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.
Data Availability
The data analyzed in this study is publicly available at the following link: https://www.bls.gov/nls/nlsy79.htm
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Bavaro, M., Tullio, F. Intergenerational mobility measurement with latent transition matrices. J Econ Inequal 21, 25–45 (2023). https://doi.org/10.1007/s10888-022-09554-6
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DOI: https://doi.org/10.1007/s10888-022-09554-6
Keywords
- Expectation-Maximization algorithm
- Intergenerational mobility
- Transition matrix