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Disturbances in the Grain Markets: What is really the cause? By Reinout Polders Student of the Erasmus University Rotterdam* July 2009 Abstract This paper investigates the disturbances in the grain markets in the year 2008. We study the possible determinants behind the grain price increases. The influence of demand factors like biofuel demand and the size of grain stocks are very small. We can draw the same conclusion for the supply factors; agricultural policy, grain production and the oil price. Since the reason for the disturbances is not in the market fundamentals, we investigate the speculation factor. We suspect that the disturbances in the grain markets were part of a commodity boom. The developments in demand and supply factors during the crisis time could have fed the panic that led to speculation in the commodity markets. We have not found any solid empirical evidence for speculation in this paper. This is a task for future research. Keywords: Grain prices, crisis, speculation *I would like to thank Lorenzo Pozzi, Chris Graham and Penny Graham for their useful comments on this paper. Introduction Just before the financial bubble exploded in 2008, oil prices were sky-rocketing. As a result of this, prices of nearly all commodities rose. These new price levels resulted in unprecedented higher inflation numbers for the Euro zone. A year later, the oil price has now returned to a more normal value of 60-70$ per barrel. The prices of commodities (especially grains) show a very similar pattern. While everyone is talking about the crisis in the financial system and global warming, a really high grain price may prove to be an even bigger problem for humanity. Being one of the most important food products, a high grain price could influence purchasing power and inflation in western countries. Yet an even bigger disaster is about to happen in developing countries, where an even consumers’ income is spent on food. A high grain price in these countries could lead to a huge food-shortage and in turn widespread starvation. This paper will therefore analyse the disturbances in the grain markets. It is not certain that we will find very relevant conclusions for policymakers. As with all markets, psychology plays an important part influencing the behaviour of agents. It could well be the case that the price increase is not the result of rational behaviour of agents influenced by market fundamentals. Yet still, we will first look at these market factors before we will deal with the speculation factor. There are a many factors that could possibly influence grain price increases. First of all, there is an increased demand in biofuels. The biofuels need ethanol, which is extracted from certain grains called oilseeds. The excess demand created by the increased popularity in biofuels could be one of the most significant factors behind the price increases in grain. Strongly linked tobiofuels is the oil price itself. As the agricultural business becomes more and more capital-intensive, the oil price is cost in the production process. The bubble in the oil market could have spillover effects on the grain markets through greater production costs, leading to an identical bubble in these markets. Besides increased demand, the grain price could also be stimulated by a lack of supply. The most direct factors on the supply-side are the harvested area and crop yield. Together, these two factors result in the total production of crops. A decline in one of these two factors could lead to under-supply. Both of these factors are in their turn affected by climate change. Though it is still not certain why and in which direction the climate is changing, there is some evidence that these changes have an 2 adverse effect on crop yields. Also, changes may reduce the amount of land that can be used as arable land in the future. A much more complicated idea is that speculation is one of the key factors behind the disturbances in grain markets. The first aspect that could have fed speculation is the decline in grain stocks. Some studies show that stocks were at an all-time low point last year. This could lead to a possible food crisis in the event of poor production. This expectation could in its turn lead to panic amongst investors; which is one of the main reasons for speculation. The second factor influencing speculation is agricultural policy. Export restraints have been introduced in major grain exporting countries. This could lead to uncertainty in the world markets, which is also a motive for panic and speculation. The fact that so many factors could influence speculation means eventually that we will discuss this phenomenon in the last chapter. Since it is mostly a psychological factor, it will be difficult to find solid evidence for speculation. Given the big variety of suspected factors, every factor has its own chapter. We will start with a chapter that compares this crisis with historical crises. The chapters dealing with the market fundamentals will be divided into two groups; demand factors and supply factors. After dealing with the market fundamentals, we will investigate the speculation factor. In total, there will be eight different chapters, culminating in an overall conclusion in chapter ten. 3 Table of Contents Introduction Table of Contents Chapter 2: Historical Grain crises page 2 page 4 page 5 Demand Factors Chapter 3: Biofuels page 9 Chapter 4: Grain Stocks page 12 Supply Factors Chapter 5: Area Harvested and Crop Yields page 13 Chapter 6: Agricultural Policy page 17 Chapter 7: Climate Change page 19 Chapter 8: The Oil Price page 21 Chapter 9: Speculation page 24 Chapter 10: Conclusion page 26 Literature List Page 28 Appendix Page 30 4 Chapter 2: Historical Grain crises Every age has had its food crisis. It is therefore questionable whether the crisis today is that special. It could well be the case that this crisis is comparable to all other crises. In order to draw a good conclusion, it is necessary that we have information about the determinants behind historical crises. The most extensive research in this field is Commodity Price Volatility and World Market Integration since 17001. The research draws a couple of very relevant conclusions for this thesis. The first conclusion is that commodity price volatility has decreased over time. This is an important result, because it supports the idea that this crisis isn’t a normal crisis. Price increases have never been so big in absolute terms in the last century. The second conclusion is that commodity prices have always shown greater volatility than manufacturing prices. This shows that grain prices can be seen as relatively volatile in general. The third and last conclusion is that globalization has a negative impact on price volatility. In closed economies, prices tend to be much more volatile. This conclusion is also striking with the globalization in the last decades. Figure 1 Commodity Prices Price (US$) yearly average 12 10 8 6 4 2 2008 2006 2004 2002 2000 1998 1996 1994 1992 1990 1988 1986 1984 1982 1980 1978 1976 1974 1972 1970 1968 1966 1964 1962 1960 0 year Soybean Price Wheat Price Corn Price 1 David S. Jacks, Kevin H O'Rourke, and Jeffrey G. Williamson: Commodity Price Volatility and World Market Integration since 1700 NBER Working Paper No. 14748 February 2009 JEL No. F14,N7,O19 5 Figure 1 confirms the conclusion that the price increases in grains last year were bigger than any other price increases in absolute terms. Furthermore, the figure suggests that the soybean price normally isn’t correlated with the prices of wheat and corn. Yet this situation seems to have changed over the last five years. The three prices now follow exactly the same trend. These suggestions are supported by the analysis of correlations amongst the three variables. Table 1 SoybeanP6003 SoybeanP6003 Pearson Correlation WheatP6003 1 Sig. (2-tailed) Pearson Correlation 0,000 0,000 44 44 0,881(**) 1 0,938(**) Sig. (2-tailed) 0,000 N CornP6003 Pearson Correlation 0,907(**) 44 N WheatP6003 CornP6003 0,881(**) 0,000 44 44 44 0,907(**) 0,938(**) 1 0,000 0,000 44 44 Sig. (2-tailed) N 44 ** Correlation is significant at the 0.01 level (2-tailed). In the period between 1960 and 2003, the correlation between corn and wheat was higher than the other correlation numbers. The three grains are o course substitutes, so changes in supply and demand will not lead to big price differences. The same analysis has been done for the period 2004-2008: Table 2 SoybeanP0408 SoybeanP0408 Pearson Correlation 1 0,955(*) 0,035 0,012 5 5 5 0,904(*) 1 0,988(**) N Pearson Correlation Sig. (2-tailed) 0,035 N CornP0408 Pearson Correlation CornP0408 0,904(*) Sig. (2-tailed) WheatP0408 WheatP0408 0,002 5 5 5 0,955(*) 0,988(**) 1 0,012 0,002 5 5 Sig. (2-tailed) N 5 * Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). The correlations for all three grains have increased compared to the period 19602003. Also, despite the low number of observations all correlations are significant. The appendix table A4 contains the same analysis for the crisis in the 70s; correlations during this crisis were much lower. It is therefore justified to conclude that the correlation between grain prices in this crisis is remarkably high. The high 6 correlation suggests that there is one universal factor behind all three price increases. In contrast, R. G. Lewis denies that there is anything special about this crisis. In his article What food Crisis?2 he argues that inflation has a big impact on today’s volatility. This argument is also put forward in an article3 by Boonekamp, in which he seeks to explain the cause of the higher prices only in terms of short-term excess demand. When corrected for inflation, this crisis is somewhat less severe than the crisis in the 1970s. Also, the weight of grain in the total consumption basket of consumers has declined. This leads to the conclusion that the crisis is less relevant for the regular consumer, which is confirmed by a study4 on the correlation between inflation and grain prices. Boonekamp has a point in both cases, but the narrow scope reduces the relevance of his conclusion for this thesis. As the first study already argued; prices are much more stable nowadays. It might not be the all-time biggest volatile movement of the price, but still it remains special in the current situation. The author also forgets to widen the scope to developing countries. Even if grains no so important to US consumers anymore, they still are for consumers in poor and developing countries. Since more than half of the world’s population is in these countries, we’re talking about an actual human crisis now. Though very extensive and interesting, the studies above don’t discuss the determinants behind the prices for grains. Luckily for this thesis, there is a good study5 that describes the determinants during and after the food shock in 1996. In their study, Light and Shevlin conclude that food prices for consumers are less dependent upon farmers’ profits. While the profit of farmers had a clear downward trend, food inflation remained modest. This shows that actual agricultural value loses importance as a determinant of retail food prices. Also, the agricultural business has become much more concentrated, leading to more economies of scale. This reduces production costs, and makes it easier to respond to shocks in the markets. Overall, this study predicts that food inflation will become much more stable. Though this Robert G. Lewis What Food Crisis? Global Hunger and Farmers’ Woes(2008) in World policy Journal Spring 2008 p 29-35 3 Loek Boonekamp The Grain of truth(2008) in OECD Observer No 267 May-June 2008 4 Bart Hobijn, Commodity Price Movements and PCE Inflation (2008) Volume 14, Number 8 November 2008 Federal reserve Bank of New York In this study, Hobijn reveals that crops accounted for 1 percent of PCE inlaftion, while oil and gas accounted for 2.8 percent. Even though they have some influence on other prices, these two commodities were not that significant behind the high inflation. 5 J. Light and T. Shevlin: The 1996 Grain price shock: how did it affect food inflation? (1998) in Monthly Labor review (august 1998) 2 7 study concentrates on retail prices instead of commodity prices, some important lessons can be learned for the determinants of the commodity prices. Retail prices are of course correlated to commodity prices. This means that lower retail inflation should also imply lower commodity price inflation. Overall, this study confirms the conclusion of the first study. The 1996 food inflation was not that severe. A better comparison with the situation today is to be found in the period 1972-1975. Volatility of commodity prices was at an all-time high level at that time. Cooper and Lawrence try to describe the determinants behind these shocks in their study The 1972-1975 Commodity Boom6. The main conclusion they draw in this study is that agricultural products were a victim of cyclical high demand and shortages in supply, leading to speculation. The main argument for this point is that trading in commodity futures exploded; both prices and the volume of positions increased. Also contributing to the speculation was the idea that resources could get exhausted; supply would be outpaced by demand in the long-run. The third factor behind speculation was the expected inflation, caused by the rise in oil prices. Investors tried to get ahead of this inflation and bought enormous amounts of grain. This inflation argument was supported by exchange rate uncertainties. The last factor that possibly led to speculation was the US policy on commodity prices. In 1973, the United States introduced a ceiling for some commodity prices. This may have led to a run on commodities; investors needed to buy fast in order to make a profit. The four studies just discussed support the idea that this is not just a normal crisis. While commodity price volatility has reduced with time and globalization, we now experience the greatest volatility in absolute terms ever noticed. Though the relative price increase is not an all-time high, it is a strong change in the trend of stable prices. Also, the studies give us a direction to find out which determinants might be relevant for this crisis. The empirics show that it is likely that there is a universal factor behind the price increases. 6 R. N. Cooper and R.Z. Lawrence The 1972-1975 Commodity Boom(1975), in Brookings Papers on Economic Activity, 3 8 Chapter 3: Biofuels Many economists suspect that the increased demand for biofuels is an important factor. Some grains can be processed into ethanol, which is a very clean substitute for gasoline and other oil products. Yet the high costs of the production process has kept market demand low for a long time. The only way to encourage industries to use ethanol was through subsidies. This changed when the crude oil price rose to $140 per barrel. Ethanol became a much more interesting substitute, leading to more demand for grains. This could have resulted in excess demand, which in turn led to a higher price. The crisis report of the Farm Foundation7 draws a couple of interesting conclusions about the relevance of biofuels. First, the overall conclusion is that demand for biofuels did influence grain prices. The report bases this conclusion on the fact that there is a very strong link between ethanol and corn prices. The fall in oil prices at the end of 2008 resulted in a decline in the demand for the ethanol. This put a downward pressure on the ethanol price, which is highly correlated with the grain price. In the end, the grain price also drops. This scenario can be used for both the price increases at the beginning of 2008 as well as the price falls at the end of 2008. This idea is supported by a study of Kanamura8 and a study by the Iowa State University9. Both conclusions in these papers are that the correlation between the energy price and grain prices increases with the energy price. When inserting biofuels in this model, the correlation increases even more for grains like wheat and soybeans. The Iowa study explores the implications of the tight linkages between energy and grain prices. The lack of competitiveness in the oligopolic oil market could also decrease competitiveness in the grain market. This may be an important stimulus for biofuels. Despite the upward pressure on the grain prices, biofuels could force the oil cartels to become more competitive. In the end, this could lead to a downward pressure on grain prices. Philip C. Abbott, Christopher Hurt and Wallace E. Tyner.: What’s driving food prices (March 2009 update), for the Farm Foundation 8 T. Kanamura Monitoring the Upsurge of Biofuels in Commodity Futures Markets (2008) 9 Dermot J. Hayes, Bruce A. Babcock, Jacinto F. Fabiosa, Simla Tokgoz, Amani Elobeid, Tun-Hsiang Yu, Fengxia Dong, Chad E. Hart, Edward Chavez, Suwen Pan, Miguel Carriquiry, and Jerome Dumortier; Biofuels: Potential Production Capacity, Effects on Grain and Livestock Sectors, and Implications for Food Prices and Consumers(2009) Center for Agricultural and Rural Development Iowa State University 7 9 The paragraph above gives a one-sided view on the influence of biofuels. Luckily, there are also other studies that make a more balanced and wider assessment. The idea that biofuels are a big factor behind the price increases is countered by three scientists from the ZEF. In their study The Impacts of Biofuel Production on Food Prices: a review10 the authors argue that demand for biofuels is mainly policy driven. In other words, governments have the greatest influence over ethanol demand. They conclude that even though demand for biofuels has been a factor behind the price increases, it is probably not the biggest one. The market was already on a path leading to a crisis; higher demand for biofuels just made the crisis more severe. This conclusion can be supported by the following figure: Figure 2 Production and processing of Soybean 250000000 40000000 35000000 30000000 25000000 150000000 20000000 100000000 15000000 10000000 Processed (tonnes) Production (tonnes) 200000000 50000000 5000000 0 19 61 19 63 19 65 19 67 19 69 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 0 years Production of soybean Soybeans processed to oil Figure 2 shows the relationship between the production of soybeans and the demand for biofuels. The two follow the same trend since 1960, yet there’s no clear correlation for both variables. Growth in biofuel production from soybeans has been higher than production growth for soybeans. This is especially true for 2007, when worldwide soybean production experienced negative growth. This points at a significant influence of the biofuel demand on soybean prices. Still, the weight of the 10 Nicolas Gerber, Manfred van Eckert and Thomas Breuer: The Impacts of Biofuel Production on Food Prices: a review, ZEF – Discussion Papers On Development Policy No. 127, Center for Development Research, Bonn, October 2008, pp.19. 10 biofuel demand as a factor can be questioned. The two scales show that the amount of soybeans that is used for the processing to oil is still a minor part of the total soybean production. The same conclusions can be drawn for maize, as can be seen in Figure 3. The connectedness of trends between production and biofuel demand is less strong, but even here the correlation changes significantly over the last five years. The production of maize is generally volatile but a two-year decline in worldwide production occurred only once before 2005. The demand for maize as a biofuel input has a very steady trend, but became more volatile over the last five years. The combination of these two factors could lead to uncertainty in the markets. It is highly unlikely that it will have direct influence on the maize price, as the volume of processed maize is only marginal. Figure 3 Production and processing of Maize 900000000 2500000 800000000 Production (tonnes ) 600000000 1500000 500000000 400000000 1000000 300000000 200000000 Processed (tonnes ) 2000000 700000000 Production of Maize Processed Maize to oil 500000 100000000 0 19 61 19 63 19 65 19 67 19 69 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 0 years We cannot deny the influence of biofuels on grain prices, yet this influence remains very small. The fact that governments have a really big influence on the ethanol demand, and the expectation that they will keep raising the goals for ethanol production in the near future, could increase the influence on the grain price. Still, it is much more likely that the increased demand for biofuels is just a factor that fed panic amongst investors, and that it is not a significant factor on its own. 11 Chapter 4: Grain Stocks The fall of grain stocks between 1998 and 2005 is the major argument supporting the influence of the supply-side in the report of the Farm Foundation7. The fall in stocks was created by over-consumption, in its turn a consequence of lower production. The lower stocks implied that food shortages and under-nutrition were becoming an actual threat in 2008, mainly in grain importing countries. Yet the market reacted quickly. In the report of the Farm Foundation, predictions for future grain stocks are much more positive. This is supported by the higher price, which scares of consumers and therefore removes the over-consumption. A bit outdated, but nevertheless very interesting illustration is the earlier mentioned study of the 1972-1975 commodity boom11. The difference between the boom in the 1970s and the recent boom is that stocks were at a normal level in the 1970s. Yet still prices rose sharply in both cases. The study argues that it is possible to reduce the magnitude of the price increases, but that it won’t be able to completely avoid price increases. Once there is panic amongst investors, even stocks become a victim of the massive speculation. The authors also doubt whether it is economically efficient to hold big reserves. They are primarily concerned about the capital that is required to acquire the commodities, next to the costs that are involved to maintain the reserves as opportunity costs. The importance of grain stocks has become much bigger today, according to a study Bruins and Bu12. This is true for most grain importing countries, especially for China. Population growth has been outpaced by production growth, but the country faces limits in arable area. A year of bad yields could lead to huge excess demand for grains. Cash reserves remain less costly than food reserves, but the danger of food shortages is becoming bigger and bigger. For countries like the United States, it would be possible to withstand bad production with cash, since their domestic production exceeds domestic demand. Yet this would create a very big crisis on the other side of the world. So even though the costs are very high, food reserves are simply needed to withstand global food crises. 11 R. N. Cooper and R.Z. Lawrence The 1972-1975 Commodity Boom(1975), in Brookings Papers on Economic Activity, 3 12 Hendrik J. Bruins and Fengxian Bu: Food Security in China and Contingency Planning: the Significance of Grain Reserves (2006) in Journal of Contingencies and Crisis Management Volume 13, number 3, 2006 12 In contrast to Bruins and Bu, Dawe completely neglects the role of China and stocks as factors that caused the food crisis. In his study The Unimportance of “Low” World Grain Stocks for Recent World Price Increases13 he argues that China’s policy for grain stocks wasn’t relevant for the global food crisis. This study concentrates on the market movements without the role of China, since China is only a small player in the World’s grain markets. Without China, stocks were not at an all-time low level. It is therefore unlikely that low stocks were a major factor behind the price increases. The discussion about stocks is a very hard one, and both sides make a good point. Yet it is far too easy to completely neglect the role of stocks in the last food crisis. The best answer is to be found in the study of the 1972-1975 Commodity Boom. A low stock isn’t an important factor in itself, but it can be a factor that stimulates the speculation amongst investors. This is especially true when a country like China starts to make moves on the world markets. It might not be one of the biggest players on the market, yet with around 18% of the World’s population, the country will always remain a significant factor. Chapter 5: Area harvested and crop yield Stocks of grain started to reduce at the end of the 90s. In the early years of the reduction, the decline in stocks of grains was mostly due to a fall in harvested areas. Yet in the years 2006 and 2007, bad crop yields were the major contributors to the lower production. With the expectation of another year of low yields, this resulted in a speculation bubble in commodity prices. The revised version of the study of the Farm Foundation shows that these higher prices stimulated production and has a negative effect on consumption, so at the end of the year 2008 predictions for stock changes in 2009 were very positive. This is how the markets itself adjusts to a shock. Still, there are limits in expanding production or increasing yield. This is one of the biggest threats in the future for the agricultural business. In an article in for the USDA, S. Malcolm14 studies the effects of an increase in arable land or yields. His main concern is the environmental damage that is caused by an increased yield. The more D. Dawe The Unimportance of “Low” World Grain Stocks for Recent World Price Increases (2009), ESA Working Paper No. 09-01 14 Scott Malcolm, Growing Crops for Biofuels has Spillover Effects(2009) in Amber Waves March 2009 13 13 intensive use of land could lead to more erosion and environmental degradation. Especially the increased use of chemical inputs could destroy the soil in many regions. Indirectly, these chemical fertilizers reduce water quality. An increase in arable land is less likely. More likely is that an increase in production in one grain will mean that the production of another grain has to be sacrificed. This has an important spill-over effect; in the end not only oilseed grains will have higher prices but through less supply all the other grain prices will also be affected. The lack of arable land is illustrated in figure 4 below. Figure 4 90000000 80000000 70000000 60000000 50000000 40000000 30000000 20000000 10000000 0 19 61 19 63 19 65 19 67 19 69 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 Area Harvested Area Harvested top-10 exporters year Argentina Germany Ukraine Australia Kazakhstan United States of America Canada Russian Federation France Thailand Figure 4 shows the total harvested area for cereals for the ten biggest cereal exporting countries. The results suggest a bleak future. Only the United States and the Russian Federation have been able to increase their harvested area significantly in the last years. Despite these efforts, the US is still on the same level as the 1960s. The Russian Federation has experienced a dramatic fall since 1992 and is still far below the level of 1960. All other countries are in the same situation as the US; they haven’t been able to increase their harvested area over a period of 40 years. This reduces the chance of an increase in both short-time and long-time production. The argument of environmental degradation is especially true in Australia, a country that faces huge problems with water management. This is shown by figure 5 below. 14 Figure 5 Yield 80000 Yield (hg/Ha) 70000 60000 50000 40000 30000 20000 10000 Argentina Australia Canada France Germany Ukraine Kazakhstan United States Russian Federation Thailand Crop yield is in general very volatile, because of the dependence on weather. Still, there is a clear trend of an end in yield growth. Only Argentina and the United States have been able to achieve a growth in crop yield since the start of the new millennium. For all other countries, yield levels are the same as eight years ago, or in some cases the yield has diminished. According to a study by V. Thampapillai15 the over-allocation of water for the agricultural business is one of the main reasons for the environmental degradation in the country. This process of environmental degradation is stimulated by climate change. The over-allocation of water has two important consequences for future production increases. First, there is not enough water to supply new arable land. Second, because of the land degradation caused by over-allocation the yield will be difficult to increase. Overall, it will prove to be very hard to increase grain production in Australia. 15 Vinoli Thampapillai, Limits to Government Water Buy-backs for Environmental Flows in the Murray Darling Basin, Australia(2008) 15 07 05 Year 20 03 20 01 20 99 20 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 19 81 19 79 19 77 19 75 19 73 19 71 19 69 19 67 19 65 19 63 19 19 19 61 0 The excess demand is not large enough on its own to create directly such a big upward pressure on grain prices. Indirectly, the reduced supply could have a much bigger effect. With depleted stocks, the expectation of a stop in production growth is a very big threat. The combination of area harvested and yield leads to the conclusion that it is highly unlikely that production growth can keep up with demand. This is because consumption of cereals has a very steady growth and is closely correlated (see correlation in Table 3 below) to world population, as illustrated again in the appendix by Figures A2, A3 and A4. The scatter plot in Figure 6 below supports the idea that there’s a big causality between population and corn consumption. Predictions of population growth are often quite accurate. As long as humanity is spared from big environmental disasters or biological plagues, the world’s population will grow at a steady pace at least for the next 50 years. Especially in combination with the fast growing demand for oilseeds, it will prove to be difficult for producers to keep up with demand. The expectation of a growing excess demand could be one of the biggest factors behind the massive speculation on grain prices. Table 3 Figure 6 World Cereal Consu m ption World Cereal Cons umpti on = -113976142,23 + 0,18 * Wor ldPop R-Squar e = 0,99 1000000000,00 800000000,00 600000000,00 400000000,00 3000000000,00 4000000000,00 5000000000,00 6000000000,00 Wor ld Po p 16 Chapter 6: Agricultural policy The third major factor on the supply-side is the agricultural policy of major grain producing countries. As shown in the Figure 7 below, 98% of global total grain exports are in the hands of only 10 countries. This creates a certain market power for these countries. In such an ‘oligopoly’, controversial agricultural policies could affect the domestic grain prices. China’s exports constraints were so high that they even fell out of the top-10 of cereal exporters. The appendix figure A5 shows that this fall in export wasn’t caused by a fall in production. The same conclusion can be drawn for Argentina, as Figure A6 in the appendix shows. A closer look at Figure 7 shows that the United States accounts for 37% of the total world export. This huge market domination could imply that even smaller policies like the support for biofuels can have an impact on the world price. Figure 7 Top-10 biggest exporters of cereals in the World Argentina Australia Canada France Germany Kazakhstan Russian Fedration Thailand Ukraine United States Rest of World The ‘bad guys’ in the major producing group are China, Ukraine and Argentina. This is the conclusion of a study done by the US International Trade Commission16. Their argument is that the export constraints in these three countries, forces importing countries to get all their grain from the remaining 7 major exporters. This of course creates a huge excess demand, which leads to higher prices. The 16 Kendall Dollive The Impact of Export Restraints on Rising Grain Prices (2008), U.S. International Trade Commission 17 countries with restraints are very successful in keeping their domestic prices at normal level. Nevertheless, this action can create food shortages in many other countries; especially poor and developing countries. The next study17 has a much smaller scope; it only focuses on policy in China. This study is especially interesting because next to the grains with export constraints, there is also a crop without these constraints; soybeans. The first conclusion in this study is that the export constraints for grains have the desired effect. While the soybean price in China follows nearly the same steep path of the world price, the grain prices in China remains at a very low level compared to world prices. Nevertheless, the danger of depleted stocks will have an upward pressure on the prices of grains too, according to this study. It is very likely that a market with such a lack of competitiveness leads to high uncertainty and thereby to speculation. This speculation argument is supported by the fact that China’s export constraints and the US ethanol policies were already present long before the crisis. The fact that they were long-term factors makes it less likely that these policies caused a shock, but increases the credibility that the policies contributed to uncertainty and speculation. The results of the studies just discussed are very satisfying for Chinese policymakers, but could be a great threat to the rest of the world. The great success of the policy could lead to an extension of the Chinese program. Yet far worse; it could also spread to other major grain producing countries. If more of these countries develop programs for export constraints, the world market could experience more and more excess demand. On the first hand, this is not bad for the exporting countries because it will lead to higher exporting prices. Yet in turn, this higher export could lead to food shortages in the exporting countries. In the end, to protect domestic food security, more and more major grain exporters will come up with export constraints. It is in the interest of the whole world that this scenario is avoided. There is a very important role for the World trade Organisation (WTO) in the coming years to prevent a much bigger crisis. 17 Jun Yang, Huanguang Qiu, Jikun Huang, Scott Rozelle: Fighting global food price rises in the developing world: the response of China and its effect on domestic and world markets(2008) Agricultural Economics 39 (2008) supplement 453–464 18 Chapter 7: Climate Change The third possible factor that will be discussed is climate change. The popularity of this issue has been enormous over the last five years, yet environmental scientists still have not reached a clear conclusion on how much the climate is changing and will change in the future. Therefore, we will not discuss global warming itself in this thesis. Yet there is enough evidence to believe that the climate in some regions of the world is changing. This makes this factor worth discussing, also because the climate simply is a big input factor of agriculture. Even the slightest risk of climate change can result in speculation in the grain markets. Also, despite the negative image of climate change and global warming, it is not clear whether or not any changes in the climate will be bad for agricultural profits. So the main question is; what kind of influence has possible climate change on agricultural outputs? It is very difficult to study the effects of climate change for the whole world altogether. The most extensive study at this moment is performed by the US National Bureau of Economic Research; The Economic impacts of climate change: Evidence from agricultural profits and random fluctuations in weather18. The study focuses on the United States, in particular on differences in the effects of climate change the different states. The results are a bit surprising, to say the least. In contrast to the negative image of climate change, this study predicts that long-run annual agricultural profits will increase with 3, 4% ($1.1 billion). The confidence interval for this expectation is very low; so accuracy of the prediction is high, at least with the assumptions of this model. This conclusion counts for the United States as a whole, but amongst the states the differences in predicted profits are high. The states can be divided roughly into two groups; the northern states will profit, while the southern states will experience a decline in annual profits. The most important conclusion in this paper is that climate change will not have significant effects on crop yields for the major grains. The negative point of this paper is that it uses explicit models. Climate change is very difficult to put into such a model. Though very interesting and quite relevant for this thesis, we cannot simply accept the conclusions of this study. An example of the shortcomings of climate models is given by a study of Schenkler and 18 Olivier Deschenes and Michael Greenstone The Economic Impacts of Climate Change: Evidence from Agricultural Profits and Random Fluctuations in Weather (2006), NBER Working Paper No. 10663 August 2004, Revised February 2006 JEL No. Q50, Q12, C23, Q54, Q51 19 Robert19; they find that climate change will have severe effects on crop yields. The fact that they use different assumptions and a broader time view results in a very different conclusion on the exact same topic. The second study that will be discussed is on a much smaller scale. This make the study somewhat less interesting, but predictions can be more accurate. In their study20 in the Mosel vineyard region (Germany), Ashenfelter and Storchman find that climate change here can be very profitable. They assume that climate change will lead to more solar radiation. Since crops need solar radiation to grow, more solar radiation would lead to bigger crops. They conclude that an increase in temperature of 1 degree Celsius would lead to an increase in crop value with more than 30 percent. The crop value would double should the temperature rises by 3 degrees Celsius. These results are in line with results of the study in the United States. The Mosel vineyard valley is comparable with the northern states in the US. Furthermore, the explicit focus on solar radiation is selective. It is likely that other weather parameters will also experience change, such as for example rainfall. Nevertheless, this study shows that climate change is not necessarily bad for agricultural profits. It is very difficult to include climate change in the empirics of this thesis. The fact that environmental scientists are not sure how much and where the climate will change, makes it very difficult for economist to include climate change in their models. The models that are made need unrealistic assumptions and are therefore less reliable. There is much in the literature on this subject, but the studies are difficult to compare and even if we were to insert a dozen more studies in this thesis, we still would not come to a clear consensus on the effect of climate change. The third chapter will however show some empirics for yield and area harvested, but we cannot conclude that changes in yield are directly the result of climate change. Being an important input factor of agriculture, it is essential that the economic community follows developments in the climate closely. Nonetheless, there is still much to be done before climate change can be properly introduced into economic models. 19 Wolfram Schlenker and Michael Roberts, Estimating the impact of climate change on crop yield: The importance of nonlinear temperature effects (2008) NBER working paper series 20 Orley Ashenfelter and Karl Storchmann: Using a Hedonic Model of Solar Radiation to Assess the Economic Effect of Climate Change: The Case of Mosel Valley Vineyards(2006) NBER Working Paper No. 12380 July 2006 JEL No. C2, Q5 20 Chapter 8: The Oil Price Probably the most obvious factor behind the price increases of grains is the oil price. The disturbances in the grain markets took place at nearly the exact same time as the bubble in the oil market, and in both cases the price increases followed nearly the same pattern, as shown in Figure 7 below. Besides the obvious conclusion that the prices follow the same trend over the last five years, there are some more interesting things to be drawn from the figure. The oil price starts to rise first, than the wheat price follows. This points at causality from oil price to wheat. This idea is rejected by the order of price decreases in 2008. In this case, the wheat price starts to fall and the oil price then follows. This is certainly unexpected; it could imply that there is no specific causality at all. In that case, a high correlation isn’t really relevant for the question whether the oil price is a significant factor behind the price increases in grains. With correlation and no causality, it is much more likely that there is one factor that influences the price increases in both markets. So the main question is; to which extent was the increase in oil price a factor behind the increase in grain prices? Figure 8 Oil and Wheat Prices 450 120 400 100 350 300 80 250 60 200 150 40 100 20 50 feb-09 Mar 2008 apr-07 May 2006 jul-04 jun-05 aug-03 sep-02 nov-00 Oct 2001 jan-99 dec-99 feb-98 Mar 1997 apr-96 jun-94 May 1995 jul-93 aug-92 sep-91 Oct 1990 nov-89 dec-88 jan-88 feb-87 apr-85 0 Mar 1986 0 month of year Oil Price Wheat Price 21 Wheat Price (USD per metric ton) 500 May 1984 Oil Price (USD per barrel) 140 The fact that market situations for both commodities are still highly unstable makes it really difficult to draw preliminary conclusions. This is the main reason why there is only limited literature yet on this topic. For that reason, we will have to rely mainly on recent working papers. An important conclusion for this topic is drawn in a study by Kanamura21. There is an increasing correlation between petroleum and major grains such as wheat and soybeans after the start of the oil bubble in 2004; this is a general observation in times with higher energy prices. Yet in this special case, the author believes that this increasing correlation is an effect of the increased popularity of biofuels. This idea is confirmed by a second study22, which draws a conclusion on the exact same linkages. The fact that energy prices influence biofuels prices (and thereby ethanol), combined with the fact that ethanol influences the price of grains, means that energy prices influence indirectly the grain prices. The conclusion in the report by the Farm Foundation is also in line with the other conclusions. Correlation between crude oil price and corn price rose from -0.26 in 1988-2005 to 0.8 in 2006-2008.23 We have done the same analysis for the oil price and the wheat price, and the conclusions are approximately the same; Table 4 MonthlyoilP MonthlyoilP Monthlywh eatP 1 0,754(**) Pearson Correlation Sig. (2-tailed) N MonthlywheatP Pearson Correlation Sig. (2-tailed) N 0,000 300 300 0,754(**) 1 0,000 300 300 ** Correlation is significant at the 0.01 level (2-tailed). 21 T. Kanamura Monitoring the Upsurge of Biofuels in Commodity Futures Markets (2008) Dermot J. Hayes, Bruce A. Babcock, Jacinto F. Fabiosa, Simla Tokgoz, Amani Elobeid, Tun-Hsiang Yu, Fengxia Dong, Chad E. Hart, Edward Chavez, Suwen Pan, Miguel Carriquiry, and Jerome Dumortier; Biofuels: Potential Production Capacity, Effects on Grain and Livestock Sectors, and Implications for Food Prices and Consumers(2009) Center for Agricultural and Rural Development Iowa State University 23 Philip C. Abbott, Christopher Hurt and Wallace E. Tyner.: What’s driving food prices (March 2009 update), for the Farm Foundation 22 22 Table 5 MonthlyoilP0409 MonthlyoilP040 9 Monthlywhe atP0409 1 0,808(**) Pearson Correlation Sig. (2-tailed) 0,000 N MonthlywheatP0409 Pearson Correlation 61 61 0,808(**) 1 Sig. (2-tailed) 0,000 N 61 61 ** Correlation is significant at the 0.01 level (2-tailed). Simply relying on correlation is much too easy in this case. As mentioned earlier, there is no clear evidence for causality. Yet this is the main thing we’re looking for. Panic amongst investors could be the cause for the price increases of both commodities. This is called a lurking variable. Unfortunately, this panic is really hard to put into an economic model because its nearly impossible to quantify. We will have to rely on a basic scatter plot for the wheat price and the oil price. Figure 9 Line ar Reg re ssio n wi th 95,00% Me an Pre dicti on In te rv al Month ly_wh eat_Price 400,00 100,00 300,00 200,00 25,00 50,00 75,00 100,00 125,00 Mon th ly_o il_Pr ice Monthly_wheat_Price = 103,82 + 1,85 * Monthly_oil_Price R-Square = 0,57 The scatter plot shows that there’s not a very high causality for the oil price on the wheat price. It is difficult to find a clear pattern in the figure, and therefore the rsquare value is low. This confirms the idea that despite the correlation, there is no real causality. We’ve run the same analysis for the situation in the last five years. Figure A8 in the appendix shows that the causality has increased a bit, but it is still too weak to be of any relevance. 23 The main conclusion in the literature study on oil is that there was a very high positive correlation between the crude oil price and the prices in the grain markets during the crisis. Before the crisis, the correlation was significantly less strong and in some periods even negative. Not surprisingly, figure 7 corresponded with the conclusion in the literature study. Still, the fact that both prices are correlated isn’t enough in this case. Since oil is a commodity itself, both price increases could be a part of a much bigger commodity boom. This idea is supported by the missing causality. On first hand, there is no clear evidence of a direct influence of oil on grains. A suitable explanation could again be panic amongst investors, leading to a run on commodities. Chapter 9: Speculation The factor speculation has already been mentioned a couple of times in this thesis, but we will now have a more detailed look at this phenomenon. This factor can be used to explain the part of the price disturbances that weren’t caused by fundamental market factors. Speculation itself can be caused by a broad range of factors; some of these factors have already been discussed. The most obvious factor that could have caused speculation is the herding behavior of investors. At the start of the commodity bubble, the financial bubble was about to blow. In order to find a safe heaven for their money, investors could have exchanged their stocks for commodity futures. It is really difficult to find solid evidence for speculation, since it is mostly a psychological phenomenon. The best evidence at this time is to try and find a causal link between the increased future trading and the higher grain price. This paragraph will investigate whether this was the case and, if so, the weight of the impact of speculation on the grain prices. It takes a lot of time for a thorough analysis of these recent market movements, so the literature study in this part consists of working papers and articles. First of all, it is important to look at the general features of the future markets. Speculation is not determined by market forces, so it could influence many different commodities at the same time. The first study that will be discussed 24 analyses the situation before the crisis. Kim and Doucouliagos24 conclude that the prices for three grain futures (corn, soybean and wheat) are correlated. Also, there are interaction effects between the futures that are found in the different volatilities. This conclusion tells us that it is common for the prices of grain futures to move in the same direction. Therefore, we must be cautious to draw conclusions on speculation that are supported by theories on future markets. The study of Kim and Doucouliagos is a bit outdated, since the most recent data used is from 2004. It is possible that the market situations change over time. Evidence for these changes is given by a study by Bhar and Hamori25. The strongest point of this study is that it compares correlations in two different periods. The conclusion in this paper is that correlation amongst commodity futures increases over time. This suggests that the correlation at the time of the crisis (five years later) was very significant. This reduces the relevance of correlation to explain speculation amongst futures during crisis times even further. The most recent study to the crisis itself comes up with an unexpected conclusion. In their article26, Robles Torero and von Braun present a lot of figures that lead to the conclusion that future trading in commodities increased significantly over the last two years. Both volume as well as prices for grain futures increased until the summer of 2008. Though the data is really clear; the authors question whether there is a significant causality between the increased future trading and the higher grain prices. Surprisingly, they find that there is no direct causality for all individual grains but they suspect that the bubble in the futures market creates uncertainty in the real market for grains. All three conclusions of the discussed studies suggest that speculation can’t be revealed by analysis of the future market for grains. This opinion is shared by Gilbert27, who is still convinced that the crisis was caused by market fundamentals. We will not react on the last conclusion in this paragraph, but the theory he describes on futures is nevertheless interesting. He mainly blames the commodity investors for the crisis, not the speculators. Commodity futures were interesting in general, so the grain futures lifted on the popularity of energy futures 24 Jae H. Kim and Hristos Doucouliagos, Realized Volatility and Correlation in Grain Futures Markets:Testing for Spill-Over Effects (2005) SSRN working papers 25 Ramaprasad Bhar and Shigeyuki Hamori, Linkages among agricultural commodity futures prices: some further evidence from Tokyo(2006) Applied Economics Letters, 2006, 13, 535–539 26 M. Robles, M. Torero and J. von Braun, When Speculation Matters (2009) in IFPRI Issue Brief 57 February 2009 27 Christopher L. Gilbert, How to Understand High Food Prices (2008) Università degli Studi di Trento Discussion paper no 23 25 trough index funds. Yet this is still not a really relevant factor, because it remains very hard to find a link between actual crop prices and future prices. The literature study for speculation hasn’t been that successful; it is very difficult to find hard evidence for speculation in the future markets. First of all, grain futures tend to be correlated in both price and volatility. This makes it hard to blame index fund investors for the general rise in grain futures. The second problem in finding evidence is that there is no clear direct link between the prices of grain futures and the actual crop prices. It is suspected that a high volatility in the grain future markets can stimulate uncertainty in the real markets, yet this is difficult to prove. Overall we can conclude that it will not be relevant to analyze the data for the future markets. Speculation remains a psychological phenomenon that is hard to prove through statistical research. This is very unfortunate, because there is enough literature that suspects a significant influence of speculation on grain prices. Finding hard evidence for this link between speculation and grain prices remains to be done in other studies, and could prove to be very useful in explaining bubbles in both real and financial markets. Chapter 10: Conclusion This study tried to find the cause behind the disturbances in the grain markets. In the second chapter we concluded that this crisis was special, supported by the fact that it contrasts with the general trend of reduced volatility in the commodity markets. Despite this specialty, most of the factors that caused earlier crises are still significant today. We first discussed the demand factors. Demand for biofuels was too small to be of much influence on the grain prices. The decline of grain stocks were very unsatisfying for the future, but had no direct influence on grain prices. After having discussed the demand factors, we continued with supply factors. The decline of harvested area and the lack of growth for yield combined did not cause the price increases either; changes in these numbers were too small. The second supply factor is the agricultural policy of major grain producers. Countries like China, Argentina and Ukraine introduced export restraints for major grains. Though very 26 successful in keeping domestic prices at a normal level, this further increased excess demand on the world markets. Agricultural policies were a significant factor behind the grain price increases. This is not the case for the climate change factor. As long as environmental scientists are not sure how much and where the climate will change, it very difficult to put climate change into a model. Models have to rely on a range of unrealistic assumptions, leading to very different conclusions amongst the various studies. Most of the fundamental factors were not directly significant. However, it is very well possible that these factors could have fed panic amongst investors, leading to speculation. The problem with panic and speculation is that it is really difficult to put into a model. To add to this, the solid evidence for speculation cannot be found in the future markets. This is very unfortunate, because the data on futures would have been able to fit into a model. Overall, we suspect that the disturbances in the grain markets were part of a commodity boom. Panic amongst investors that led to speculation is one of the factors that can explain the events in the grain markets. We have not found any solid empirical evidence for speculation in this paper. This is a task for future research. Also, it would be useful to investigate how to reduce the risk of comparable price increases in the future. Chapter five showed that there’s little scope for a big production increase in the future. With a future excess demand for grains prospect, investors are likely to panic again. 27 Literature List - Philip C. Abbott, Christopher Hurt and Wallace E. Tyner.: What’s driving food prices (March 2009 update), for the Farm Foundation - Orley Ashenfelter and Karl Storchmann: Using a Hedonic Model of Solar Radiation to Assess the Economic Effect of Climate Change: The Case of Mosel Valley Vineyards(2006) NBER Working Paper No. 12380 July 2006 JEL No. C2, Q5 - Ramaprasad Bhar and Shigeyuki Hamori, Linkages among agricultural commodity futures prices: some further evidence from Tokyo(2006) Applied Economics Letters, 2006, 13, 535–539 - Loek Boonekamp The Grain of truth(2008) in OECD Observer No 267 May-June 2008 - Hendrik J. Bruins and Fengxian Bu: Food Security in China and Contingency Planning: the Significance of Grain Reserves (2006) in Journal of Contingencies and Crisis Management Volume 13, number 3, 2006 - R. N. Cooper and R.Z. Lawrence The 1972-1975 Commodity Boom(1975), in Brookings Papers on Economic Activity, 3 - D. Dawe The Unimportance of “Low” World Grain Stocks for Recent World Price Increases (2009), ESA Working Paper No. 09-01 - Olivier Deschenes and Michael Greenstone The Economic Impacts of Climate Change: Evidence from Agricultural Profits and Random Fluctuations in Weather (2006), NBER Working Paper No. 10663 August 2004, Revised February 2006 JEL No. Q50, Q12, C23, Q54, Q51 - Kendall Dollive The Impact of Export Restraints on Rising Grain Prices (2008), U.S. International Trade Commission - Nicolas Gerber, Manfred van Eckert and Thomas Breuer: The Impacts of Biofuel Production on Food Prices: a review, ZEF – Discussion Papers On Development Policy No. 127, Center for Development Research, Bonn, October 2008, pp.19. - Christopher L. Gilbert, How to Understand High Food Prices (2008) Università degli Studi di Trento Discussion paper no 23 28 - Dermot J. Hayes, Bruce A. Babcock, Jacinto F. Fabiosa, Simla Tokgoz, Amani Elobeid, Tun-Hsiang Yu, Fengxia Dong, Chad E. Hart, Edward Chavez, Suwen Pan, Miguel Carriquiry, and Jerome Dumortier; Biofuels: Potential Production Capacity, Effects on Grain and Livestock Sectors, and Implications for Food Prices and Consumers(2009), Center for Agricultural and Rural Development Iowa State University - Bart Hobijn, Commodity Price Movements and PCE Inflation (2008) Volume 14, Number 8 November 2008 Federal reserve Bank of New York - David S. Jacks, Kevin H O'Rourke, and Jeffrey G. Williamson: Commodity Price Volatility and World Market Integration since 1700 NBER Working Paper No. 14748 February 2009 JEL No. F14,N7,O19 - T. Kanamura Monitoring the Upsurge of Biofuels in Commodity Futures Markets (2008) - Jae H. Kim and Hristos Doucouliagos, Realized Volatility and Correlation in Grain Futures Markets: Testing for Spill-Over Effects (2005) SSRN working papers - Robert G. Lewis What Food Crisis? Global Hunger and Farmers’ Woes(2008) in World policy Journal Spring 2008 p 29-35 - J. Light and T. Shevlin: The 1996 Grain price shock: how did it affect food inflation? (1998) in Monthly Labor review (august 1998) - Scott Malcolm, Growing Crops for Biofuels has Spillover Effects(2009) in Amber Waves March 2009 - M. Robles, M. Torero and J. von Braun, When Speculation Matters (2009) in IFPRI Issue Brief 57 February 2009 - Wolfram Schlenker and Michael Roberts, Estimating the impact of climate change on crop yield: The importance of nonlinear temperature effects (2008) NBER working paper series - Vinoli Thampapillai, Limits to Government Water Buy-backs for Environmental Flows in the Murray Darling Basin, Australia(2008) - Jun Yang, Huanguang Qiu, Jikun Huang, Scott Rozelle: Fighting global food price rises in the developing world: the response of China and its effect on domestic and world markets(2008) Agricultural Economics 39 (2008) supplement 453–464 29 Appendix Figure A1 Commodity Prices 2008 and start of 2009 Price (US$) monthly average 14 12 10 8 6 4 2 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar month Soybean Price 08-09 Wheat Price 08-09 Corn Price 08-09 Figure A2 World population and cereal Consumption 7000000000 1000000000 900000000 6000000000 700000000 600000000 4000000000 500000000 3000000000 400000000 300000000 2000000000 200000000 1000000000 100000000 0 0 YR 1 YR 9 61 1 YR 9 63 1 YR 9 65 1 YR 9 67 1 YR 9 69 1 YR 9 71 1 YR 9 73 1 YR 9 75 1 YR 9 77 1 YR 9 79 1 YR 9 81 1 YR 9 83 1 YR 9 85 1 YR 9 87 1 YR 9 89 1 YR 9 91 1 YR 9 93 1 YR 9 95 1 YR 9 97 1 YR 9 99 2 YR 0 01 20 03 Population 5000000000 Cereal Consumption 800000000 year World Population Cereal Consumption 30 Figure A3 7000000000 140000000 6000000000 120000000 5000000000 100000000 4000000000 80000000 3000000000 60000000 2000000000 40000000 1000000000 20000000 0 Consumption (tonnes)(tonnes) Population World Population and Maize Consumption 2003 1999 2001 1995 1997 1991 1993 1989 1985 1987 1981 1983 1977 1979 1973 1975 1971 1967 1969 1963 1965 1961 0 years World Population Consumption Figure A4 14000000 6000000000 12000000 5000000000 10000000 4000000000 8000000 3000000000 6000000 2000000000 4000000 1000000000 2000000 0 Consumption (tonnes)(tonnes) 7000000000 0 19 61 19 63 19 65 19 67 19 69 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 Population World Population and Soybean Consumption years World population Soybeans consumption 31 Figure A5 Export restriction China 500000000 1200000 450000000 Production (tonnes) 350000000 800000 300000000 250000000 600000 200000000 400000 150000000 100000000 Export (tonnes) 1000000 400000000 200000 50000000 0 19 61 19 64 19 67 19 70 19 73 19 76 19 79 19 82 19 85 19 88 19 91 19 94 19 97 20 00 20 03 20 06 0 year Production China Export China Figure A6 Export restriction Argentina 45000000 6000000 40000000 5000000 4000000 25000000 3000000 20000000 15000000 2000000 10000000 1000000 5000000 2005 2003 2001 1999 1997 1995 1993 1991 1989 1987 1985 1983 1981 1979 1977 1975 1973 1971 1969 1967 1965 0 1963 0 year Production Argentina Export Argentina 32 Export (tonnes) 30000000 1961 Production (tonnes) 35000000 Figure A7 Month ly_wh eat_Pri ce_2004_20 09 400,00 300,00 200,00 40,00 60,00 80,00 100,00 120,00 M on th ly_o il_Pr ice _2004_2009 Monthly_w heat _Pr ice_2004_2009 = 47,13 + 2,65 * Monthly_oil_Pr ice_2004_2009 R-Square = 0,65 Table A1 US Soybean price (yearly average) US Soybean price (yearly average) Pearson Correlation 1 Sig. (2-tailed) Pearson Correlation 0,924(**) 0,000 49 49 0,893(**) 1 0,944(**) Sig. (2-tailed) Pearson Correlation 0,893(**) 0,000 0,000 N US Corn price (yearly average) US Corn price (yearly average) 49 N US Wheat price (yearly average) US Wheat price (yearly average) 0,000 49 49 49 0,924(**) 0,944(**) 1 0,000 0,000 49 49 Sig. (2-tailed) N 49 ** Correlation is significant at the 0.01 level (2-tailed). 33 Table A2 Correlations Monthly_oil_Price Monthly_oil_Pri ce 1 Pearson Correlation Monthly_wheat _Price 0,754(**) Sig. (2-tailed) 0,000 N Monthly_wheat_Price Pearson Correlation Sig. (2-tailed) 300 300 0,754(**) 1 0,000 N 300 300 ** Correlation is significant at the 0.01 level (2-tailed). Table A3 Correlations Monthly_oil_Price_ 2004_2009 Pearson Correlation Monthly_oil_Pri ce_2004_2009 1 Sig. (2-tailed) 0,000 N Monthly_wheat_Pri ce_2004_2009 Monthly_wheat _Price_2004_2 009 0,808(**) Pearson Correlation Sig. (2-tailed) 61 61 0,808(**) 1 0,000 N 61 61 ** Correlation is significant at the 0.01 level (2-tailed). Table A4 Correlations Soybean_Price_1971_197 5 Pearson Correlation Pearson Correlation Sig. (2-tailed) N Corn_Price_1971_1975 Wheat_Price_1 971_1975 Corn_Price_19 71_1975 1 0,902(*) 0,780 0,036 0,120 Sig. (2-tailed) N Wheat_Price_1971_1975 Soybean_Price _1971_1975 5 5 5 0,902(*) 1 0,969(**) 0,036 0,007 5 5 5 Pearson Correlation 0,780 0,969(**) 1 Sig. (2-tailed) 0,120 0,007 5 5 N 5 * Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). 34