Y2K Bibliography of Experimental Economics and Social Science
Bayesian Learning

updated December 29, 1999
Charles A. Holt, cah2k@virginia.edu, suggestions and corrections welcome
(for online and personal use only)

Allsopp, Louise, and John D. Hey (1999) “Two Experiments to Test a Model of Herd Behavior,” University of York, Discussion Paper. Keywords: experiments, decisions, cascades, information, herd behavior, Bayes' rule. Abstract: This paper provides an experimental test of the Banerjee model of herd behavior. Herding does occur, but not as frequently as theory predicts. Herding is affected by the probability of receiving a signal and by its accuracy, contrary to theoretical predictions. Email Contact: jdh1@york.ac.uk

Anderson, Matthew J., and Shyam Sunder (1995) “Professional Traders as Intuitive Bayesians,” Organizational Behavior and Human Decision Processes, 64185-202. Keywords: experiments, markets, asset markets, information processing, Bayes' rule. Email Contact: shyam.sunder@yale.edu

Anderson, Lisa, and Charles A. Holt (1996) “Classroom Games: Information Cascades,” Journal of Economic Perspectives, 10:4 (Summer), 187-193. Keywords: experiments, classroom games, decisions, information cascades, Bayes' rule. Abstract: This paper describes a simple classroom game in which students rely on others' information as cascades form. The experiment can be used to stimulate discussions of Bayes' rule and informational inferences in interactive contexts. Email Contact: lrande@mail.wm.edu

Anderson, Lisa, and Charles A. Holt (1996) “Classroom Games: Understanding Bayes' Rule,” Journal of Economic Perspectives, 10:2 (Spring), 179-187. Keywords: experiments, classroom games, decisions, Bayes' rule, decisions. Abstract: This paper presents a simple counting heuristic that can be used to teach Bayes' rule via a classroom experiment. Email Contact: lrande@mail.wm.edu

Anderson, Lisa, and Charles A. Holt (1998) “Information Cascade Experiments,” in Handbook of Experimental Economics Results, edited by C. R. Plott and V. L. Smith, New York: Elsevier Press, forthcoming. Keywords: experiments, information, survey, information cascades, information, Bayes' rule. Abstract Results of information cascade experiments are summarized. Email Contact: lrande@mail.wm.edu

Anderson, Matthew J. (1999) “Replication in Laboratory Asset Markets,” Michigan State University, Keywords:
experiments, markets, asset markets, Bayes' rule, video taping.

Argote, L., M. A. Seabright, and L. Dyer (1986) “Individual Versus Group Use of Base Rate and Individuating Information,” Organizational Behavior and Human Decision Processes, 3865-75. Keywords: experiments, decisions, probability judgement, Bayes' rule, base rate fallacy, group decisions.

Argote, L., R. Devadas, and N. Melone (1990) “The Base-Rate Fallacy: Contrasting Processes and Outcomes of Group and Individual Judgement,” Organizational Behavior and Human Decision Processes, 46296-310. Keywords: experiments, decisions, probability judgement, Bayes' rule, base rate fallacy.

Berg, Eric, Daniel Friedman, Hugh E. Kelly, Stephen Kitzis, and Dominic Massara (1998) “Broadening the Tests of Learning Models,” University of California at Santa Cruz, Discussion Paper, presented at the Summer 1998 ESA Meeting. Keywords: experiments, decisions, multiple symptoms, medical diagnosis, Bayes' rule, learning. Abstract: Subjects are asked to make diagnostic decisions in an enriched environment with four possible levels of each symptom. The best model of individual behavior is a simple Bayesian model with a single estimated parameter that represents prior precision. Email Contact: hukelley@cats.ucsc.edu

Calegari, M., and N. Fargher (1997) “Evidence that Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings,” Contemporary Accounting Research, 14:3 397-433. Keywords: experiments, decisions, forecasting, asset markets, finance, accounting, information, Bayes' rule.

Cason, Timothy N., and Daniel Friedman (1997) “Price Formation in Single Call Markets,” Econometrica, 65:2 (March),
311-345. Keywords: experiments, markets, call markets, random values and costs, Bayesian Nash equilibrium, experience effects, payoff flatness, errors, direction learning theory. Abstract: Values and costs are randomly determined each period, and price is determined by crossing the bid and ask arrays in a call market institution. The Bayesian Nash equilibrium predicts qualitative features of the data, but bids and asks are too close to underlying values and costs for some treatments, especially with experienced traders. Bids (asks) exhibit more noise when they are very high or very low, and hence where expected payoffs are less sensitive to deviations from Nash predictions. Email Contact: cason@mgmt.purdue.edu

Cason, Timothy N., and Daniel Friedman (1999) “Learning in a Laboratory Market with Random Supply and Demand,” Experimental Economics, 2:1 77-98. Keywords: experiments, markets, call markets, two-sided sealed bid/ask auctions, Bayesian Nash bidding strategies, private values and costs, learning, adaptive learning, partial adjustment to an ex post best response. Email Contact: cason@mgmt.purdue.edu

Cox, James C., Jason Shachat, and Mark Walker (1997) “An Experiment to Evaluate Bayesian Learning of Nash Equilibrium Play,” University of Arizona, Discussion Paper. Keywords: experiments, game theory, learning, Bayes' rule. Email Contact: jcox@bpa.arizona.edu

Duh, Rong Ruey, and Shyam Sunder (1986) “Incentives, Learning, and Processing of Information in a Market Environment: An Examination of the Base-Rate Fallacy,” in Laboratory Market Research, edited by S. Moriarty, Norman, Ok.: University of Oklahoma, Center for Economic and Management Research, . Keywords: experiments, markets, asset markets, probability judgement, base-rate fallacy, Bayes' rule. Email Contact: shyam.sunder@yale.edu

Duh, Rong Ruey, and Shyam Sunder (1994) “Economic Agents as Intuitive Bayesians: Experimental Evidence,”
Cuadernos Economicos, 54101-128. Keywords: experiments, markets, asset markets, probability judgement, base-rate fallacy, Bayes' rule. Email Contact: shyam.sunder@yale.edu

El-Gamal, Mahmoud A., Richard D. McKelvey, and Thomas R. Palfrey (1993) “A Bayesian Sequential Experimental Study of Learning in Games,” Journal of the American Statistical Association, 88:442 (June), 428-435. Keywords: experiments, game theory, learning, Bayes' rule. Email Contact: melgamal@1.wisc.edu

El-Gamal, Mahmoud A., and David M. Grether (1995) “Are People Bayesian? Uncovering Behavioral Strategies,” Journal of American Statistical Association, 90:432 (December), 1137-1145. Keywords: experiments, decisions, Bayes' rule. Email Contact: melgamal@1.wisc.edu

Friedman, Daniel (1998) “Monty Hall's Three Doors: Construction and Deconstruction of a Choice Anomaly,” American Economic Review, 88:4 (September), 933-946. Keywords: experiments, decisions, Bayes' rule, anomalies, Monty Hall problem, experience, tutorials, incentives. Abstract: The three-door (Monty Hall) anomaly is pervasive in experiments, although it declines with experience, increased incentives, and tutorials. Email Contact: dan@cats.ucsc.edu

Ganguly, Amanda R., John H. Kagel, and Donald V. Moser (1998) “Do Asset Market Prices Reflect Traders' Judgment Biases?,” University of Pittsburgh, Discussion Paper, presented at the Summer 1998 ESA Meetings. Keywords: experiments, markets, asset markets, judgement biases, Bayes' rule, base rate fallacy. Abstract: Subjects are provided with prior and sample information about asset dividends, and probabilities are elicited before asset market trading. The base rate fallacy (ignoring the prior probabilities) persists in the market when the base-rate-fallacy traders have higher expected dividend values than those of Bayesian traders. Email Contact: kagel+@pitt.edu

Grether, David M. (1978) “Recent Psychological Studies of Behavior under Uncertainty,” American Economic Review, 68:2 (May), 70-74. Keywords: experiments, decisions, Bayes' rule, psychology. Email Contact: dmg@doxie.caltech.edu

Grether, David M. (1980) “Bayes' Rule as a Descriptive Model: The Representativeness Heuristic,” Quarterly Journal of Economics, 95(November), 537-557. Keywords: experiments, decisions, Bayes' rule, representativeness, biases, payment incentives, methodology. Email Contact: dmg@doxie.caltech.edu

Grether, David M. (1992) “Testing Bayes' Rule and the Representativeness Heuristic: Some Experimental Evidence,” Journal of Economic Behavior and Organization, 17:1 (January), 31-57. Keywords: experiments, decisions, Bayes' rule, representativeness. Email Contact: dmg@doxie.caltech.edu

Hanson, R. (1996) “Correction to McKelvey and Page, "Public and Private Information: An Experimental Study of Information Pooling",” Econometrica, 64:5 (September), 1223-1224. Keywords: experiments, decisions, Bayes' rule, information aggregation.

Holt, Charles A. (1986) “Discussant's Comments on: Incentives, Learning, and Processing of Information in a Market Environment: An Examination of the Base-Rate Fallacy,” in Laboratory Market Research, edited by S. Moriarity, Norman, Ok.: University of Oklahoma, 80-85. Keywords: experiments, markets, asset markets, Bayes' rule, base rate bias, risk aversion. Email Contact: holt@virginia.edu

Holt, Charles A. (1992) “ISO Probability Matching,” University of Virginia, Discussion Paper. Keywords: experiments, decisions, probability matching, Bayes' rule. Abstract: Probability matching is not observed; subjects predict the more likely event a high percentage of the time, with and without money incentives, although convergence toward the rational decisions is faster under money incentives. Email Contact: holt@virginia.edu

Huck, Steffen, and Jörg Oechssler (1998) “Information Cascades with Continuous Action Spaces,” Economics Letters,
60:2 (August), 162-166**. Keywords: experiments, decisions, information cascades, Bayes' rule. Email Contact: huck@wiwi.hu-berlin.de, oechssler@uni-bonn.de

Hung, Angela, and Charles R. Plott (1999) “Information Cascades: A Replication and Extension to Majority Rule and Grand Jury Instructions,” American Economic Review, forthcoming. Keywords: experiments, decisions, information cascades, Bayes' Rule, majority rule. Email Contact: angela@hss.caltech.edu

Kahneman, Daniel, and Amos Tversky (1972) “Subjective Probability: A Judgement of Representativeness,” Cognitive Psychology, 3430-454. Keywords: experiments, decisions, probability judgement, Bayes' rule, representativeness, biases. Email Contact: kahneman@wws.princeton.edu

Kraemer, Carlo, and Markus Nöth (1999) “Information Aggregation with Costly Signals and Random Ordering: Experimental Evidence,” University of Manheim, Discussion Paper, presented at the Fall 1999 European Regional ESA Meetings. Keywords: experiments, information, cascades, probability judgement, Bayes' rule. Abstract: Subjects are selected in a random order to make a decision on the basis of others' previous decisions and on a costly signal if it is purchased. About half of the subjects overestimate the value of a private signal, which results in excessive information purchases and reduced
conformity. Email Contact: kraemer@bank.bwl.uni-mannheim.de

Laury, Susan K., and Melayne Morgan McInnes (1999) “Information and Insurance: An Experimental Investigation,” Georgia State University, Discussion Paper, presented at the Summer 1999 ESA Meeting. Keywords: experiments, decisions, information, insurance, risk pricing, representativeness bias, Bayes' rule. Email Contact: slaury@gsu.edu

McKelvey, Richard D., and Talbot Page (1990) “Public and Private Information: An Experimental Study of Information Pooling,” Econometrica, 58:6 (November), 1321-1339. Keywords: experiments, decisions, information pooling, Bayes' rule, public information. Email Contact: rdm@hss.caltech.edu

Nöth, Markus, and Martin Weber (1998) “Information Aggregation with Random Ordering: Cascades and Overconfidence,” University of Mannheim, Discussion Paper, presented at the Summer 1998 ESA Meetings. Keywords: experiments, decisions, information cascades with strong or weak private signals, Bayes' rule, overconfidence. Abstract: Subjects receive a noisy signal about whether the unknown state is A or B. The signal is informative, but the accuracy for a given signal is randomly determined to be high or low, which is also known to the subject. Participants make public predictions in a random order. Cascades are observed, but overconfidence reduces the incidence of reverse cascades. Email Contact: noeth@bank.BWL.uni-mannheim.de, weber@bank.bwl.uni-mannheim

Nöth, Markus (1999) “Greed and Fear: Information Aggregation with Endogenous Ordering in an Experiment,” University of Mannheim, Discussion Paper, presented at the Summer 1999 ESA Meeting. Keywords: experiments, information, information cascades, endogenous timing, Bayes' rule, information aggregation. Email Contact: noeth@bank.BWL.uni-mannheim.de

Ouwersloot, H., P. Nijkamp, and P. Rietveld (1998) “Errors in Probability Updating Behavior: Measurement and Impact Analysis,” Journal of Economic Psychology, 19:5 (October), 535-563. Keywords: experiments, decisions, Bayes' rule,
probability judgement, errors.

Thaler, Richard H. (1987) “The Psychology of Choice and the Assumptions of Economics,” in Laboratory Experimentation in Economics: Six Points of View, edited by A. E.. Roth, Cambridge: Cambridge University Press, 99-130. Keywords: experiments, decisions, psychology, methodology, lotteries, sunk costs, marginal analysis, invariance, dominance, opportunity costs, rational expectations, Bayes' rule, learning, incentives, bounded rationality. Email Contact: richard.thaler@gsbsun.uchicago.edu