{
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  "Title": "Tools to Cope with Endogeneity Problems",
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  "Description": "Researchers across disciplines often face biased\nregression model estimates due to endogenous regressors\ncorrelated with the error term. Traditional solutions require\ninstrumental variables (IVs), which are often difficult to find\nand validate. This package provides flexible, alternative\nIV-free methods using copulas, as described in the practical\nguide to endogeneity correction using copulas (Yi Qian, Tony\nKoschmann, and Hui Xie 2025) <doi:10.1177/00222429251410844>.\nThe current version implements the two-stage copula endogeneity\ncorrection (2sCOPE) method to fit models with continuous\nendogenous regressors and both continuous and discrete\nexogenous regressors, as described in Fan Yang, Yi Qian, and\nHui Xie (2024) <doi:10.1177/00222437241296453>. Using this\nmethod, users can address regressor endogeneity problems in\nnonexperimental data without requiring IVs.",
  "License": "MIT + file LICENSE",
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  "Author": "Anthony Obrzut [aut, cre], Yi Qian [aut], Hui Xie [aut]",
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