Calculating the financing gap for achieving the poverty MDG using the growth-elasticity approach_2010
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Calculating the financing gap for achieving the poverty MDG using the growth-elasticity approach_2010

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"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......

"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.

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  • 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, 2010INTERNATIONAL 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? 2/1/2010 – Page 2 IFPRI
  • 3. The Challenge from USAID1. To estimate the cost and financing gap among a select group of countries from SSA, Asia and Latin America for achieving the poverty MDG2. 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 total3. To calculate the per capita cost in closing the financing gap by country – given total finance gap and total number of beneficiaries 2/1/2010 – Page 3 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. 2/1/2010 – Page 4 IFPRI
  • 5. The Steps to Calculating the Financing Gap1. First, we determine the annual rate of reduction in poverty required to meet the poverty MDG target by 2015 and against current rates2. 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 poverty3. 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 expenditures4. Finally, the financing gap is then calculated using simple accounting – as the difference between required and current government expenditures5. 2/1/2010 – Page 5 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 2/1/2010 – Page 6 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 2/1/2010 – Page 7 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 2/1/2010 – Page 8 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 $US) increase in GDP Baseline information (various country and international data sources) » Current average annual growth rates of GDP and Agriculture GDP » The size of the agriculture sector in a countrys GDP (as a percent) » Projected annual population growth rates and levels by 2015 » National poverty rates from household surveys (anywhere between 1990 and 2008) » Most recent poverty rates and future trajectory scenarios (one fixed at the current rate, another under a current trend line, and another on course to achieve the MDG1 target) » Current total agriculture expenditures in constant 2007 US$ » 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 ZambiaAgriculture-led GDP -1.7 -1.8 -1.4 -1.6 -0.6growthNon Agriculture-led -0.7 -1.3 -0.8 -1.1 -0.4GDP growth Source: Diao et al 2007 2/1/2010 – Page 10 IFPRI
  • 11. Agriculture Poverty reduction to growth GDP growth Ag GDP to Ag ExpElasticities and Country multiplier* elasticity** growth elasticity***,6multipliers SSA 1.20 -1.20 0.308country 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 CountryCurrent growth SSA 6.2 5.5 6.0rates 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 YearNational Poverty SSA 44.6 42.9 2004Rates 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 2020Required Country GDP Ag GDP GDP Ag GDPgrowth rates to SSA 9.5 13.9 6.5 6.2meet 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 2020Computing (% (US$ million) (%)required Ag SSA 20.1 13,978.3 13.1 17.7expenditures 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 atComputing If MDG goal is on track 1 unchanged (Baseline) current rates (BAU)number of Country 2008 2015 (A) (B) (C) SSA 668.3 786.8 256.7 407.5 379.6beneficiaries 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 PovertyReduction 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 NigerMozambique 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 19IFPRI