We build a general equilibrium production-based asset pricing model with heterogeneous firms that jointly accounts for firm-level and aggregate facts emphasized by the recent macroeconomic literature, and for important asset pricing moments. Using administrative firm-level data, we establish empirical properties of large negative idiosyncratic shocks and their evolution. We then demonstrate that these shocks play an important role for delivering both macroeconomic and asset pricing predictions. Finally, we combine our model with data on the universe of U.S. seaborne import since 2007, and establish the importance of supply chain disasters for the cross-section of asset prices.
We study the incidence and the optimal design of nonlinear income taxes in a Mirrleesian economy with a continuum of endogenous wages. We characterize analytically the incidence of any tax reform by showing that one can mathematically formalize this problem as an integral equation. For a CES production function, we show theoretically and numerically that the general equilibrium forces raise the revenue gains from increasing the progressivity of the U.S. tax schedule. This result is reinforced in the case of a Translog technology where closer skill types are stronger substitutes. We then characterize the optimum tax schedule, and derive a simple closed-form expression for the top tax rate. The U-shape of optimal marginal tax rates is more pronounced than in partial equilibrium. The joint analysis of tax incidence and optimal taxation reveals that the economic insights obtained for the optimum may be reversed when considering reforms of a suboptimal tax code.
We propose a theory of asset prices that emphasizes heterogeneous information as the main element determining prices of diﬀerent securities. Our main analytical innovation is in formulating a model of noisy information aggregation through asset prices, which is parsimonious and tractable, yet flexible in the speciﬁcation of cash flow risks. We show that the noisy aggregation of heterogeneous investor beliefs drives a systematic wedge between the impact of fundamentals on an asset price, and the corresponding impact on cash flow expectations. The key intuition behind the wedge is that the identity of the marginal trader has to shift for diﬀerent realization of the underlying shocks to satisfy the market-clearing condition. This identity shift ampliﬁes the impact of price on the marginal trader’s expectations. We derive tight characterization for both the conditional and the unconditional expected wedges. Our ﬁrst main theorem shows how the sign of the expected wedge (that is, the diﬀerence between the expected price and the dividends) depends on the shape of the dividend payoﬀ function and on the degree of informational frictions. Our second main theorem provides conditions under which the variability of prices exceeds the variability for realized dividends. We conclude with two applications of our theory. First, we highlight how heterogeneous information can lead to systematic departures from the Modigliani-Miller theorem. Second, in a dynamic extension of our model we provide conditions under which bubbles arise.
We study the interplay of share prices and ﬁrm decisions when share prices aggregate and convey noisy information about fundamentals to investors and managers. First, we show that the informational feedback between the ﬁrm’s share price and its investment decisions leads to a systematic premium in the ﬁrm’s share price relative to expected dividends. Noisy information aggregation leads to excess price volatility, over-valuation of shares in response to good news, and undervaluation in response to bad news. By optimally increasing its exposure to fundamental risks when the market price conveys good news, the ﬁrm shifts its dividend risk to the upside, which ampliﬁes the overvaluation and explains the premium. Second, we argue that explicitly linking managerial compensation to share prices gives managers an incentive to manipulate the ﬁrm’s decisions to their own beneﬁt. The managers take advantage of shareholders by taking excessive investment risks when the market is optimistic, and investing too little when the market is pessimistic. The ampliﬁed upside exposure is rewarded by the market through a higher share price, but is ineﬀicient from the perspective of dividend value.
This paper studies strategic information transmission in a dynamic environment where, each period, a privately informed expert sends a message and a decision maker takes an action. Our main result is that, in contrast to a static environment, full information revelation is possible. The gradual revelation of information and the eventual full revelation is supported by the dynamic rewards and punishments. The construction of a fully revealing equilibrium relies on two key features. The ﬁrst feature is that the expert is incentivized, via appropriate actions, to join separable groups in which she initially pools with far-away types, then later reveals her type. The second feature is the use of trigger strategies. The decision maker is incentivized by the reward of further information revelation if he chooses the separation-inducing actions, and the threat of a stop in information release if he does not. Our equilibrium is non-monotonic. With monotonic partition equilibria, full revelation is impossible.