IDEAS home Printed from https://ideas.repec.org/p/eei/rpaper/eeri_rp_2010_43.html
   My bibliography  Save this paper

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

Author

Listed:
  • Christian Pfarr
  • Andreas Schmid
  • Udo Schneider

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

  • Christian Pfarr & Andreas Schmid & Udo Schneider, 2010. "Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure," EERI Research Paper Series EERI_RP_2010_43, Economics and Econometrics Research Institute (EERI), Brussels.
  • Handle: RePEc:eei:rpaper:eeri_rp_2010_43
    as

    Download full text from publisher

    File URL: http://www.eeri.eu/documents/wp/EERI_RP_2010_43.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Stefan Boes & Rainer Winkelmann, 2006. "Ordered response models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 167-181, March.
    3. Guillaume R. Frechette, 2001. "Random-effects ordered probit," Stata Technical Bulletin, StataCorp LP, vol. 10(59).
    4. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204, March.
    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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maurice Mutisya & Moses W. Ngware & Caroline W. Kabiru & Ngianga-bakwin Kandala, 2016. "The effect of education on household food security in two informal urban settlements in Kenya: a longitudinal analysis," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 8(4), pages 743-756, August.
    2. Zara Daghbashyan & Björn Hårsman, 2014. "University choice and entrepreneurship," Small Business Economics, Springer, vol. 42(4), pages 729-746, April.
    3. Eiji Yamamura, 2014. "Smokers’ Sexual Behavior and Their Satisfaction with Family Life," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(3), pages 1229-1247, September.
    4. Udo Schneider & Christian Pfarr & Brit Schneider & Volker Ulrich, 2012. "I feel good! Gender differences and reporting heterogeneity in self-assessed health," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(3), pages 251-265, June.
    5. Brown, Heather & van der Pol, Marjon, 2015. "Intergenerational transfer of time and risk preferences," Journal of Economic Psychology, Elsevier, vol. 49(C), pages 187-204.
    6. Laetitia Duval & François-Charles Wolff, 2016. "“I even met happy gypsies”," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 24(4), pages 727-764, October.
    7. Pfarr, Christian & Schmid, Andreas & Schneider, Udo, 2011. "Reporting Heterogeneity in Self-Assessed Health among Elderly Europeans: The Impact of Mental and Physical Health Status," MPRA Paper 29900, University Library of Munich, Germany.
    8. Nicolas Lampach & Kene Boun My & Sandrine Spaeter, 2016. "Risk, Ambiguity and Efficient Liability Rules: An experiment," Working Papers of BETA 2016-30, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    9. Samanthi Durage & Lina Kattan & S. Wirasinghe & Janaka Ruwanpura, 2014. "Evacuation behaviour of households and drivers during a tornado," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 71(3), pages 1495-1517, April.
    10. Chaudhuri, Kausik & Reilly, Kevin T. & Spencer, David A., 2015. "Job satisfaction, age and tenure: A generalized dynamic random effects model," Economics Letters, Elsevier, vol. 130(C), pages 13-16.
    11. Jürgen Bierbaumer-Polly & Werner Hölzl, 2016. "Business Cycle Dynamics and Firm Heterogeneity. Evidence for Austria Using Survey Data," WIFO Working Papers 504, WIFO.
    12. Yang, Qingqing & Rosenman, Robert, 2015. "Adjusting Self-Assessed Health for Potential Bias Using a Random-Effects Generalized Ordered Probit model," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205217, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    13. repec:bla:ausecr:v:49:y:2016:i:4:p:453-470 is not listed on IDEAS

    More about this item

    Keywords

    Generalized ordered probit; panel data; autofit; self-assessed health.;

    JEL classification:

    • 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
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • I10 - Health, Education, and Welfare - - Health - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eei:rpaper:eeri_rp_2010_43. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Julia van Hove). General contact details of provider: http://edirc.repec.org/data/eeriibe.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.