IDEAS home Printed from https://ideas.repec.org/a/bla/obuest/v62y2000i4p553-560.html
   My bibliography  Save this article

Seemingly Unrelated Negative Binomial Regression

Author

Listed:
  • Rainer Winkelmann

Abstract

This paper discusses the specification and estimation of seemingly unrelated multivariate count data models. A new model with negative binomial marginals is proposed. In contrast to a previous model based on the multivariate Poisson distribution, the new model allows for over‐dispersion, a phenomenon that is frequently encountered in economic count data. Semi‐parametric estimation is possible if some of the assumption of the fully specified model are violated.

Suggested Citation

  • Rainer Winkelmann, 2000. "Seemingly Unrelated Negative Binomial Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(4), pages 553-560, September.
    • Handle: RePEc:bla:obuest:v:62:y:2000:i:4:p:553-560
    DOI: 10.1111/1468-0084.00188
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1468-0084.00188
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1468-0084.00188?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
    ---><---

    Citations

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


    Cited by:

    1. Drivas, Kyriakos & Economidou, Claire & Karkalakos, Sotiris & Tsionas, Efthymios G., 2016. "Mobility of knowledge and local innovation activity," European Economic Review, Elsevier, vol. 85(C), pages 39-61.
    2. Marco Alfò & Giovanni Trovato, 2004. "Semiparametric Mixture Models for Multivariate Count Data, with Application," CEIS Research Paper 51, Tor Vergata University, CEIS.
    3. Stefan Lang & Samson B. Adebayo & Ludwig Fahrmeir & Winfried J. Steiner, 2003. "Bayesian Geoadditive Seemingly Unrelated Regression," Computational Statistics, Springer, vol. 18(2), pages 263-292, July.
    4. Herriges, Joseph A. & Phaneuf, Daniel J. & Tobias, Justin L., 2008. "Estimating demand systems when outcomes are correlated counts," Journal of Econometrics, Elsevier, vol. 147(2), pages 282-298, December.
    5. Katsuhito Nohara & Masaki Narukawa & Akira Hibiki, 2021. "Using contingent behavior analysis to estimate benefits from coral reefs in Kume Island, Japan: A Poisson-inverse Gaussian approach with on-site correction," TUPD Discussion Papers 1, Graduate School of Economics and Management, Tohoku University.
    6. Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
    7. Shi, Peng & Valdez, Emiliano A., 2014. "Multivariate negative binomial models for insurance claim counts," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 18-29.
    8. Katsuhito Nohara, 2014. "Economic Valuation of the Damage to Tourism Benefits by Eastern Japan Great Earthquake Disaster," ERSA conference papers ersa14p1017, European Regional Science Association.
    9. Antonello Maruotti & Pierfrancesco Alaimo Di Loro, 2023. "CO2 emissions and growth: A bivariate bidimensional mean‐variance random effects model," Environmetrics, John Wiley & Sons, Ltd., vol. 34(5), August.
    10. Egan, Kevin & Herriges, Joseph, 2006. "Multivariate count data regression models with individual panel data from an on-site sample," Journal of Environmental Economics and Management, Elsevier, vol. 52(2), pages 567-581, September.
    11. Stephen Hynes & William Greene, 2013. "A Panel Travel Cost Model Accounting for Endogenous Stratification and Truncation: A Latent Class Approach," Land Economics, University of Wisconsin Press, vol. 89(1), pages 177-192.
    12. Jie Yan & Sheng Zeng & Bijiang Tian & Yuanwen Cao & Wenchen Yang & Feng Zhu, 2023. "Relationship between Highway Geometric Characteristics and Accident Risk: A Multilayer Perceptron Model (MLP) Approach," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    13. Umeair Shahzad & Fukai Luo & Jing Liu, 2023. "Debt financing and technology investment Kuznets curve: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 751-765, January.
    14. Katsuhito Nohara & Masaki Narukawa, 2015. "Measuring lost recreational benefits in Fukushima due to harmful rumors using a Poisson-inverse Gaussian regression?," ERSA conference papers ersa15p344, European Regional Science Association.
    15. Vishaal Baulkaran & Pawan Jain, 2023. "Who uses robo‐advising and how?," The Financial Review, Eastern Finance Association, vol. 58(1), pages 65-89, February.
    16. Burkey, Mark L. & Obeng, Kofi, 2005. "Crash Risk Reduction at Signalized Intersections Using Longitudinal Data," MPRA Paper 36281, University Library of Munich, Germany.
    17. Aristidis Nikoloulopoulos & Dimitris Karlis, 2010. "Regression in a copula model for bivariate count data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1555-1568.
    18. Amaya-Gómez, Rafael & Sánchez-Silva, Mauricio & Muñoz, Felipe & Schoefs, Franck & Bastidas-Arteaga, Emilio, 2024. "Spatial characterization and simulation of new defects in corroded pipeline based on In-Line Inspections," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    19. Ping Zhang & Chenzhu Wang & Fei Chen & Suping Cui & Jianchuan Cheng & Wu Bo, 2022. "A Random-Parameter Negative Binomial Model for Assessing Freeway Crash Frequency by Injury Severity: Daytime versus Nighttime," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    20. Shon R. Hiatt & W. Chad Carlos, 2019. "From farms to fuel tanks: Stakeholder framing contests and entrepreneurship in the emergent U.S. biodiesel market," Strategic Management Journal, Wiley Blackwell, vol. 40(6), pages 865-893, June.
    21. Park, Timothy A. & Lohr, Luanne, 2002. "Organic Pest Management Decisions: A Systems Approach," Faculty Series 16655, University of Georgia, Department of Agricultural and Applied Economics.

    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:bla:obuest:v:62:y:2000:i:4:p:553-560. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/sfeixuk.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.