IDEAS home Printed from https://ideas.repec.org/p/bfr/banfra/249.html
   My bibliography  Save this paper

Bayesian estimation of Cox models with non-nested random effects: an application to the ratification of ILO conventions by developing countries

Author

Listed:
  • Bernhard Boockmann.
  • Dragana Djurdjevic.
  • Guillaume Horny.
  • François Laisney.

Abstract

We use a multivariate hazard model to analyse the ratification behaviour of ILO conventions by developing countries. The model accounts for two random effects: one at the country level, the other at the convention level. After investigating identification, we use a semi-parametric Bayesian approach based on the partial likelihood. We find diverging results between Bayesian and frequentist estimates concerning the importance of the two unobserved heterogeneities.

Suggested Citation

  • Bernhard Boockmann. & Dragana Djurdjevic. & Guillaume Horny. & François Laisney., 2009. "Bayesian estimation of Cox models with non-nested random effects: an application to the ratification of ILO conventions by developing countries," Working papers 249, Banque de France.
    • Handle: RePEc:bfr:banfra:249
    as

    Download full text from publisher

    File URL: https://publications.banque-france.fr/sites/default/files/medias/documents/working-paper_249_2009.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Ridder, Geert & Tunali, Insan, 1999. "Stratified partial likelihood estimation," Journal of Econometrics, Elsevier, vol. 92(2), pages 193-232, October.
    3. Samuli Ripatti & Juni Palmgren, 2000. "Estimation of Multivariate Frailty Models Using Penalized Partial Likelihood," Biometrics, The International Biometric Society, vol. 56(4), pages 1016-1022, December.
    4. Germán Rodríguez & Noreen Goldman, 2001. "Improved estimation procedures for multilevel models with binary response: a case‐study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 339-355.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    6. Guillaume Horny, 2009. "Inference in mixed proportional hazard models with K random effects," Statistical Papers, Springer, vol. 50(3), pages 481-499, June.
    7. Lancaster, Tony, 1979. "Econometric Methods for the Duration of Unemployment," Econometrica, Econometric Society, vol. 47(4), pages 939-956, July.
    8. Bolstad W. M & Manda S. O, 2001. "Investigating Child Mortality in Malawi Using Family and Community Random Effects: A Bayesian Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 12-19, March.
    9. Bo E. Honoré, 1993. "Identification Results for Duration Models with Multiple Spells," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(1), pages 241-246.
    10. Kelvin K. W. Yau, 2001. "Multilevel Models for Survival Analysis with Random Effects," Biometrics, The International Biometric Society, vol. 57(1), pages 96-102, March.
    11. Bernhard Boockmann, 2001. "The ratification of ILO conventions: A hazard rate analysis," Economics and Politics, Wiley Blackwell, vol. 13(3), pages 281-309, November.
    12. Chris Elbers & Geert Ridder, 1982. "True and Spurious Duration Dependence: The Identifiability of the Proportional Hazard Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(3), pages 403-409.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guillaume Horny & Rute Mendes & Gerard J. van den Berg, 2012. "Job Durations With Worker- and Firm-Specific Effects: MCMC Estimation With Longitudinal Employer--Employee Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 468-480, March.
    2. Guillaume Horny & Rute Mendes & Gerard J. Van den Berg, 2006. "Job mobility in Portugal: a Bayesian study with matched worker-firm data," Working Papers of BETA 2006-32, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    3. Konstantinos, Pouliakas & Ioannis, Theodossiou, 2010. "An Inquiry Into the Theory, Causes and Consequences of Monitoring Indicators of Health and Safety At Work," MPRA Paper 20336, University Library of Munich, Germany.
    4. Guillaume Horny, 2009. "Inference in mixed proportional hazard models with K random effects," Statistical Papers, Springer, vol. 50(3), pages 481-499, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jaap H. Abbring, 0000. "Mixed Hitting-Time Models," Tinbergen Institute Discussion Papers 07-057/3, Tinbergen Institute, revised 11 Aug 2009.
    2. 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.
    3. Hausman, Jerry A. & Woutersen, Tiemen, 2014. "Estimating a semi-parametric duration model without specifying heterogeneity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 114-131.
    4. Horowitz, Joel L., 2004. "Semiparametric models," Papers 2004,17, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    5. Jaap H. Abbring, 2012. "Mixed Hitting‐Time Models," Econometrica, Econometric Society, vol. 80(2), pages 783-819, March.
    6. Nicoletti, Cheti & Rondinelli, Concetta, 2010. "The (mis)specification of discrete duration models with unobserved heterogeneity: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 159(1), pages 1-13, November.
    7. 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.
    8. 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.
    9. Jaap H. Abbring, 2010. "Identification of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 367-394, September.
    10. Khan, Shakeeb & Tamer, Elie, 2007. "Partial rank estimation of duration models with general forms of censoring," Journal of Econometrics, Elsevier, vol. 136(1), pages 251-280, January.
    11. Guido Imbens & Lisa Lynch, 2006. "Re-employment probabilities over the business cycle," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 5(2), pages 111-134, August.
    12. Horowitz, Joel L. & Lee, Sokbae, 2004. "Semiparametric estimation of a panel data proportional hazards model with fixed effects," Journal of Econometrics, Elsevier, vol. 119(1), pages 155-198, March.
    13. Jaap Abbring & James Heckman, 2008. "Dynamic policy analysis," CeMMAP working papers CWP05/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Bijwaard, Govert, 2011. "Unobserved Heterogeneity in Multiple-Spell Multiple-States Duration Models," IZA Discussion Papers 5748, Institute of Labor Economics (IZA).
    15. Florens, Jean-Pierre & Fougère, Denis & Mouchart, Michel, 2007. "Duration Models and Point Processes," IZA Discussion Papers 2971, Institute of Labor Economics (IZA).
    16. Wienke, Andreas & Kuss, Oliver, 2009. "Random effects Weibull regression model for occupational lifetime," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1249-1250, August.
    17. Wolfgang Hess & Maria Persson, 2012. "The duration of trade revisited," Empirical Economics, Springer, vol. 43(3), pages 1083-1107, December.
    18. Adriaan S. Kalwij, 2004. "Unemployment Experiences of Young Men: on the Road to Stable Employment?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(2), pages 205-237, May.
    19. Govert Bijwaard, 2014. "Multistate event history analysis with frailty," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(58), pages 1591-1620.
    20. Pierre Koning & Dinand Webbink & Nicholas Martin, 2015. "The effect of education on smoking behavior: new evidence from smoking durations of a sample of twins," Empirical Economics, Springer, vol. 48(4), pages 1479-1497, June.

    More about this item

    Keywords

    Gibbs sampling; partial likelihood; frailties; duration analysis.;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • D78 - Microeconomics - - Analysis of Collective Decision-Making - - - Positive Analysis of Policy Formulation and Implementation
    • J80 - Labor and Demographic Economics - - Labor Standards - - - General
    • O19 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - International Linkages to Development; Role of International Organizations

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bfr:banfra:249. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael brassart (email available below). General contact details of provider: https://edirc.repec.org/data/bdfgvfr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.