Sequential testing of duration data: the case of the Pennsylvania ‘reemployment bonus’ experiment

By Yannis Bilias. 2000

14 citations recorded by the source corpus.

Subfields: Statistics and Probability

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In Statistics and Probability

1. Victor Chernozhukov
2. Stefan Wager
3. Whitney K. Newey
4. Christian Hansen
5. Susan Athey
6. D. Chetverikov
7. James M. Robins
8. Guido W. Imbens

Citations in the corpus

• Double/Debiased/Neyman Machine Learning of Treatment Effects (2017, methodology): “This experiment has been previously studied by Bilias (2000) and Bilias and Koenker (2002).”
• Double/Debiased Machine Learning for Treatment and Causal Parameters (2016, methodology): “employment duration using the partially linear model and interactive model in panel A and B, respectively. To reduce the disproportionate 7There are six treatment groups in the experiments. Following [3]. we merge the groups 4 and 6. DOUBLE MACHINE LEARNING 27 impact of extreme propensity score weig”
• Double/debiased machine learning for treatment and structural parameters (2017, unknown): “Following Bilias (2000). we merge the groups 4 and 6. obtained by estimating each nuisance function with a random forest which averages over 1000 trees.”