Bridging logistic and OLS regression

Constantine Kapsalis

MPRA Paper from University Library of Munich, Germany

Abstract: There is broad consensus that logistic regression is superior to ordinary least squares (OLS) regression at predicting the probability of an event. OLS is still widely used in binary choice models because its coefficients are easier to interpret, while the resulting estimates tend to be close to the logit estimates anyway. Although some statistical software provide an easy way of calculating marginal effects (equivalent in interpretation to OLS coefficients) this is not always the case. This paper shows a simple way of calculating marginal effects from logistic coefficients.

Keywords: regression; analysis (search for similar items in EconPapers)
JEL-codes: C35 (search for similar items in EconPapers)
Date: 2010-04, Revised 2010-12
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Related works:
Working Paper: Bridging logistic and OLS regression (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:27706

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