|Behavioral Economics and Public Policy
|Saturday, May 27, 2023
|10:00 AM–11:50 AM
|Hyatt Regency, Centennial Ballroom C
|Area: EAB/BPN; Domain: Translational
|Chair: Justin Charles Strickland (Johns Hopkins University School of Medicine)
|Discussant: Steven R Hursh (Institutes for Behavior Resources, Inc.)
|CE Instructor: Derek D. Reed, Ph.D.
|Abstract: Behavioral economics is an approach to understanding behavior though integrating behavioral psychology and microeconomic principles. Advances in behavioral economics have resulted in quick-to-administer tasks to assess discounting (i.e., decrements in the subjective value of a commodity due to delayed or probabilistic receipt) and demand (i.e., effort exerted to defend baseline consumption of a commodity amidst increasing constraints)—these tasks are built upon decades of foundational work from the experimental analysis of behavior and exhibit adequate psychometric properties. We propose that the behavioral economic approach is particularly well suited, then, for experimentally evaluating potential public policy decisions, particularly during urgent times or crises. This symposium showcases four unique areas in which behavioral economics can inform policy, beyond the popularized area of application in substance use. We are honored to have Dr. Steve Hursh as discussant to provide general commentary on these talks and this topic.
|Instruction Level: Intermediate
|Keyword(s): behavioral economics, demand curves, discounting, public policy
|Target Audience: Intermediate. Attendees should have foundational knowledge in behavioral economics.
|Learning Objectives: describe behavioral economic tasks that can inform policy;
identify behavioral economic metrics relevant to policymakers;
discuss advantages of a behavioral economic approach to policy development
|Using Commodity Purchase Tasks to Inform and Evaluate Policy
|DEREK D. REED (University of Kansas)
|Abstract: Consumers decide what to purchase, under conditions of constraint (e.g., commodity price). According to behavioral economic demand, commodity purchase task (CPT) can measure hypothetical decisions about purchases under varied simulated policy conditions (e.g., introduction of new cigarette taxes, happy hour drinking specials). These tasks permit rapid data collection without sacrificing methodological rigor or the validity of conclusions reached. The CPT allows researchers to simulate new policies, to determine their relative risks and benefits, thus offering an opportunity to optimize prior to rollout. Behavioral outcomes related to consumer purchases also make the CPT data readily translatable to policymakers, including constituent health behavior. This presentation provides a brief background on CPTs, a review of literature related to policy-aimed CPTs, and a start on best practices for other behavioral scientists interested in applying CPT to inform public policy efforts.
|Using Behavioral Economics to Optimize Safer Undergraduate Late-Night Transportation
|BRETT GELINO (Johns Hopkins University School of Medicine), Madison Graham (University of Kansas; Cofrin Logan Center for Addiction Research and Treatment), Justin Charles Strickland (Johns Hopkins University School of Medicine), Hannah Glatter (University of Kansas), Derek D. Reed (University of Kansas)
|Abstract: Many university campuses sponsor student-oriented transit services as part of a broader student safety initiative. Such options could prove effective in reducing alcohol-induced risks, but only if services adequately anticipate and adapt to student needs. Human choice data offer a foundation from which to plan and optimally execute late-night transit services. In this simulated choice experiment, respondents opted to either (a) wait an escalating delay for a free, university-sponsored “safe” option, (b) pay an escalating fee for an on-demand rideshare service, or (c) pick a free, immediately available “unsafe” option (e.g., ride with an alcohol-impaired driver). We fit averaged choice-data using operant behavioral economic nonlinear modeling to examine preference across arrangements. Best-fit metrics indicate adequate sensitivity to contextual factors (i.e., wait time, preceding late-night activity). At short delay, students generally preferred the free transit option. As delays extend (i.e., beyond 30 minutes), most students shifted preference toward competing alternatives. These data depict a policy-relevant delay threshold as a target to better safeguard undergraduate student safety.
|Behavioral Economic Considerations for Tornado Hazard Mitigation Strategies
|MADISON GRAHAM (University of Kansas; Cofrin Logan Center for Addiction Research and Treatment), Brett Gelino (Johns Hopkins University School of Medicine), Elaina Sutley (University of Kansas), Derek D. Reed (University of Kansas)
|Abstract: The present study describes an interdisciplinary collaboration between behavioral economists and engineers to begin modeling the effects of tornado hazard messaging on adults’ shelter seeking behavior. We will describe our experimental efforts to crowdsource data collection across regions most impacted by tornadoes, as well as our translational efforts to apply behavioral economic principles to understanding how decisions to seek shelter are influenced by
messaging components such as impact descriptors, storm intensity, as well as other factors such as availability of adequate shelters and delays/speeds of storms. Finally, we will report how framing the messaging of tornado impacts may have significant effects on improving shelter seeking behavior to ultimately increase tornado safety.
It’s the Prices, Stupid: Modeling Barriers to Healthcare Utilization With Behavioral Economics
|MARK JUSTIN RZESZUTEK (University of Kentucky)
The United States has the highest per capita healthcare spending in the world, but some of the worst healthcare outcomes. The US lags behind other similarly developed countries with regard to life expectancy and preventable deaths in spite of US healthcare costs being nearly twice that of comparable countries. A major factor that could be responsible for this are the upfront costs of healthcare access being placed on the individual in forms of private insurance, co-pays, and deductibles, thus deterring healthcare utilization. Three experiments using crowdsourced samples (Amazon Mechanical Turk, 200 per experiment) were conducted to examine how hypothetical healthcare seeking for three common symptoms (headache, nausea, and cough) was affected by duration of symptoms, severity of symptoms, and cost to access healthcare. Decision-making generally followed a hyperbolic form, while increased costs of healthcare resulted in significant delays of access to healthcare regardless of symptom severity. Shallower delay discounting was positively associated with physical health, while steeper delay discounting was positively associated with earlier treatment seeking. The results of these experiments can provide insight into health decision-making and help inform areas of policy reform to improve health outcomes in the US.