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.

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Abstract
Estimation procedures for ordered categories usually assume that the estimated coefficients of independent variables do not vary between the categories (parallellines 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 parallellines 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.
Item Type:  MPRA Paper 

Original Title:  Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure 
Language:  English 
Keywords:  generalized ordered probit; panel data; autofit, selfassessed health 
Subjects:  C  Mathematical and Quantitative Methods > C8  Data Collection and Data Estimation Methodology; Computer Programs > C87  Econometric Software C  Mathematical and Quantitative Methods > C2  Single Equation Models; Single Variables > C23  Models with Panel Data; Longitudinal Data; Spatial Time Series C  Mathematical and Quantitative Methods > C2  Single Equation Models; Single Variables > C25  Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions I  Health, Education, and Welfare > I1  Health > I10  General 
Item ID:  23203 
Depositing User:  Christian Pfarr 
Date Deposited:  11. Jun 2010 00:55 
Last Modified:  19. Mar 2014 14:57 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/23203 