IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v72y1990i1p108-15.html
   My bibliography  Save this article

Analyzing Frequencies of Several Types of Events: A Mixed Multinomial-Poisson Approach

Author

Listed:
  • Terza, Joseph V
  • Wilson, Paul W

Abstract

A flexible, generalized Poisson model is combined with the multinomial distribution to jointly predict households' choices among types of trips and frequency of trips. The model is compared with conventional Poisson models. The problem of a time-variant mean for frequencies is also addressed, as well as the mean-variance property of the conventional Poisson model that is avoided by use of the generalized formulation. The generalized model is found to outperform the conventional models. Copyright 1990 by MIT Press.

Suggested Citation

  • Terza, Joseph V & Wilson, Paul W, 1990. "Analyzing Frequencies of Several Types of Events: A Mixed Multinomial-Poisson Approach," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 108-115, February.
    • Handle: RePEc:tpr:restat:v:72:y:1990:i:1:p:108-15
    as

    Download full text from publisher

    File URL: http://links.jstor.org/sici?sici=0034-6535%28199002%2972%3A1%3C108%3AAFOSTO%3E2.0.CO%3B2-7&origin=repec
    File Function: full text
    Download Restriction: Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. T.R.L. Fry & R.D. Brooks & Br. Comley & J. Zhang, 1993. "Economic Motivations for Limited Dependent and Qualitative Variable Models," The Economic Record, The Economic Society of Australia, vol. 69(2), pages 193-205, June.
    2. Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
    3. Parsons, George R. & Jakus, Paul M. & Tomasi, Ted, 1999. "A Comparison of Welfare Estimates from Four Models for Linking Seasonal Recreational Trips to Multinomial Logit Models of Site Choice," Journal of Environmental Economics and Management, Elsevier, vol. 38(2), pages 143-157, September.
    4. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    5. Andr? Romeu-Santana & ?gel M. Vera-Hern?dez, "undated". "A Semi-Nonparametric Estimator For Counts With An Endogenous Dummy. Variable," UFAE and IAE Working Papers 452.00, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    6. Andrés Romeu & Marcos Vera-Hernández, 2005. "Counts with an endogenous binary regressor: A series expansion approach," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 1-22, March.
    7. A. Colin Cameron & Per Johansson, 2004. "Bivariate Count Data Regression Using Series Expansions: With Applications," Working Papers 9815, University of California, Davis, Department of Economics.
    8. Mark K. Cassell & Michael Schwan & Marc Schneiberg, 2023. "Bank Types, Inclusivity, and Paycheck Protection Program Lending During COVID-19," Economic Development Quarterly, , vol. 37(3), pages 277-294, August.
    9. Efthymios Tsionas & George Halkos, 2000. "Posterior Analysis of Environmental Damage Evaluation in Europe," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(3), pages 371-390.
    10. Terza, Joseph V., 1998. "Estimating count data models with endogenous switching: Sample selection and endogenous treatment effects," Journal of Econometrics, Elsevier, vol. 84(1), pages 129-154, May.
    11. Cuffe, Barry P. & Friedman, Moshe F., 1996. "The joint distribution of the number of occurrences of two interrelated Poisson processes," European Journal of Operational Research, Elsevier, vol. 89(3), pages 660-667, March.
    12. W. Scott Comulada & Robert E. Weiss, 2007. "On Models for Binomial Data with Random Numbers of Trials," Biometrics, The International Biometric Society, vol. 63(2), pages 610-617, June.
    13. Bhat, Chandra R., 2022. "A closed-form multiple discrete-count extreme value (MDCNTEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 65-86.
    14. Sfeir, Georges & Abou-Zeid, Maya & Kaysi, Isam, 2020. "Multivariate count data models for adoption of new transport modes in an organization-based context," Transport Policy, Elsevier, vol. 91(C), pages 59-75.
    15. Miravete, Eugenio, 2009. "Multivariate Sarmanov Count Data Models," CEPR Discussion Papers 7463, C.E.P.R. Discussion Papers.

    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:tpr:restat:v:72:y:1990:i:1:p:108-15. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Kelly McDougall (email available below). General contact details of provider: https://direct.mit.edu/journals .

    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.