Jude Chukwu (Department of Economics, University of Nigeria and Visiting Research Fellow, IPC-IG) introduced his research, presenting its empirical findings during a presentation on the IPC-IG’s Seminar Series. He delved into the patterns of growth and inequality in Nigeria, as well as on the extent of pro-poorness and inclusiveness of growth in the country.

1. Growth, Redistribution and Inequality
Effects on Poverty Changes in Nigeria
Jude Okechukwu Chukwu
PhD Candidate
Department of Economics
University of Nigeria
jude.chukwu@unn.edu.ng
Visiting Research Fellow
IPC-IG, Brasilia/Brazil
IPC-IG, SEMINAR SERIES, 28th July, 2014

2. Presentation Outline
1. Introduction: context and motivation
2. Study objectives
3. What does theory tell us?
4. Empirical Evidence4. Empirical Evidence
5. Estimation Method: Models and data
6. Empirical Results
7. Conclusion and Policy Implications

3. Introduction/1
The economy has been growing on average between 6.5% and
7.2% for a decade (NPC, 2012).
GDP growth rate was 3.7% in 2004. By 2010, it had increased to
7.8% (World Bank, 2013). Rise of 4.1%, which is above
continental Africa’s average growth rate of 4.0%.
Trickle-down theory: increase in growth rates enables the poor toTrickle-down theory: increase in growth rates enables the poor to
derive maximum benefits.
Growth is good for the poor (Dollar & Kraay, 2000)
Yet in rare cases the economic growth might increase inequality
and offset gains of the poor from the economic growth (Esanov,
2006).
The paradox is that the poverty level in Nigeria contradicts the
country’s immense wealth (Obadan, 2004).

4. Introduction/2
Fig. 1: Nigeria GDP Growth Annual (%)

5. Introduction/3
Fig. 1: Change in GDP Growth (%) 2004 - 2010

6. Introduction/4
Figure 3 show that poverty increased at National level
by 14.6%; in rural sector by 9.9% and urban sector
by 18.6%
Poverty changes were positive in Rural and UrbanPoverty changes were positive in Rural and Urban
sectors, Southern zones but negative in all the
Northern zones
South-east showed worst evidence of poverty
increase by 29.72%, while South-west showed least
increase by 3.10% followed by South-south (17.7%)

7. Introduction/5: Poverty Trends and Changes: 2004 & 2010/Fig 3
50
60
70
80
-20
-10
0
10
20
30
40
National Rural Urban South
South
South
East
South
West
North
Central
North
East
North
West
14.6
9.9
18.6 17.72
29.72
3.1
-10.68
-5.52
-3.52
Poverty 2004
Poverty 2010
Poverty Change

8. Introduction/6
Inequality rose by 4.1% at national level; increased
by 2.2% and 4.2% at rural and urban sectors
respectively
Inequality changes were positive in all SouthernInequality changes were positive in all Southern
zones, North east and North West but negative in
North central (about -5.4%)
Highest increase by 18.1% was in the South east
followed by South south (oil rich/coastal region) with
an increase of 12.8% while South west (Lagos axis)
had least increase in inequality by 0.2%

9. Introduction/7: Inequality Trends and changes: 2004 & 2010/Fig 4
10
15
20
12.8
18.1
8.6
-10
-5
0
5
National Rural Urban South
South
South
East
South
West
North
Central
North
East
North
West
4.1
2.2
4.2
0.2
-5.4
0.7
Inequality 2004
Inequality 2010
Inequality Change

10. Introduction/8
Nigeria’s growth paradox is a policy concern since average
growth rates have been trending upwards, while poverty
and inequality deteriorate
HNLSS, 2010 indicted the high growth rates between 2004
and 2010 - both poverty & inequality were reported to haveand 2010 - both poverty & inequality were reported to have
increased: poverty rose by 14.6% and inequality by 4.1%
Why did the impressive growth in the 2000s not lead to
decline in poverty and inequality in Nigeria?
Has growth been pro-poor and inclusive in Nigeria?

11. Introduction/9
Departs from Adigun et al (2011); Odozi & Awoyemi (2010);
Aigbokhan (2008) in three main respects:
employed latest 2010 HNLSS for analyses. Previous
Nigerian studies used 1996 NLSS and 2004 HNLSS
considered poverty elasticity with respect to within and
between-group inequality using models by Araar (2007)
evaluates pro-poorness and inclusiveness of growth
between 2004 and 2010

12. Study objectives
i. decomposes poverty changes into growth effect and
redistribution effect
ii. estimate marginal FGT impact and FGT elasticity
with respect to within-and-between groupwith respect to within-and-between group
inequality
iii. estimate the pro-poorness and inclusiveness of
growth

13. What does theory tell us?/1
Poverty-growth-inequality triangle (Bourguignon, 2004):
inequality has direct impact on poverty as well as indirectly on
poverty through growth
Kuznet’s (1955) inverted-U predicts rise in inequality at early
periods of high and rising growth rates and fall in inequality
during later periodsduring later periods
Okun’s (1975) treatise on equality and efficiency argue that
greater income inequality is an incentive for work and investment
Trickle down hypothesis states that inequality is good for growth

14. What does theory tell us?/2
Barro (2000): effect of inequality on growth may be non-linear: it
may be bad for growth in poor countries but good for growth in
rich countries
Four stylized facts on the relative importance of growth and
inequality on poverty exists:
*1. Growth effect is dominant
*2. Growth is less effective in reducing poverty in high inequality
economies
*3. Growth is less effective in reducing poverty in LDCs than in
mature economies
*4. Growth has larger impact on poverty reduction in rural areas,
while distribution has larger impact on poverty reduction in urban
areas

15. Empirical Evidence
Studies that find that poverty change was mainly due to inequality
include Esanov (2006) for Kazakhstan, Anwar (2010) for Pakistan,
Kirama (2013) for Tanzania etc
Studies that find that poverty change was mainly due to growth
include Baye (2006) for Cameroon, Epoh & Baye (2007) for
Cameroon, Odozi and Awoyemi (2010) for Nigeria and so on.Cameroon, Odozi and Awoyemi (2010) for Nigeria and so on.
Cheema and Sial (2010) for Pakistan found that growth and
redistribution effects were negative indicating that both effects
reinforced each other to reduce poverty
Studies that support the prospective viewpoint are Araar (2012)
and Klasen & Misselhorn (2008).

16. Estimation Method/1
Model for objective 1: Shapley Value approach by Shorrocks
(1999) and Datt & Ravallion (1992) approach were employed for
growth and redistribution decomposition.
Model for objective 2: Araar’s (2007) models for poverty and
inequality within-group and between-group were employed.inequality within-group and between-group were employed.
Model for objective 3: Pro-poor indices such as Ravallion and Chen
(2003); Ravallion & Chen index – g; Kakwani and Pernia (2000);
Kakwani and Pernia (2000) - 1; Kwakani, Khander &
Son–PEGR-(2003); PEGR – g; and the Growth Incidence Curve
were used

17. Estimation Method/2
Data and their features:
* 2004 NLSS & 2010 HNLSS obtained by NBS were employed
* Both covered 36 states and FCT (37 Strata), and used two-stage
multi-stage sampling technique with EAs as Psu-first stage and
Households as Usu-second stageHouseholds as Usu-second stage
* 2004 NLSS surveyed 19, 158 households: 4646 in Urban (24.2%)
and 14, 512 in rural (75.8%)
•
* 2010 HNLSS surveyed 34, 619 households: 9,348 in Urban (27%)
and 25, 271 in rural (73%)
* Both were survey set for sample design prior to estimations

18. Empirical Results/1
Table 1: Poverty Decomposition into Growth and Redistribution Components, 2004-2010, NIGERIA
FGT Growth Effect Redistribution Effect Residual Difference in
Poverty
(d2 – d1)
Datt & Ravallion Shapley Datt & Ravallion Shapley Datt & Ravallion (d2 – d1)Datt & Ravallion Shapley
Value
Datt & Ravallion Shapley
Value
Datt & Ravallion (d2 – d1)
2010 - 2004
P0 -0.3381
(-0.3262)
-0.3321 0.1006
(0.1125)
0.1065 0.0119
(-0.0119)
-0.2256
P1 -0.1624
(-0.1984)
-0.1804 0.0875
(0.0514)
0.0695 -0.0360
(0.0360)
-0.1109
P2 -0.0974
(-0.1343)
-0.1159 0.0657
(0.0288)
0.0473 -0.0369
(0.0369)
-0.0686
Source: Author’s calculation based on NLSS 2004 and HNLSS 2010
Note: Values in brackets are for 2010 as reference period

19. Empirical Results/2
Table 1 show that P0 fell by 22.56%; the growth = 33.21% in
poverty reduction while, redistribution adversely accounted for
10.65%; thus dampened positive impacts of growth on poverty
It is likely that national poverty would have fallen the more due to
growth, iff, inequality had not varied given the realized decrease
in poverty of -0.2256 as against the potential of -0.3321 (growth)in poverty of -0.2256 as against the potential of -0.3321 (growth)
Poverty gap declined by 11.09%, growth accounted for 18.04% in
poverty reduction; while redistribution adversely accounted for
6.95%
Poverty severity fell by 6.86%, the pure growth effect accounted
for 11.59% in poverty reduction, while redistribution adversely
accounted for about 4.73%

20. Empirical Results/3
The results suggest that had inequality not increased, the
reduction in poverty would have been more
Tables 2 and 3 show the sectoral decomposition (urban and rural)
of poverty changes, and follow same pattern as for Nigeria
Poverty reduction was more due to growth than due to
redistribution
In urban sector, poverty declined by 35.74%, 16.56% and 10.2%
for headcount ratio, poverty gap and poverty severity respectively
In rural sector, poverty declined by 18.04%, 9.25% and 5.74%
for headcount ratio, poverty gap and poverty severity respectively
Poverty reduction declined faster in urban than rural areas
Study finds that for all FGT poverty measures, redistribution
reduced the positive impacts of growth on poverty
This finding is consistent with Anwar (2010) for Pakistan

21. Empirical Results/4
Table 2: Poverty Decomposition into Growth and Redistribution Components, 2004-2010, URBAN Sector/1
FGT Growth Effect Redistribution Effect Residual Difference in
Poverty
(d2 – d1)
Datt & Ravallion Shapley
Value
Datt & Ravallion Shapley
Value
Datt & Ravallion (d2 – d1)
2010 - 2004
P0 -0.4719
(-0.4718)
-0.4718 0.1143
(0.1144)
0.1141 0.000011
(-0.000011)
-0.3574
P1 -0.2045 -0.2433 0.1166 0.0778 -0.0776 -0.1656P1 -0.2045
(-0.2822)
-0.2433 0.1166
(0.0389)
0.0778 -0.0776
(0.0776)
-0.1656
P2 -0.1177
(-0.1888)
-0.1533 0.0868
(0.0157)
0.0512 -0.0712
(0.0712)
-0.1020
Source: Author’s calculation based on NLSS 2004 and HNLSS 2010
Note: Values in brackets are for 2010 as reference period

22. Empirical Results/5
Table 3: Poverty Decomposition into Growth and Redistribution Components, 2004-2010, RURAL Sector/2
FGT Growth Effect Redistribution Effect Residual Difference in
Poverty
(d2 – d1)
Datt & Ravallion Shapley
Value
Datt & Ravallion Shapley
Value
Datt & Ravallion d2 – d1
2010 - 2004Value Value 2010 - 2004
P0 -0.2853
(-0.2786
-0.2820 0.0982
(0.1049)
0.1016 0.0067
(-0.0067)
-0.1804
P1 -0.1428
(-0.1679)
-0.1553 0.0753
(0.0502)
0.0628 -0.0251
(0.0251)
-0.0925
P2 -0.0871
(-0.1134)
-0.1003 0.0560
(0.0298)
0.0429 -0.0262
(0.0262)
-0.0574
Source: Author’s calculation based on NLSS 2004 and HNLSS 2010
Note: Values in brackets are for 2010 as reference period

23. Empirical Results/6
Findings in South south, South west, North central and North west
are consistent with those of Nigeria, urban and rural sector
Results for South east and North east differ a little from others:
for the south east, poverty reduced by 2.41% for P0, while, P1
and P2 increased marginally by 1.69% and 2.26% respectively
For North east, change in poverty reduced by 21.7% for P0, the
P1 & P2 decreased by 8.45% and 4.13% points respectively.
Redistribution impact supplemented the growth effect
Despite that growth made inequality to deteriorate, the
distributional change was targeted towards exiting the marginally
poor households out of poverty. This is consistent with the
findings of Kang and Imai (2010) for NU minority in Vietnam.

24. Empirical Results/7
Table 4: Elasticity of poverty with respect to within-group and between-group inequality
Group MII MIP
P0
ELS
P0
MIP
P1
ELS
P1
MIP
P2
ELS
P2
South south 0.00708 0.000328 0.450556 0.000767 2.281928 0.000797 3.998963
South east 0.000688 0.000227 0.321574 0.000729 2.232403 0.000792 4.091086
Source: Author’s calculation using DASP in STATA 13.1
NOTE: MII means marginal impact on inequality; MIP represents marginal impact on poverty; ELS means
elasticity; P0 = poverty headcout, P1 = poverty gap; and P2 = poverty severity.
South east 0.000688 0.000227 0.321574 0.000729 2.232403 0.000792 4.091086
South west 0.001113 0.000211 0.184137 0.001186 2.246063 0.001380 4.409713
North central 0.000727 0.000425 0.568770 0.000749 2.169840 0.000745 3.642724
North east 0.000869 0.000457 0.512063 0.000893 2.166069 0.000931 3.808073
North west 0.001121 0.000967 0.839879 0.001159 2.178917 0.000996 3.158547
Within 0.005226 0.002616 0.487000 0.005483 2.210817 0.005641 3.837036
Between 0.000135 0.000076 0.548316 0.000143 2.245673 0.000127 3.364633
Population 0.005421 0.002526 0.453362 0.005704 2.217143 0.005942 3.896517

25. Empirical Results/8 Elasticity of poverty with respect to
within- and between-group inequality
Simulated elasticities are all positive
Results are sensitive to the choice of poverty measure
Between-group elasticities are numerically larger than within-
group elasticities for P0 and P1
Between-group elasticity is less than within-group in the case of
poverty severitypoverty severity
heterogeneity exists in impact and elasticity estimates across geo-
political zonal distributions using all the FGT poverty measures
Heterogeneity exists despite that same redistributive processes,
same “inequality and poverty aversion” parameters and same
poverty line are employed.
Study finds that heterogeneity is due to variations in initial sub-
group distributions, not due to disparities in the quality of growth
nor differences in redistributive policies

26. Empirical Results/9
Table 5: Pro-poor indices
NIGERIA 2004 - 2010
Pro-poor indices Poverty
Incidence (P0)
Poverty Depth
(P1)
Poverty Severity
(P2)
Growth Rate of Mean Income (g) 1.1125 1.1125 1.1125Growth Rate of Mean Income (g) 1.1125 1.1125 1.1125
Ravallion & Chen (2003) index 0.3463 0.3463 0.3463
Ravallion & Chen (2003) - g -0.7662 -0.7662 -0.7762
Kakwani & Pernia (2000) index 0.6672 0.5514 0.5396
Kakwani & Pernia (2000) index -1 -0.3328 -0.4486 -0.4604
Kakwani, Khander & Son (2003)
PEGR Index
0.7423 0.6134 0.6003
PEGR - g -0.3702 -0.4990 -0.5121

27. Empirical Results/10
Growth is pro-poor if the resulting growth rate is greater than the
mean income growth rate (Stoterau, 2010; Kabubo-Mariara et al,
2012).
In table 5, growth in mean income is everywhere greater than all
estimated pro-poor indices
Results show positive growth rate between 2004 and 2010
suggesting that mean income increasedsuggesting that mean income increased
Ravallion & Chen (2003) index is 0.3463 which is less than growth
rate of the mean income (1.1125): Growth was anti-poor instead
of pro-poor
Growth process b/w 2004 and 2010 could not have been pro-poor
since the Kakwani and Pernia (2000) indices are less than unity in
all FGT poverty measures

28. Empirical Results/11
Absolute and Relative Pro-poorness of growth
Absolute pro-poorness of growth: Ravallion & Chen (2003) index,
Kakwani & Pernia (2000), and Kakwani, Khander & Son (2003)
Relative pro-poorness of growth: Ravallion & Chen (2003) index
minus g; Kakwani, Khander & Son (2003) minus g; and the
Kakwani & Pernia (2000) minus unity
Estimates of 3 indices of absolute pro-poorness are statistically
greater than zero signifying that the change decreased absolute
poverty; while, the estimates of the indices of relative pro-
poorness are –ve but not statistically different from zero
Growth between 2004 and 2010 has not been sufficiently relative
pro-poor. Result is consistent with Duclos and Verdier-Chouchane
(2010) for Mauritius.

29. Conclusion and Policy implications
Overall, economic growth does not seem to be accompanied by
poverty reduction
Poverty is worsening in Northern geo-political zones, and they lag
behind their southern counterparts in the fight against poverty
Inequality is also worsening in the Northern zones than in the
Southern zones
Growth has neither been pro-poor nor inclusive
While growth has been anti-poor, inequality has been rising and
inhibiting the growth process
It is likely that robust inequality reducing policies to complement
growth promoting policies are needed
The low response of growth to poverty could be due to poor
targeting of vulnerable groups and lack of quality institutional
frameworks

30. Thank you for your rapt attention
OBRIGADO!!!!!