An econometric analysis of veterans’ health care utilization using two-part models
Based on the 1992 US National Survey of Veterans, we analyzed veterans’ inpatient and outpatient health care utilization patterns by estimating count data two-part hurdle models. We also identified factors that affect veterans’ choice of health care between VA and non-VA facilities using count data selection models. Not surprisingly, we found that health condition measures are the most important factors in determining veterans’ health care utilization. Gender, disability, and employment status are also significant. Veterans with lower socio-economic status, without other health insurance coverages, or living near VA health care facilities are more likely to use VA health care system for outpatient visits and inpatient admissions. Our study underscores the role of alternative sources of health care and insurance in discerning the true effects of the explanatory variables on an individual’s total demand for health care and its allocation between alternative providers. Copyright Springer-Verlag 2004
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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 29 (2004)
Issue (Month): 2 (05)
|Contact details of provider:|| Web page: http://www.springer.com|
|Order Information:||Web: http://www.springer.com/economics/econometrics/journal/181/PS2|
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.:
- White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
- A. C. Cameron & 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, Oxford University Press, vol. 55(1), pages 85-106.
- Winfried Pohlmeier & Volker Ulrich, 1995. "An Econometric Model of the Two-Part Decisionmaking Process in the Demand for Health Care," Journal of Human Resources, University of Wisconsin Press, vol. 30(2), pages 339-361.
- Gourieroux, Christian & Monfort, Alain & Renault, Eric & Trognon, Alain, 1987. "Generalised residuals," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 5-32.
- Grogger, Jeffrey, 1990. "A simple test for exogeneity in probit, logit, and poisson regression models," Economics Letters, Elsevier, vol. 33(4), pages 329-332, August.
- Smith, Richard J & Blundell, Richard W, 1986. "An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply," Econometrica, Econometric Society, vol. 54(3), pages 679-85, May.
- Christofides, Louis N. & Stengos, Thanasis & Swidinsky, Robert, 1997. "On the calculation of marginal effects in the bivariate probit model," Economics Letters, Elsevier, vol. 54(3), pages 203-208, July.
- Cragg, John G, 1971. "Some Statistical Models for Limited Dependent Variables with Application to the Demand for Durable Goods," Econometrica, Econometric Society, vol. 39(5), pages 829-44, September.
- Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
- Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
- Windmeijer, F A G & Silva, J M C Santos, 1997.
"Endogeneity in Count Data Models: An Application to Demand for Health Care,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 12(3), pages 281-94, May-June.
- Frank Windmeijer & Joao Santos Silva, 1996. "Endogeneity in count data models; an application to demand for health care," IFS Working Papers W96/15, Institute for Fiscal Studies.
- Debra S. Dwyer & Olivia S. Mitchell, .
"Health Problems as Determinants of Retirement: Are Self-Rated Measures Endogenous?,"
Pension Research Council Working Papers
98-7, Wharton School Pension Research Council, University of Pennsylvania.
- Dwyer, Debra Sabatini & Mitchell, Olivia S., 1999. "Health problems as determinants of retirement: Are self-rated measures endogenous?," Journal of Health Economics, Elsevier, vol. 18(2), pages 173-193, April.
- Debra Sabatini Dwyer & Olivia S. Mitchell, 1998. "Health Problems as Determinants of Retirement: Are Self-Rated Measures Endogenous?," NBER Working Papers 6503, National Bureau of Economic Research, Inc.
When requesting a correction, please mention this item's handle: RePEc:spr:empeco:v:29:y:2004:i:2:p:431-449. 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: (Sonal Shukla)or (Rebekah McClure)
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.