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

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

EERI Research Paper Series from Economics and Econometrics Research Institute (EERI), Brussels

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: 2010-10-23
New Economics Papers: this item is included in nep-dcm
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Citations: View citations in EconPapers (9)

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http://www.eeri.eu/documents/wp/EERI_RP_2010_43.pdf (application/pdf)

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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Persistent link: https://EconPapers.repec.org/RePEc:eei:rpaper:eeri_rp_2010_43

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