Separate literatures study violations of uncovered interest parity (UIP) using regression-based and portfolio-based methods. We propose a decomposition of these violations into a cross-currency, a between-time-and-currency, and a cross-time component that allows us to analytically relate regression-based and portfolio-based facts and to estimate the joint restrictions they put on models of currency returns. Subject to standard assumptions on investors’ information sets, we find that the forward premium puzzle (FPP) and the “dollar trade” anomaly are intimately linked: both are driven almost exclusively by the cross-time component. By contrast, the “carry trade” anomaly is driven largely by cross-sectional violations of UIP. The simplest model that the data do not reject features a cross-sectional asymmetry that makes some currencies pay permanently higher expected returns than others, and larger time series variation in expected returns on the U.S. dollar than on other currencies. Importantly, conventional estimates of the FPP are not directly informative about expected returns because they do not correct for uncertainty about future mean interest rates. Once we correct for this uncertainty, we never reject the null that investors expect high-interest-rate currencies to depreciate, not appreciate.

Since the 1972 U.S. Clean Water Act, government and industry have invested over |$|1 trillion to abate water pollution, or |$|100 per person-year. Over half of U.S. stream and river miles, however, still violate pollution standards. We use the most comprehensive set of files ever compiled on water pollution and its determinants, including 50 million pollution readings from 240,000 monitoring sites and a network model of all U.S. rivers, to study water pollution’s trends, causes, and welfare consequences. We have three main findings. First, water pollution concentrations have fallen substantially. Between 1972 and 2001, for example, the share of waters safe for fishing grew by 12 percentage points. Second, the Clean Water Act’s grants to municipal wastewater treatment plants, which account for |$|650 billion in expenditure, caused some of these declines. Through these grants, it cost around |$|1.5 million (2014 dollars) to make one river-mile fishable for a year. We find little displacement of municipal expenditure due to a federal grant. Third, the grants’ estimated effects on housing values are smaller than the grants’ costs; we carefully discuss welfare implications.

We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual U.S. firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing that it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firm’s actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. These results continue to hold after controlling for news about the mean (as opposed to the variance) of political shocks. Interestingly, the vast majority of the variation in our measure is at the firm level rather than at the aggregate or sector level, in the sense that it is captured neither by the interaction of sector and time fixed effects nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.