Knowledge that Transforms

Abstract We implement Pigovian transport pricing in a field experiment in urban agglomerations of Switzerland over the course of 8 weeks. Our pricing considers the external costs from climate damages, health outcomes from pollution, accidents and physical activity, and congestion. It varies across time, space, and mode of transport and is deducted from a budget provided to GPS-tracked participants. The treatment significantly reduces the external costs of transport during the course of the experiment. The main underlying mechanism is a shift away from driving towards other modes, such as public transport, walking, and cycling. Providing information about the external costs of transport alone is insufficient to change the transport behaviour for the sample majority. A time-invariant tax on CO2 and health-related externalities would capture most of the welfare gains associated with the first-best policy.

Abstract In many markets, buyers make discrete choices between differentiated products and negotiate prices that are specific to the choice. We develop for estimation a model for this class of markets which is consistent with non-cooperative models of bargaining between a buyer and competing sellers. We show that when the buyer’s utility has GEV disturbances, the model has a tractable likelihood function which can be used with transaction-level data giving the selected product and its price. We estimate the model using data from the UK brick industry and use it to measure market power and analyse mergers. We analyse how spatial differentiation and ownership concentration affect the distribution of market power across transactions. In counterfactuals we find that switching from individually negotiated to uniform pricing causes markups, and merger price effects, to increase on average but to decrease for a minority of transactions.

Abstract We use decision theory to confront uncertainty that is sufficiently broad to incorporate “models as approximations.” We presume the existence of a featured collection of what we call “structured models” that have explicit substantive motivations. The decision-maker confronts uncertainty through the lens of these models, but also views these models as simplifications, and hence, as misspecified. We extend the max–min analysis under model ambiguity to incorporate the uncertainty induced by acknowledging that the models used in decision making are simplified approximations. Formally, we provide an axiomatic rationale for a decision criterion that incorporates model misspecification concerns. We then extend our analysis beyond the max-min case allowing for a more general criterion that encompasses a Bayesian formulation.

Abstract This article studies competition under information heterogeneity in selection markets and examines the impact of public information regulations aimed at reducing information asymmetries between competing firms. We develop a novel model and introduce new empirical strategies to analyse imperfect competition in markets where firms have heterogeneous information about consumers, vary in cost structures, and offer differentiated products. Using data from the Italian auto insurance market, we find substantial differences in the precision of risk ratings across insurers, and those with less accurate risk-rating algorithms tend to have more efficient cost structures. We assess the equilibrium effects of giving firms equal access to aggregated risk information from a centralized bureau. This policy significantly reduces prices by increasing competition, leading to a 15.7% boost in consumer surplus, almost reaching the efficiency benchmark where firms have full knowledge of consumers’ true risk. Aggregating information through the bureau favours low-risk consumers and reduces average costs by 12 euros per contract through more efficient insurer–insuree matching.

Abstract How much does firm intangibility amplify CEOs’ persistent private information and reduce firms’ public listing propensity? We develop a model of competing public and private investors financing firms heterogeneously exposed to persistent private cash flows. Equilibrium financing is driven by information rent differentials in CEO compensation. We validate and structurally estimate the model using firm listing and CEO compensation data. We find private (intangible) cash flows exhibit 63% higher persistence than their tangible counterparts. Further, if firm intangibility levels returned to those of 1980, mean listing propensities would increase 5 percentage points while mean CEO variable pay growth would decrease by 61%.

Abstract We conduct an experimental analysis of selective disclosure in communication. In the model, an informed sender aims to influence a receiver by disclosing verifiable evidence that is selected from a larger pool of available evidence. Our experimental design leverages this model’s rich comparative statics, allowing us to systematically quantify the effects of selection relative to concealment. Our findings confirm the key qualitative predictions of the theory, suggesting that selection, rather than concealment, is often the dominant distortion in communication. We also identify deviations from the theory: Some senders are “deception averse” and overcommunicate relative to predictions; receivers respond too optimistically to both concealed and selected evidence, with errors of similar magnitude. Yet selection generates greater overall distortion in receiver behavior because it is far more prevalent than concealment.

Abstract We study structural change in production networks for intermediate inputs (inputoutput network) and new capital (investment network). For each network, we document that the share of output produced by services (relative to goods) is rising over time. While the relative prices of services that produce intermediates and consumption are rising, we find that the relative price of services that produce investment is falling over time. We then develop a multi-sector growth model to study these trends and their implications for economic growth. To match the relative price trends, inputs to intermediates production are complements and inputs to investment production are substitutes. Hence, structural change endogenously reallocates resources to the slowest growing intermediates producers and the fastest growing investment producers. Growth accounting exercises reveal that investment-specific technical change accounts for an increasing share of U.S. aggregate growth, with 20% of aggregate growth since 2000 due to investment structural change. Growth projections from our model show that structural change within investment networks alone can offset stagnating or declining growth in other sectors due to Baumol’s cost disease.

Abstract An agent samples projects over time, observing quality for each, while a principal can select at most one. The principal values quality, whereas the agent only wants a project chosen. Transfers are unavailable, but the principal can verify quality by paying a cost. We fully characterize the dynamics of verification by determining optimal mechanisms for this problem. With a low verification cost and a long horizon, the optimal mechanism involves a deterministic selection rule that initially discriminates on quality but chooses a project irrespective of its quality at a deadline. Verification occurs with an intermediate probability before the deadline, declining over time. We show how these conclusions change if the verification cost is high or the horizon is short, and under certain forms of imperfect commitment. Our analysis provides guidelines on how dynamics interact with the benefits of verification.

Abstract We develop a model of multi-dimensional misspecified learning in which an overconfident agent learns about groups in society from observations of his and others’ successes. We show that the average person sees his group relative to other groups too positively, and this in-group bias exhibits systematic comparative-statics patterns. First, a person is most likely to have negative opinions about other groups he competes with. Second, while information about another group’s achievements does not lower a person’s prejudice, information about economic or social forces affecting the group can, and personal contact with group members has a beneficial effect that is larger than in classical settings. Third, the agent’s beliefs are subject to “bias substitution”, whereby forces that decrease his bias regarding one group tend to increase his biases regarding unrelated other groups.

Abstract This article studies the impact of income-based criminal punishments on crime. In Finland, speeding tickets become income-dependent if the driver’s speed exceeds the speeding limit by more than 20 km/h, leading to a substantial jump in the size of the speeding ticket. Contrary to predictions of a traditional Becker model, individuals do not bunch below the fine hike. Instead, the speeding distributions are smooth at the cutoff. However, I demonstrate that the size of the realized speeding ticket has sizable, but short-lived, impacts on reoffending. I use a regression discontinuity design to show that fines that are, on average, 200 euros larger decrease reoffending by 15% in the following 6 months. The drop in reoffending is driven by high-income individuals facing the highest fine at the cutoff. I estimate that a fixed fine hike that matches the current deterrence effect would raise the fine increase faced by the bottom income quartile by about 300% at the cutoff, relative to the increase they face under the current income-based schedule. My empirical results are consistent with an explanation that people operate under information frictions. To illustrate this, I construct a Becker model with misperception and learning that can explain all the empirical findings.