IDEAS home Printed from https://ideas.repec.org/p/ags/waeaar/245039.html
   My bibliography  Save this paper

Theoretical and Empirical Advantages of Truncated Count Data Estimators for Analysis of Deer Hunting in California

Author

Listed:
  • Creel, Michael D.
  • Loomis, John B.

Abstract

No abstract is available for this item.

Suggested Citation

  • Creel, Michael D. & Loomis, John B., 1989. "Theoretical and Empirical Advantages of Truncated Count Data Estimators for Analysis of Deer Hunting in California," WAEA/ WFEA Conference Archive (1929-1995) 245039, Western Agricultural Economics Association.
  • Handle: RePEc:ags:waeaar:245039
    DOI: 10.22004/ag.econ.245039
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/245039/files/waea-invitedpapers-071.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.245039?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. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    2. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    3. Lee, Lung-Fei, 1986. "Specification Test for Poisson Regression Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 27(3), pages 689-706, October.
    4. 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.
    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. Damien Euzénat & Meradj Mortezapouraghdam, 2016. "Les changements d’organisation du travail dans les entreprises : quelles conséquences sur les accidents du travail des salariés ?," Économie et Statistique, Programme National Persée, vol. 486(1), pages 129-147.
    2. Dionne, Georges & Artis, Manuel & Guillen, Montserrat, 1996. "Count data models for a credit scoring system," Journal of Empirical Finance, Elsevier, vol. 3(3), pages 303-325, September.
    3. de Rassenfosse, Gaétan & Schoen, Anja & Wastyn, Annelies, 2014. "Selection bias in innovation studies: A simple test," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 287-299.
    4. Gary King, 1989. "A Seemingly Unrelated Poisson Regression Model," Sociological Methods & Research, , vol. 17(3), pages 235-255, February.
    5. Gurmu, Shiferaw & Rilstone, Paul & Stern, Steven, 1998. "Semiparametric estimation of count regression models1," Journal of Econometrics, Elsevier, vol. 88(1), pages 123-150, November.
    6. Papke, Leslie E., 1991. "Interstate business tax differentials and new firm location : Evidence from panel data," Journal of Public Economics, Elsevier, vol. 45(1), pages 47-68, June.
    7. Brambilla, Irene, 2009. "Multinationals, technology, and the introduction of varieties of goods," Journal of International Economics, Elsevier, vol. 79(1), pages 89-101, September.
    8. Dionne, Georges & Gagne, Robert & Gagnon, Francois & Vanasse, Charles, 1997. "Debt, moral hazard and airline safety An empirical evidence," Journal of Econometrics, Elsevier, vol. 79(2), pages 379-402, August.
    9. Gabriele Fiorentini & Enrique Sentana, 2021. "Specification tests for non‐Gaussian maximum likelihood estimators," Quantitative Economics, Econometric Society, vol. 12(3), pages 683-742, July.
    10. Gourieroux, C. & Jasiak, J., 2004. "Heterogeneous INAR(1) model with application to car insurance," Insurance: Mathematics and Economics, Elsevier, vol. 34(2), pages 177-192, April.
    11. Miguel A. Delgado & Thomas J. Kniesner, 1997. "Count Data Models With Variance Of Unknown Form: An Application To A Hedonic Model Of Worker Absenteeism," The Review of Economics and Statistics, MIT Press, vol. 79(1), pages 41-49, February.
    12. Bartolucci, Francesco & Belotti, Federico & Peracchi, Franco, 2015. "Testing for time-invariant unobserved heterogeneity in generalized linear models for panel data," Journal of Econometrics, Elsevier, vol. 184(1), pages 111-123.
    13. Michael R. Baye & J. Rupert J. Gatti & Paul Kattuman & John Morgan, 2009. "Clicks, Discontinuities, and Firm Demand Online," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 18(4), pages 935-975, December.
    14. Bruno Crépon & Emmanuel Duguet, 1994. "Innovation : mesures, rendements et concurrence," Économie et Statistique, Programme National Persée, vol. 275(1), pages 121-134.
    15. Dionne, Georges, 2000. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud," Working Papers 00-4, HEC Montreal, Canada Research Chair in Risk Management.
    16. Anders Skrondal & Sophia Rabe-Hesketh, 2022. "The Role of Conditional Likelihoods in Latent Variable Modeling," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 799-834, September.
    17. Wang, Jian & Hicks, Diana, 2015. "Scientific teams: Self-assembly, fluidness, and interdependence," Journal of Informetrics, Elsevier, vol. 9(1), pages 197-207.
    18. Koen Jochmans & Vincenzo Verardi, 2022. "Instrumental‐variable estimation of exponential‐regression models with two‐way fixed effects with an application to gravity equations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1121-1137, September.
    19. Czarnitzki, Dirk & Hünermund, Paul & Moshgbar, Nima, 2020. "Public Procurement of Innovation: Evidence from a German Legislative Reform," International Journal of Industrial Organization, Elsevier, vol. 71(C).
    20. 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.

    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:ags:waeaar:245039. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/waeaaea.html .

    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.