Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations
AbstractEconometric duration data are typically interval-censored, that is, not directly observed, but observed to fall within a known interval. Known non-parametric identification results for duration models with unobserved heterogeneity rely crucially on exact observation of durations at a continuous scale. Here, it is established that the mixed hazards model is non-parametrically identified through covariates that vary over time within durations as well as between observations when durations are interval-censored. The results hold for the mixed proportional hazards model as a special case.
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Bibliographic InfoPaper provided by Research Department of Statistics Norway in its series Discussion Papers with number 539.
Date of creation: Apr 2008
Date of revision:
duration analysis; interval-censoring; non-parametric identification;
Find related papers by JEL classification:
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
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- Klein, Roger W & Spady, Richard H, 1993.
"An Efficient Semiparametric Estimator for Binary Response Models,"
Econometric Society, vol. 61(2), pages 387-421, March.
- Klein, R.W. & Spady, R.H., 1991. "An Efficient Semiparametric Estimator for Binary Response Models," Papers 70, Bell Communications - Economic Research Group.
- Matzkin, Rosa L., 1986. "Restrictions of economic theory in nonparametric methods," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 42, pages 2523-2558 Elsevier.
- Elbers, Chris & Ridder, Geert, 1982. "True and Spurious Duration Dependence: The Identifiability of the Proportional Hazard Model," Review of Economic Studies, Wiley Blackwell, vol. 49(3), pages 403-09, July.
- Edin, P.A. & Bergstrom, R., 1991.
"Time aggregation and the Distributional Shape of Unemployment Duration,"
1991u, Uppsala - Working Paper Series.
- Bergstrom, R & Edin, P-A, 1992. "Time Aggregation and the Distributional Shape of Unemployment Duration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 5-30, Jan.-Marc.
- Knut Roed & Tao Zhang, 2003. "Does Unemployment Compensation Affect Unemployment Duration?," Economic Journal, Royal Economic Society, vol. 113(484), pages 190-206, January.
- Arulampalam, Wiji & Stewart, Mark B, 1995. "The Determinants of Individual Unemployment Durations in an Era of High Unemployment," Economic Journal, Royal Economic Society, vol. 105(429), pages 321-32, March.
- Christopher J. Flinn & James J. Heckman, 1982. "Models for the Analysis of Labor Force Dynamics," NBER Working Papers 0857, National Bureau of Economic Research, Inc.
- Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
- van den Berg, Gerard J & van Ours, Jan C, 1994. "Unemployment Dynamics and Duration Dependence in France, the Netherlands and the United Kingdom," Economic Journal, Royal Economic Society, vol. 104(423), pages 432-43, March.
- Sueyoshi, Glenn T, 1995. "A Class of Binary Response Models for Grouped Duration Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 411-31, Oct.-Dec..
- Van den Berg, Gerard J., 2000.
"Duration Models: Specification, Identification, and Multiple Durations,"
9446, University Library of Munich, Germany.
- Van den Berg, Gerard J., 2001. "Duration models: specification, identification and multiple durations," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 55, pages 3381-3460 Elsevier.
- Heckman, J & Singer, B, 1984. "The Identifiability of the Proportional Hazard Model," Review of Economic Studies, Wiley Blackwell, vol. 51(2), pages 231-41, April.
- Ridder, Geert, 1990. "The Non-parametric Identification of Generalized Accelerated Failure-Time Models," Review of Economic Studies, Wiley Blackwell, vol. 57(2), pages 167-81, April.
- Jaap H. Abbring & Gerard J. van den Berg, 2003. "The identifiability of the mixed proportional hazards competing risks model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(3), pages 701-710.
- Knut R�ed & Tao Zhang, 2002. "A note on the Weibull distribution and time aggregation bias," Applied Economics Letters, Taylor and Francis Journals, vol. 9(7), pages 469-472.
- Heckman, James J. & Navarro, Salvador, 2005.
"Dynamic Discrete Choice and Dynamic Treatment Effects,"
IZA Discussion Papers
1790, Institute for the Study of Labor (IZA).
- Heckman, James J. & Navarro, Salvador, 2007. "Dynamic discrete choice and dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 136(2), pages 341-396, February.
- James J. Heckman & Salvador Navarro, 2005. "Dynamic Discrete Choice and Dynamic Treatment Effects," NBER Technical Working Papers 0316, National Bureau of Economic Research, Inc.
- Roger W. Klein & Robert P. Sherman, 2002. "Shift Restrictions and Semiparametric Estimation in Ordered Response Models," Econometrica, Econometric Society, vol. 70(2), pages 663-691, March.
- Carling, Kenneth & Edin, Per-Anders & Harkman, Anders & Holmlund, Bertil, 1996. "Unemployment duration, unemployment benefits, and labor market programs in Sweden," Journal of Public Economics, Elsevier, vol. 59(3), pages 313-334, March.
- Brinch, Christian N., 2007. "Nonparametric Identification Of The Mixed Hazards Model With Time-Varying Covariates," Econometric Theory, Cambridge University Press, vol. 23(02), pages 349-354, April.
- Sueyoshi, Glenn T., 1992. "Semiparametric proportional hazards estimation of competing risks models with time-varying covariates," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 25-58.
- Bierens, Herman J., 2008. "Semi-Nonparametric Interval-Censored Mixed Proportional Hazard Models: Identification And Consistency Results," Econometric Theory, Cambridge University Press, vol. 24(03), pages 749-794, June.
- Bearse, Peter & Canals-Cerd , Jos & Rilstone, Paul, 2007. "Efficient Semiparametric Estimation Of Duration Models With Unobserved Heterogeneity," Econometric Theory, Cambridge University Press, vol. 23(02), pages 281-308, April.
- McCall, Brian P, 1994. "Testing the Proportional Hazards Assumption in the Presence of Unmeasured Heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(3), pages 321-34, July-Sept.
- Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
- Christian N. Brinch, 2011.
"Non‐parametric identification of the mixed proportional hazards model with interval‐censored durations,"
Royal Economic Society, vol. 14(2), pages 343-350, 07.
- Christian N. Brinch, 2009. "Non-parametric identication of the mixed proportional hazards model with interval-censored durations," Discussion Papers 600, Research Department of Statistics Norway.
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