training workshop on modeling agricultural sector …...training workshop on modeling agricultural...

Training workshop on Modeling

Agricultural Sector and

Agricultural Policy in a CGE

Framework

David Laborde – IFPRI

PEP Network

Manila, Philippines, December 6th, 2008

jcoc

Stamp

Overview

• Supply side

• Demand side

• Agricultural policies

• Hot topics

Different points of view

• Static versus dynamic model

• Short term versus Long term

• Single country versus Multicountry

• Developing country versus Developed country▫ Political economy of agricultural policies

• Several models: GOAL (Gohin, 2004), GTAP-AGR (Keeney and al. 2005), Linkage (van Der Mensbrugghe, 2005), MIRAGE (Decreux and al, 2007)

Why agriculture is important for poor

people• They are the consumers the most concerned by

the price of food products

• Most of poor people work in the agriculture sector

A. Production factors

Labor market

• Dual labor demand: Imperfect substitution between agricultural labor and non ag. Labor▫ CES ▫ Lewis

• Dual labor supply: trade off between farm and non farm activities for household

• Hertel and Winters. Poverty and the WTO: Impacts of the Doha Development Agenda by Thomas W. Hertel and L Alan Winters, Editors. The labour market plays a critical role in pro-poor effects of agricultural trade liberalizaiton

Integrating Land as a production factor

• Beyond Capital and Labour

• Where in the SAM

• The value of Land

• The ownership of land

Land Use

• Two main issues:

▫ Land supply

▫ Land mobility

• "Economic Analysis of Land Use in Global Climate Change Policy," edited by Thomas W. Hertel, Steven Rose, and Richard S.J. Tol

• Step 1: describing the physical world

An heterogenous world (1)

From Ramankutty, N., A.T. Evan, C. Monfreda Foley, J.A. in Manfreda and al. 2008,

An heterogenous world (2)

From Ramankutty, N., A.T. Evan, C. Monfreda Foley, J.A. in Manfreda and al. 2008,

LGP: period of 60 days with conditions

(temperature-moisture) for growing

crop

3 x 6 = 18 Agro-Environmental Zones

Other considerations

• FAO: 18 AEZ x 175 products

• Difference between Harvested areas and physically cultivated area

• Land rents and splitting operation

Step 2: New Land – Land supply• Virgin forests and meadows

• An elastic land supply function

• But also demands (urbanisation etc.)

r

Surface

Potential arable land

See Van Meijl and al (2006) for elasticities

Step 3: Land mobility – Applying the

PEM (OECD) approach

From Huang and al, 2004

This can be done for each AEZ…

A Simple illustration – Reduction of

subsidies in the EU – EU land use

From Huang and al, 2004

Other issues

• Water▫ Green water vs Blue Water: Rain Fed and irrigation. Two types of

land. Different yields (average and variance)▫ Water demand in the model: a matter of technology▫ Water cycle▫ Price of Water: see “When Water is No Longer Heaven Sent…”

Decaluwe and ali, 1999▫ Defining water supply. Allocation versus new sources▫ Food safety dimension▫ Virtual water in trade

• Regional modelling▫ Sub country level▫ Redistribution issue. Land is not mobile geographically

B. Modeling specific inputs

Specific intermediate consumptions

• Fertilizers-Pesticides (crops) and Feedstocks(livestocks)

• They increase the efficiency of production factors

• Define the degree of intensification of the agricultural sectors

• A real value added for a CGE framework (sectoral linking)

Exemple: The Linkage model – Crop (a)

Van Der Mensbrugghe (2005)

Exemple: The Linkage model – Crop (b)


Remarks

• Substitution between fertilizers and other factors depends of the level of development

• What is the fertilizer sector in your model?

▫ Different fertilizers (6 in Gohin, 2004, + 1 pesticide)

▫ The role of natural gas price

Exemple: The Linkage model –

Livestocks (a)


Energy

• Modern agriculture is energy intensive

• Different type of energy

▫ Fuels for tractors and trucks

▫ Electricity for irrigation

• Interactions between agriculture are numerous, in particular in the context of biofuels

C. Multi-products sector

Examples from GOAL (Gohin, 2004,

2008) – Farm ProductsAGRICULTURE

Sector Agricultural sub-sectors

Agriculture Soft wheat

Barley

Maize

Rape

Sunflower

Soya

Protein crops

Sugar beet

Fodder

Grass

Poultry

Pigs

Laying hen

Dairy cows

Suckling cows

Beef calf

Calf rearing

Heifers

Bulls and Steers

Sheep and goats

Fruits vegetables

Other agricultural activities

Soft wheat

Barley

Maize

Rape

Sunflower

Soybean

Protein crops

A&B Sugar beet, C sugar beet

Fodder on arable land

Grass

Poultry, Organic nitrogen, Organic phosphate, Organic

potassium

Pigs, Organic nitrogen, Organic phosphate, Organic potassium

Eggs, Poultry, Organic nitrogen, Organic phosphate, Organic

potassium

Bovine cattle, Raw milk, Calves, Dairy cows, Organic nitrogen,

Organic phosphate, Organic potassium

Bovine cattle, Calves, Suckling cows, Organic nitrogen,


Beef calf, Organic nitrogen, Organic phosphate, Organic

potassium

Bovine cattle, Heifers, Bulls and Steers, Organic nitrogen,


Bovine cattle, Dairy cows, Suckling cows, Organic nitrogen,


Bovine cattle, Organic nitrogen, Organic phosphate, Organic

potassium

Sheep and goat milk, sheep and goat animals

Fruits, potatoes and vegetables

Other agricultural products

Examples from GOAL (Gohin, 2004,

2008) – Food and other ProductsFOOD PROCESSING

Meat industry Bovine meat, Pig meat, Poultry meat, Veal, sheep and goat

meats, Carcass meals, Animal fats

Dairy industry Butter, Skimmed milk powder, Cheese frow cow, cheeses from

sheep and goat, Whole milk powder, fluid milk, Other dairy

products

Compound feed industry Compound feed

Cereal processing industry Grains bran, Corn gluten feed, iso-glucose, Other cereal

processed products, bio-ethanol

Oilseed crushing industry Rape oil, Sunflower oil, Soybean oil, Rape cake, Sunflower

cake, Soybean cake, palm oil

Sugar industry A&B Sugar, C sugar, Sugar beet pulp, Molasses

AGRICULTURAL STATIONERIES

Mono product sectors supplying: Mineral nitrogen, Mineral phosphate, Mineral potassium,

pesticides, veterinary products, fish meals, other energy rich

feed, other protein rich feed, other feed ingredients, seeds

OTHER SECTORS

Food retail trade Food retail trade services

Other sectors Other products and services

Implementation

• CET• Leontieff technology

▫ Technical constraints (Two wings per chicken)▫ by products

• Keep in mind that differentiated products can be related to quality range or standard of production (organic, export certificate)

D. Risk and Agriculture

Agriculture is a risky business

• Productions and Prices are volatile.• Exogenous uncertainty

▫ Weather▫ Pests and diseases

• Endogenous risk▫ Producer choice: the pig meat market ▫ Speculation▫ Boussard, J.; Gerard, F.; Piketty, M. G.; Ayouz, M. &

Voituriez, T. (2006)

• Public and private storage• Most of “farm” policies address this problem

E. Agriculture and Technical progress

Productivity gains in agriculture

• Very important in dynamic model• Standard approach of the TPF: Homogenous across

sectors (manufacturing and agri)• If biased towards some sectors, changes in relative

prices and sector specialization▫ Difficult to have a general rule

• Differences across agricultural sectors:▫ In some country, we know that new seeds (varieties)

exist for crops and that we “just “have to implement them

▫ Strong productivity gains have been seen in poulty and pig sectors compared to bovine and ovine sectors.

A. Modeling food demand

Functional form and Agricultural goods

• Stylized facts

▫ Share of food decreased in total expenditures with increase in income

▫ Shift from staple food to animal and “exotic” products with increase in income

• In a static framework with policy scenarios focusing on relative prices, income effects are limited at a macro level, but not for some households.

• In a dynamic model, the problem is crucial for a relevant baseline.

How to get relevant Engel curves?

• Cobb-Douglas and CES not relevant

• LES and CES-LES give poor results

• CDE (GTAP) small improvements

• Non Nested CES demand system with semi flexible functional forms. See Perroni and Rutherford (1995). Gohin (2003) non homothetic system based on latent separability.

• Almost Ideal Demand System

In Keeney and Hertel, 2005

+ a third level…

In Keeney and Hertel, 2005

Source of data

• Seal, Regmi and Bernstein (2003), cross country analysis based on 1996 data.

• Updated estimates are coming

• Visit the USDA-ERS website for an online database on income and price elasticities + a list of country specific studies

• FAPRI website

The Armington assumption applied to

agricultural products• Differentiated goods with the Armington

assumption (1969)

• Which interpretation? Gohin and Laborde (2006)

• More or less differentiation in agricultural products?

▫ Higher sigma for reflecting homogenous good (corn)

▫ Lower sigma for reflecting product differentiation (wine, cheese)

▫ Different behavior between final consumers and processing industries

The consequences of domestic

migration• For countries with important Rural Urban

▫ Shifts in consumer behavior

▫ Higher Armington elasticities

▫ Strong shift towards processed food products

Quality related issues

• The Genetically Modified Organisms (GMO)▫ Product differenciation sub-markets ▫ Banned products and trade

• Mad cow disease, Avian influenza▫ Shift in consumption▫ Short and long term effects

• But also a strong supply side effects▫ Yields▫ Contamination effects (regional model, stochastic

simulations)

Some references on GMO mainly

focused on the supply side• Anderson, K., and S. Yao. 2003. China, GMOs, and world

trade in agricultural and textile products. Pacific Economic Review 8: 157–69.

• Anderson, K., E. Valenzuela, and L.A. Jackson. 2006. GM cotton adoption, recent and prospective: A global CGE analysis of economic impacts. Discussion Paper 5568. London: Center for Economic Policy Research.

• Anderson, K., L.A. Jackson, and C.P. Nielsen. 2004. Genetically modified rice adoption: implications for welfare and poverty alleviation. Policy Research Working Paper 3380. Washington, D.C.: World Bank.

• Gruere, G.; Bouet, A. and Mevel, S. (2008), 'Genetically Modified Food and International Trade', IFPRI Discussion Paper.

B. Market power and distribution

Link between farmers and markets

• Exogenous parameter: transport costs

• Domestic transportation cost from rural areas to cities

▫ P_Farm = P_Market – Transport costs

▫ If Transport costs are ad valorem and constant (P_Farm = P_Market x (1+tr), same price variations .

▫ Otherwise, imperfect price transmission

Link between farmers and consumers

• Endogenous parameter: market behaviour• Oligopsoly and Oligopsony• In CGE, more studies on forestry than agricultural

sector• GE - Laborde, D. & Le Cacheux, J. (2003), 'Price and

Welfare Effects of Agricultural Liberalization with Imperfect Competition in Food Industries and Trade„Limits of constant mark-up framework. Need to

have changes in elasticity of demand.• PE - Sexton Richard J. and Zhang Mingxia. « An

assessment of the Impact of Food Industry Market Power on U.S. Consumers ». Agribusiness, Vol 17 (1) 59-79. 2001

A. Modeling domestic support

A developed country issue?

• Active farm policies are mainly used by developed countries (EU Common Agricultural Policy, US Farm bill)

• But,

▫ They have strong and contrasted effects on developing countries

Diao, X., Diaz-Bonilla, E., Robinson, S., & Orden, D. (2005); Bouët, A., Bureau, J.-C., Decreux, Y., & Jean, S. (2005

▫ Emerging countries may use these policies too

Static vs dynamic

• Domestic support policy can become naturally very costly for government (as a % of GDP, see the EU CAP).

• Dynamic modeling requires to consider the budget constraint of the government

• Asymmetry of problematic between Developed and Developing countries

Production subsidies vs Income support

• Production subsidy Direct effect on production. Strong distortions in trade.

• Input subsidies:

▫ Subsidized loans (capital)

▫ Fertilizers

▫ Energy : gas for tractors, but also pumping water (India)

▫ Input for processing industries (butter, tomatoes)

• Direct support to income: decoupled payments

Decoupled payments = non distortive?

• Designed as a direct payment to farmer without correlation to present level of production. In general, based on the surface of the farm, cultivated or not.

• Numerous works (Gohin, 2006; Blandford, 2005, USDA…)

• Basic approach: use of a re-coupling factor

▫ X % of the direct subsidy is shift to a production subsidy

Why?

• Basic argument: “If you give money to a farmer, he remains a farmer and buy a new tractor…”

• Rolling approach in computing historical payments Strategic behavior of farmers

• Transmission to land prices: the role of land ownership structure

• Wealth effects and risk aversion

• Link to invesment and capital market imperfections

Production quotas

• In general, joint uses with other support

• If initially binding, change the supply answer of any scenario

• Value of the rents

• Programming choice (in GAMS)

▫ MCP

▫ Loop procedure with “regime” and conditional equations

S

p

Q

D

quota

Pw+t1

Pw + t2

B. Modeling trade policies

Different kind of protectionist

measures• Ad valorem duty %• Specific duty USD10 per ton

▫ Endogenous level of distortions If export price = $100/ton, AVE = 10%

If export price = $50/ton, AVE = 20%

• Compound tariff 10% + USD10 per ton• Mixed tariff 10% Minimum of USD10 per ton• Tariff rate quotas• Contingent protections• Entry prices• NTBs

Tariff Rate Quotas

58

Seasonal protection and more

23.44 EUR / 1000 kg

15.22 EUR / 1000 kg

49.94 EUR / 1000 kg

Imported by land, inland waterway or sea from Mediterranean, Black Sea or Baltic Sea Ports

11.44 EUR / 1000 kg

3.22 EUR / 1000 kg

37.95 EUR / 1000 kg

Imported by sea from ports other than Mediterranean, Black Sea or Baltic Sea Ports and arriving via the Atlantic Ocean with the port of unloading in Ireland, the United Kingdom, Denmark, Sweden, Finland or on the Atlantic Coast of the Iberian Peninsula

10.44 EUR / 1000 kg

2.22 EUR / 1000 kg

36.95 EUR / 1000 kg

Imported by sea from ports other than Mediterranean, Black Sea or Baltic Sea Ports and arriving via the Atlantic Ocean or the Suezcanal with the port of unloading on the Mediterranean Sea

13.44 EUR / 1000 kg

5.22 EUR / 1000 kg

39.95 EUR / 1000 kg

Imported by sea from ports other than Mediterranean, Black Sea or Baltic Sea ports or imported by air

September 2001

May 2001March 2001Low quality durum wheat : 1001 10 00 30

Very strong heterogeneity of tariffs

The EU example in dairy sectorsAVE NC8 - 170 Bound tariff lines

0.00

50.00

100.00

150.00

200.00

250.00

300.00

0401

1010

0401

2099

0401

3091

0402

1099

0402

2199

0402

2999

0402

9151

0402

9919

0403

1011

0403

1039

0403

1093

0403

9031

0403

9059

0403

9073

0404

1002

0404

1016

0404

1036

0404

1056

0404

1076

0404

9023

0405

1011

0405

2010

0406

1020

0406

3039

0406

9001

0406

9006

0406

9021

0406

9031

0406

9050

0406

9075

0406

9082

0406

9088

2105

0099

Whey and modified

whey

Butter

From complex policies to a simple Ad

Valorem Equivalent (AVE)• MAcMapHS6 database (2001, 2004)

provides bilateral tariffs for 682 agricultural products (and 5,113 products in total) at a bilateral level for 166 importers and 213 exporters

• Important improvement for researchers.

• Used in GTAP6 and GTAP7.

• Several assumptions to compute AVE at the tariff line level and to aggregate it to a CGE

61

MAcMap Methology : The Reference

Group• Clustering on countries (real gdp per capita,

trade openness) : 5 reference groups

• Group of exporters : Computation of Unit values, ERGUV.

▫ To limit the noise in unit value data

▫ To keep economic relevant of ad-valorem equivalent of specific tariffs

• Group of importers : weights for the MAcMap methodology of aggregation (against the endogeneity problem).

62

How to weight a HS6 product tariffs ?

Brazil

EU

US

Japan

Australia

Other Ref. Group A ’s

countries

Ref. Group A

Trade weight

Ref. Group Weight

63

TRQ in MacMapHS6

• Source : AMAD and WTO notifications + National sources

• In quota / Out Quota rate ?▫ Three regimes are defined based on the filling rate

of the quota

• When not available, quota allocation based on trade

Robustness of the methodology to the aggregation procedure

MAcMapHS6 includes also non ag.

goods

Tariff structure

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Aus

tralia

Can

ada

Eur

opea

n Union

Japa

nUSA

Bra

zil

China

India

Sou

th a

frica

Thaila

nd

Rus

sian

fede

ratio

n

Wor

ld

Pref_Margins

Trq_margins

Ad_valorem

AVE_specific

The role of TRQ in measuring

protectionCountries Inside rate

appliedMacMapHS6solution

Outside rate applied

South Africa 12.6 15.1 18.0

Canada 5.7 15.9 17.3

China 10.6 11.1 25.9

South Korea 23.8 36.8 55

United States 3.8 8.9 9.9

Japan 20.0 28.2 31.6

Panama 13.1 15.8 17,7

Switzerland 30.1 53.2 83.6

European Union 16.1 21.3 24.2

All countries with TRQ

14.7 18.8 22.0

Other issues

• Tariff escalation▫ Higher tariffs on final good▫ Lower tariffs on raw or intermediate products▫ At the world level for agriculture, tariffs on final

goods = 1.8 tariffs on inputs

• The role of trade policies on agricultural inputs▫ Fertilizers▫ Seeds▫ Machinery

• Poor people and protection on staple food.

Modeling strategy

• More important issues to deal with:▫ Tariff heterogenity▫ Specific tariffs to be introduced explicitly▫ The role of TRQs

• Depends of the goal of your study▫ Unilateral trade reform in a small country. Complexity of

foreign policy have small implications (except on quality effects)

▫ Bilateral agreement or multilateral agreements: very challenging task. Linking models can be a solution (global CGE and country level CGE).

▫ Keep in mind that in some cases, a limited number of products are relevant in terms of exports for a small country

C. Interaction between domestic and trade policies

Intervention price

• Domestic government fixes a target price for commodity A

• Market intervention to maintain price▫ Public storage

• Regulation based on world markets▫ If world price is lower than intervention price: tariff =

intervention price – world price▫ If domestic demand < domestic supply at the

intervention price: Export subsidy to clear the market. Export subsidy= intervention price – world price

▫ Both measures at the same time▫ Otherwise, Import subsidies may be implemented

Modeling options

• If mono-country and small country assumption, things are simple. Exogenous computation.

• If world prices are endogenous:▫ MCP approach▫ Loop structure in GAMS using shift in regime (as for

production quota)

• Remark on the side effect: what to do if the country under investigation is “just” indirectly affected by a reform: The EU sugar reform and the ACP countries▫ Beyond a reduction in export prices

A. The trade negotiations of the Doha Round

Main issues

• Larger of the overall gains related to agriculture

▫ Highest distortions

▫ Winners and losers?

Consumers/Taxpayers in the North

Producers in the South

• Flexibilities within formula

▫ Selecting sensitive and special products

• Domestic support – Thinking within boxes

▫ Green, blue and orange

The suspension of agricultural

multilateral trade negotiations:

What is the true responsibility of the

European Union?

Fabienne Féménia, Alexandre Gohin

INRA Rennes

IATRC Meeting Washington, 7-9 january 2008

1. Lamy triangle of issues

Market Access

Agriculture

Domestic Subsidies

Agriculture

Market Access

Manufacturing

Developing

Countries

EU

US

Economic evaluations of the three

agricultural pillars

Developed Developing World

Export Competition

Domestic support

Market access

Total

2554

2450

31811

36815

-1511

359

11984

10832

1043

2809

43795

47647

Position of the European

Commission

WB study OECD study USDA study

Market access

Domestic support

Export Competition

Total

93%

5%

2%

100%

79%

19%

2%

100%

54%

32%

14%

100%

Main objectives of the paper

• Measure the real contribution of EU subsidies and tariffs▫ With the widely used GTAP CGE framework▫ Last database

• Test the sensitivity of results to the modeling and data assumptions▫ To analyze EC comments▫ To integrate last researches

2. Methodology: GTAP-AGR framework

• Detailed database

• Computable General Equilibrium model

• Policy measurements:

▫ Export competition : WTO notification

▫ Domestic support : OECD PSE

▫ Market access : CEPII MacMaps

3. Welfare impacts of developed

agricultural policies

Hertel and Keeney

Export subsidies 2554 -1511 1043

Domestic support 2450 359 2809

Market access 31811 11984 43795

Total 36815 10832 47647

All developed

Export subsidies 2469 -113 -536 2190 -1699 489

Domestic support 4091 2184 -661 6161 -794 5370

Market access 193 1613 24376 28719 12197 40919

Total 6829 3856 23246 37426 10179 47606

Total

developing

WorldTotal

developed

EU15 US Japan

Effects of the CAP, farm bill and

Japanese policy

EU15

Export subsidies 2479 -118 -510 2204 -1663 542

Domestic support 4658 89 -81 4857 179 5038

Market access -363 356 -449 619 9519 10141

Total 6139 298 -1084 6909 8224 15135

Total with sensitive pds 3550 369 -1016 4548 2697 7245

US

Export subsidies -21 2 -19 -30 -31 -61

Domestic support -552 1991 -850 846 -1082 -235

Market access 21 -551 19 -329 402 73

Total -554 1431 -858 468 -710 -243

Japan

Export subsidies 0 0 0 0 0 0

Domestic support -16 21 310 339 63 402

Market access 859 995 24638 27622 2364 29988

Total 795 1012 24781 27743 2304 30048

Total with sensitive pds 4 1289 763 3094 470 3563

Total

developing

WorldTotal

developed

EU15 US Japan

4. Sensitivity Analysis: Self

imports

EU15 Total

developed

Brazil-

Argentina

India Other

developing

Total

developing

World

Initial modelling 2115 2086 74 14 -1098 -1097 989

Export subsidies 4605 4806 331 -6 -55 180 4986

Domestic support 2425 3118 3611 774 1775 6164 9282

Market access 7881 8610 4345 938 634 5704 14314

Total

Self-imports

Export subsidies 1871 1931 99 21 -891 -841 1090


Market access 1299 1774 2512 496 1794 4988 6762

Total 6308 6992 3194 633 1052 4901 11893

Sensitivity Analysis: Production quotas

EU15 Total

developed

Brazil-

Argentina

India Other

developing

Total

developing

World




Market access 7881 8610 4345 938 634 5704 14314

Total

Data



Market access -231 201 1793 -8 604 2627 2828

Total 5593 6267 2440 33 -16 2528 8795

Production quotas



Market access -927 -521 1715 -19 589 2539 2018

Total 5048 5637 2241 7 -301 2038 7675

Sensitivity Analysis: TRQ

EU15 Total

developed

Brazil-

Argentina

India Other

developing

Total

developing

World




Market access 7881 8610 4345 938 634 5704 14314

Total

Production quotas



Market access -927 -521 1715 -19 589 2539 2018

Total 5048 5637 2241 7 -301 2038 7675

Tariff rate quotas



Market access -274 184 632 -20 61 996 1181

Total 5484 6152 1031 4 -663 540 6693

Sensitivity Analysis: Intervention

regime

EU15 Total

developed

Brazil-

Argentina

India Other

developing

Total

developing

World




Market access 7881 8610 4345 938 634 5704 14314

Total

Tariff rate quotas



Market access -274 184 632 -20 61 996 1181

Total 5484 6152 1031 4 -663 540 6693

Intervention regime


Market access -261 103 409 -21 170 857 959

Sensitivity Analysis: direct

payments

EU15 Total

developed

Brazil-

Argentina

India Other

developing

Total

developing

World




Market access 7881 8610 4345 938 634 5704 14314

Total

Direct payments


Domestic support 3453 3665 341 18 -61 215 3879

Market access -347 24 323 -22 131 722 746

Total 4589 5266 1073 16 -791 422 5709

B. Climate change

Climate change and Agriculture

• Mitigation and adaptation strategy• Agriculture as a GHG source of emissions

▫ Cattle – CO2▫ Deforestation – CO2▫ N cycle

• Productivity in Agriculture impacted by▫ Changes in average temperature, CO2, water

availability▫ Extreme events

• Linking models Physical model/PE/Single Country GE / Global GE

HydrologyAgriculture

Socio-Economic Analysis

(Partial Equilibrium)

Agricultural Cost-Benefit Analysis Hydrological Cost-Benefit Analysis

Adaptation Cost Estimation


(General Equilibrium)

Climate Projections


(General Equilibrium)

Avoided

Damages

Adaptation

Scenario

BAU

Scenario

Iterative

adjustment

General Methodology of the Study

Socio-Econ.Impacts

Alternatives ofadaptation

ClimateImpacts

Bio-physicalImpacts

Economy-wideImpacts

AlternativesSelection

WB research project on EAC

C. Biofuels

Issues at stake

• New production sector – new investment

▫ Not in the SAM initially

• Market or policy driven

▫ Mandate

• Integration of Energy and agricultural markets

▫ Input markets

▫ Demand markets

• Land use

▫ The role of by products

D. Food Prices

Impact of Biofuels on Global Agricultural

Markets: A Preliminary General

Equilibrium Assessment

Antoine Bouet

Betina Dimaranan

April 2008

Modeling strategy: Description

• Use of the MIRAGE model of the world economy• We introduce ethanol and biodiesel in the Social

Accounting Matrix. • We adopt conservative assumptions: for example

substitution elasticities between ethanol, biodiesel and some other energies (petroleum products, oil, gas) are fixed at 2

• We shock each country‟s natural reserves of oil, coal and gas in order to get what has been observed from 2001 and 2008 in terms of world prices:▫ Oil price: multiplied by 4▫ Coal price: multiplied by 2.4▫ Gas price: multiplied by 2.2

Modeling strategy: Description• We implement ad valorem equivalent of production subsidies provided by Hertel and al. (2008):

▫ US/Ethanol: +20%▫ US/Biodiesel: +31%▫ EU/Ethanol: +51%▫ EU/Biodiesel: +81%

• We implement export taxes and exports bans and other trade-related measures adopted in 2008 in order to cope with food crisis (source: medias and FAO coverage at IFPRI):▫ China:

export taxation on wheat = 20%

export ban of cereals (nec)

▫ India: export taxation on wheat = 20%

export ban of cereals (nec)

▫ Indonesia: Import duty on wheat = 0%

Import duty on cereals (nec) = 0%

▫ Argentina: export taxation on oilseeds = 40%

▫ EU: Import duty on wheat = 0%

Import duty on cereals (nec) = 0%

…

Modeling strategy: Description

• Three scenarios

▫ Central scenario: energy shock + biofuel subsidies in the EU and the US implemented from 2001 to 2007

▫ Scenario 2: only energy shock implemented from 2001 to 2007

▫ Scenario 3 : energy shock + biofuel subsidies in the EU and the US implemented from 2001 to 2007 + export bans, export taxations and removal of some import duties implemented in 2008

Recent trade policies (export bans…)

amplify the phenomenon – Scenario 3

Increases in world agricultural prices - % - 2007/2001

49.0%

5.6%

56.8%

5.7%

2.4%

0.7% 2.7% 0.5%0%

20%

40%

60%

Cere

als

(nec)

Wh

eat

Oth

er

agric. P

roducts

Oils

eeds

Sug

ar cane, sugar

beet

Liv

esto

ck

Veg

eta

ble

s and

oils

Sug

ar

Summary: price augmentation –

2008/2001 (1) (2) (3)

Cereals (nec) 6.8% 16.2% 49.0%

Wheat 1.7% 5.4% 5.6%

Other agric. Products -1.0% 2.4% 2.4%

Oilseeds 4.3% 50.8% 56.8%

Sugar cane, sugar beet 3.6% 5.7% 5.7%

Livestock -2.3% 0.6% 0.7%

Vegetables and oils -3.8% 3.5% 2.7%

Sugar -1.8% 0.7% 0.5%

(1) Energy shock(2) Energy shock + biofuel subsidies(3) Energy shock + biofuel subsidies+export bans…

Conclusion

• Energy shock▫ Big impact on fossile energy prices▫ Susbtantial impact on agricultural prices, in

particular some cereals (corn) and oilseeds• Support program in favor of biofuels in the US

and in Europe▫ Amplify the augmentation of agr. prices▫ Contribute to a substantial increase in agric.

prod‟n, in rich countries and elsewhere • Export bans/taxation may have a very negative

impact on world markets

training workshop on modeling agricultural sector …...training workshop on modeling agricultural...

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