"Prioritizing agricultural subsector growth and investments at the country level: Methodology to assess economy-wide impacts", presentation by James Thurlow and Paul Dorosh at the USAID, IFPRI Financial Gap Analysis Workshop held at the World Bank, January 7, 2010.

1. IFPRI
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
INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE

2. 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?
IFPRI

3. 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
IFPRI

4. 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)
IFPRI

5. 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
IFPRI

6. 1. Growth and poverty analysis
Economywide (“CGE”) modeling framework
Economic production Incomes and poverty
Wages, rents,
profits
Agriculture Factor markets Urban/Rural
Industry
Production
Commodity markets Consumption
Farm/
Services Foreign trade Nonfarm
Taxes Foreign markets/
Spending countries
and market
policies Foreign aid
Taxes and
Public sector/ social policies
government
Public investment
and macro
Productivity/technology policies
Foreign Private
investment investment
Human/physical capital
IFPRI

7. 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)
Sector contributions to national gross domestic product (GDP) (%)
Zambia Kenya Mozam- Tanzania Malawi Ethiopia
bique
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 44.9
Cereals 5.5 4.4 5.3 8.3 11.9 13.5
Exports 3.5 4.6 1.1 2.8 10.2 4.5
Livestock 3.1 5.4 1.7 5.5 2.5 12.9
Manufacturing 13.0 11.0 13.7 8.8 10.8 5.2
Agro-processing 11.5 3.1 2.0 6.7 6.3 2.4
Other non-mining industry 10.4 7.1 9.5 10.4 5.7 1.9
IFPRI

8. 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)
Sector contributions to trade in Tanzania (%)
Share (%) Intensity (%)
Export Import Export Import
Whole economy 100.0 100.0 9.4 22.0
Agriculture 34.9 6.1 13.2 7.3
Cereals 0.0 5.5 0.0 18.2
Exports 21.5 0.3 63.5 7.1
Livestock 1.6 0.0 3.6 0.0
Manufacturing 12.8 87.9 8.3 61.4
Agro-processing 2.1 10.0 2.0 20.8
Other non-mining industry 0.0 0.0 0.0 0.0
“Intensity” is the share of exports in output, and share of imports in demand
IFPRI

9. 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
Land allocated to crops by region in Malawi (%)
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
IFPRI

10. 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)
Land allocated to crops by scale of production in Malawi (%)
Malawi Large Medium Small Urban
(>3ha) (0.75-3ha) (<0.75ha)
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
IFPRI

11. 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
IFPRI

12. Agro-ecological Zones (AEZ’s):
“3 Ethiopias” split into 5 AEZs
Source: 2005/06 EDRI Social Accounting Matrix.
IFPRI

13. 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
Household income shares in Ethiopia (%)
Labor income Land Capital Other All Economywide model
Low High & live- profits income sources
skilled skilled stock Agriculture Non-agriculture
Poor 24.9 7.2 27.5 34.9 5.5 100.0
Rural
Non-poor 14.1 6.1 41.7 34.4 3.7 100.0 Rural Urban
Small Poor 0.7 37.8 0.0 49.1 12.5 100.0
urban Non-poor 0.2 20.9 0.0 69.3 9.6 100.0
Large Poor 0.6 41.4 0.0 20.1 38.0 100.0
urban 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 Micro-simulation poverty module
IFPRI

14. 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
IFPRI

15. 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
IFPRI

16. 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)
IFPRI

17. 2. Modeling alternative growth scenarios:
Economy-wide impact assessment, Uganda
Total GDP growth increases from
5.1% to 6.1%
Agricultural GDP growth
increases from 2.7% to 6.0%
(i.e., CAADP target)
Export crops have higher growth
potential
Agricultural processing GDP growth
rises from 4.4% to 5.8%
(linkage-effects for the
nonagriculture sector)
Average GDP growth rates (%)
IFPRI

18. 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)
IFPRI

19. 2. Modeling alternative growth scenarios:
Market constraints and price effect, Uganda
1.10
Some crops face serious
1.05 Coffee
market constraints
1.00
Price index (2005=1)
Prices fall more if income 0.95 Vege.
elasticity is low and 0.90 Fish
production increases too 0.85
rapidly (e.g. matoke) Potatoes
0.80 Maize
Export opportunities are 0.75
small for domestic staple 0.70 Matoke
crops even after prices fall 0.65
2005 07 09 11 13 15
Assuming exported crops are not More domestic-focused food
constrained by world market demand crops are affected most
(e.g. coffee) (e.g. maize, matoke)
IFPRI

20. 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
IFPRI

21. 3. Growth options and investment prioritization
Results from Uganda
Strongest poverty
Strongest growth reducing effects
spillovers to rest
of economy Forestry
Cereals Livestock
Roots
Coffee & export crops
Matoke
Pulses
Best growth potential &
largest subsectors
IFPRI

22. 3. Growth options and investment prioritization:
Summary of sector ranking for selected countries
Criteria 1: Criteria 2: Criteria 3: Criteria 4:
Growth potential Poverty- Linkage- Price-
and size-effect effect effect effect
Maize, Rice, Livestock, Livestock,
Kenya
export crops export crops roots sorghum
Maize, Vegetables, Rice, Tobacco,
Malawi
tobacco pulses roots vegetables
Planned biofuels, Maize, Roots, Cashews,
Mozambique
maize other cereals livestock export crops
Cassava, Rice, Pulses, Wheat,
Nigeria
rice millet/sorghum cereals maize
Potatoes, Pulses, Maize,
Rwanda -
livestock maize rice
Maize, Maize, Livestock, Rice,
Tanzania
livestock roots pulses tobacco
Roots, Vegetables, Vegetables,
Uganda Coffee, fisheries
matoke roots forestry
Export crops, Roots, Roots, Export crops,
Zambia
maize maize livestock livestock
IFPRI

23. 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
IFPRI

24. 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
IFPRI