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We document that seasonal temperatures have significant and systematic effects on the U.S. economy, both at the aggregate level and across a wide cross section of economic sectors. This effect is particularly strong for the summer: a 1°F increase in the average summer temperature is associated with a reduction in the annual growth rate of state-level output of 0.15 to 0.25 percentage points. We combine our estimates with projected increases in seasonal temperatures and find that rising temperatures could reduce U.S. economic growth by up to one-third over the next century.

We propose an equilibrium model that can explain a wide range of international finance puzzles, including the high correlation of international stock markets, despite the lack of correlation of fundamentals. We conduct an empirical analysis of our model, which combines cross-country-correlated long-run risk with Epstein and Zin preferences, using U.S. and U.K. data, and show that it successfully reconciles international prices and quantities, thereby solving the international equity premium puzzle. These results provide evidence suggesting a link between common long-run growth perspectives and exchange rate movements.

Although weather has been shown to affect financial markets and financial decision making, a still open question is the channel through which such influence is exerted. By employing a multiple price list method, this paper provides direct experimental evidence that sunshine and good weather promote risk-taking behavior. This effect is present whether relying on objective measures of meteorological conditions or subjective weather assessments. Finally, employing a psychological test, we find evidence that weather may affect individual risk tolerance through its effect on mood.

We propose a new entropy-based correlation measure (coentropy) to evaluate the performance of international asset pricing models. Coentropy captures the codependence of two random variables beyond normality. We document that the coentropy of international stochastic discount factors (SDFs) can be decomposed into a series of entropy-based correlations of permanent and transitory components of the SDFs. We employ the cross section of G-10 countries to obtain model-free estimates of all the components of coentropy at various horizons and we show that the generalization of the long-run risk model featuring two predictable components of consumption growth rates, global disasters, and recursive preferences can account for the composition of codependence at all horizons. This paper was accepted by Tomasz Piskorski, finance.

Focusing on data from the United States and the United Kingdom, we document that both the anomaly identified by Backus and Smith, which concerns the low correlation between consumption differentials and exchange rates, and the forward premium anomaly, which concerns the tendency of high interest rate currencies to appreciate, have become more severe over time. Taking into account different capital mobility regimes, we show that these anomalies turn into general equilibrium regularities in a two-country and two-good economy with Epstein and Zin preferences, frictionless markets, and correlated long-run growth prospects.

We document that the first and third cross-sectional moments of the distribution of GDP growth rates made by professional forecasters can predict equity excess returns, a finding that is robust to controlling for a large set of well-established predictive factors. We show that introducing time-varying skewness in the distribution of expected growth prospects in an otherwise standard endowment economy can substantially increase the model-implied equity Sharpe ratios, and produce a large amount of fluctuation in equity risk premiums.

We study how a concern for robustness modifies a policymaker's incentive to experiment. A policymaker has a prior over two submodels of inflation-unemployment dynamics. One submodel implies an exploitable trade-off, the other does not. Bayes' law gives the policymaker an incentive to experiment. The policymaker fears that both submodels and his prior probability distribution over them are misspecified. We compute decision rules that are robust to misspecifications of each submodel and of the prior distribution over submodels. We compare robust rules to ones that Cogley, Colacito, and Sargent (2007) computed assuming that the models and the prior distribution are correctly specified. We explain how the policymaker's desires to protect against misspecifications of the submodels, on the one hand, and misspecifications of the prior over them, on the other, have different effects on the decision rule.

We study the response of international investment flows to short- and long-run growth news. Among developed G7 countries, positive long-run news for domestic productivity induces a net outflow of investments, in contrast to the effects of short-run growth shocks. We document that a standard Backus, Keho, and Kydland (1994) (BKK) model fails to reproduce this novel empirical evidence. We augment this model with Epstein and Zin (1989) preferences (EZ-BKK) and characterize the resulting recursive risk-sharing scheme. The response of international capital flows in the EZ-BKK model is consistent with the data.

A policy maker knows two models. One implies an exploitable inflation-unemployment trade-off, the other does not. The policy maker's prior probability over the two models is part of his state vector. Bayes' law converts the prior probability into a posterior probability and gives the policy maker an incentive to experiment. For models calibrated to U.S. data through the early 1960s, we compare the outcomes from two Bellman equations. The first tells the policy maker to \"experiment and learn.\" The second tells him to \"learn but don't experiment.\" In this way, we isolate a component of government policy that is due to experimentation and estimate the benefits from intentional experimentation. We interpret the Bellman equation that learns but does not intentionally experiment as an \"anticipated utility\" model and study how well its outcomes approximate those from the \"experiment and learn\" Bellman equation. The approximation is good. For our calibrations, the benefits from purposeful experimentation are small because random shocks are big enough to provide ample unintentional experimentation.

We characterize the equilibrium of a two-country, two-good economy in which agents have opposite preference bias toward one of the two consumption goods and fear model misspecification. We document that disagreement about endowments' growth prospects is a persistent endogenous outcome of this class of economies.