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A Stochastic Markov Chain for Estimating New Entrants into Professional Pension Funds

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  • Alessandro Fiori Maccioni

    (Department of Economic and Business Sciences, University of Cagliari, Via Sant’Ignazio 74, 09123 Cagliari, Italy)

Abstract

This paper presents a stochastic Markov chain model for estimating new entrants into professional orders and their related pension funds. The model considers the interactions between demographic, socio-economic and regulatory variables. The intuition behind it is that, in the medium term, trends in academic education can anticipate changes in the job market and preferences for highly skilled professions. Similarly, in the long term, fertility trends can anticipate the number of future young adults, thus influencing the overall occupational structure of employment. The model has been formalized mathematically and successfully validated by backtesting over historical data. The model’s predictions have been compared with the observed data of new entrants into the Italian order of chartered accountants (CNDCEC) between 2012 and 2021. The related professional pension fund (CNPADC) has also been analyzed under the additional assumption of stochastic returns with an evaluation of the impact of future new chartered accountants on its demographic and financial evolution between 2020 and 2070.

Suggested Citation

  • Alessandro Fiori Maccioni, 2023. "A Stochastic Markov Chain for Estimating New Entrants into Professional Pension Funds," JRFM, MDPI, vol. 16(5), pages 1-26, May.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:5:p:276-:d:1149225
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    References listed on IDEAS

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