Value of Sample Separation Information in a Sequential Probit Model: Another Look at SSA's Disability Determination Process
We have estimated a 4-step sequential probit model with and without sample separation information to characterize SSA's disability determination process. Under the program provisions, different criteria dictate the outcomes at different steps o f the process. We used data on health, activity limitations, demographic traits, and work from 1990 SIPP exact matched to SSA administrative records on disability determinations. Using GHK Monte Carlo simulation technique, our estimation results suggest that the correlations in errors across equations that may arise due to unobserved individual heterogeneity are not statistically significant. In addition, we examined the value of administrative data on the basis for allow/deny determinations at each sta ge of the process. Following the marginal likelihood approach adopted by Benitez-Silva, Buchinsky, Chan, Rust, and Sheidvasser (1999), we also estimated the above sequential probit model without the sample separation information for the purpose of direct comparison. We found that without the detailed administrative information on outcomes at each stage of the screening process, we could not properly evaluate the importance of a large number of program-relevant survey-based explanatory v ariables. In terms of both in-sample and jackknife-type out-of-sample predictive analysis, the value of modeling the sequential structure of the determination process in generating correct eligibility probabilities is confirmed.
|Date of creation:||01 Aug 2000|
|Contact details of provider:|| Phone: 1 212 998 3820|
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC
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.:
- Meng, Chun-Lo & Schmidt, Peter, 1985. "On the Cost of Partial Observability in the Bivariate Probit Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(1), pages 71-85, February.
- Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
- Schmidt, Peter, 1981. "Further Results on the Value of Sample Separation Information [Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model]," Econometrica, Econometric Society, vol. 49(5), pages 1339-1343, September.
- Benitez-Silva, Hugo & Buchinsky, Moshe & Chan, Hiu Man & Rust, John & Sheidvasser, Sofia, 1999.
"An empirical analysis of the social security disability application, appeal, and award process,"
Elsevier, vol. 6(2), pages 147-178, June.
- Hugo Benitez-Silva & Moshe Buchinsky & Hiu-Man Chan & John Rust & Sofia Sheivasser, 1997. "An Empirical Analysis of the Social Security Disability Application, Appeal, and Award Process," Public Economics 9712001, EconWPA, revised 16 Feb 1998.
- Vassilis A. Hajivassiliou, 1991. "Simulation Estimation Methods for Limited Dependent Variable Models," Cowles Foundation Discussion Papers 1007, Cowles Foundation for Research in Economics, Yale University.
- Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, "undated". "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Kiefer, Nicholas M, 1978. "Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model," Econometrica, Econometric Society, vol. 46(2), pages 427-434, March.
- Blundell, Richard & Ham, John & Meghir, Costas, 1987. "Unemployment and Female Labour Supply," Economic Journal, Royal Economic Society, vol. 97(388a), pages 44-64, Supplemen.
- Blundell, Richard William & Ham, John & Meghir, Costas, 1987. "Unemployment and Female Labour Supply," CEPR Discussion Papers 149, C.E.P.R. Discussion Papers.
- Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
- Goldfelfd, Stephen M. & Quandt, Richard E., 1975. "Estimation in a disequilibrium model and the value of information," Journal of Econometrics, Elsevier, vol. 3(4), pages 325-348, November.
- Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
- Vassilis A. Hajivassiliou & Daniel L. McFadden & Paul Ruud, 1993. "Simulation of Multivariate Normal Rectangle Probabilities and their Derivatives: Theoretical and Computational Results," Working Papers _024, Yale University.
- Poirier, Dale J., 1980. "Partial observability in bivariate probit models," Journal of Econometrics, Elsevier, vol. 12(2), pages 209-217, February.
- Jones, Andrew M, 1989. "A Double-Hurdle Model of Cigarette Consumption," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(1), pages 23-39, Jan.-Mar..
- 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 829-844, September. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:ecm:wc2000:0340. 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: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.