Alexander Coutts

Assistant Professor of Economics, Schulich School of Business

Corruption is often harmful for economic development, yet it is difficult to measure due to its illicit nature. We propose a novel corruption game to characterize the interaction between actual political leaders and citizens, and implement it in Northern Mozambique. Contrary to the game-theoretic prediction, both leaders and citizens engage in corruption. Importantly, corruption in the game is correlated with real-world corruption by leaders: citizens send bribes to leaders whom we observe appropriating community money. In corrupt behavior, we identify an important trust dimension captured by a standard trust game.
Use of lab-in-the-field experiments has steadily increased, given benefits of studying relevant populations and their preferences. In the field, researchers must often relinquish the control of a standard laboratory, raising the specter of communication from past to future participants. Little is known about the consequences of such spillovers, and recent literature indicates variation in how authors deal with them. I provide estimates of communication spillovers using existing data from public goods games in Rwanda, leveraging variation in planning the sequence of visiting 147 villages. The resulting order created opportunities for some villages to communicate with past participants. Using ex-post matching of villages with and without these opportunities I find that communication led to substantial increases in cooperation, suggesting that unanticipated spillovers can bias inference. I conclude with advice for creating protocols to deal with communication spillovers.
Natural resources can have a negative impact on the economy through corruption and civil conflict. This paper tests whether information can counteract this political resource curse. We implement a large-scale field experiment following the dissemination of information about a substantial natural gas discovery in Mozambique. We measure outcomes related to the behavior of citizens and local leaders through georeferenced conflict data, behavioral activities, lab-in-the-field experiments, and surveys. We find that information targeting citizens and their involvement in public deliberations increases local mobilization and decreases violence. By contrast, when information reaches only local leaders, it increases elite capture and rent-seeking.
Bayesian updating remains the benchmark for dynamic modeling under uncertainty within economics. Recent theory and evidence suggest individuals may process information asymmetrically when it relates to personal characteristics or future life outcomes, with good news receiving more weight than bad news. I examine information processing across a broad set of contexts: 1) ego relevant, 2) financially relevant, and 3) non value relevant. In the first two cases, information about outcomes is valenced, containing either good or bad news. In the third case, information is value neutral. In contrast to a number of previous studies I do not find differences in belief updating across valenced and value neutral settings. Updating across all contexts is asymmetric and conservative: the former is influenced by sequences of signals received, a new variation of confirmation bias, while the latter is driven by non-updates. Despite this, posteriors are well approximated by those calculated using Bayes' rule. Most importantly these patterns are present across all contexts, cautioning against the interpretation of asymmetric updating or other deviations from Bayes' rule as being motivated by psychological biases.
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 introduce a theoretical framework that trades off anticipatory benefits against two potential costs of forming biased beliefs: (1) material costs which result from poor decisions, of Brunnermeier and Parker (2005), and (2) direct psychological costs of distorting reality, of Bracha and Brown (2012). The experiment exploits the potential of the increasingly popular BDM elicitation procedure adopted to lotteries to distort beliefs in different directions, depending on which costs are most important. Relative to an elicitation procedure without distortionary incentives, beliefs are biased in the optimistic direction. Increasing payments for accuracy further increases belief reports, in many cases away from the truth, consistent with psychological costs of belief distortion. Yet the overall results suggest that theories of optimism based on anticipatory benefits and material or psychological costs fail to explain how beliefs respond to financial incentives.
Working Papers
People often receive feedback that depends on factors beyond their ability, yet little is known about how this alters the scope for self-serving biases. In a theory-guided experiment, individuals receive a noisy signal about their ability, which comes bundled with another source of uncertainty – a teammate’s ability. In this environment individuals can attribute the feedback across these two dimensions, updating in a self-serving fashion, leveraging the additional flexibility from multi-dimensional uncertainty. In the experiment, rather than blaming their teammate, they process information about them in a positively biased way. This reduces costs associated with over-attribution towards own performance, but later impedes learning by decreasing willingness to change teammates. These results suggest that individuals distort their perceptions of the environment in order to arrive at self-serving beliefs.
Work in Progress