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Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure

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  • Pfarr, Christian
  • Schmid, Andreas
  • Schneider, Udo

Abstract

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.

Suggested Citation

  • Pfarr, Christian & Schmid, Andreas & Schneider, Udo, 2010. "Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure," MPRA Paper 23203, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:23203
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    References listed on IDEAS

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    1. Stefan Boes & Rainer Winkelmann, 2006. "Ordered Response Models," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 12, pages 167-181, Springer.
    2. Stephen Pudney & Michael Shields, 2000. "Gender, race, pay and promotion in the British nursing profession: estimation of a generalized ordered probit model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(4), pages 367-399.
    3. Guillaume R. Frechette, 2001. "Random-effects ordered probit," Stata Technical Bulletin, StataCorp LLC, vol. 10(59).
    4. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204, November.
    5. William H. Greene & Mark N. Harris & Bruce Hollingworth & Pushkar Maitra, 2008. "A Bivariate Latent Class Correlated Generalized Ordered Probit Model with an Application to Modeling Observed Obesity Levels," Working Papers 08-18, New York University, Leonard N. Stern School of Business, Department of Economics.
    6. 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.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I10 - Health, Education, and Welfare - - Health - - - General

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