Corn area response to local ethanol markets in the United States: A grid cell level analysis

Mesbah Motamed, Lihong McPhail, Ryan Williams

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

We measure corn and total agricultural area response to the biofuels boom in the United States from 2006 to 2010. Specifically, we use newly available micro-scale grid cell data to test whether a location's corn and total agricultural cultivation rose in response to the capacity of ethanol refineries in their vicinity. Based on these data, acreage in corn and overall agriculture not only grew in already-cultivated areas but also expanded into previously uncultivated areas. Acreage in corn and total agriculture also correlated with proximity to ethanol plants, though the relationship dampened over the time period. A formal estimation of the link between acreage and ethanol refineries, however, must account for the endogenous location decisions of ethanol plants and areas of corn supply. We present historical evidence to support the use of the US railroad network as a valid instrument for ethanol plant locations. Our estimates show that a location's neighborhood refining capacity exerts strong and significant effects on acreage planted in corn and total agricultural acreage. The largest impacts of ethanol plants were felt in locations where cultivation area was relatively low. This high-resolution evidence of ethanol impacts on local agricultural outcomes can inform researchers and policy-makers concerned with crop diversity, environmental sustainability, and rural economic development.

Original languageEnglish
Pages (from-to)726-743
Number of pages18
JournalAmerican Journal of Agricultural Economics
Volume98
Issue number3
DOIs
StatePublished - Apr 1 2016

Keywords

  • agricultural land use
  • biofuels
  • corn acreage
  • ethanol refineries
  • grid cell data

Fingerprint

Dive into the research topics of 'Corn area response to local ethanol markets in the United States: A grid cell level analysis'. Together they form a unique fingerprint.

Cite this