matching estimates and their robustness," Empirical Economics, Springer, vol. 59(4), pages 1605-1631, October.
  11. Massimiliano Mazzanti & Antonio Musolesi, 2020. "Modeling Green Knowledge Production and Environmental Policies with Semiparametric Panel Data Regression models," SEEDS Working Papers 1420, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Sep 2020.
  12. Adeola Oyenubi & Martin Wittenberg, 2021. "Does the choice of balance-measure matter under genetic matching?," Empirical Economics, Springer, vol. 61(1), pages 489-502, July.
  13. Arun Advani & Toru Kitagawa & Tymon Słoczyński, 2019. "Mostly harmless simulations? Using Monte Carlo studies for estimator selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 893-910, September.
  14. Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2022. "Heterogeneous Employment Effects of Job Search Programs: A Machine Learning Approach," Journal of Human Resources, University of Wisconsin Press, vol. 57(2), pages 597-636.
  15. Meike Weltin & Silke Hüttel, 2023. "Sustainable Intensification Farming as an Enabler for Farm Eco-Efficiency?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(1), pages 315-342, January.
  16. Susan Athey & Guido W. Imbens & Jonas Metzger & Evan M. Munro, 2019. "Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations," NBER Working Papers 26566, National Bureau of Economic Research, Inc.
  17. Lombardi, Stefano & van den Berg, Gerard J. & Vikström, Johan, 2020. "Empirical Monte Carlo evidence on estimation of Timing-of-Events models," Working Paper Series 2020:26, IFAU - Institute for Evaluation of Labour Market and Education Policy, revised 05 Jan 2021.
  18. Strittmatter, Anthony & Wunsch, Conny, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," Working papers 2021/05, Faculty of Business and Economics - University of Basel.
  19. Martin Huber & Michael Lechner & Andreas Steinmayr, 2015. "Radius matching on the propensity score with bias adjustment: tuning parameters and finite sample behaviour," Empirical Economics, Springer, vol. 49(1), pages 1-31, August.
  20. Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2017. "The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 91-102.
  21. Felipe Barrera-Osorio & Paul Gertler & Nozomi Nakajima & Harry Patrinos, 2020. "Promoting Parental Involvement in Schools: Evidence From Two Randomized Experiments," NBER Working Papers 28040, National Bureau of Economic Research, Inc.
  22. Michael C. Knaus, 2021. "A double machine learning approach to estimate the effects of musical practice on student’s skills," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 282-300, January.
  23. Michael C Knaus, 2022. "Double machine learning-based programme evaluation under unconfoundedness [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 602-627.
  24. Doerr, Annabelle, 2022. "Vocational Training for Female Job Returners - Effects on Employment, Earnings and Job Quality," Working papers 2022/02, Faculty of Business and Economics - University of Basel.
  25. Andrea Albanese & Bart Cockx & Yannick Thuy, 2020. "Working time reductions at the end of the career: Do they prolong the time spent in employment?," Empirical Economics, Springer, vol. 59(1), pages 99-141, July.
  26. Iga Magda & Katarzyna Sałach, 2021. "Gender pay gaps in domestic and foreign-owned firms," Empirical Economics, Springer, vol. 61(4), pages 2237-2263, October.
  27. Albanese, Andrea & Gallo, Giovanni, 2020. "Buy flexible, pay more: The role of temporary contracts on wage inequality," Labour Economics, Elsevier, vol. 64(C).
  28. Doerr, Annabelle & Strittmatter, Anthony, 2014. "Assignment Mechanisms, Selection Criteria, and the Effectiveness of Training Programs," Economics Working Paper Series 1421, University of St. Gallen, School of Economics and Political Science, revised May 2017.
  29. Pohlmeier, Winfried & Seiberlich, Ruben & Uysal, Selver Derya, 2016. "A simple and successful shrinkage method for weighting estimators of treatment effects," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 512-525.
  30. Doerr Annabelle & Strittmatter Anthony, 2021. "Identifying Causal Channels of Policy Reforms with Multiple Treatments and Different Types of Selection," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 67-88, January.
  31. Advani, Arun & Sloczynski, Tymon, 2013. "Mostly Harmless Simulations? On the Internal Validity of Empirical Monte Carlo Studies," IZA Discussion Papers 7874, Institute of Labor Economics (IZA).
  32. Annabelle Doerr & Bernd Fitzenberger & Thomas Kruppe & Marie Paul & Anthony Strittmatter, 2017. "Employment and Earnings Effects of Awarding Training Vouchers in Germany," ILR Review, Cornell University, ILR School, vol. 70(3), pages 767-812, May.
  33. Daniel Boller & Michael Lechner & Gabriel Okasa, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," Papers 2104.04601, arXiv.org.
  34. Chen, Jiayuan & Gong, Di & Muckley, Cal, 2020. "Stock market illiquidity, bargaining power and the cost of borrowing," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 181-206.
  35. Doerr, Annabelle, 2017. "Back to work: The Long-term Effects of Vocational Training for Female Job Returners," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168213, Verein für Socialpolitik / German Economic Association.
  36. Anthony Strittmatter, 2018. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," Papers 1812.06533, arXiv.org, revised Dec 2021.
  37. 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.
  38. Heiler, Phillip & Kazak, Ekaterina, 2021. "Valid inference for treatment effect parameters under irregular identification and many extreme propensity scores," Journal of Econometrics, Elsevier, vol. 222(2), pages 1083-1108.
  39. Franziska Zimmert, 2023. "Early child care and the employment potential of mothers: evidence from semi-parametric difference-in-differences estimation," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-22, December.
  40. Doerr, Annabelle, 2022. "Vocational training for female job returners - Effects on employment, earnings and job quality," Labour Economics, Elsevier, vol. 75(C).
  41. Sakaue, Katsuki & Wokadala, James, 2022. "Effects of including refugees in local government schools on pupils’ learning achievement: Evidence from West Nile, Uganda," International Journal of Educational Development, Elsevier, vol. 90(C).
  42. Draheim, Matthias & Schanbacher, Peter & Seiberlich, Ruben, 2021. "On the effectiveness of case management for people with disabilities," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-15.
  43. Hong Kai, 2017. "School Bond Referendum, Capital Expenditure, and Student Achievement," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 17(4), pages 1-26, October.
  44. Massimiliano Mazzanti & Antonio Musolesi, 2020. "A Semiparametric Analysis of Green Inventions and Environmental Policies," SEEDS Working Papers 0920, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jun 2020.
  45. Seonho Shin, 2022. "Evaluating the Effect of the Matching Grant Program for Refugees: An Observational Study Using Matching, Weighting, and the Mantel-Haenszel Test," Journal of Labor Research, Springer, vol. 43(1), pages 103-133, March.
  46. Gabriel Okasa & Kenneth A. Younge, 2022. "Sample Fit Reliability," Papers 2209.06631, arXiv.org.
  47. Hugo Bodory & Martin Huber & Michael Lechner, 2022. "The finite sample performance of instrumental variable-based estimators of the Local Average Treatment Effect when controlling for covariates," Papers 2212.07379, arXiv.org.
  48. Strittmatter, Anthony & Lechner, Michael, 2020. "Sorting in the used-car market after the Volkswagen emission scandal," Journal of Environmental Economics and Management, Elsevier, vol. 101(C).
  49. Michael Lechner & Jana Mareckova, 2022. "Modified Causal Forest," Papers 2209.03744, arXiv.org.
  50. Caliendo, Marco & Tübbicke, Stefan, 2019. "Do Start-Up Subsidies for the Unemployed Affect Participants' Well-Being? A Rigorous Look at (Un-)Intended Consequences of Labor Market Policies," IZA Discussion Papers 12755, Institute of Labor Economics (IZA).
  51. Chen, Bowen & Gramig, Ben & Yun, Seong Do, 2020. "A Causal Analysis of the Effect of Conservation Tillage on U.S. Corn and Soybean Yield and Profitability," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304296, Agricultural and Applied Economics Association.
  52. Mary Ying-Fang Wang & Paul Tuss & Lihong Qi, 2019. "Augmented Weighted Estimators Dealing with Practical Positivity Violation to Causal inferences in a Random Coefficient Model," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 447-467, June.
  53. Strittmatter, Anthony, 2023. "What is the value added by using causal machine learning methods in a welfare experiment evaluation?," Labour Economics, Elsevier, vol. 84(C).
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