WORKING PAPERS
Personalizing policies can theoretically increase their e!ectiveness. However, personalization is difficult when individual types are unobservable and the preferences of policymakers and individuals are not aligned, which could cause individuals to misreport their type. Mechanism design offers a strategy to overcome this issue: offer an "incentive-compatible" menu of policy choices designed to induce participants to select the variant intended for their type. Using a field experiment that personalized incentives for exercise among 6,800 adults with diabetes and hypertension in urban India, we show that personalizing with an incentive-compatible choice menu substantially improves program performance, increasing the treatment e!ect of incentives on exercise by 80% without increasing incentive costs relative to a one-size-fits-all benchmark. Offering choice achieves similar performance to personalizing with an extensive set of observable variables, but without the same data requirements.
Many people are impatient. We test a prediction for how to make incentives work particularly well when people are impatient over effort: implement time-bundled contracts that make the payment for future effort increase in current effort. We find empirical support for this prediction using a randomized evaluation of an incentive program for exercise (walking) among diabetics in India. On average, a time-bundled contract generates as much effort as a time-separable linear contract, yet at a 15% lower cost. Moreover, time-bundled contracts perform roughly 30% better among individuals with above-median impatience over effort than those with below-median. Pooled across contracts, incentives increase daily steps by roughly 20% and improve blood sugar control relative to a control group.
Policymakers often seek to reduce resource consumption but face constraints that preclude the use of prices or other first-best instruments. This paper studies the design and effectiveness of an alternative approach: payments for voluntary conservation. We offered payments for reduced groundwater use among farmers in Gujarat, India in a randomized controlled trial. Price incentives work: The program reduced irrigation time by 22 percent. Conservation payments are a practical policy tool in this setting: The program saved energy at a per-unit cost comparable to the electric utility’s supply costs. Contract design greatly affects cost-effectiveness: More stringent benchmark values (against which conservation is measured and rewarded) halved the average cost of conservation.
Energy efficiency is a global priority, but investments in energy efficiency do not always deliver the expected benefits. This paper studies micro-irrigation systems (MIS), a technology thought to reduce the energy required for irrigation by as much as 70 percent. We installed individual meters to directly measure the energy consumption of several hundred farmers in Gujarat, India, and linked this meter data with survey data to yield a comprehensive view into energy use patterns in smallholder agriculture. We document two facts. One, energy use varies widely across farmers, and this variation is unexplained by factors such as farm area or village geography. Two, MIS users in our sample consume 30 to 40 percent more energy than non-users of MIS. This difference does not appear to be explained by observable differences across farmers nor by rebound effects, suggesting that the energy impacts of MIS under real-world conditions may be disappointing. While these findings are not causal, they highlight a need for increased attention to details of implementation and further research into the actual benefits of resource-conserving technologies.
IN THE WORKS
Encouraging Drug Abstinence with Dynamic Incentives
With Rebecca Dizon-Ross
Combatting the rise of the opioid epidemic is a central challenge of U.S. health care policy. A promising approach for improving welfare and decreasing medical costs of people with substance abuse disorders is offering incentive payments for healthy behaviors. This approach, broadly known as "contingency management" in the medical literature, has repeatedly shown to be effective in treating substance abuse. However, the use of incentives by treatment facilities remains extremely low. Furthermore, it is not well understood how to design optimal incentives over time to treat opioid abuse. We will conduct the first evaluation of a scalable incentive program delivered through a mobile application. Our experiment will also directly address a key open question in the literature on incentives for drug-users: how to dynamically adjust incentives for abstinence behaviors according to how well individuals are complying with incentivized behaviors. Behavior-dependent dynamic incentive schedules can take two overarching forms: escalating or de-escalating. Escalating schedules feature incentive payments for compliance that increase as individuals comply with the behavior, and decrease with failures to comply. Escalating incentive schedules increase the stakes of good behavior now by hinging the size of future earnings opportunities on current behavior, and are frequently tested in substance-use settings. However, a pitfall of escalating schedules is that they are poorly targeted: they pay the largest incentives to individuals who are complying with behaviors, and offer the smallest incentives to individuals who are struggling to achieve compliance. De-escalating schedules can address the poor targeting of escalating schedules. De-escalating schedules feature incentive payments that increase when individuals fail to comply with the behavior. By delivering larger incentives where they are needed most, these schedules could particularly help individuals when they are struggling, an especially desirable feature in the addition space where the costs of substance abuse may be convex. However, the stakes of good behavior are lower than in an escalating schedule, because failure to comply now increases the size of future earnings. Our experiment will empirically assess the tradeoff between these two approaches. Effects will be measured on abstinence outcomes, including longest duration of abstinence and the percentage of negative drug tests. In combination with survey data, variation from the experiment will shed light on the barriers to abstinence more broadly and inform our understanding of optimal incentive design. A randomized pilot at the Aurora Health Adult Behavioral Program in Milwauke, Wisconsin is currently under way (AEA Registry Record No. AEARCTR-0005000.)
DE-BIASING OVER-OPTIMISM ABOUT PERSONAL COVID-19 HEALTH RISK
With Seema Jayachandran and Rebecca Dizon-Ross
Providing people with information about their health risk is an important part of the policy response to a public health crisis. However, the most effective way to present such information is unknown, particularly in light of behavioral biases people have. One such bias is over-optimism about one's health risk (i.e., a tendency to believe that one's risk is lower than it is), which has been documented in many settings and shown to lead to riskier behaviors. This study aims to test whether interventions that offset people’s over-optimism can improve the effectiveness of information provision. We do so in the context of the COVID-19 pandemic, among a population that is particularly vulnerable to severe complications from COVID-19, namely diabetics, pre-diabetics and hypertensives, who represent a large and growing segment of the population in India.
PAYING FOR PREVENTION: THE ROLE OF INCENTIVES IN ELIMINATING CARE GAPS
An important aspect of the Affordable Care Act was an increased focus on quality-of-care. The act created new quality measures that emphasize closing gaps in care and decreasing the use of costly acute care through preventive services. While insurance providers now have substantial stake in encouraging their members to close preventive care gaps, there is limited evidence on the most effective means to do so. We conduct a randomized controlled trial among members of a large health insurance provider in a midwestern state who had one of seven critical care gaps in 2018. Members either receive a letter with an incentive to close their (or their child’s) care gap, a letter with information regarding the gap, or no letter. We find that while incentives are effective for encouraging closure of children and teens’ care gaps, the do not improve care gap closures for adults – and may even discourage gap closure among this population. Information regarding existing care gaps has no detectable effect on closures.