This paper examines long-run development effects of regional productivity shocks in the United States. We exploit the timing and location of large resource discoveries to measure exogenous variation in the demand for labor and consider heterogeneous effects created by environmental and geographic features of the discovery site. Doing so requires developing novel, geographically delineated measures of both amenity value and geographic isolation. Using a dynamic event-study analysis we find that resource discoveries cause population to swell both in the short and long-run (e.g., fifty years), though this effect is largely driven by discoveries in unfavorable locations that either suffer from low natural amenity value or geographic isolation. The event study is complemented by a cross-sectional analysis of a broader set of modern-day economic outcomes that generally offers consistent results. This paper highlights the importance of considering environmental characteristics of a place when examining the influence of regional economic shocks and offers insights about the observed spatial pattern of development in the United States.
We show that the synthetic control algorithm can have a systematic bias in a set of panel data settings commonly employed in empirical research. The bias comes from matching to idiosyncratic error terms (noise) in the treated unit and the donor units' pre-treatment outcome values. This in turn leads to a biased counterfactual for the post-treatment periods. We use a Monte Carlo analysis to illustrate the determinants of the bias in terms of error term variance, sample characteristics and DGP complexity. We present two procedures to reduce the bias: one based on a specification for the matching variables that includes estimates of unit-level polynomial trend parameters, and the other a direct computational bias-correction procedure based on re-sampling from a pilot model. Both of these can reduce the bias in empirically feasible implementations. However, both corrections increase the sampling variance and mean-squared error in our simulations relative to a baseline of matching on all pre-period outcome values.
Theoretical links between sex ratio imbalance and risky sexual activity are well-established, but empirically establishing causal links remains elusive. This paper uses the U.S. fracking boom as a plausibly exogenous and persistent shifter of the sex ratio in certain regions to evaluate the impact on STI transmission and prostitution activity, as measured by online prostitution review counts. We first document significant and robust positive effects on Gonorrhea rates in fracking counties at the national level, though we find no evidence of increases in prostitution. We then perform a series of case studies focusing on remote, high-fracking production areas that experienced large increases in sex ratios due to male in-migration. Using both synthetic controls and two-way fixed effects models with randomization inference, we find large effects on both Gonorrhea transmission and prostitution reviews in North Dakota. For other remote, high-production areas we observe positive effects for both outcomes, though the evidence is somewhat mixed. This study highlights public health concerns with lasting effects relating to occupational conditions that alter the local demographic composition in the direction of less gender parity.
"Geographic Dispersion of Economic Shocks: Evidence from the Fracking Revolution: Comment", with Alexander James, American Economic Review (forthcoming).
Feyrer, Mansur and Sacerdote (2017) estimate the spatial dispersion of the effects of the recent shale-energy boom by unconditionally regressing income and employment on energy production at various levels of geographic aggregation. However, producing counties tend to be located near each other and receive inward spillovers from neighboring production. This inflates the estimated effect of own-county production and spatial aggregation does not address this. We propose an alternative estimation strategy that accounts for these spillovers and identify reduced propagation effects. The proposed estimation strategy can be applied more generally to estimate the dispersion of multiple, simultaneously occurring economic shocks.
"Measuring Inequality", with with Thomas McGregor and Samuel Wills, Oxford Review of Economic Policy.
Inequality is important, both for its own sake and for its political, social, and economic implications. However, measuring inequality is not straightforward, as it requires decisions to be made on the variable, population, and distributional characteristics of interest. These decisions will naturally influence the conclusions that are drawn so they must be closely linked to an underlying purpose, which is ultimately defined by a social welfare function. This paper outlines important considerations when making each of these decisions, before surveying recent advances in measuring inequality and suggesting avenues for future work. "Dutch Disease and the Oil Boom and Bust", Canadian Journal of Economics, 2019. (working paper version)
This paper examines the impact of the oil price boom in the 1970s and the subsequent bust on non-oil economic activity in oil-dependent countries. During the boom, manufacturing exports and value added increased significantly relative to non-oil dependent countries, along with wages, employment, and capital formation. These measures decreased, though to a lesser and more gradual extent, during the bust and subsequent period of low prices, displaying a positive relationship with oil prices. However, exports of agricultural products sharply decreased during the boom. Imports of all types of goods displayed strong pro-cyclicality with respect to oil prices. The results suggest that increased local demand and investment spillovers induced by the oil revenue windfall resulted in increased manufacturing activity.
How are oil revenues shared throughout society? We combine high-resolution geo-coded data on night-time lights and population to construct global measures of rural poverty from 2000-2013. We find that oil booms, due either to high prices or new discoveries, increase light intensity and GDP. However, the increase in output is limited to cities and towns, with no evidence that it benefits the rural poor. We also find that while urbanization is occurring throughout the developing world, there is no evidence that it is hastened by oil wealth.
Over the past decade, the production of tight oil and shale gas significantly increased in the United States. This paper uniquely examines how this energy boom has affected regional crime rates throughout the United States. There is evidence that, as a result of the ongoing shale-energy boom, shale-rich counties experienced faster growth in rates of both property and violent crimes including rape, assault, murder, robbery, burglary, larceny and grand-theft auto. These results are particularly robust for rates of assault, and less so for other types of crimes. Examining the migratory behavior of convicted sex offenders indicates that boomtowns disproportionately attract convicted felons. Policy makers should anticipate these effects and invest in public infrastructure accordingly.
This paper evaluates the impact of major natural resource discoveries since 1950 on GDP per capita. Using panel fixed-effects estimation and resource discoveries in countries that were not previously resource-rich as a plausibly exogenous source of variation, I find a positive effect on GDP per capita levels following resource exploitation that persists in the long term. Results vary significantly between OECD and non-OECD treatment countries, with effects concentrated within the non-OECD group. I further test GDP effects with synthetic control analysis on each individual treated country, yielding results consistent with the average effects found with the fixed-effects model.
Gregory Clark argued in A Farewell to Alms that preindustrial societies, including England, were Malthusian. Day wages show incomes were trendless: as high in Europe in the medieval era as in 1800, even in England. The opposed view is that England and the Netherlands grew substantially from 1200 to 1800. Early day wages overestimate living standards. Here we show that preindustrial farm employment shares can be estimated from probate occupation reports. These imply only 60 percent employed in farming in England in 1560–1579 and 1653–1660, consistent with the high incomes indicated by wages. Day wages do measure preindustrial living standards.
"Terrorist Attacks and Nationalist Voting Share in European Elections", with Giovanni Peri and Daniel Rees.