Sample selection models for discrete and other non-Gaussian response variables

Adelchi Azzalini, Hyoung-Moon Kim () and Hea-Jung Kim
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Adelchi Azzalini: University of Padua
Hyoung-Moon Kim: Konkuk University
Hea-Jung Kim: Dongguk University

Statistical Methods & Applications, 2019, vol. 28, issue 1, No 2, 27-56

Abstract: Abstract Consider observation of a phenomenon of interest subject to selective sampling due to a censoring mechanism regulated by some other variable. In this context, an extensive literature exists linked to the so-called Heckman selection model. A great deal of this work has been developed under Gaussian assumption of the underlying probability distributions; considerably less work has dealt with other distributions. We examine a general construction which encompasses a variety of distributions and allows various options of the selection mechanism, focusing especially on the case of discrete response. Inferential methods based on the pertaining likelihood function are developed.

Keywords: Sample selection; Selection bias; Heckman model; Binary variables; Skew-normal distribution; Count data; Symmetry-modulated distributions; Skew-symmetric distributions (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10260-018-0427-1

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