Estimating discount factors for public and private goods and testing competing discounting hypotheses
- 576 Downloads
The observation of declining discount rates in experimental settings has led many to promote hyperbolic discounting over standard exponential discounting as the preferred descriptive model of intertemporal choice. I develop a new framework, consistent with the random utility model, which directly models the intertemporal utility function and produces explicit maximum likelihood estimates of discounting parameters. I apply this estimation method to a stated-preference survey of river basin cleanup options and revealed-preference lottery payment choices. Formal statistical tests fail to find evidence in support of hyperbolic or quasi-hyperbolic discounting. Annual discount rates range from ten to fourteen percent across the data sets and empirical specifications.
KeywordsDiscounting Hyperbolic Random utility Intertemporal choice
JEL ClassificationsD90 Q25 Q53 H43
I thank Nicholas Flores for helpful comments concerning the survey design and data collection, for allowing me to borrow liberally from his MRB description, and for guidance throughout my dissertation process. I thank Randy Walsh for helpful comments at the inception of this research. I thank two anonymous reviewers for multiple insightful comments that greatly enhanced the quality of this paper. Finally, I thank participants at the 2008 AERE Sessions at the Summer Meeting of the AAEA and at the 10th Occasional Workshop on Environmental and Resource Economics at UC Santa Barbara.
- Andreoni, J., & Sprenger, C. (2010a). Estimating time preferences from convex budgets. Working Paper.Google Scholar
- Andreoni, J., & Sprenger, C. (2010b). Risk preferences are not time preferences: discounted expected utility with a disproportionate preference for certainty. Working Paper.Google Scholar
- Bosworth, R., Cameron, T.A., DeShazo, J.R. (2006). Preferences for preventative public health policies with jointly estimated rates of time preference. Working paper.Google Scholar
- Cameron, T.A., & Gerdes, G.R. (2003). Eliciting individual-specific discount rates. Working Paper.Google Scholar
- Clotfelter, C.T., Cook, P.J., Edell, J.A., Moore, M. (1999). State lotteries at the turn of the century: report to the national gambling impact study commission. Available online: http://www3.nd.edu/~jstiver/FIN360/lottery.pdf.
- Coller, M., & Williams, M.B. (1999). Eliciting individual discount rates. Experimental Economics, 2(2), 107–127.Google Scholar
- Herrnstein, R. (1981). Self-control as response strength. In C. M. Bradshaw, E. Szabadi, C. F. Lowe (Eds.), Quantification of steady-state operant behavior (pp. 3–20). New York: Elsevier/North-Holland.Google Scholar
- Mathworks, T. (2006). Matlab.Google Scholar
- Mazur, J.E. (1987). An adjustment procedure for studying delayed reinforcement. In M. L. Commons, J. E. Mazur, J. A. Nevin, H. Rachlin (Eds.), Quantitative analysis of behaviour: the effect of delay and intervening events on reinforcement value. Hillsdale: Erlbaum.Google Scholar
- Minnesota River Basin Data Center (2007). Minnesota river basin data center. Available at http://mrbdc.mnsu.edu/. Accessed 15 Nov 2007.
- United States Census Bureau (2007). American factfinder: 2007 American community survey 3-year estimates.Google Scholar
- University of Houston Center for Public Policy (2007). Demographic survey of Texas lottery players 2007. Available at http://www.uh.edu/hcpp/txlottery.pdf. Accessed 1 Oct 2010.
- University of Houston Center for Public Policy (2008). Demographic survey of Texas lottery players 2008. Available at http://www.uh.edu/hcpp/txlottery2008.pdf. Accessed 1 Oct 2010.