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 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

Regional Poverty Distribution

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)

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

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

Agriculture-led growth is more pro-poor

National poverty rate(with GDP growth rate of 5.7%)

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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

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

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

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