Rcope: Tools to Cope with Endogeneity Problems
Researchers across disciplines often face biased regression
model estimates due to endogenous regressors correlated with the error
term. Traditional solutions require instrumental variables (IVs), which
are often difficult to find and validate. This package provides
flexible, alternative IV-free methods using copulas, as described in
the practical guide to endogeneity correction using copulas (Yi Qian,
Tony Koschmann, and Hui Xie 2025) <doi:10.1177/00222429251410844>. The
current version implements the two-stage copula endogeneity correction
(2sCOPE) method to fit models with continuous endogenous regressors and
both continuous and discrete exogenous regressors, as described in Fan
Yang, Yi Qian, and Hui Xie (2024)
<doi:10.1177/00222437241296453>. Using this method, users can address
regressor endogeneity problems in nonexperimental data without
requiring IVs.
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