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Double machine learning for sample selection models

  1. TitleDouble machine learning for sample selection models
    Author infoMichela Bia ... [et al.]
    Author Bia Michela (34%)
    Co-authors Huber Martin (33%)
    Lafférs Lukáš (33%) UMBFP10 - Katedra matematiky
    Source document Journal of business & economic statistics. Vol. 42, no. 3 (2024), pp. 958-969. - Philadelphia : Taylor & Francis, 2024
    Keywords strojové učenie - machine learning   odhadovanie  
    Form. Descr.články - journal articles
    LanguageEnglish
    CountryUnited States of America
    AnnotationThis article considers the evaluation of discretely distributed treatments when outcomes are only observed for a subpopulation due to sample selection or outcome attrition. For identification, we combine a selection-on-observables assumption for treatment assignment with either selection-on-observables or instrumental variable assumptions concerning the outcome attrition/sample selection process. We also consider dynamic confounding, meaning that covariates that jointly affect sample selection and the outcome may (at least partly) be influenced by the treatment. To control in a data-driven way for a potentially high dimensional set of pre- and/or post-treatment covariates, we adapt the double machine learning framework for treatment evaluation to sample selection problems. We make use of (a) Neyman-orthogonal, doubly robust, and efficient score functions, which imply the robustness of treatment effect estimation to moderate regularization biases in the machine learning-based estimation of the outcome, treatment, or sample selection models and (b) sample splitting (or cross-fitting) to prevent overfitting bias. We demonstrate that the proposed estimators are asymptotically normal and root-n consistent and investigate their finite sample properties in a simulation study. We also apply our proposed methodology to the Job Corps data. The estimator is available in the causalweight package for the statistical software R.
    URLLink na zdrojový dokument
    Public work category ADC
    No. of Archival Copy54594
    Catal.org.BB301 - Univerzitná knižnica Univerzity Mateja Bela v Banskej Bystrici
    Databasexpca - PUBLIKAČNÁ ČINNOSŤ
    ReferencesPERIODIKÁ-Súborný záznam periodika
Number of the records: 1  

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