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Semiparametric mixture models for multivariate count data, with application

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Author Info
Marco Alfò
Giovanni Trovato

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Abstract

The analysis of overdispersed counts has been the focus of a wide range of literature, with the general objective of providing reliable parameter estimates in the presence of heterogeneity or dependence among subjects. In this paper we extend the standard variance component models to the analysis of multivariate counts, defining the dependence among counts through a set of correlated random coefficients. Estimation is carried out by numerical integration through an EM algorithm without parametric assumptions upon the random coefficients distribution. The proposed model is computationally parsimonious and, when applied to a real dataset, seems to produce better results than parametric models. A simulation study has been carried out to investigate the behaviour of the proposed models in a series of empirical situations. Copyright Royal Economic Socciety 2004

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Article provided by Royal Economic Society in its journal The Econometrics Journal.

Volume (Year): 7 (2004)
Issue (Month): 2 (December)
Pages: 426-454
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Handle: RePEc:ect:emjrnl:v:7:y:2004:i:2:p:426-454

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Brannas, Kurt & Rosenqvist, Gunnar, 1994. "Semiparametric estimation of heterogeneous count data models," European Journal of Operational Research, Elsevier, vol. 76(2), pages 247-258, July. [Downloadable!] (restricted)
  2. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March. [Downloadable!] (restricted)
  3. Biernacki, Christophe & Celeux, Gilles & Govaert, Gerard, 2003. "Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 561-575, January. [Downloadable!] (restricted)
  4. Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," NBER Technical Working Papers 0017, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  5. Davies, Richard B., 1993. "Nonparametric control for residual heterogeneity in modelling recurrent behaviour," Computational Statistics & Data Analysis, Elsevier, vol. 16(2), pages 143-160, August. [Downloadable!] (restricted)
  6. Jung, Robert C & Winkelmann, Rainer, 1993. "Two Aspects of Labor Mobility: A Bivariate Poisson Regression Approach," Empirical Economics, Springer, vol. 18(3), pages 543-56.
  7. Murat K. Munkin & Pravin K. Trivedi, 1999. "Simulated maximum likelihood estimation of multivariate mixed-Poisson regression models, with application," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 29-48.
  8. Cameron, A Colin & Trivedi, Pravin K, 1993. "Tests of Independence in Parametric Models with Applications and Illustrations," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 29-43, January.
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  9. Chib, Siddhartha & Winkelmann, Rainer, 2001. "Markov Chain Monte Carlo Analysis of Correlated Count Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 428-35, October.
  10. van Ophem, Hans, 1999. "A General Method To Estimate Correlated Discrete Random Variables," Econometric Theory, Cambridge University Press, vol. 15(02), pages 228-237, April. [Downloadable!]
  11. Cameron, A Colin & Johansson, Per, 1997. "Count Data Regression Using Series Expansions: With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 203-23, May-June. [Downloadable!]
  12. Cameron, A C & P. K. Trivedi & Frank Milne & J. Piggott, 1988. "A Microeconometric Model of the Demand for Health Care and Health Insurance in Australia," Review of Economic Studies, Blackwell Publishing, vol. 55(1), pages 85-106, January. [Downloadable!] (restricted)
  13. Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, vol. 77(2), pages 329-342, April. [Downloadable!] (restricted)
  14. Gurmu, Shiferaw & Elder, John, 2000. "Generalized bivariate count data regression models," Economics Letters, Elsevier, vol. 68(1), pages 31-36, July. [Downloadable!] (restricted)
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  1. Alka Chadha, 2005. "Trips and Patenting Activity: Evidence from the Indian Pharmaceutical Industry," Departmental Working Papers wp0512, National University of Singapore, Department of Economics. [Downloadable!]
  2. Leonardo Becchetti & Luisa Corrado & Fiammetta Rossetti, 2008. "Easterlin-types and Frustrated Achievers: the Heterogeneous E¤ects of Income Changes on Life Satisfaction," CEIS Research Paper 127, Tor Vergata University, CEIS, revised 09 Sep 2008. [Downloadable!]
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  3. Leonardo Becchetti & Roberto Rocci & Giovanni Trovato, 2007. "Industry and time specific deviations from fundamental values in a random coefficient model," Annals of Finance, Springer, vol. 3(2), pages 257-276, March. [Downloadable!] (restricted)
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