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Journal article
Yet another look at the omitted variable bias
ECONOMETRIC REVIEWS, v 42(1)
02 Jan 2023
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
When conducting regression analysis, econometricians often face the situation where some relevant regressors are unavailable in the data set at hand. This article shows how to construct a new class of nonparametric proxies by combining the original data set with one containing the missing regressors. Imputation of the missing values is done using a nonstandard kernel adapted to mixed data. We derive the asymptotic distribution of the resulting semiparametric two-sample estimator of the parameters of interest and show, using Monte Carlo simulations, that it dominates the solutions involving instrumental variables and other parametric alternatives. An application to the PSID and NLS data illustrates the importance of our estimation approach for empirical research.
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Details
- Title
- Yet another look at the omitted variable bias
- Publication Details
- ECONOMETRIC REVIEWS, v 42(1)
- Publisher
- TAYLOR & FRANCIS INC; PHILADELPHIA
- Grant note
- Financial support through grants from Japan Society for the Promotion of Science (M. Hirukawa, Project No. 19K01595) and the Russian Science Foundation (A. Prokhorov, Project No. 16-18-10432) for various and non-overlapping parts of this research is gratefully acknowledged.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Drexel University
- Web of Science ID
- WOS:000931764800001
- Scopus ID
- 2-s2.0-85147746631
- Other Identifier
- 991021861282004721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Economics
- Mathematics, Interdisciplinary Applications
- Social Sciences, Mathematical Methods
- Statistics & Probability