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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: EERI Research Paper Series ; No. 43/2010

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities ; Econometric Software ; Health: General
• Subject: Generalized ordered probit ; panel data ; autofit ; self-assessed health

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Pfarr, Christian ; Schmid, Andreas ; Schneider, Udo
• Event: Veröffentlichung
• (who): Economics and Econometrics Research Institute (EERI)
• (where): Brussels
• (when): 2010

Further information

• Handle: http://hdl.handle.net/10419/142604
• Last update: 10.03.2025, 11:44 AM CET