Logo
Munich Personal RePEc Archive

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

Pfarr, Christian and Schmid, Andreas and Schneider, Udo (2010): Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure.

[thumbnail of MPRA_paper_24181.pdf]
Preview
PDF
MPRA_paper_24181.pdf

Download (10MB) | Preview

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.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.