Is neglected heterogeneity really an issue in binary and fractional regression models? A simulation exercise for logit, probit and loglog models

Esmeralda Ramalho () and Joaquim Ramalho ()

CEFAGE-UE Working Papers from University of Evora, CEFAGE-UE (Portugal)

Abstract: In this paper we examine theoretically and by simulation whether or not unobserved heterogeneity independent of the included regressors is really an issue in logit, probit and loglog models with both binary and fractional data. We found that unobserved heterogeneity: (i) produces an attenuation bias in the estimation of regression coefficients; (ii) is innocuous for logit estimation of average sample partial effects, while in the probit and loglog cases there may be important biases in the estimation of those quantities; (iii) has much more destructive effects over the estimation of population partial effects; (iv) only for logit models does not affect substantially the prediction of outcomes; and (v) is innocuous for the size and consistency of Wald tests for the significance of observed regressors but, in small samples, reduces their power substantially.

Keywords: Binary models; fractional models; neglected heterogeneity; partial effects; prediction; wald tests. (search for similar items in EconPapers)
JEL-codes: C12 C13 C15 C25 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2009
New Economics Papers: this item is included in nep-ecm
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Related works:
Journal Article: Is neglected heterogeneity really an issue in binary and fractional regression models? A simulation exercise for logit, probit and loglog models (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:cfe:wpcefa:2009_10

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