This paper incorporates a time-varying intensity of disasters in the Rietz-Barro hypothesis that risk premia result from the possibility of rare, large disasters. During a disaster, an asset's fundamental value falls by a time-varying amount. This in turn generates time-varying risk premia and thus volatile asset prices and return predictability. Using the recent technique of linearity-generating processes (Gabaix 2007), the model is tractable, and all prices are exactly solved in closed form. In the "variable rare disasters" framework, the following empirical regularities can be understood qualitatively: (i) equity premium puzzle (ii) risk-free rate-puzzle (iii) excess volatility puzzle (iv) predictability of aggregate stock market returns with price-dividend ratios (v) value premium (vi) often greater explanatory power of characteristics than covariances for asset returns (vii) upward sloping nominal yield curve (viiii) a steep yield curve predicts high bond excess returns and a fall in long term rates (ix) corporate bond spread puzzle (x) high price of deep out-of-the-money puts. I also provide a calibration in which those puzzles can be understood quantitatively as well. The fear of disaster can be interpreted literally, or can be viewed as a tractable way to model time-varying risk-aversion or investor sentiment.

This article defines and analyzes a “sparse max” operator, which is a less than fully attentive and rational version of the traditional max operator. The agent builds (as economists do) a simplified model of the world which is sparse, considering only the variables of first-order importance. His stylized model and his resulting choices both derive from constrained optimization. Still, the sparse max remains tractable to compute. Moreover, the induced outcomes reflect basic psychological forces governing limited attention. The sparse max yields a behavioral version of basic chapters of the microeconomics textbook: consumer demand and competitive equilibrium. I obtain a behavioral version of Marshallian and Hicksian demand, Arrow-Debreu competitive equilibrium, the Slutsky matrix, the Edgeworth box, Roy’s identity, and so on. The Slutsky matrix is no longer symmetric: nonsalient prices are associated with anomalously small demand elasticities. Because the consumer exhibits nominal illusion, in the Edgeworth box, the offer curve is a two-dimensional surface rather than a one-dimensional curve. As a result, different aggregate price levels correspond to materially distinct competitive equilibria, in a similar spirit to a Phillips curve. The Arrow-Debreu welfare theorems typically do not hold. This framework provides a way to assess which parts of basic microeconomics are robust, and which are not, to the assumption of perfect maximization.

This paper proposes that idiosyncratic firm-level shocks can explain an important part of aggregate movements and provide a microfoundation for aggregate shocks. Existing research has focused on using aggregate shocks to explain business cycles, arguing that individual firm shocks average out in the aggregate. I show that this argument breaks down if the distribution of firm sizes is fat-tailed, as documented empirically. The idiosyncratic movements of the largest 100 firms in the United States appear to explain about one-third of variations in output growth. This “granular” hypothesis suggests new directions for macroeconomic research, in particular that macroeconomic questions can be clarified by looking at the behavior of large firms. This paper's ideas and analytical results may also be useful for thinking about the fluctuations of other economic aggregates, such as exports or the trade balance.

This paper analyzes how bounded rationality affects monetary and fiscal policy via an empirically relevant enrichment of the New Keynesian model. It models agents’ partial myopia toward distant atypical events using a new microfounded “cognitive discounting” parameter. Compared to the rational model, (i) there is no forward guidance puzzle; (ii) the Taylor principle changes: with passive monetary policy but enough myopia equilibria are determinate and economies stable; (iii) the zero lower bound is much less costly; (iv) price-level targeting is not optimal; (v) fiscal stimulus is effective; (vi) the model is “ neo-Fisherian” in the long run, Keynesian in the short run. (JEL E12, E31, E43, E52, E62, E70)

A central difficulty in economics is to create a model with both good business cycle properties and asset pricing properties. I show how to solve this difficulty by a simple portable modeling device: the “disasterization” of models. Take an economy with good business cycle properties and create a new, “disasterized” economy, which is essentially identical to the original one except that disasters can destroy part of the capital stock and productivity. In such a disasterized economy, asset prices exhibit high and volatile risk premia, but macro variables remain unchanged. Perturbations of this benchmark allow for feedback from finance to macro.

[This article presents a market equilibrium model of CEO assignment, pay, and incentives under risk aversion and moral hazard. Each of the three outcomes can be summarized by a single closed-form equation. In the presence of moral hazard, assignment is distorted from positive assortative matching on firm size as firms with higher risk or disutility choose less talented CEOs. Such firms also pay higher salaries in the cross-section, but economy-wide increases in risk or the disutility of being a CEO do not affect pay. The strength of incentives depends only on the disutility of effort and is independent of risk and risk aversion. If the CEO can affect firm risk, incentives rise and are increasing in risk and risk aversion. We calibrate the losses from various forms of poor corporate governance, such as failures in monitoring and inefficiencies in CEO assignment.]

[This article develops a framework that delivers tractable (i.e., closed-form) optimal contracts, with few restrictions on the utility function, cost of effort, or noise distribution. By modeling the noise before the action in each period, we force the contract to provide correct incentives state-by-state, rather than merely on average. This tightly constraints the set of admissible contracts and allows for a simple solution to the contracting problem. Our results continue to hold in continuous time, where noise and actions are simultaneous. We illustrate the potential usefulness of our setup by a series of examples related to CEO incentives. In particular, the model derives predictions for the optimal measure of incentives and whether the contract should be convex, concave, or linear.]

We propose a new model of exchange rates, based on the hypothesis that the possibility of rare but extreme disasters is an important determinant of risk premia in asset markets. The probability of world disasters as well as each country’s exposure to these events is time-varying. This creates joint fluctuations in exchange rates, interest rates, options, and stock markets. The model accounts for a series of major puzzles in exchange rates: excess volatility and exchange rate disconnect, forward premium puzzle and large excess returns of the carry trade, and comovements between stocks and exchange rates. It also makes empirically successful signature predictions regarding the link between exchange rates and telltale signs of disaster risk in currency options.