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Learning in a Laboratory Market with Random Supply and Demand

Published online by Cambridge University Press:  14 March 2025

Timothy N. Cason  and
Daniel Friedman
Timothy N. Cason*
Affiliation:
Department of Economics, Krannert School of Management, Purdue University, West Lafayette, IN 47907-1310
Daniel Friedman
Affiliation:
Department of Economics, University of California at Santa Cruz, Santa Cruz, CA 95064
*
email: [email protected]
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Abstract

We propose a simple adaptive learning model to study behavior in the call market. The laboratory environment features buyers and sellers who receive a new random value or cost in each period, so they must learn a strategy that maps these random draws into bids or asks. We focus on buyers’ adjustment of the “mark-down” ratio of bids relative to private value and sellers’ adjustment of the corresponding “mark-up” ratio of asks relative to private cost. The learning model involves partial adjustment of these ratios towards the ex post optimum each period. The model explains a substantial proportion of the variation in traders’ strategies. Parameter estimates indicate strong recency effects and negligible autonomous trend, but strongly asymmetric response to different kinds of ex post error. The asymmetry is only slightly attenuated in “observational learning” from other traders’ ex post errors. Simulations show that the model can account for the main systematic deviations from equilibrium predictions observed in this market institution and environment.

Keywords

experimentcall marketauctionbidding

JEL classification

D44: Auctions C92: Laboratory, Group Behavior D83: Search • Learning • Information and Knowledge • Communication • Belief • Unawareness
Type
Research Article
Information
Experimental Economics , Volume 2 , Issue 1 , August 1999 , pp. 77 - 98
Copyright
Copyright © 1999 Economic Science Association

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