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Testing the Proportional Hazards Assumption in the Presence of Unmeasured Heterogeneity

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  • McCall, Brian P

Abstract

This paper develops a discrete-time hazard model which accounts for unmeasured heterogeneity while allowing the coefficients of the regressors to vary over time. Sufficient conditions for nonparametric identifiability of the unmeasured heterogeneity distribution are derived. Testing for time-varying coefficients in this model is, under suitable conditions, equivalent to testing the proportionality assumption of the underlying continuous-time hazard model. Some Monte Carlo evidence is presented regarding the small-sample properties of this test. As an illustration, these tests are applied to the joblessness durations of displaced workers. Copyright 1994 by John Wiley & Sons, Ltd.

Suggested Citation

  • 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 321-334, July-Sept.
  • Handle: RePEc:jae:japmet:v:9:y:1994:i:3:p:321-34
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    Citations

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    Cited by:

    1. Wolfgang Hess & Maria Persson, 2011. "Exploring the duration of EU imports," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 147(4), pages 665-692, November.
    2. Bhattacharjee, A. & Samarjit Das, 2002. "Testing Proportionality in Duration Models with Respect to Continuous Covariates," Cambridge Working Papers in Economics 0220, Faculty of Economics, University of Cambridge.
    3. Bhattacharjee, A. & Higson, C. & Holly, S. & Kattuman, P., 2004. "Business Failure in UK and US Quoted Firms: Impact of Macroeconomic Instability and the Role of Legal Institutions," Cambridge Working Papers in Economics 0420, Faculty of Economics, University of Cambridge.
    4. Bent Jesper Christensen & Malene Kallestrup‐Lamb, 2012. "The Impact Of Health Changes On Labor Supply: Evidence From Merged Data On Individual Objective Medical Diagnosis Codes And Early Retirement Behavior," Health Economics, John Wiley & Sons, Ltd., vol. 21(S1), pages 56-100, June.
    5. Hess, Wolfgang & Persson, Maria, 2010. "The Duration of Trade Revisited. Continuous-Time vs. Discrete-Time Hazards," Working Papers 2010:1, Lund University, Department of Economics.
    6. ter Hofstede, Frenkel & Wedel, Michel, 1998. "A Monte Carlo study of time aggregation in continuous-time and discrete-time parametric hazard models," Economics Letters, Elsevier, vol. 58(2), pages 149-156, February.
    7. Bhat, Chandra R. & Steed, Jennifer L., 2002. "A continuous-time model of departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 207-224, March.
    8. Darrell J. Glaser & Ahmed S. Rahman, 2017. "Development and Retention of Human Capital in Large Bureaucracies," Departmental Working Papers 60, United States Naval Academy Department of Economics.
    9. Addison, John T. & Portugal, Pedro, 2004. "How does the unemployment insurance system shape the time profile of jobless duration?," Economics Letters, Elsevier, vol. 85(2), pages 229-234, November.
    10. DesJardins, S. L. & Ahlburg, D. A. & McCall, B. P., 1999. "An event history model of student departure," Economics of Education Review, Elsevier, vol. 18(3), pages 375-390, June.
    11. Stefan Bojnec & Imre Ferto, 2018. "Drivers of the duration of comparative advantage in the European Union's agri-food exports," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(2), pages 51-60.
    12. DesJardins, Stephen L. & Ahlburg, Dennis A. & McCall, Brian P., 2006. "The effects of interrupted enrollment on graduation from college: Racial, income, and ability differences," Economics of Education Review, Elsevier, vol. 25(6), pages 575-590, December.
    13. Brinch, Christian N., 2007. "Nonparametric Identification Of The Mixed Hazards Model With Time-Varying Covariates," Econometric Theory, Cambridge University Press, vol. 23(2), pages 349-354, April.
    14. Ana M. Fernandes & Caroline Paunov, 2015. "The Risks of Innovation: Are Innovating Firms Less Likely to Die?," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 638-653, July.
    15. Christian N. Brinch, 2011. "Non‐parametric identification of the mixed proportional hazards model with interval‐censored durations," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 343-350, July.
    16. Glaser, Darrell & Rahman, Ahmed, 2015. "Human Capital on the High Seas - Job Mobility and Returns to Technical Skill During Industrialization," MPRA Paper 68351, University Library of Munich, Germany.
    17. Brinch,C., 2000. "Identification of structural duration dependence and unobserved heterogeneity with time-varying," Memorandum 20/2000, Oslo University, Department of Economics.
    18. Zsurkis, Gabriel & Nicolau, João & Rodrigues, Paulo M. M, 2021. "The expected time to cross a threshold and its determinants: a simple and flexible framework," Journal of Economic Dynamics and Control, Elsevier, vol. 122(C).
    19. Wolfgang Hess & Maria Persson, 2012. "The duration of trade revisited," Empirical Economics, Springer, vol. 43(3), pages 1083-1107, December.
    20. Audrey Light & Yoshiaki Omori, 2004. "Unemployment Insurance and Job Quits," Journal of Labor Economics, University of Chicago Press, vol. 22(1), pages 159-188, January.
    21. Giovanni Mastrobuoni, 2007. "Do better–informed workers make better retirement choices? A test based on the Social Security Statement," Carlo Alberto Notebooks 51, Collegio Carlo Alberto.
    22. Darrell J. Glaser & Ahmed S. Rahman, 2012. "Technical Human Capital and Job Mobility in an Era of Rapid Technological Innovation," Departmental Working Papers 37, United States Naval Academy Department of Economics.
    23. Christian N. Brinch, 2008. "Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations," Discussion Papers 539, Statistics Norway, Research Department.

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