In legislative bargaining, the proposer is often able to extract a greater proportion of the surplus. However, a higher likelihood of being selected as the proposer can backfire, as it may reduce the probability that the agent is included in a winning coalition. We experimentally test the theoretical prediction of potentially negative returns to recognition probability in two-period legislative bargaining noted in Baron and Ferejohn (1989). We find that higher recognition probability benefits subjects in all treatments, except one in which we automate the second period. It is because proposers often favor the member with the greater recognition probability as a coalition partner, and such tendency varies depending on the proposer’s recognition probability, counter to the theoretical prediction. In all treatments, a vast majority of subjects exhibit a strict preference for higher recognition probability.

Expectations are among the main driving forces for economic dynamics. Therefore, managing expectations has become a primary objective for monetary policy seeking to stabilize the business cycle. In this paper, we study whether central banks can manage private-sector expectations by means of publishing one-period ahead inflation projections in a New Keynesian learning-to-forecast experiment. Subjects in the experiment observe these projections along with the historic development of the economy and subsequently submit their own one-period ahead inflation forecasts. In this context, we find that the central bank can significantly manage private-sector expectations and that this management strongly supports monetary policy in stabilizing the economy. Moreover, published central bank inflation projections drastically reduce the probability of a deflationary spiral after strong negative shocks to the economy.

With the aid of a lab experiment, we explored how imperfect monitoring and punishment networks impacted appropriation, punishment and beliefs in a common pool resource appropriation dilemma. We studied the differences between the complete network (with perfect monitoring and punishment, in which everyone can observe and punish everyone else) and two ‘imperfect’ networks (that systematically reduce the number of subjects who could monitor and punish others): the directed and undirected circle networks. We found that free riders were punished in all treatments, but the network topology impacted the type of punishment: the undirected circle induced more severe punishment and prosocial punishment compared to the other two networks. Both imperfect networks were more efficient because the larger punishment capacity available in the complete network elicited higher punishment amount.

Companies that manage mandatory pension funds are frequently accused of excessive fee taking. International analyses have found that in countries with legal caps, commissions remain within these caps; hence, market competition does not function. Surprisingly, there are few international cases where local regulators implement mechanisms to facilitate competition. The variety of auction mechanisms available raises the question of whether an optimal solution exists for this purpose. Therefore, in this study, we present evidence, based on a controlled regulatory experiment, on the fee-reduction potential of reverse auctions.

The present article discusses general issues associated with experimental auctions and their relative advantages and disadvantages over other marketing research techniques. Experimental auctions create an active market environment with feedback where subjects exchange real goods and real money, which is not generally the case with other methods. The article also discusses four experimental design issues associated with experimental auctions: auction mechanism, market feedback and bidder affiliation, demand reduction and wealth effects, and multiple attribute valuation. Each of these experimental design issues, if not properly controlled, have the potential to create serious flaws in marketing recommendations.

The roots and uses of economic experiments in problem solving and hypothesis testing are explored in the present article. The literature suggests that the primary advantage of economics experiments is the ability to use controlled stimuli to test economic hypotheses. Other literature also suggests that experiments are useful in problem solving settings. The advantages and disadvantages of experiments are discussed.

Laboratory market experiments are used to estimate the incidence of a stylized subsidy in factor market negotiations with university student and agricultural professional subjects. In separate sessions with both groups, prices converged approximately four and a half tokens higher when a 20-token per-unit subsidy was paid to buyers; this equates to 44% of the predicted 10-token split. A proportional market incentive treatment clarifies this subsidy effect. Discrepancies between predicted and observed incidence are similar to previous empirical estimates of subsidy incidence in agricultural land rental markets. A behavioral anomaly as well as buyer-buyer market competition may contribute to experimental results.

Competition in a multi-unit auction is measured both by the number of bidders and by the relative size of their demands, compared to the number of units on sale. For the same degree of competition (identical aggregate demand and supply), we can observe different demand structures. Do they have an impact on the auction efficiency and revenue-raising properties? It is essential to understand better the impact of competition structure on performance in order to draw recommendations for the design of multi-unit auctions. Theoretical results demonstrate on a simple case contrasting a uniform-price auction of two bidders with a demand of 6 units each, and an auction of 6 bidders with a demand of two units each, that there are multiple equilibria leading to different performance outcome. Experiments are conducted to compare the performance of these two auctions. Results support that with a constant competition degree, the seller gets higher expected revenue with a lower variance when he faces a large number of bidders with small individual demands. We show that this result is attained with no significant effect on allocative efficiency.

The past decade has witnessed an unprecedented growth in our understanding of the brain basis of economic decision-making. In particular, research is uncovering not only the location of brain regions where certain processes are taking place, but also the nature of the (economically meaningful) latent variables that are represented, as well as how they relate to behavior. This transition from understanding where to how economic decisions are being made in the brain has been integral to relating neural processes to economic models of behavior. This progress, however, has been notably uneven. Neu-roeconomic studies of individual decision-making, such as those involve risk and time preferences, have the benefit of drawing on decades of work from neuroscientific studies of animal behavior. Critically, many of these findings are based on quantitative, computational approach that lends well to economic experimentation. In contrast, our understanding of the neural systems underlying social behavior is much less specific. A large measure of the current challenge in fact arises from the empirical shortcomings of standard game theoretic predictions of behavior, which are largely equilibrium-based. Using our own study as an example, we show how one can directly search for the latent variables implied by current economic models of strategic learning, and attempt to localize them in the brain. Specifically, we show that the neural systems underlying strategic learning build directly on top of those involved in simple trial-and-error learning, but incorporate additional computations that capture belief-based learning. Finally, we discuss how our approach can be extended to address fundamental problems in economics.