We introduce a new methodology to detect and measure economic activity using geospatial data and apply it to steel production, a major industrial pollution source worldwide. Combining plant output data with geospatial data, such as ambient air pollutants, nighttime lights, and temperature, we...

In applied historical research, geographic units often differ in level of aggregation across datasets. One solution is to use crosswalks that associate factors located within one geographic unit to another, based on their relative areas. We develop an alternative approach based on relative...

Since 1980, US wage growth has been fastest in large cities. Empirically, we show that most of this urban-biased growth reflects wage growth at large Business Services firms, which are also the most intensive users of information and communications technology (ICT) capital in the US economy. We...

Previous research finds that the greater geographic mobility of foreign than native-born workers following economic shocks helps to facilitate local labor market adjustment to shifting regional economic conditions. We examine the role that immigration may have played in enabling U.S. commuting...

Fatal school shootings often spark support for stricter gun laws, threatening the gun lobby's influence and agenda. To prevent political fallout, do pro-gun Political Action Committees increase contributions after fatal school shootings? Leveraging a novel dataset of pro-gun PAC contributions...

We study two-way-fixed-effects regressions (TWFE) with several treatment variables. Under a parallel trends assumption, we show that the coefficient on each treatment identifies a weighted sum of that treatment's effect, with possibly negative weights, plus a weighted sum of the effects of the...

Standard methods for estimating production functions in the Olley and Pakes (1996) tradition require assumptions on input choices. We introduce a new method that exploits (increasingly available) data on a firm's expectations of its future output and inputs that allows us to obtain consistent...

We study a difference-in-differences (DiD) framework where groups experience unequal treatment statuses in the pre-policy change period. This approach is commonly employed in empirical studies but it contradicts the canonical model's assumptions. We show that in such settings, the standard DiD...

This paper develops a new algorithm for detecting US recessions in real time. The algorithm constructs millions of recession classifiers by combining unemployment and vacancy data to reduce detection noise. Classifiers are then selected to avoid both false negatives (missed recessions) and false...

We develop a dynamic macroeconomic model in which the secular decline in real interest rates arises endogenously from rising wealth inequality. Challenging the standard "safe asset shortage" hypothesis, the model shows how falling real rates can coexist with a stable safe asset ratio--closely...