The biofuel industry has been rapidly growing around the world in recent years. Several papers have used general equilibrium models and addressed the economy-wide and environmental consequences of producing biofuels at a large scale. They mainly argue that since biofuels are mostly produced from agricultural sources, their effects are largely felt in agricultural markets with major land use and environmental consequences. In this paper, we argue that virtually all of these studies have overstated the impact of liquid biofuels on agricultural markets due to the fact that they have ignored the role of by-products resulting from the production of biofuels. Feed by-products of the biofuel industry, such as Dried Distillers Grains with Solubles (DDGS) and biodiesel by-products (BDBP) such as soy and rapeseed meals, can be used in the livestock industry as substitutes for grains and oilseed meals used in this industry. Hence, their presence mitigates the price impacts of biofuel production on the livestock and food industries. The importance of incorporating by-products of biofuel production in economic models is well recognized by some partial equilibrium analyses of biofuel production. However, to date, this issue has not been tackled by those conducting CGE analysis of biofuels programs. Accordingly, this paper explicitly introduces DDGS and BDBP, the major by-products of grain based ethanol and biodiesel production processes, into a worldwide CGE model and analyzes the economic and environmental impacts of regional and international mandate policies designed to stimulate bioenergy production and use. We first explicitly introduce by-products of biofuel production into the GTAP-BIO database, originally developed by Taheripour et al. (2007). Then we explicitly bring in DDGS 3 and BDBP into the Energy-Environmental version of the Global Trade Analysis Project (GTAP-E) model, originally developed by Burniaux and Truong (2002), and recently modified by McDougall and Golub (2007) and Birur, Hertel, and Tyner (2008). The structure of the GTAP-E model is redesigned to handle the production and consumption of biofuels and their by-products, in particular DDGS, across the world. Unlike many CGE models which are characterized by single product sectors, here grain based ethanol and DDGS jointly are produced by an industry, named EthanolC. The biodiesel industry also produces two products of biodiesel and BDBP jointly. This paper divides the world economy into 22 commodities, 20 industries, and 18 regions and then examines global impacts of the US Energy Independence and Security Act of 2007 and the European Union mandates for promoting biofuel production in the presence of by-products. We show that models with and without by-products demonstrate different portraits from the economic impacts of international biofuel mandates for the world economy in 2015. While both models demonstrate significant changes in the agricultural production pattern across the world, the model with by-products shows smaller changes in the production ...

Few of the numerous published studies of the emissions from biofuels-induced "indirect" land use change (ILUC) attempt to propagate and quantify uncertainty, and those that have done so have restricted their analysis to a portion of the modeling systems used. In this study, we pair a global, computable general equilibrium model with a model of greenhouse gas emissions from land-use change to quantify the parametric uncertainty in the paired modeling system's estimates of greenhouse gas emissions from ILUC induced by expanded production of three biofuels. We find that for the three fuel systems examined-US corn ethanol, Brazilian sugarcane ethanol, and US soybean biodiesel-95% of the results occurred within ±20 g CO2e MJ -1 of the mean (coefficient of variation of 20-45%), with economic model parameters related to crop yield and the productivity of newly converted cropland (from forestry and pasture) contributing most of the variance in estimated ILUC emissions intensity. Although the experiments performed here allow us to characterize parametric uncertainty, changes to the model structure have the potential to shift the mean by tens of grams of CO2e per megajoule and further broaden distributions for ILUC emission intensities.

Although CGE models have received heavy usage, they are often criticized as being insufficiently validated. Key parameters are often not econometrically estimated, and the performance of the model as a whole is rarely checked against historical outcomes. As a consequence, questions frequently arise as to how much faith one can put in CGE results. In this paper, we employ a novel approach to the validation of a widely utilized global CGE model-GTAP-E. By comparing the variance of model generated petroleum price distributions-driven by historical demand and supply shocks to the model-with observed five-year moving average price distributions, we conclude that energy demand in GTAP-E is far too price-elastic over this time frame. After incorporating the latest econometric estimates of energy demand and supply elasticities, we revisit the validation question and find the model to perform more satisfactorily. As a further check, we compare a deterministic global general equilibrium simulation, based on historical realizations over the 2001-2006 period during which petroleum prices rose sharply, along with growing global energy demands. As anticipated by the stochastic simulations, the revised model parameters perform much better than the original GTAP-E parameters in this global, general equilibrium context.

The authors thank Wally Tyner for valuable discussions on this topic. V. Kerry Smith served as our NBER discussant; he and members of the NBER workshop, as well as two anonymous reviewers, provided useful comments on this paper. The views expressed are the authors' and do not necessarily reflect those of the Economic Research Service, the USDA, or the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Much of the attention from COVID‐19 has been on the impacts on tourism and other service sectors; but there has been a growing interest in some agricultural and food topics, such as the decline in food away from home (FAFH) expenditures. Our work considers the importance of FAFH in the overall economy, and we also consider changes in agricultural production and trade that have occurred because of COVID‐19. We gather data on actual changes to these components, as well as similar shocks to non‐agricultural sectors, and employ a simulation model to estimate the impacts on gross domestic product (GDP). Results indicate that changes from agriculture due to COVID‐19 have had a larger effect on the overall U.S. economy than the share of agriculture in the economy at the beginning of COVID‐19. But the non‐agricultural shocks still outweigh the impacts from agriculture by a magnitude of 3. Breaking the results down along the components, we find that the loss in FAFH expenditures is the largest contributor to the change in GDP resulting from shocks to agricultural markets and conclude that agricultural production/trade markets have been very resilient during the pandemic. Our results also indicate that our model (computable general equilibrium) does reasonably well in estimating GDP compared to actual changes due to the inclusion of data on actual demand, supply, and fiscal responses to COVID‐19.