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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
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2
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1998
1996
1994
1992
1990
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year
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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
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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
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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
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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
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Australia
Canada
France
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Ukraine
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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
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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
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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
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Planning: the Significance of Grain Reserves (2006) in Journal of Contingencies and
Crisis Management Volume 13, number 3, 2006
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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
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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
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Number 8 November 2008 Federal reserve Bank of New York
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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