NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Option Value of Work, Health Status, and Retirement Decisions in Japan: Evidence from the Japanese Study on Aging and Retirement (JSTAR)

Satoshi Shimizutani, Mayu Fujii, Takashi Oshio


This chapter is a preliminary draft unless otherwise noted. It may not have been subjected to the formal review process of the NBER. This page will be updated as the chapter is revised.

Chapter in forthcoming NBER book Social Security Programs and Retirement Around the World: Disability Insurance Programs and Retirement, David A. Wise, editor
Conference held September 26-28, 2013
Forthcoming from University of Chicago Press
in NBER Book Series - International Social Security

This study examines the factors that affect the retirement decisions of the middle-aged and elderly in Japan, focusing especially on their earnings, public pension benefits, and health status. Using two-year panel data from the JSTAR and applying the option value (OV) model proposed by Stock and Wise (1990a, 1990b), we found that the probability of retirement has a negative and significant correlation with the OV of work, and that correlation does not depend on the health status. Our counterfactual simulation based on the OV model shows that if the probability of being enrolled in the disability program were zero, the average years of work when individuals are in their 50s and 60s would increase. However, it should be emphasized that in Japan, where being enrolled in the disability program is unlikely to make one a candidate for the retirement path, the result of this simulation does not indicate that satisfying the eligibility criteria for disability pension receipts will more stringently increase the labor supplied by the middle-aged and elderly.

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This paper was revised on April 10, 2014

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This chapter first appeared as NBER working paper w20001, Option Value of Work, Health Status, and Retirement Decisions in Japan: Evidence from the Japanese Study on Aging and Retirement (JSTAR), Satoshi Shimizutani, Takashi Oshio, Mayu Fujii
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