Biofuel Plant Great Plains Data

Description

This dataset accompanies the manuscript, "The Impact of Biofuel Plants and Capacity on Agricultural Earnings, Land Values, and Farm Employment in the Great Plains Region, 1997-2017." In this manuscript, we estimate the impact of these biofuel plants on the local agricultural economy with county-level data on agricultural employment, net farm income, and agricultural land values during 1997 to 2017 for 798 counties in twelve Great Plains States.

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We use Hornbeck’s (2012) definition of the Great Plains, a balanced panel of 798 Plains counties with common vegetation and growing conditions from 1997 to 2017. The agricultural outcome variables (Y) of net farm income, land values, and agricultural employment (defined here as the number of farm operators) are from the US Census of Agriculture (USDA/NASS 2017) and Haines et al. (2018). Census data are available every five years. Data on annual biofuel production capacity are obtained from Biodiesel Magazine and Ethanol Producer Magazine. Biofuel County Capacity was defined as million gGallons per year (MMgy) production capacity of all plants within a county in a given year. Adjacent Biofuel Capacity is defined to be the sum of biofuel production capacity in all adjacent counties (MMgy) in all counties adjacent to the county where the biofuel plant is located. Regional Biofuel Capacity is defined as the sum of within-county Biofuel Capacity and the capacity in adjacent counties (Adjacent Capacity). Net Farm Income is from US Ag Census, USDA/NASS 2017 . NFI observations were deflated using the implicit GDP price deflator (USBEA). Land Values (1000 USD/acre) are from US Ag Census, USDA/NASS 2017. Land values were deflated using the implicit GDP price deflator (USBEA). Agricultural employment is the number of principal operators whose primary occupation is farming taken from USDA/NASS 2017. Data for the Rural-Urban Continuum Codes was obtained from USDA/ERS (2017). Daily gridded weather data are obtained from PRISM and climate variables are constructed for each county using the method described in Schlenker et al. (2006). All climate variables were computed as 30-year rolling averages of yearly weather variables at county level up to the census year so as to capture long-run climate conditions . The climate variables used span the growing season (April – September) following the definitions used by Schlenker and Roberts (2009) and Ortiz-Bobea (2020). Biofuel feedstock prices were deflated using the implicit GDP price deflator (USBEA).

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