Estimating Discount Functions with Consumption Choices Over the Lifecycle

50 Pages Posted: 24 Aug 2007 Last revised: 19 Nov 2021

See all articles by David Laibson

David Laibson

Harvard University - Department of Economics; National Bureau of Economic Research (NBER)

Andrea Repetto

University of Chile - Engineering Department

Jeremy Tobacman

Alfred Lerner College of Business and Economics, University of Delaware

Date Written: August 2007

Abstract

Intertemporal preferences are difficult to measure. We estimate time preferences using a structural buffer stock consumption model and the Method of Simulated Moments. The model includes stochastic labor income, liquidity constraints, child and adult dependents, liquid and illiquid assets, revolving credit, retirement, and discount functions that allow short-run and long-run discount rates to differ. Data on retirement wealth accumulation, credit card borrowing, and consumption-income comovement identify the model. Our benchmark estimates imply a 40% short-term annualized discount rate and a 4.3% long-term annualized discount rate. Almost all specifications reject the restriction to a constant discount rate. Our quantitative results are sensitive to assumptions about the return on illiquid assets and the coefficient of relative risk aversion. When we jointly estimate the coefficient of relative risk aversion and the discount function, the short-term discount rate is 15% and the long-term discount rate is 3.8%.

Suggested Citation

Laibson, David I. and Repetto, Andrea and Tobacman, Jeremy, Estimating Discount Functions with Consumption Choices Over the Lifecycle (August 2007). Available at SSRN: https://ssrn.com/abstract=1008808

David I. Laibson (Contact Author)

Harvard University - Department of Economics ( email )

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National Bureau of Economic Research (NBER) ( email )

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Andrea Repetto

University of Chile - Engineering Department ( email )

Republica 701 Santiago
Chile

Jeremy Tobacman

Alfred Lerner College of Business and Economics, University of Delaware ( email )

Newark, DE 19716
United States

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