"Assessing Economy-wide Returns of Agricultural Public Investment in Rwanda", presentation by Xinshen Diao at the USAID, IFPRI Financial Gap Analysis Workshop held at the World Bank, January 7, 2010.

1. IFPRI
Assessing Economy-wide Returns of
Agricultural Public Investment in
Rwanda
Xinshen Diao
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 6% agricultural growth of CAADP goal enough
to reach national poverty targets? If not what is the
required agricultural growth rate?
 How can different sectors (sub-sectors) contribute
to accelerating growth and poverty reduction?
 What is the level of agricultural investment needed
to accelerate growth in these sectors?
 What are potential returns to agricultural
investment?
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3. Outline
 Challenges in assessing agricultural investment
returns
 What is the simulation approach using an
economy-wide model
 Linking public investment with growth and
poverty reduction
 Assessing economy-wide impact of agricultural
public investment
IFPRI

4. What Rwanda’s Ministry of Agriculture has done in costing
assessment?
 Developed a costing tool to assess national needs for achieving agriculture-
related targets set in EDPRS
 Put together investment plan with detail program information:
e.g. “Intensification and development of sustainable production systems” is one
of the four broad programs; (a) sustainable management of natural resources
and soil conservation, (b) marshland development, (c) irrigation development
are three of the six subprograms of this program, while terracing, water tanks
and trenches are specific interventions (under “soil conservation
subprogram”)
 Set specific targets for individual interventions; e.g. x hectares of radical
terraces in which year between 2008 and 2012
 Provided unit cost for each intervention; e.g. x RWF per ha terracing or y
RWF per unit of small scale dam development
 Added up total cost (annual and five years) for achieving the planned
programs

5. Summary of total cost, adjusted from 5 years (2008-2012) to 9 years for
modeling purpose
Fertilizer+ Annual
9 years Fixed seed total
Agricultural spending used in the model, million RWF total investment Recurrent subsidy average
Crop directly related 415,077 182,956 45,278 186,842 46,120
Forestry 8,641 6,742 1,899 960
Livestock 203,253 154,259 48,994 22,584
R&D, extension 26,963 26,963 2,996
Rural finance 13,662 13,662 1,518
Other investment, horticulture 122,236 90,660 31,576 13,582
Other investment, traditional export 22,840 16,940 5,900 2,538
Rural road 21,965 21,965 2,441
Ag institution 16,230 16,230 1,803
Other investment 11,265 11,263 1,252
Total 862,132 484,787 190,502 186,842 95,792
Current annual total agr. spending in million Rwf (2007) 13,517 6,434 19,951
share in total government budget 1.4 7.4 3.9
Proposed agr. spending, in EDPRS, 2008-2012 (5 years), million Rwf
242,000 158,000 84,000 48,400
share in total government budget 7.0 11.5 4.1
Increase from the current annual level (times) 1.4
Amount of ag spending, if ag = 10% of total budget, annual 69,143
Compared with the number used in model, without fertilizer subsidy (model/10% budget) 1.09
Compared with the number used in model, with fertilizer subsidy (model/10% budget) 1.39
Source: Authors’ calculation based on “Total Cost of EDPRS Agriculture Sector.” MINAGRI (2008)

6. What are the requirements of the Rwandan
government?
 How to link the specific targets (e.g. terracing or
irrigation projects) to growth (e.g. improvement in
rice yield due to irrigation)
 How to link program intervention to broad growth
targets (e.g., whether it is reachable for 6% of
CAADP growth target with such investment plan)
 How to link agricultural investment to MDG1
 How to measure the impact of agricultural
investment
 With financial constraints, how to prioritize the
allocation
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7. Challenges in assessing agricultural public
investment
 A simple cost-benefit assessment is commonly used
 However, project-based assessment may underestimate the
impact, given public good provision generates positive
externalities often going beyond individual projects and
agricultural growth has strong linkage effect
 Ex post analysis is necessary, but it is often impossible to do
such analysis in many African countries such as Rwanda, not
only because data limitation or poor data quality, but also
because that history is unlikely to tell future in these countries
 Therefore, we develop a simulation approach to assess
economy-wide impact of investment
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8. What is the simulation approach?
 Develop an economy-wide (e.g. CGE) model for the
country first (already introduced by Paul)
 Conduct growth option analysis using the model
(already covered by Paul)
 Decompose agricultural public resource allocation
 Link growth at sub-sector level with public
investment allocation
 Assess economy-wide impact according to the
allocation
 Measure the economy-wide cost-benefit ratio
IFPRI

9. Decompose spending to agricultural subsector: what is the
current situation?
Share of current land allocation by types of interventions
Modern Terrace & Marshland
(irri & fert fert & Terrace & fert & Marshland &
& seed) seed &seed Terrace seed seed Marshland Seed Traditional
Wheat 0.2 0.1 6.5 0.2 0.4 92.7
Maize 0.2 0.4 6.0 0.2 0.3 92.9
Paddy rice 15.0 4.0 22.7 18.4 40.0
Sorghum 0.1 0.2 6.4 0.1 0.3 93.0
Irish potatoes 1.0 1.9 0.4 6.5 90.3
Sweet potatoes 0.1 0.0 3.1 1.7 95.1
Cassava 0.1 0.1 3.0 3.3 93.5
Other roots 0.1 0.0 3.1 1.7 95.1
Pulses 0.1 0.2 0.9 0.7 98.1
Vegetables 8.4 91.6
Bananas 0.3 0.1 2.8 0.3 96.5
Fruits 5.6 94.4
Oil seed 0.1 0.6 2.8 0.1 96.5
Coffee 29.6 70.4
Green tea 35.3 64.7
Other export crops 8.0 1.4 18.8 38.5 33.3
Total 1.5 0.3 2.6 1.2 0.0 0.3 0.3 0.1 93.7
Source: Author’s calculation based on various information
IFPRI

10. Decompose spending to agricultural subsector:
Share of land allocation by types of interventions – Model results for 2015
Modern (irri Terrace & Marshland
& fert & fert & Terrace & fert & Marshland
seed) seed & seed Terrace seed & seed Marshland Traditional
Wheat 4.0 2.5 8.5 7.0 78.0
Maize 3.2 3.0 11.2 4.9 77.7
Paddy rice 15.0 23.0 30.0 17.0 15.0
Sorghum 0.5 0.8 12.6 3.3 82.8
Irish potatoes 2.2 3.5 3.8 13.6 76.9
Sweet potatoes 0.7 0.5 4.6 6.4 87.8
Cassava 0.8 1.4 4.3 9.1 84.5
Other roots 0.3 0.5 5.1 6.0 88.2
Pulses 0.2 0.6 1.3 4.4 93.4
Vegetables 20.2 79.8
Bananas 0.6 2.5 7.3 23.6 66.0
Fruits 12.4 87.6
Oil seed 1.5 3.1 6.0 12.0 77.4
Coffee 59.3 40.7
Green tea 70.6 29.4
Other export crops 9.6 18.6 40.0 29.2 2.6
Total 4.4 3.0 5.1 9.5 0.5 0.7 0.5 76.3
Source: Author’s calculation based on “Total Cost of EDPRS Agriculture Sector.” MINAGRI (2008)
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11. Achievable yield (mt/ha) under different types of investment
Modern Average Targeted
(irri & Terrace Marshland yield by average
fert & & fert Terrace & fert & Marshland Current 2015 in yield by
seed) & seed &seed Terrace seed & seed Marshland Traditional average base-run 2015
Wheat 3.0 2.8 1.4 2.3 1.2 0.8 1.2 1.6
Maize 3.5 3.1 1.5 2.5 1.2 0.8 1.0 1.5
Paddy rice 6.4 5.8 5.5 5.8 6.1 6.1 5.5 3.7 4.9 4.7
Sorghum 3.4 2.7 1.7 2.4 1.5 1.1 1.5 1.7
Irish potatoes 27.2 24.9 15.5 20.2 12.6 9.1 11.9 14.7
Sweet
potatoes 15.0 16.8 11.2 11.5 7.7 5.5 6.9 7.8
Cassava 27.3 24.7 11.2 18.8 8.6 6.2 8.0 10.5
Other roots 24.5 17.3 9.6 12.3 6.8 4.9 6.0 6.8
Pulses 2.7 2.4 1.2 2.1 1.1 0.8 1.0 1.0
Vegetables 29.5 19.6 14.0 19.6 14.0 9.4 7.3 9.4
Bananas 17.9 15.7 10.5 14.9 9.9 7.2 10.0 12.9
Fruits 28.6 19.1 13.6 19.1 13.6 9.7 14.3 17.1
Oil seed 2.7 1.8 1.1 1.4 0.8 0.6 0.8 1.1
Coffee 1.0 0.8 0.7 0.8 0.7 0.7 1.1 1.1
Green tea 1.7 1.4 1.2 1.4 1.2 1.1 1.7 1.7
O. export
crops 45.8 38.2 27.3 38.2 32.7 23.8 32.7 27.3 17.6 26.5 35.0
Source: Drawn from broad literature review
IFPRI

12. Agricultural subsector annual growth rate as
investment outcomes – the model results
Base-run Simulation with investment
Wheat 4.9 8.5
Maize 3.9 8.2
Paddy rice 3.9 9.7
Sorghum 3.1 4.2
Irish potatoes 3.6 6.5
Sweet potatoes 2.1 2.4
Cassava 3.2 5.2
Other roots 3.9 5.7
Pulses 3.4 4.6
Vegetables 4.4 7.5
Bananas 3.7 6.6
Fruits 3.5 5.4
Oil seed 3.7 6.6
Coffee 6.3 9.8
Green tea 6.1 10.5
Other export crops 4.5 10.1
Source: Rwanda DCGE model results
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13. Economy-wide impact of agricultural investment – the
model result
Base-run Simulation with investment
GDP 4.8 6.0
AgGDP 3.8 6.5
Grains 3.6 7.0
Root crops 3.1 5.1
Other food 4.1 6.5
Cash and exportables 4.7 7.9
Livestock 5.5 12.6
Fish and forestry 4.0 6.9
Industry 5.1 5.1
Processing manufacturing 6.2 7.9
Coffee processing 8.3 11.8
Tea processing 6.7 10.6
Services 5.7 5.8
Trade 4.4 6.2
Transport 7.0 6.5
Communication 8.0 6.4
Source: Rwanda DCGE model results
IFPRI

14. Poverty reduction impact of agricultural
investment – the model result
2015
Current Simulation with
level (2006) Base-run investment
National 57.6 46.7 37.2
Urban 28.8 27.9 19.9
Rural 63.4 50.4 40.7
Note: 1999’s national poverty rate = 60%
Source: Rwanda DCGE model results
IFPRI

15. Economy-wide cost-benefit assessment –
the model results
GDP/investment AgGDP/investment
Maize 7.02 6.59
Paddy rice 1.41 1.22
Wheat 5.34 5.15
Cassava 5.46 4.61
Irish potatoes 5.88 5.66
Sweet potatoes 2.53 2.22
Pulses 9.09 8.21
Bananas 5.35 4.94
Oil seed 5.89 4.73
Coffee 1.01 1.74
Green tea 1.95 2.52
Other cash and export crops 1.08 1.07
Poultry 10.54 10.09
Other livestock 1.81 1.74
Fishing 12.50 12.35
Grains 2.75 2.73
Root crops 5.03 4.65
Cash and export crops 1.02 1.24
Livestock 2.02 1.90
Staple crops and livestock 3.84 3.63
Agriculture total 3.19 3.11
Source: Rwanda DCGE model results
IFPRI

16. Conclusions
 Project-based cost-benefit analysis may under-estimate impact of
agricultural investment because
» Provision of public goods has strong and positive externalities
» Agricultural growth has strong linkage effects
 Prioritization of public investment is challenged by lack of data and
poor quality of data. Moreover, in many African countries, ex post
analysis using historical data is unlikely to point in the right direction
for the future
 Model simulations based on detailed data of the structure of Rwanda’s
economy that capture economy-wide effects show that returns to
agricultural investment in Rwanda are high:
$1 investment $3.19 increase in GDP
 Investing in staples has the highest economy-wide returns:
$1 investment $3.84 increase in GDP
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