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pro vyhledávání: '"Heiler, Phillip"'
This paper is concerned with identification, estimation, and specification testing in causal evaluation problems when data is selective and/or missing. We leverage recent advances in the literature on graphical methods to provide a unifying framework
Externí odkaz:
http://arxiv.org/abs/2308.04963
Autor:
Heiler, Phillip
We propose a method for estimation and inference for bounds for heterogeneous causal effect parameters in general sample selection models where the treatment can affect whether an outcome is observed and no exclusion restrictions are available. The m
Externí odkaz:
http://arxiv.org/abs/2209.04329
Autor:
Heiler, Phillip, Knaus, Michael C.
Binary treatments are often ex-post aggregates of multiple treatments or can be disaggregated into multiple treatment versions. Thus, effects can be heterogeneous due to either effect or treatment heterogeneity. We propose a decomposition method that
Externí odkaz:
http://arxiv.org/abs/2110.01427
Autor:
Heiler, Phillip
This paper develops an empirical balancing approach for the estimation of treatment effects under two-sided noncompliance using a binary conditionally independent instrumental variable. The method weighs both treatment and outcome information with in
Externí odkaz:
http://arxiv.org/abs/2007.04346
Autor:
Heiler, Phillip, Mareckova, Jana
This paper introduces a flexible regularization approach that reduces point estimation risk of group means stemming from e.g. categorical regressors, (quasi-)experimental data or panel data models. The loss function is penalized by adding weighted sq
Externí odkaz:
http://arxiv.org/abs/1901.01898
Autor:
Heiler, Phillip, Mareckova, Jana
Publikováno v:
In Journal of Econometrics July 2021 223(1):161-189
Autor:
Heiler, Phillip, Kazak, Ekaterina
Publikováno v:
In Journal of Econometrics June 2021 222(2):1083-1108
Autor:
Heiler, Phillip1 (AUTHOR)
Publikováno v:
Journal of Business & Economic Statistics. Oct2022, Vol. 40 Issue 4, p1569-1582. 14p.
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