EU Biofuel policy impact
on price fluctuations
David Laborde
July 2014
Biofuels and Price stability: Overview



A demand effect:

Short term: “Surprise effect”  role on inventories. Should disappear

Long term: effect Link to energy markets on the demand side ( more or less
price stability?)

Current effect: the role of mandatory policies (G20). Agricultural demand
becomes more inelastic
Supply response:

Shift in supply structure (commodities x countries)

Feedback via energy markets (diversification)

Investments and R&D: Specialized vs generics

Risk linked to increase crop specialization (lack of rotation)
But keep in mind that prices, and price transmissions are not
fully transmitted (eg. Corn in Africa vs Corn in the US;
heterogenous wheat markets)
Page 2
The Worst: the role of Mandatory
Policies



An additional “Inelastic” demand (fixed amount of biofuels, not
sensitive to prices)
in a system already inelastic:

Food demand is inelastic: people need to eat

Agricultural supply is inelastic in the short term

It takes time to grow crops (intertemporal issue)

Factors are scarce (water, land)

And in the medium term (R&D)
When a (climatic) shock happens:

Prices will over-react

Other components of demand (mainly Feed) are forced to adapt.
Page 3
The Past: Impact on inventories
Structure of the new demand from 2001 to
2011
Biofuels demand




Quick increase (partially
driven by policies) of
biofuels during the last 6
years
Large share in Marginal
Demand of Crops
Accelerates Depletion of
inventories (or)
Reduces the rate of
accumulation
Food/Feed component
Palm oil
Soybean oil
Corn
Rapeseed
Wheat
0%
50%
Page 4
100%
(not) Dealing with stocks
 No
room for a rationale expectation multi country CGE
 Reduced
form equation?
 Are
biofuels / Biofuels policies shifting storage
behavior?
 Average
 More
stocks as a proportion of production
flexible policy: may lead to a decrease in the ratio
between Average stocks and production
Illustration of structural changes
Evolution of the
EU biodiesel
production
Page 7
External trade EU 27 Imports and Exports- Rape
seeds – Tons
Surge of rape seeds
imports!
Evolution of the
EU biodiesel
production
External trade EU 27 - Imports Protein Meals – Tons
Limited effects on meal imports
Page 8
Introducing a stochastic component in the
MIRAGE model



Caveats:

No storage behavior

No expectations

No risk aversion… or not explicitly
Introducing yield shocks. Different cases

Normalized and homogenous

“Historic scenario”

Monte Carlo approach based on

Realistic matrix based on “cleaned” FAO time series

Multivariate normal distribution crops x countries
Land allocation taken based on the average yield (without shock)
Page 9
Coefficient of variations - yields
Row Labels
Brazil
CAMCarib
China
CIS
EU27
IndoMalay
LAC
RoOECD
RoW
SSA
USA
PalmFruit
Rapeseed Rice Sugar_cb Soybeans Sunflower Maize Wheat VegFruits
7.6%
19.7% 17.7%
2.2%
8.5%
19.6% 16.7% 22.7%
4.6%
8.6%
6.1%
11.8%
12.4%
6.6% 20.4%
7.8%
4.0%
9.1% 6.9%
12.5%
14.7%
13.8% 11.9% 7.0%
9.0%
13.7% 10.7%
13.7%
9.9%
11.5% 12.0% 10.5%
6.6%
7.3% 4.5%
9.7%
25.6%
10.7% 10.6% 7.7%
4.0%
5.7%
6.0%
8.7%
2.6%
16.9%
7.4%
6.3%
18.5% 6.0%
2.3%
17.8%
18.0% 12.3% 9.8%
3.0%
4.8%
11.2% 5.3%
10.0%
16.0%
17.7% 9.1% 17.1%
2.8%
12.8%
13.5% 3.2%
3.8%
11.9%
12.0% 8.4% 2.8%
2.7%
2.2%
34.1% 6.0%
6.2%
19.9%
17.0% 7.5% 8.8%
2.9%
9.7% 5.3%
5.8%
7.8%
11.5% 9.1% 8.2%
4.5%
And country x crop correlation matrices!
But complex estimations
Page 10
Scenarios

Focus on the EU policy

Mandate -> very limited flexibilities (compared to RINs)

Both ethanol and biodiesel

Baseline: 2020 with biofuels incorporation remains at 2008 level in the EU
(full policies implemented in ROW)

Scenarios


EU NREAP by 2020 without trade liberalization

EU NREAP by 2020 with trade liberalization
Yield shock
Structural changes
Land use changes for main crops, 1000
Ha
Page 13
Location of cropland extension. Changes
compared to the baseline. Km2
Page 14
Price changes (EU Biofuel scenario)
15.0%
10.0%
5.0%
0.0%
-5.0%
-10.0%
-15.0%
No Trade liberalizaiton
Trade Liberalization
Impact on volatility
Price fluctuations
Homogenous shock
without trade
liberalization
Heterogenous shock
with trade
liberalization
without trade
liberalization
trade liberalization
3%
2%
4%
6%
Rapeseed
16%
14%
14%
12%
Soybeans
2%
2%
4%
4%
Sugar_cb
3%
5%
2%
2%
Wheat
4%
2%
2%
5%
Maize
Impact on world price volatility – Monte Carlo approach
(changes in the standard deviation – full EU mandate – no trade lib.)
Preliminary results – do not
quote
More robust results coming
Main trend: reduction in the
amplitude
Page 18
Concluding remarks


Role of structural changes

Demand

Supply structure

Sectoral dimension

Spatial dimension
In terms of price fluctuations

Demand effect seems to dominate