IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v26y1998i3p368-400.html
   My bibliography  Save this article

An Analytic and Empirical Examination of Zero-Inflated and Hurdle Poisson Specifications

Author

Listed:
  • CHRISTOPHER J. W. ZORN

    (Emory University)

Abstract

This article examines two alternative specifications for estimating event-count models in which the data-generating process results in a larger number of zero counts than would be expected under standard distributional assumptions. The author compares King's hurdle event count model and Greene's zero-inflated Poisson model, using data on congressional responses to Supreme Court decisions from 1979 to 1988. The author shows that each of these models is a special case of a more general dual regime data-generating process that results in extra-Poisson zero counts. Furthermore, because this data-generating process can produce overdispersion in its own right, these models are also shown to be related to variance function negative binomial specifications. The underlying correspondence between these models leads to similar results in estimating and interpreting them in practice.

Suggested Citation

  • Christopher J. W. Zorn, 1998. "An Analytic and Empirical Examination of Zero-Inflated and Hurdle Poisson Specifications," Sociological Methods & Research, , vol. 26(3), pages 368-400, February.
  • Handle: RePEc:sae:somere:v:26:y:1998:i:3:p:368-400
    DOI: 10.1177/0049124198026003004
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124198026003004
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0049124198026003004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    2. Schmidt, Peter & Witte, Ann Dryden, 1989. "Predicting criminal recidivism using 'split population' survival time models," Journal of Econometrics, Elsevier, vol. 40(1), pages 141-159, January.
    3. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    4. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    5. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    6. Landes, William M & Posner, Richard A, 1975. "The Independent Judiciary in an Interest-Group Perspective," Journal of Law and Economics, University of Chicago Press, vol. 18(3), pages 875-901, December.
    7. Gurmu, Shiferaw, 1991. "Tests for Detecting Overdispersion in the Positive Poisson Regression Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 215-222, April.
    8. Goldfelfd, Stephen M. & Quandt, Richard E., 1975. "Estimation in a disequilibrium model and the value of information," Journal of Econometrics, Elsevier, vol. 3(4), pages 325-348, November.
    9. Cameron, A. Colin & Trivedi, Pravin K., 1990. "Regression-based tests for overdispersion in the Poisson model," Journal of Econometrics, Elsevier, vol. 46(3), pages 347-364, December.
    10. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    11. Spiller, Pablo T & Spitzer, Matthew L, 1992. "Judicial Choice of Legal Doctrines," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 8(1), pages 8-46, March.
    12. John M. Abowd & Henry S. Farber, 1982. "Job Queues and the Union Status of Workers," ILR Review, Cornell University, ILR School, vol. 35(3), pages 354-367, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Greene, William, 2007. "Functional Form and Heterogeneity in Models for Count Data," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(2), pages 113-218, August.
    2. Niklas Elert, 2014. "What determines entry? Evidence from Sweden," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 55-92, August.
    3. Ulf‐ G. Gerdtham, 1997. "Equity in Health Care Utilization: Further Tests Based on Hurdle Models and Swedish Micro Data," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 303-319, May.
    4. Dahen, Hela & Dionne, Georges, 2010. "Scaling models for the severity and frequency of external operational loss data," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1484-1496, July.
    5. Mihaela DAVID, 2014. "Modeling The Frequency Of Claims In Auto Insurance With Application To A French Case," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 13, pages 69-85, June.
    6. Rock, Steve & Sedo, Stanley & Willenborg, Michael, 2000. "Analyst following and count-data econometrics," Journal of Accounting and Economics, Elsevier, vol. 30(3), pages 351-373, December.
    7. V. J. Cano Fernandez & G. Guirao Perez & M. C. Rodriguez Donate & M. E. Romero Rodriguez, 2009. "An analysis of count data models for the study of exclusivity in wine consumption," Applied Economics, Taylor & Francis Journals, vol. 41(12), pages 1563-1574.
    8. William Greene, 2009. "Models for count data with endogenous participation," Empirical Economics, Springer, vol. 36(1), pages 133-173, February.
    9. Kornelius Kraft & Jörg Stank & Ralf Dewenter, 2011. "Co-determination and innovation," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 35(1), pages 145-172.
    10. Banri ITO & Tatsufumi YAMAGATA, 2007. "Who Develops Innovations In Medicine For The Poor? Trends In Patent Applications Related To Medicines For Hiv/Aids, Tuberculosis, Malaria, And Neglected Diseases," The Developing Economies, Institute of Developing Economies, vol. 45(2), pages 141-171, June.
    11. Bilgic, Abdulbaki & Florkowski, Wojciech J., 2003. "Explaning Anglers Behavior Using Count Data Models With Endogenous Switching Regime," 2003 Annual meeting, July 27-30, Montreal, Canada 22087, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. Sirchenko Andrei, 2012. "A model for ordinal responses with an application to policy interest rate," EERC Working Paper Series 12/13e, EERC Research Network, Russia and CIS.
    13. Sisira Sarma & Wayne Simpson, 2006. "A microeconometric analysis of Canadian health care utilization," Health Economics, John Wiley & Sons, Ltd., vol. 15(3), pages 219-239, March.
    14. Margarita E. Romero Rodríguez & Enrique Los Arcos & Victor Cano Fernández & Miguel Sánchez Padrón, 2001. "Modelo para datos de recuentro de corte transversal con exceso de ceros. Aplicación a citas patentes," Documentos de trabajo conjunto ULL-ULPGC 2001-05, Facultad de Ciencias Económicas de la ULPGC.
    15. Martijn Burger & Frank van Oort & Gert-Jan Linders, 2009. "On the Specification of the Gravity Model of Trade: Zeros, Excess Zeros and Zero-inflated Estimation," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(2), pages 167-190.
    16. Greene, William, 2008. "Functional forms for the negative binomial model for count data," Economics Letters, Elsevier, vol. 99(3), pages 585-590, June.
    17. Serge Garcia & Julien Jacob, 2010. "La valeur récréative de la forêt en France : une approche par les coûts de déplacement," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 91(1), pages 43-71.
    18. Meisner, Craig & Wang, Hua & Laplante, Benoit, 2006. "Welfare measurement bias in household and on-site surveying of water-based recreation : an application to Lake Sevan, Armenia," Policy Research Working Paper Series 3932, The World Bank.
    19. Gourieroux, C. & Visser, M., 1997. "A count data model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 79(2), pages 247-268, August.
    20. Dohse, Dirk & Schertler, Andrea, 2003. "Explaining the regional distribution of new economy firms: a count data analysis," Kiel Working Papers 1193, Kiel Institute for the World Economy (IfW Kiel).

    More about this item

    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:sae:somere:v:26:y:1998:i:3:p:368-400. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.