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Maintaining and improving future food and energy security poses key challenges globally, especially in the face of climate change and climate mitigation. a computable general equilibrium (CGE) model -- the Applied Dynamic Analysis of the Global Economy model focusing on agriculture and land use (ADAGE-ALU), is used to examine how the global economy, especially energy, agriculture and land use, responds when facing these challenges. Despite continued increases in land productivity and energy efficiency in future decades, the effects of population and economic growth would dominate, leading to global increases in agricultural production, but also rising food and energy prices as well as continually growing GHG emissions in the BAU scenario. Comparing the climate change scenario with the BAU scenario, there are substantial reductions in global crop production and significant further increases in food prices, but little change in fossil fuel and biofuel production and energy prices, and only mild increases in CO2 emissions due to land-use changes. Relative to the BAU case, the implementation of a carbon tax on emissions other than those from land use change leads to the expansion of global biofuel production and a shift in the mix of crops produced towards those used as biofuels feedstocks, raises food prices, and reduces oil consumption and price slightly. Meanwhile, GHG emissions are slightly reduced as a result of lower oil consumption. In the REDD scenario, some cropland is afforested to store carbon, leading to a moderate rise in food and energy prices and significant GHG emission reductions. When climate change, REDD scenarios are implemented together, we see even higher reductions in global crop production and larger food price increases, along with greater reduction in GHG emissions compared with the CC scenario.

Efforts to satisfy global energy demand and improve food security while simultaneously taking action to mitigate climate change pose many key challenges for the world. In this study, the Applied Dynamic Analysis of the Global Economy (ADAGE), a computable general equilibrium (CGE) model, is applied to examine the impact of oil price on biofuel expansion, and subsequently, on food supply/price, land use change and climate mitigation potential, when both first and second generation biofuel feedstocks are considered. The results indicate despite a continued increase in land productivity and energy efficiency, increases in population and economic growth lead to a global increase in agriculture production, rising food, agriculture, biofuels, and energy prices, and land conversion from the other four land types to cropland in the REF scenario from 2010 to 2040. Oil price plays an important role in biofuel expansion. Globally, higher oil price leads to the expansion of biofuel production, increasing its share in total liquid fuel consumption in the private transportation sector. Consequently, more land is allocated for biofuel production, reducing global agriculture output and increasing agricultural consumption prices. Although emissions from land-use change increase, the overall emissions including fossil fuel emissions decreases. Regions display different patterns on biofuel expansions, land-use change, prices for food/agriculture and energy/biofuels, and GHG emissions.

Revised version dated October 2015, posted December 29, 2015.

Global production of biofuels has been expanding with the enduring concerns on climate change and energy security. The U.S. Congress has established a renewable fuel standard 2 (RFS2) rule that mandates annual combined production of 36 billion gallons (bg) biofuels by 2022 (USEPA, 2010). Large scale production of biofuels results in far-reaching intended and unintended consequences on the economy and environment. In this study, a computable general equilibrium model (CGE) - Applied Dynamic Analysis of Global Economy -- ADAGE-Biofuel is developed to examine the global implications of the U.S. RFS2 policy. This model is built upon a dynamic version of ADAGE model (Ross, 2009) by introducing eight crop categories, one livestock and one forestry sectors, seven first generation biofuels, three second generation biofuels and five land categories and explicitly model land-use changes. We find out that despite of continued increase in land productivity and energy efficiency, increase in population and economic growth leads to a global-wide increase in agriculture production, rise in price of food, agriculture, biofuel and energy and land conversion from the other four land types to cropland from 2010 to 2025 when RFS2 is not implemented and biofuel consumption remain at the base year (2010) level in all the regions until 2025 (BAU scenario). The implementation of RFS2 policy would require 36.3 million ha (mha) of land for switchgrass production by 2025, where 34.8 mha from existing cropland, 0.9 mha from pasture, and 0.6 mha from managed forest land. Compared with the BAU scenario, price is projected to increase by around 5~7% for eight crops, 1.6% for livestock and 1.6% for forestry as a result of reducing production. Globally, due to reduction in agriculture exports from U.S. as a result of the RFS2 policy, all other regions would allocate slightly more land for crop and food production, leading to gentle loss of natural grassland and natural forestland, especially in Africa, which would lose 0.5 million ha of natural grassland for crop and livestock production. The RFS2 policy would bring environmental benefits too. The accumulated carbon saving from 2010 to 2025 would be arround 392 mmt c globally with 207 mmt c from fossile fuel and 185 mmt from land. Among it, U.S. alone would contribute 300 mmt c with 208 mmt c from fossile fuel and 92 mmt c from land.

As the biofuels are emerging as promising alternative transportation fuels across the world, they also offer huge potential for international trade in biofuels. A number of trade barriers such as import tariffs and domestic support have limited the scope for trade in biofuels. The purpose of this study is to analyze the implications of U.S. biofuel mandates, subsidies and import tariffs on global trade and welfare. We utilize the GTAP-BIO model, which was developed as a customized version of the Global Trade Analysis Project (GTAP) model capable of analyzing domestic and trade policy issues associated with biofuels (Birur, 2010). We supplement this model with updated and detailed sectoral level information on feedstock crops, different types of first and second generation biofuels and their byproducts. This highly refined data base facilitates the model for simulating changes in cropping patterns at individual crop level, land use changes, commodity prices, etc. We analyze the following policy scenarios in this study: (a) implementation of volume requirements consistent with the U.S RFS2 volumes for the year 2022 relative to a starting point of the base year 2004, (b) reduction in the ethanol specific import tariff from 54 ¢/gallon to 45 ¢/gallon, so that there will be “parity” between the U.S. and exporting country’s ethanol price, (c) Complete removal of the U.S. ethanol blenders’ credit and import tariff on ethanol, (d) combined implementation of (a) and (c) policy scenarios. This paper offers insights regarding the prospective policy options that can affect potential trade in biofuels amongst the major producing countries, such as the extent to which a removal of U.S. import tariff on ethanol affects pasture and forest land conversion in Brazil.

With the rising global interest in energy security and climate change mitigation, biofuels have gained the prominent attention of researchers and policy makers. The U.S. has emerged as the leading producer of biofuels and is aiming for achieving a target of 36 billion gallons of renewable fuels by 2022 under its updated renewable fuels standard (RFS2) policy. In this paper, we study the longer-term global implications of large-scale renewable fuels production in the U.S. We utilize the GTAP v7.1 data base and introduce a detailed breakdown of agricultural crops, first and second generation biofuels and by-products. We update this fully disaggregated data base to reflect the 2010 global economy, based on secondary data for the sectors and regions included. We adapt the Applied Dynamic Analysis of Global Economy (ADAGE) model developed by Ross (2009) into a recursive dynamic framework and introduce agriculture, biofuels, and land use linkages. We construct a dynamic baseline from 2010 through 2050 in five-year time steps. The dynamics in the model comes from growth in GDP, population, capital accumulation, labor productivity, growth in natural resource stocks, and technological changes in the energy intensive and agricultural sectors. We implement a representative RFS2 policy scenario in the U.S for 2025, using two alternative approaches: (i) RFS permits approach – which assumes biofuels and petroleum fuels are perfect substitutes after adjusting for energy content, and (ii) Target share of biofuels in transportation fuels approach – which treats biofuels and petroleum fuels as imperfect substitutes. Both approaches offer insights regarding potential policy impacts, particularly on the international market and indirect land use change. Because the share approach keeps the biofuels share fixed in the regions outside the U.S., it does not result in dramatic changes in the rest of the world. In the permits approach, however, the regions without a specific policy requiring a given level of biofuels tend to reduce biofuels consumption. This is a result of the reduction in relative price of petroleum products as U.S. policy increases demand for biofuels and reduces global demand for petroleum, making renewable fuels less cost-competitive in the rest of the world.

There is general consensus in the scientific literature that human-induced climate change has taken place and will continue to do so over the next century. The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change concludes with “very high confidence” that anthropogenic activities such as fossil fuel burning and deforestation have affected the global climate. The AR4 also indicates that global average temperatures are expected to increase by another 1.1°C to 5.4°C by 2100, depending on the increase in atmospheric concentrations of greenhouse gases that takes place during this time. Increasing atmospheric carbon dioxide levels, temperature increases, altered precipitation patterns and other factors influenced by climate have already begun to impact U.S. agriculture. Climate change will continue to have significant effects on U.S. agriculture, water resources, land resources, and biodiversity in the future as temperature extremes begin exceeding thresholds that harm crop growth more frequently and precipitation and runoff patterns continue to change. In this study, we provide an assessment of the potential long-term implications of climate change on landowner decisions regarding land use, crop mix, and production practices in the U.S., combining a crop process model (Environmental Policy Integrated Climate model) and an economic model of the U.S. forestry and agricultural sector (Forest and Agricultural Sector Optimization Model). Agricultural producers have always faced numerous production and price risks, but forecasts of more rapid changes in climatic conditions in the future have raised concerns that these risks will increase in the future relative to historical conditions.

A key consideration for development of energy and climate policy affecting the forestry and agricultural sectors is that the selection of specific mechanisms implemented to achieve bioenergy production and/or greenhouse gas (GHG) mitigation targets may have substantial effects on landowner incentives to adopt alternative practices. For instance, the prices of allowances and offsets are expected to diverge under some policies being considered where there is a binding cap on the quantity of offsets from the agricultural and forest sectors. In addition, provisions that limit or exclude specific practices from receiving carbon payments will affect the quantity and cost of GHG mitigation opportunities available. In this study, the recently updated Forest and Agriculture Sector Optimization Model with GHGs (FASOMGHG) was used to estimate GHG mitigation potential for private land in the contiguous U.S. under a variety of GHG price policies. Model scenarios suggest that U.S. forestry and agriculture could provide mitigation of 200 – 1000 megatons carbon dioxide equivalent per year (Mt CO2e/year) at carbon prices of $15 to $50/tCO2e. Binding limits on offsets have increasingly large effects on both the total magnitude and distribution of GHG mitigation across options over time. In addition, discounting or excluding payments for forest sinks can reduce annualized land-based mitigation potential 37-90 percent relative to the full eligibility scenario whereas discounting or excluding agricultural practices reduces mitigation potential by less than 10 percent.

With the increasing research interests in biofuels, global implications of biofuels production have been generally examined either in a partial equilibrium (PE) or general equilibrium (GE) frameworks. Though both of these approaches have unique strengths, they also suffer from many limitations due to complexity of addressing all the relevant aspects of biofuels. In this paper we have exploited the strengths of both PE and GE approaches for analyzing the economic and environmental implications of the U.S. policies on corn-ethanol and biodiesel production. In this study, we utilize the Forest and Agricultural Sector Optimization Model (FASOMGHG: Adams et al. 1996, 2005; Beach et al. 2009), a non-linear programming, PE model for the United States. We also use the GTAP-BIO model (Birur et al. 2008), a multi-region, multi-sector CGE model for global-scale assessment of biofuels policies. Following Britz and Hertel (2009), we link the GTAP-BIO model through a static, quadratic restricted revenue function obtained from perturbing crop prices from the FASOMGHG model. With this linkage we implement the U.S. Corn ethanol and biodiesel scenarios in the GTAP-BIO model and obtain the FASOMGHG-consistent, global land use changes. The resulting crop price changes from the GE model are fed back into the FASOMGHG model to obtain the disaggregated impacts in the U.S.

Consumer concerns regarding food safety can have substantial impacts on their consumption patterns. Thus, understanding consumer response to food safety information is important for quantifying consumer response to food safety events, predicting market impacts, and developing appropriate risk communication strategies. Flexible demand systems have gained much popularity in analyzing effects of food safety outbreaks on consumer demand because of their ability to capture interactions between the demand for substitutable and complementary goods. Using Italian scanner data on meat sales, we show the economic importance of accounting for the impact of avian flu outbreaks on group expenditures for meats in a dynamic Almost Ideal Demand System (AIDS) specification with intertemporally optimizing consumers. Failure to account for this form of expenditure endogeneity results in a substantial understatement of the food safety effect.

To better understand how information about potential health hazards influences food demand, this case study examines consumers’ responses to newspaper articles on avian influenza, informally referred to as bird flu. The focus here is on the response to bird flu information in Italy as news about highly pathogenic H5N1 avian influenza (HPAI H5N1) unfolded in the period October 2004 through October 2006, beginning after reports of the first outbreaks in Southeast Asia and extending beyond the point at which outbreaks were reported in Western Europe. Estimated poultry demand, as influenced by the volume of newspaper reports on bird flu, reveals the magnitude and duration of newspaper articles’ impacts on consumers’ food choices. Larger numbers of bird flu news reports led to larger reductions in poultry purchases. Most impacts were of limited duration, and all began to diminish within 5 weeks.

We examine the effects of domestic advertising and promotion expenditures on meat demand, extending previous efforts in several areas, including the use of more recent data, employing a complete demand system and simultaneously measuring the impacts of generic pork and beef advertising and food safety information on the demand for beef, pork, and poultry. Using the Generalized Almost Ideal Demand System (GAIDS), own- and cross- beef and pork advertising and own- and cross- beef, pork, and poultry food safety effects are measured jointly and consistently. To allow for a more complex dynamic response of advertising and food safety effects, the flexible distributed lag technique of Mitchell and Speaker (1986) is employed. The coefficients on pork advertising in the pork and poultry equations are highly significant. The coefficients on beef advertising are only statistically significantly different from zero in the poultry equation indicating the primary impact from these efforts is a cross-commodity effect. To investigate the economic significance of these effects, elasticities for price, expenditure, food safety and advertising are calculated and compared. Consistent with previous work we find the impacts of advertising and food safety effects to be economically small compared with price and expenditure effects.

In January 2000, the Nevada Board of Wildlife Commissioners (Wildlife Commissioners) directed Nevada’s state game management agency, the Nevada Department of Wildlife (NDOW), to secure wildlife damage management (WDM) assistance from the United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services Program (WS) for the purpose of protecting a struggling population of pronghorn antelope located in northern Washoe County, Nevada. NDOW had documented, over a several-year period, that this northern Nevada antelope population had consistently demonstrated unacceptably low fawn recruitment levels. While NDOW was unsure of the cause for this consistent poor production record, the Wildlife Commissioners suspected “excessive” fawn predation to be one of the primary causes for the unacceptable recruitment levels. WS was contracted by NDOW to initiate fawn protection efforts for this population with an emphasis on coyote predation management. In collaboration with WS, NDOW mapped out a designated protection area where WDM activities would be conducted, established that WDM activities would only be conducted during the vulnerable fawning period, and set a target recruitment level for the herd which, when reached, would conclude the WDM activities. Prior to the initiation of WDM actions, WS personnel conducted several predator surveys to establish the coyote incidence level within the designated protection area. These data were to serve as a baseline indicator to help gauge the effectiveness of ongoing coyote removal efforts. While WS removed any coyote encountered within the specified protection area during the critical fawning season, removal efforts were primarily directed at older, territorial coyotes. The doe-to-fawn ratio was determined by NDOW at the end of each season, and when the ratio reached NDOW’s predetermined level of 32 fawns per 100 does, WDM activities were terminated. Additional benefits stemming from the antelope project included reduced predator pressure on other game species inhabiting the same area (such as mule deer), and collection of coyote blood samples for the monitoring of wildlife diseases such as plague.

The tobacco quota buyout is expected to have significant impacts on U.S. tobacco markets, farmers, tobacco-dependent communities, and public health. Using data from four surveys of a panel of North Carolina tobacco farmers conducted between 1997 and 2004, we investigate changing farmer attitudes towards and intentions following a quota buyout.

Basic economic theory predicts that a consumer's willingness to pay for a good is affected by the presence of complements and substitutes. In an auction setting, this theory implies that the presence of complements would increase bid prices for a good, while the presence of substitutes would decrease bid prices for a good. However, several experimental auction studies have sold complementary or substitutable products without regard for the effects these actions could have on bidding behavior. Using data from an experimental auction specifically designed to test the effect of complements and substitutes on bids, we used both unconditional tests and conditional tests where we derived demand flexibilities to analyze whether selling complementary and substitutable products has an effect on bids. Our results show that the availability of complementary and substitutable products affects bids in the expected directions. This finding has important implications for researchers who design experimental auctions.

As U.S. farm income from tobacco production has declined in recent years, there has been increased interest in developing alternative sources of farm revenue to replace lost tobacco income, particularly in tobacco-dependent communities of the southeastern United States. The recent end of the tobacco quota program is expected to accelerate the exit of tobacco farmers and has heightened concern regarding the availability of profitable substitutes for tobacco. In this study, we examine the impact of farm, household, and market characteristics on tobacco farmer interest and success in on-farm and off-farm income diversification. Using survey data collected from a panel of North Carolina tobacco farmers in 1997, 1999, 2001, and 2004 combined with market data collected from secondary sources, we evaluate the influence of farmer preferences, resource endowments, market incentives, risk, and biophysical factors on tobacco farmers' attitudes regarding diversification into non-tobacco products, the extent to which they reallocated resources towards non-tobacco products, and their success in identifying profitable alternatives to tobacco production. Our research contributes empirical findings to the public dialogue concerning the ability of tobacco farmers and tobacco-dependent communities to adjust to structural changes taking place in the tobacco market.

Many agricultural commodities have industry-funded generic promotion and/or research ("checkoff") programs designed to improve the economic performance of producers. To determine the effectiveness of these programs, the net benefits to producers attributable to activities funded by the checkoff must be separated from those due to other factors influencing commodity markets. One such factor that is very important in many agricultural commodity markets is the effect of government programs. However, studies evaluating the returns to checkoff programs often do not explicitly discuss the impact of pre-existing distortions caused by federal farm programs. Because the distortions caused by farm programs can be quite large, this omission can lead to seriously biased estimates of the returns to the checkoff programs. In this study, we develop a model that captures the influence of two Federal programs (loan deficiency payments to farmers and subsidies to consuming mills) on the estimated returns to the Cotton Research and Promotion Program. Using an econometrically estimated model of the U.S. cotton market, we find that the program interaction effects have a large impact on checkoff program returns.

The U.S. Department of Agriculture (USDA) and National Agricultural Statistics Service (NASS) conducted a nationwide survey of agricultural producers to determine what proportion of producers were sustaining losses caused by wildlife and which wildlife species were believed to be responsible for the damage. The survey was conducted in August 1989 for the USDA, Animal and Plant Health Inspection Service, Animal Damage Control (ADC). Results are based on useable responses received from 5,085 farmers in the eastern United States. The results presented here may differ from a previous press release by NASS because losses and animals causing losses were determined specifically for all producers of each commodity rather than all losses to producers as classified by primary farm types.