| 来源类型 | Working Paper
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| 规范类型 | 报告
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| DOI | 10.3386/w29708
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| 来源ID | Working Paper 29708
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| Addressing Endogeneity Using a Two-stage Copula Generated Regressor Approach |
| Fan Yang; Yi Qian; Hui Xie
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| 发表日期 | 2022-01-31
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| 出版年 | 2022
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| 语种 | 英语
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| 摘要 | 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. Existing copula correction methods require non-normal endogenous regressors: normally or nearly normally distributed endogenous regressors cause model non-identification or significant finite-sample bias. Furthermore, existing copula control function methods presume the independence of exogenous regressors and the copula control function. Our proposed two-stage copula endogeneity correction (2sCOPE) method simultaneously relaxes the two key identification requirements, and we prove that 2sCOPE yields consistent causal-effect estimates with correlated endogenous and exogenous regressors as well as normally distributed endogenous regressors. Besides relaxing identification requirements, 2sCOPE has superior finite-sample performance and addresses the significant finite sample bias problem due to insufficient regressor non-normality. 2sCOPE employs generated regressors derived from existing regressors to control for endogeneity, and is straightforward to use and broadly applicable. Overall, 2sCOPE can greatly increase the ease and broaden the applicability of using instrument-free methods to handle regressor endogeneity. We further demonstrate the performance of 2sCOPE via simulation studies and an empirical application. |
| 主题 | Econometrics
; Estimation Methods
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| URL | https://www.nber.org/papers/w29708
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| 来源智库 | National Bureau of Economic Research (United States)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/587382
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推荐引用方式
GB/T 7714 |
Fan Yang,Yi Qian,Hui Xie. Addressing Endogeneity Using a Two-stage Copula Generated Regressor Approach. 2022.
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文件名：
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w29708.pdf
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格式：
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Adobe PDF
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