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 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.
Volume (Year): 54 (2011)
Issue (Month): 1 ()
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"Ordered Response Models,"
SOI - Working Papers
0507, Socioeconomic Institute - University of Zurich.
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- Christian Pfarr & Andreas Schmid & Udo Schneider, 2010. "REGOPROB2: Stata module to estimate random effects generalized ordered probit models (update)," Statistical Software Components S457153, Boston College Department of Economics.
- Guillaume R. Frechette, 2001. "Random-effects ordered probit," Stata Technical Bulletin, StataCorp LP, vol. 10(59).
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