Inclusive Growth and Employment Risk 1985-2009

Inclusive Growth and Employment Risk 1985-2009: The effect of Unemployment on
economic growth and Development in Nigeria.
Non-Experimental Impact Evaluation using SPSS and R
Olorunfemi Oladayo
1
and Raheem Kabir Kola
2

August, 2014
3

Today, graduate-unemployment has taken a new dimension in Nigeria. With scarce jobs,
many more seek higher education than the ability of the already saturated labour market
to absorb (Augustus N. Gbosi, 2005).

This material is a complement to the PEP International Policy Forum – held in Santa
Cruz, Bolivia, May 7, 2014. The Annual Conference is based on a special Policy Forum
organized by the Partnership for Economic Policy (PEP, www.pep-net.org). It consists of a
series of examples illustrating the basic economic policy and labour market reforms and
interventions used by Nigeria government between 1985-2009 period of growth and
employment issues. Users and researchers are advised to further analyze the data
contained in this material, before making adjustment towards policy that limits the
potential of 21
st
century youth in Sub Saharan Africa.

From the foregoing, it is obvious that unemployment, especially the
unemployment of graduates, impedes Nigeria’s progress in many ways. Apart from
economic waste, it also constitutes danger for political stability (Ipaye, 1998). The state
of unemployment can even lead to depression, low self-esteem, frustration and a

1
Head of Research and Development: DWIPS Technology Lokoja Nigeria.
2
Head of Software Engineering: DWIPS Technology Abuja, Nigeria.
3
The researchers welcome criticism and suggestion to improve future research directions on the issues analyzed in
this study. We also wish to thank the anonymous sponsor of this study. Send critics to [email protected]
number of other negative consequences (Ipaye, 1998). Youth employment is a crucial
issue in Nigeria because the youth constitute a major part of the labour force and they
have innovative ideas, which among other factors are important in the development
process of the country.
Aside the changes in labour market institution, urbanization issues and the rising
rate of the population demographics of the country which is faster than the job
opportunities, total neglect of the agricultural sectors and consequent mass exodus of
able bodied youths from the rural to urban areas has also worsen the effect of
unemployment due to continuous search of the none existing white cooler jobs. It is
against this backdrop of unemployment problems affecting states and the economy
that this research tries to investigate as a contemporary study in Nigeria. This is because
employment problem has become chronic and should be a matter of utmost national
concern.
Research Questions
Based on the problem of the study, the following research questions form the basis of
this investigation:
I. What is the magnitude impact of unemployment on Nigeria economy?
II. What step should be taken to ensure that economic growth is such that brings
about decrease in unemployment in Nigeria?
III. What is the tradeoff between seasonality in agricultural produce and rate of
unemployment change in Nigeria?

Objective of the Study
The objectives that will guide this study are as follows;
I. To determine the relationship between unemployment and economic growth in
Nigeria.
II. To ascertain how structural changes in agricultural & manufacturing production
can affect unemployment rate.
III. To measure the likelihood effect of unemployment on Nigeria growth &
development
IV. To conduct a comparative evaluation of unemployment rate among the 36 state
in Nigeria.
V. To fill gap in literature and make policy recommendations based on findings of
this research.

Significance of the study
One of the macroeconomics goals of any country is the actualization of full
employment. Therefore, unemployment in any system is seen as a policy failure.
However, there is always concerted effort on the part of the government in checkmating
the impact of unemployment in an economy. This study of unemployment is therefore
important to the economic policy makers, politicians, and graduates of higher
institutions in all discipline most especially graduate of business management. Firstly, to
the policy makers, this study will help in ascertaining the rate of unemployment in
Nigeria to the desired height. And the policy maker with the knowledge of the state of
unemployment in the system stands the best chance of controlling it through
appropriate initiative like poverty eradication programmes and creation of employment
opportunities that touches the lives of the population. Secondly, to Politicians, this
study is informative to would be Nigerian states governors to take decision concerning
the formation of policy towards setting-up cottage industry to reduce structural
unemployment affecting states that are public sector driven. Thirdly, university graduate
of business that have access to the findings of this report will also learn to be proactive
in the choice of sector where their managerial skills can be channel to; thereby averting
under capacity utilization (underemployment).
Data Presentation

Analysis and Interpretations
The fundamental reasoning & directions in the measurement of economic development
in the 21
st
century is, advancement towards equitable opportunities (inclusive) for
economic participants during the process of economic growth with benefits to every
Year Rate of Unemployment % change of unemployment GDP % change in GDP % Agricultural contribution to GDP % Manufacturing contribution to GDP
1985 6.1 _ 201036.3 _ 32.7 10.95
1986 5.3 -13.11 205971.4 2.45 35 11.04
1987 7 32.08 204806.5 -0.57 33.9 8.24
1988 5.1 -27.14 219875.6 7.36 34.9 9.23
1989 4.5 -11.76 236729.6 7.67 34.1 6.70
1990 3.5 -22.22 267550 13.02 31.5 6.20
1991 3.1 -11.43 265379.1 -0.81 32.97 7.00
1992 3.5 12.90 271365.5 2.26 32.92 5.66
1993 3.4 -2.86 274833.3 1.28 32.96 6.64
1994 3.2 -5.88 275450.6 0.22 33.7 8.54
1995 1.9 -40.63 281407.4 2.16 34.1 6.37
1996 2.8 47.37 293745.4 4.38 34.1 5.68
1997 3.4 21.43 302022.5 2.82 34.6 6.01
1998 3.5 2.94 310890.1 2.94 35 6.30
1999 17.5 400.00 312183.5 0.42 36.69 5.63
2000 13.1 -25.14 329178.7 5.44 35.83 4.18
2001 13.6 3.82 356994.3 8.45 34.32 4.94
2002 12.6 -7.35 433203.5 21.35 43.89 3.89
2003 14.8 17.46 477533 10.23 42.59 3.84
2004 13.4 -9.46 527576 10.48 40.98 3.59
2005 11.9 -11.19 561931.4 6.51 41.19 3.32
2006 12.3 3.36 595821.6 6.03 41.72 3.06
2007 12.7 3.25 634251.1 6.45 42.01 2.99
2008 14.9 17.32 672202.6 5.98 42.12 2.85
2009 19.7 32.21 716949.7 6.66 41.84 3.01
Sources: NBS, 2010, CBN 2005, 2006 and 2009 Annual Reports
Table I: Unemployment Rate and Gross Domestic Product (Value Approach)
section of the society. Inclusive growth takes a longer-term perspective, as the focus is
on productive employment as a means of increasing the income of the poor and
excluded groups & raising their standard of living (Wikipedia, 2014). In this case, what is
the tradeoff between seasonality in agricultural produce and rate of unemployment
change in Nigeria? The insight required to find answers to this research question can be
found in exhibit A below. This question hinges on axiom that economic growth cannot
be divorced of productive sector development and employment creation.

One objective of this study is to ascertain how structural shift in the productivity of
agricultural & manufacturing outputs can affect unemployment rate. Following
Wikipedia 2014 report- sustainable economic growth requires inclusive growth. An
insight from exhibit A reveals that seasonal growth in agriculture produce ranges
Source: Data factbook from Ni geri an bureau of stati sti cs 2010 and Central bank of Ni geri a 2005 - 2009
0
2
4
6
8
10
12
0
5
10
15
20
25
30
35
40
45
50
1
9
8
5
1
9
8
6
1
9
8
7
1
9
8
8
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9
8
9
1
9
9
0
1
9
9
1
1
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9
2
1
9
9
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1
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1
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6
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7
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8
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9
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9
2
0
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0
2
0
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2
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2
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Exhibit A: Tradeoff between seasonality of Agricultural produce,
downturn in Nigeria Manufacturing output and development issues
(1985-2009)
% of Agricultural contribution to GDP (left scale axis)
% of Manufacturing contribution to GDP (right scale axis)
between 32%-43% approximation within twenty five years (1985-2009) of development
period. However, due to urbanization & repeated migration of youth (age group of 20-
44) in rural to urban communities adapting Todaro (1985) migration hypothesis;
agricultural productivity in relation to economic growth is therefore traceable to activity
based predominantly to people living in rural area within specific age limits (age group
of 15–19, 55–59 and 65+).
Conversely, the downturn in local productivity of manufacturing sector in Nigeria
is a limiting factor hindering inclusive growth. Within 1985-1990, close to 6%-11%
productive manufacturing performance was achieved in Nigeria. In contrast, fewer than
4% growth ratio in manufacturing contribution to GDP is the reality in 2004-2009
periods (see exhibit A). Simply put, a significant employment risk factor of 1.3% on
average, will impact youth employment potential adversely in manufacturing sector.
Employment risk is a comparison of 1.68 average of absolute deviation of 1985-1990
data points to that of 0.37 within 2004-2009 respectively.
To this end, one fundamental approach to address youth unemployment as
development issues that is peculiar to this study is a prime readjustment of
empowerment program for the youth in relation to inclusive growth. For example, using
25-44 age distribution, an optimal scheme for the unemployed with self-employment or
SMEs operational interest, should go beyond short-term (1-2 years period) skill training
programme addressing technical aspects of business setup; but rather, empowerment
program to beneficiary should also be inclusive of 3-5 years cash transfer payment on
quarterly basis within entrepreneurial trial period required to risk failure and create
sustainable activities for his/her setup venture in support towards productive
employment needs in low-income countries, like the case of Nigeria where general
unemployment rate is rising (see Exhibit B below).
In Nigeria, another instrumental factor to address development issues of youth
unemployment is urbanization processes. A situation where many believed that gainful
employment opportunity is city bound due to large factories possibilities & high activity
rate in the urban communities. Based on the premise where structural unemployment
affects many states among the 36 states including federal capital territory (Abuja) that is
public sector driven, what step should be taken to ensure that economic growth is such
that brings about decrease in unemployment in Nigeria? If given the research objective
to determine the relationship between unemployment and economic growth in Nigeria.
The ideal approach cannot be divorced of nonlinear correlation estimate threshold
found in table II & Exhibit B below.
Table II: Correlations

Unemployment
rate (%)
Gross Domestic
Product value
Spearman's rho Unemployment rate (%) Correlation Coefficient 1.000 .612
**

Sig. (2-tailed) . .001
N 25 25
Gross Domestic Product
value
Correlation Coefficient .612
**
1.000
Sig. (2-tailed) .001 .
N 25 25
**. Correlation is significant at the 0.01 level (2-tailed).

The result in table II shows that Nigeria economic growth (GDP) and prevailing
unemployment rate are both interdependent at 61.2% rank (rho) correlation coefficient
measurement. Put differently, that positive relationship exist between this two
macroeconomic variables (the reverse is also possible).

Using baseline threshold in Exhibit B aligned with the prime readjustment strategy, this
study therefore follow policy analysis on growth and employment report (PAGE
Initiative, 2013). Adapting the thematic focus of partnership for economic policy -
inclusive growth is about raising the pace of growth and enlarging the size of the
economy, while leveling the playing field for investment and increasing productive
employment opportunities (PEP, 2013). In this case therefore, the sub-optimal or
defunct reform of structural adjustment programme (SAP 1986-1994) and NEEDs
(national economic empowerment development strategy 1&2) crafted with key cardinal
focus to drive employment generation for youth, did not achieved sustainable impact
beyond reform periods (see exhibit B). Why? because the intervention
programme/reforms were not planned with impact evaluation & follow-up policy
review; Hence, the 32.08% high change in unemployment rate recorded in 1987 after
SAP launch, remains the same 32.21% in 2009 immediately after NEEDs programme
suspension (see exhibit B) by the new federal government regime in Nigeria by May,
2007. Though, series of reforms inclusive of MDG intervention, had yielded 6.66% GDP
growth in 2009 when compare to the adverse growth (-0.57%) level in 1987, this
economic growth is not inclusive due to the rise in general unemployment level and
population in Nigeria as at 2009 observation.
Hypothesis testing
What is the magnitude impact of unemployment on Nigeria economy? Considering the
learning or research outcome with scientific goals to measure the likelihood effect of
unemployment on Nigeria growth & development; the hypothesis restated here is:
H
0
: Unemployment does not have significant effect on economic growth &
development in Nigeria.
H
1
: Unemployment does have a significant effect on the economic growth &
development in Nigeria.

Table III: Model Summary and Parameter Estimates
Dependent Variable: Gross Domestic Product value
Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1
d
i
m
en
si
o
n
1
Power .482 21.430 1 23 .000 162713.042 .387
Growth .562 29.548 1 23 .000 12.277 .054
The independent variable is Unemployment rate (%).

The model summary result found in table III shows that an estimated 48.2% (R
2
= 0.482)
variability in Nigeria economic growth on average (dependent variable being GDP
values) is being explained by annual changing rate of unemployment variable
(predictor), if power calculation technique is administered. A counterfactual
investigation conducted by Tabeuina Daveri (2000) found empirical support by raising a
hypothesis that unemployment has a negative effect on economic growth while Layard
and Nickell (1999) supported findings that the labour market institution that increase
unemployment also lower economic growth. By contrast, following result in table III, the
growth equation lacked sufficient impact estimate (b
1
= 0.054) to predict Nigerian
economy from changes found in unemployment rate (25 years period: [1985-2009])

Fundamentally, using a causal effect approach in table III, the Interpretation of
parameter estimate statistic on average outcome suggest that; each unit group of
persons added to unemployment grid thus produces 38.7% impact (see table III: b
1
=
0.387) on economic growth (GDP value). But the average outcome here is without
feedback effect to explain development issues relating to inclusive growth and
productive employment in the long-run. However, the regression parameter estimate
found in the power equation result (see Table III) is statistically significant (Sig.=0.000 <
0.05 level tested) at 95% confidence interval. Hypothesis decision: we reject the null (H
0
)
hypothesis that unemployment does not impact economic growth, and make conclusion
to support alternative (H
1
) hypothesis that Unemployment rate does have a significant
short-term effect on the economic growth, but lacked power to explain long-term
productive employment in Nigeria.
Due to paucity of data, the research objective to carry out comparative evaluation of
unemployment rate among the 36 state in Nigeria was a major challenge. This however
can be a major area for further research direction towards impact evaluation quest by
other researchers. Moreover, we adopted cluster analysis to investigate migration issues
across states, based on the data available, unemployment rates by states in Nigeria
(2002-2008) for the scope of this study. Source: NBS/CBN Surveys 2007 and 2008,
Federal Office of Statistics 2010.
> data
X2002 X2003 X2004 X2005 X2006 X2007 X2008
ABIA 14.8 11.4 9.65 7.9 13.5 10.9 14.50
ADAMAWA 12.9 11.9 16.65 21.4 17.9 11.9 29.40
AKWA-IBOM 12.3 14.4 14.40 14.4 15.3 13.5 34.10
ANAMBRA 6.6 9.1 9.45 9.8 10.8 11.1 16.80
BAUCHI 10.4 20.5 25.10 29.7 23.9 7.3 37.20
BAYELSA 3.5 7.1 14.00 20.9 16.0 6.9 38.40
BENUE 8.2 4.8 11.70 18.6 10.8 67.4 8.50
BORNO 6.4 0.8 3.55 6.3 5.8 7.8 27.70
CROSS-RIVER 7.9 12.0 11.50 11.1 16.9 11.8 14.30
DELTA 14.9 17.1 10.80 4.5 13.8 18.9 18.40
EBONYI 2.8 16.7 11.80 7.0 10.9 11.5 12.00
EDO 4.8 3.1 6.50 9.9 8.6 5.1 12.20
EKITI 17.5 8.2 7.85 7.5 8.7 15.6 20.60
ENUGU 15.2 16.5 21.60 27.4 20.0 11.5 14.90
GOMBE 13.4 7.6 15.20 22.8 15.6 10.5 32.10
IMO 19.9 22.1 19.30 16.5 21.5 7.6 20.80
JIGAWA 6.1 20.5 19.80 19.1 21.6 17.4 26.50
KADUNA 8.4 19.6 15.90 12.1 14.1 5.9 11.60
KANO 12.8 25.9 22.50 19.1 19.4 12.7 27.60
KATSINA 10.4 20.3 22.10 23.8 19.3 5.8 37.30
KEBBI 12.3 19.8 19.90 19.9 15.2 11.8 12.00
KOGI 19.9 14.9 11.80 8.7 12.5 16.5 19.00
KWARA 8.8 5.4 4.20 2.9 7.5 16.4 11.00
LAGOS 8.0 25.6 16.10 6.5 15.5 10.2 19.50
NASARAWA 1.6 5.1 6.90 8.7 8.1 7.6 10.10
NIGER 6.3 6.7 3.50 0.2 3.6 17.0 11.93
OGUN 9.2 1.3 1.90 2.5 2.3 3.9 8.50
ONDO 16.8 7.3 6.80 6.2 6.7 5.8 14.90
OSUN 1.0 0.4 1.20 1.9 2.7 6.3 12.60
OYO 7.0 0.8 3.10 5.3 4.3 6.5 14.90
PLATEAU 11.8 0.4 1.60 2.8 2.9 8.7 7.10
RIVERS 6.6 15.3 11.20 7.0 25.0 4.7 27.90
SOKOTO 4.1 4.9 4.50 4.1 6.4 12.1 22.40
TARABA 16.8 23.8 13.60 3.4 14.0 5.9 26.80
YOBE 15.0 12.1 10.70 8.0 13.6 19.9 27.30
ZAMFARA 46.4 71.5 61.30 51.1 50.8 12.8 13.30
FCT 14.4 5.3 5.90 6.5 16.4 16.4 21.50


> data.agnes <- agnes(data, metric = "manhattan", method = "average", stand =
TRUE)
> data.agnes
Call: agnes(x = data, metric = "manhattan", stand = TRUE, method =
"average")
Agglomerative coefficient: 0.8758194
Order of objects:
[1] ABIA ANAMBRA CROSS-RIVER EBONYI KADUNA LAGOS
[7] DELTA YOBE KOGI EKITI FCT RIVERS
[13] TARABA BORNO OYO SOKOTO EDO NASARAWA
[19] OGUN PLATEAU OSUN KWARA NIGER ONDO
[25] ADAMAWA GOMBE AKWA-IBOM BAYELSA BAUCHI KATSINA
[31] ENUGU KEBBI IMO JIGAWA KANO BENUE
[37] ZAMFARA
Height (summary):
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.890 2.925 3.804 5.440 5.467 35.260

Available components:
[1] "order" "height" "ac" "merge" "diss" "call"
"method"
[8] "order.lab" "data"

From the evidences contained the data, the Dendrogram (using average linkage
between groups: see graph below) result suggests that people living in various state like
Delta, Yobe, Kogi, Ekiti and FCT (federal capital territory tends to have similar
unemployment challenges. These category of states are therefore classified as one
group. However, the dendogram suggests further that when the dwellers, particularly
the youth living in this particular group of five as one identity, decides to migrate to
another neighbor class of group (Abia, Anambra, Cross-River, Ebonyi, Kaduna and
lagos), to search and compete for few available jobs in a state with high population
density and large number of manufacturing and service firms or industry; such migrants
that may be faced with information asymmetric in the labour market might create an
unintended job competition among the people in the other states. The possible solution
to this issue stated here, is for policy makers to address inclusive growth and
employment risk as explained in context found previously in exhibit A model.

Discussion of Findings
For policy review, another major example of sub-optimal empowerment program in
practice is the graduate internship scheme (GIS) initiative under the SURE-P (Subsidy
reinvestment and empowerment programme) intervention of Nigeria federal
government in 2011. GIS aims to provide Nigerian graduates with quality temporary
work experience that will make them stronger candidates for job openings in the labour
market through a one-year internship placement (Papka P.M. August 6, Project Director
(GIS) report, 2014). Stating further that, during the period of internship, the Federal
Government will provide each intern with a monthly stipend payment of N30,000, and a
group life Insurance.
Empirically, consequent upon the findings in this study, the rising rate of unemployed
persons irrespective of gender, age distribution and geographical location is a signal to
measure the unproductive sector in which the youth as a group is more vulnerable.
Unemployment rate according to Begg, (2004) is the percentage of people in the labour
force without jobs. However, to level up this scientific investigation, the productive
sector cannot be left out of research equation. Productive sector of the Nigeria
economy in this context is inclusive of Agricultural & manufacturing sectors
contribution, but not limited to this critical sector (see Exhibit A). For comparison, the
impact of productive sector to the economy which is the unexplained factor (see Model
summary in table III) in the curve estimation regression model (1- R
2
statistic: [1-0.482]
= 0.518) is put at 51.8% probability estimate approximately for power calculation.


Summary of Findings
One major rationale to understand the strong positive correlation (rho= 0.612) between
unemployment rate and economic growth indicator in Nigeria is that raising the gross
domestic product (value approach) is critical for the control of rising unemployment rate
though; the outcome may not be parallel in the long-run (see exhibit C & table II).



Corroborating Walterskirchen (1999) the simple, but wrong argument is: There can be
no negative relationship between economic growth and unemployment, because GDP
and unemployment are both rising in the long run. Conversely, the macroeconomic
policy framework has enhanced the stability (year-on-year change in GDP) of Nigerian
economy. In contrast, the shift (year-on-year change in unemployment rate) in labour
market issues extends towards an irrational patterns (1988-2000: see exhibit B) hence,
the need for prime readjustment strategy to tackle unemployment affecting the
standard of living of the youth in Nigeria.


Conclusions
The dynamics of impact evaluation in relation to unemployment and economic growth
in Nigeria have been fully explained in this study. Although few hindrances to interpret
the cause-effect factor (predictive) of labour market supply and economic development
in developing countries such as the Nigeria case is still problematic. However, the
estimated 38.7% average impact of unemployment on economic growth indicator for
twenty five annual period (long-term: 1985-2009) can be approached as implicit cost
associated with marginal unit of output that can be produced locally if the unemployed
grid of people – particularly the youth are nationally motivated to experiment
entrepreneurial initiatives to create value to their immediate communities, rather than
migrating to urban labour market in search of high rewarding jobs.

Recommendations
One main recommendation based on evidences in this study is that government policy
relating to labour market reforms in Nigeria should be integrated with a baseline &
follow-up actions of reforms impact evaluation to curb policy shock or unintended
effect of empowerment scheme.
Policy makers especially in Nigeria and particularly the policy interventions at the state
level should acknowledge the fact that civil service jobs extension is not likely to account
for productive employment creation for 21
st
century youth. This explains the missing link
of inclusive growth approach.
The Nigerian youth are likely to be left behind when short-term skills acquisition
program is not planned with sustainable Prime readjustment strategy that can absorb
failure risk of self-employed or green entrepreneurial drives to create activity based
business that can employ more people locally.
The employment risk factor attributed to loss of jobs in the manufacturing sector in
Nigeria on a long-term measurement approach should be controlled through optimal
labour market reforms and economic development policies review.













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