Mental Time Travel and Retirement Savings

We portray the valuation of retirement savings in terms of a mental time travel journey in which a proposed contribution to a pension plan is projected forward to the plan member’s retirement date and this projected value is then discounted back to today, thereby giving a present or personal value. We set this within a broader framework of pension planning, which seeks to smooth consumption over the lifecycle. We explain how two psychological biases—exponential growth bias and present bias—can lead to a difference between the initial value of a pension contribution and its present value, such a difference reflecting an asymmetry between projection and discounting, and how such a difference might lead to inadequate retirement savings and hence to a lower than desired standard of living in retirement. We consider how the two biases might be mitigated.

Identifying Present Bias from the Timing of Choices

A (partially naïve) quasi-hyperbolic discounter repeatedly chooses whether to complete a task. Her net benefits of task completion are drawn independently between periods from a time-invariant distribution. We show that the probability of completing the task conditional on not having done so earlier increases towards the deadline. Conversely, we establish nonidentifiability by proving that for any time-preference parameters and any dataset with such (weakly increasing) task-completion probabilities, there exists a stationary payoff distribution that rationalizes the agent’s behavior if she is either sophisticated or fully naïve. Additionally, we provide sharp partial identification for the case of observable continuation values. (JEL C14, D11, D15, D90, D91)

The Effect of a Future-Self Avatar mHealth Intervention on Physical Activity and Food Purchases: The FutureMe Randomized Controlled Trial (Preprint)

BACKGROUND Insufficient physical activity and unhealthy diets are contributing to the rise in non-communicable diseases. Preventative mobile health (mHealth) interventions may enable reversing this trend, but present bias might reduce their effectiveness. Future-self avatar interventions have resulted in behavior change in related fields, yet evidence whether such interventions can change health behavior is lacking. OBJECTIVE Our primary objectives are to investigate the impact of a future-self avatar mHealth intervention on physical activity and food purchasing behavior, and to examine the feasibility of a novel automated nutrition tracking system. We also aim to understand how this intervention impacts related attitudinal and motivational constructs. METHODS We conducted a 12-week parallel randomized-controlled trial (RCT), followed by semi-structured interviews. German-speaking smartphone users aged ≥18 years living in Switzerland, and using at least one of the two leading Swiss grocery loyalty cards, were recruited for the trial. Data were collected from November 2020 to April 2021. The intervention group received the FutureMe intervention—a physical activity and food purchase tracking mobile phone application that uses a future-self avatar as the primary interface and provides participants with personalized food basket analysis and shopping tips. The control group received a conventional, text- and graphic-based primary interface intervention. We pioneered a novel system to track nutrition leveraging digital receipts from loyalty card data analyzing food purchases in a fully automated way. Data were consolidated in 4-week intervals and non-parametric tests were conducted to test for within- and between-group differences. RESULTS We recruited 167 participants; 95 eligible participants were randomized into either the intervention (n=42) or control group (n=53). The median age was 44.00 years (IQR 19.00), and the gender ratio was balanced (female 52/95, 55%). Attrition was unexpectedly high with only 30 participants completing the intervention, negatively impacting the statistical power of our study. The FutureMe intervention led to directional, small increases in physical activity (median +242 steps/day) and to directional improvements in the nutritional quality of food purchases (median –1.28 British Food Standards Agency Nutrient Profiling System Dietary Index points) at the end of the intervention. Intrinsic motivation significantly increased (P=.03) in the FutureMe group, but decreased in the control group. Outcome expectancy directionally increased for the FutureMe group, but decreased for the control group. Leveraging loyalty card data to track the nutritional quality of food purchases was found to be a feasible and an accepted fully automated nutrition tracking system. CONCLUSIONS Preventative future-self avatar mHealth interventions promise to encourage improvements in physical activity and food purchasing behavior in healthy population groups. A full-powered RCT is needed to confirm this preliminary evidence and to investigate how future-self avatars might be modified to reduce attrition, overcome present bias, and promote sustainable behavior change. CLINICALTRIAL The trial has been registered on ClinicalTrials.gov(NCT04505124)

Discounting Behavior in Problem Gambling

Problem gamblers discount delayed rewards more rapidly than do non-gambling controls. Understanding this impulsivity is important for developing treatment options. In this article, we seek to make two contributions: First, we ask which of the currently debated economic models of intertemporal choice (exponential versus hyperbolic versus quasi-hyperbolic) provides the best description of gamblers’ discounting behavior. Second, we ask how problem gamblers differ from habitual gamblers and non-gambling controls within the most favored parametrization. Our analysis reveals that the quasi-hyperbolic discounting model is strongly favored over the other two parametrizations. Within the quasi-hyperbolic discounting model, problem gamblers have both a significantly stronger present bias and a smaller long-run discount factor, which suggests that gamblers’ impulsivity has two distinct sources.

Verification of a theory of planned behavior model of medication adherence in Korean adults: focused on moderating effects of optimistic or present bias

Background To prevent or recover from a disease, the prescriptions for medications must be correct, and the patient must comply with the medication’s instructions. Therefore, this study verified the theory of planned behavior (TPB) model to predict medication adherence among Korean adults and examined the role of optimistic or present bias in that model. Methods The participants were 357 Korean male and female adults whose ages ranged from 18 to 76 (M = 41.53, SD = 9.89). Their medication adherence was measured with the Morisky Green Levine Scale. The study examined TPB factors with modified items related to medication adherence and optimistic bias with items developed based on the concept and on previous studies. Results An alternative TPB model, including a direct path from attitude to behavior, a direct path from the perceived behavioral control to the behavior, and an insignificant path from behavioral intention to behavior, was validated for Korean adults’ medication adherence. This model was found to be moderated by optimistic or present bias. Conclusions The findings of this study should provide useful information for future research and for medical or health professionals who wish to improve the medication adherence of their patients.

Closing the Gap: The Effect of Reducing Complexity and Uncertainty in College Pricing on the Choices of Low-Income Students

High-achieving, low-income students attend selective colleges at far lower rates than upper-income students with similar achievement. Behavioral biases, intensified by complexity and uncertainty in the admissions and aid process, may explain this gap. In a large-scale experiment we test an early commitment of free tuition at a flagship university. The intervention did not increase aid: rather, students were guaranteed before application the same grant aid that they would qualify for in expectation if admitted. The offer substantially increased application (68 percent versus 26 percent) and enrollment rates (27 percent versus 12 percent). The results suggest that uncertainty, present bias, and loss aversion loom large in students’ college decisions. (JEL I22, I23, I24, D31, I28)