Govinda R. Timilsina

The World Bank, Washington, DC

Fourth Berkeley Bioeconomy ConferenceMarch 24-26, 2011

Economic and Environmental Impacts of Biofuels

Disclaimer

The views expressed in this presentation are those of the authors only, and do not necessarily represent the World Bank and its affiliated organizations

Presentation Outline

Introduction (Model/Data) Impacts on Land Use & Food Supply Impacts on Climate Change Mitigation Oil Prices and Biofuels Conclusions

Biofuel Production and Commodity Prices

0

50

100

150

200

250

300

2000 2002 2004 2006 2008 2010

Pric

e in

dex

(200

0 =

100)

Maiz Sugar

Wheat Soybean

Rice Sorghum

Barley

0

20

40

60

80

100

2004 2005 2006 2007 2008 2009

Biof

uel p

rodu

ction

(Bi

llion

Lite

r) Ethanol

Biodiesel

Biofuels

0

100

200

300

400

500

2000 2002 2004 2006 2008 2010

Pric

e in

dex

(200

0 =

100) Agriculture

Energy

Fertilizers

Ethanol 13.1% Biofuel 13.6%Biodiesel 15.6%

Maize -14.1% Agriculture 2.6%Sugar 65.3% Energy -18.8%Wheat -31.6% Fertilizers -49.8%Soybean -12.8%Sorghum -23.5%Barley -29.2%

% ChangeProduction (2008 - 2009)

Price (2008-2010)

World Bank Biofuel Studies

Study type Issues analyzed or investigated

Back

grou

nd

or re

view

st

udy

Biofuels: markets, targets and impacts Advanced biofuel technologies: status and barriers Second generation biofuels: economics and policies Are there any surplus grains to produce biofuels?

Parti

al

equi

libriu

m

mod

elin

g

Quantifying the role of biofuels in the global food crisis

Gen

eral

eq

uilib

rium

m

odel

ing

Biofuels, land-use change and food supply Biofuels and climate change mitigation Biofuels, global income distribution and poverty Biofuel subsidies and import duties World oil price and biofuels Carbon tax and biofuels

CGE Model

• Multi-sector, multi-region, global recursive dynamic CGE model

• The model is flexible enough to accommodate new regions/countries or sectors and is calibrated with GTAP database

• Nested CES and CET functional forms to represent production behavior and land supply, respectively

• Nonhomothetic Constant Difference of Elasticities (CDE) function form for households

• Detailed representation of land-use biofuel sectors

• Representation of bilateral and international trade

Data

• GTAP Data Version 7.1 (Base Year 2004; 112 countries, 57 sectors)

• As the existing GTAP database is limited for conducting biofuel analysis we disaggregate it further, introducing 7 new sectors:

– 1 sector for feedstock: Corn

– 2 sectors for fossil fuels: Gasoline and Diesel

– 4 sectors for biofuels (1st generation):

• 3 ethanol sectors: sugar ethanol, corn ethanol, and other grains ethanol,

• 1 biodiesel: biodiesel from rapeseed oil, soybean and palm oil

Regional and sector decomposition

• Computational limitations require aggregation of countries/regions and sectors

(GTAP: 112 regions & 57 sectors

or 112* 57 = 6,384 equations for 1

variable only defined on 2 dimensions)

• Focus on main countries/regions producer of biofuels

• Keep as much detail as possible for agriculture (especially biofuel feedstocks) and for energy sectors

1 Paddy rice2 Sugar (cane & beet)3 Vegetables, fruit4 Wheat5 Corn6 Other cereal grains7 Oilseeds8 Livestock9 Sugar Ethanol

10 Corn Ethanol11 Grains Ethanol12 Biodiesel13 Processed food14 Forestry15 Coal16 Crude oil17 Natural gas18 Other mining19 Gasoline20 Diesel21 Refined oil22 Chemicals23 Other manufacturing24 Electricity25 Gas distribution26 Construction27 Transport services28 Other services

1 Australia and New Zealand2 Japan3 Canada4 United States5 France6 Germany7 Italy8 Spain9 UK

10 Rest of EU & EFTA11 China12 Indonesia13 Malaysia14 Thailand15 Rest of East Asia & Pacific16 India17 Rest of South Asia18 Argentina19 Brazil20 Rest of LAC21 Russia22 Rest of ECA23 MENA24 South Africa25 Rest of Sub-Saharan Africa

Base Year, Baseline and Scenarios

• Base year: 2004

• Baseline or reference case: A business as usual scenario for 2009-2020 period. It includes policies already in place (e.g., already introduced mandates, subsidies)

• The model is calibrated in such a way that key variables (e.g., oil prices, population, GDP, investments, etc.) retain the historical values for 2004-2009 period

• Two scenarios for biofuel targets:

– Announced Targets (AT) scenario: all the announced biofuel targets are fully implemented by 2020, starting 2009

– Enhanced Targets (ET) scenario: all the announced biofuel targets are doubled (except for India – extremely high announced target) and fully implemented by 2020, starting 2009

• Biofuel targets are achieved by introducing direct subsidies to biofuels, the subsidies are financed through an increase of gasoline and diesel tax (government revenue neutrality)

Targets and Required Subsidies and Taxes

AT ET AT ET AT ETAustralia and New Zealand 1.23 2.46 36.40 57.71 0.13 0.34Japan 0.60 1.20 14.80 45.68 0.05 0.19Canada 4.10 8.20 48.88 68.11 0.50 0.91United States 4.07 8.14 1.01 28.21 0.04 0.77France 10.00 20.00 58.33 74.55 1.05 1.80Germany 10.00 20.00 43.25 65.01 0.95 1.91Italy 10.00 20.00 65.29 78.38 0.81 1.30Spain 10.00 20.00 60.99 75.11 0.64 1.48UK 10.00 20.00 73.14 82.90 0.44 1.06Rest of EU & EFTA 10.00 20.00 75.60 84.82 0.65 0.97China 3.65 7.30 18.20 47.22 0.37 1.34Indonesia 5.00 10.00 19.24 49.16 0.41 1.52Malaysia 1.81 3.62 1.59 39.31 0.02 0.60Thailand 5.20 10.40 51.58 73.69 0.91 1.80Rest of East Asia & Pacific 1.49 2.98 42.00 57.77 0.19 0.38India 20.00 20.00 58.37 58.92 4.14 4.22Rest of South Asia - - - - - -Argentina 5.00 10.00 52.10 70.32 0.86 1.53Brazil 11.77 23.54 - 2.76 - 0.93Rest of LAC 1.48 2.96 16.30 44.58 0.10 0.39Russia - - - - - -Rest of ECA - - - - - -MENA - - - - - -South Africa 2.00 4.00 0.93 10.05 0.03 0.68Rest of Sub-Saharan Africa - - - - - -

Target (%) Subsidy Rate (%) Tax Rate (%) Country/Region

Global Biofuels Penetration

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

2005 2010 2015 2020

Reference Case

AT Scenario

ET Scenario

Impacts on Biofuel Production – Country/Region

Brazil, France, India would realize the relativelyhigher production of biofuels; while biofuel production increase is caused by international trade in Brazil, the increase in other countries is driven by domestic targets

Countries which do not have biofuel targets could experience decrease in production due to increased export demand for their biofuel feedstock, but the reductions are negligible

0 5 10 15 20

Australia and New Zealand

Japan

Canada

United States

France

Germany

Italy

Spain

UK

Rest of EU & EFTA

China

Indonesia

Malaysia

Thailand

Rest of East Asia & Pacific

India

Argentina

Brazil

Rest of LAC

South Africa

ET Scenario

AT Scenario

Baseline

Global Production of Biofuels in 2020

% Change from the baseline

0 100 200

Developed World

Developing World

Global

ET

AT

Reference

0 100 200 300

Developing World

Developed World

GlobalET

AT

Production in value (2004 Billion US$)

Impacts on GDP in 2020(% change from the baseline)

Countries which have already advanced in biofuels production and produce feedstock whose price increases exhibit positive or small negative impacts

Oil producing countries such as MENA, Russia would suffer due to reduction in their oil exports which is replaced by biofuels

For sub-Saharan Africa, it is the aggregation effect, highly influenced by Nigeria

-0.30 -0.23 -0.15 -0.08 0.00 0.08

Aus-NZJapan

CanadaUnited States

FranceGermany

ItalySpain

UKRest of EU & EFTA

ChinaIndonesiaMalaysiaThailand

Rest of EAPIndia

Rest of SAArgentina

BrazilRest of LAC

RussiaRest of ECA

MENASouth AfricaRest of SSA

AT ET

Change in Agricultural Production in 2020

-3.0 0.0 3.0 6.0 9.0 12.0 15.0

Agriculture

Paddy rice

Sugar crops

Corn

Wheat

Other grains

Oil seeds

Fruit & vegetables

Livestocks

ET

AT

AT ETAgriculture 14.6 38.3Paddy rice -0.2 -0.5Sugar crops 5.8 9.7Corn 1.4 5.5Wheat 1.9 5.6Other grains 3.0 7.5Oil seeds 4.3 13.6Fruit & vegetables-1.0 -1.8Livestocks -0.6 -1.3

2004 Billion US$% change from the baseline

Impacts on Total Agricultural Production

EU countries exhibit the higher increase in agricultural outputs due to large scale expansion of biofuels

None of the countries in the world would have a reduction in agricultural outputs

Countries which experience decrease in biofuel production would still get their agricultural outputs increased due to their increased export demands for biofuel feedstock

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

World totalHigh-income

Australia and New ZealandJapan

CanadaUnited States

FranceGermany

ItalySpain

UKRest of EU & EFTA

Middle & Low-incomeChina

IndonesiaMalaysiaThailand

Rest of East Asia & PacificIndia

Rest of South AsiaArgentina

BrazilRest of LAC

RussiaRest of ECA

MENASouth Africa

Rest of Sub-Saharan Africa

ET

AT

% change from the baseline in 2020

Impacts on Commodities Prices

Prices of agricultural commodities increase due to direct and indirect pull from increased biofuel production

Energy prices decrease due to direct and indirect substitution of fossil fuels with biofuels

-2.0 0.0 2.0 4.0 6.0 8.0 10.0

Paddy riceSugar (cane & beet)

Vegetables, fruitWheat

CornOther cereal grains

OilseedsLivestock

EthanolBiodiesel

Processed foodForestry

CoalCrude oil

Natural gasOther mining

GasolineDiesel

Refined oilChemicals

Other manufacturingElectricity

Gas distributionConstruction

Transport servicesOther services

AT

ET

% Change from the baseline in 2020

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

AT ET AT ET AT ET

Forest Pasture Crops

Impacts on Global Land Use (% change from the baseline)

Impacts on Land Use by Country(% change from the baseline)

-2.0 -1.5 -1.0 -0.5 0.0 0.5

Australia and New Zealand

Japan

Canada

United States

France

Germany

Italy

Spain

UK

Rest of EU & EFTA

China

Indonesia

Malaysia

Thailand

Rest of East Asia & Pacific

India

Rest of South Asia

Argentina

Brazil

Rest of LAC

Russia

Rest of ECA

MENA

South Africa

Rest of Sub-Saharan Africa

Crops Pasture Forest

-6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0

Crops Pasture Forest

AT Scenario ET Scenario

Impacts on Food Supply (Change from the baseline, Billion US$)

-16.0

-14.0

-12.0

-10.0

-8.0

-6.0

-4.0

-2.0

0.0

AT ET

High-income Middle & Low-income

Impacts on Food Supply by Country (Change from the baseline)

Country/Regions AT ET  US$ Billion % US$ Billion %World total -6.5 -0.1 -14.1 -0.2High-income -2.2 -0.1 -5.8 -0.2Australia and New Zealand 0.0 0.0 -0.1 -0.1Japan -0.1 0.0 -0.2 -0.1Canada 0.0 -0.1 -0.1 -0.2United States -0.9 -0.1 -2.5 -0.3France -0.1 0.0 -0.3 -0.1Germany -0.2 -0.1 -0.6 -0.2Italy -0.1 -0.1 -0.3 -0.2Spain -0.1 0.0 -0.2 -0.1UK -0.2 -0.1 -0.4 -0.1Rest of EU & EFTA -0.5 -0.1 -1.1 -0.2Middle & Low-income -4.3 -0.2 -8.3 -0.3China -0.5 -0.1 -1.3 -0.2Indonesia -0.1 -0.1 -0.1 -0.1Malaysia 0.0 -0.1 0.0 -0.3Thailand 0.0 0.1 0.0 0.1Rest of East Asia & Pacific 0.0 0.0 -0.2 -0.1India -1.4 -0.4 -1.2 -0.3Rest of South Asia 0.0 0.0 -0.1 -0.1Argentina 0.0 0.0 0.0 -0.1Brazil 0.0 0.0 0.0 0.0Rest of LAC -0.2 -0.1 -0.6 -0.3Russia -0.3 -0.2 -0.7 -0.6Rest of ECA 0.0 0.0 0.0 0.0MENA -1.3 -0.4 -3.0 -1.0South Africa 0.0 0.0 0.0 0.0Rest of Sub-Saharan Africa -0.5 -0.2 -1.2 -0.5

Biofuel penetration, GHG emissions and carbon payback period

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

2010

2015

2020

2025

2030

2035

2040

AT Scenario

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

2010

2015

2020

2025

2030

2035

2040

AT Scenario

Fossil fuels Land-Use Net0

10

20

30

40

50

60

2010

2015

2020

2025

2030

2035

2040

AT Scenario

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

2010

2015

2020

2025

2030

2035

2040

ET Scenario

0

10

20

30

40

50

60

2010

2015

2020

2025

2030

2035

2040

ET Scenario

-10000

-7500

-5000

-2500

0

2500

5000

7500

10000

12500

15000

2010

2015

2020

2025

2030

2035

2040

ET Scenario

Fossil fuels Land-Use Net

GHG emissions: Deforestation vs. No-Deforestation (Million tCO2)

-10,000

-5,000

0

5,000

10,000

15,000

Fossil Fuels

Land Use

Net Fossil Fuels

Land Use

Net Fossil Fuels

Land Use

Net Fossil Fuels

Land Use

Net

AT ET AT ET

Deforestation No-deforestation

2020

2030

2040

Oil Price & Biofuels: Scenarios

Source: EIA (2009) and IEA (2009) for baseline data for period 2009-2015.

• Scenarios: 25% to 100% increase from the baseline prices;

• 2020 price in the baseline would be 65% higher than the 2009 level;

• 2020 prices under the 25%, 50% and 100% scenarios are 106%, 147% and 230% higher than the 2009 level.

Year Baseline

25% 50% 100%

2009 56

2010 67

2015 87 109 130 174

2020 93 116 140 186

2009 0

2010 19

2015 54 92 131 208

2020 65 106 147 230

Scenario

US$/barrel (2008 price)

% Change from 2009 level

Biofuel Penetration under Various Oil Price Scenarios

2%

4%

6%

8%

10%

12%

14%

2010 2015 2020

Baseline 25% 50% 100%

Impacts of 50% Oil Price Increase on Production of Biofuel Feedstock

-2.8%

2.4%

-1.0%-0.4%

3.7%

-1.7%

-3.2%-3.7%

Rice

Corn

Wheat

Other Grains

Sugar crops

Oil Seeds

Fruits & Vegetables

Livestock

Key Conclusions

Biofuel mandates, as announced or doubling them, would cause moderate impacts on the economy (price changes across commodities: -2% to 9%; GDP impacts -0.35 to 0.15 across countries)

It would cause significant re-allocation of lands between forest, pasture and crops leading to deforestation and pasture land conversion, particularly in countries with higher targets

No net reduction of GHG emissions is found in the short-run; in the long-run GHG reduction is possible, but takes 1 to 20 years depending upon if deforestation is avoided or not

Oil price play a significant role in stimulating biofuels; if oil prices rise

150% from their 2009 levels by 2020, rather than the 65% in the baseline, the penetration of biofuels would be even higher than that would be caused by current mandates and targets

Govinda R. Timilsina

Sr. Research Economist (Climate Change & Clean Energy)

Development Research Group

The World Bank

1818 H Street, NW

Washington, DC 20433, USA

Room: MC3-451

Mail Drop: MC3-300

Tel: 1 202 473 2767

Fax: 1 202 522 1151

E-mail: gtimilsina@worldbank.org

THANK YOU