IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

A Generalized Parametric Selection Model for Non-Normal Data

  • James E. Prieger

    (Department of Economics, University of California Davis)

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.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://wp.econ.ucdavis.edu/00-9.pdf
Our checks indicate that this address may not be valid because: 500 Can't connect to wp.econ.ucdavis.edu:80 (10060). If this is indeed the case, please notify (Scott Dyer)


Download Restriction: no

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

as
in new window

Length: 37
Date of creation: 16 Jan 2003
Date of revision:
Handle: RePEc:cda:wpaper:00-9
Contact details of provider: Postal: One Shields Ave., Davis, CA 95616-8578
Phone: (530) 752-0741
Fax: (530) 752-9382
Web page: http://www.econ.ucdavis.eduEmail:


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.:

as in new window
  1. Donald, Stephen G., 1995. "Two-step estimation of heteroskedastic sample selection models," Journal of Econometrics, Elsevier, vol. 65(2), pages 347-380, February.
  2. 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.
  3. 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.
  4. R. Winkelmann, 1998. "Count data models with selectivity," Econometric Reviews, Taylor & Francis Journals, vol. 17(4), pages 339-359.
  5. Gronau, Reuben, 1974. "Wage Comparisons-A Selectivity Bias," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1119-43, Nov.-Dec..
  6. 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.
  7. 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.
  8. repec:att:wimass:9001 is not listed on IDEAS
  9. repec:att:wimass:8909 is not listed on IDEAS
  10. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-23, May.
  11. Crepon, B. & Duguet, E., 1995. "Research and Development, Competition and Innovation; Pseudo Maximum Likelihood and Simulated Maximum Likelihood Methods Applied to Count Data Models with Heterogeneity," Papiers d'Economie Mathématique et Applications 95.08, Université Panthéon-Sorbonne (Paris 1).
  12. 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.
  13. 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.
  14. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
  15. 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.
  16. 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.
  17. 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.
  18. Levinson, Arik & Ullman, Frank, 1998. "Medicaid managed care and infant health," Journal of Health Economics, Elsevier, vol. 17(3), pages 351-368, June.
  19. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-90, March.
  20. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-94, July.
  21. 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.
  22. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-12, March.
  23. 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.
  24. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
  25. 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.
  26. 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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:cda:wpaper:00-9. 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 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.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.