Investigating the Effect of Saving Experience on Individuals’ Time Preferences

اقتصاد پولی مالی

Article 3, Volume 24, Issue 13, April 2017, Pages 69-89   

Document Type: پژوهشی

DOI: 10.22067/pm.v24i14.61013

Authors

parvin tashakori saleh^{* 1}; mahdi khoda parast mashhadi²; mahdi feizi²

¹ferdowsi mashhad

²ferdowsi

Abstract

Introduction
Estimating time preferences is of great importance to economists, and policy makers who seek to understand the process of consumers’ decision-making about savings, education, life insurance and so on. The standard model of intertemporal choice in economics is time-separable utility with exponential discounting. However, people often seem to deviate systematically from these implications of the exponential discounting model. Empirical and experimental studies show that time preferences for long runs are smaller than for short runs. In other words, people are present bias. Hence, the saving level becomes less than its optimal level. Because people procrastinate and postpone saving to the future period. Cognitive science investigates evolution of cognitive systems. These systems have the capacity of adaptation and coevolution. We elicit individual time preferences with incentivized choice experiments, and match resulting time preference measures to individual’s experiences.
Theoretical Framework
A convenient functional form for representing such time preferences that value declines rapidly over the short run but at a slower rate over the long run is the quasi hyperbolic discount function (Laibson, 1997) according to which the present value of a stream of consumptions (c1, c2, …) is as follows:
Where u is the utility function, and discount parameters β and δ are bounded between 0 and 1. Hyperbolic discounting is a particular mathematical model devised as an improvement over exponential discounting in the sense that it better fits the experimental data about actual behavior. But note the time inconsistency of this behavior has some quite perverse consequences. Hyperbolic discounting has been observed in humans and animals.
In hyperbolic discounting, valuations fall very rapidly for small delay periods, but then fall slowly for longer delay periods. This contrasts with exponential discounting, in which evaluation falls by a constant factor per unit delay, regardless of the total length of the delay. The standard experiment used to reveal a test subject's hyperbolic discounting curve is to compare short-term preferences with long-term preferences. For instance: "Would you prefer a dollar today or three dollars tomorrow?" or "Would you prefer a dollar in one year or three dollars in one year and one day?" For certain range of offerings, a significant fraction of subjects will take the lesser amount today, but will gladly wait one extra day in a year in order to receive the higher amount instead. Individuals with such preferences are described as "present-biased".
Individuals using hyperbolic discounting reveal a strong tendency to make choices that are inconsistent over time. This dynamic inconsistency happens because the value of future rewards is much lower under hyperbolic discounting than under exponential discounting. The degree of discounting is vitally important in describing hyperbolic discounting, especially in the discounting of specific rewards such as money. The discounting of monetary rewards varies across age groups due to the varying discount rate. The rate depends on a variety of factors including the species being observed, age, experience, and the amount of time needed to consume the reward.
Methodology
Time preferences are fundamental to theoretical and applied studies of decision-making, and are a critical element of much of economic analysis. At both aggregate and individual levels, accurate measures of discounting parameters can provide helpful guidance on the potential impacts of policy and provide useful diagnostics for effective policy targeting. Though efforts have been made to identify time preferences from naturally occurring field data, the majority of research has relied on laboratory samples using variation in monetary payments. Most of estimating time preferences studies have favored in laboratory environments while some have used aggregate consumption data. Among the many laboratory techniques, recent studies have employed multiple price lists (MPL) with monetary payments. With MPLs, in the two different time frames, individuals are asked to choose between sooner-smaller payments (SS) and later-larger (LL) for multiple times. The interest rate increases monotonically in a price list such that the point where an individual switches from preferring sooner payments to later payments carries interval information about their time preferences. Assuming time-separable stationary preferences and linear utility, individual discount rates can be bounded and potentially calculated from MPL switching points. Using information from both price lists allows us to measure discount factors and to identify present and future bias.
Experimental Design
In this paper we have examined this hypothesis that leaning process could affect time preferences. In our experiment, 129 students participated and they answered the "MPL" tests and completed our experience questionnaire. Our experiment was conducted at Ferdowsi University of Mashhad, in May 2016. In a paper-pencil experiment, subjects faced 24 convex budget decisions. These 24 budgets involved four combinations of starting times, t, and delay lengths, k, with annual interest rates that varied from zero to over 1000 percent per year.
A (2*2) design was implemented with two sooner payments date, t= (0, 35) days from the experiment date, crossed with two delay lengths, k= (35,63) days. Thus, there are 4 (t, k) cells and within each cell are six MPL questions.
In a "MPL", subjects are given the choice of ($X, $0), ($0, $Y) that Pxt + x t+k = Y , where P represents the gross interest rate. Subjects faced four intertemporal MPLs. For the intertemporal decisions, variables are the start dates, t, delay lengths, k, and gross interest rates, P. The experimental budget was always $120 such that the intertemporal budget constraint in each decision was Pxt + xt+k = 120.
We have randomly selected one of the decisions as the decision that counts. We have used the decision-that-counts to determine their actual earnings. All payments they receive were sent to their credit card. That includes payments that they receive today as well as payments they may receive at later dates.
Results and Discussion
The findings showed time inconsistent behavior in average. Because distribution of data is not normal, nonparametric regression was used. The results of this study show that the present bias parameter was different for individuals with different experiences. But the parameter of long run time preference has not been affected by experiences. Our observation of an association of intertemporal decision making with choices between an immediate and delayed reward and an association of subjects experiences are consistent with existing theory regarding the cognitive science and functions of brain neural systems.
Conclusions and Suggestions
This, in turn, provides a framework within which quantitative predictions about the dynamics of the neural mechanisms underlying intertemporal choice can be generated. Such studies that join economic theory with hypotheses about and measurements of mechanism from neuroscience remain a priority for future works.

Keywords

time preference; Present Bias; behavioral economics; Experience; Experimental economic

References

[1] Andreoni, J., & Sprenger, C. (2012). Estimating time preferences from convex budgets. The American Economic Review, 102(7), 3333-3356.

[2] Andreoni, J., & Sprenger, C. (2012). Risk preferences are not time preferences. The American Economic Review, 102(7), 3357-3376.

[3] Andreoni, J., Kuhn, M. A., & Sprenger, C. (2015). Measuring time preferences: A comparison of experimental methods. Journal of Economic Behavior & Organization, 116, 451-464.

[4] Angeletos, G. M., Laibson, D., Repetto, A., Tobacman, J., & Weinberg, S. (2001). The hyperbolic consumption model: Calibration, simulation, and empirical evaluation. The Journal of Economic Perspectives, 15(3), 47-68.

[5] Bakhshi Dastjerdi, R. & Dallali Esfahani, R. (2004); An Introduction to Subjective Origins of Interest from Bohm-Bawerk's viewpoint (acritical study), The Quarterly Journal of The Economic Research, No. 13, Autumn, Tarbiat Modares University. (In Persian)

[6] Bardsley, N., Cubitt, R., Loomes, G., Moffat, P., Starmer, C., & Sugden, R. (2010). Experimental economics: Rethinking the rules. Princeton University Press.

[7] Becker, G. S., & Mulligan, C. B. (1997). The endogenous determination of time preference. The Quarterly Journal of Economics, 112(3), 729-758.

[8] Bisin, A., & Hyndman, K. (2014). Present-bias, procrastination and deadlines in a field experiment (No. w19874). National Bureau of Economic Research.

[9] Benhabib, J., & Bisin, A. (2005). Modeling internal commitment mechanisms and self-control: A neuroeconomics approach to consumption–saving decisions. Games and economic Behavior, 52(2), 460-492.

[10] Bourgine, P., & Nadal, J. P. (Eds.). (2013). Cognitive economics: an interdisciplinary approach. Springer Science & Business Media.

[11] Bishai, D. M. (2004). Does time preference change with age?. Journal of Population Economics, 17(4), 583-602.

[12] Böhm-Bawerk, E. (1895). The Origin of Interest. The Quarterly Journal of Economics, 9(4), 380-387.

[13] Camerer,Colin. Cohen,Jonatan. Fehr, Ernst. Glimcher, Poal. Libson, David (2014). Neuroeconomics, Handbook of Experimental economics.

[14] Chabris, C. F., Laibson, D., Morris, C. L., Schuldt, J. P., & Taubinsky, D. (2008). Individual laboratory-measured discount rates predict field behavior. Journal of Risk and uncertainty, 37(2), 237-269.

[15] Cristian, LB (1993). Exprimental Methodology. Translation of Delavari, A. Tehran. Roshd Publishers. (In Persian)

[16] Fisher, I. (1930). The theory of interest. New York, 43.

[17] Haushofer, J. (2014). The cost of keeping track. Working Paper.

[18] Kalenscher,Tobias. Penartz, Cyriel. (2007). Is a bird in the hand worth two in the future? The neuroeconomics of intertemporal decision making

[19] khodaparast mashhadi, M & Tarahomi, F (2013). Analysis of Trans action costs in the Iranian Economy. The first sustainable development conference with a business environment improvement approach. (In Persian)

[20] Laibson, D. (2003). Intertemporal decision making.

[21] Laibson, D. I. (1996). Hyperbolic discount functions, undersaving, and savings policy (No. w5635). National bureau of economic research

[22] March, Leslie. Ross, Don. Economics, cognitive science and social cognition

[23] McClure, S. M., Ericson, K. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2007). Time discounting for primary rewards. Journal of neuroscience, 27(21), 5796-5804

[24] Meier, S., & Sprenger, C. (2010). Stability of time preferences.

[25] Meier, S., & Sprenger, C. D. (2013). Discounting financial literacy: Time preferences and participation in financial education programs. Journal of Economic Behavior & Organization, 95, 159-174.

[26] Meier, S., & Sprenger, C. (2010). Present-biased preferences and credit card borrowing. American Economic Journal: Applied Economics, 2(1), 193-210.

[27] North, D (1990). Institutions, institutional changes and economic performance. Translation of Moieni, M. Samt Publishers. (In Persian)

[28] O'Donoghue, T., & Rabin, M. (1999). Doing it now or later. American Economic Review, 103-124.

[29] Romer, P. M. (1990). Endogenous technological change. Journal of political Economy, 98(5, Part 2), S71-S102.

[30] Shettleworth, S. J. (2010). Cognition, evolution, and behavior. Oxford University Press.

[31] Ramsey, F. P. (1928). A mathematical theory of saving. The economic journal, 38(152), 543-559.

[32] Rizzello, S. (2003). Cognitive developments in economics. Routledge.

[33] Robberstad, B. (2005). Estimation of private and social time preferences for health in northern Tanzania. Social science & medicine, 61(7), 1597-1607.

[34] Samson, A. (2014). The behavioral economics guide 2014 (with a foreword by George Loewenstein and Rory Sutherland).

[35] Shosha, H (1990). Explore psychological sociology. Translation of Katbi, M. Nei Publishers. (In Persian)

[36] Strotz, R. H. (1955). Myopia and inconsistency in dynamic utility maximization. The Review of Economic Studies, 23(3), 165-180.

[37] Tashakori saleh, P & khodaparast mashhadi, M & Feizi, M (2017). Experimental and theoretical study of the effect of property right on intertemporal. Journal of Economics Research (Tahghighat-E-Eghtesadi). (In Persian)