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
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Englisch
- Erschienen in
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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
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Geistige Schöpfung
- (wer)
-
Pfarr, Christian
Schmid, Andreas
Schneider, Udo
- Ereignis
-
Veröffentlichung
- (wer)
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Economics and Econometrics Research Institute (EERI)
- (wo)
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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