Abstract  Ethanol production in the United States, driven by federal renewable fuel policy, has exploded over the past two decades and has prompted the construction of many ethanol refineries throughout the US Corn Belt. These refineries have introduced a new inelastic demand for corn in the areas where they were built, reducing basis for nearby farmers and effectively subsidizing local corn production. In this paper, I explore whether and to what extent the construction of new ethanol refineries has actually increased local corn acreage. I also explore some environmental e↵ects of this acreage increase. Using a thirteen year panel of over two million field-level observations in Illinois, Indiana, Iowa, and Nebraska, I estimate a net increase of nearly 300,000 acres of corn in 2014 relative to 2002 that can be attributed to the placements of new ethanol refineries. This increase comprises approximately 0.75% of the total 2014 corn acreage within my dataset. Furthermore, this effect is separate from the general equilibrium e↵ect of ethanol policy increasing aggregate demand for corn. Back-of-the-envelope calculations suggest that over 21,000 tons of the nitrogen applied to fields in my sample in 2014 can be attributed to refinery location effects. Essentially all of these observed effects occur only in areas within 30 miles of an ethanol refinery, suggesting that refineries have meaningful localized impacts on land use and environmental quality such as nitrate runoff. JEL codes: Q15, Q16, Q53

Abstract  When a government imposes a regulation, it usually indicates that the market would not produce the socially desired outcome. A good example is the U.S. Renewable Fuel Standard (RFS). This paper examines the extent to which biofuel production has been driven over time by the RFS and the extent to which it was driven by market changes unforeseen at the time of RFS passage. While the RFS has played a critical role in providing a secure environment to produce and use more biofuels, it was not the only factor that encouraged the biofuel industry to grow. To some extent, at least in the 2000s, the non-RFS biofuel policies and market forces have also influenced the rapid expansion in biofuels. Over the past decade, many papers have studied the economic impacts of biofuel production and policy. The existing literature has failed to properly quantify the impacts and contributions of each of these drivers separately. This paper develops short and long run economic analyses, using Partial Economic (PE) and Computable General Equilibrium (CGE) models, to differentiate the economic impacts of the RFS from other drivers that have helped biofuels to grow. Results show: i) the bulk of the ethanol production prior to 2012 was driven by what was happening in the national and global markets for energy and agricultural commodities and by the federal and sometimes state incentives for biofuel production; ii) the medium to long run price impacts of biofuel production were not large; iii) Due to biofuel production, regardless of the drivers, real crop prices have increased between 1.1% and 5.5% in 2004-11 with only one-tenth of the price increases were assigned to the RFS, iv) For 2011-16, the long run price impacts of biofuels were less than the time period of 2004-11, as in the second period biofuel production increased at much slower rate, v) Biofuel production, regardless of the drivers, has increased US annual farm incomes by $10.6 billion between 2002-16 with 28% share for the RFS.

Abstract  We evaluated several variants of a variable biofuel subsidy and compared them with the fixed subsidy and Renewable Fuel Standard using two different modeling approaches. First we used a partial equilibrium model encompassing crude oil, gasoline, ethanol, corn, and ethanol by-products. Second, we used a stochastic simulation model of a prototypical ethanol plant. From the partial. equilibrium analysis, it appears the variable subsidy provides a safety net for ethanol producers when oil prices are low; yet, it does not put undue pressure on corn prices when oil prices are high. At high oil prices, the level of ethanol production is driven by market forces. From the plant level stochastic analysis, essentially the same conclusions are reached. As with the fixed subsidy, the variable subsidy can increase the net present value (NPV) sufficiently to encourage investment, but with lower risk for the producer, lower probability of a loss from the investment, and often lower expected cost to government. Finally, in the US, the ethanol industry is up against a blending limit called the blend wall. If the blending wall remains in place and no way around it is found, it does not matter much what other policy options are used.

Abstract  This study looks at the land use impact of the biofuels expansion on both the intensive and extensive margin, and its environmental consequences. We link economic, geographical and environmental models by using spatially explicit common units of analysis and use remote sensing crop cover maps and digitized soils data as inputs. Land use changes are predicted via economic analysis of crop rotation choice and tillage under alternative crop prices, and the Environmental Policy Integrated Climate (EPIC) model is used to predict corresponding environmental impacts. The study focuses on Iowa, which is the leading biofuels hotspot in the U.S. due to intensive corn production and the high concentration of ethanol plants that comprise 28% of total U.S. production. We consider the impact of the biofuels industry both on current cropland and on land in the Conservation Reserve Program (CRP), a land set-aside program. We find that substantial shifts in rotations favoring continuous corn rotations are likely if high corn prices are sustained. This is consistent with larger scale analyses which show a shift of the current soybean production out of the Corn Belt. We find that sediment losses increase substantially on the intensive margin, while nitrogen losses increase less. Returning CRP land into production has a vastly disproportionate environmental impact, as non-cropped land shows much higher negative marginal environmental effects when brought back to row crop production. This illustrates the importance of differentiating between the intensive and extensive margin when assessing the expansion of biofuel production. (C) 2010 Elsevier Ltd. All rights reserved.

Abstract  This study uses a county-level difference-in-difference framework to estimate the share of re-enrollment into the Conservation Reserve Program (CRP) in response to local ethanol production capacity after the Renewable Fuels Standard (RFS). Relatively more land remained in CRP in ethanol-intensive areas after the RFS. This seemingly counter-intuitive result can be explained by post-RFS changes to the CRP that favored ethanol-intensive areas. Both CRP design changes and production trends correlated with ethanol plant location pose challenges for empirical strategies that use ethanol plant location to study production or land use decisions. Changes to CRP policies can play an important role in participation and land use decisions.

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.

Abstract  We use field-level data to estimate the response of corn and soybean acreage to price shocks. Our sample contains more than 8 million observations derived from satellite imagery and includes every cultivated field in Iowa, Illinois, and Indiana. We estimate that aggregate crop acreage responds more to price shocks in the short run than in the long run, and we show theoretically how the benefits of crop rotation generate this response pattern. In essence, farmers who change crops due to a price shock have an incentive to switch back to the previous crop to capture the benefits of crop rotation. Our result contradicts the long-held belief that agricultural supply responds gradually to price shocks through partial adjustment. We would not have obtained this result had we used county-level panel data. Standard econometric methods applied to county-level data produce estimates consistent with partial adjustment. We show that this apparent partial adjustment is illusory, and we demonstrate how it arises from the fact that fields in the same county are more similar to each other than to fields in other counties. This result underscores the importance of using models with appropriate micro-foundations and cautions against inferring micro-level rigidities from inertia in aggregate panel data. Our preferred estimate of the own-price long-run elasticity of corn acreage is 0.29, and the cross-price elasticity is -0.22. The corresponding elasticities for soybean acreage are 0.26 and -0.33. Our estimated short-run elasticities are 37% larger than their long-run counterparts.

Abstract  The US Renewable Fuel Standard sets a lower bound on the amount of biofuels used, with consequences for behavior of agricultural commodity markets that currently supply the vast majority of feedstocks for biofuel production. In this article, maize biotechnology is considered taking into account the impacts of US biofuel mandates. The impact of a hypothetical technology that reduces the severity of negative maize yield shocks is estimated using a structural economic model simulated stochastically. The importance of mandated levels of use of biofuels depends on whether they are binding. If biofuel use exceeds mandated levels, then mandates have little impact. If mandates are binding, then the markets' ability to respond to price movements can be reduced. In either case, aggregate maize demand is inelastic in these projections, so yield technology improvements can reduce total revenue to maize production.

Abstract  The contribution of biofuels to save greenhouse gas emissions has been challenged over the last years. A still unresolved question is how to quantify emissions from indirect land use change (iLUC). In this paper we review approaches to quantify iLUCemissions. We conclude that economic simulation models have fewer drawbacks compared to two other approaches. We find that economic simulation models contain a high level of uncertainty with respect to key model parameters. Further, we conclude that it is inappropriate to calculate crop-specific iLUC-emissions and to include them into binding regulation. We argue that modelling results, particularly crop-specific ones, should not be used for policy decisions.

Abstract  The increase in ethanol blended into U.S. gasoline is often attributed to the Renewable Fuels Program (RFS), however, other factors such as rising gasoline prices and the phase-out of MTBE were also factors driving ethanol demand at the same time that the RFS program was being implemented. This study conducts a detailed evaluation of ethanol’s blending cost into E10 gasoline, including octane and volatility costs, production cost and spot prices, distribution costs, and federal and state subsidies, while omitting RIN values, to assess whether ethanol would have been economical to blend into gasoline regardless of the RFS program. Based on this analysis, economic factors alone were sufficient to cause the observed growth in ethanol use.

Abstract  Recent expansion of croplands in the United States has caused widespread conversion of grasslands and other ecosystems with largely unknown consequences for agricultural production and the environment. Here we assess annual land use change 2008-16 and its impacts on crop yields and wildlife habitat. We find that croplands have expanded at a rate of over one million acres per year, and that 69.5% of new cropland areas produced yields below the national average, with a mean yield deficit of 6.5%. Observed conversion infringed upon high-quality habitat that, relative to unconverted land, had provided over three times higher milkweed stem densities in the Monarch butterfly Midwest summer breeding range and 37% more nesting opportunities per acre for waterfowl in the Prairie Pothole Region of the Northern Great Plains. Our findings demonstrate a pervasive pattern of encroachment into areas that are increasingly marginal for production, but highly significant for wildlife, and suggest that such tradeoffs may be further amplified by future cropland expansion.

Abstract  The biomass scenario model (BSM) is a dynamic model of the biomass-to-biofuels supply chain in the U.S.A., developed during a multi-year analysis effort conducted by the National Renewable Energy Laboratory (NREL), under sponsorship from the United States Department of Energy (DOE) Bioenergy Technologies Office (BETO). The BSM project, which received the 2018 Applications Award by the International System Dynamics Society, has supported collaborative analyses, developed scenarios for industry development and facilitated stakeholder engagement. We summarize insights gained from the BSM project that may be useful to other large-scale dynamic modeling efforts. We summarize the project focus, the analysis process, key outcomes and observations on successful execution of such a product. Key points include the value of a multidisciplinary team with clear roles, engagement of experts and stakeholders, and use and reuse of simple, modular structures. The overall effort suggests that these practices may aid long-term, team-focused, multi-stakeholder modeling efforts.

Abstract  The Energy Independence and Security Act of 2007 targets use of 36 billion gallons of biofuels per year by 2022. Achieving this may require substantial changes to current transportation fuel systems for distribution, dispensing, and use in vehicles. The U.S. Department of Energy and the National Renewable Energy Laboratory designed a system dynamics approach to help focus government action by determining what supply chain changes would have the greatest potential to accelerate biofuels deployment. The National Renewable Energy Laboratory developed the Biomass Scenario Model, a system dynamics model which represents the primary system effects and dependencies in the biomass-to-biofuels supply chain. The model provides a framework for developing scenarios and conducting biofuels policy analysis. This paper focuses on the downstream portion of the supply chain–represented in the distribution logistics, dispensing station, and fuel utilization, and vehicle modules of the Biomass Scenario Model. This model initially focused on ethanol, but has since been expanded to include other biofuels. Some portions of this system are represented dynamically with major interactions and feedbacks, especially those related to a dispensing station owner’s decision whether to offer ethanol fuel and a consumer’s choice whether to purchase that fuel. Other portions of the system are modeled with little or no dynamics; the vehicle choices of consumers are represented as discrete scenarios. This paper explores conditions needed to sustain an ethanol fuel market and identifies implications of these findings for program and policy goals. A large, economically sustainable ethanol fuel market (or other biofuel market) requires low end-user fuel price relative to gasoline and sufficient producer payment, which are difficult to achieve simultaneously. Other requirements (different for ethanol vs. other biofuel markets) include the need for infrastructure for distribution and dispensing and widespread use of high ethanol blends in flexible-fuel vehicles.

Abstract  The Biomass Scenario Model (BSM) is a system-dynamics simulation model intended to explore the potential for rapid expansion of the biofuels industry. The model is not predictive — it uses scenario assumptions based on various types of data to simulate industry development, emphasizing how incentives and technological learning-by-doing might accelerate industry growth. The BSM simulates major sectors of the biofuels industry, including feedstock production and logistics, conversion, distribution, and end uses, as well as interactions among sectors. The model represents conversion of biomass to biofuels as a set of technology pathways, each of which has allowable feedstocks, capital and operating costs, allowable products, and other defined characteristics. This study and the BSM address bioenergy modeling analytic needs that were identified in recent literature reviews. Simulations indicate that investments are most effective at expanding biofuels production through learning-by-doing when they are coordinated with respect to timing, pathway, and target sector within the biofuels industry. Effectiveness metrics include timing and magnitude of increased production, incentive cost and cost effectiveness, and avoidance of windfall profits. Investment costs and optimal investment targets have inherent risks and uncertainties, such as the relative value of investment in more-mature versus less mature pathways. These can be explored through scenarios, but cannot be precisely predicted. Dynamic competition, including competition for cellulosic feedstocks and ethanol market shares, intensifies during times of rapid growth. Ethanol production increases rapidly, even up to Renewable Fuel Standards-targeted volumes of biofuel, in simulations that allow higher blending proportions of ethanol in gasoline-fueled vehicles. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.