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Semiparametric identification in duration models


  • Andrew Chesher

    () (Institute for Fiscal Studies and University College London)


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 CWP20/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:20/02

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    Cited by:

    1. 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.
    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. Andrew Chesher, 2004. "Identification of sensitivity to variation in endogenous variables," CeMMAP working papers CWP10/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Andrew Chesher, 2005. "Identification with excess heterogeneity," CeMMAP working papers CWP19/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Chesher, Andrew, 2009. "Excess heterogeneity, endogeneity and index restrictions," Journal of Econometrics, Elsevier, vol. 152(1), pages 37-45, September.
    6. Berg, Gerard J. van den & Bonev, Petyo & Mammen, Enno, 2016. "Nonparametric instrumental variable methods for dynamic treatment evaluation," Working Papers 16-02, University of Mannheim, Department of Economics.

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