Abstract  The global indirect land use change (ILUC) implications of biofuel use in the United States of America (USA) from 2001 to 2010 are evaluated with a dynamic general equilibrium model. The effects of biofuels production on agricultural land area vary by year; from a net expansion of 0.17 ha per 1000 gallons produced (2002) to a net contraction of -0.13 ha per 1000 gallons (2018) in Case 1 of our simulation. In accordance with the general narrative about the implications of biofuel policy, agricultural land area increased in many regions of the world. However, oil-export dependent economies experienced agricultural land contraction because of reductions in their revenues. Reducing crude oil imports is a major goal of biofuel policy, but the land use change implications have received little attention in the literature. Simulations evaluating the effects of doubling supply elasticities for land and fossil resources show that these parameters can significantly influence the land use change estimates. Therefore, research that provides empirically-based and spatially-detailed agricultural land-supply curves and capability to project future fossil energy prices is critical for improving estimates of the effects of biofuel policy on land use. Published by Elsevier Ltd.

Abstract  The increase in corn ethanol production has raised concerns about its indirect impacts on the expansion of cropland and implications for the environment and continues to be a controversial issue. In particular, land enrolled in the Conservation Reserve Program (CRP) declined by 7.2 million acres between 2007 and 2012 while corn ethanol production more than doubled. However, the extent to which this decline in CRP acres can be causally attributed to increased ethanol production is yet to be determined. Using a dynamic, partial equilibrium economic model for the US agricultural sector we find that doubling of com ethanol production over the 2007-2012 period (holding all else constant) led to the conversion of 3.2 million acres of unused cropland, including 1 million acres in CRP, to crop production. While substantial in magnitude, we find that these land use changes due to biofuel production accounted for only 16% and 13% of the total reduction in unused cropland and in CRP acres, respectively, that occurred over the 2007-2012 period. We also find that the land use change per million gallons of corn ethanol has declined non-linearly over time from 453 acres to 112 acres over the 2007-2012 period.

Abstract  We present a novel bottom-up approach to estimate biofuel-induced land-use change (LUC) and resulting CO2 emissions in the U.S. from 2010 to 2022, based on a consistent methodology across four essential components: land availability, land suitability, LUC decision-making, and induced CO2 emissions. Using high-resolution geospatial data and modeling, we construct probabilistic assessments of county-, state-, and national-level LUC and emissions for macroeconomic scenarios. We use the Cropland Data Layer and the Protected Areas Database to characterize availability of land for biofuel crop cultivation, and the CERES-Maize and BioCro biophysical crop growth models to estimate the suitability (yield potential) of available lands for biofuel crops. For LUC decision-making, we use a county-level stochastic partial-equilibrium modeling framework and consider five scenarios involving annual ethanol production scaling to 15, 22, and 29 BG, respectively, in 2022, with corn providing feedstock for the first 15 BG and the remainder coming from one of two dedicated energy crops. Finally, we derive high-resolution above-ground carbon factors from the National Biomass and Carbon Data set to estimate emissions from each LUC pathway. Based on these inputs, we obtain estimates for average total LUC emissions of 6.1, 2.2, 1.0, 2.2, and 2.4 gCO2e/MJ for Corn-15 Billion gallons (BG), Miscanthus × giganteus (MxG)-7 BG, Switchgrass (SG)-7 BG, MxG-14 BG, and SG-14 BG scenarios, respectively.

Abstract  Purpose The purpose of this paper is to examine the market impacts of US biofuels and biofuel policies. Design/methodology/approach Two methods of analysis are employed. The first method looks back in time and estimates what US crop prices would have been during the 2005 to 2009 marketing years under two scenarios. The second method of analysis is forward looking and examines the market impacts of the blender tax credit and mandate on the distribution of prices in the 2011 calendar and marketing year. Findings The results developed in the previous two sections show that US ethanol policies modestly increased maize prices from 2006 to 2009 and that market impacts of the policies will be larger under tighter market conditions. Practical implications More flexible US biofuel policy including removing the blenders tax credit, which does not help US biofuel industry as long as the mandates are in place, and relaxing blending mandates when feedstock supplies are low. Originality/value This report makes three contributions to understanding the extent to which US biofuel policies contribute to higher agricultural and food prices. First, estimates of the impact of US ethanol policies on crop and food prices reveal that the impacts of the subsidies were quite modest. The second contribution is to provide estimates of the impact on agricultural commodity prices and food prices from market‐driven expansion of ethanol. The final contribution of this report is improved insight into how current US biofuel policies are expected to affect crop prices in the near future.

Abstract  The U.S. Renewable Fuel Standard (RFS) has been implicated as an agent of influence in agricultural commodity markets and a driver of land use and land management changes. However, direct attribution of these effects to the RFS has remained elusive and uncertain, a shortcoming that has hindered policy evaluation and potential reform. We analyze the effects of the RFS on corn, soy, and wheat prices and integrate these results with (i) spatially explicit observations of land use change, (ii) an econometric model of land use response, and (iii) additional models of agro-ecological processes, carbon emissions, and watershed hydrology to quantify the total land and water impacts of the RFS policy implementation. We independently model the effects of the policy via two pathways—land use intensification, or the preferential planting of corn instead of other crops, and cropland extensification, or the conversion of grasslands and other natural lands to cropland. We find that in the 8 years following passage of the RFS in 2007, the policy bolstered the amount of corn planted on existing cropland each year by an average of over 5 million acres. During the same time period, over 10 million acres of uncultivated land were converted to crop production in the U.S., of which nearly 3 million may be directly attributable to the RFS. These landscape changes resulted in more than a million tons of additional nitrogen application as well as novel carbon emissions on the order of 10 TgC yr-1. Our study is the first spatially explicit assessment of RFS impacts on total U.S. land use change and the first to quantify associated field-level water quality and carbon effects. The approach provides a blueprint for the integration of comprehensive land change data with causal economic models and demonstrates a novel method for measuring environmental outcomes across an entire agricultural industry, from the policymaking process through to implementation on the landscape.

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  We investigate the impacts of the U.S. renewable fuel standard (RFS2) and several alternative biofuel policy designs on global GHG emissions from land use change and agriculture over the 2010-2030 horizon. Analysis of the scenarios relies on GLOBIOM, a global, multi-sectoral economic model based on a detailed representation of land use. Our results reveal that RFS2 would substantially increase the portion of agricultural land needed for biofuel feedstock production. U.S. exports of most agricultural products would decrease as long as the biofuel target would increase leading to higher land conversion and nitrogen use globally. In fact, higher levels of the mandate mean lower net emissions within the U.S. but when the emissions from the rest of the world are considered, the US biofuel policy results in almost no change on GHG emissions for the RFS2 level and higher global GHG emissions for higher levels of the mandate or higher share of conventional corn-ethanol in the mandate. Finally, we show that if the projected crop productivity would be lower globally, the imbalance between domestic U.S. GHG savings and additional GHG emissions in the rest of the world would increase, thus deteriorating the net global impact of U.S. biofuel policies. (C) 2013 Elsevier Ltd. All rights reserved.

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  This paper studies the spillover effects of rising biofuel production on participation in the Conservation Reserve Program. Landowner participation decisions are modeled using a real options framework. We develop a land use decision model that captures biofuel-driven structural changes in market demand and derive threshold conditions that trigger participation in the program. We then quantify the impacts of biofuel production on participation at both the national and state levels using Monte Carlo simulations. The model is also used to analyze how changes in the persistence of the biofuel production boom and in the volatility of farming returns affect conservation participation decisions. Policy implications of the results are discussed.