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Risk Management of Pension Fund: A Model for Salary Evolution

Author

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  • Guglielmo D'Amico

    (Department of Pharmacy, University of G. D’Annunzio Chieti, 66100 Chieti, Italy
    These authors contributed equally to this work.)

  • Ada Lika

    (Department of Business, University of Cagliari, 09123, Cagliari, Italy
    These authors contributed equally to this work.)

  • Filippo Petroni

    (Department of Management, Marche Polytechnic University, 60121 Ancona, Italy
    These authors contributed equally to this work.)

Abstract

In this paper, we propose a semi-Markov chain to model the salary levels of participants in a pension scheme. The aim of the models is to understand the evolution in time of the salary of active workers in order to implement it in the construction of the actuarial technical balance sheet. It is worth mentioning that the level of the contributions in a pension scheme is directly proportional to the incomes of the active workers; in almost all cases, it is a percentage of the worker’s incomes. As a consequence, an adequate modeling of the salary evolution is essential for the determination of the contributions paid to the fund and thus for the determination of the fund’s sustainability, especially currently, when all jobs and salaries are subject to changes due to digitalization, ICT, innovation, etc. The model is applied to a large dataset of a real compulsory Italian pension scheme of the first pillar. The semi-Markovian hypothesis is tested, and the advantages with respect to Markov chain models are assessed.

Suggested Citation

  • Guglielmo D'Amico & Ada Lika & Filippo Petroni, 2019. "Risk Management of Pension Fund: A Model for Salary Evolution," IJFS, MDPI, vol. 7(3), pages 1-17, August.
    • Handle: RePEc:gam:jijfss:v:7:y:2019:i:3:p:44-:d:259293
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    References listed on IDEAS

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    1. Samis Trevezas & Nikolaos Limnios, 2011. "Exact MLE and asymptotic properties for nonparametric semi-Markov models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 719-739.
    2. Guglielmo D’Amico & Jacques Janssen & Raimondo Manca, 2010. "Initial and Final Backward and Forward Discrete Time Non-homogeneous Semi-Markov Credit Risk Models," Methodology and Computing in Applied Probability, Springer, vol. 12(2), pages 215-225, June.
    3. D'Amico, Guglielmo & Guillen, Montserrat & Manca, Raimondo, 2009. "Full backward non-homogeneous semi-Markov processes for disability insurance models: A Catalunya real data application," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 173-179, October.
    4. Fredrik Stenberg & Raimondo Manca & Dmitrii Silvestrov, 2007. "An Algorithmic Approach to Discrete Time Non-homogeneous Backward Semi-Markov Reward Processes with an Application to Disability Insurance," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 497-519, December.
    5. Wang, Suxin & Lu, Yi & Sanders, Barbara, 2018. "Optimal investment strategies and intergenerational risk sharing for target benefit pension plans," Insurance: Mathematics and Economics, Elsevier, vol. 80(C), pages 1-14.
    6. Aleka A. Papadopoulou & George Tsaklidis & Sally McClean & Lalit Garg, 2012. "On the Moments and the Distribution of the Cost of a Semi Markov Model for Healthcare Systems," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 717-737, September.
    7. Guglielmo D’Amico & Filippo Petroni & Flavio Prattico, 2015. "Performance Analysis of Second Order Semi-Markov Chains: An Application to Wind Energy Production," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 781-794, September.
    8. Aleka Papadopoulou & George Tsaklidis, 2007. "Some Reward Paths in Semi-Markov Models with Stochastic Selection of the Transition Probabilities," Methodology and Computing in Applied Probability, Springer, vol. 9(3), pages 399-411, September.
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    Cited by:

    1. P.-C.G. Vassiliou, 2020. "Non-Homogeneous Semi-Markov and Markov Renewal Processes and Change of Measure in Credit Risk," Mathematics, MDPI, vol. 9(1), pages 1-27, December.

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