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Testing for selection bias
Joo, Joonhwi; LaLonde, Robert John - 2014
framework is if the usual assumptions hold for matching or IV estimators, the control function identifies the presence and … appropriate to use more efficient estimators of treatment effects, such as those based on least squares or matching. Another …
Persistent link: https://www.econbiz.de/10010407986
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How much should we trust staggered difference-in-differences estimates?
Baker, Andrew; Larcker, David F.; Wang, Charles C. Y. - 2021
Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the presence of treatment...
Persistent link: https://www.econbiz.de/10012504212
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Testing conditional independence in macroeconomic policy evaluation for time series data
Fang, Ying; Lin, Ming; Tang, Shengfang; Cai, Zongwu - 2021
Persistent link: https://www.econbiz.de/10012663950
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Marginal Treatment Effects in Difference-in-Differences
Picchetti, Pedro; Campos de Xavier Pinto, Cristine - 2022
Difference-in-Differences (DiD) is a popular method used to evaluate the effect of a treatment. In its most simple version a control group remains untreated at two periods, whereas the treatment group becomes fully treated at the second period. However, it is not uncommon in applications of the...
Persistent link: https://www.econbiz.de/10014084358
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Estimation and inference for distribution functions and quantile functions in treatment effect models
Donald, Stephen G.; Hsu, Yu-Chin - 2012
Persistent link: https://www.econbiz.de/10009682440
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Consistent tests for conditional treatment effects
Hsu, Yu-Chin - 2013
Persistent link: https://www.econbiz.de/10009778555
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Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed
Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2019
Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation … of average treatment effects on the treated using a radius matching framework. Considering two popular methods, the …
Persistent link: https://www.econbiz.de/10012060603
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Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed
Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2019
Persistent link: https://www.econbiz.de/10012098947
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Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed
Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2020
Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation … of average treatment effects on the treated using a radius matching framework. Considering two popular methods, the …Propensity Score Matching-Schätzer sind ein zentrales Tool, um Wirkungen aktiver Arbeitsmarktpolitik mit …
Persistent link: https://www.econbiz.de/10012165548
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Model averaging in semiparametric estimation of treatment effects
Kitagawa, Toru; Muris, Chris - 2015
model averaging as a statistical decision problem in a limit experiment, and derive an averaging scheme that is Bayes …
Persistent link: https://www.econbiz.de/10011309717