IDEAS home Printed from https://ideas.repec.org/p/zbw/zewdip/3180.html
   My bibliography  Save this paper

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

Author

Listed:
  • Horney, Guillaume
  • Boockmann, Bernhard
  • Djurdjevic, Dragana
  • Laisney, François

Abstract

We use a multivariate hazard model for the analysis of data on the timing of ratifications of different conventions. The model accounts for two random effects, one at the country level and the other at the convention level. We use a semi-parametric Bayesian approach, based on the partial likelihood. Our findings confirm the results of preceding studies that ratification behaviour varies substantially across members states and conventions. Furthermore, the results yield insights on the impact of unobserved heterogeneity on the ratification process.

Suggested Citation

  • Horney, Guillaume & Boockmann, Bernhard & Djurdjevic, Dragana & Laisney, François, 2005. "Bayesian estimation of Cox model with non-nested random effects: an application to the ratification of ILO conventions by developing countries," ZEW Discussion Papers 05-23, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:3180
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/24116/1/dp0523.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Ridder, Geert & Tunali, Insan, 1999. "Stratified partial likelihood estimation," Journal of Econometrics, Elsevier, vol. 92(2), pages 193-232, October.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, November.
    4. Guillaume Horny, 2009. "Inference in mixed proportional hazard models with K random effects," Statistical Papers, Springer, vol. 50(3), pages 481-499, June.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Bernhard Boockmann, 2001. "The ratification of ILO conventions: A hazard rate analysis," Economics and Politics, Wiley Blackwell, vol. 13(3), pages 281-309, November.
    10. 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.
    11. Lancaster, Tony, 1979. "Econometric Methods for the Duration of Unemployment," Econometrica, Econometric Society, vol. 47(4), pages 939-956, July.
    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, 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.
    2. Pouliakas, Konstantinos & Theodossiou, Ioannis, 2010. "An Inquiry Into The Theory, Causes And Consequences Of Monitoring Indicators Of Health And Safety At Work," SIRE Discussion Papers 2010-120, Scottish Institute for Research in Economics (SIRE).
    3. Guillaume Horny, 2009. "Inference in mixed proportional hazard models with K random effects," Statistical Papers, Springer, vol. 50(3), pages 481-499, June.
    4. 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.

    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. 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. Jaap H. Abbring, 2012. "Mixed Hitting‐Time Models," Econometrica, Econometric Society, vol. 80(2), pages 783-819, March.
    3. Jaap H. Abbring, 2010. "Identification of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 367-394, September.
    4. Horowitz, Joel L., 2004. "Semiparametric models," Papers 2004,17, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    5. 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.
    6. Jaap H. Abbring, 0000. "Mixed Hitting-Time Models," Tinbergen Institute Discussion Papers 07-057/3, Tinbergen Institute, revised 11 Aug 2009.
    7. 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.
    8. 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.
    9. 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.
    10. Govert Ewout Bijwaard, 2014. "Multistate event history analysis with frailty," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(58), pages 1591-1620.
    11. 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.
    12. Jaap H. Abbring & Gerard J. Van Den Berg, 2007. "The unobserved heterogeneity distribution in duration analysis," Biometrika, Biometrika Trust, vol. 94(1), pages 87-99.
    13. Bijwaard, Govert, 2011. "Unobserved Heterogeneity in Multiple-Spell Multiple-States Duration Models," IZA Discussion Papers 5748, Institute of Labor Economics (IZA).
    14. Abbring, Jaap H. & Berg, Gerard J. van den, 2000. "The non-parametric identification of the mixed proportional hazards competing risks model," Serie Research Memoranda 0024, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    15. 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.
    16. Hess, Wolfgang & Persson, Maria, 2009. "Survival and Death in International Trade - Discrete-Time Durations of EU Imports," Working Papers 2009:12, Lund University, Department of Economics.
    17. Frijters, Paul & de New, John & Shields, Michael A., 2005. "Socio-Economic Status, Health Shocks, Life Satisfaction and Mortality: Evidence from an Increasing Mixed Proportional Hazard Model," IZA Discussion Papers 1488, Institute of Labor Economics (IZA).
    18. Picchio, Matteo, 2012. "Lagged duration dependence in mixed proportional hazard models," Economics Letters, Elsevier, vol. 115(1), pages 108-110.
    19. Horny, Guillaume & Picchio, Matteo, 2010. "Identification of lagged duration dependence in multiple-spell competing risks models," Economics Letters, Elsevier, vol. 106(3), pages 241-243, March.
    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:

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

    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:zbw:zewdip:3180. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zemande.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.