Partial Identification of the Effect of Retirement on Mental Health with Panel Data.

We study how retirement affects mental health using a partial identification framework for panel data. With this framework, we estimate identification regions that are transformed into quantitative policy recommendations by adopting a minimax-regret decision rule. Under relatively weak assumptions, we find that retirement can have a moderate, positive effect on individuals whose pre-retirement mental health is below average of the corresponding age cohort. Our minimax-regret analysis further suggests that while retirement can be delayed without affecting the mental health of most of the population, it is advisable to facilitate the retirement of people with poor mental health.