We summarize existing empirical findings regarding the adoption of robotics and AI and its effects on aggregated labor and productivity, and argue for more systematic collection of the use of these technologies at the firm level. Existing empirical work primarily uses statistics aggregated by...

This paper, which introduces the special issue on corporate governance co-sponsored by the Review of Financial Studies and the National Bureau of Economic Research (NBER), reviews and comments on the state of corporate governance research. The special issue features seven papers on corporate...

In this chapter, we discuss field experiments in surveys that are conducted with the purpose of learning about expectation formation and the link between expectations and behavior. We begin by reviewing the rationale for conducting experiments within surveys, rather than just relying on...

Audit correspondence studies are field experiments that test for discriminatory behavior in active markets. Researchers measure discrimination by comparing how responsive individuals ("audited units") are to correspondences from different types of people. This paper elaborates on the tradeoffs...

Economic data engineering deliberately designs novel forms of data to solve fundamental identification problems associated with economic models of choice. I outline three diverse applications: to the economics of information; to life-cycle employment, earnings, and spending; and to public policy...

Linear panel models, and the "event-study plots" that often accompany them, are popular tools for learning about policy effects. We discuss the construction of event-study plots and suggest ways to make them more informative. We examine the economic content of different possible identifying...

This paper tests the retrieved context model of Wachter and Kahana (2019) using a long-term panel of economic forecasts by participants in the Livingston Survey. Events in historical time contribute additional explanatory power to a relative time series model. Historical precedents for current...

In many health domains, we are concerned that observed links - for example, between "healthy" behaviors and good outcomes - are driven by selection into behavior. This paper considers the additional factor that these selection patterns may vary over time. When a particular health behavior...

We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premia. We demonstrate large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based...

Over the last two decades, there has been a surge of opioid-related overdose deaths resulting in a myriad of state policy responses. Researchers have evaluated the effectiveness of such policies using a wide-range of statistical models, each of which requires multiple design choices that can...