Estimating Ordered Categorical Variables Using Panel Data: A Generalized Ordered Probit Model with an Autofit Procedure
By Christian Pfarr, A. Schmid, U. Schneider. 2010
54 citations recorded by the source corpus.
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.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/9a2efea70ecd71e7b1f2d14e1bd54380acf6cf88
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In Economics and Econometrics
Citations in the corpus
- The effect of education on household food security in two informal urban settlements in Kenya: a longitudinal analysis (2016, methodology): “We analysed data in STATA 13 using the REGOPROB2 command (Pfarr et al. 2010).”