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  1. Addressing Endogeneity Using a Two-stage Copula Generated Regressor Approach
    Autor*in: Yang, Fan; Qian, Yi; Xie, Hui
    Erschienen: 2022
    Verlag:  National Bureau of Economic Research, Cambridge, Mass

    A prominent challenge when drawing causal inference using observational data is the ubiquitous presence of endogenous regressors. The classical econometric method to handle regressor endogeneity requires instrumental variables that must satisfy the... mehr

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    Sächsische Landesbibliothek - Staats- und Universitätsbibliothek Dresden
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    Universitätsbibliothek Freiburg
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    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky
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    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    A prominent challenge when drawing causal inference using observational data is the ubiquitous presence of endogenous regressors. The classical econometric method to handle regressor endogeneity requires instrumental variables that must satisfy the stringent condition of exclusion restriction, making it infeasible to use in many settings. We propose new instrument-free methods using copulas to address the endogeneity problem. The existing copula correction method focuses only on the endogenous regressors and may yield biased estimates when exogenous and endogenous regressors are correlated. Furthermore, (nearly) normally distributed endogenous regressors cause model non-identification or finite-sample poor performance. Our proposed two-stage copula endogeneity correction (2sCOPE) method simultaneously overcomes the two key limitations and yields consistent causal-effect estimates with correlated endogenous and exogenous regressors as well as normally distributed endogenous regressors. 2sCOPE employs generated regressors derived from existing regressors to control for endogeneity, and is straightforward to use and broadly applicable. Moreover, we prove that exploiting correlated exogenous regressors can address the problem of insufficient regressor non-normality, relax identification requirements and improve estimation precision (by as much as ∼50% in empirical evaluation). Overall, 2sCOPE can greatly increase the ease of and broaden the applicability of instrument-free methods for dealing with regressor endogeneity. We demonstrate the performance of 2sCOPE via simulation studies and an empirical application

     
    Export in Literaturverwaltung   RIS-Format
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    Schriftenreihe: NBER working paper series ; no. w29708
    Schlagworte: Kausalanalyse; Multivariate Verteilung; Schätztheorie
    Umfang: 1 Online-Ressource, illustrations (black and white)
    Bemerkung(en):

    Hardcopy version available to institutional subscribers
  2. A Practical Guide to Endogeneity Correction Using Copulas
    Autor*in: Qian, Yi; Koschmann, Anthony; Xie, Hui
    Erschienen: March 2024
    Verlag:  National Bureau of Economic Research, Cambridge, Mass

    Causal inference is of central interests in many empirical applications yet often challenging because of the presence of endogenous regressors. The classical approach to the problem requires using instrumental variables that must satisfy the... mehr

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

    Standort:
    Sächsische Landesbibliothek - Staats- und Universitätsbibliothek Dresden
    Fernleihe:
    keine Fernleihe

    Standort:
    Universitätsbibliothek Freiburg
    Fernleihe:
    keine Fernleihe

    Standort:
    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
    Fernleihe:
    keine Fernleihe

    Standort:
    Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky
    Fernleihe:
    keine Fernleihe

    Standort:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Fernleihe:
    keine Fernleihe

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Fernleihe:
    keine Fernleihe

     

    Causal inference is of central interests in many empirical applications yet often challenging because of the presence of endogenous regressors. The classical approach to the problem requires using instrumental variables that must satisfy the stringent condition of exclusion restriction. At the forefront of recent research, instrument-free copula methods have been increasingly used to handle endogenous regressors. This article aims to provide a practical guide for how to handle endogeneity using copulas. The authors give an overview of copula endogeneity correction and its usage in marketing research, discuss recent advances that broaden the understanding, applicability, and robustness of copula correction, and examine implementation challenges of copula correction such as construction of copula control functions and handling of higher-order terms of endogenous regressors. To facilitate the appropriate usage of copula correction, the authors detail a process of checking data requirements and identification assumptions to determine when and how to use copula correction methods, and illustrate its usage using empirical examples

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: NBER working paper series ; no. w32231
    Schlagworte: Multivariate Verteilung; Ökonometrie; Econometrics; General; Econometric Modeling
    Umfang: 1 Online-Ressource, illustrations (black and white)
    Bemerkung(en):

    Hardcopy version available to institutional subscribers