NPR Discussions

Working papers cited in recent NPR discussions

The Behavioralist Goes to School: Leveraging Behavioral Economics to Improve Educational Performance

Levitt, Steven, John A. List, Susanne Neckermann, and Sally Sadoff

American Economic Journal: Economic Policy, forthcoming

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Research on behavioral economics has established the importance of factors such as reference dependent preferences, hyperbolic discounting, and the value placed on non-financial rewards. To date, these insights have had little impact on the way the educational system operates. Through a series of field experiments involving thousands of primary and secondary school students, we demonstrate the power of behavioral economics to influence educational performance. Several insights emerge. First, we find substantial incentive effects from both financial and non-financial incentives on test scores. Second, we find that non-financial incentives are considerably more cost-effective than financial incentives for younger students, but were less effective with older students. Third, and perhaps most importantly, consistent with hyperbolic discounting, all motivating power of the incentives vanishes when rewards are handed out with a delay. Since the rewards to educational investment virtually always come with a delay, our results suggest that the current set of incentives may lead to underinvestment. Fourth, in stark contrast to previous laboratory experiments, we do not see an increased response of effort when rewards are framed as losses. Our findings imply that in the absence of immediate incentives, many students put forth low effort on standardized tests, which may create biases in measures of student ability, teacher value added, school quality, and achievement gaps.

The Behavoralist Visits the Factory: Increasing Productivity using Simple Framing Manipulations

Hossain, Tanjim and List, John A.

Management Science, INFORMS, (2012), 58(12), pp. 2151-2167

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Recent discoveries in behavioral economics have led to important new insights concerning what can happen in markets. Such gains in knowledge have come primarily via laboratory experiments—a missing piece of the puzzle in many cases is parallel evidence drawn from naturally-occurring field counterparts. We provide a small movement in this direction by taking advantage of a unique opportunity to work with a Chinese high-tech manufacturing facility. Our study revolves around using insights gained from one of the most influential lines of behavioral research—framing manipulations—in an attempt to increase worker productivity in the facility. Using a natural field experiment, we report several insights. For example, conditional incentives framed as both losses and gains increase productivity for both individuals and teams. In addition, teams more acutely respond to bonuses posed as losses than as comparable bonuses posed as gains. The magnitude of the effect is roughly 1%: that is, total team productivity is enhanced by 1% purely due to the framing manipulation. Importantly, we find that neither the framing nor the incentive effect lose their importance over time; rather the effects are observed over the entire sample period. Moreover, we learn that worker reputation and conditionality of the bonus contract are substitutes for sustenance of incentive effects in the long-run production function.

Enhancing the Efficacy of Teacher Incentives Through Loss Aversion: A Field Experiment

Fryer, Roland G., Levitt, Steven D., List, John A., Sadoff, Sally

NBER Working Paper No. 18237

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Domestic attempts to use financial incentives for teachers to increase student achievement have been ineffective. In this paper, we demonstrate that exploiting the power of loss aversion—teachers are paid in advance and asked to give back the money if their students do not improve sufficiently—increases math test scores between 0.201 (0.076) and 0.398 (0.129) standard deviations. This is equivalent to increasing teacher quality by more than one standard deviation. A second treatment arm, identical to the loss aversion treatment but implemented in the standard fashion, yields smaller and statistically insignificant results. This suggests it is loss aversion, rather than other features of the design or population sampled, that leads to the stark differences between our findings and past research.

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