Transcript Slide 1

Implications of Global Demand for Biofuels:
CGE Analysis for Argentina
Presentation by Miles Perry,
Centre for Environmental Policy,
Imperial College, London
[email protected]
Kiel Institut für Weltwirtschaft
June 30th, 2009
UK Bioenergy Research & my PhD Project
The TSEC-Biosys Project:
a whole systems approach to bioenergy
demand and supply
Theme 1:
Integrated analysis of bioenergy demand
and supply dynamics
Theme 2:
Analysis of potential evolution and
implications of UK biomass supply
Theme 3:
Sustainability analysis of bioenergy supply
chains for heat, power and transport.
Theme 4:
Total system performance and evolution
Theme 1.4:
Analysis of potential for international bioenergy
trade and implications for the UK
= my PhD project
Project Partners:
- 8 UK universities
- 4 Research institutes and consultancies
- Includes experts in:
soil science, agronomy, hydrology, engineering, policy
appraisal, sustainability frameworks, biomass conversion
technologies
My PhD Project II
TSEC Theme 1.4:
Analysis of potential for international bioenergy trade and implications for the UK
Analysis of potential for
international bioenergy trade
Literature Review:
Implications for the UK:
Where does imported biomass fit in?
Substantial global bioenergy potential – subject to many
caveats
- Review of UK biomass trade history:
(Biomass & Bioenergy, 32 8 2008)
- Modifications to UK-MARKAL model
What are the implications of policy-driven mass
biomass import?
CGE Analysis of Biomass Exporter
Why CGE?
At the time (winter 2006):
- Literature had demonstrated potential for large-scale bioenergy use and biomass trade
with ex ante sustainability conditions assumed to hold
- Lifecycle analysis and case studies provided insight into environmental and social impact
for individual supply chain scenarios
But for large importer (UK) in a growing global market:
- We need to start from a scenario resembling current reality…
- … and consider the systemic impacts of bioenergy trade
hence CGE
Research Premise
Argentina is a significant exporter
of biofuel-relevant agricultural
commodities:
Commodity
Share of Global Exports
2000-2006
Maize
13%
Wheat
8%
Soybean Oil
43%
Oilseed Meal
30%
If foreign biofuel policies cause a leap in export demand for these
products,
what would the implications be for Argentina?
The BioTradeLand CGE Model
Argentina Social Accounting Matrix (SAM) for the year 2000
Petri & Parra, IFPRI, 2005
+
Small open-economy, comparative static
CGE model in GAMS/MPSGE
=
BioTradeLand model
Modelling Scenarios
Commodity Price Shock Simulates Demand for Biofuels
Medium-term world price effect of US and EU biofuel mandates taken from
Wiggins et al. (2008) Review of the Indirect Effects of Biofuels: Economic
Benefits and Food Insecurity. Overseas Development Institute, London.
Soybeans: +34.5%
Maize: +11%
Vegetable Oils & Co-products: +5.8%
Minor changes in other sectors
Fed into the model as changes to (exogenous) world prices
Alternative Scenarios
- Price Shocks for Vegetable Oils and Oilseed Meals
20% Vegetable Oil price
 19% Oilseed Meal price
Symptom of ‘pure’ biofuel price shock. Based on Schmidhuber1
- Allowing for Land-use Change
‘Classic’ CGE (finite factors of production and full employment)
of limited use. Two alternatives proposed
- ‘Flat’ land.
- Upward-sloping land supply curve
- Rural:Urban Mobility of Labour
How does imperfect labour mobility affect response to the price shock?
- Oilseed Meal as Animal Feed
What is the effect of allowing oilseed meal to substitute for other animal
feeds?
1 – Impact of an increased biomass use on agricultural markets, prices and food security. FAO, 2006
Land Use Change
i.e. possible expansion of agricultural land area
- ‘Flat’ land: solve for quantity instead of price in equilibrium
- Asymptote:
Price shock  D Land price  D Quantity of agricultural land:
 Solve model with new land quantity  D Land price
Repeat until land P:Q converges
Maximum Land Area
(asymptote)
= 266 Mha
From GTAP-AEZ database
Curve from Van Meijl et al.
Agriculture, Ecosystems &
Environment. 114 1.
Oilseed as Animal Feed
Standard CGE classifies
land as primary factor of
production.
We also consider the case
where land, feed crops
and oilseed meal are
substitutable
Results: Effect of Price Shock
- Shift towards soybeans in agriculture, at the expense of other crops
(except maize)
- Increase in output from oilseed-crushing sector
but only when oil and meal prices rise
- Relatively small impact on other sectors in % terms
Results: Effect of Land Supply Variations
- Extra land allows further increase in production of oilseeds and maize
with fewer sacrifices in other areas.
- Point Elasticity of land supply:
0.76 < eta < 0.86
- After 15 iterations;
land quantity
= 10.5% above baseline
land price
= 17% above baseline
eta
= 0.79
Results: Effect of Labour Mobility Restrictions
% Change in Production. Land Supply Curve. Separate Vegetable Oil/Meal shocks
100.00
% change compared to baseline
80.00
60.00
40.00
20.00
0.00
-20.00
-40.00
Mobile Labour
Restricted Labour Mobility
Results: Effect of Land/Feed Substitutability
- Substitutability reduces land intensity of livestock sector
- But maize and soybeans replace grazing – not oilseed meal
- Substitutability reduces land supply growth to +7% compared to +7.3%
without substitutability
Results: Wage & Welfare Implications
- Representative Agent consumption increases, but
only slightly
+ 0.61% with Mobile Labour (Land supply curve, separate oil/meal shocks)
+ 0.51% with Restricted Mobility (same)
- Wage earners’ purchasing power falls slightly
except for rural workers when labour market is segregated
Overall
Mobile
-0.35%
Restricted-urban
-0.58%
Restricted-rural
+12.41%
Wage purchasing power for staple foodstuffs falls by 5-10%
But >70% RA consumption is services.
Welfare implications possibly serious for some groups but not observable
from SAM aggregation.
Results: Summary
Reaction to the same price shock in different scenarios
Baseline
Fixed
Agricultural
Area
Land Supply
Curve:
Mobile
Labour
Land Supply
Curve:
Restricted
Mobility
Land Supply
Curve:
Livestock
Feed
Substitutable
Soybean Exports
(USD)
777
2,500
3,140
2,930
2,890
Vegetable Oil
Exports
2,013
1,940
2,440
2,290
2,240
Land Area (Mha)
128.77
128.77
142.36
138.55
137.43
RA Consumption
(USD)
246,810
247,490
248,330
248,070
248,020
Real Wage
(baseline = 1)
1
0.99
0.997
Urban: 0.99
Rural: 1.12
Urban: 0.99
Rural: 1.10
USD figures refer to million year 2000 US dollars.
Conclusions
- Effect of meal price is significant, but will we ever see a 'pure'
biofuel shock?
25% increase in vegetable oil exports becomes 4% decrease when meal price
falls
- Macro-level impact of shock appears small, esp. if agricultural area
does not expand
Vegetable oil imports only increase after prices shock when additional land is
available
- Welfare effects difficult to discern other than benefit to rural labour
force
Directions for Future Research
- Insights limited by SAM-calibration nature of model.
- Next steps would be to incorporate more robust technical or
economic data:
- Technically explicit land-use and livestock nutrition characterisation
- More disaggregation of urban/rural household incomes
- More realistic drivers of land-use change
THANK YOU
QUESTIONS?