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The federal tax code provides preferential treatment for the production and use of renewable energy. We report estimates of the subsidies' effects on greenhouse gases (GHG) emissions developed in a recent National Research Council (NRC) Report. Due to lack of estimates of the impact of tax provisions on GHG emissions, new modeling studies were commissioned. The studies found, at best, a small impact of subsidies in reducing GHG emissions; in some cases, emissions increased. The NRC report also identified the need to capture the complex interactions among subsidies, pre-existing regulations, and commodity markets.

We present a new framework to identify demand and supply elasticities of agricultural commodities using yield shocks - deviations from a time trend of output per area, which are predominantly caused by weather fluctuations. Demand is identified using current-period shocks that give rise to exogenous shifts in supply. Supply is identified using past shocks, which affect expected future prices through inventory accretion or depletion. We use our estimated elasticities to evaluate the impact of ethanol subsidies and mandates on world food commodity prices, quantities, and food consumers' surplus. The current US ethanol mandate requires that about 5 percent of world caloric production from corn, wheat, rice, and soybeans be used for ethanol generation. As a result, world food prices are predicted to increase by about 30 percent and global consumer surplus from food consumption is predicted to decrease by 155 billion dollars annually. If a third of the biofuel calories are recycled as feed stock for livestock, the predicted price increase scales back to 20 percent. While commodity demand is extremely inelastic, price response is muted by a significant supply response that is obscured if futures prices are not instrumented. The resulting expansion of agricultural growing area potentially offsets the CO2 emission benefits from biofuels.

Every now and then a set of technologies becomes available that sets off a period of “combinatorial innovation.” Think of standardized mechanical parts in the 1800s, the gasoline engine in the early 1900s, electronics in the 1920s, integrated circuits in the 1970s, and the internet in the last decade or so. The component parts of these technologies can be combined and recombined by innovators to create new devices and applications. Since these innovators are working in parallel with similar components, it is common to see simultaneous invention. There are many well-known examples, such as the electric light, the airplane, the automobile, and the telephone. Many scholars have described such periods of innovation, using terms such as “recombinant growth,” “general purpose technologies,” “cumulative synthesis” and “clusters of innovation.” The internet and the web are wonderful examples of combinatorial innovation. In the last 15 years we have seen a huge proliferation of web applications, all built from a basic set of component technologies. The internet itself was a rather unlikely innovation; I like to describe it as a “lab experiment that got loose.” Since the internet arose from the research community rather than the private sector, it had no obvious business model. Other public computer networks, such as AOL, CompuServe, and Minitel, generally used a subscription models, but were centrally controlled and offered little scope for innovation at the user level. The internet won out over these alternatives, precisely because it offered a flexible set of component technologies which encouraged combinatorial innovation.

The food commodity price boom of 2003–2008 was the most notable in the past several decades, having a substantial impact on global economic activity. It affected developing nations by impacting real output, the balance of payments, government budgetary positions and, most important, the well being of the very poor. High commodity prices also affected developed countries, by transmitting business cycle disturbances and creating inflationary pressures. Several recent studies tried to identify and quantify the factors that caused the food commodity price boom of 2003–2008 (see, for instance, Isabel Vansteenkiste 2009). These studies suggest that one key factor is growth in demand, which, since the 1980s, has outpaced growth in supply. Other studies argued that biofuel is the culprit, since it increases demand for staple crops (see, for instance, Donald Mitchell 2008). All these studies, however, assumed competitive markets and did not consider the impact of biofuel on energy costs to farmers. Moreover, they ignored the Organization of Petroleum Exporting Countries (OPEC). These studies leave us perplexed regarding the true impact of biofuel on food commodity prices— was it or was it not an important contributor to the recent food commodity boom? We believe that to answer this question, the interactions between energy and food must be modeled and OPEC introduced, and the impact of biofuels compared with other factors that are argued by the literature to be important. This paper aims to analyze the multiple contributions of energy and biofuels to the increase Are Biofuels the Culprit? OPEC, Food, and Fuel

Debate has raged about the consequences of US corn-based ethanol. Studies sought to identify how much it affected world commodity markets (Josef Schmidhuber 2006; Dileep Birur, Thomas Hertel, and Wallace Tyner 2008; Seth D. Meyer, Pat Westhoff, and Wyatt W. Thompson 2009). The popular press speculated on the potential for growing US ethanol production to drive up world prices, with unintended consequences for world food supplies and changes in land use outside the United States, possibly leading to increased greenhouse gas emissions (Angelo Gurgel, John M. Reilly, and Sergey Paltsev 2007; Martin Banse, Hans van Meijl, and Geert Woltjer 2008). But these discussions focus narrowly on one set of related markets, namely those for agricultural commodities. Other studies have estimated that greater ethanol availability reduces gasoline prices to the benefit of US motor fuel consumers (Xiaoyang Wang 2008; Xiaodong Du and Dermot J. Hayes 2009). We focus on the direct effects on the US natural gas market of US biofuel policies, specifically tax credits, ethanol tariff, and mandates. Increased ethanol production based on current technologies and policies is likely to lead to greater corn demand and indirectly to more land allocated to growing corn. Both these activities use natural gas either directly for firing an ethanol plant or indirectly through the fertilizers and other chemical inputs used to grow corn. Ethanol Policy Effects on US Natural Gas Prices and Quantities

The Energy Independence and Security Act of 2007 (EISA) sets a goal for 36 billion gal lons of biofuels available by 2022 according to the Renewable Fuels Standard (RFS). The RFS is accompanied by tax credits which are sub ject to change. Tax credits are used as produc tion incentives for different types of ethanol made from corn starch and cellulosic material.1 There are arguments for and against the use of tax credits. Generally, tax credits are considered as welfare-reducing instruments similar to subsi dies. However, tax credits could be rationalized as improving energy security and reducing green house gas emissions as they can correct for mar ket failures (Wallace E. Tyner 2007 and Paul N. Leiby 2007). Furthermore, tax incentives for an infant industry such as cellulosic ethanol might be justified where there are dynamic learning costs (Ian Sheldon and Matthew Roberts 2007). It is estimated that tax credits could cost taxpay ers nearly $28.7 billion annually by 2022 (Harry

Tax expenditures are a major source of support for energy related activities in the federal budget exceeding direct budget support for energy by a factor of nearly six. Focusing on the policy goals of reducing greenhouse gas emissions and petroleum consumption, I find these tax expenditures highly cost ineffective at best and counterproductive at worse. The tax credit for ethanol is an example of a cost ineffective subsidy. The cost of reducing CO2 emissions through this subsidy exceeded $1,000 per ton of CO2 avoided in 2006. A change in the way the subsidy is administered provides an opportunity to measure its incidence. I find that the entire subsidy is passed backward to ethanol producers and possibly farmers. Consideration of market structure suggests that farmers receive little of the subsidy.