Eliminating the omitted variable bias by a regime-switching approach

Andrea Beccarini

Journal of Applied Statistics, 2010, vol. 37, issue 1, 57-75

Abstract: This work shows a procedure that aims to eliminate or reduce the bias caused by omitted variables by means of the so-called regime-switching regressions. There is a bias estimation whenever the statistical (linear) model is under-specified, that is, when there are some omitted variables and they are correlated with the regressors. This work shows how an appropriate specification of a regime-switching model (independent or Markov-switching) can eliminate or reduce this correlation, hence the estimation bias. A demonstration is given, together with some Monte Carlo simulations. An empirical verification, based on Fisher's equation, is also provided.

Keywords: omitted variable bias; regime-switching model; EM algorithm; Monte Carlo simulations; Fisher's equation (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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DOI: 10.1080/02664760902914474

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