Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure

Christian Pfarr, Andreas Schmid () and Udo Schneider ()

MPRA Paper from University Library of Munich, Germany

Abstract: 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.

Keywords: generalized ordered probit; panel data; autofit, self-assessed health (search for similar items in EconPapers)
JEL-codes: C23 C25 C87 I10 (search for similar items in EconPapers)
Date: 2010-06-10
New Economics Papers: this item is included in nep-dcm and nep-ecm
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Related works:
Journal Article: Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure (2011)
Working Paper: Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure (2010)
Working Paper: Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure (2010)
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