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Behavioral Economics. Will Dow UC-Berkeley April 2010. Many Uses of Term “Behavioral Economics”. Unhelpful use: any analysis by economists of health behaviors Use by non-economists: Interventions that use incentives to change behavior
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Behavioral Economics Will Dow UC-Berkeley April 2010
Many Uses of Term “Behavioral Economics” • Unhelpful use: any analysis by economists of health behaviors • Use by non-economists: Interventions that use incentives to change behavior • Economists: Modification of neoclassical economic theory of behaviors to incorporate various insights from psychology
Long tradition • Saint Augustine in 4th century: "Grant me chastity and continence, but not yet" • Herb Simon: bounded rationality in 1956, satisficing (1978 Nobel Prize winner) • Kahneman and Tversky: prospect theory in 1970s (2002 Nobel Prize) • 1990s rapidly increasing interest, now explosion in field experiments • Now popular dissemination (“Nudge” etc.)
Neoclassical Economics:Home economicus • Behaviors determined by: • Rational self-interest, responding to extrinsic incentives • Fully informed (past information) • Forward-looking • Fixed preferences • Thus: Maximize expected utility
Cognitive Psychology • Add to economic model of behavior: • Mental models and perceptions • Framing matters • Cues can influence decisions (“nudges”) • Heuristics commonly used • Intrinsic emotions/attitudes • Self-control problems (hot/cold) • Fairness matters (social preferences) • Memory of past experiences • Thus behavior is adaptive; it is dependent on the context and transitory perceptual conditions.
Kahneman and Tversky • People judge probabilities poorly. • Use “law of small numbers”: Over-emphasize lessons from small samples • “Availability”: give too much weight to personal experience • Use “heuristics” to process complex decisions; often systematically biased • Prospect Theory: • Status quo bias and loss aversion in small risks, risk-loving behavior in large risks.
Time Inconsistency: self control problems • Neoclassical model: • Tradeoff present and future at fixed discount rate, e.g. 3%. • Thus: Indifferent between $1 today and $1.03 in one year and $1.06 in two years. • Quasi-hyperbolic discounting: • Tradeoffs in future same as neoclassical (so $1.03 in one year still valued same as $1.06 in two years). But immediate gratification gets extra value (neural cause?). • So to give up $1 today would need say $1.30 next year (instead of $1.03 in neoclassical model). • Theory for binge eating, postponing tobacco quits to tomorrow, underuse preventive care such as vaccines, etc. • Provides “libertarian paternalism” rationale for policy intervention
Some Empirical Evidence • Lab experiments by Kahneman/Tversky and many others (experimental economics). • More recent evidence from field/natural experiments (DellaVigna 2009 review): • Non-standard preferences: time inconsistency • Incorrect beliefs: e.g., systematic overconfidence (naifs overestimate ability to choose healthy behaviors such as attending exercise club) • Systematic biases in decisions (heuristics/framing/status-quo): E.g., 401k choices depend on opt-in/opt-out. Could be explained by heuristics, or self-control problems combined with naivete.
Health Applications (1): Choice Architecture (defaults) • Key principles: • Defaults important, so set carefully to encourage good health • Avoid defaults that are not socially acceptable (organ donation) • Avoid paternalistic choice restrictions, barriers to switching • Opt-out health care (Halpern): • HIV testing, health worker flu shot, inpatient pneumococcal vaccination, catheter removal after 72 hours, organ donation, etc. • Health insurance • Opt-out enrollment: large employers, Medicare part D duals • Limit # choices
HIV screening defaults • CDC 2006 universal opt-out screening guideline, since 20% HIV+ undiagnosed • Prior studies show opt-out feasible: between 29% and 87% accept. • But studies don’t show whether increased testing is due to opt-out design, or simply greater promotion of testing. This is crucial distinction, since opt-out still controversial. • Opt-out also controversial since some perceive as coercive when done by health care provider. Would “active choice” be equally effective? • Proposed study at SF-General ER (Montoy, Kaplan, Dow): 1-year intervention with 18,000 patients. Day-level randomization to opt-out, opt-in, or active choice.
Health Applications (2):Pre-Commitments • Binding pre-commitments to overcome time inconsistency (illiquid savings…): • Insure preventive care even if low cost • Avoid temptation by not stocking sweets • Buy cigarettes in small numbers; use patch • Smoking cessation and weight loss commitment contracts • Non-binding commitments, which introduce cognitive dissonance if violate. E.g., “foot-in-the-door” effects: • Blood donations increase if first ask hypothetically in survey if would donate
“Foot-in-the-door”for HIV screening • First ask patient hypothetically in waiting room survey if would accept HIV test if offered. Then follow-up with actual offer. Would this increase HIV screening? • We propose to test this in our SF-General study. • Randomly assign patients to hypothetical question in pre-survey (others receive pre-survey without hypothetical question). • Randomization independent of opt-out randomization, so can test interactive effects. • If “foot-in-the-door” effective, could lead to wide set of hypothetical asks, taking advantage of current unproductive time in waiting rooms.
Tobacco cessation binding commitment contracts • Gine, Karlan, and Zinman (2010): • Recruited 2000 smokers in Philippines wanting to quit. • Randomized to: • Control group: smoking cessation pamphlets • Treatment group: deposit funds regularly, which would be returned at 6 months only if quit. • Results: • 11% take-up. Deposits average 3% income. • 9% controls quit, vs. 12.5% treatments. • Effects statistically significant but not large
Smoking commitment contracts:Proposed Thailand study (White & Dow) • Similar idea to Philippine study: use deposit boxes, with deposits only returned if quit smoking. • But test group commitment contracts: • Treatment enrollees paired with buddy • Thus social support added to intervention. • Introduce joint liability: Incentive based on partner’s quit status • Thus social peer pressure added to intervention • Ambiguous theoretical prediction due to possible adverse effect of group contract: • Mixed prior evidence on effects of buddies on quitting; hypothesize that buddy effects could be enhanced via incentives. • But if buddy fails to quit, may lessen own motivation to sustain quitting.
Health Applications (3): Incentives for behavioral change • Conditional cash transfer programs: • Mexico’s Oportunidades: Large cash transfers to poor conditional on preventive health care etc. Large program, widely copied. Some health benefits, though pathway unclear (incentives versus income). • Incentives for specific health-related behaviors: • Contingency management in substance abuse: regular rewards for staying on wagon. Accepted practice, shown effective • Opportunity NYC: Increased dental care… small effects overall. But incentivized few behaviors, and these were generally good among controls anyway. Structuring incentives is a challenge! • Malawi: $3 incentive increased pick-up of HIV test results by 27%. • Incentives for reducing risky behaviors / improving outcomes: • Smoking cessation: $750 incentive raised quitting (after >1 year) from 3.6% to 9.4% (Volpp). • Weight loss (lottery or commitment contracts): 13 lb loss over 4 month trial with ~$300 incentive, but smaller and insignificant at 7 month post-trial follow-up (Volpp). • Stay HIV negative: Malawi study offered $4-$16 if HIV negative after one year. Results show no effect (Thornton and Kohler, 2010).
Incentives to reduce unwanted pregnancy among SF Latinas (Ali Minnis et al.) • Proposed study tests use of incentives (up to $150) for using reproductive health services (plus completing education/training goals, etc.). • What are theoretical pathways through which incentives might affect fertility?
Theoretical pathways through which incentives might affect fertility • Neoclassical: $150 incentive rationally induces behavioral change. E.g., if reproductive health services were expensive, but $150 reduces the effective cost sufficiently to raise use. But unlikely this would be sufficient incentive to exert any effect on fertility in a neoclassical model, since the cost of fertility is far greater. • Time inconsistency: Reproductive health services may be quite valuable to subjects in terms of reducing future unwanted fertility, but they may not be getting those services due to time inconsistent behavior. $150 delivered in the present may be sufficient to overcome this. • Incentives are a “nudge” to get effective services, counseling, etc. Multiple possible pathways: they provide a cue of value of these services, they provide excuse to friends for getting them, etc. Then family planning services could directly reduce unintended fertility -- and/or counseling/education could indirectly reduce fertility by reducing current demand for children.
Incentives to Reduce STI Incidence in Tanzania (Dow et al.) • On-going randomized prevention trial. • Controls: STI testing every 4 months, free treatment, counseling • Treatments: adds incentive payments for negative STI tests. • Pathways: • Neoclassical price effect: incentives raise “price” (lost incentive payment) of risky sex. • Neoclassical time discounting: bring rewards of risk reduction closer to present, rather than AIDS reduction far in future. (Not necessarily an aid to self-control problems in “hot state”; instead exploits high discount rates in setting.) • Nudge: cash provides a nudge/excuse to alter conventional practices and norms. Qualitative data suggest this is particularly helpful to women in getting their husbands to reduce risky behavior.
Homework Thinking about the material from today, what are theoretical pathways discussed in the health behavior and health behavior change theories that overlap with one or more of the behavior economics approach? What are differences? Selecting one specific behavioral area in your field, how would you expect an incentive-based program to affect your outcome? How would you want to measure change?