ethanol

The link provides data and reports related to bioenergy - ethanol and biodiesel produced by Minnesota.

Ethanol production doubled in a very short period of time in the U.S. due to a combination of natural disasters, political tensions, and much more demand globally from petroleum. Responses to this expansion will span many sectors of society and the economy. As the Midwest gears up to rapidly add new ethanol manufacturing plants, the existing regional economy must accommodate the changes. There are issues for decision makers regarding existing agricultural activities, transportation and storage, regional economic impacts, the likelihood of growth in particular areas and decline in others, and the longer term economic, social, and environmental sustainability. Many of these issues will have to be considered and dealt with in a simultaneous fashion in a relatively short period of time. This chapter investigates sets of structural, industrial, and regional consequences associated with ethanol plant development in the Midwest, primarily, and in the nation, secondarily. The first section untangles the rhetoric of local and regional economic impact claims about biofuels. The second section describes the economic gains and offsets that may accrue to farmers, livestock feeding, and other agri-businesses as production of ethanol and byproducts increase. The last section discusses the near and longer term growth prospects for rural areas in the Midwest and the nation as they relate to biofuels production.

The Federal Trade Commision performs a market concentration analysis of the ethanol production industry to determine whether there is sufficient competition among industry participants to avoid price-setting and other anticompetitive behaviour.The FTC must report its findings to Congress and to the
Administrator of the Environmental Protection Agency. This link presents the FTC’s
concentration analysis of ethanol production up to year 2009.

This is an overview of transportation issues facing a rapidly expanding U.S. ethanol industry in the context of the U.S. corn market—currently the main source of ethanol production in the United States. The aim of the report is to present a frame of reference as the ethanol industry continues to grow and additional transportation benchmarks and indicators develop by providing analysis of transportation requirements for corn-based ethanol and its impact on grain transportation.

The objective of the research here is to more carefully investigate the claims of localized
impacts on two fronts. The first is the impact a local ethanol plant has on the rate of agricultural
land conversion to other uses (if an ethanol plant increases the value of local agricultural land as
a result of increased commodity prices, one might expect a slower rate of conversion relative to
other communities). Second, we investigate whether the siting of an ethanol plant has had a
negative impact on local residential land values.

This paper summarizes some of the major impacts rapid growth in the corn
based ethanol (CE) production is now having on infrastructure in the Midwestern corn
producing states and examines some of the likely infrastructure needs that might be
expected to occur as a consequence of the future development of biomass based ethanol (BE) production

Many site specific factors have been identified to influence ethanol plant location and production. These include availability of corn, water, cattle and access to a major highway. The objective of this paper is to determine whether these factors actually have influence on plant size. The rapid expansion of the industry could make these factors crucial in its survival. The study involved 122 ethanol plants in similar number of US counties. Data was obtained as follows: County level shape files from Arc View software; ethanol plant capacity data from Renewable Fuels Association; corn production from United States Department of Agriculture. Exploratory spatial analyses using Choropleth map, Moran�s scatter plot and Moran�s I did not show spatial dependence among nearby ethanol plants. However, a spatial error model was found to be superior to its a-spatial version. The site specific factors, except corn, were not statistically significant in ethanol production level. The implication of these results is beginning to be seen in the current transportation bottleneck facing the industry.

A key objective of U.S. energy policy is to increase biofuel use by highway vehicles to 36 billion gallons per year by 2022. The Energy Independence and Security Act envisions that nearly all of this target will be met by gasohol (E10) or neat ethanol (E85). Since the market for blending ethanol with gasoline at 10% by volume will saturate at about 15 billion gallons, most of the ethanol will need to be sold in the form of E85 unless higher order blends are approved by automakers and the Environmental Protection Agency. The demand for E85 is likely to be very sensitive to the relative prices of E85 and gasoline and to the availability of E85 at retail outlets. The key objective of this study is to estimate the sensitivity of aggregate demand for E85 to the relative availability of E85 versus gasoline at retail outlets, as well as the sensitivity of E85’s market share to the prices of E85 and gasoline. Monthly data from the state of Minnesota for the period 1997 to 2008 are used to estimate a model of E85 choice by owners of flexible fuel vehicles. The results indicate that E85 availability at 10% to 20% of retail outlets might be sufficient to achieve a very substantial market share given an appropriate price advantage for E85.

One fundamental issue influencing the economic viability of the ethanol industry is consumers' demand responsiveness to both gasoline and ethanol price changes. This paper presents an alternative approach by estimating the geographic variation of price elasticity of demand for ethanol across the study area.

The market for E85�a fuel blend of 85 percent ethanol and 15 percent gasoline�is small
but growing rapidly. I use data for E85 sales at fueling stations in Minnesota to estimate
demand for E85 as a function of retail E85 and gasoline prices. I find that demand is
highly sensitive to price changes, with an own-price elasticity as high as -13 and a gasolineprice
elasticity as high as 16 at sample mean price levels. Demand is most sensitive to
price changes when the relative price of E85 is at an intermediate level, at which point
small price changes induce fuel switching by a large number of consumers. These results
are qualitatively consistent with a simple theoretical model of E85 demand, and the large
elasticities are in line with previous literature that estimates demand for fuels with nearperfect
substitutes. I estimate that roughly 40�50 percent of current E85 consumers are
fuel switchers, and that the average fuel-switching consumer is indifferent between the two
fuels when the ratio of gasoline to E85 prices is about 1.05�1.15. These ratios are somewhat
smaller than the ratio of gasoline to E85 fuel economy implied by government tests of
flex-fuel vehicles but consistent with reports on E85 fuel economy in the popular press.