Discrepancy in regression estimates between log-normal and gamma: some case studies

Rabindra Nath Das and Jeong-Soo Park

Journal of Applied Statistics, 2012, vol. 39, issue 1, 97-111

Abstract: In regression models with multiplicative error, estimation is often based on either the log-normal or the gamma model. It is well known that the gamma model with constant coefficient of variation and the log-normal model with constant variance give almost the same analysis. This article focuses on the discrepancies of the regression estimates between the two models based on real examples. It identifies that even though the variance or the coefficient of variation remains constant, but regression estimates may be different between the two models. It also identifies that for the same positive data set, the variance is constant under the log-normal model but non-constant under the gamma model. For this data set, the regression estimates are completely different between the two models. In the process, it explains the causes of discrepancies between the two models.

Date: 2012
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DOI: 10.1080/02664763.2011.578618

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