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Markovian networks in labour markets

Author

Listed:
  • A Rodrigo

    (Universidad Complutense de Madrid)

  • M Vazquez

    (Universidad Complutense de Madrid)

  • C Carrera

    (Universidad Complutense de Madrid)

Abstract

In labour theory, equilibrium is described in terms of mean variables, which is limited and can be misleading. In this article, we model the labour market as a closed Markovian network and find the steady state distribution of unemployment and advertised vacancies. We determine the stochastic equilibrium distribution for two different types of matching functions and allow for both unemployed and on the job search. In general cases, where probabilities cannot be analytically computed, we find restrictions that must hold for all matching processes. Our modelling is applicable to most economic markets with frictions.

Suggested Citation

  • A Rodrigo & M Vazquez & C Carrera, 2006. "Markovian networks in labour markets," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 526-531, May.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:5:d:10.1057_palgrave.jors.2602015
    DOI: 10.1057/palgrave.jors.2602015
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    References listed on IDEAS

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    1. Christopher A. Pissarides & Barbara Petrongolo, 2001. "Looking into the Black Box: A Survey of the Matching Function," Journal of Economic Literature, American Economic Association, vol. 39(2), pages 390-431, June.
    2. Christopher A. Pissarides, 1994. "Search Unemployment with On-the-job Search," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(3), pages 457-475.
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    5. Artalejo, J. R., 2000. "G-networks: A versatile approach for work removal in queueing networks," European Journal of Operational Research, Elsevier, vol. 126(2), pages 233-249, October.
    6. Andolfatto, David, 1996. "Business Cycles and Labor-Market Search," American Economic Review, American Economic Association, vol. 86(1), pages 112-132, March.
    Full references (including those not matched with items on IDEAS)

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