Transcript How to Understand High Food Prices

How to Understand High Food Prices
Christopher L. Gilbert
University of Trento, Italy, and
Birkbeck, University of London, UK
[email protected] and [email protected]
ICABR Conference, 18 June 2009, Ravello, Italy
The story so far …
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Maize
Rice
Sugar
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Palm Oil
Soybeans
Wheat
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Major grain and oil
seed prices rose
sharply in 2007
through to mid-2008.
Palm oil led, followed
by wheat; maize
(corn) lagged. Sugar
remained flat.
Prices fell back, although not to their original levels, in the second
half of 2008, rice less so than other grains. Prices have staged a
recovery in 2009, although not on a dramatic scale.
The wider story
500
Food
Beverages
Agricultural Raw Materials
Metals
Oil
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(2000 = 100)
Movements in agricultural
prices were less dramatic
than those in either metals
or energy, both of which
also rose earlier than ags.
Agricultural raw materials
(natural rubber excepted)
did not participate in the
boom
IMF commodity price indices
Structure of this talk
1.
2.
3.
4.
5.
6.
What type of factors can explain major movements in
agricultural commodity prices?
Time series analysis: What are the lessons from
history?
The possible role of futures markets
What explained the 2006-08 price spike?
Was diversion of food crops into biofuels the (or a)
main culprit? If not, what was the cause?
[Why are prices rising again?]
1. Explaining common price movements
Demand and supply
• Movements in prices in 2006-08 were common to a large
number of agricultural commodities.
• Ag economists generally see demand as stable with price
rises resulting from supply shocks. Although there were some
supply problems in 2006 and 2007, harvests were generally
good in 2008.
• Stock levels for many major ags had become low, but this was
not new in 2007 and 2008. Low stocks can explain why a
shock has a large impact (positive or negative) but cannot
explain the origin of the shock.
• Because standard explanations of price change are
unavailable, economists have tended to seize on biofuel
demand to explain the 2006-08 price changes.
Biofuels (after Don Mitchell, 2008)
• Biofuels demand was responsible for the largest part of the rise in
food prices but resists the temptation to quantify this share. Abbot et
al (2008) concurred with this view.
• Maize is the main feedstock crop in the US, oilseeds hold that
position in Europe, Brazil uses sugar cane. Thailand uses cassava
while palm oil has been most important elsewhere in south Asia.
• The global use of maize for feed rose by 1.5% over the four years
2004-07 while its use as a biofuel feedstock grew by 65% over the
same period. 70% of the increase in maize production over this
period has gone into biofuels.
• The expansion in maize production was largely at the expense of
soybeans – the 23% increase in the US area devoted to maize in
2007 was associated with a 16% decline in soybean area.
• The eight largest wheat exporting countries expanded the area
devoted to rapeseed and sunflower by 36% over the period 2001-07
while wheat area in the same countries fell by 1%.
1973-74
• Many commentators have noted the parallels with between
the 1973-74 and 2006-08 commodity price booms.
• The1973-74 boom in ag prices in 1973-74 occurred against
the backdrop of a general rise in commodity prices.
• Both this and the 2006-08 boom took place in the context of
enormous world liquidity resulting in part from large US trade
deficits and loose monetary policies.
• In both cases, oil prices jumped sharply upwards.
• Both booms ended sharply with the onset of recession, in the
second quarter of 1974 and third quarter of 2008
respectively.
• Metals prices rose strongly in both booms.
• Coffee and cocoa were sidelined in both cases.
• Ags led other commodities in 1973-74 but lagged in 2006-08.
Cooper and Lawrence (1975)
• Movements in prices in 2006-08 were common to a large
number of agricultural commodities.
• Cooper and Lawrence (1975), who discussed the causes of
the 1973-74 boom, emphasized that the markets were
inter-related at that the boom required a “general
explanation” over and above “intriguing and sometimes
significant” stories relating to particular markets.
• Common price movements need to be explained by
common factors.
• Is biofuels demand an “intriguing” and perhaps “significant
story relating to particular markets” or can it explain the
general rise in prices?
Finance 101 – the CAPM
• A simple CAPM-like model views the change in the jth food commodity
price as
r   ln p     x  
j
j
j
j
j
Regression of the price change on the shock x gives an R2 of
2 2

j x
2
rj  2 2
 j  x  2j
• If we aggregate across n such goods we get
1 n
 ln P   rj     x  
n j 1
• If the shocks j are completely idiosyncratic, they become unimportant
in an aggregate index. Regression of the aggregate price change on
the common shock x gives an R2 of
2 2


R 2  2 2 x1 2
 x  n 
• Common price movements need to be explained by common factors
2. Time series analysis 1971-2008
Sir Clive Granger
(1934 – 2009)
2003 Nobel laureate
Possible common factors
1.
2.
3.
4.
5.
GDP growth?
Monetary expansion?
Exchange rate changes?
The oil price?
Futures market factors?
I use Granger (non-)causality analysis to investigate, in
a deliberately a-theoretical manner, which of these
factors played a significant role over the period 19712008 (152 quarterly observations).
Granger Causality Tests
IMF agricultural foods price index lnPF
1971q11989q4
F(2,71)
1990q12008q4
F(2,71)
1971q12008q4
F(2,147)
Chow
F(5,142)
GDP Y
3.45
[0.7%]
2.71
[7.3%]
6.14
[0.3%]
0.56
[73.0%]
Dollar exchange
rate X
3.13
[4.9%]
1.38
[25.9%]
4.25
[1.6%]
0.76
[57.8%]
Oil price O
2.87
[6.4%]
7.03
[0.1%]
0.02
[98.1%]
3.71
[0.3%]
Money supply M
6.51
[0.3%]
1.05
[35.7%]
6.22
[0.3%]
1.56
[17.5%]
Futures velocity F
0.77
[46.8%]
1.40
[25.3%]
1.75
[17.8%]
0.48
[79.2%]
1971-1989:
GDP growth, monetary expansion and the dollar
exchange rate predominate.
1990-2008:
The oil price is seen as predominant.
Summary
• Cooper and Lawrence (1975) argued for the importance of
monetary factors in 1973-74: commodities were seen as a
safe real asset in a period of unreliable monetary values.
• Futures markets do not emerge as important from the
Granger causality analysis but this may be because I lack a
good measure of their potential impact over the long period.
• Dollar depreciation has a consistent impact over time – but
the the less than unit elasticity implies a relatively low impact.
• Oil price rises resulted in deflationary measures by
governments and central banks in the ’70s and ’80s and so
impacted ag prices negatively. The impact has become
positive in the current decade.
• GDP growth is seen as less important now than historically. It
is unclear whether this is indeed the case or whether world
rapid growth in middle income countries has rendered GDP
measures less accurate than previously.
3. Futures markets
Price formation
• There are active futures markets for many of the most important
agricultural commodities – wheat, maize, soybeans, where prices
rose sharply over 2006-08, and also cocoa, coffee, cotton and
sugar, where there was no boom.
• Active trading allows markets to efficiently incorporate
information about supply and demand fundamentals. If nonfundamentally based trading takes place, futures markets can act
as a distorting lens.
• If prices become too high won’t Warren Buffett sell? If there are
too few experts relative to the amateurs, and if the experts have
short time horizons (for example, because of quarterly reporting),
they will tend to follow the amateurs hoping to get out in time (De
Long et al, 1991).
• Many commentators (Desai, Masters, Phillips, Soros) have
suggested that commodity futures prices were a type of bubble
over 2006-08.
Index investment in futures markets
•
•
•
a)
b)
c)
•
This is a relatively new phenomenon.
Investors have identified commodities as an “asset
class” . They see portfolio diversification advantages in
adding a proportion of commodity futures to equity and
bond portfolios – Gorton and Rouwenhorst (2006).
These position differ from traditional speculative
positions in several respects:
They are almost invariably long.
They are typically rolled forward and turn over slowly.
They track specific indices (e.g. DJ-GSCI) rather than
taking positions on specific markets.
They can be large in relation to the overall market.
Index Fund Values and Shares
U.S. Agricultural Markets
31 Dec 2007
30 June 2008
$bn
Share
$bn
Share
Corn
7.6
25.8%
13.1
27.4%
Soybeans
8.7
26.1%
10.9
20.8%
Soybean oil
2.1
24.8%
2.6
21.7%
Wheat
9.3
38.2%
9.7
41.9%
Cocoa
0.4
11.3%
0.8
14.1%
Coffee
2.2
26.0%
3.1
25.6%
Cotton
2.6
33.0%
2.9
21.5%
Sugar
3.2
29.0%
4.9
31.1%
Feeder cattle
0.4
23.2%
0.6
30.7%
Live cattle
4.5
48.4%
6.5
41.8%
Lean hogs
2.1
43.6%
3.2
40.6%
Total
43.1
26.9%
58.3
27.1%
Since 2006, the CFTC
has published figures
on the offsetting
futures positions taken
by index providers.
These can account for
up to 40% of all
outstanding positions
on these markets.
Elena Corazzella and
I have constructed an
index of these
positions, IF, which we
use in the subsequent
analysis.
Index positions and ag prices move
broadly together
220
0.16
Index futures position
index
Food price index
0.14
200
0.12
180
0.10
160
0.08
140
0.06
120
r = 0.81
100
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4. 2006-08
Variables analyzed
• I have 36 monthly observations from 2006/1 to 2008/12.
This forces a parsimonious analysis.
• I start by using a standard ADL model to exclude
variables from the analysis.
• Candidate variables are
IP
Industrialized production of industrialized countries
M
World money supply (nominal USD)
B
Chinese trade balanced (nominal USD)
X
Index of value of US dollar
O
Oil price (WTI, nominal)
IF
Net positions of index providers on US ag markets
Narrowing down the list of suspects
• After simplifying the lag distributions I obtain
 ln Iaft =
+
0.000
 0.005
+
0.312
 0.153
 ln Iaf t 1 +
0.072
 0.122 
 ln IPt-2 
0.478
 0.256 
 ln M t-1
1.040
1.060
0.134
1.695
Bt-1 
 ln X t +
 ln Ot-2 
IFt 1
1.057 
 0.332 
 0.072 
 0.561
Sample: April 2006 - December 2008 R 2  0.722 s.e.  2.82% DW  1.88
• The dollar exchange rate X, the oil price O and the
futures index position index IF emerge as statistically
significant. I carry these variables forward to the next
stage of the analysis.
Cointegration
•
•
1.
2.
•
Is there an equilibrium relationship between these three variables
and the IMF’s agricultural food price index in the Engle-Granger
sense that the food price index reverts back to the level implied
for equilibrium.
I investigate this question in two ways:
I use OLS to estimate the long run equation, as the initial stage of
the Engle-Granger two stage procedure.
I use the Johansen procedure to test for the cointegrating rank in
a VAR(2) model linking the levels of the four variables.
In both cases, I establish the presence of a single cointegrating
relationship. However, the unrestricted Engle-Granger procedure
gives an exchange rate elasticity in excess of unity. Imposition of
a unit elasticity is acceptable.
Analysis of Peak Food Price Change
Johansen
Engle-Granger
29 month
change
restricted
unrestricted
restricted
Dollar depreciation
lnX
16.8%
16.8%
34.9%
16.4%
Oil price
lnO
71.6%
5.3%
7.8%
14.0%
Futures index positions
IF
0.0364
14.1%
5.0%
18.1%
36.1%
41.6%
40.3%
-
21.1%
15.6%
16.9%
57.2%
57.2%
57.2%
57.2%
Total
Residual
Agricultural food prices
lnIAF
•
The oil price impact is lower than the 17% estimated by Baffes
(2007) and the 15%-20% estimated by Mitchell (2008).
•
The unrestricted exchange rate elasticities are too high from a
theoretical standpoint.
•
All three estimates imply some inflation of food prices from futures
market activity. This explanation competes with the exchange rate.
5. Biofuels
Getting behind the numbers
•
•
1.
2.
3.
•
The preceding analysis identified dollar depreciation, the
rising oil price and futures activity as the proximate causes
of the 2006-08 price rises. Where does this leave biofuels
demand?
There are three possible channels:
The higher the oil price, the more attractive becomes
biofuels production. Anticipating this, the market bids up the
prices of grains and oil seeds in relation to rises in the price
of oil.
Index futures positions may be speculations on future
biofuels demand.
Biofuels may be in the residual (unexplained) component of
the food price change (but how can we know?)
To the extent that food prices were driven by exchange rate
changes, there is no room for a biofuels explanation.
Reasons for scepticism
• Index investments are made for reasons of portfolio
diversification (on a generous view) or to speculate in
commodities in general (less generously). Ags account for a
small proportion of the standard indices. Awareness of biofuel
demand is unlikely to have been a major driver of these
investments.
• The estimated elasticities of food prices with respect to the oil
price are in line with those projected on the basis of cost
pass-through.
• Maize is the major US biofuel feedstock. Wheat is not used as
a biofuel so is only affected indirectly. One would expect a
smaller impact on wheat than on maize. In fact, wheat prices
rose more and earlier than maize prices.
• I suspect that biofuels demand is indeed an “intriguing” and
perhaps “significant story relating to particular markets”.
• More concretely, I think it too early for this audience to
concede that biofuels demand has pushed up food prices.
Thank you for your attention