We study a behavioral SIR model with time-varying costs of distancing. The two main causes of the variation in the cost of distancing we explore are distancing fatigue and public policies. We show that for a second wave of an epidemic to arise, a steep increase in distancing cost is necessary. Distancing fatigue cannot increase the distancing cost sufficiently fast to create a second wave. However, public policies that discontinuously affect the distancing cost can create a second wave. With that in mind, we characterize the largest change in the distancing cost (due to, for example, lifting a public policy) that will not cause a second wave. Finally, we provide a numerical analysis of public policies under distancing fatigue and show that a strict lockdown at the beginning of an epidemic (as, for example, recently in China) can lead to unintended adverse consequences. Once the policy is lifted, the disease spreads rapidly due due to the accumulated distancing fatigue of the individuals causing high prevalence levels.

We propose a formal theory to capture the tension between problem-driven and solution-driven search in innovation and science. We model discovery as a two-dimensional match between novel ideas and technical methods. Our framework disciplines empirical evidence by generating sharp predictions about the optimal ``research mix'' and its response to the economic environment. We characterize how funding shocks, collaboration, and new technologies alter the balance between exploring breadth of questions and mastering depth of solution methods. Our results rationalize heterogeneous findings on the direction of innovation and provide a structural basis for empirical analysis.

We study information design in a vertically differentiated market. Two firms offer products of ex-ante unknown qualities. A third party designs a system to publicly disclose information. More precise information guides consumers toward their preferred product but increases expected product differentiation, allowing firms to raise prices. Full disclosure of the product ranking alone suffices to maximize industry profits. Consumer surplus is maximized, however, whenever no information about the product ranking is disclosed, as the benefit of competitive pricing always dominates the loss from suboptimal choices. The provision of public information on product quality becomes questionable.

We study optimal test design in settings where the testing variable is itself a choice. Agents with heterogeneous productivity invest inputs (such as money or effort) to increase outputs (such as product quality or human capital) that they sell in a competitive market. The market cares only about outputs and receives credible information solely through the ratings assigned by a public test. Aiming to maximize expected output, the test designer may base ratings on inputs, outputs, or any combination of the two. Although both the market and the designer ultimately care only about outputs, output-only tests are always dominated because they allow high-productivity agents to ``coast on their talent" and pass with minimal input. By contrast, input-only tests best incentivize input investments across all types and are optimal if the designer can coordinate the market and agents on her preferred equilibrium. Yet input tests are fragile: because they provide no guarantee on output, which still depends on type, they are vulnerable to no-investment equilibria. To balance robustness to adverse equilibria with input incentive provision, the designer adopts tests that optimally combine input and output components. For pass-fail tests, the optimal design takes the form of a \emph{step test} with one input threshold and two output thresholds: agents pass either by meeting the higher output bar or by satisfying the minimum output requirement along with the input threshold.

I study a continuous-time moral hazard problem with learning about a two-stage project of unknown quality. The first-stage arrival time is informative but not conclusive about the project’s quality. Due to the informativeness, the optimal contract features a combination of continuation value and intermediate bonus payments as a reward. There is a negative correlation between the first success time and the share of bonus payments in the reward. Second-stage deadlines adjust to the first-stage success time: early successes are rewarded with longer deadlines in the second stage. When agent replacement between stages is possible, the principal will replace the agent if the first success arrives late.

We study Airbnb hosts' strategic pricing incentives when prices affect ratings. Two channels determine the price-rating interaction: higher prices reduce the value for money, worsening ratings, but increase the taste-based valuation of travelers, improving ratings. The price further determines the frequency of rating updates through its effect on demand. Our empirical results show a dominant value-for-money effect and that hosts lower their prices to surpass rating thresholds. We provide evidence that hosts benefit from low entry prices: offering a median entry discount of seven percent improves medium-run monthly revenues by three percent.

A seller serving two generations of short lived heterogeneous consumers sells a product under uncertain demand. We characterize the seller's optimal pricing, taking into account that the current period's price affects the information transmission to the next period consumers via consumer ratings. While the seller always prefers to generate more information, it is not necessarily in the consumers' interest. We characterize situations in which consumer surplus and welfare are decreasing in additional information. We provide conditions under which aggregate consumer surplus and welfare are lower with than without a rating system.

We study competitive awarding procedures of short haul railway passenger services in Germany from 1995 to 2011 by means of a newly collected data set. In particular, we use regression techniques to investigate the determinants of the number of bidders, the identity of the winning bidder and the subsidy level. We find that there are more bidders when the contract duration is high and the revenue risk low. The dominant operator is more likely to win contracts if it is the incumbent, the network is large, the contract duration is high, when used rolling stock is admitted and when there are few other bidders.