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.
Year of publication: |
2010-10-23
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Authors: | Pfarr, Christian ; Schmid, Andreas ; Schneider, Udo |
Institutions: | Economics and Econometrics Research Institute (EERI) |
Subject: | Generalized ordered probit | panel data | autofit | self-assessed health |
Saved in:
freely available
Extent: | application/pdf |
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Series: | |
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Number EERI_RP_2010_43 |
Classification: | C23 - Models with Panel Data ; C25 - Discrete Regression and Qualitative Choice Models ; C87 - Econometric Software ; I10 - Health. General |
Source: |
Persistent link: https://www.econbiz.de/10008684449