We provide the first, in experimental economics, consistent estimates of a dynamic learning model with a continuous outcome. The econometric approach we propose can be used in many experimental studies including auctions, bargaining with transfers, and gift exchange experiments. We focus on affiliated private value auctions, where subjects are generally assumed to converge to the rule-of-thumb bidding, but our general approach is applicable to many other settings. Our IV estimates suggest that subjects become significantly less aggressive over time; specifically, they decrease their bids in proportion to the previous period’s signal minus bid. However, the inconsistent OLS and FE estimators imply that subjects become significantly more aggressive over time—they raise their bids in proportion to the previous period’s signal minus bid. Our instruments are randomly generated by the experiment, and pass popular weak instrument tests.

We investigate the differential effects of open versus closed amendment rules within the framework of a distributive model of legislative bargaining. The data show that there are longer delays in distributing benefits and a more egalitarian distribution of benefits under the open amendment rule, the proposer gets a larger share of the benefits than coalition members under both rules, and play converges toward minimal winning coalitions under the closed amendment rule. However, there are important quantitative differences between the theoretical model underlying the experiment (Baron and Ferejohn 1989) and data, as the frequency of minimal winning coalitions is much greater under the closed rule (the theory predicts minimal winning coalitions under both rules for our parameter values) and the distribution of benefits between coalition members is much more egalitarian than predicted. The latter are consistent with findings from shrinking pie bilateral bargaining game experiments in economics, to which we relate our results.Research support from the Economics Division and the DRMS Divisions of NSF and the University of Pittsburgh is gratefully acknowledged. We have benefited from comments by David Cooper, Massimo Morelli, Jack Ochs, and seminar participants at Carnegie Mellon University, École des Hautes Études Commerciales, Harvard University, Indiana University, ITAM, Université de Montreal, Universite du Québec a Montréal, University of Pittsburgh, Joseph L. Rotman School, University of Toronto, Ohio State University, Texas \widehat{{\rm A}{\&}{\rm M}} University, Tilburg University CENTER, Western Michigan University, The Wharton School, University of Pennsylvania, the 2000 Public Choice Meetings, the 2000 Summer Institute in Behavioral Economics, the 2000 Econometric Society World Congress meetings, and the CEA 35th Annual Meetings. We are responsible for all remaining errors.