Estimating Ordered Categorical Variables Using Panel Data : A Generalized Ordered Probit Model with an Autofit Procedure

Estimation procedures for ordered categories usually assume that the estimated coefficients of independent variables do not vary between the categories (parallel-lines assumption). This view neglects possible heterogeneous effects of some explaining factors. This paper describes the use of an autofit option for identifying variables that meet the parallel-lines assumption when estimating a random effects generalized ordered probit model. We combine the test procedure developed by Richard Williams (gologit2) with the random effects estimation command regoprob by Stefan Boes

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Year of publication:	2011
Authors:	Pfarr, Christian ; Schmid, Andreas ; Schneider, Udo
Publisher:	[S.l.] : SSRN
Subject:	Probit-Modell \| Probit model \| Schätztheorie \| Estimation theory \| Panel \| Panel study

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