From page 417-- "Economists have long been interested in explaining the observed instability of economic aggregates. Though several reasons for variation in the pace of production are easily given, such as exogenous variation in tastes or in production possibilities, it it hard to see why there should be large variations in those factors that are synchronized across the entire economy. Instead , it seems more likely to suppose that variations in demand or in production costs in different parts of the economy should be largely independent and hence that a law of large numbers would imply that significant variations in aggregate activity (relative to the typical size of aggregate activity) are not likely to occur. ... Here we explore another type of explanation, which relies on an entirely different mechanism. Our proposal is that the effects of many small independent shocks to different sectors of the economy need not cancel out in the aggregate, due to the presence of significantly nonlinear, strongly localized interactions between different parts of the economy. The type of macroscopic instability that can result has been studied by condensed-matter physicists, under the name of 'self-organized criticality' (Per Bak and Kan Chen, 1991)."

In this article, the authors measure and interpret the common 'factors' that describe money market returns. Results are presented for both three- and four-factor models. The authors find that the three-factor model explains, on average, 86 percent of the total variation in most money market returns while the four-factor model explains, on average, 90 percent of this variation. Using mimicking portfolios, they provide an interpretation of the systematic risks represented by these factors.

U.S. beef cattle stocks are among the most periodic economic time series. A theory of cattle cycles is constructed on the basis of breeding stock inventory decisions. The low fertility rate of cows and substantial lags and future feedback between fertility and consumption decisions cause the demographic structure of the herd to respond cyclically to exogenous shocks in demand and production costs. Known demographic parameters of cattle imply sharp numerical benchmarks for the resulting dynamic system and closely compare with independent econometric time-series estimates over the 1875-1990 period. The model fits extremely well.

We create an analytical structure that reveals the long-run risk-return relationship for nonlinear continuous-time Markov environments. We do so by studying an eigenvalue problem associated with a positive eigenfunction for a conveniently chosen family of valuation operators. The members of this family are indexed by the elapsed time between payoff and valuation dates, and they are necessarily related via a mathematical structure called a semigroup. We represent the semigroup using a positive process with three components: an exponential term constructed from the eigenvalue, a martingale, and a transient eigenfunction term. The eigenvalue encodes the risk adjustment, the martingale alters the probability measure to capture long-run approximation, and the eigenfunction gives the long-run dependence on the Markov state. We discuss sufficient conditions for the existence and uniqueness of the relevant eigenvalue and eigenfunction. By showing how changes in the stochastic growth components of cash flows induce changes in the corresponding eigenvalues and eigenfunctions, we reveal a long-run risk-return trade-off.

Continuous-time Markov processes can be characterized conveniently by their infinitesimal generators. For such processes there exist forward and reverse-time generators. We show how to use these generators to construct moment conditions implied by stationary Markov processes. Generalized method of moments estimators and tests can be constructed using these moment conditions. The resulting econometric methods are designed to be applied to discrete-time data obtained by sampling continuous-time Markov processes.

In models of trading with heterogeneous beliefs following Harrison‐Kreps, short selling is prohibited and agents face constant marginal costs‐of‐carry. The resale option guarantees that prices exceed buy‐and‐hold prices and the difference is identified as a bubble. We propose a model where risk‐neutral agents face asymmetric increasing marginal costs on long and short positions. Here, agents also value an option to delay, and a Hamilton‐Jacobi‐Bellman equation quantifies the influence of costs on prices. An unexpected decrease in shorting costs may deflate a bubble, linking financial innovations that facilitated shorting of mortgage‐backed securities to the collapse of prices.

Motivated by the behavior of asset prices, trading volume, and price volatility during episodes of asset price bubbles, we present a continuous-time equilibrium model in which overconfidence generates disagreements among agents regarding asset fundamentals. With short-sale constraints, an asset buyer acquires an option to sell the asset to other agents when those agents have more optimistic beliefs. As in a paper by Harrison and Kreps, agents pay prices that exceed their own valuation of future dividends because they believe that in the future they will find a buyer willing to pay even more. This causes a significant bubble component in asset prices even when small differences of beliefs are sufficient to generate a trade. In equilibrium, bubbles are accompanied by large trading volume and high price volatility. Our analysis shows that while Tobin's tax can substantially reduce speculative trading when transaction costs are small, it has only a limited impact on the size of the bubble or on price volatility.

We propose an incentive-based theory of how a savings glut produces financial fragility. Originators must be incentivized to produce high-quality assets. Assets are distributed to informed intermediaries or uninformed investors. A savings glut reduces origination incentives by compressing spreads between the prices paid for high-quality assets by informed intermediaries and prices paid by uninformed investors for generic assets. The narrowing of spreads relaxes intermediaries’ borrowing constraints, resulting in higher leverage. This generates financial fragility: intermediaries are more likely to become insolvent if unforeseen losses arise. Our model offers a coherent narrative of the run-up to the Global Financial Crisis.

Climate finance is the study of local and global financing of public and private investment that seeks to support mitigation of and adaptation to climate change. In 2017, the Review of Financial Studies launched a competition among scholars to develop research proposals on the topic with the goal of publishing this special volume. We describe the competition, how the nine projects featured in this volume came to be published, and frame their findings within what we view as a broader climate finance research program.