We report an experiment designed to measure how (and how well) subjects choose between biased sources of instrumentally valuable information. Subjects choose between two information sources with opposing biases in order to inform their guesses of a binary state. By varying the nature of the bias, we vary whether it is optimal to consult sources biased towards or against subjects’ prior beliefs. We find that subjects frequently choose sub-optimal information sources, and that these mistakes can be described by a handful of well-defined decision rules. Most common among these is a confirmation-seeking rule that guides subjects to systematically choose information sources that are biased towards their priors. Analysis of post-experiment survey questions suggest that subjects follow these rules intentionally and find them normatively appealing. Combined with incentivized belief data and post-experiment cognitive tests, this suggests that mistakes like confirmation-seeking are driven by fundamental errors in reasoning about the informativeness of biased information sources.
We present results from laboratory experiments studying the impacts of affirmative action policies. We induce statistical discrimination in simple labor-market interactions between firms and workers. We then introduce affirmative-action policies that vary in the size and duration of a subsidy firms receive for hiring discriminated-against workers. These different affirmative-action policies have nearly the same effect and practically eliminate discriminatory hiring practices. However, once lifted, few positive effects remain and discrimination reverts to its initial levels. One exception is lengthy affirmative-action policies, which exhibit somewhat longer-lived effects. Stickiness of beliefs, which we elicit, helps explain the evolution of these outcomes.
I am an Assistant Professor in Economics at the Yale School of Management, an affiliated faculty member of the Department of Economics, and a research staff member of the Cowles Foundation. My research interests include organizational economics, the economics of innovation, and experimental economics, particularly focusing on how firms design compensation and performance evaluation schemes to motivate workers.
Axel Ockenfels is Professor of Economics at the University of Cologne, and Speaker of the University of Cologne Excellence Center for Social and Economic Behavior. His research focuses on market design and behavioral research. It has benefitted from various DFG funding programs and from various collaborations with governments, market platforms, companies and research institutions across Europe and the US.
Daniel Friedman joined the UCSC Economics faculty in 1985 after teaching at UCLA and UC Berkeley. He has broad research interests in applied economic theory, with emphasis on learning and evolution, laboratory experiments, and financial markets. The coauthor of five academic books, fourteen NSF grants, and roughly 100 research articles, he currently is studying a) financial market design, b) strategic behavior in real time, and c) evolutionary dynamics of continuous strategies or traits.
His popular book, Morals and Markets: An Evolutionary Perspective on the Modern World, was published by Palgrave-MacMillan in October 2008. A second paperback edition, co-authored with journalist Daniel McNeill, appeared in June 2013 with the subtitle: A Dangerous Balance.
In a large randomized controlled trial, we test the hypothesis that incentives for physical activity can improve academic performance. We found strong support for this hypothesis: University students who were incentivized to go to the gym had a significant improvement in academic performance, by, on average, 0.15 standard deviations compared to a control group that did not receive any incentives. The success of this indirect incentive for academic performance emphasizes the importance of non-cognitive skills in achieving academic goals. Students who were incentivized to exercise report improved self-control and a healthier life-style. Overall, the study demonstrates that incentivizing exercise can be an important tool in improving educational achievements.
Her research focuses on economic experiments based on game theory. She investigates how people strategically interact in various setups, for example, when some people can spy their opponent’s actions or when people can walk away from their partners and meet new ones. In another paper, Natalie also studies how people vary the amount of risk they take on behalf of other people, depending on what they learn about the outcome of their choices.
Social norms are a ubiquitous feature of social life and pervade almost every aspect of human social interaction. However, despite their importance, we still have relatively little empirical knowledge about the forces that drive the formation, the maintenance and the decay of social norms. In particular, our knowledge about how norms affect behavior and how norm obedience and violations shape subsequent normative standards is quite limited. Here, we present a new method that makes norms identifiable and continuously observable and, thus, empirically measurable. We show – in the context of public goods provision – the quick emergence of a widely accepted social cooperation norm that demands high contributions but – in the absence of the punishment of free-riders – norm violations are frequent and, therefore, the initial normative consensus as well as the high cooperation demands required by the norm break down. However, when peer punishment is possible, norm violations are rare from the beginning and a strong and stable normative consensus as well as high contribution requests prevail throughout. Thus, when norm compliance is costly social norms tend to unravel unless norm violations are kept to a minimum. In addition, our results indicate that – in an environment that has previously shown to be detrimental for cooperation and welfare – the opportunity to form a social norm unambiguously causes high public good contributions and group welfare when peer-punishment is possible.
Andrea Robbett is an Assistant Professor of Economics at Middlebury College. She received her PhD from Caltech in 2011. Her research uses lab experiments to address topics related to public economics, labor economics, social dilemmas, and voting. This talk will focus on a series of experiments investigating expressive voting and rational ignorance among American political partisans.
We study the pattern of correlations across a large number of behavioral regularities, with the goal of creating an empirical basis for more comprehensive theories of decision making. We elicit 21 behaviors using an incentivized survey on a representative sample (n = 1,000) of the U.S. population. Our data show a clear pattern of high and low correlations, with important implications for theoretical representations of social and risk preferences. Using principal components analysis, we reduce the 21 variables to six components corresponding to clear clusters of correlations. We examine the relationship between these components, cognitive ability, demographics, and qualitative self-reports of preferences.