IFPRI

INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE

Prioritizing agricultural subsector growth and

investments at the country level:

Methodology to assess economy-wide impacts

James Thurlow and Paul Dorosh

International Food Policy Research Institute

USAID/World Bank Workshop on

“Agricultural investment priorities and financing gaps for achieving growth and

poverty reduction targets: Review of evidence and methodology”

January 7, 2010

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Broad Strategic Questions

Is a 6% agricultural growth rate enough to reach national poverty targets? If not what is the required agricultural growth rate?

How can different agricultural sectors contribute to accelerating growth?

How do outcomes vary across sub-national regions?

How will different types of farmers be affected, and what is the impact on rural employment and the non-farm economy?

What are the potential product market constraints caused by expanding agricultural productivity?

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Overview

1. Economywide growth and poverty analysis Overview and key features of the methodology

2. Modeling future growth scenarios Results from the Uganda case study

3. Prioritizing sectors for investment Criteria for ranking crops and sub-sectors

Results from selected country studies

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IFPRI Estimates of Impacts of Agricultural Investments:

Two Analytical Approaches

1. Costing of MDG and Development Objectives using a reduced

form approach (“spreadsheet” calculations of growth and poverty

reduction effects)

» Fan, Johnson, Saurkar and Makobe (2009), “Investing in African

Agriculture to Halve Poverty by 2015”, ReSAKSS Working Paper

No. 25 (February).

» Costing studies for Ghana and Uganda

2. Individual country studies for CAADP using economy-wide

models

» Ghana, Kenya, Nigeria, Rwanda, Uganda, Zambia

» Ethiopia, Mozambique, Tanzania (CGE analysis not including

investment costs)

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Approach 2: Impacts of Agricultural Investments

using Economy-Wide Models (CAADP analysis)

Individual country studies for CAADP using

economy-wide models

» Output-investment elasticities for individual agricultural

sub-sectors (derived from econometric analysis)

» CGE model simulations of the agricultural productivity

shocks showing

Changes in real prices

Sectoral and total GDP growth

Household income and consumption

Poverty rates

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1. Growth and poverty analysisEconomywide (“CGE”) modeling framework

Factor markets

Commodity markets

Foreign markets/

countries

Public sector/

government

Human/physical capital

Productivity/technology

Urban/Rural

Farm/

Nonfarm

Agriculture

Industry

Services

Economic production Incomes and poverty

Production Consumption

Wages, rents,

profits

Foreign trade

Foreign aid

TaxesSpending

and market

policies

Foreign

investment

Taxes and

social policies

Public investment

and macro

policiesPrivate

investment

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1. Growth and poverty analysis: Agriculture-nonagriculture linkages

Models include detailed agricultural and nonagricultural sectors

Capture upstream and downstream linkages (e.g., maize cultivation and

grain milling)

Considers all different income sources (e.g., off-farm, remittances)

Captures labor mobility and rural-urban migration

Includes the government (e.g., public spending, transfers, taxes)

Zambia Kenya Mozam-bique

Tanzania Malawi Ethiopia

Whole economy 100.0 100.0 100.0 100.0 100.0 100.0

Agriculture 20.5 25.7 25.9 31.8 40.1 44.9Cereals 5.5 4.4 5.3 8.3 11.9 13.5Exports 3.5 4.6 1.1 2.8 10.2 4.5

Livestock 3.1 5.4 1.7 5.5 2.5 12.9Manufacturing 13.0 11.0 13.7 8.8 10.8 5.2

Agro-processing 11.5 3.1 2.0 6.7 6.3 2.4Other non-mining industry 10.4 7.1 9.5 10.4 5.7 1.9

Sector contributions to national gross domestic product (GDP) (%)

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1. Growth and poverty analysis: Domestic and foreign markets and prices

Models consider demand and supply interactions in both domestic and

international markets

Includes transaction costs separating home/marketed production

Considers macroeconomic conditions (e.g., balance of payments

constraints and exchange rates)

Share (%) Intensity (%)

Export Import Export ImportWhole economy 100.0 100.0 9.4 22.0

Agriculture 34.9 6.1 13.2 7.3Cereals 0.0 5.5 0.0 18.2Exports 21.5 0.3 63.5 7.1

Livestock 1.6 0.0 3.6 0.0Manufacturing 12.8 87.9 8.3 61.4

Agro-processing 2.1 10.0 2.0 20.8Other non-mining industry 0.0 0.0 0.0 0.0

Sector contributions to trade in Tanzania (%)

“Intensity” is the share of exports in output, and share of imports in demand

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1. Growth and poverty analysis:

Spatial variation in production patterns

Models capture differences in

production patterns across sub-

national regions

Reflects differences in agro-

ecological conditions and

potential

Malawi North Center South Urban

Maize 49.9 43.9 51.1 47.2 72.3

Other cereals 4.7 4.3 2.1 8.0 0.6

Root crops 11.0 20.4 9.7 10.4 4.2

Pulses & oils 23.2 18.4 24.2 24.5 16.5

Horticulture 3.1 4.0 3.3 2.7 2.2

Tobacco 4.4 7.6 6.6 1.5 2.6

Other export crops 3.8 1.3 3.1 5.6 1.7

All crops 100.0 100.0 100.0 100.0 100.0

Land allocated to crops by region in Malawi (%)

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1. Growth and poverty analysis:

Farm-level variations in cropping patterns

Models capture differences in production patterns across farmers with

different characteristics or endowments (e.g., land holding size)

Reflects differences in farmers’ opportunities and constraints (i.e.,

structure of production/crop mix, scale of production, access to

irrigation, etc)

Malawi Large

(>3ha)

Medium

(0.75-3ha)

Small

(<0.75ha)

Urban

Maize 49.9 45.4 47.8 52.4 72.3

Other cereals 4.7 1.2 5.5 6.2 0.6

Root crops 11.0 4.6 12.6 12.8 4.2

Pulses & oils 23.2 14.6 25.5 24.3 16.5

Horticulture 3.1 1.7 3.4 3.3 2.2

Tobacco 4.4 22.5 1.8 0.0 2.6

Other export crops 3.8 10.0 3.5 1.0 1.7

All crops 100.0 100.0 100.0 100.0 100.0

Land allocated to crops by scale of production in Malawi (%)

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The Data Base

EDRI 2004/05 Social Accounting Matrix (SAM)

Constructed as part of a project with the University of

Sussex (w/support of IFPRI-ESSP2)

65 production sectors (24 agricultural, 10 agricultural

processing, 20 other industry, 11 services)

Regional SAM based on the “3 Ethiopias”

• Rainfall sufficient, drought prone, pastoralist

• Rainfall sufficient AEZ disaggregated to humid lowlands,

enset-based systems, and other (highland) rainfall

sufficient areas

Poor household groups defined as poorest 40% of rural and

urban households according to HICES 2004/05 per capita

expenditure data

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Agro-ecological Zones (AEZ’s):

“3 Ethiopias” split into 5 AEZs

Source: 2005/06 EDRI Social Accounting Matrix.

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1. Growth and poverty analysis: Household income distribution and poverty

Models identify representative household groups based on location,

income sources, endowments, etc

Households in the model are linked to a survey-based micro-

simulation module in order to measure poverty impacts

Farm typology

Agriculture Non-agriculture

Rural Urban

Micro-simulation poverty module

Economywide modelLabor income Land

& live-

stock

Capital

profits

Other

income

All

sourcesLow

skilled

High

skilled

RuralPoor 24.9 7.2 27.5 34.9 5.5 100.0

Non-poor 14.1 6.1 41.7 34.4 3.7 100.0

Small

urban

Poor 0.7 37.8 0.0 49.1 12.5 100.0

Non-poor 0.2 20.9 0.0 69.3 9.6 100.0

Large

urban

Poor 0.6 41.4 0.0 20.1 38.0 100.0

Non-poor 0.1 15.9 0.0 48.9 35.1 100.0

All households 13.2 10.5 27.7 39.8 8.7 100.0

Household income shares in Ethiopia (%)

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1. Growth and poverty analysis: Summary of key features of the models

Economywide (agriculture and non-agriculture)

Detailed crop and livestock production technologies

Sub-national agricultural production patterns

Farm typologies (e.g., land endowments, technologies)

Domestic and foreign markets and prices

Representative households captures distributional change

Households linked to survey-based micro-simulation module to capture poverty outcomes

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2. Modeling alternative growth scenarios:

Business-as-usual versus accelerated growth

Dynamic models: considers growth paths for next

10 – 15 years

Three growth scenarios commonly considered:

1. Business-as-usual growth path as a baseline

2. Accelerated agricultural growth scenario to meet

CAADP target

3. Accelerated agricultural and nonagricultural growth to

achieve MDG1

Accelerated growth in both agricultural and

nonagricultural sectors are driven by productivity

improvements

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2. Modeling alternative growth scenarios:Accelerated growth by closing yield gaps in Uganda

Yield gaps are drawn from the country, and in most cases

obtained from Ministry of Agriculture

Yields for selected crops in Uganda (current and targeted)

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2. Modeling alternative growth scenarios:Economy-wide impact assessment, Uganda

Average GDP growth rates (%)

Total GDP growth increases from

5.1% to 6.1%

Agricultural GDP growth

increases from 2.7% to 6.0%

(i.e., CAADP target)

Agricultural processing GDP growth

rises from 4.4% to 5.8%

(linkage-effects for the

nonagriculture sector)

Export crops have higher growth

potential

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2. Modeling alternative growth scenarios:

Impact on poverty reduction, Uganda

Faster agricultural growth greatly accelerates poverty reduction…

Base scenario: achieves MDG1 (i.e., half 1991 poverty by 2015)

CAADP: additional 7.6% poverty reduction (2.9 million people by 2015)

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2. Modeling alternative growth scenarios:Market constraints and price effect, Uganda

Some crops face serious

market constraints

Prices fall more if income

elasticity is low and

production increases too

rapidly (e.g. matoke)

Export opportunities are

small for domestic staple

crops even after prices fall

More domestic-focused food

crops are affected most

(e.g. maize, matoke)

Assuming exported crops are not

constrained by world market demand

(e.g. coffee)

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

1.10

2005 07 09 11 13 15

Price

in

de

x (

20

05

=1

)

Coffee

Vege.

Maize

Fish

Potatoes

Matoke

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3. Growth options and investment prioritization

Four criteria for agricultural sub-sector prioritization

1. Growth potential and size-effect: Larger sectors can contribute more to national growth

Some sectors may be small but can grow fast

2. Poverty-effect: Some sectors are better at reducing poverty (stronger

income generation for poorer households)

3. Linkage-effect: Some sectors generate more growth outside of agriculture

4. Price-effect: Some sector face greater demand or market constraints

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3. Growth options and investment prioritization

Results from Uganda

Best growth potential & largest subsectors

Strongest poverty reducing effectsStrongest growth

spillovers to rest of economy

Roots

CerealsForestry

Coffee & export crops

Matoke

Pulses

Livestock

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3. Growth options and investment prioritization:Summary of sector ranking for selected countries

Criteria 1:Growth potential

and size-effect

Criteria 2:Poverty-

effect

Criteria 3:Linkage-

effect

Criteria 4:Price-

effect

KenyaMaize,

export crops

Rice,

export crops

Livestock,

roots

Livestock,

sorghum

MalawiMaize,

tobacco

Vegetables,

pulses

Rice,

roots

Tobacco,

vegetables

MozambiquePlanned biofuels,

maize

Maize,

other cereals

Roots,

livestock

Cashews,

export crops

NigeriaCassava,

riceRice,

millet/sorghumPulses,cereals

Wheat, maize

RwandaPotatoes,livestock

Pulses, maize

-Maize,

rice

TanzaniaMaize,

livestock

Maize,

roots

Livestock,

pulses

Rice,

tobacco

UgandaRoots,

matoke

Vegetables,

roots

Vegetables,

forestryCoffee, fisheries

ZambiaExport crops,

maize

Roots,

maize

Roots,

livestock

Export crops,

livestock

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3. Growth options and investment prioritization:

Completed country-level studies

IFPRI has provided technical

support to COMESA and

ECOWAS to prepare for the

CAADP roundtables

IFPRI has also provided technical

support to three regional

organizations (CORAF,

ASARECA, CARDESA) for

regional level strategic analysis

Detailed country study

Covered by regional studies

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Summary

1. The evaluation of alternative investments depends on:

The output-investment ratio (which is exogenous to the models)

Economy-wide effects of the increase in crop or sub-sector productivity

2. Economy-wide growth and poverty analysis

Models are based on detailed data on crop production patterns, sectoral output,

factor earnings, and household incomes and expenditures captured in Social

Accounting Matrices (SAMs) for individual countries

The CGE models used use conservative estimates of parameters for supply and

demand response to changes in price incentives

3. Modeling future growth scenarios

Base-line simulations are derived from historical growth rates

Alternative investment patterns are modeled as exogenous increases in

productivity

The simulations show the economy-wide impact of these productivity increases on

production, incomes, prices and poverty in consistent economy-wide framework

4. Prioritizing sectors for investment

Various criteria are used for ranking investments in crops and sub-sectors