Time Preferences and Consumer Behavior

Abstract

We thank Will Mautz and Camden Sweed for valuable research assistance, GSU, UNCG, and the Harvard Center for Risk Analysis for funding, Darren Lubotsky for providing his code to implement the multiple proxies procedure, and Allen Bellas and conference and seminar participants at UNCG, GSU, Harvard School of Public Health, and the Midwest Economics Association meetings for helpful comments. Ruhm thanks the University of Virginia Bankard Fund for partial financial support. The views expressed in this article are those of the authors and do not necessarily reflect those of the Federal Trade Commission. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. ABSTRACTWe investigate the predictive power of survey-elicited time preferences using a representative sample of US residents. In regressions controlling for demographics and risk preferences, we show that the discount factor elicited from choice experiments using multiple price lists and real payments predicts various health, energy, and financial outcomes, including overall self-reported health, smoking, drinking, car fuel efficiency, and credit card balance. We allow for time-inconsistent preferences and find that the long-run and present bias discount factors ( and ) are each significantly associated in the expected direction with several of these outcomes. Finally, we explore alternate measures of time preference. Elicited discount factors are correlated with several such measures, including self-reported willpower. A multiple proxies approach using these alternate measures shows that our estimated associations between the time-consistent discount factor and health, energy, and financial outcomes may be conservative.

A large-scale test of the effects of time discounting, risk aversion, loss aversion, and present bias on household adoption of energy-efficient technologies

“…For households in the USA, Newell and Siikamäki (2015) find that the standard time discount rate is positively related to the adoption of energy-efficient water heaters; similarly, Allcott and Taubinsky (2015) conclude that standard time discounting helps explain the choice of compact fluorescent lightbulbs (CFLs) versus incandescent light bulbs in the USA. Also for the USA, Bradford et al (2014) find a positive correlation for low cost technologies such as CFLs or thermostats, but not for higher cost measures such as thermal insulation. In comparison, Heutel (2017) does not find a statistically significant link between standard time dis-A large scale test of the effects of time discounting, risk aversion, loss aversion and present bias on household adoption of energy technologies 3 counting and several low and high cost measures for the USA.…”

Present Bias and Everyday Self‐Control Failures: A Day Reconstruction Study

“…In line with Mishra & Lalumière (), our data thus suggest that delay discounting tasks are not the best way to measure implicit processes involved in real‐world choices between present and future outcomes. This would explain why present bias does not correlate with some field behaviors and why the correlations between present bias and other field behaviors tend to be small, such as in the case of credit card borrowing (Meier & Sprenger, ), credit default (Meier & Sprenger, ), obesity (Courtemanche et al, ), and consumer behavior (Bradford, Courtemanche, Heutel, McAlvanah, & Ruhm, ).…”

Assessing the Energy-Efficiency Gap

“…For example, researchers could manipulate intertemporal trade-offs through information provision and pricing interventions, and examine decision making. Another approach may be to combine elicitation of time preferences with choice data and compare choices observed across multiple domains (Bradford et al 2014).…”