IDEAS home Printed from https://ideas.repec.org/p/crs/wpaper/2002-23.html
   My bibliography  Save this paper

Bayesian Inference for the Mover-Stayer Model in Continuous Time with an Application to Labour Market Transition Data

Author

Listed:
  • Denis Fougère

    (Crest)

  • Thierry Kamionka

    (Crest)

Abstract

This paper presents Bayesian inference procedures for the continuous time mover-stayer model applied to labour market transition data collected in discrete time. These methods allow us to derive the probability of embeddability of the discrete-time modelling with the continuous-time one. A special emphasis is put on two alternative procedures, namely the importance sampling algorithm and a new Gibbs sampling algorithm. Transition intensities, proportions of stayers and functions of these parameters are then estimated with the Gibbs sampling algorithm for individual transition data coming from the French Labour Force Surveys collected over the period 1986-2000. Copyright © 2003 John Wiley & Sons, Ltd.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Denis Fougère & Thierry Kamionka, 2002. "Bayesian Inference for the Mover-Stayer Model in Continuous Time with an Application to Labour Market Transition Data," Working Papers 2002-23, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2002-23
    as

    Download full text from publisher

    File URL: http://crest.science/RePEc/wpstorage/2002-23.pdf
    File Function: Crest working paper version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521471626.
    3. Neumark, David & Polsky, Daniel & Hansen, Daniel, 1999. "Has Job Stability Declined Yet? New Evidence for the 1990s," Journal of Labor Economics, University of Chicago Press, vol. 17(4), pages 29-64, October.
    4. Kiefer, Nicholas M, 1978. "Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model," Econometrica, Econometric Society, vol. 46(2), pages 427-434, March.
    5. Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
    6. Burton Singer & Seymour Spilerman, 1976. "Some Methodological Issues in the Analysis of Longitudinal Surveys," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 447-474, National Bureau of Economic Research, Inc.
    7. Denis Fougère & Thierry Kamionka, 1992. "Un modéle markovien du marché du travail," Annals of Economics and Statistics, GENES, issue 27, pages 149-188.
    8. Robert E. McCulloch & Ruey S. Tsay, 1994. "Statistical Analysis Of Economic Time Series Via Markov Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(5), pages 523-539, September.
    9. Van Dijk, Herman K. & Kloek, Teun & Boender, C. Guus E., 1985. "Posterior moments computed by mixed integration," Journal of Econometrics, Elsevier, vol. 29(1-2), pages 3-18.
    10. John Geweke & Robert C. Marshall & Gary A. Zarkin, 1986. "Exact Inference for Continuous Time Markov Chain Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 653-669.
    11. van Dijk, H. K. & Kloek, T., 1980. "Further experience in Bayesian analysis using Monte Carlo integration," Journal of Econometrics, Elsevier, vol. 14(3), pages 307-328, December.
    12. Thierry Kamionka, 1998. "Simulated maximum likelihood estimation in transition models," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 129-153.
    13. Denis Fougère & Thierry Kamionka, 1992. "Mobilité et précarisation sur le marché français du travail : une analyse longitudinale pour les années 1986 à 1988," Économie et Prévision, Programme National Persée, vol. 102(1), pages 157-178.
    14. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models 2 volume set," Cambridge Books, Cambridge University Press, number 9780521478373, July.
    15. John Geweke, 1991. "Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments," Staff Report 148, Federal Reserve Bank of Minneapolis.
    16. Gottschalk, Peter & Moffitt, Robert, 1999. "Changes in Job Instability and Insecurity Using Monthly Survey Data," Journal of Labor Economics, University of Chicago Press, vol. 17(4), pages 91-126, October.
    17. Heckman, James J. & Singer, Burton, 1984. "Econometric duration analysis," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 63-132.
    18. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
    19. repec:adr:anecst:y:1992:i:27:p:06 is not listed on IDEAS
    20. Geweke, John & Marshall, Robert C & Zarkin, Gary A, 1986. "Mobility Indices in Continuous Time Markov Chains," Econometrica, Econometric Society, vol. 54(6), pages 1407-1423, November.
    21. Light, Audrey & Ureta, Manuelita, 1992. "Panel Estimates of Male and Female Job Turnover Behavior: Can Female Nonquitters Be Identified?," Journal of Labor Economics, University of Chicago Press, vol. 10(2), pages 156-181, April.
    22. Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99.
    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. Moshe Buchinsky & Denis Fougère & Francis Kramarz & Rusty Tchernis, 2002. "Interfirm Mobility, Wages and the Returns to Seniority and Experience in the U.S," Working Papers 2002-29, Center for Research in Economics and Statistics.
    2. Bosch, Mariano & Maloney, William, 2008. "Cyclical movements in unemployment and informality in developing countries," Policy Research Working Paper Series 4648, The World Bank.
    3. Thierry Kamionka & Cyriaque Edon, 2007. "Modélisation dynamique de la participation au marché du travail des femmes en couple," Annals of Economics and Statistics, GENES, issue 86, pages 77-108.
    4. Thierry Kamionka & Xavier VU NGOC, 2015. "Trajectoire des jeunes sur le marché du travail, quartier d’origine et diplôme : une modélisation dynamique," Working Papers 2015-01, Center for Research in Economics and Statistics.
    5. Legrand D. F. Saint-Cyr & Laurent Piet, 2017. "Movers and stayers in the farming sector: accounting for unobserved heterogeneity in structural change," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 777-795, August.
    6. Laurent, Piet & Legrand D.F. Saint-Cyr, 2016. "Projection de la population des exploitations agricoles françaises à l’horizon 2025," Working Papers SMART 16-11, INRAE UMR SMART.
    7. Saint-Cyr, Legrand D. F. & Piet, Laurent, 2014. "Movers and Stayers in the Farming Sector: Another Look at Heterogeneity in Structural Change," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 183068, European Association of Agricultural Economists.
    8. Michael K. Ng & Yuho Chung, 2012. "Double Mover–Stayer model on customer switching in telecommunications industry," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(8), pages 663-674, December.
    9. Saint-Cyr, Legrand D. F., 2016. "Accounting for farm heterogeneity in the assessment of agricultural policy impacts on structural change," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235778, Agricultural and Applied Economics Association.

    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. HOOGERHEIDE, Lennart F. & VAN DIJK, Herman K. & VAN OEST, Rutger D., 2007. "Simulation based Bayesian econometric inference: principles and some recent computational advances," LIDAM Discussion Papers CORE 2007015, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    3. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(3), pages 409-431, August.
    4. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    5. Vijverberg, Wim P. M., 1997. "Monte Carlo evaluation of multivariate normal probabilities," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 281-307.
    6. Ardia, David & Hoogerheide, Lennart F., 2010. "Efficient Bayesian estimation and combination of GARCH-type models," MPRA Paper 22919, University Library of Munich, Germany.
    7. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    8. VAN DIJK, Herman K., 1987. "Some advances in Bayesian estimations methods using Monte Carlo Integration," LIDAM Reprints CORE 783, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
    10. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.
    11. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    12. Heckelei, Thomas & Mittelhammer, Ronald C., 1996. "Bayesian Bootstrap Analysis of Systems of Equations," Discussion Papers 18786, University of Bonn, Institute for Food and Resource Economics.
    13. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 557-587.
    14. Gordon, Stephen & Bélanger, Gilles, 1996. "Échantillonnage de Gibbs et autres applications économétriques des chaînes markoviennes," L'Actualité Economique, Société Canadienne de Science Economique, vol. 72(1), pages 27-49, mars.
    15. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2003. "Neural network approximations to posterior densities: an analytical approach," Econometric Institute Research Papers EI 2003-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. John Geweke, 1991. "Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments," Staff Report 148, Federal Reserve Bank of Minneapolis.
    17. Hoogerheide, Lennart & van Dijk, Herman K., 2010. "Bayesian forecasting of Value at Risk and Expected Shortfall using adaptive importance sampling," International Journal of Forecasting, Elsevier, vol. 26(2), pages 231-247, April.
    18. Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2011. "A Class of Adaptive EM-based Importance Sampling Algorithms for Efficient and Robust Posterior and Predictive Simulation," Tinbergen Institute Discussion Papers 11-004/4, Tinbergen Institute.
    19. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
    20. Heckelei, Thomas & Mittelhammer, Ron C., 2003. "Bayesian bootstrap multivariate regression," Journal of Econometrics, Elsevier, vol. 112(2), pages 241-264, February.

    More about this item

    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:crs:wpaper:2002-23. 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: Secretariat General (email available below). General contact details of provider: https://edirc.repec.org/data/crestfr.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.