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Intergenerational mobility measurement with latent transition matrices

Author

Listed:
  • Michele Bavaro

    (University of Oxford, INET and Department of Social Policy and Intervention)

  • Federico Tullio

    (Bank of Italy)

Abstract

We propose a multivariate approach for the estimation of intergenerational transition matrices. Our methodology is grounded on the assumption that individuals’ social status is unobservable and must be estimated. In this framework, parents and offspring are clustered on the basis of the observed levels of income and occupational categories, thus avoiding any discretionary rule in the definition of class boundaries. The resulting transition matrix is a function of the posterior probabilities of parents and young adults of belonging to each class. Estimation is carried out via maximum likelihood by means of an expectation-maximization algorithm. We illustrate the proposed method using National Longitudinal Survey Data from the United States in the period 1978-2006.

Suggested Citation

  • Michele Bavaro & Federico Tullio, 2023. "Intergenerational mobility measurement with latent transition matrices," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 21(1), pages 25-45, March.
  • Handle: RePEc:spr:joecin:v:21:y:2023:i:1:d:10.1007_s10888-022-09554-6
    DOI: 10.1007/s10888-022-09554-6
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