Recovery of causal relationships in data is an essential part of scholarly inquiry in the social sciences. This chapter discusses strategies that have been successfully used in urban and regional economics for recovering such causal relationships. Essential to any successful empirical inquiry is...

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...

U.S. invention has become increasingly concentrated around major tech centers since the 1970s, with implications for how much cities across the country share in concomitant local benefits. Is invention becoming a winner-takes-all race? We explore the rising spatial concentration of patents and...

Does a location's growth benefit or suffer from being geographically close to large economic centers? Spatial proximity may lead to competition and hurt growth, but it may also improve market access and enhance growth. Using data on U.S. counties and metro areas for the period 1840-2017, we...

We measure the importance of increasing returns to scale and trade in medical services. Using Medicare claims data, we document that "imported" medical care -- services produced by a medical provider in a different region -- constitute about one-fifth of US healthcare consumption. Larger regions...

Between 1880 and 1920, the US agricultural employment share fell from 50% to 25%. However, despite aggregate demand shifting away from their sector of specialization, rural labor markets saw faster wage growth and industrialization than non-agricultural parts of the US. We propose a spatial...

We evaluate how anticipation and adaptation shape the aggregate and local costs of climate change. We develop a dynamic spatial model of the U.S. economy and its 3,143 counties that features costly forward-looking migration and capital investment decisions. Recent methodological advances that...

We use restricted-access, geocoded data on the near-universe of workers in 23 U.S. states in order to quantify the impact of wind energy development on local earnings and employment, by race, ethnicity, sex, and educational attainment. We find the largest relative impacts for workers without a...

We provide a spatial theory of clean growth to assess the global impact of the rise of renewable energy. We model the details of the combined production and transmission network of electricity ("the grid") that determine the supply and losses of energy in space. The local rate of clean energy...

We conduct a benefit-cost analysis of a U.S. child allowance, based on a systematic literature review of the highest quality available causal evidence on the short- and long-term effects of cash and near-cash transfers. In contrast to the previous studies we synthesize, which tend to measure a...