We design and conduct a real-effort experiment to jointly estimate present bias and sophistication across effort and monetary domains. Unlike prior work (e.g.,Augenblick and Rabin, 2019; Fedyk, 2024), we do not assume that these parameters are identical across domains. We explain and empirically demonstrate how assuming identical sophistication across money and effort domains can bias the estimates of key parameters. In our online experiment, participants chose to (predicted to) complete 14% (10%) fewer tasks on the same day than on a future day, leading to an estimated present bias ($\beta_e$) over effort of 0.70–0.79, and an estimated sophistication ($\widehat{\beta}_e$) of 0.80–0.88. For money, aggregate present bias ($\beta_m$) is near zero, but there is substantial heterogeneity, with roughly equal numbers of participants exhibiting present bias and future bias. At the individual level, roughly three quarters of all participants correctly anticipate the direction of their bias in both domains, even if not its full magnitude.

We present and conduct a novel experiment on a multi-period beauty contest game. Leveraging the multi-period feature, we investigate how participants revise their forecasts in periods when new information—such as shocks or announcements—arrives and how they form their expectations in the absence of new information. We make two key contributions. First, we develop a new method based on forecast revisions to evaluate whether participants behave in a forward-looking manner. The experimental results show that participants do react to anticipated shocks: namely, the announcements of future shocks. Second, we identify a new strategic environment effect during periods without new information; only when the game exhibits strategic complementarity do participants use extrapolation and expect continuously rising prices. This finding suggests that expectation formation is endogenous to the economic environment; and policy design should thus take this endogeneity into account.

We build an experiment to uncover the bandit-like nature of consumer behavior usually masked by the product and time aggregation of consumption data. Subjects make repeated choices between musical styles (either all familiar or unfamiliar), and post-choice satisfaction is observed. We estimate Bayesian bandit models of learning taste by consuming with satiation. Our best model features decreasing random exploration, with openness being associated with higher exploration. Early exploration is more intensive in the unfamiliar treatment and persists throughout the experiment in both treatments. Overall, subjects make choices that deviate from their best prediction 61.5% of the time in the unfamiliar treatment versus 44.7% in the familiar treatment. Our model offers a rational interpretation of random utility in discrete consumer choices which does not rest on perception and/or decision errors.

This study investigates how in-game virtual currencies influence consumer spending behaviour. In an incentivized randomized controlled trial with 753 UK participants, we estimate the willingness-to-pay (WTP) for loot boxes represented as risky and ambiguous lotteries. We test the effects of virtual currencies, money illusion, and cognitive-demanding (non-intuitive) exchange rates, three practices commonly used to sell loot boxes. Our results show that WTP is significantly higher when transactions are conducted in virtual currencies with a 1:1 exchange rate compared to British pounds, contributing to the debate on the neutrality of virtual currencies and experimental currency units. Moreover, participants in our study are affected by money illusion distortions, regardless of the exchange rate’s intuitiveness. However, we find no evidence that non-intuitive exchange rates affect participants’ WTP compared to intuitive exchange rates of comparable size. These findings highlight the behavioural distortions induced by common monetization practices in games and provide empirical support for the European Commission’s call for stricter regulation of virtual currencies in digital environments.

We experimentally investigate preferences for clumping-versus-separating information in the gain and the loss domains, and also preferences for timing. Our design is motivated by the idea that information preferences may depend on reference points. Subjects participate in two monetary lotteries and choose how to receive the outcome information. For half of the subjects, the lotteries are framed as two gain lotteries; for the other half, as two loss lotteries. Based on Thaler (1985) one can expect that people want to learn the outcomes of the gain lotteries separately and the outcomes of the loss lotteries clumped together (cf. hedonic editing hypothesis). On the other hand, a different reference dependent model by Koszegi and Rabin (2009) relies on expectations-based reference points, and predicts that subjects should prefer clumped information irrespective of the frame.

The results of our experiment show a preference for separating information about gains, and no preference for clumping or separating information about losses. Regarding timing, we find a weak overall preference for receiving information sooner. These findings provide new insights into information preferences. We conclude by discussing policy implications, as well as our additional contributions to related literature.

Groups often agree that change is needed, but differing preferences and information may still lead to difficulty coordinating on a particular alternative. In a laboratory experiment, we study coordination and information aggregation in a divided-majority voting game with public information and conflicting preferences. Voters observe private signals and a public signal about whether alternative $A$ or $B$ is socially optimal. Unless sufficiently many voters agree, an inferior default $C$ occurs. When the public signal is more accurate than the private signal and voters have common preferences, most voters coordinate on the public signal. However, when public-signal accuracy is reduced or preferences conflict, voters follow the public signal less frequently. While reduced public-signal accuracy substantially increases the frequency of coordination failure, conflicting preferences between subgroups do not. These results highlight the importance of accurate public information in achieving collective action.

In a $k$-replica Edgeworth box economy, we compare outcomes of laboratory markets in which human traders have different visualizations available on their screens. Novel visualizations include a heat map that shows at a glance the value of all feasible portfolios (i.e., final allocations); a geometric display of the order book; and order entry via point-and-click on the heat map. Efficiency metrics focus on allocations, prices and profitability. Compared to the traditional text-oriented trader screen for the continuous double auction, we find that the novel features generally increase all three efficiency metrics.