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  1. Two-stage least squares random forests with a replication of angrist and evans (1998)
    Autor*in: Biewen, Martin; Kugler, Philipp
    Erschienen: August 2020
    Verlag:  Verein für Socialpolitik, [Köln]

    We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to... mehr

    Zugang:
    Resolving-System (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DSM 13
    Fernleihe:
    keine Fernleihe

     

    We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental variables in Angrist and Evans (Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size, American Economic Review, Vol. 88, 1998). The two-stage least squares random forest allows one to investigate local heterogenous effects that cannot be investigated using ordinary 2SLS.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/224538
    Schriftenreihe: Jahrestagung 2020 / Verein für Socialpolitik ; 33
    Discussion paper series / IZA ; no. 13613
    Schlagworte: machine learning; generalized random forests; fertility,instrumental variable estimation
    Umfang: 1 Online-Ressource (circa 25 Seiten), Illustrationen
  2. Two-stage least squares random forests with an application to Angrist and Evans (1998)
    Autor*in: Biewen, Martin; Kugler, Philipp
    Erschienen: August 2020
    Verlag:  IZA - Institute of Labor Economics, Bonn, Germany

    We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to... mehr

    Zugang:
    Verlag (kostenfrei)
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 4
    Fernleihe:
    keine Fernleihe

     

    We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental variables in Angrist and Evans (Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size, American Economic Review, Vol. 88, 1998). The two-stage least squares random forest allows one to investigate local heterogenous effects that cannot be investigated using ordinary 2SLS.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/224055
    Schriftenreihe: Discussion paper series / IZA ; no. 13613
    Umfang: 1 Online-Ressource (circa 24 Seiten), Illustrationen