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Inhaltsverzeichnis

Frontmatter

Introduction

Biofuel policies remain one of the most misunderstood and controversial set of government actions that has ever impacted contemporary food commodity price and policy analysis. The goal of this book is to rectify this by carefully explaining how it all happened. There have been eight years of turmoil in world food grain/oilseed prices. Biofuel policies effectively began a new (modern) era for agriculture, particularly affecting grains/oilseed prices directly. It all started in late 2006 with the six-month boom in corn prices and by the second half of 2007, all food commodity prices caught fire, tripling from their 2005 levels, followed by a collapse in prices in the second-half of 2008 and early 2009. Economists quickly pointed out that this was just another boom and bust as in previous decades, with sectoral supply/demand shocks, inventory adjustments, and macro-economic factors explaining pretty much everything. However, then food commodity prices marched straight back up in 2010–2011 and were still high in 2012. Even in 2013, with record world grain supplies and stocks, prices were relatively high with corn prices double their historical levels prior to late 2006 and commentators were puzzled by the entire grain-oilseed complex into 2014, with exclamations like “beans are in the teens,” how can that be? Well, because this time it is different. And the difference is simply biofuel policies.

Chapter 1. How Biofuel Policies Ushered in the New Era of High and Volatile Grain and Oilseed Prices

So far, we have emphasized the importance of the crop-biofuel-energy-crude oil price links, and the resulting two states of nature where corn prices can go no lower than when locked onto crude oil prices through ethanol and gasoline prices, and with tax credits.1 To illustrate the importance of price links and how quantity (sectoral supply/demand) shocks may not be the principal driving force in explaining food commodity price levels, consider Figure 1.1. Production of biofuels accelerated in mid-2000s and has now leveled off. Many commentators use that fact along with the pronounced volatility in grain prices in the meantime as a proof that biofuels are not the leading cause of high prices (e.g., Hamelinck 2013).

Chapter 2. The Economics of Biofuel Policies: The Theory of Corn-Ethanol and Ethanol-Gasoline Price Links

Wright (2011,32) argues that:

Recent price spikes are not as unusual as many discussions imply. Further, the balance between consumption, available supply, and stocks seems to be as relevant for our understanding of these markets as it was decades ago …the tools at hand are capable of explaining the main forces at work.

Chapter 3. Measures of Biofuel Policy Impact on Food Commodity Prices

The previous chapter developed the required analytical framework in order to determine how much of the food grain and oilseed price increase observed over the last several years is due to biofuel policies. We established the price links between corn and ethanol, and between ethanol and gasoline. However, we failed to provide empirical estimates of the ethanol price premiums due to the tax credit versus the mandate; these premiums were far too high. Our predicted monthly corn prices went far too low (and even negative). Using annual data, Drabik (2011) estimates that actual ethanol price was, on average, 3.6 times that of the estimated free market levels as per equation (2.2). Therefore, historical ethanol policy price premiums have to be adjusted to account for the ethanol shutdown price (at positive corn prices). In other words, we have to first determine the intercept of the ethanol supply curve and then adjust the data for the redundancy in ethanol price premiums (which we call “water” in a biofuel price premium). This is the first order of business in this chapter; namely, derive the ethanol supply curve and its intercept by analyzing the link between corn and ethanol quantities (the “horizontal link” to complement the “vertical” price link derived in the previous chapter), including the “recycling effect” of DDGS.

Chapter 4. A Forensic Analysis of the Food Commodity Price Boom of 2008

T

his chapter will contribute to the understanding of how this price spiral happened, which has quickly become one of the most analyzed period of food commodity price movements in history. As Timmer and Dawe (2010, 8) state:

No lessons from the food crisis are of much relevance without understanding how this price spiral happened.

Chapter 5. A Critique of the Literature Analyzing Biofuel Policy and the 2008 Food Commodity Price Boom

M

ost academics analyze issues through the lens of their own expertise. Therefore, it should be no surprise when a recently minted Nobel Prize-winning behavioral economist wrote in the New York Times that:

Commodities followed the euphoria cycle that we had along with housing. Shiller (2008)

Chapter 6. The Economics of Developing Country Policy Responses and Biofuel Policies

Recall in Chapter 1 that corn prices almost doubled in the six months beginning in September 2006, precipitating the Mexican tortilla crisis in January 2007 and India’s ban of wheat exports the following month. This was the beginning of a long list of countries restricting exports (export bans, export taxes, value-added tax rebates, and actions by state trading enterprises and government to government sales) and promoting imports (lowering import barriers and manipulating domestic prices to be below world prices).1 Even peasants hoarded rice (Timmer 2008), which can have the same effects as a developing country policy response. Developing countries are presumed to be responding to a world market price shock, which we argue was due to biofuel policies whereas most others argue it was a “perfect storm” of factors. The source of the shock does not concern us here; it is the economics of the policy responses.

Chapter 7. An Enhanced Exposition of the Corn-Ethanol-Energy Price Linkages and Implications for Time Series Analysis of Biofuel Policy Impacts

The purpose of this chapter is to critically assess a burgeoning literature that uses high-frequency time series (HFT) econometric analysis (using daily, weekly or monthly data) that frantically seeks a link between feedstock and biofuel prices (say corn and ethanol), biofuel and gasoline/diesel prices, or directly between feedstock (e.g., corn) and crude oil prices. All of these papers explicitly or implicitly state that their objective is to determine the impact of biofuel policies on food commodity prices, and that their results have policy implications. To them, the impact of biofuel policies simply depends on the size and significance of the positive relationship between these prices: feedstock, biofuel, energy, or crude oil prices. Granger causality tests are also undertaken (studies even find corn prices “cause” crude oil prices!) If no link is found or the evidence is mixed then biofuel policies’ impact on crop prices is just that: none or unclear, respectively. All papers in this HFT econometric literature come to one of these three conclusions on biofuel policies’ impact on commodity markets: yes, no, or maybe.

Chapter 8. The Impact of Biofuel Policies on Food Commodity Price Volatility

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he controversy over biofuel policies has sparked debate not only on what caused the high levels of grain and oilseed prices, but also the alleged increase in price volatility and its potential deleterious effects. To illustrate, take two headlines, each involving a Cornell professor:

“Cornell’s Per Pinstrup-Andersen: Don’t Believe the Hype (and Data) Surrounding Food Price Crises. Cites Food Price Volatility as Greater Danger than High Food Prices,” an International Food Policy Research Institute (IFPRI) news headline on Per Pinstrup-Andersen (2013b)

Chapter 9. The Economics of Biodiesel and the Central Role of the European Union’s Policies

Biodiesel averaged 20 percent of total world biofuel production by volume in the period 2010–2012.1 Biodiesel is expected to reach 25 percent of total biofuel volume by 2025. However, its share in vehicle miles traveled is higher because a gallon of biodiesel obtains 91.3 percent of the miles traveled compared to a gallon of diesel whereas ethanol produces an estimated 70 percent of the miles traveled as gasoline—and diesel engines, on average, get approximately 37 percent more miles per gallon than gasoline (see Box 2.2). The European Union, United States, and Brazil are, respectively, the world’s largest producers and consumers of biodiesel. The European Union consumed 42 percent of total biodiesel in 2013 (down from 75 percent in 2005), and it is expected to decline to 40 percent in 2020 (OECD/FAO 2014).

Chapter 10. The Complex Structure of the US Biofuel Mandate: A Handbook

Taleb (2012, 373) notes that “We have developed a fondness for neomanic complication over archaic simplicity.” Never have truer words been spoken when describing and explaining the logic of the US biofuel mandate under the rubric of the renewable fuel standard (RFS) with its nested structure and many interactions. For example, we delayed our explanation for the prediction errors in 2011 and 2013 of the soybean oil-biodiesel price linkage model because it hinges on the interaction of sub-mandates in the RFS. It turns out that the nested structure of the US mandate also has implications for corn-ethanol and corn prices, and trade in both ethanol (including two-way trade with Brazil) and biodiesel. Therefore, prices of both biofuels and three main feedstocks: corn, soybean, and canola oil and sugarcane (and, thus, sugar) are being affected by the way in which the complex US RFS mandate works. Furthermore, the primary driver of prices and trade since early 2013 has been the ethanol blend wall in the United States and more recently, uncertainty in what the Environmental Protection Agency (EPA) will finally rule for 2014 (which at the time of writing, has still not been resolved),1 both having implications for the way forward in 2015 and beyond. Therefore, we devote an entire chapter to explain the economics of the complex structure of the US mandate, given its importance, and as the reader will quickly find out, its complexity.

Chapter 11. The Economics of Brazil’s Sugarcane-Ethanol/Sugar Complex and Policies

The previous chapter emphasized the importance of the complex structure of the US mandate and how the nested mandates interact with one another. Brazilian sugarcane ethanol is central to the outcome, being an advanced biofuel. Brazil was the world’s largest ethanol producer until the United States surpassed it in the mid-2000s, but Brazil is still the world’s largest net exporter of ethanol. However, this may not last either as our discussion in the previous chapter showed how the ethanol blend wall in the United States has made biomass-based diesel the biofuel of choice (especially because of the 1.5 to 1.7 ethanol equivalence values) and has converted the United States into a significant net exporter of ethanol in recent years. Brazilian sugarcane-ethanol, in 2013 and 2014, has to compete head on with corn-ethanol (before, it received higher D5 RIN prices as an advanced biofuel). The only advantage Brazil’s sugarcane ethanol receives is higher prices with the California Low Carbon Fuel Standard (LCFS); thus, there is still two-way trade: Brazil exports sugarcane-ethanol to the United States and the United States exports ethanol to Brazil. These types of ethanol are identical products; it is just that their greenhouse gas (GHG) emissions thresholds differ and, therefore, the way in which binary GHG emission thresholds operate in the US renewable fuel standard (RTS along with the California LCFS) causes the two-way trade (Meyer et al. 2012).

Chapter 12. The Interaction Effects Among Biofuels, Policies, and Countries

The models developed in this book span different feedstocks, biofuels, and countries and, therefore, we have already come across several important interactions. For example, we closed the previous chapter on how the expiring US tax credit impacted Brazilian ethanol prices. In the chapter before that, we showed how the complex structure of the US mandate affected domestic and international ethanol and biodiesel prices and trade. Throughout the book so far, we showed how market shocks or policy changes can affect regime changes (e.g., the mandate versus tax credit binding). These interactions can occur across biofuel policies, within a country and across countries and biofuels.

Chapter 13. The Impact of Biofuel Policies in the Future: Some Concluding Remarks

We have analyzed the great food commodity price boom since late 2006 using a strict meat-and-potatoes approach. We do not discuss tulip manias or Malthus’ revenge. We do not wax poetic about how Henry Ford had ethanol as his fuel of choice for the Model-T (this time is different) or that prohibition was a conspiracy to monopolize the gasoline market. We did not use the fanciest statistical techniques known to mankind nor did we use Big Data—we were not flashy and, therefore, minimized the use of algos and routers. We did not run numerical simulations with potentially unbounded price expectations to generate bubble like price behavior. Nor did we indulge in instant economics or take shortcuts. We take the straight and narrow path to the core of the issue: the economics of blend mandates and the new price linkages between crops and biofuels and between biofuels and energy (gasoline/diesel and crude oil) prices where sectoral supply/demand shocks have a very different impact on food commodity prices than before. In doing so, we just stuck to the basics—an application of microeconomics to biofuels production and consumption, the price and quantity links backwards to the feedstocks and forward to energy and crude oil markets, with due regard to co-products, joint products and by-products along the way. We simply assume profit-maximizing agents under competition.

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