Arbeitspapier

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.

Sprache
Englisch

Erschienen in
Series: EERI Research Paper Series ; No. 43/2010

Klassifikation
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
Thema
Generalized ordered probit
panel data
autofit
self-assessed health

Ereignis
Geistige Schöpfung
(wer)
Pfarr, Christian
Schmid, Andreas
Schneider, Udo
Ereignis
Veröffentlichung
(wer)
Economics and Econometrics Research Institute (EERI)
(wo)
Brussels
(wann)
2010

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Pfarr, Christian
  • Schmid, Andreas
  • Schneider, Udo
  • Economics and Econometrics Research Institute (EERI)

Entstanden

  • 2010

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