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A Generalized Parametric Selection Model for Non-Normal Data

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  • James E. Prieger

    (Department of Economics, University of California Davis)

Abstract

I develop a new approach for sample selection problems that allows parametric forms of any type to be chosen for both for the selection and the observed variables. The Generalized Parametric Selection (GPS) model can incorporate both duration and count data models, unlike previous parametric models. MLE does not require numerical integration or simulation techniques, unlike previous models for count data. I discuss application to common duration models (exponential, Weibull, log-logistic) and count models (Poisson, negative binomial). I demonstrate the usefulness of the model with an application to the effects of insurance status and managed care on hospitalization duration data. The example indicates that the GPS model may be preferred even in cases for which other parametric approaches are available.

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Bibliographic Info

Paper provided by University of California, Davis, Department of Economics in its series Working Papers with number 09.

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Length: 37
Date of creation: 16 Jan 2003
Date of revision:
Handle: RePEc:cda:wpaper:00-9

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Related research

Keywords: sample selection; bivariate distribution; duration models; count data models; lee's model; managed care; Medical Expenditure Panel Survey;

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References

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  1. 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.
  2. Dor, Avi & Farley, Dean E., 1996. "Payment source and the cost of hospital care: Evidence from a multiproduct cost function with multiple payers," Journal of Health Economics, Elsevier, vol. 15(1), pages 1-21, February.
  3. repec:att:wimass:9001 is not listed on IDEAS
  4. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
  5. Levinson, Arik & Ullman, Frank, 1998. "Medicaid managed care and infant health," Journal of Health Economics, Elsevier, vol. 17(3), pages 351-368, June.
  6. repec:att:wimass:8909 is not listed on IDEAS
  7. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
  8. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-36, May-June.
  9. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-12, March.
  10. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-94, July.
  11. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
  12. R. Winkelmann, 1998. "Count data models with selectivity," Econometric Reviews, Taylor & Francis Journals, vol. 17(4), pages 339-359.
  13. Crepon, Bruno & Duguet, Emmanuel, 1997. "Research and development, competition and innovation pseudo-maximum likelihood and simulated maximum likelihood methods applied to count data models with heterogeneity," Journal of Econometrics, Elsevier, vol. 79(2), pages 355-378, August.
  14. Brigitte C. Madrian, 1993. "Employment-Based Health Insurance and Job Mobility: Is There Evidence ofJob-Lock?," NBER Working Papers 4476, National Bureau of Economic Research, Inc.
  15. Welch, W. P., 1985. "Health care utilization in HMO'S : Results from two national samples," Journal of Health Economics, Elsevier, vol. 4(4), pages 293-308, December.
  16. Gronau, Reuben, 1974. "Wage Comparisons-A Selectivity Bias," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1119-43, Nov.-Dec..
  17. Rosenman, Robert E., 1993. "Health plan effects on inpatient resource use: Some contrary evidence about IPAs," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 22(2), pages 131-140.
  18. Ettner, Susan L., 1997. "Adverse selection and the purchase of Medigap insurance by the elderly," Journal of Health Economics, Elsevier, vol. 16(5), pages 543-562, October.
  19. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
  20. Terza, Joseph V., 1998. "Estimating count data models with endogenous switching: Sample selection and endogenous treatment effects," Journal of Econometrics, Elsevier, vol. 84(1), pages 129-154, May.
  21. 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.
  22. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-23, May.
  23. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-90, March.
  24. Donna B. Gilleskie, 1998. "A Dynamic Stochastic Model of Medical Care Use and Work Absence," Econometrica, Econometric Society, vol. 66(1), pages 1-46, January.
  25. Donald, Stephen G., 1995. "Two-step estimation of heteroskedastic sample selection models," Journal of Econometrics, Elsevier, vol. 65(2), pages 347-380, February.
  26. Newey, Whitney K & Powell, James L & Walker, James R, 1990. "Semiparametric Estimation of Selection Models: Some Empirical Results," American Economic Review, American Economic Association, vol. 80(2), pages 324-28, May.
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