options for reducing regional disparities in growth and poverty reduction in ghana
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Options for Reducing Regional Disparities in Growth and Poverty Reduction in Ghana. Ramatu M. Al-Hassan, University of Ghana Xinshen Diao, IFPRI Beijing, China, 24 May, 2006. Outline of presentation. Regional diversity and poverty distribution Trends in poverty in the 1990s - PowerPoint PPT PresentationTRANSCRIPT
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Options for Reducing Regional Disparities in
Growth and Poverty Reduction in Ghana
Ramatu M. Al-Hassan, University of GhanaXinshen Diao, IFPRI
Beijing, China, 24 May, 2006
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Outline of presentation
Regional diversity and poverty distribution
Trends in poverty in the 1990s Sources of poverty reduction and growth Simulation results of Economy-wide
Multimarket Model Implications and conclusions
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Regional Diversity Agro-ecological diversity Rainfall distribution History Education Infrastructure distribution
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Regional Poverty Distribution
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Poverty Trends in the 1990sGroup
Year Pop. Share
P0
% change in P0
P1
% change in P1
Forest 1991/1992 40.6 0.519 0.183
1998/1999 43.3 0.326 -37.19 0.092 -49.73
Savannah 1991/1992 28.4 0.664 0.273
1998/1999 25.4 0.649 -2.26 0.284 4.03
Export farmers 1991/1992 6.3 0.64 0.245
1998/1999 7 0.387 -39.53 0.103 -57.96
Food crop farmers 1991/1992 43.6 0.681 0.268
1998/1999 38.6 0.594 -12.78 0.24 -10.45
National 1991/19921998/1999
100100
0.5170.395
-23.60
0.1850.139
-24.86
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Sources of poverty reduction in the 1990s
Growth from Structural Adjustment Programme (Mid 1980s)
Period GDP Growth 1961 – 1983 0.9% 1983 – 2003 4.8% (2.0% per capita)
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Factors underlying growth
Trade – 39% of GDP growth over 1983-2003 due to export growth
Public spending financed largely through aid
Growth of Services sector (trading, transportation)
Increased receipts of remittances
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Factors underlying growth (2)
Agriculture’s share in total exports – 25% Cocoa’s share – 70% Non-traditional agricultural exports
growth – 20% Northern Ghana does not produce many
of these fast growing export commodities Only yam as a non-traditional agric
export
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Methodology
Economy-wide multimarket (EMM) model developed for Ghana (at IFPRI).
Identification of crops based on those with largest effect on income (Using GLSS 4 data)
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Poverty will be halved by 2015
Projected poverty rate in the base run
8
12
16
20
24
28
32
36
40
44
48
52
56
60
64
1992 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
National Rural Urban
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But, regional inequality increases
Regions 1999 2003 2015 % decline by
2015 from 1999 ACCRA 5.2 3.8 1.6 -68.4 ASHANTI 27.7 23.8 14.1 -49.1 BRONG_AHAFO 35.8 27.4 12.0 -66.6 CENTRAL 48.4 40.4 20.1 -58.4 EASTERN 43.7 40.6 32.5 -25.6 NORTHERN 69.2 65.7 57.0 -17.6 UPPER_EAST 88.2 86.3 70.3 -20.3 UPPER_WEST 83.9 75.8 70.5 -16.0 VOLTA 37.7 30.9 15.8 -58.1 WESTERN 27.3 23.4 10.3 -62.0 National, rural 49.5 44.2 30.9 -37.5 National, urban 19.4 16.0 9.1 -53.2 National, total 39.5 34.8 23.7 -40.0
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Agriculture-led growth is more pro-poor
National poverty rate(with GDP growth rate of 5.7%)
17
19
21
23
25
27
29
31
33
35
2003 2005 2007 2009 2011 2013 2015
Ag-led grow th Nonag-led grow th
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Northern Ghana benefits more from agriculture-led growth
1999Agric-led growth
Non agric-led growth
NORTHERN 69.2 45.5 52.8
UPPER_EAST 88.2 55.0 69.0
UPPER_WEST 83.9 57.8 66.6
---- Poverty rate by 2015 ----
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Conclusions from simulation results
Current patterns of growth will halve poverty by 2015 at the national level, while regional inequality will be worsened.
Agriculture-led growth will be more effective in reducing poverty both at the national level and in the poor regions.
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Targeted growth simulations in Northern Ghana
Productivity growth in groundnut generates the largest poverty reduction effects in the three northern regions.
Cassava next to groundnut in Northern Region
Cowpea next to groundnut in Upper West region
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Effects of growth in productivity of staples on absolute poverty incidence by 2015
1999 Base Groundnut Cassava Cowpea National Staples
NORTHERN 69.2 57.0 37.9 47.3 - 49.5
UPPER_EAST 88.2 70.3 47.8 - 67.0 68.1
UPPER_WEST 83.9 70.5 55.4 66.8 60.9 66.8
NATIONAL 39.7 23.7 18.0 21.2 20.1 20.5
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Figure 6: Simulations of Poverty Trends in Northern Region
35
40
45
50
55
60
65
70
1999 2001 2003 2005 2007 2009 2011 2013 2015
Pov
erty
rat
e (%
)
Base-run National Staple Northern Groundnut Northern Cassava
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Figure 7: Simulations of Poverty Trends in Upper East Region (Crop level effects)
45
50
55
60
65
70
75
80
85
90
1999 2001 2003 2005 2007 2009 2011 2013 2015
Pov
erty
rat
e (%
)
Base-run National Staple UpperEast Groundnut
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Figure 8: Simulations of Poverty Trends in Upper West Region
55
60
65
70
75
80
85
1999 2001 2003 2005 2007 2009 2011 2013 2015
Pov
erty
ra
te (%
)
Base-run National Staple UpperWest Groundnut UpperWest Cow pea
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Why are these crops making such impact?
They are widely grown as staple and cash crops
Actualising productivity growth requires addressing production constraints
Need to reduce yield gap Pest control for groundnuts and cowpea
(Integrated crop pest management)
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Adequacy of crop productivity growth
Crop productivity increases probably not enough
Poverty levels in 2015 still range between 38% in Northern region and 55% in Upper West region.
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What complementary investments?
Increased investment in human capital to optimise returns from migration
Increased investment in production infrastructure to attract additional private sector investment that generates forward linkages from groundnut production
Livestock not included in model; investments here can generate additional income growth.
Conglomeration of private sector activities necessary for private investment to take off
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In addition, reduction in poverty and inequality requires political commitment