Optimal annuity demand for general expected utility agents

We study the robustness of the results of Milevsky and Huang (2018) on the optimal demand for annuities to the choice of the utility function. To do so, we first propose a new way to span the set of all increasing concave utility functions by exploiting a one-to-one correspondence with the set of pr...

Full description

Saved in:
Bibliographic Details
Published in:Insurance, mathematics & economics mathematics & economics, 2021-11, Vol.101, p.70-79
Main Authors: Bernard, Carole, De Gennaro Aquino, Luca, Levante, Lucia
Format: Article
Language:English
Subjects:
Annuities
Annuity equivalent wealth
Annuity puzzle
Demand
Distribution functions
Expected utility
Expected utility theory
Life-cycle model
Longevity risk pooling
Mathematical functions
Numerical analysis
Numerical methods
Probability distribution functions
Robustness
Robustness (mathematics)
Utility functions
Wealth
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We study the robustness of the results of Milevsky and Huang (2018) on the optimal demand for annuities to the choice of the utility function. To do so, we first propose a new way to span the set of all increasing concave utility functions by exploiting a one-to-one correspondence with the set of probability distribution functions. For example, this approach makes it possible to present a five-parameter family of concave utility functions that encompasses a number of standard concave utility functions, e.g., CRRA, CARA and HARA. Second, we develop a novel numerical method to handle the life-cycle model of Yaari (1965) and the annuity equivalent wealth problem for a general utility function. We show that the results of Milevsky and Huang (2018) on the optimal demand for annuities proved in the case of a CRRA and logarithmic utility maximizer hold more generally.
ISSN:0167-6687
1873-5959
DOI:10.1016/j.insmatheco.2020.07.004