We study a dynamic setting in which stochastic information (news) about the value of a privately informed seller's asset is gradually revealed to a market of buyers. We construct an equilibrium that involves periods of no trade or market failure. The no-trade period ends in one of two ways: either enough good news arrives, restoring confidence and markets reopen, or bad news arrives, making buyers more pessimistic and forcing capitulation that is, a partial sell-off of low-value assets. Conditions under which the equilibrium is unique are provided. We analyze welfare and efficiency as they depend on the quality of the news. Higher quality news can lead to more inefficient outcomes. Our model encompasses settings with or without a standard static adverse selection problem—in a dynamic setting with sufficiently informative news, reservation values arise endogenously from the option to sell in the future and the two environments have the same equilibrium structure.

We study how supply disruptions interact with monopoly pricing, inventory management, and consumer stockpiling in a continuous-time model. Preemption incentives—consumers prefer to stock up before a price hike while the firm prefers to hike before consumers stock up—lead to an equilibrium with gradual stockpiling and endogenous uncertainty over the timing of a price hike, which can trigger a run at the disruption onset. Consumer storage introduces welfare losses from randomized pricing, but can also strengthen the firm’s incentive to hold buffer stock. Rationing, price controls, and reserve mandates can each improve welfare, but only strategic government reserves can implement the social optimum.

We develop a model where some investors are uncertain whether others are trading on informative signals or noise. Uncertainty about others leads to a nonlinear price that reacts asymmetrically to news. We incorporate this uncertainty into a dynamic setting where traders gradually learn about others and show that it generates empirically relevant return dynamics: expected returns are stochastic but predictable, and volatility exhibits clustering and the “leverage” effect. The model nests both the rational expectations (RE) and differences of opinions (DO) approaches and highlights a link between disagreement about fundamentals and uncertainty about other traders.

We develop a rational theory of liquidity sentiments in which the market outcome in any given period depends on agents’ expectations about market conditions in future periods. Our theory is based on the interaction between adverse selection and resale considerations giving rise to an intertemporal coordination problem that yields multiple self-fulfilling equilibria. We construct “sentiment” equilibria in which sunspots generate fluctuations in prices, volume, and welfare, all of which are positively correlated. The intertemporal nature of the coordination problem disciplines the set of possible sentiment dynamics. In particular, sentiments must be sufficiently persistent and transitions must be stochastic. We consider an extension with production in which asset quality is endogenously determined and provide conditions under which sentiments are a necessary feature of any equilibrium. A testable implication is that assets produced in good times are of lower average quality than those produced in bad times.

We study information spillovers in a dynamic setting with correlated assets owned by privately informed sellers. In the model, a trade of one asset can provide information about the value of other assets. Importantly, the information content of trading behavior is endogenously determined. We show that this endogeneity leads to multiple equilibria when assets are sufficiently correlated. The equilibria are ranked in terms of both trade volume and efficiency. The model has implications for policies targeting post-trade transparency. We show that introducing post-trade transparency can increase or decrease welfare and trading volume depending on the asset correlation, equilibrium being played, and the composition of market participants.

We embed adverse selection into a dynamic, general equilibrium model with heterogeneous capital and study its implications for aggregate dynamics. The friction leads to delays in firms’ divestment decisions and thus slow recoveries from shocks, even when these shocks do not affect the economy’s potential output. The impediments to reallocation increase with the dispersion in productivity and decrease with the interest rate, the frequency of sectoral shocks, and households’ consumption smoothing motives. When households are risk averse, delaying reallocation serves as a hedge against future shocks, which can lead to persistent misallocation. Our model also provides a micro-foundation for convex adjustment costs and a link between the nature of these costs and the underlying economic environment.

We study a bargaining model in which a buyer makes frequent offers to a privately informed seller, while gradually learning about the seller’s type from “news.” We show that the buyer’s ability to leverage this information to extract more surplus from the seller is remarkably limited. In fact, the buyer gains nothing from the ability to negotiate a better price despite the fact that a negotiation must take place in equilibrium. During the negotiation, the buyer engages in a form of costly “experimentation” by making offers that are sure to earn her negative payoffs if accepted, but speed up learning and improve her continuation payoff if rejected. We investigate the effects of market power by comparing our results to a setting with competitive buyers. Both efficiency and the seller’s payoff can decrease by introducing competition among buyers.

We propose an information‐based theory to explain time variation in liquidity and link it to a variety of patterns in asset markets. In “normal times,” the market is fully liquid and gains from trade are realized immediately. However, the equilibrium also involves periods during which liquidity “dries up,” which leads to endogenous liquidation costs. Traders correctly anticipate such costs, which reduces their willingness to pay. This foresight leads to a novel feedback effect between prices and market liquidity, which are jointly determined in equilibrium. The model also predicts that contagious sell‐offs can occur after sufficiently bad news.

We study the optimal incentive scheme for a multistage project in which the agent privately observes intermediate progress. The optimal contract involves a soft deadline wherein the principal guarantees funding up to a certain date—if the agent reports progress at that date, then the principal gives him a relatively short hard deadline to complete the project—if progress is not reported at that date, then a probationary phase begins in which the project is randomly terminated at a constant rate until progress is reported. We explore several variants of the model with implications for optimal project design. In particular, we show that the principal benefits by imposing a small cost on the agent for submitting a progress report or by making the first stage of the project somewhat “harder” than the second.

We propose a model of due diligence and analyze its effect on prices, payoffs, and deal completion. In our model, if the seller accepts an offer, the winning bidder (or “acquirer”) can gather information and chooses when to complete the transaction. In equilibrium, the acquirer engages in “too much” due diligence. Our quantitative results suggest that the magnitude of the distortion is economically significant. Nevertheless, allowing for due diligence can improve both total surplus and the seller's payoff compared to a setting without due diligence. We use our framework to explore the timing of due diligence, bidder heterogeneity, and breakup fees.