Nigeria Country Strategy Support Program

Agriculture Growth and Investment Options for Poverty

Reduction in NigeriaXinshen Diao, Manson Nwafor, Vida Alpuerto

Research Background

• Part of a wider effort to increase the use of research evidence in agriculture policy making in Africa.

• Part of a wider advisory program launched around 2003 by the World Bank and other agencies.

• A collaborative effort between ReSAKSS WA, IITA and the Agriculture Policy Support Facility (APSF), IFRPI-Nigeria.

Purpose of The Seminar

• To obtain feedback on the analysis in

general

• To discuss the assumptions of the model

• To discuss the adequacy of experiments

done

• To discuss the results obtained

Challenges and Opportunities Facing Agriculture (1)

• High poverty rate, particularly in the rural areas (54.4%

for the country and 63.3% in rural areas in 2004)

• Rising poverty between 1980 and 1996 (from 27.2% in

1980 to 65.6% in 1996) and slow decline after 1996

• High growth rates in recent periods (6.6% annual growth

rate for GDP in 2002-2006 period, but poverty is still

higher than the 1980 level.

• Agriculture is the single most important engine of recent

growth, accounting for 47% of growth (oil for 39%).

• Agriculture is the single largest employer of labor and the

largest share of the poor are farmers.

Challenges and Opportunities Facing Agriculture (2)

• However, recent agricultural growth is still led by area expansion without enough

productivity increase. Possible increases in productivity show that there are

supply opportunities in the sector. Increasing food imports show that there is

local unsatisfied demand for agricultural output – this is a demand opportunity

(ReSAKSS WA [2009]).

• To improve outcomes, numerous goals and targets have been articulated by the

government in many policy documents. However, there is little analysis which

assesses the ability of these intermediate targets to lead to the ultimate targets

of sectoral and national growth as well as poverty reduction.

• An economy-wide, computable general equilibrium (CGE) model for Nigeria is

developed in order to:

1. analyze synergies and trade-offs between economic growth and poverty

reduction

2. Identify priority products for investment and growth.

3. Evaluate the expected poverty and growth outcomes of present government

targets.

Key Policy Documents

• The National Food Security Programme (NFSP) – released in 2008

• The National Economic Empowerment and Development Strategy (NEEDS) II

• The national medium term investment Programme under the Comprehensive Africa Agriculture Development Program.

• Presidential initiatives and Medium term sector strategy documents.

Key Government Targets I : NFSP

Targets defined in NFSP

Current level Level by 2011 Total increase annual growth

Million mt Million mt % (08-11, %)

Crops

Cassava 49 100 104.1 19.5

Rice 2.8 5.6 100 18.9

Millet 4 6.5 62.5 12.9

Wheat 0.1 0.5 614.3 63.5

Sugar 0.2 2.2 1034 83.5

Tomato 1.1 2.2 100 18.9

Cotton 0.4 1 185.7 30

Cocoa 0.4 0.7 84.2 16.5

Palm Oil 0.8 1.3 50 10.7

Palm Kernel 0.4 0.6 50 10.7

Rubber 0.2 0.3 50 10.7

Key Government Targets II

• Other specific targets for crops, livestock and

fisheries

• 6% agriculture growth (Comprehensive Africa

Agriculture Development Programme , CAADP)

• 10% agriculture growth in 2008 – 2011 (NEEDS

II)

• Halving of poverty by 2015 (NEEDS II) and

MDG1. Also supported as ultimate goal by

CAADP.

Data and Modelling I

• The Social Accounting Matrix (SAM) is the basic data set used by the

Computable General Equilibrium Model.

• A SAM for the year 2006 was built for the study. A SAM is a table which shows

the incomes and expenditures of production factors, firms, households, the

government and the rest of the world.

• It is built such that every income to one agent/institution is an expenditure to

another. It is designed to show the inter dependence between agents and

institutions which we observe in everyday life. It uses figures to document the

circular flow of income in an open economy.

• The SAM documents how the economy functioned in the year 2006. This base

year is then used to assess possible future outcomes given the structure of the

economy and economic relationships between agents and institutions (firms,

government etc) in 2006. On their own, SAMS provide useful insights into the

income and expenditure priorities and constraints of firms, farms, households

and the government.

• Most of the data for the SAM came from the National Bureau of statistics, the

Federal Ministry of Agriculture and Rural Development and the Central Bank of

Nigeria.

• A CGE model is a simultaneous equations model which replicates the functioning of the economy in a way that allows equilibrium to be achieved in major markets in the economy. It is therefore a good indicator of the eventual impacts of policies or uncontrollable events after markets adjust.

• They are used to analyze a wide range of policies - fiscal, trade, agriculture , income, energy, technology and investment amongst others.

• Unlike other models they capture how changes in one market may lead to changes in others due to forward and backward linkages in the production process. It also captures how low supply can reduce demand and vice-versa as it they track both total supply for commodities and total demand for them.

• They are therefore ideal for analyzing the impacts of policies which can affect many sectors or whose success depends on the reactions of other sectors. They also analyze the impacts of these interactions on household incomes and expenditure levels. This allows assessments of the poverty impacts of policies/uncontrollable events to be captured.

Data and Modelling II

Data and Modelling III

• The CGE model and SAM have 62 sub-sectors, more than half in

agriculture, but also include agro-processing sectors in detail and the

most important nonagricultural sectors in both industry and services

• In agriculture: (i) 5 cereal crops; (ii) 5 root crops; (iii) 7 other food crops;

(iv) 10 higher-value export-oriented crops; (v) livestock products; (vi)

forestry; and (vii) fisheries

• Agricultural production disaggregated across six zones

• Dynamic model: 2006 – 2017.

• Two types of capital – agriculture capital and non-agriculture capital

• 3 types of labour – farm labour, unskilled labour and skilled labour.

• Models the behavior of firms and farms, households, the government

and the rest of the world (goods and services trade, income and

transfers- remittances etc- to and from the world)

Data and Modelling IV– Assumptions

• The targets articulated by the government are unlikely to be met by 2011

• Population growth rate for 2008 – 2017 remains the same as for 1991 –2006 (3% p.a)

• Rural farm labour supply grows at 2% p.a. while other unskilled and skilled labour grow at 3.3% and 3.4% respectively.

• Land expansion rate (area cultivated) which was 5.2% p.a. in 2001-2006 is maintained for 2007-2011 but is reduced to 4.2% for 2012 – 2017

• In a given year factors are fully employed

• The exchange rate is the numeraire

• The current account balance is fixed in each year but grows initially by 3.5% and then by 2.8% each year to reflect changes in the international oil market

• Real government expenditure and transfers to households increase by 5% each year.

• Real foreign payments to the government from assets abroad etc increases by 3.5% each year.

• The model is savings driven: total investment in the economy adjusts to the level of available savings of the government, firms, households etc.

Yield Gaps

Current yield (mt/ha) Potential yield (mt/ha)

Yield Gap % (Potential -

Current)

Rice 1.9 7 268

Cassava 12.3 28.4 131

Maize 1.6 4 150

Sorghum 1.1 3.2 191

Millet 1.1 2.4 118

Yam 12.3 18 46

Irish Potato 7.6 10.5 38

Soybean 1.2 2 67

Beniseed 0.6 1 67

Melon 0.4 0.5 25

Cocoa 0.2 2 900

Cowpea 0.5 2.3 360

Okra 3.1 5.5 77

Crop yields

Initial level Baseline Target CAADP

mt/ha growth % mt/ha growth %

Cereals

Rice 1.5 1.1 2.4 5.1

Wheat 1.1 0.1 1.3 1.8

Maize 1.4 0.3 1.8 2.9

Sorghum 1.4 0.6 1.7 2.8

Millet 1.5 0.3 1.9 2.6

Root crops

Cassava 13 1.1 18.2 3.8

Yams 8.3 1.2 11.2 3.4

Cocoyam 0.6 2.5 0.8 3.4

Potato 8.9 5.7 18.8 8.7

Sweet potato 3.4 0.7 4.3 2.7

Data and Modelling V – Targeted Crop Yields

Data and Modelling VI – Targeted Crop Yields

Crop yields

Initial level

Baseline Target CAADP

mt/ha growth % mt/ha growth %

Other food crops

Plantain 6.9 2 9.7 3.7

Beans 0.5 1.5 0.7 3.4

Groundnuts 1.2 1.3 1.6 3.6

Soybeans 0.7 1.2 0.9 3.4

Other oilseeds 1.8 0.9 2.2 2.1

Vegetables 7.6 1.2 10 3

Fruits 5.2 1.6 6.8 3.2

Data and Modelling VII – Targeted Crop Yields

Crop yields

Initial level Baseline Target CAADP

mt/ha growth % mt/ha growth %

High-value crops

Cocoa 0.3 5.3 0.5 6.5

Coffee 0.5 1.7 0.6 3.2

Cotton 0.8 0.4 0.9 1.5

Oil palm 1.4 2.5 2 4.1

Sugar 19.2 1.4 30 5.1

Tobacco 8.7 1.9 11.8 3.4

Nuts 0.8 1.3 1 2.7

Cashew nuts 4.2 2 5.5 3.1

Rubber 0.6 -0.1 0.6 0.4

Other crops 0.5 1.8 0.7 3.3

Scenarios I

• Considering changing global environment a modest annual

GDP growth rate of 6.5% is targeted in the next 9 years

(2009 – 2017) in the base-run, while agriculture grows at

5.9%

• Growth is driven by increases in land, labor and capital

accumulation, as well as by productivity changes

• A series of agriculture-led scenarios are considered, and in

these scenarios, additional growth is led by productivity.

• Growth in different crops/crop groups are considered while

an aggregate scenario (CAADP) considers a simultaneous

increase in the different agriculture products‟ yield and

productivity.

Scenarios II

Base Run CAADP

Labour Supply

growth

Rural farm labour grows at 2% p.a.

while other unskilled and skilled

labour grow at 3.3% and 3.4%

respectively.

Rural farm labour grows at 2% p.a.

while other unskilled and skilled

labour grow at 3.3% and 3.4%

respectively.

Land growth (area

cultivated)

Land expansion which was 5.2% p.a.

in 2001-2006 is maintained for 2007-

2011 but is reduced to 4.2% for 2012

– 2017

Land expansion which was 5.2% p.a.

in 2001-2006 is maintained for 2007-

2011 but is reduced to 4.2% for 2012

– 2017. Additional expansion where

the government targeted it.

Yield growth Based on 1999-2006 growth rates Modest increases in yield up to 2017.

2017 yields are still much lower than

potential yields.

Total factor

Productivity growth

Levels consistent with 5.9%

agriculture growth and 6.5% economy

growth.

Levels consistent with the agriculture

output targets in the National Food

Security Programme (2008) and other

government policy documents

Results – economic growth ITable III.1 GDP growth rates in the Base-run and CAADP scenario (1)

Share of GDPAnnual growth rate 08-

17 (%)

In 2006 Baseline CAADP scenario

Total GDP 19,909 billion Naira 6.5 8

Agriculture 29.7 5.7 9.5

Cereals 7.7 5.4 9.5

Rice 2.6 5.1 10.2

Wheat 0 5 25.9

Maize 2.2 7.3 12

Sorghum 1.6 4 5.7

Millet 1.3 4.2 5.7

Root crops 9.4 6 8.9

Cassava 4.4 5.6 8.7

Yams 3.9 6.4 9.3

Cocoyam 0.2 4.7 6

Potato 0.3 8.8 12.4

Sweet potato 0.6 4.7 7

Share of GDPAnnual growth rate, 08-17

(%)

In 2006 Baseline CAADP scenario

Total GDP 19,909 billion Naira 6.5 8

Agriculture 29.7 5.7 9.5

Other food crops 7.6 5.7 8.1

Plantain 0.6 3.8 4.9

Beans 1 5.3 7.6

Groundnuts 1.1 5.5 7.7

Soybeans 1.1 5.7 8.5

Other oilseeds 0.1 4.5 6.3

Vegetables 1.8 6.1 8.6

Fruits 1.6 6.4 8.7

Results – economic growth II

Share of GDP Annual growth rate, 08-17 (%)

In 2006 Baseline CAADP scenario

Total GDP 19,909 billion Naira 6.5 8

Agriculture 29.7 5.7 9.5

High-value crops 1.5 5.6 17.6

Cocoa 0.1 3.9 4.9

Coffee 0.2 6.1 8.8

Cotton 0.1 5.2 11.2

Oil palm 0.5 3.8 5.7

Sugar 0.3 7.3 33.1

Tobacco 0.1 6.8 10

Nuts 0 5.7 7.9

Cashew nuts 0.004 5.7 7.7

Rubber 0.2 6.1 6.1

Other export crops 0.017 8.5 12.8

Results – economic growth III

Results – economic growth IV

Annual input and TFP growth rate (%)

Baseline CAADP

Land 4.8 5.7

Labor 3 3

Ag labor 2.2 2.1

Nag labor 3.7 3.7

Capital 4.6 4.7

Ag capital 6.7 7.1

Nag capital 4.5 4.6

TFP 2.5 3.8

Ag TFP 2.3 5.6

Nag TFP 2.5 3

Baseline Results – National Poverty Reduction

28

32

36

40

44

48

52

56

60

64

2008 09 10 11 12 13 14 15 16 2017

%

Poverty Rate in Base-run Scenario

National

Rural

Urban

Baseline Results – Poverty Reduction Across Six Zones

Figure III.2:

Source: Nigerian CGE model results

13

23

33

43

53

63

73

2008 09 10 11 12 13 14 15 16 2017

%Regional Poverty Rate in Base-run Scenario

Southsouth Southeast

Southwest North center

Northeast Northwest

Agriculture-Led Growth – Poverty Reduction under Different Growth Scenarios

30

32

34

36

38

40

42

44

46

48

50

52

2008 09 10 11 12 13 14 15 16 2017

National Poverty Rate (%) under Alternative Agricultural Growth Scenarios

Base Cereal-led

Root-led Pulse-led

Export-led Livestock-led

CAADP

Results

• Achieving 5.7% growth in agriculture will leave the population

in poverty slightly increased by 2017. The estimated 1990

poverty level of 44% would not be halved by 2017.

• high growth target in agriculture will lift 16.5 million people out

off poverty by 2017. The 1990 poverty rate would still not be

halved as poverty would drop from 44% (1990) to 30.8%

(2017). With 10% of agricultural growth, the national poverty

rate of 1996 can be halved by 2017 – 2018.

• Food security is improved considerably with additional

kilograms of cereals root products available for each person

by 2017.

• dependence on imported cereals will not be eliminated, but

cereal imports will much less under the high growth scenario.

Poverty Reduction at the Zone Level

Table IV.5: Regional level poverty reduction with CAADP growthSource: Nigerian CGE model results

National 65.6 54.4 39.7 30.8 -34.8 -8.9 -53 -22.4

Rural 69.8 63.3 47.9 37.3 -32.5 -10.6 -46.6 -22.1

Urban 58.2 43.2 29.4 22.6 -35.6 -6.8 -61.1 -23.1

Southsouth 58.2 35.1 21.5 14 -44.2 -7.4 -75.9 -34.6

Southeast 53.5 26.7 13.4 8.5 -45 -4.9 -84.1 -36.5

Southwest 60.9 43 30 24.7 -36.2 -5.3 -59.4 -17.6

North central 64.7 67 51.5 41.9 -22.8 -9.6 -35.2 -18.7

Northeast 70.1 72.2 55.6 42.2 -27.9 -13.4 -39.8 -24.1

Northwest 77.2 71.2 55.4 43.7 -33.5 -11.7 -43.4 -21.1

S imulation res ults by 2017

(% )

Additional reduction

(percentage points ) % change

1996 2004 B as e-run

C AADP

growth from 1996

from bas e

2017 from 1996 from bas e 2017

Results – impacts on other sectors

• Agricultural growth has backward and forward

linkages (multipliers) with other sectors, and this

induced growth in other sectors also impacts on

poverty

• In terms of poverty impacts we find cereals-led

growth strategies are highly pro-poor

• In terms of linkages, we find negative effects on

other sectors of export-led growth, and large

positive effects of pulses

Results – impacts on other sectors

Table VI.6: Poverty-growth elasticity and growth multipliers

Growth multipliers

Poverty-growth elasticity (Change in poverty rate/change

in GDPpc per year)

Increased GDP/ increased sector output

Increased AgGDP/ increased sector output

Base -0.851

Growth is:

Rice-led -0.928 1.033 1.036

Wheat-led -0.853 1.013 1.037

Maize-led -0.914 1.282 1.146

Millet-led -0.915** 3.642 2.786

Cereal-led -1.024 1.305 1.184

Cassava-led -0.893 1.286 1.12

Root-led -0.923 1.246 1.088

Pulse-led -0.892 1.857 1.518

Export-led -0.814 0.7 0.974

Livestock-led -0.858

Fish-led -0.896 1.084 1.027

Forestry-led -0.861

CAADP -1.144

Nonagr-led -0.73 1.012

Price Effects

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1.10

1.20

1.30

2008 09 10 11 12 13 14 15 16 2017

Level of selected agricultural prices in CAADP scenario (normalized by prices in 2008 and deflated by CPI)

Rice Maize

Cassava Cocoa

Cotton Sugar

Poultry Fish

CPI

Results

• However, broader market opportunities do exist for

agriculture by developing agro-processing industries

in the country and by expanding export market.

• eg-1. Cassava - accounts for largest land allocation

and highest agricultural value-addition, an input for

both feed and agro-processing and highly

demanded in international markets.

• Thailand produces 10% of world cassava output, but

captures 70–80% of world exports

• Clearly there are opportunities for Nigeria to capture

larger share of world market

Results

• eg-2. Poultry – price is artifically high because of

import restrictions. A productivity surge in poultry

would make these restrictions unnecessary

• In fact, there are good export opportunities to

regional neighbours

• A poultry „boom‟ would also boost domestic

demand for maize and other feeds, which will

further enhance the linkage and multiplier effects

Messages from the Model

Size in the economy Growth multiplier Pro-poornessNegative price effect

Qualitative assessment Ranking

Qualitative assessment Ranking

Qualitative assessment Ranking

Qualitative assessment Ranking

Growth led by

Cereals Large 2 Large 3 Large 1

Rice Large 4 Large 8 Large 2 Small 7

Maize Large 7 Large 5 Large 5 Large 2

Millet/sorghum Large 5 Large 1 Large 4 Small 6

Wheat Small 13 Small 9 Large 11 Large 1

Roots Large 1 Large 6 Large 3

Cassava Large 3 Large 4 Large 7 Small 5

Pulses Large 6 Large 2 Large 8

Export-oriented crops Small 9 Small 10 Small 12 Small 9

Livestock Small 8 NM Large 9

Poultry Small 12 NM NM Large 3

Fishery Large 10 Large 7 Large 6 Large 4

Forestry Small 11 NM Large 10 Small 8

Messages from the model

• Agricultural growth targets should take into account:

1. Initial conditions: size, yields, poverty profile.

2. Multiplier effects

3. Market potential: price effects, domestic demand

(consumers, agro-processing), exports

4. Productivity levels: ag productivity growth has to

double

• All these 4 factors depend on policies, but market

potential and productivity levels depend heavily on

policies that are often “outside” agriculture: trade,

investment, energy, land tenure …

• Ideally, we should also consider state-

level policies

• We need to be aware of tradeoffs

between growth & poverty, but also that

there are lots of win-win strategies within

agriculture, as this study demonstrates

Messages from the model

Thank You For Your

Attention