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Some communities endure environmental hazards from abandoned mines and job loss from the energy transition away from coal. Recent US legislation provides a historic appropriation for abandoned mine hazards like the acidic water that often drains from them. Who the investment will benefit and what it will accomplish is unclear. Here we provide answers for the case of abandoned mine drainage in Pennsylvania. We find that communities most exposed to mine drainage have incomes 30 percent below that of unaffected communities and are twice as vulnerable to the energy transition. Within affected communities, exposure is associated with a greater urban, non-white, renter population. Analytical modeling using data from past treatment efforts shows that they have been relatively cost effective, protecting streams for about $5700 per kilometer per year. Federal appropriations for Pennsylvania could address all impaired streams for 25 years but would leave insufficient funding for other abandoned mine hazards.In Pennsylvania, incomes are lower in communities with streams damaged by abandoned mine drainage, but these streams could be protected cost-effectively, according to an analysis combining demographic, economic, hydrological, and cost data.

Several US programs provide smaller-scale forest landowners access to carbon markets where they can earn payments in exchange for stricter timber management. We study participation in one program—the Family Forest Carbon Program—and find that 1% of likely eligible owners in five high-enrollment counties in Pennsylvania enrolled in the first 3 years, less than what landowner surveys predict. Comparisons of enrolled parcels with those of the likely eligible population reveal a similar average extent of harvesting over the 35 years prior to enrollment. Under the current owner, however, enrolled parcels had 50% more harvesting than comparable parcels. We find that more harvesting in the past 20 years reduces harvesting in the present, suggesting that, absent the Program, enrolled parcels might have less future harvests. The findings indicate that expanding carbon market access is one challenge, enrolling landowners, especially those with high offset potential, is another. Lower-than-expected enrollment in a carbon program for family forest owners in Pennsylvania, with selection patterns hinting at below-average carbon offset potential, according to an analysis that uses program enrollment, satellite, and tax data.

We study the effects of the property tax base shock caused by natural gas drilling in the Barnett Shale in Texas—a state that taxes oil and gas wells as property. Over the boom and bust in drilling, housing appreciation closely followed the oil and gas property tax base, which expanded the total tax base by 23 percent at its height. The expansion led to a decline in property tax rates while maintaining or increasing revenues to schools. Overall, each $1 per student increase in the oil and gas property tax base increased the value of the typical home by $0.15. Some evidence suggests that the cumulative density of wells nearby may lower housing values, indicating that drilling could reduce local welfare without policies to increase local public revenues.

How much decoupled payments, such as direct payments in the U.S., affect agricultural production remains an open empirical question with implications for policy. Using data from multiple years of the Census of Agriculture, we exploit a provision of the 2002 Farm Act that departed from previous policy by making oilseeds eligible for direct payments, thus increasing payments to areas that historically produced more oilseeds. Our instrumental variable estimates, in contrast to OLS estimates, suggest that changes in payments over the period 2002 to 2007 had little effect on aggregate production at the ZIP-code level.

Recent increases in farm real estate values in the United States have increased farm equity. By exploiting periods of high and low appreciation that caused various increases in wealth for farmers owning various shares of their farmland, we examine whether U.S. grain farmers expanded their acres harvested or acres owned in response to an increase in their land wealth. We find that land wealth had little effect on farm size. However, for similarly-sized farms, a larger ownership share (10 percentage points) led to an increase in the growth of land owned (2 percentage points). Because older farmers own more of the land that they farm, greater land appreciation slows the rate at which younger farmers acquire land relative to older farmers.

Farmers dramatically increased their use of federal crop insurance in the 2000s. From 2000 to 2013, premium subsidies increased sevenfold and acres enrolled increased by 77%. Although designed for nonenvironmental goals, subsidized insurance may affect the use of land, fertilizer, and agrochemicals and, therefore, environmental externalities from agriculture. Using novel panel data, we examine farmer responses to changes in coverage with an empirical approach that exploits program limits on coverage that were more binding for some farmers than for others. Estimates indicate that expanded coverage had little effect on the share of farmland harvested, crop specialization, productivity, or fertilizer and chemical use. More broadly, we construct and describe a new nationwide, farm-level panel data set with nearly 32,500 farms observed at least twice over the 2000–2013 period, a resource that should enrich US agro-environmental research.

We study how increases in wealth from rapid appreciation of farmland influenced farmer decisions to borrow, buy land, and expand. Exploiting periods of high and low appreciation and a panel data model that allows for correlation between prior growth trends and the share of land owned, we find that a dollar increase in paper wealth led younger farmers to increase real-estate-secured borrowing by 48 cents. Land purchases accompanied the increase in borrowing, supporting the view that collateral-based lending may be contributing to the recent run-up in farmland prices. We find no effect of land wealth on production or acres harvested.

We study how subsurface ownership shapes the income effects of oil and gas extraction. For the average US county with growth in extraction from 2000 to 2014, we find that royalty income and its multiplier effect accounted for 70% of the total income gain, with each royalty dollar generating an additional 49 cents of local income. A county where residents own the subsurface captured 28 cents more of each dollar in production than one with absentee ownership. Nationally, oil and gas production increased US personal income in 2014 by $67 billion (0.5%) more than if all royalties accrued abroad. Areas with the same resource abundance can therefore experience contrasting economic outcomes because of differences in ownership.

We study farm real estate values in the Barnett shale (Texas) and the northeastern part of the Marcellus shale (Pennsylvania and New York). We find that shale gas development caused appreciation in real estate values in both areas but the effect was much larger for the Marcellus, suggesting broader ownership of oil and gas rights by surface owners. In both regions, the greatest appreciation occurred when land was leased for drilling, not when drilling and production boomed. We find evidence that effects vary by farm type, which may reflect correlation between farm type and ownership of oil and gas rights.

The Agricultural Resource Management Survey is the primary annual source of information on U.S. farms, but in a typical year one‐third of sampled farms do not respond. We use Census of Agriculture data to study nonresponse to the survey and how it affects estimates in two econometric models. Despite larger farms responding less, the coefficients estimated from the respondent subsample always fall inside confidence intervals based on draws from the full sample of respondents and nonrespondents. Although nonresponse bias can vary by application, the findings suggest that bias is unlikely to undermine conclusions based on econometrics using respondent data.