Mark Dean
a
“Search, Choice and Revealed Preference (with Andrew Caplin), Theoretical Economics, Forthcoming
With complete information, choice of one option over another conveys preference. Yet when search is incomplete, this is not necessarily the case. It may instead reflect unawareness that a superior alternative was available. To separate these phenomena, we consider non-standard data on the evolution of provisional choices with contemplation time. We characterize precisely when the resulting data could have been generated by a general form of sequential search. We characterize also search that terminates based on a reservation utility stopping rule. We outline an experimental design that captures provisional choices in the pre-decision period. Paper
“Measuring Beliefs and Rewards: A Neuroeconomic Approach” (with Andrew Caplin, Paul Glimcher and
Robb Rutledge), Quarterly Journal of Economics, Forthcoming
The neurotransmitter dopamine is central to the emerging discipline of neuroeconomics; it is hypothesized to encode the difference between expected and realized rewards and thereby to mediate belief formation and choice. We develop the first formal test of this theory of dopaminergic function, based on a recent axiomatization by Caplin and Dean [2008A]. These tests are satisfied by neural activity in the nucleus accumbens, an area rich in dopamine receptors. We find evidence for separate positive and negative reward prediction error signals, suggesting that behavioral asymmetries in response to losses and gains may parallel asymmetries in nucleus accumbens activity. Paper
“Axiomatic Methods, Dopamine and Reward Prediction Error” (with Andrew Caplin), Current Opinion in
Neurobiology, August 2008, 18(2): 197-202
The phasic firing rate of midbrain dopamine neurons has been shown to respond both to the receipt of rewarding stimuli, and the degree to which such stimuli are anticipated by the recipient. This has led to the hypothesis that these neurons encode reward prediction error (RPE)—the difference between how rewarding an event is, and how rewarding it was expected to be. However, the RPE model is one of a number of competing explanations for dopamine activity that have proved hard to disentangle, mainly because they are couched in terms of latent, or unobservable, variables. This article describes techniques for dealing with latent variables common in economics and decision theory, and reviews work that uses these techniques to provide simple, non-parametric tests of the RPE hypothesis, allowing clear differentiation between competing explanations. Paper
“Dopamine, Reward Prediction Error, and Economics” (with Andrew Caplin), Quarterly Journal of
Economics, May 2008 123(2): 663-701
The neurotransmitter dopamine has been found to play a crucial role in choice, learning, and belief formation. The best-developed current theory of dopaminergic function is the “reward prediction error” hypothesis—that dopamine encodes the difference between the experienced and predicted “reward” of an event. We provide axiomatic foundations for this hypothesis to help bridge the current conceptual gap between neuroscience and economics. Continued research in this area of overlap between social and natural science promises to overhaul our understanding of how beliefs and preferences are formed, how they evolve, and how they play out in the act of choice. Paper
“Trading off Speed and Accuracy in Rapid, Goal-Directed Movements” (with Shih-Wei Woo and Laurence
Maloney), Journal of Vision, July 2007, 7(5): 1-12
Many studies have shown that humans face a trade-off between the speed and accuracy with which they can make movements. In this article, we asked whether humans choose movement time to maximize expected gain by taking into account their own speed–accuracy trade-off (SAT). We studied this question within the context of a rapid pointing task in which subjects received a reward for hitting a target on a monitor. The experimental design we used had two parts. First, we estimated individual trade-offs by motivating subjects to perform the pointing task under four different time constraints. Second, we tested whether subjects selected movement time optimally in an environment where they were rewarded for both speed and accuracy; the value of the target decreased linearly over time to zero. We ran two conditions in which the subjects faced different decay rates. Overall, the performance of 13 out of 16 subjects was indistinguishable from optimal. We concluded that in planning movements, humans take into account their own SAT to maximize expected gain. Paper
a
“Enhanced Choice Experiments” (with Andrew Caplin), forthcoming in The Method of Modern Experimental Economics, Guillaume Frechette and Andrew Schotter, eds
We outline experiments that improve our understanding of decision making by analyzing behavior in the period of contemplation that preceeds commitment to a
nal choice. The experiments are based on axiomatic models of the decision making process that relate closely to revealed preference logic. To test the models, we arti
cially incentivize particular choices to be made in the pre-decision period. We show how the resulting experiments can improve our understanding not only of the decision making process, but of the decision itself. Our broad method is to make aspects of search visible while retaining the disciplined approach to data that axiomatic modeling best provides. Paper
“Economic Insights from ‘Neuroeconomic’ Data” (with Andrew Caplin), American Economic Review Papers and Proceedings, May 2008, 98(2): 169-174
No Abstract Paper
“Axiomatic Neuroeconomics” (with Andrew Caplin), Chapter in Neuroeconomics: Decision Making and the Brain, Paul Glimcher, Colin Camerer, Ernst Fehr and Russell Poldrack, eds, 2008
No Abstract Paper
“The Neuroeconomic Theory of Learning” (with Andrew Caplin), American Economic Review Papers and Proceedings, May 2007, 97(2): 148-152
No Abstract Paper
“Why has World Trade Grown Faster than World GDP?” (with Maria Sebastia-Barriel), Bank of England Quarterly Bulletin, Autumn 2004: 310-320
Between 1980 and 2002, world trade has more than tripled while world output has "only" doubled. The rise in trade relative to output is common across countries and regions, although the relative growth in trade and output varies greatly. This article attempts to explain why the ratio of world trade to output has increased over recent decades. It provides a brief review of the key determinants of trade growth and identifies proxies that will enable us to quantify the relative importance of the different channels. We estimate this across a panel of ten developed countries. This will allow us to understand better the path of world trade and thus the demand for UK exports. Furthermore this approach will help us to distinguish between long-run trends in trade growth and cyclical movements around it. Paper
a
“Falsifying the Reward Prediction Error Hypothesis with an Axiomatic Model” (with Robb Rutledge, Andrew Caplin and Paul Glimcher), revise and resubmit at the Journal of Neuroscience
Neuroimaging studies typically identify neural activity correlated with the predictions of highly parameterized models, like the many reward prediction error (RPE) models used to study reinforcement learning. Identified brain areas might encode RPEs or alternatively simply have activity correlated with RPE model predictions. Here we use an alternate axiomatic approach rooted in economic theory to formally test the entire class of RPE models on neural data. We show that measurements of neural activity from the
striatum, medial prefrontal cortex, amygdala, and posterior cingulate cortex satisfy necessary and sufficient conditions for the entire class of RPE models. However, activity measured from the anterior insula falsifies the axiomatic model and therefore no RPE model can account for this activity. Further analysis suggests the anterior insula might instead encode something related to the salience of an outcome. As cognitive neuroscience matures and models proliferate, formal approaches that assess entire classes of models rather than specific model exemplars may take on increased significance. Paper
“Search and Satisficing” (with Andrew Caplin and Daniel Martin), revise and resubmit at American Economic Review
Many options are available even for everyday choices. In practice, most decisions are made without full examination of all such options, so that the best available option may be missed. We develop a search-theoretic choice experiment to study the impact of incomplete consideration on the quality of choices. We find that many decisions can be understood using the satisficing model of Simon [1955]: most subjects search sequentially, stopping when a “satisficing” level of reservation utility is realized. We find that reservation utilities and search order respond systematically to changes in the decision making environment. Paper
“How Rational are your Choice Data?” (with Daniel Martin)
We present an algorithm that finds the size of the largest subset of a choice data set that is consistent with acyclicality. Our algorithm is orders of magnitude more efficient than existing methods. It can be used to calculate measures of rationality, such as the Houtman-Maks index and the minimum multiple rationales, that have been previously impractical. We also develop a new measure of how close a data set is to rationality. Further, we demonstrate the efficiency of our algorithm on data from laboratory experiments [Choi et al. 2007] and household consumption data [Blundell, Browning and Crawford 2003, 2008]. In doing so, we provide previously unavailable rationality measures for these data sets. Paper
“Status Quo Bias in Large and Small Choice Sets”
This paper introduces models of status quo bias based on the concept of decision avoidance,
by which a decision maker may select the status quo in order to avoid a difficult decision. These
models capture the experimental finding that the status quo is more frequently chosen in larger
choice sets. This phenomenon violates the predictions of current preference-based models of status
quo bias that assume a decision maker with a fixed status quo will make consistent choices. Using
laboratory experiments, I show that subjects in large choice sets do exhibit behavior in line with
decision avoidance, while in small choice sets, preference-based models offer a better explanation of
behavior. These findings raise questions for advocated policies of “benign paternalism.” Paper
Department of Economics
Brown University, Rm 303c, Robinson Hall, 64 Waterman Street, Providence, Rhode Island, 02912, USA
+1 401 863 2097