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Point Processes

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Part of the book series: Advanced Studies in Theoretical and Applied Econometrics ((ASTA,volume 33))

Abstract

Point processes are a mathematical formalisation which allows one to describe individual mobilities or transitions between a finite number of states through time. They are particularly useful for the micro-econometric analysis of labour market dynamics. Labour statistics are often concerned with samples of workers’ histories from which the econometrician can retrospectively observe individual transitions between distinct participation states: employment in a stable job (i.e., with an unlimited duration labour contract), employment in an unstable job (i.e., with a limited duration contract), unemployment (with or without eligibility to unemployment insurance systems), education, training, out—of—labour force, etc.1

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References

  • Aalen, O. [1978]: Non-parametric inference for a family of counting processes, Annals of Statistics, 6, 701 – 726.

    Article  Google Scholar 

  • Aalen, O. [1987]: Mixing distributions on a Markov chain, Scandinavian Journal of Statistics, 14, 281 – 289.

    Google Scholar 

  • Andersen, P.K. [1991]: Survival analysis; 1982–1991: the second decade of the proportional hazards regression model, Research Report 91/1, Statistical Research Unit, University of Copenhagen.

    Google Scholar 

  • Andersen, P.K. and O. Borgan [1985]: Counting process models for life history data: a review (with discussion), Scandinavian Journal of Statistics, 12, 97 – 158.

    Google Scholar 

  • Andersen, P.K. and R. Gill [1982]: Cox’s regression model for counting processes: a large sample study, Annals of Statistics, 10, 1100 – 1120.

    Article  Google Scholar 

  • Basawa, I.V. and B.L.S. Prakasa Rao [1980]: Statistical inference of stochastic processes. New-York: Academic Press.

    Google Scholar 

  • Bhattacharya, R.N. and E.C. Waymire [1990]: Stochastic processes with applications. New-York: Wiley and Sons.

    Google Scholar 

  • Billingsley, P. [1961]: Statistical inference for Markov processes. The University of Chicago Press.

    Google Scholar 

  • Chung, K.L. [1967]: Markov chains with stationary transition probabilities. New-York: Springer-Verlag.

    Google Scholar 

  • Courgeau, D. and E. Lelievre [1989]: Analyse démographique des biographies. Paris: Editions de l’INED.

    Google Scholar 

  • Cox, D.R. [1972]: Regression models and life tables (with discussion), Journal of the Royal Statistical Society, B, 34, 187 – 220.

    Google Scholar 

  • Cox, D.R. [1975]: Partial likelihood, Biometrika, 62, 269 – 276.

    Article  Google Scholar 

  • Cox, D.R. and V. Isham [1980]: Point processes. London: Chapman and Hall.

    Google Scholar 

  • Cox, D.R. and P.A.W. Lewis [1966]: The statistical analysis of series of events. London: Chapman and Hall.

    Google Scholar 

  • Cox, D.R. and H.D. Miller [1966]: The theory of stochastic processes. London: Methuen.

    Google Scholar 

  • Daley, D.J. and D. Vere-Jones [1988]: An introduction to the theory of point processes. New-York: Springer-Verlag.

    Google Scholar 

  • Dellacherie, C. and P.A. Meyer [1980]: Probabilité et potentiel (Chapitres V à VIII: Théorie des martingales). Paris: Hermann.

    Google Scholar 

  • Doob, J.L. [1953]: Stochastic processes. New-York: Wiley and Sons.

    Google Scholar 

  • Ethier, S.N. and T.G. Kurtz [1986]: Markov processes: characterization and convergence. New-York: Wiley and Sons.

    Google Scholar 

  • Flinn, C. and J.J. Heckman [1983]: Are unemployment and out of the labour force behaviorally distinct labour force states?, Journal of Labour Economics, 1, 28 – 42.

    Article  Google Scholar 

  • Florens, J.P. and D. Fougère [1991]: Non-causality in continuous-time: application to counting processes, Working Paper 91-b, GREMAQ, Université des Sciences Sociales, Toulouse.

    Google Scholar 

  • Freedman, D. [1971]: Markov chains. San Francisco: Holden-Day.

    Google Scholar 

  • Gill, R.D. [1980]: Non-parametric estimation based on censored observations of a Markov renewal process, Zeitschrift fir Wahrscheinlichkeitstheorie und Verwandte Gebiete, 53, 97–116.

    Google Scholar 

  • Jacobsen, M. [1982]: Statistical analysis of counting processes. Berlin: Springer-Verlag.

    Google Scholar 

  • Karr, A.F. [1986]: Point processes and their statistical inference. New-York: Marcel Dekker.

    Google Scholar 

  • Revuz, D. [1975]: Markov chains. New-York: North Holland/American Elsevier.

    Google Scholar 

  • Ross, S. [1989]: Introduction to probability models, 4-th edition, San Diego: Academic Press.

    Google Scholar 

  • Rubino, G. and B. Sericola [1989]: Sojourn times in finite Markov processes, Journal of Applied Probability, 27, 744 – 756.

    Article  Google Scholar 

  • Schweder, T. [1970]: Composable Markov processes, Journal of Applied Probability, 7, 400 – 410.

    Article  Google Scholar 

  • Serfozo, R.F. [1990]: Point processes, in D.P. Heyman and M.J. Sobel (eds): Handbooks in operations research and management science, Vol. 2, 1 – 94, Amsterdam: North-Holland.

    Google Scholar 

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© 1996 Kluwer Academic Publishers

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Florens, JP., Fougère, D. (1996). Point Processes. In: Mátyás, L., Sevestre, P. (eds) The Econometrics of Panel Data. Advanced Studies in Theoretical and Applied Econometrics, vol 33. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0137-7_20

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  • DOI: https://doi.org/10.1007/978-94-009-0137-7_20

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-0-7923-3787-4

  • Online ISBN: 978-94-009-0137-7

  • eBook Packages: Springer Book Archive

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