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Title: When Do Covariates Matter? And Which Ones, and How Much?
Resulting in 1 citation.
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Gelbach, Jonah B. |
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When Do Covariates Matter? And Which Ones, and How Much? Journal of Labor Economics 34,2 (April 2016): 509-543. Also: http://www.journals.uchicago.edu/doi/abs/10.1086/683668 Cohort(s): NLSY97 Publisher: University of Chicago Press Keyword(s): Modeling, Instrumental Variables; Racial Differences; Variables, Independent - Covariate; Wage Gap Authors often add covariates to a base model sequentially either to test a particular coefficient's "robustness" or to account for the "effects" on this coefficient of adding covariates. This is problematic, due to sequence sensitivity when added covariates are intercorrelated. Using the omitted variables bias formula, I construct a conditional decomposition that accounts for various covariates' role in moving base regressors' coefficients. I also provide a consistent covariance formula. I illustrate this conditional decomposition with NLSY data in an application that exhibits sequence sensitivity. Related extensions include instrumental variables, the fact that my decomposition nests the Oaxaca-Blinder decomposition, and a Hausman test result. |
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Bibliography Citation
Gelbach, Jonah B. "When Do Covariates Matter? And Which Ones, and How Much?" Journal of Labor Economics 34,2 (April 2016): 509-543.
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