Skip to main content
Log in

Simplified estimation of multivariate duration models with unobserved heterogeneity

  • Original Paper
  • Published:
Computational Statistics Aims and scope Submit manuscript

Abstract

A simple structure is suggested for modelling unobserved heterogeneity in multivariate duration models which avoids the “curse of dimensionality” and numerical integration of the likelihood function.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Anderson J, Louis JT, Holm N, Harvald B (1992) Time-dependent association measures for bivariate survival distributions. J Am Stat Assoc 87(419):541–650

    Article  MathSciNet  Google Scholar 

  • Behrman JR, Sickles RC, Taubman P (1990) Age-specific death rates with tobacco smoking and occupational activity: sensitivity to sample length, functional form, and unobserved frailty. Demography 27(2):267–284

    Article  Google Scholar 

  • Butler JS, Anderson KH, Burkhauser RV (1989) Work and health after retirement: A competing risks model with semiparametric unobserved heterogeneity. Rev Econ Stat 46–53

  • Colby G, Rilstone P (2004a) Nonparametric identification of latent competing risks and Roy duration models, Department of Economics. York University, Toronto

    Google Scholar 

  • Colby G, Rilstone P (2004b) Nonparametric identification of latent competing risks and Roy duration models. Econ Theory 20:883–890

    MATH  MathSciNet  Google Scholar 

  • Flinn CJ, Heckman JJ (1982) Models for the analysis of labor force dynamics, advances in econometrics, vol.1. JAI Press Inc., Greenwich

    Google Scholar 

  • Gruttola V, Tu X (1994) Modelling progression of CD4-lymphocyte count and its relationship of survival Time. Biometrics 50(4):1003–1014

    Article  MATH  Google Scholar 

  • Gurmu S, Rilstone P, Stern S (1995) Nonparametric hazard rate estimation, mimeo, Department of Economics. University of Virginia, Charlottesville

    Google Scholar 

  • Heckman JJ, Honore BE (1990) The empirical content of the Roy model. Econometrica 58:1121–1149

    Article  Google Scholar 

  • Heckman JJ, Singer B (1984a) A method for reducing the impact of distributional assumptions in econometric models for duration data. Econometrica 52:271–320

    Article  MATH  MathSciNet  Google Scholar 

  • Heckman JJ, Singer B (1984b) Econometric duration analysis. J Econom 24:63–132

    Article  MATH  MathSciNet  Google Scholar 

  • Heckman JJ, Singer B (1985) Social science duration data. In: Longitudinal analysis of labor market data. Cambridge University Press, New York

  • Heckman JJ, Walker JR (1990) The relationship between wages and income and the timing and spacing of births: evidence from swedish longitudinal data. Econometirca 58:1411–1441

    Article  MATH  Google Scholar 

  • Johnson NL, Kotz S (1972) Distributions in statistics: continuous multivariate distributions. Wiley, New York

    MATH  Google Scholar 

  • Lancaster T (1990) The econometric analysis of transition data. Cambridge University Press, New York

    MATH  Google Scholar 

  • Lancaster T, Intrator O (1998) Panel data with survival: hospitalization of HIV-positive patients. J Am Stat Assoc 93:46–53

    Article  MATH  Google Scholar 

  • Lillard LA (1993) Simultaneous equations for hazards. J Am Stat Assoc 56:189–217

    Google Scholar 

  • Linderboom M, Van Den Berg G (1994) Heterogeneity in models for bivariate survival: the importance of the mixing distribution. J Stat 56(1):49–60

    Google Scholar 

  • Meyer BD (1990) Unemployment insurance and unemployment spells. Econometrica 58:757–782

    Article  Google Scholar 

  • Pawitan Y, Self S (1993) Modeling disease marker processes in AIDS. J Am Stat Assoc 88:719–726

    Article  MATH  Google Scholar 

  • Ridder G, Verbakel W (1983) On the estimation of the proportional hazard model in the presence of heterogeneity’, A & E report 22/83, Faculty of Actuarial Science and Econometrics. University of Amsterdam, Amsterdam

    Google Scholar 

  • Shih JH, Louis TA (1995) Inferences on the association parameter in copula models for bivariate survival data. Biometrics 51:1384–1399

    Article  MATH  MathSciNet  Google Scholar 

  • Soderberg H, Lyhagen J (1999) Testing for independence in multivariate duration models, Working Paper Series in Economics and Finance, No. 202, Stockholm School of Economics, Stockholm

  • Van Den Berg G, Lindeboom M, Ridder G (1994) Attrition in longitudinal panel data and the empirical analysis of dynamic labour market behaviour. J Appl Econom 9:421–435

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gordana Colby.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Colby, G., Rilstone, P. Simplified estimation of multivariate duration models with unobserved heterogeneity. Computational Statistics 22, 17–29 (2007). https://doi.org/10.1007/s00180-006-0019-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00180-006-0019-7

Keywords

Navigation