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Semiparametric identification in duration models

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  • Andrew Chesher

Abstract

This paper explores the identifiability of ratios of derivatives of the index function in a model of a duration process in which the impact of covariates on the hazard function passes through a single index. The model allows duration and the index to appear in a nonseparable form in the hazard function and includes a latent heterogeneity term which acts multiplicatively on the hazard function. The model allows covariates to be endogenous, that is to be correlated with the heterogeneity term. Quantile invariance, local order and local rank conditions are shown to be sufficient to permit identification of ratios of derivatives of the index function. The framework constructed in this paper is suitable for the analysis of identification in panel duration models with heterogeneity.

Suggested Citation

  • Andrew Chesher, 2002. "Semiparametric identification in duration models," CeMMAP working papers 20/02, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:20/02
    DOI: 10.1920/wp.cem.2002.2002
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    Cited by:

    1. Andrew Chesher, 2004. "Identification of sensitivity to variation in endogenous variables," Econometric Society 2004 Australasian Meetings 353, Econometric Society.
    2. Abbring, Jaap H & van den Berg, Gerard J, 2005. "Social experiments and intrumental variables with duration outcomes," Working Paper Series 2005:11, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    3. Bonev, Petyo & Matsumoto, Shigeru, 2022. "An empirical evaluation of environmental Alternative Dispute Resolution methods," Economics Working Paper Series 2208, University of St. Gallen, School of Economics and Political Science.
    4. Bonev, Petyo, 2020. "Nonparametric identification in nonseparable duration models with unobserved heterogeneity," Economics Working Paper Series 2005, University of St. Gallen, School of Economics and Political Science.
    5. van den Berg, Gerard J. & Bonev, Petyo & Mammen, Enno, 2016. "Nonparametric Instrumental Variable Methods for Dynamic Treatment Evaluation," IZA Discussion Papers 9782, Institute of Labor Economics (IZA).
    6. Gerard J. van den Berg & Petyo Bonev & Enno Mammen, 2020. "Nonparametric Instrumental Variable Methods for Dynamic Treatment Evaluation," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 355-367, May.
    7. Guido W. Imbens & Whitney K. Newey, 2009. "Identification and Estimation of Triangular Simultaneous Equations Models Without Additivity," Econometrica, Econometric Society, vol. 77(5), pages 1481-1512, September.
    8. Chesher, Andrew, 2009. "Excess heterogeneity, endogeneity and index restrictions," Journal of Econometrics, Elsevier, vol. 152(1), pages 37-45, September.
    9. Andrew Chesher, 2005. "Identification with excess heterogeneity," CeMMAP working papers CWP19/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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