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Bias of OLS Estimators due to Exclusion of Relevant Variables and Inclusion of Irrelevant Variables

Deepankar Basu

Oxford Bulletin of Economics and Statistics, 2020, vol. 82, issue 1, 209-234

Abstract: In this paper, I discuss three issues related to bias of OLS estimators in a general multivariate setting. First, I discuss the bias that arises from omitting relevant variables. I offer a geometric interpretation of such bias and derive sufficient conditions in terms of sign restrictions that allows us to determine the direction of bias. Second, I show that inclusion of some omitted variables will not necessarily reduce the magnitude of bias as long as some others remain omitted. Third, I show that inclusion of irrelevant variables in a model with omitted variables can also have an impact on the bias of OLS estimators. I use a running example of a simple wage regression to illustrate my arguments.

Date: 2020
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Citations: View citations in EconPapers (10)

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https://doi.org/10.1111/obes.12322

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Oxford Bulletin of Economics and Statistics is currently edited by Christopher Adam, Anindya Banerjee, Christopher Bowdler, David Hendry, Adriaan Kalwij, John Knight and Jonathan Temple

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