Abstract  This paper broadens the analysis of the interactions between energy and agricultural commodity markets by focusing on five major commodities: oil, natural gas, soybean, corn, and ethanol, and intends to provide more updated information regarding the degree of the connection among the markets. We estimate a DCC-MGARCH model to accommodate the dynamic and changing degree of interconnections among the five markets with respect to price levels and price volatilities. In doing so, we control for additional economic variables including oil and gas inventories, interest rate spread, exchange rate and economic activities. Our empirical evidence suggests that there are varying degrees of interconnections among the energy and agricultural commodities in the long term as well as the short term, but the interactions among the agricultural commodities and ethanol are generally higher than the interactions between oil and gas and agricultural markets. In addition, we reveal some weak evidence of commodity market speculation. The estimated conditional volatility correlations suggest that volatility spillovers among the markets were time dependent and dynamic.

Abstract  Background: This study evaluates the global economic effects of the current US RFS2, and the potential contribution from advanced biofuels. Results & discussion: Our simulation results suggest that these mandates lead to an increase of 0.21% in the global gross domestic product in 2022, including an increase of 0.8% in the USA and 0.02% in the rest of the world, relative to our baseline no-RFS scenario. The incremental contributions to gross domestic product from advanced biofuels in 2022 are estimated at 0.41 and 0.04% in the USA and the rest of the world, respectively. Conclusion: Although production costs of advanced biofuels are higher than for conventional biofuels in our model, their economic benefits result from reductions in oil use and their smaller impacts on food markets compared with conventional biofuels. Thus, the US advanced biofuels targets are expected to have positive net economic benefits.

Abstract  Since 2007, capital markets have acquired a newfound interest in agricultural land as a portfolio investment. This phenomenon is examined through the theoretical lens of financialization. On the surface the trend resembles a sort of financialization in reverse – many new investments involve agricultural production in addition to land ownership. Farmland also fits well into current financial discourses, which emphasize getting the right kind of exposure to long-term agricultural trends and ‘value investing’ in genuinely productive companies. However, capital markets' current affinity for farmland also represents significant continuity with the financialization era, particularly in the treatment of land as a financial asset. Capital gains are central to current farmland investments, both as a source of inflation hedging growth and of potentially large speculative profits. New types of farmland investment management organizations (FIMOs) are emerging, including from among large farmland operators that formerly valued land primarily as a productive asset. Finally, the first tentative steps toward the securitization of farmland demonstrate the potential for a much more complete financialization of farmland in the future.

Abstract  Within the last few decades, the extended use of biodiesel and bioethanol has established interlinkages between energy markets and agricultural commodity markets. The present work examines the bivariate relationships of crude oil–corn and crude oil–soybean futures prices with the assistance of the ARDL cointegration approach. Our findings confirm that crude oil prices affect the prices of agricultural products used in the production of biodiesel, as well as of ethanol, validating the interaction of energy and agricultural commodity markets. The practical value of the present work is that the findings provide policy makers with insight into the interlinkages between agricultural and energy markets to promote biodiesel or bioethanol by affecting crude oil prices. The novelty of the present work stands on the use of futures prices that incorporate all available information and thus are more appropriate to identify supply and demand shocks and price spillovers than real prices. Finally, the period of study includes extremely low, as well as extremely high, crude oil prices and the results illustrate that biofuels cannot be substituted for crude oil and protect economies from energy volatility.

Abstract  This study observationally and statistically assesses theories put forth regarding expected price behavior of Renewable Identification Numbers (RINs) using a dataset of daily RIN price observations from January 2009 through May 2013. RIN price behavior tends to follow theoretical expectations, but some notable exceptions occur, the causes of which remain uncertain. Information provided by RIN prices is used to test the implications of a binding renewable fuel standard (RFS) versus a nonbinding RFS on ethanol-gasoline and corn-gasoline price relationships. In certain cases, cointegration tests provide evidence that the relationships are weaker when the RFS mandates are believed to be binding.

Abstract  The impact of biofuel mandates on the prices of commodities used to produce food continues to be a major consideration by policy makers. More recently concern about high compliance costs of oil companies due to mandates led to reductions in US biofuel mandates. To gain insights into the policy impacts of mandates on agricultural commodity prices and compliance costs requires development of dynamic models that can capture the fact that many agricultural commodities used to produce biofuels can be stored and that flexible compliance mechanisms allow for banking and borrowing of tradable permits. US biofuel mandates are enforced using a system of tradable permits, called RINs. RIN market dynamics are important because RINs can be banked for the future or borrowed from the future. Corn is the primary U.S. biofuel feedstock and is storable. Rational expectations competitive storage models are well suited to capture the dynamic behavior of commodity markets. Such a model is developed here for corn and RIN markets to estimate the impacts of alternative future ethanol mandate levels. The model considers corn use for ethanol, storage and all other uses in each period, accounting for two random variables: oil prices and corn yields. Borrowing and banking provisions of the Renewable Fuels Standard mandate are explicitly integrated into the model. We use the model to provide estimates of the impact on corn prices, corn plantings and ethanol production under two ethanol mandate scenarios for six marketing years from 2016/17. Our scenarios are a combination of volume requirements and infrastructure investment. The first scenario is one in which corn ethanol mandates stay the same as required in the current and proposed RFS and additional E85 stations are introduced that allow for compliance with higher mandates. The second scenario is one in which no investment occurs and the Environmental Protection Agency reduces the mandate to 13.87 billion gal, a level that can just be met with 10 percent ethanol blends. Comparing the results for two scenarios, we find that average corn prices are about 5 to 6% lower with the reduced mandates or about 22 to 30 cents per bushel, while average RIN prices drop from around 60 to 40 cents per RIN.

Abstract  Carbon dioxide (CO(2)) from ethanol production facilities is increasing as more ethanol is produced for alternative transportation fuels. CO(2) produced from ethanol fermentation processes is of high purity and is nearly a saturated gas. Such highly-concentrated source of CO(2) is a potential candidate for capture and utilization by the CO(2) industry. Quantity, quality and capture of CO(2) from ethanol fermentations are discussed in this review. The established and emerging value-added opportunities and markets for CO(2) from ethanol plants also are reviewed. The majority of CO(2) applications are dedicated to serving carbonated beverage and food processing and preservation markets. Beyond traditional merchant markets, the potential for exploring some fresh and profitable markets are discussed including carbon sources in chemical industries for the following: enhanced oil recovery; production of chemicals, fuels, and polymers; and production of algae-based biofuels through CO(2) fixation by microalgae.

Abstract  By diverting agricultural land away from food, feed, and livestock production, increased production of biofuel feedstock crops tend to drive up prices for agricultural commodities. But by how much? This question has been heavily debated in recent years, following the food price crisis of 2007-2008. A systematic review of 121 studies that quantifies the impact of biofuel demand on agricultural commodity markets reveals that there is still considerable uncertainty around the exact magnitude of the price response. Increased demand for corn ethanol in the United Statesthe focus of the majority of studiesis estimated to have accounted for 14-43% of the rise in US corn prices in the period 2000-2008. The divergence in results between studies is mainly due to different assumptions regarding demand and supply elasticities for agricultural commodities, and there is very limited empirical evidence that can help reduce the uncertainty around the value of these parameters, especially outside the United States. Few studies analyze the impact of biofuel demand beyond current or near-future levels and it is argued that estimated price effects can neither be extrapolated to large-scale biofuel demand shocks, nor are most models able to capture accurately the impacts of such shocks due to weaknesses in how land markets and land transformation process are modeled. To better gauge current and future impacts of biofuel demand on agricultural commodity markets, we need better data on supply and demand responses, both in the short and long run, as well as improved modeling of land competition and land-use change.

Abstract  An open-economy equilibrium model is derived to investigate the effects of energy policy on the U.S. economy, with emphasis on corn-based ethanol. A second best policy of a fuel tax and ethanol subsidy is found to approximate fairly closely the welfare gains associated with the first best policy of an optimal carbon tax and tariffs on traded goods. The largest economic gains to the U.S. economy from these energy policies arise from their impact on U.S. terms of trade, particularly in the oil market. Conditional on the current fuel tax, an optimal ethanol mandate is superior to an optimal ethanol subsidy.

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 ethanol blend wall and high RIN prices has become a controversial policy issue. We develop a model showing how RIN prices reflect the costs of overcoming the blend wall, namely biodiesel consumed in excess of its mandate and expansion of E85 sales. These costs are very high and are shown to be borne by producers and consumers of ethanol and gasoline. Although RIN prices reduce consumer prices of ethanol in both the E10 and E85 blends, the net price of E10 rises because obligated parties, who are required to purchase RINs, recoup the cost by passing on higher gasoline prices to blenders. This tax on gasoline production to pay for the subsidy on all ethanol consumption and RIN prices are a means of payment for “excess” RINs that are required to pay for costs overcoming the blend wall. Burkholder (2015) and EPA (2015) emphasize this first round subsidy that also increases ethanol market prices. But these papers downplay the overall increased costs of fuel to consumers due to RINs taxing gasoline producers, and the separate adverse market effects of a binding blend mandate. The latter has been missing in the debate where it is often implied that the RIN price represents the degree to which the ethanol mandate is binding. We show the RIN price represents the costs of overcoming the blend wall and the ethanol price premium due to the binding blend mandate reflects costs of the RFS itself. Our model determines RIN prices, the costs of overcoming the blend wall and the relationship with the ethanol price premium due to the binding mandate. We use economic theory consistent with the reality of the RFS and its associated complexities. From our empirical simulations, we find RIN prices went up because of the costs of the blend wall. Increasing the mandate with a blend wall caused E10 prices and market gasoline prices to increase, along with an increase in ethanol consumption and market prices. But ethanol and market prices would increase far more without a blend wall for the same increase in the mandated volume. In addition to the costs of overcoming the blend wall, our analysis finds the cost of the mandate price premium for ethanol to fuel consumers is $53.7 billion between 2007 and 2014, and to consumers of crops (including animal agriculture) by $285.4 billion per year worldwide. Our model also obtains the result that the RFS of the 2007 EISA is infeasible with exponentially increasing volume mandates under two situations. First, the E85 price goes to zero with ever increasing RIN prices. Second, when we assume costs of E85 sales expansion levels off at $2 per gallon with the ethanol price peaking and then slowly declines (with E85 and E10 consumption). This may explain why the EPA scaled back the RFS. Details

Abstract  The Renewable Fuel Standard (RFS) specifies the use of biofuels in the United States and thereby guides nearly half of all global biofuel production, yet outcomes of this keystone climate and environmental regulation remain unclear. Here we combine econometric analyses, land use observations, and biophysical models to estimate the realized effects of the RFS in aggregate and down to the scale of individual agricultural fields across the United States. We find that the RFS increased corn prices by 30% and the prices of other crops by 20%, which, in turn, expanded US corn cultivation by 2.8 Mha (8.7%) and total cropland by 2.1 Mha (2.4%) in the years following policy enactment (2008 to 2016). These changes increased annual nationwide fertilizer use by 3 to 8%, increased water quality degradants by 3 to 5%, and caused enough domestic land use change emissions such that the carbon intensity of corn ethanol produced under the RFS is no less than gasoline and likely at least 24% higher. These tradeoffs must be weighed alongside the benefits of biofuels as decision-makers consider the future of renewable energy policies and the potential for fuels like corn ethanol to meet climate mitigation goals.

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  The objective of the paper is to analyse causality among prices of corn, crude oil and ethanol. The analysis conducted in this paper is a dynamic one, and the data used consist of weekly futures prices of crude oil, corn, and ethanol from January 5, 2007 till April 11, 2014. The assessment of causal links between prices of corn, crude oil and ethanol is carried out with the use of rolling regression applied to augmented-VAR framework proposed by Toda and Yamamoto [22]. The application of the rolling regression procedures into the modified Wald (MWALD) causality test allows for the investigation of the persistence of stability in causal relations between analysed prices. The results obtained indicate that the linkages between energy prices and agricultural commodity prices change in the period analysed. The results of Granger causality tests reveal that in the analysed period the price of corn influences the price of energy (crude oil and ethanol). Also crude oil prices influence corn prices and ethanol prices. However, the influence of ethanol prices on crude oil prices and corn prices has not been observed.

Abstract  We conduct meta-analyses of the estimated impacts of corn ethanol on food and fuel prices, as well as greenhouse gases, and analyze the implications for the balance of trade. The meta-analyses suggest that corn ethanol has minor effects on greenhouse gas emissions and significant yet moderate effects on food and fuel prices. However, corn ethanol has a relatively significant impact on fuel security in terms of reductions in the import of oil to the U.S. and its overall effect on the U.S. balance of trade.