"Calculating the financing gap for achieving the poverty MDG using the growth-elasticity approach", presentation by Michael Johnson at the USAID, IFPRI Financial Gap Analysis Workshop held at the World Bank, January 7, 2010.

1. IFPRI
Calculating the financing gap for
achieving the poverty MDG using
the growth-elasticity approach
Michael Johnson
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 2/1/2010

2. Overall Motivation – Demand
 Policy makers are asking tough questions
» What will it take in terms of resources to achieve the poverty MDG?
Of this total, what is the financing gap that will need to be filled by
donors?
» What impact will this have in terms of number of beneficiaries
(number of people rising above the poverty line)? What share can be
attributed to donor interventions?
» What are the critical drivers behind this change? What type of
investments will contribute to such results – impact on growth and
poverty to achieve MDG
» How do we monitor change over time to determine whether
investments are having their desirable impact?
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IFPRI

3. The Challenge from USAID
1. To estimate the cost and financing gap among a select
group of countries from SSA, Asia and Latin America for
achieving the poverty MDG
2. To determine the number of beneficiaries or people who
rise above the poverty rate if the MDG target is met
among these countries – by country, region and total
3. To calculate the per capita cost in closing the financing gap
by country – given total finance gap and total number of
beneficiaries
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IFPRI

4. Methodology Adopted: The Elasticity Approach
 We use growth-to-poverty and agricultural expenditure-to-growth
elasticities to estimate the total cost for achieving MDG1 through
agriculture
» The growth-to-poverty elasticity measures a percent change in the reduction of
poverty due to a 1% change in per capita GDP
» The agricultural expenditure-to-growth elasticity measures a percent change in
agricultural GDP growth due to a 1% change in total agricultural expenditures
 Given a wide range and number of countries, elasticities are drawn
from the literature and those that have been estimated at country
or regional level.
 Combining these elasticities with past performance in growth and
agricultural spending trends, we compute the required growth and
future financing needs based on the rate at which poverty rates
need to decline in order to achieve the MDG poverty goal by 2015.
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IFPRI

5. The Steps to Calculating the Financing Gap
1. First, we determine the annual rate of reduction in poverty required
to meet the poverty MDG target by 2015 and against current rates
2. Then from this, the required annual agricultural growth rate
required to achieve this annual rate of poverty reduction is
calculated using a per capita GDP growth-to-poverty elasticity and a
growth multiplier effect – to capture economy-wide effects of
agricultural growth on poverty
3. The required agricultural growth rate is then used to calculate the
required growth in total agricultural expenditures using an
expenditure-to-growth elasticity (which measures a percent change
in agricultural GDP growth due to a 1% change in total agricultural
expenditures
4. Finally, the financing gap is then calculated using simple accounting
– as the difference between required and current government
expenditures
5.
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IFPRI

6. Determining the annual agricultural growth
rate required to meet the poverty MDG
 We chose to pay attention to the overall economic growth effects
on poverty reduction stemming from a stimulus in the agricultural
sector
 This allows us to maintain an economy wide perspective in
calculating the poverty reducing effects of an agriculture-led growth
strategy, a situation where the agricultural sector serves as the key
source of overall GDP growth.
 The required agricultural growth rate is ultimately derived from the
required total GDP growth rate, given the sector’s share of total GDP
and any past evidence of growth multiplier effects which occur
through linkages with other sectors
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IFPRI

7. Determining the Financing Gap
 The annual growth rate of agricultural expenditures needed to
achieve the required annual agricultural growth rate is
determined using the expenditure to growth elasticity – and
represent a total financing cost.
 From this, the required annualized expenditures (or financing
costs) to 2015 are determined using current baseline levels (in
constant 2007 US$ million).
 The Finance Gap is then computed based on the difference
between a projected business-as-usual growth in government
expenditures (as a constant share of current Ag GDP growth
trends) and the required growth of total expenditures
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IFPRI

8. Computing the number of beneficiaries and
cost per beneficiary
 The number of beneficiaries from closing the Finance Gap is
computed for each country as the difference between:
» The total number of poor by 2015 under a current trend line of fixed
annual changes in the poverty rate (or business-as-usual), minus
» The total number of poor people by 2015 if the MDG target is met
 The total number of beneficiaries for each country is the difference
between:
» The total number of poor by 2015 under fixed current poverty rates,
minus
» The total number of poor by 2015 under a current trend line of fixed
annual changes in the poverty rate (or business-as-usual)
 The cost per beneficiary for each country is derived by dividing the
number of total beneficiaries (above) and total estimated costs as
defined earlier
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IFPRI

9. Summary of key coefficients, parameters, and data
 Key estimated coefficients (from research and literature)
» The growth-to-poverty elasticity
» The agricultural expenditure-to-growth elasticity
 Parameters (from research)
» The growth multiplier effect of agricultural growth on total GDP growth accounts for the indirect
effect of agricultural growth on non-agricultural growth and vice versa (usually calculated via a SAM
and based on in-country surveys)
» The growth multiplier is measured as the ratio of increases in GDP over increases in agricultural GDP,
both in real value terms. For example, if the multiplier is 1.2, it indicate that one unit (e.g. a million
$US in constant prices) increase in agricultural GDP results in 1.2 unit (1.2 million $US) increase in
GDP
 Baseline information (various country and international data sources)
» Current average annual growth rates of GDP and Agriculture GDP
» The size of the agriculture sector in a country's GDP (as a percent)
» Projected annual population growth rates and levels by 2015
» National poverty rates from household surveys (anywhere between 1990 and 2008)
» Most recent poverty rates and future trajectory scenarios (one fixed at the current rate, another
under a current trend line, and another on course to achieve the MDG1 target)
» Current total agriculture expenditures in constant 2007 US$
» 2/1/2010 – Page 9
IFPRI

10. GDP Growth-to-Poverty elasticity :
By how much would poverty rates decline from a 1%
increase in GDP?
Poverty Reduction Effect of Agriculture vs. Non-agriculture Led
Growth Strategies
Ethiopia Ghana Rwanda Uganda Zambia
Agriculture-led GDP
-1.7 -1.8 -1.4 -1.6 -0.6
growth
Non Agriculture-led
-0.7 -1.3 -0.8 -1.1 -0.4
GDP growth
Source: Diao et al 2007
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IFPRI

11. Agriculture Poverty reduction to
growth GDP growth Ag GDP to Ag Exp
Elasticities and Country multiplier* elasticity** growth elasticity***,6
multipliers SSA 1.20 -1.20 0.308
country Congo, DR
Ethiopia1
1.20
1.27
-1.20
-1.27
0.308
0.308
Ghana1 1.27 -1.41 0.308
Kenya2 1.15 -0.99 0.308
Liberia 1.27 -1.10 0.308
Malawi3 1.15 -1.20 0.308
Mali 1.27 -1.30 0.308
Mozambique4 1.17 -1.10 0.308
Niger 1.20 -1.20 0.308
Nigeria5 1.27 -1.16 0.308
Rwanda1 1.27 -1.41 0.308
Senegal 1.15 -1.10 0.308
Tanzania 1.24 -1.10 0.308
Uganda1 1.27 -1.58 0.308
Zambia1 1.17 -0.87 0.308
Bangladesh 1.20 -1.10 0.220
Cambodia 1.20 -1.10 0.220
Guatemala 1.10 -0.95 0.180
Haiti 1.10 -0.95 0.180
Honduras 1.10 -0.95 0.180
India 1.30 -1.10 0.220
Nepal 1.20 -1.10 0.220
Nicaragua 1.10 -0.95 0.180
Sri Lanka 1.30 -1.20 0.220
Tajikistan 1.20 -1.20 0.200

12. GDP Ag GDP Non-Ag GDP
Country
Current growth SSA 6.2 5.5 6.0
rates Congo, DR 5.1 3.2 7.0
Ethiopia 4.7 4.7 4.9
Ghana 4.9 4.8 4.9
Kenya 6.0 3.7 5.6
Liberia 4.9 4.9 5.0
Malawi 3.2 2.8 3.5
Mali 6.0 5.3 6.7
Mozambique 5.8 4.8 6.0
Niger 6.0 6.4 3.1
Nigeria 6.5 5.7 6.7
Rwanda 5.4 4.9 6.2
Senegal 4.8 2.0 5.8
Tanzania 6.3 5.2 6.6
Uganda 5.1 4.5 6.2
Zambia 5.7 2.0 6.0
Bangladesh 5.5 4.5 6.0
Cambodia 4.2 2.7 5.5
Guatemala 5.2 2.0 5.8
Haiti 2.6 1.8 3.0
Honduras 6.2 1.8 6.5
India 8.9 2.9 13.0
Nepal 2.8 1.2 3.1
Nicaragua 4.8 4.2 5.0
Sri Lanka 6.7 5.0 7.1
Tajikistan 4.6 5.4 4.3

13. Baseline Most Recent
Country (1990-1996) (1998-2006) Survey Year
National Poverty SSA 44.6 42.9 2004
Rates Congo, DR 74.0 83.6 2004
Ethiopia 51.1 44.2 2000
Ghana 51.7 28.5 2006
Kenya 48.8 46.9 2005
Liberia 74.0 83.7 2006
Malawi 54.1 51.0 2006
Mali 68.0 60.7 2003
Mozambique 69.4 54.4 2004
Niger 72.8 65.9 2005
Nigeria 49.2 54.4 2004
Rwanda 51.2 57.0 2006
Senegal 54.1 44.2 2001
Tanzania 38.6 35.7 2001
Uganda 56.0 31.1 2005
Zambia 69.7 67.9 2004
Bangladesh 66.8 49.6 2005
Cambodia 47.0 35.0 2004
Guatemala 15.7 11.7 2006
Haiti 68.0 54.9 2001
Honduras 69.0 50.7 2004
India 36.0 28.6 2000
Nepal 41.8 30.9 2005
Nicaragua 32.5 15.8 2005
Sri Lanka 20.0 22.7 2002
Tajikistan 44.5 36.3 2003

14. Required growth rates to meet MDG2
By 2015 By 2020
Required Country GDP Ag GDP GDP Ag GDP
growth rates to SSA 9.5 13.9 6.5 6.2
meet MDG1 Congo, DR
Ethiopia
11.5
8.0
14.5
10.1
7.7
-
7.9
-
Ghana 2.2 4.8 - -
Kenya 10.1 16.8 6.9 6.5
Liberia 12.4 14.2 8.3 9.1
Malawi 6.7 11.6 - -
Mali 8.8 11.5 - -
Mozambique 6.5 7.6 - -
Niger 8.3 11.3 - -
Nigeria 7.3 7.7 - -
Rwanda 8.5 10.7 - -
Senegal 5.7 6.7 - -
Tanzania 9.4 10.8 - -
Uganda 4.1 4.5 - -
Zambia 10.9 23.4 7.2 8.0
Bangladesh 5.7 5.1 - -
Cambodia 6.6 9.4 - -
Guatemala 7.0 9.5 - -
Haiti 6.7 15.2 4.6 8.4
Honduras 7.3 8.9 - -
India 4.0 2.9 - -
Nepal 5.8 8.4 - -
Nicaragua 1.3 4.2 - -
Sri Lanka 6.9 6.1 - -
Tajikistan 5.6 8.8 - -

15. Required growth in Ag As share of Ag GDP
Expenditures, annual Total Annualized Ag Exp By By
Country (%) Needed to meet MDG1 2015 2020
Computing (% (US$ million) (%)
required Ag SSA 20.1 13,978.3 13.1 17.7
expenditures Congo, DR1 25.5 981.4 10.5 22.5
(Financing Ethiopia
Ghana
32.7
15.6
890.0
441.7
12.2
8.3
-
-
cost) Kenya 21.2 1,259.6 10.9 20.8
Liberia1 29.7 129.8 10.6 25.1
Malawi 37.5 287.9 22.4 -
Mali 37.3 704.1 26.5 -
Mozambique 24.8 248.2 12.1 -
Niger 36.7 342.7 17.5 -
Nigeria 24.9 2,813.1 9.6 -
Rwanda 34.6 185.7 14.1 -
Senegal 21.6 218.0 15.2 -
Tanzania 35.0 853.7 12.3 -
Uganda 14.6 185.7 6.1 -
Zambia 26.1 654.0 11.6 25.2
Bangladesh 23.4 1,148.5 10.1 -
Cambodia1 42.7 216.0 9.4 -
Guatemala 52.8 857.6 11.6 -
Haiti1 46.5 542.7 10.3 46.8
Honduras1 49.6 248.0 23.2 -
India2 10.7 15,586 10.4 -
Nepal 38.1 495.1 16.4 -
Nicaragua1 23.5 168.1 20.5 -
Sri Lanka 27.5 866.9 22.5 -

16. Total Population Number of Poor in 2015
If poverty rates If decline at
Computing If MDG goal is
on track 1
unchanged
(Baseline)
current rates
(BAU)
number of Country 2008 2015 (A) (B) (C)
SSA 668.3 786.8 256.7 407.5 379.6
beneficiaries
Congo, DR 63.3 73.4 38.1 61.3 61.3
Ethiopia 81.1 96.4 24.6 42.6 40.2
Ghana 24.0 28.0 7.2 8.0 7.3
Kenya 38.2 44.6 14.6 20.9 20.1
Liberia 3.7 4.4 2.3 3.6 3.6
Malawi 14.2 16.5 5.4 8.4 7.9
Mali 12.7 15.7 5.3 9.5 9.1
Mozambique 22.0 26.2 9.1 14.2 12.4
Niger 14.5 17.5 6.8 11.5 11.0
Nigeria 151.2 176.4 57.8 95.9 87.4
Rwanda 9.9 11.7 3.5 6.7 6.5
Senegal 12.7 14.9 4.0 6.6 5.2
Tanzania 41.2 48.0 9.3 17.1 16.2
Uganda 32.1 40.9 11.4 12.7 12.1
Zambia 12.1 13.6 6.3 9.2 8.8
Bangladesh 164.3 182.4 60.9 90.5 82.5
Cambodia 14.9 16.5 3.9 5.8 5.7
Guatemala 13.9 16.0 1.3 1.9 1.7
Haiti 9.9 10.9 4.3 6.0 5.2
Honduras 7.4 8.3 2.9 4.2 4.1
India 1,140 1,255 226 359.1 276
Nepal 29.3 33.0 6.9 10.2 9.2
Nicaragua 5.7 6.2 0.9 1.0 0.9
Sri Lanka 20.6 21.9 2.7 5.0 4.5

17. Agriculture Financing Gaps to Meet MDG 1
Under current agricultural spending Under CAADP-level agricultural
commitments spending (10% of total spending)
US$, constant 2007 (millions) US$, constant 2007 (millions)
IFPRI Source: Johnson et al, 2009

18. Agriculture Spending and Poverty
Reduction
Number of people lifted out of poverty by 2015, under current
trends vs. after closing financing gap (millions)
Ghana
Uganda
Liberia Under Current
Senegal Scenario
Zambia
Malawi After Closing
Rwanda Financing Gap
Mali
Niger
Mozambique
Kenya
Tanzania
Ethiopia
Congo, DR
Nigeria
0 5 10 15 20 25 30 35 40
IFPRI Source: Johnson et al, 2009

19. Thank You
2/1/2010 – Page 19
IFPRI