In housing markets, neighborhood characteristics are a key source of information heterogeneity: sellers are usually better informed about neighborhood values than buyers are, but some sellers and buyers are better informed than their peers are. Consistent with predictions from a new framework for analyzing such markets with heterogeneous assets and differentially informed agents, we find that changes in the composition of sellers toward more informed sellers and sellers with a larger supply elasticity predict subsequent house price declines. This effect is larger for houses with more price exposure to neighborhood characteristics, and smaller for houses bought by buyers that are more informed.

I define a notion of competitive equilibrium for asset markets where assets are heterogeneous and traders have heterogenoeus information about them. Markets are defined by a price and a procedure for clearing trades. Any asset can in principle be traded in any market but traders can use their information to impose acceptance rules which specify which goods they are willing to trade in each market. I then apply this notion to a model of distressed sales under asymmetric information and examine whether it can account for fire sales: sharp drops in prices when distressed agents need to sell assets. Standard models of asymmetric information with informed sellers, heterogenous assets and identical uninformed buyers predict the opposite phenomenon, as more distressed sellers on average sell less-adversely-selected pools of assets. With heterogeneity among buyers in their ability to distinguish assets of different qualities, the possibility of fire sales depends on the joint distribution of wealth and ability.

I study expertise acquisition in a model of trading under asymmetric information. I propose and implement a method to measure r, the ratio of the marginal social value to the marginal private value of expertise. This can be decomposed into three sufficient statistics: traders’ average profits, the fraction of bad assets among traded assets, and the elasticity of good assets traded with respect to capital inflows. I measure r = 0.16 for the junk bond underwriting market. Since this is less than 1, it implies that marginal investments in expertise destroy surplus.

I study a dynamic economy featuring adverse selection in asset markets. Borrowing constrained entrepreneurs sell past projects to finance new investment, but asymmetric information creates a lemons problem. I show that this friction is equivalent to a tax on financial transactions. The implicit tax rate responds to aggregate shocks, generating amplification in the response of investment and cyclical variation in liquidity.

This paper proposes a theory of liquidity dynamics. Illiquidity results from asymmetric information. Observing the historical track record teaches agents how to interpret public information and helps overcome information asymmetry. However, an illiquidity trap can arise: too much asymmetric information leads to the breakdown of trade, which interrupts learning and perpetuates illiquidity. Liquidity falls in response to unexpected events that lead agents to question their valuation models (especially in newer markets) may be slow to recover after a crisis, and is higher in periods of stability.

We study competitive equilibria in a signalling economy with heterogeneously informed buyers. In terms of the classic Spence (1973, The Quarterly Journal of Economics, 87, 355—374) model of job market signalling, firms have access to direct but imperfect information about worker types, in addition to observing their education. Firms can be ranked according to the quality of their information, i.e., their expertise. In equilibrium, some high-type workers forgo signalling and are hired by better informed firms, which make positive profits. Workers’ education decisions and firms’ use of their expertise are strategic complements, allowing for multiple equilibria that can be Pareto ranked. We characterize wage dispersion and the extent of signalling as a function of the distribution of expertise among firms. Our model can also be applied to a variety of other signalling problems, including securitization, corporate financial structure, insurance markets, or dividend policy.

We use equity returns to construct a time-varying measure of the zero-beta interest rate: the expected return of a stock portfolio orthogonal to the stochastic discount factor. In contrast to safe rates, the zero-beta rate fits the aggregate consumption Euler equation remarkably well both unconditionally and conditional on monetary policy shocks and is high, volatile, and persistent enough to explain the average return and most of the volatility of the market portfolio. The puzzle is why safe rates are so low, stable, and disconnected from both consumption and the zero-beta rate.

In housing markets, neighborhood characteristics are a key source of information heterogeneity: sellers are usually better informed about neighborhood values than buyers are, but some sellers and buyers are better informed than their peers are. Consistent with predictions from a new framework for analyzing such markets with heterogeneous assets and differentially informed agents, we find that changes in the composition of sellers toward more informed sellers and sellers with a larger supply elasticity predict subsequent house price declines. This effect is larger for houses with more price exposure to neighborhood characteristics, and smaller for houses bought by buyers that are more informed.