The Review of Economic Studies is one of the core journals in economics. It is essential reading for economists, consistently ranking among the top five journals.

When employers face a trade-off between being large and paying low wages—and in this sense have monopsony power—some productive employers decide against building large business networks, forgo sales, and remain small. These decisions have adverse consequences for aggregate labor productivity.

We show that the financial sector’s asset supply elasticities are sufficient statistics summarizing its macroeconomic effects for a large class of financial frictions. These elasticities are crucial for a wide range of policy questions, ranging from the size of fiscal multipliers to the relative effectiveness of asset purchases targeting the financial sector versus tax cuts targeting households.

We study the effect of risk on how firms organize their supply chains. We use transaction-level data on U.S. manufacturing imports to construct a novel measure of input sourcing risk based on the historical volatility of ocean shipping times. Our measure isolates the unexpected component of shipping times that is induced by weather conditions along more than 331,000 maritime routes.

Linear instrumental variable estimators, such as two-stage least squares (TSLS), are commonly interpreted as estimating non-negatively weighted averages of causal effects, referred to as local average treatment effects (LATEs). We examine whether the LATE interpretation actually applies to the types of TSLS specifications that are used in practice. We show that if the specification includes covariates—which most empirical work does—then the LATE interpretation does not apply in general.

Economists are often interested in the mechanisms by which a treatment affects an outcome. We develop tests for the “sharp null of full mediation” that a treatment D affects an outcome Y only through a particular mechanism (or set of mechanisms) M. Our approach exploits connections between mediation analysis and the econometric literature on testing instrument validity.

This paper combines new data and a narrative approach to identify variation in political pressure on the Federal Reserve. From archival records, I build a data set of personal interactions between U.S. Presidents and Fed officials between 1933 and 2016. Since personal interactions do not necessarily reflect political pressure, I develop a narrative identification strategy based on President Nixon’s pressure on Fed Chair Burns. I exploit this narrative through restrictions on a structural vector autoregression that includes the President-Fed interaction data.