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Seemingly Unrelated Negative Binomial Regression

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  • 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
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    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. 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.
    3. Marco Alfò & Giovanni Trovato, 2004. "Semiparametric Mixture Models for Multivariate Count Data, with Application," CEIS Research Paper 51, Tor Vergata University, CEIS.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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).
    12. Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Wen, Yuni, 2024. "Public interest v.s. special interest: The strategic framing tactics of technologies in the political arena," Research Policy, Elsevier, vol. 53(8).
    20. 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.
    21. Vishaal Baulkaran & Pawan Jain, 2023. "Who uses robo‐advising and how?," The Financial Review, Eastern Finance Association, vol. 58(1), pages 65-89, February.
    22. Burkey, Mark L. & Obeng, Kofi, 2005. "Crash Risk Reduction at Signalized Intersections Using Longitudinal Data," MPRA Paper 36281, University Library of Munich, Germany.

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