Bivariate Count Data Regression Using Series Expansions: With Applications
Most research on count data regression models, i.e. models for there the dependent variable takes only non-negative integer values or count values, has focused on the univariate case. Very little attention has been given to joint modeling of two or more counts. We propose parametric regression models for bivariate counts based on squared polynomial expansions around a baseline density. The models are more flexible than the current leading bivariate count model, the bivariate Poisson. The models are applied to data on the use of prescribed and nonprescribed medications.
|Date of creation:||21 Jul 2004|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (530) 752-0741
Fax: (530) 752-9382
Web page: http://www.econ.ucdavis.edu
More information through EDIRC
References listed on IDEAS
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.:
- Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
- Gurmu, Shiferaw & Rilstone, Paul & Stern, Steven, 1998. "Semiparametric estimation of count regression models1," Journal of Econometrics, Elsevier, vol. 88(1), pages 123-150, November.
- Cameron, C. & Trivedi, P.K., 1992.
"Tests of Independence in Parametric Models : with Applications and Illustrations,"
9237, Tilburg - Center for Economic Research.
- 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.
- Cameron, A. & Trivedi, P., 1992. "Tests of Independence in Parametric Models : With Applications and Illustrations," Discussion Paper 1992-37, Tilburg University, Center for Economic Research.
- Gourieroux Christian & Monfort Alain & Trognon A, 1982.
"Pseudo maximum lilelihood methods : applications to poisson models,"
CEPREMAP Working Papers (Couverture Orange)
- Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-20, May.
- 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.
- 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, Wiley Blackwell, vol. 55(1), pages 85-106, January.
- 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.
- Hausman, Jerry A. & Leonard, Gregory K. & McFadden, Daniel, 1995. "A utility-consistent, combined discrete choice and count data model Assessing recreational use losses due to natural resource damage," Journal of Public Economics, Elsevier, vol. 56(1), pages 1-30, January.
- Gallant, A.R. & Tauchen, G., 1988.
"Seminonparametric Estimation Of Conditionally Constrained Heterogeneous Processes: Asset Pricing Applications,"
88-59, Chicago - Graduate School of Business.
- Gallant, Ronald & Tauchen, George, 1989. "Seminonparametric Estimation of Conditionally Constrained Heterogeneous Processes: Asset Pricing Applications," Econometrica, Econometric Society, vol. 57(5), pages 1091-1120, September.
- Gurmu, Shiferaw, 1997. "Semi-Parametric Estimation of Hurdle Regression Models with an Application to Medicaid Utilization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 225-43, May-June.
- 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 108-15, February.
When requesting a correction, please mention this item's handle: RePEc:cda:wpaper:98-15. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Scott Dyer)
If references are entirely missing, you can add them using this form.