Alexander Coutts

Assistant Professor of Economics, Nova School of Business and Economics

Working Papers
Optimistic beliefs affect important areas of economic decision making, yet direct knowledge on how belief biases operate remains limited. To better understand these biases I conduct an experiment examining beliefs about binary events with financial stakes. By varying financial prizes in outcomes, as well as incentive payments for accuracy, the experiment is able to distinguish between two leading theories of optimistic belief formation that differ in their assumptions about how such beliefs are constrained. The Optimal Expectations theory of Brunnermeier and Parker (2005) models beliefs as being constrained through the future costs of holding incorrect beliefs, while the Affective Decision Making model of Bracha and Brown (2012) argues that beliefs are constrained by mental costs of distorting reality. The results suggest that people hold optimistically biased beliefs, and comparative statics indicate that these beliefs are not constrained by increasing the costs of making inaccurate judgments. In fact, the results support the theory of Bracha and Brown (2012), as observed bias is increasing in the size of incentive payments for accuracy.
Bayesian updating remains the benchmark for dynamic modeling under uncertainty within economics. Recent theory and evidence suggests individuals may process information in a biased manner when it relates to personal characteristics or future life outcomes. Specifically, updating has been found to be asymmetric, with good news receiving more weight than bad news. I put this theory and evidence to the test, by examining information processing across multiple domains with varying stake conditions. I do not find that good news is over-weighted relative to bad news, but in fact, I find the opposite asymmetry. However these updating patterns are present more generally, including when news is neither good nor bad. While updating across all domains and stake conditions is asymmetric and conservative, posteriors remain well approximated by those calculated using Bayes' rule. I investigate further possible determinants of asymmetry and conservatism, finding that the former is sensitive to signal types and the latter is driven solely by non-updates. Most importantly these patterns are present across all domains, cautioning against the interpretation of asymmetric updating or other deviations from Bayes' rule as being motivated by psychological biases.
Artefactual and lab experiments are increasingly utilized to study variation in preferences across groups and the relationship between preferences and economic outcomes. Social learning across experimental sessions is rarely considered within the literature and not well understood, but may alter the validity of such studies. In this paper I provide evidence of social learning during a large implementation of public goods games in the Rusizi district in Rwanda. Contact with previous participants led to significant behavioral change, despite theoretical predictions that such contact will have no effects. Using GPS data on over 1,700 participants across 150 villages I document an increasing pattern of contributions in public goods games over space and time. An investigation of the mechanism behind the effect finds that it is strongest for individuals who exhibit conditionally cooperative behavior, suggestive that contact involves social learning about cooperative norms.
Work in Progress