Data on individual labor earnings are reported from two experimental economies where the primary factors responsible for income differences were differences in tastes for market income versus leisure and differences in abilities working manual job tasks. Measured income dispersion under these conditions was strikingly similar to that in the United states and other market economies, indicating that these two factors alone are sufficient to generate such income differences. Further, in tests of the functional form of the distributions of income, the hypothesis of lognormality fit better than the hypothesis of normality, just as it does in national data.

Alternating-offer and demand bargaining models of legislative bargaining make very different predictions in terms of both ex ante and ex post distribution of payoffs, as well as in the role of the order of play. The experiment shows that actual bargaining behavior is not as sensitive to the different bargaining rules as the theoretical point predictions, whereas the comparative statics are in line with both models. We compare our results to studies that attempt to distinguish between these two approaches using field data, finding strong similarities between the laboratory and field data regardless of the underlying bargaining process. Copyright The Econometric Society 2005.

We compare individuals with two-person teams in signaling game experiments. Teams consistently play more strategically than individuals and generate positive synergies in more difficult games, beating a demanding “truth-wins” norm. The superior performance of teams is most striking following changes in payoffs that change the equilibrium outcome. Individuals play less strategically following the change in payoffs than inexperienced subjects playing the same game. In contrast, the teams exhibit positive learning transfer, playing more strategically following the change than inexperienced subjects. Dialogues between teammates are used to identify factors promoting strategic play.

This paper synthesizes findings from an ongoing research program on learning in signaling games. The present paper focuses on cross-game learning- the ability of subjects to take what has been learned in one game and generalize it to related games- an issue that has been ignored in most of the learning literature. We begin by laying out the basic experimental design and recapitulating early results characterizing the learning process. We then report results from an initial experiment in which we find a surprising degree of positive cross-game learning, contrary to the predictions of commonly employed learning models and to the findings of cognitive psychologists. We next explore two features of the environment that help to explain when and why this positive transfer occurs. First, we examine the effects of abstract versus meaningful context, an issue that has been largely ignored by economists out of the belief that behavior is largely dictated by the deep mathematical structure of a game. In contrast, results from cognitive psychology suggest that behavior may well be sensitive to context employed. Our results show that the use of meaningful context serves as a catalyst for positive transfer. Second, we explore how play by two-person teams differs from play by individuals. The psychology literature is quite pessimistic about the ability of teams to beat a “truth wins ” standard based on performance of individuals. But teams easily surpass this norm in our cross-game experiment. We use the dialogues between team members to gain insight into how this transfer occurs, gaining direct confirmation for hypotheses generated by econometric analysis of earlier data. I. The Experimental Environment: Our experiments are based on a simplified version of Paul Milgrom and John Roberts ' (1982) entry limit pricing game. The game proceeds as follows: (1) Monopolists (Ms) observe their cost level- high (MH) or low (ML) cost- realized according to equal probabilities that are common knowledge. (2) Ms choose a quantity (output) whose payoff is contingent on the entrant’s (Es) response (see Table 1). (3) E sees this output, but not M’s type, and either enters or stays out. The asymmetric information, in conjunction with the fact that it is profitable to enter against MHs, but not against MLs, provides an incentive for strategic play (limit pricing).

In his recent paper in this Review, Glenn Harrison (1989) argues that the conclusions of James Cox et al. (1982, 1983, 1985, 1988) in their studies of first-price private-value auctions are not well supported, because of shortcomings in the way their experimental investigations were designed, analyzed, and reported. Harrison argues that the expected cost of deviations from risk-neutral Nash equilibrium (RNNE) bidding in these auctions was quite small (less than $0.05 at the median), so that in terms of expected monetary payoffs (payoff space) many subjects had little to lose from deviating from the RNNE strategy. Harrison suggests that the significance of the differences Cox, Vernon Smith, and James Walker (hereafter CSW) report between subjects' bids and the RNNE bids (deviations in the message space) may therefore need to be reexamined. In discussing Harrison versus CSW we have three primary points to make.' First, in arguing that it is more natural to evaluate subject behavior in expected payoff space (Harrison, 1989 p. 749), we think Harrison has overstated his case. However, we agree with his more important point that looking at the cost of deviations is a useful diagnostic tool for determining when experimenters are likely to have lost control over subjects' incentives. Further, as we will show in Section I, this part of Harrison's critique applies with special force to CSW's studies of bidding. Second, a broader examination of the results of private-value auction experiments indicates that risk aversion cannot be the only factor and may well not be the most important factor behind bidding above the RNNE found so often in first-price privatevalue auctions. The most telling evidence here is bidding above the dominant bid price found in second-price auctions (Kagel et al., 1987; Kagel and Levin, 1990) and the risk-loving found under several treatment conditions in CSW's (1984) own multipleunit discriminative auctions (auctions in which the high bidders pay their bid price). These and other data inconsistent with risk-averse bidding are largely ignored in CSW (1988) but are nevertheless relevant to the substantive issue of risk aversion in private-value auctions. They are discussed in Section II. Third, there are data gathered in other investigations which provide strong support for the view that the deviations from RNNE bidding reported in first-price auctions are not the results of the low expected cost of such deviations. However, these data, unlike the higher-stakes payoff data that CSW offer in response to Harrison, are not consistent with CSW's subsidiary conclusions that the data can be well accounted for by a narrow class of risk-aversion parameters for the bidders, together with the assumption that all agents are playing a Nash equilibrium of the resulting game of incomplete information. A key difference between these experiments and CSW's is that if subjects do not respond to CSW's treatment condition (increasing the payoffs from experimental to U.S. dollars) their behavior will be consistent with CSW's theory. In contrast, * Department of Economics, University of Pittsburgh, Pittsburgh, PA 15260. We thank Jack Ochs and Emilie Roth for thoughtful discussions on earlier drafts of the paper, Jim Cox and Glenn Harrison for helpful comments on the initial draft of the paper, Susan Garvin for research assistance, and Ray Battalio, Carl Kogut, and Don Meyer for providing us with access to their data. Research support was provided by the Information Science and Technology and Economics divisions of the National Science Foundation, the Alfred P. Sloan Foundation, and the Russell Sage Foundation. The usual caveat applies with special force. IWe do not respond to specific comments that CSW (1992) make in response to our comment as, in order to avoid indefinite regress, the ground rules for this debate required us to comment on CSW's criticism of Harrison, after which they would be given the opportunity to respond to our comment.

John H. Kagel, Ronald M. Harstad, Dan Levin, Information Impact and Allocation Rules in Auctions with Affiliated Private Values: A Laboratory Study, Econometrica, Vol. 55, No. 6 (Nov., 1987), pp. 1275-1304

Raymond C. Battalio, John H. Kagel, Robin C. Winkler, Richard A. Winett, Residential Electricity Demand: An Experimental Study, The Review of Economics and Statistics, Vol. 61, No. 2 (May, 1979), pp. 180-189

Results of recent empirical and theoretical research have shown the applicability of consumer demand theory in describing and predicting choices of nonhuman consumers (see A. Covich, D. Rapport and J. Turner, Battalio et al., Kagel et al., 1975, 1980). Commodities used in these studies have been largely limited to different kinds of edibles: food grains, water, and sweet tasting (preferred) fluids. A natural extension of the commodity choice model is to consider leisure as a good. This paper presents results of experiments showing that nonhuman workers (pigeons) are willing to trade off income for leisure if the price is right. More specifically our results show that the Slutsky-substitution effect is positive for (exactly) compensated wage decreases, and that leisure is a normal good at all points in the choice space. In addition to demonstrating the pervasiveness of income-leisure tradeoffs, the experiments show strong regularities in the size of the substitution and income effects at varying wage rates; with increases in real wages both income and substitution effects get smaller, but the substitution term decreases more rapidly than the income term resulting in a backward bending labor supply curve at higher wages. The plan of the paper is as follows. In Section I we characterize the procedures employed in the laboratory for studying labor supply, and summarize well-established characteristics of this behavior as it is relevant to the present experiments. Sections II and III describe the hypotheses tested and the experimental procedures employed in the tests. Results of the experiments are given in Section IV. Some of the implications of these results are discussed in a brief concluding section. Space considerations do not permit a detailed discussion of the reasons why economists should take seriously the investigation of economic theories using nonhuman subjects (see Kagel and Battalio for this argument). For the more skeptical reader we simply note that if one defines economics as .. . .the study of the allocation of scarce resources among unlimited and competing uses (Albert Rees, 1968, p. 472), then animal psychologists, ecologists and biologists have been involved in studying economic behavior for some time now (Rapport and Turner; Jack Hirschleifer; H. Rachlin). It is but a small step to take the technologies of these related disciplines and apply them to behavior of interest to economists, for example labor supply behavior. At a minimum, such studies expand considerably the scope for comparative economic analysis. At a maximum they provide a laboratory for identifying, testing, and better understanding general laws of economic behavior. Use of this laboratory is predicated on the fact that behavior as well as structure vary continuously across species, and that principles of economic behavior would be unique among behavioral principles if they did not apply, with some variation, of course, to the behavior of nonhumans.

Inexperienced women, along with economics and business majors, are much more susceptible to the winner’s curse, as are subjects with lower SAT/ACT scores. There are strong selection effects in bid function estimates for inexperienced and experienced subjects due to bankruptcies and bidders who have lower earnings returning less frequently as experienced subjects. These selection effects are not identified using standard econometric techniques but are identified through experimental treatment effects. Ignoring these selection effects leads to misleading estimates of learning.