Response to updated mortality forecasts in life cycle saving and labor supply |
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| Institution: | 1. Rhode Island Hospital/Alpert Medical School of Brown University, Providence, RI, USA;2. The Miriam Hospital/Alpert Medical School of Brown University, Providence, RI, USA;3. The University of Indiana at Bloomington, Bloomington, ID, USA;4. Hofstra University School of Medicine, Hempstead, NY, USA;1. University of California, San Francisco, Department of Psychiatry, Weill Institute for Neurosciences, United States;2. Zuckerberg San Francisco General Hospital, Division of Infant, Child, and Adolescent Psychiatry, United States;3. Rhode Island Hospital, Department of Psychiatry, United States;4. Alpert Medical School of Brown University, Department of Psychiatry and Human Behavior, United States;5. Northeastern University, Department of Applied Psychology, United States;6. Roger Williams University, Department of Psychology, United States |
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| Abstract: | Historical evidence shows that demographic forecasts, including mortality forecasts, have often been grossly in error. One consequence of this is that forecasts are updated frequently. How should individuals or institutions react to updates, given that these are likewise expected to be uncertain? We discuss this problem in the context of a life cycle saving and labor supply problem, in which a cohort of workers decides how much to work and how much to save for mutual pensions. Mortality is stochastic and point forecasts are updated regularly. A Markovian approximation for the predictive distribution of mortality is derived. This renders the model computationally tractable, and allows us to compare a theoretically optimal rational expectations solution to a strategy in which the cohort merely updates the life cycle plan to match each updated mortality forecast. The implications of the analyses for overlapping generations modeling of pension systems are pointed out. |
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| Keywords: | Life cycle saving Demographics Stochastic mortality |
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