Optimal DB-PAYGO pension management towards a habitual contribution rate

Lin He, Zongxia Liang and Fengyi Yuan

Insurance: Mathematics and Economics, 2020, vol. 94, issue C, 125-141

Abstract: In this paper, we propose a new objective function, which reflects the costs of unstable contribution risk and discontinuity risk in DB-PAYGO pension system. The problem is to minimize the quadratic deviation between the actual contribution rate and a habitual target and the quadratic proportional deviation of the pension accumulation. A modified non-negative constraint of the contribution rate is added, which together with a stochastic habitual target process, causes difficulty in solving the minimization problem by Lagrange dual method. The results are split into two cases which depend on the habit-adjusted adequacy of the pension budget. In the inadequate case, the optimal contribution rate reveals a hump shape curve with respect to time, which is different from the exponential growth curve of the model with a fixed target. By moderately raising the contribution rate in the initial phase, it helps to increase the accumulation and reduce the contribution burden of the follow-up policyholders. Notably, the hump shape curve is a more practical policy, because of that the exponential growth curve raises anxiety about the unlimited growth of the contribution rate and harms the confidence in the sustainability of the pension fund. We also study the impacts of the certain trend in demography, and the uncertain fluctuations in salary and investment on the optimal control policies.

Keywords: DB-PAYGO pension management; Unstable contribution risk; Discontinuity risk; Habitual target; Lagrange dual method (search for similar items in EconPapers)
JEL-codes: G11 G22 I14 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:94:y:2020:i:c:p:125-141

DOI: 10.1016/j.insmatheco.2020.07.005

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