Arbeitspapier

Optimal retirement choice under age-dependent force of mortality

This paper examines the retirement decision, optimal investment, and consumption strategies under an age-dependent force of mortality. We formulate the optimization problem as a combined stochastic control and optimal stopping problem with a random time horizon, featuring three state variables: wealth, labor income, and force of mortality. To address this problem, we transform it into its dual form, which is a finite time horizon, three-dimensional degenerate optimal stopping problem with interconnected dynamics. We establish the existence of an optimal retirement boundary that splits the state space into continuation and stopping regions. Regularity of the optimal stopping value function is derived and the boundary is proved to be Lipschitz continuous, and it is characterized as the unique solution to a nonlinear integral equation, which we compute numerically. In the original coordinates, the agent thus retires whenever her wealth exceeds an age-, labor income- and mortality-dependent transformed version of the optimal stopping boundary. We also provide numerical illustrations of the optimal strategies, including the sensitivities of the optimal retirement boundary concerning the relevant model's parameters.

Sprache
Englisch

Erschienen in
Series: Center for Mathematical Economics Working Papers ; No. 683

Klassifikation
Wirtschaft
Portfolio Choice; Investment Decisions
Macroeconomics: Consumption; Saving; Wealth
Health Insurance, Public and Private
Thema
Optimal retirement time
Optimal consumption
Optimal portfolio choice
Duality
Optimal stopping
Free boundary
Stochastic control

Ereignis
Geistige Schöpfung
(wer)
Ferrari, Giorgio
Zhu, Shihao
Ereignis
Veröffentlichung
(wer)
Bielefeld University, Center for Mathematical Economics (IMW)
(wo)
Bielefeld
(wann)
2023

Handle
URN
urn:nbn:de:0070-pub-29846217
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Ferrari, Giorgio
  • Zhu, Shihao
  • Bielefeld University, Center for Mathematical Economics (IMW)

Entstanden

  • 2023

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