Conceptual And Theoretical Issues Economics Essay

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INTRODUCTION
Productivity and employment are issues that are central to the social and economic life of every country.
The extant literature refers to productivity and unemployment as constituting a vicious circle that explains the
endemic nature of poverty in developing countries. And it has been argued that continuous improvement in
productivity is the surest way to breaking this vicious circle. Growth in productivity provides a significant basis for
adequate supply of goods and services thereby improving the welfare of the people and enhancing social progress.
As pointed out by Dernburg (1985:63), "Without it there would be no growth in per capita income, and inflation
control would be all the more difficult". In fact, the observation has been made that continuous enhancement of
productivity has been very central to the brilliant performance of the Asian Tigers and Japan in recent years
(Simbeye, 1992; World Bank 1993). Recent developments in the world economy have also shown that countries
with high productivity are not only central to the determination of global balance of powers (e.g Japan and
Germany), but also serve as centres of stimulus, where world resources (including labour) are redirected to, as
opposed to countries with low or declining productivity. Recent studies, for example, Rensburg and Nande (1999)
and Roberts and Tybout (1997) have also shown that high productivity increases competitiveness in terms of
penetrating the world market. Thus, a country with high productivity is often characterized by a very high capacity
utilization (optimal use of resources), high standard of living, low rate of unemployment and social progress.
Unemployment, on the other hand, has been categorized as one of the serious impediments to social
progress. Apart from representing a colossal waste of a country's manpower resources, it generates welfare loss in
terms of lower output thereby leading to lower income and well-being (Akinboyo, 1987; and Raheem, 1993).
Unemployment is a very serious issue in Africa (Vandemoortele, 1991 and Rama, 1998) and particularly in Nigeria
(Oladeji, 1994 and Umo, 1996).
The need to avert the negative effects of unemployment has made the tackling of unemployment problems
to feature very prominently in the development objectives of many developing countries. Incidentally, most of these
countries' economies are also characterized by low productivity. Thus, it seems obvious to many policy makers that
there must be a straight forward connection between productivity and employment/unemployment. However, the
theoretical linkage between productivity and unemployment is yet to be settled in the literature. While some
researchers posit that higher productivity may increase unemployment (e.g. Diachavbre, 1991; Krugman, 1994),
some others argue that it could increase employment (e.g Yesufu, 1984; Akerele, 1994; CEC, 1993).
In view of the unfolding reality coupled with the protracted debates this paper attempts to examine the
linkage between productivity and unemployment. Specifically, it examines the dimensions of productivity and
unemployment in Nigeria as well as the direction of causality between them. To this end, the rest of the paper is
organized thus. Following this introduction is part II, which examines the conceptual and theoretical is sues. Part III
discusses the profile of productivity and unemployment in Nigeria while the empirical link between them is
examined in part IV. The final part contains the policy implications and conclusions.
II.
CONCEPTUAL AND THEORETICAL ISSUES
The literature is replete with varied categorizations of productivity and unemployment in terms of their
definitions, measurements and linkages. It is therefore important to make some clarifications on these issues.
2.1
Concept of Productivity
Productivity measures the relationship between the quantity and quality of goods and services produced
and the quantity of resources needed to produce them (i.e factor inputs such as labour, capital and technology)
(Simbeye, 1992; Okojie 1995; Roberts and Tybout, 1997). Mali (1978:6) defines it thus:
"The measure of how resources are being brought together in organizations and
utilized for accomplishing a set of results. It is reaching the highest level of
performance with the least expenditure of resources".
Productivity is viewed as the instrument for continuous progress, and of constant improvement of activities. It is
often seen as output per unit of input. Hence, higher productivity connotes achieving the same volume of output
with less factor inputs or more volume of output with the same amount of factor inputs. Thus, increased
productivity could result from the reduction in the use of resources, reduction in cost, use of better methods or
improvement in factor capabilities, particularly labour. Two variants of productivity measurements have been cited
in the literature: total factor productivity (TFP), otherwise known as multifactor productivity, and partial
productivity. Roberts and Tybout (1997) and Tybout (1992), assuming a neo-classical production function at the
2
sectoral or industry level, define total factor output to be a concave function of the vector of inputs and time (a proxy
for shift in technological innovation). To them, the elasticity of output with respect to time is the total factor
productivity. In a more general sense,
TFP
=
Total Output
..........(1)
Weighted Average of all inputs
Critical among these factor inputs are labour, capital, raw materials and purchase of spare parts, and other
miscellaneous goods and services that serve as inputs in the production process. In a more practical sense, these
factor inputs are reduced to the weighted average of labour and capital (Okojie, 1995; Roberts and Tybout, 1997).
The second variant, partial productivity (PP), is defined as:
PP
=
Total Output
............(2)
Partial Input
The partial input could either be labour or capital. This can be measured at the national level, sectoral level, industry
or factory level. Existing studies on productivity measurement show a predilection for productivity per labour input.
Several reasons have been put forward for the choice of labour as against other factors of production. First, Ilyin
and Motyler (1986) see labour as the "means and end of production". Labour is the only factor that creates value,
influences its prices and those of other factors and sets the general level of productivity. Second, it is the most easily
quantified factor of production (Okpechi, 1991). And finally, given the low technological base of developing
countries' economies, the quest for improved managerial capability and effectiveness should give the human factor
appropriate recognition and attention. While labour productivity seems to be the most convenient to use, it is
however important to note that this approach has an important limitation. It treats labour as being homogenous
instead of differentiating it according to age, sex, education, application of
skills, aptitude, among others. Nevertheless, this study applies productivity per worker as opposed to per capital or
total factor productivity.
2.2
Concept of Unemployment
There seems to be a consensus on the definition of unemployment. The International Labour Organization
(ILO) defines the unemployed as numbers of the economically active population who are without work but available
for and seeking work, including people who have lost their jobs and those who have voluntarily left work (World
Bank, 1998:63). Although there seems to be convergence on this concept, its applications have been bedeviled with
series of problems across countries. First, most published unemployment rates are recorded open unemployment.
People's attitude on this varies from country to country. While this may be high in developed countries and where
government is committed to resolving unemployment problems, it is likely to be very low in countries with the
opposite attributes.
Okigbo (1991) also points out the problem arising from the concept of labour force. In most countries,
particularly Nigeria, people below the age of 15 years and those above the age of 55, who are actively engaged in
economic activities are usually excluded from labour statistical surveys. All these factors have the tendency to
result in underestimation of unemployment thereby making international comparison very difficult. Factors such as
3
the preponderance of full housewives (but who are willing to be engaged in paid job) and unpaid family workers
also contribute significantly to the underestimation of unemployment1.
2.3
Theoretical Linkage between Productivity and Employment/Unemployment
The relationship between productivity and employment/unemployment is a complex issue. Increased
labour productivity connotes that the same volume of output can be produced with less labour. By implication, this
tends to contract employment (an increase in unemployment rate). The theoretical perspectives on this relationship
vary from one school of thought to another.
The classical economists hold the view that the relationship between employment and output is a one-way
relationship that goes from the input of labour to output2. The classical growth theory, as reflected in aggregate
production (mostly a variant of Cobb-Douglas function) derived essentially from the technical relations that make
the level of output a function of production inputs such as labour, capital, land, technology, etc. In the classical
model's steady state (conditions where the growth rate of capital stock and output are equal), the approach shows
that the rate of growth of labour force and technical progress ultimately determine the growth rate of output. And as
pointed out by McCombie and Thirlwall (1994) and Hussain and Nadol (1997), this model fails to explain the
ultimate determinant of labour force and technical progress. The premise of the classical model therefore is that the
growth rate of employment is exogenous to the growth rate of output.
This, however, does not preclude the classical economists' belief in the attaintment of a full employment
equilibrium. In this framework, the supply of labour is positively related to the level of real wage, while the demand
exhibits a negative relationship with real wage, but a positive relationship with productivity (Fashola, 1983; Todaro,
1990). As pointed out by these authors, if there is some `involuntary' unemployment at or below the current real
wage, the real wage would fail to induce employers to take more labour until all involuntary unemployment is
eliminated. However, if increases in labour productivity translate to increased wages and such increases induce the
substitution of capital for labour the effect on unemployment will be positive (Fajana, 1983; Krugman, 1994). The
policy implications of this have been viewed as misleading particularly, to developing countries (Todaro, 1990;
Hussain and Nadol, 1997). Evidence from the economic recession of the 1980s in Africa and Latin America clearly
show that real wages declined very sharply. This period of lower real wages coincided with high level of
1
2
We do not intend to do cross-country analysis, hence our unemployment data shall be restricted to the
officially published data. We believe the effect of underestimation will be relatively minor.
By referring to output instead of productivity, we invoke the Verdoorn's Law as espoused in Kaldor (1967).
The Law postulates that faster growth of output causes a faster growth of productivity. This
positive relationship is further confirmed by Dernburg (1985:55) thus: " .. a fall in output generally
brings with it a very sharp decline in productivity ...". In line with the above, both output and
productivity may be used interchangeable here.
4
unemployment than the available jobs (Todaro, 1990: 249). Also as argued by Hussain and Nadol (1997:3), the
policy implication of the neoclassical approach to primary commodities-producing countries is that, given the
existence of says Law, whatever that was produced is automatically sold irrespective of the characteristics of the
goods produced and the demand for them. Recent developments in the world market for primary commodities has
proved this to be wrong.
In contrast, Keynesian theory explains the determination of output or productivity and
employment/unemployment in terms of aggregate demand. This approach sees demand for labour as a derived
demand. Productivity growth (a la Verdoorn's Law), should increase the demand for labour thereby reducing
unemployment. The Keynesian framework, as examined by Thirlwall (1979), Grill and Zanalda (1995) and Hussain
and Nadol (1997), postulates that increases in employment, capital stock and technological change are largely
endogenous. Thus, the growth of employment is demand determined and that the fundamental determinants of long
term growth of output also influence the growth of employment.
Contrary to the strong belief of the neo-classicals that equilibrium wage rate, price, interest rate and real
cash balances guarantee the quality of national output and full-employment level, the Keynesians strongly believe in
the efficacy of aggregate demand. As shown in Figure 1, in the upper panel of the diagram, C+I+G yield a level of
national output (Y1) that is less than the potential full-employment output level (Yf). Consequently, the level of
unemployment will be given by the "gap" between Nf and N1 in the lower panel of the diagram. Rather than the
workings of the real wage, price, interest rate and real cash balances, what could guarantee the attaintment of full
employment is additional government spending from G to G1. The Keynesian prescription for reducing
unemployment is increase in aggregate total demand through direct increases in government spending or policies
that encourage more private investment. As argued by the Keynesians, as long as there is unemployment and excess
capacity in the economy, the supply of goods and services will respond automatically to this higher demand. A new
equilibrium will always be established with higher income and lower level of unemployment.
5
Figure 1
6
The extension of the Keynesian model dominated development theorizing in the 1950s and beyond. Such
extensions could be found in Okun's Law and the Harrod-Domar model. For instance, Arthur Okun developed the
relationship between the actual and potential output and between the actual and benchmark unemployment in an
equation called the "Okun's Law" thus (Dernburg, 1985):
Q* - Q
=
"(U - U*)
.............(3)
Q
where Q* is potential output, Q is actual output, U is the unemployment rate, U* is the benchmark unemployment
rate, and " is Okun's coefficient3. The implication of Okun's coefficient is that a 1 percentage rise in unemployment
causes the economy to lose " percent of its output. Okun's Law clearly gives a direct relationship between output
and unemployment and indirectly between productivity and unemployment (a la Verdoorn Law).
In a similar vein, the neo-keynesians, in their efforts to provide reasons as to why employment growth lags
behind growth of industrial output, came out with a typical variant of the Harrod-Domar unemployment equation
..........(4)
{ ) Y } over { Y } - { ) (Y/N) } over { Y/N } = { )N } over { N }
thus,
The import of this equation is that the rate of output growth (Y) minus the rate of growth in labour productivity
(Y/N) approximately equals the rate of growth of employment (N). The implication is that the gap between growth
rate of output and the growth of labour productivity accounts for the rate of labour absorption. As had been argued
hypothetically by Todaro (1990), if output is growing by 8 percent per year while employment is expanding by only
3 percent, the difference is due to the rise in labour productivity, and vice versa. By implication, rapid economic
growth could generate lagging employment creation. This tends to support Essenberg's (1996) argument that if the
reduction in labour demand resulting from productivity increases is more than compensated by overall increases in
output, then both productivity and employment can increase together. This is particularly so when higher
productivity leads to increased profit and higher rate of investment, which in turn results in higher rate of growth.
In conclusion, the neo-classical approach posits that the rate of growth of employment (unemployment) is
exogenous to the rate of growth of output (productivity). In contrast, the Keynesian argument is premised on the fact
that it is the strength of demand that determines the amount of resources utilized. As such, employment is demand
determined and the rate of output growth is itself an important determinant of the rate of growth of employment.
Thus, output, productivity and employment are determined endogenously. This approach therefore suggests the
possibility of a bi-causal relationship.
III.
3.1
PROFILE OF PRODUCTIVITY AND UNEMPLOYMENT IN NIGERIA
Trends in Productivity
The centrality of continuous productivity improvement in advancing societal development has been well
acknowledged in the literature. In spite of the general consensus on the importance of productivity, many countries
3
Okun's coefficient (") was estimated for the American economy between (1970-82) to be 3.2 percent.
7
have not paid serious attention to improving the level of productivity in their economies. Evidence from Nigeria has
shown that both the national and sectoral productivity measures have generally reflected a declining trend over the
past three decades.
Given the data limitation on total factor productivity in Nigeria, our analysis is restricted to labour
productivity. As shown in Table 1, gross productivity (i.e. real GDP per worker) consistently rose between 1973
and 1977 as a result of the appreciable improvements in the level of economic activities immediately after the oil
boom of 1973/74. The motivation associated with the Udoji salary award and the consequent spread to the private
sector also contributed to productivity improvement during the period.
The sectoral analysis clearly shows that productivity in the industrial and service sectors are higher than in
the agricultural sector (Table 2). The productivity in the former is more than three times higher than in the latter
during this period. This finding conforms with the outcome of Dike and Ezenwe (1986) who also found that
agricultural productivity was the least among the three sectors examined above. Phillips (1983) and Udokporo
(1983) provided the reasons for low productivity in this sector. Critical among the factors are: subsistence
production, prevalence of redundant labour, low income and lack of proper training on issues relating to agricultural
activities.
Total labour productivity declined consecutively from 5.53 in 1977 to 3.36 in 1983 with the highest rate of
decline experienced in 1982 (-29.53 percent) (Table 1). Meanwhile, the performance varied across the sectors.
Though agricultural productivity was at its lowest ebb during the period, it, however, increased marginally from
2.02 to 2.11 in 1983, perhaps as a result of the implementation of the Green Revolution Programme during the
period. Productivity in both the industrial and services sectors consistently declined during the period. For instance,
they declined at an annual average of 8.02 and 2.40 percent for industry and services, respectively.
The institutionalization of the War Against Indiscipline (WAI) by the Buhari/Idiagbon administration in
1984/85 yielded some positive impacts on national productivity as it recorded the highest growth rate of 20.73
percent in 1985. The ouster of this regime weakened the implementation of WAI and hence ushered in a period of
relatively low productivity. Thus, productivity dropped from 3.74 in 1985 to 3.22 in 1987 ( the lowest ever). The
introduction of the Structural Adjustment Programme (SAP) led to marginal improvement in national productivity
during the period. Though the three sectors recorded some improvements, during this period, those of the industrial
and services were more pronounced than the agricultural sector. While agricultural productivity fluctuated between
2.32 and 2.49 during 1987-1992, the industrial and services productivity fluctuated between 3.84-7.39 percent and
4.49-5.67 percent, respectively.
In spite of the improvement in real GDP between 1993 and 1996, the political upheavals experienced
during the period seriously affected the overall productivity. Thus, the rate of productivity decline fluctuated
between 0.24 and 2.03 during 1993-95 period. And as shown in Table 2, the rates of decline were much more
pronounced in the industrial and services sectors than the agricultural sector. Evidence from the Central Bank of
Nigeria's survey of industrial enterprises attributed the sector's dismal performance largely to low capacity
8
utilization and high cost of productioN4. For instance, capacity utilization fluctuated between 29.6 and 30.4 percent
during the period. This was further compounded by the increasing cost of operation which rose by 75.6 percent in
1995. This arose largely from the continuous depreciation of the domestic currency during the period.
Consequently, the cost of
Table 1: Labour Productivity in Nigeria (Gross )
Note:
The growth rate was computed on the basis of the immediate past year rather than the interval of two years
given in the table.
Sources:
Computed by the authors from CBN: Statistical Bulletin (various issues), Nigeria: Economic,
Financial and Banking Indicators (various issues); National Planning Commission: National
Development Plans (various issues); FOS: Annual Abstract of Statistics (various issues); ILO
(1996) and World Bank: African Development Indicators (various issues) and World Tables
(various issues).
4
Year
Gross Productivity ('000)
Annual Growth Rate
1973
1975
1977
1979
1981
1983
1985
1987
1989
1990
1991
1992
1993
1994
1995
1996
1974-80
1981-90
1991-96
1974-96
4.59
4.69
5.53
4.88
3.54
3.36
3.74
3.22
3.61
3.79
3.86
3.87
3.86
3.86
3.78
3.80
5.09
3.46
3.84
4.01
-
-5.77
-1.72
-1.39
-29.53
-3.93
20.73
-3.12
4.59
5.26
1.78
0.08
-0.24
-0.05
-2.03
0.58
1.71
-1.91
0.03
-0.17See the details in CBN (1995): Annual Report and Statement of Accounts, December.
9
raw materials (mostly imported) accounted for 72.3 percent of the total cost of operation while salaries and wages
accounted for only 6.6 percent (CBN, 1995). Besides the low value added that could result from these
developments, the relatively low share of salaries and wages in the total cost of production is a reflection of low
motivation in the sector. Low motivation, an important determinant of low productivity is also prevalent in the
services sector, especially the public service. For instance the index of real wages for public officers on Grade Level
08 declined from 242 in 1980 to 107, 40 and 32 in 1986, 1990 and 1992, respectively (Odusola, 1997). The same
rate of decline applied to other categories of workers in the public service.
The long-term productivity growth rate for Nigeria (1974-1996) is disappointing. It recorded an average
growth rate of -0.17 percent during the period (Table 1). This is quite disheartening when compared with the 5.0
percent in Japan for the period 1960-1990. Other countries with remarkable performances include Italy (3.8%),
France (3.5%) and Germany (2.8%) (Krugman, 1994:34).
Why is Nigeria's productivity performance so low relative to other countries? The issues raised above are
quite germane for this performance. Besides the factors raised above, inadequate training has been a major
productivity factor in Nigeria. As pointed out by the National Manpower Board (NMB) (1991), only 5.34 percent of
the total employees were sent for training in 1991 in both the private and public sectors in Nigeria. This comprises:
Federal Government Civil Service (2.60%), Federal Parastatals (5.32%), State Government Civil Service (3.94%),
State Government Parastatals (3.65%), Local Government (3.20%), Joint Ownership by Federal and State (24.87%),
Joint Ownership by Government and Private (4.26%), Purely Private Enterprises (5.14%) and Voluntary Agency
(7.79%). Given the recent endogenous growth model, which sees continuous training (human capital investment) as
a crucial factor in national productivity, then this proportion of trained staff to the total number of employees is too
small for continuous productivity growth in Nigeria.
Table 2: Sectoral Labour Productivity (Agriculture, Industrial and Services) ('000)
Year
Agriculture
Industry
Services
Productivity
Annual
Productivity
Annual
Productivity
Annual
Growth
Growth
Growth
10
1973
1975
1977
1979
1981
1983
1985
1987
1989
1990
1991
1992
1993
1994
1995
1996
1974-80
1981-90
1991-96
1974-96
2.49
2.44
2.20
2.02
2.05
2.11
2.61
2.32
2.49
2.44
2.47
2.47
2.45
2.46
2.45
2.54
2.21
2.29
2.47
2.31
-
14.86
-9.67
-7.52
-2.15
1.22
33.81
-5.75
0.57
-1.95
1.12
0.17
-1.16
0.71
-0.57
3.78
-2.04
2.01
0.68
0.41
8.56
6.23
6.31
5.87
5.82
4.78
5.00
3.84
6.72
7.11
7.39
7.04
6.69
6.62
6.34
6.43
6.48
5.16
6.75
5.73
-
-24.68
-0.91
-5.97
-4.67
-13.41
8.11
-5.51
63.35
5.85
3.88
-4.70
-4.91
-1.15
-4.17
1.43
-4.32
3.37
-1.60
-0.23
7.55
7.09
7.56
7.02
5.74
5.61
5.54
5.02
4.49
5.30
5.32
5.67
5.56
5.59
5.36
5.43
7.24
5.27
5.51
5.68
-
-7.37
-7.75
-5.50
-0.43
-1.28
11.22
2.09
-16.51
18.04
0.23
6.76
-1.88
0.49
-4.14
1.32
-3.31
-0.32
0.46
-1.02
Note:
The growth rate was computed on the basis of the immediate past year rather than the interval of two years
given in the table.
Sources:
Computed by the authors from CBN: Statistical Bulletin (various issues), Nigeria: Economic,
Financial and Banking Indicators (various issues); National Planning Commission: National
Development Plans (various issues); FOS: Annual Abstract of Statistics (various issues); ILO
(1996) and World Bank: African Development Indicators (various issues) and World Tables
(various issues).
Evidence from NCEMA and ASCON (2000) also identified low labour compensation (remuneration and
motivation), inadequate training, political interference, and inadequate provision of opportunity to use talents and
initiatives effectively as the bane behind low productivity in the Nigerian public sector. In addition to some of these
factors, Balogun (1983) and Oloko (1983) also identified lack of technical support staff and equipment, ineffective
supervision and gross indiscipline as important constraints to civil service productivity. This clearly shows that
factors militating against productivity growth in Nigeria are multi-dimensional.
3.2
Trends in Unemployment
The problem of unemployment has posed a great challenge to many countries (both developed and
developing). In recent times, the incidence of unemployment in Nigeria has been deep and widespread, cutting
11
across all facets of age groups, educational strata and geographical entities. One peculiar feature of the
unemployment problem in Nigeria is that it was more endemic in the early 1980s than any other period (a la official
statistics). This is clearly evident in Table 3. For instance, the unemployment rate rose from 4.3 percent in 1976 to
6.4 percent in 1980. Though it recorded some marginal decline between 1981 and 1986, the rates were relatively
higher than what obtained in the 1960s and 1970s. The unemployment rate oscillated
between 5.3 and 6.4 percent during 1980 - 85 period. This development was as a result of the lull in the economy
during the period. The economic down-turn did not only discourage new investment but also forced government to
implement stabilization measures including restrictions on importation. Given the high import-dependency of most
manufacturing enterprises, the import restriction forced many companies to operate below installed capacity,
causing most of them to close down or retrench a significant proportion of their workforce. For instance, the survey
of manufacturing companies undertaken by the Manufacturers Association of Nigeria (MAN) showed that 61.0
percent of the companies surveyed were shut down for different periods of not less than three months while between
62.0 and 63.9 percent of them disengaged over 100 workers (CBN; 1993). This development made job placement
for fresh school leavers to be exceedingly difficult. In addition, the government also placed embargo on
employment from September 1981, though relaxed in some periods (e.g. November 1982). This was implemented
pari-passu with the public sector retrenchment. Accordingly, the total disengagement from
Table 3: Nigeria: Unemployment Rates by Urban, Rural and National Classification (1976 - 1997)
Year
Urban
Rural
National
12
1976
1980
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
-
-
7.9
9.8
9.1
9.8
7.8
8.1
5.9
4.9
4.6
3.8
3.2
3.9
3.9
8.5
-
-
4.4
5.2
4.6
6.1
4.8
3.7
3.0
2.7
3.2
2.5
1.7
1.6
2.8
3.7
4.3
6.4
6.2
6.1
5.3
7.0
5.3
4.5
3.5
3.1
3.4
2.7
2.0
1.8
3.4
4.5
Sources:
Data for 1976 and 1980 were obtained from FOS (1997:99) while the rest were compiled from:
CBN - Nigeria: Major Economic, Financial and Banking Indicators , April 1998.
the federal civil service rose from 2,724 in 1980 to 6,294 in 19845. The Structural Adjustment Programme (SAP),
adopted in 1986, had serious implications for the short run unemployment problem. Contrary to the expectations of
SAP, which was geared towards encouraging greater employment opportunities in the private sector (especially
among the small-medium enterprises), the unemployment rate rose from 5.3 percent in 1986 to 7.0 percent in 1987.
This was partly accounted for by the organizational down-sizing, re-engineering and rationalization policies which
accompanied the introduction of SAP, especially in the private sector. This was further compounded by the
continuation of staff retrenchment and placement of embargo on employment in the public sector. Besides, the new
policy orientation brought about some structural changes within the Nigerian labour market. Sectors such as the oil,
banking and the external sectors became the "blue chips" as against the public and industrial sectors which used to
be the "prime" of the labour market prior to the adoption of SAP in 1986. This development consequently created
some structural and frictional unemployment problems in the country. When this structural and frictional
unemployment is considered along with the lack of job placement for fresh graduates, the situation becomes more
precarious. As pointed out by Umo (1996), an annual average of about 2.8 million fresh graduates enter the
5
For details see the Annual Abstract of Statistics of the Federal Office of Statistics (various issues), Lagos
13
Nigerian labour market, with only about 10 percent of them getting employment. This, no doubt, portrays
unemployment as a very serious problem in the country.
Evidence from Table 3 shows that unemployment fell very significantly after 1987. It fell consistently
from 7.0 percent in 1987 to 3.1 percent in 1991. Although it rose marginally to 3.4 percent in 1992, the
unemployment rate, however, consistently declined appreciably to 1.8 percent in 1995 before rising to 3.4 and 4.5
percent in 1996 and 1997, respectively. However, the estimated unemployment gap for Nigeria, indicates that the
unemployment rate varied between 7.27 and 8.0 between 1990 and 19986. Why is the gap between the estimated
and the actual unemployment rate as high like this? Raheem (1993) and Ohiorhenuan (1986) exp lained that only
recorded open unemployment is published by the official statistics. Many people who felt disenchmented with
searching for jobs refused to register thereby leading to gross under-estimation of the unemployed. Okigbo (1986,
1991) also pointed out that the concept of labour force adopted in the Nigerian Labour Force Statistical Survey,
which
excluded people that were less than 15 and above 55 years but actively working, is an important factor for gross
underestimation of unemployment in the country. This is further compounded by gross inconsistency in government
documents. For instance, all surveys prior 1983 used 55 years as the cut-off point for working age but in 1983, it
was raised to 59 years which was later raised to 64 in 1997. Yet, some categories of people above the age of 64 still
remain government employees e.g. Judges. This again gives room to underestimation. As argued by Okigbo
(1991), it also excludes people who have been categorized as incapable of working but are willing to work (e.g. the
handicapped). Also excluded from the labour force are the full housewives who are willing to be engaged in a paid
job. The preponderance of unpaid family workers as a proportion of active workers, as presented by the World
Bank (1999) is also a potential source of underestimation of unemployment or underemployment in the country.
Thus, taking cognisance of the above, Okigbo (1991: 13), estimated the unemployment rate for 1986 to be 28
percent.
6
For details see Federal Republic of Nigeria: Fourth National Development Plan (1981 - 1985) , Federal
Ministry of National Planning, Lagos, and Federal Republic of Nigeria: National Rolling Plan ,
Abuja (Various Issues).
14
In spite of the differences, the official unemployment rate appears to be on a declining trend. The observed
downward trend may be attributed partly to the intensification of the implementation of the Agricultural
Development Programmes (ADPs) and the Accelerated Development Area Programmes (ADAPs). The latter was
later transformed into the Directorate of Food, Roads and Rural Infrastructure (DFRRI). The activities of the
National Directorate of Employment (launched in 1986), the Peoples Bank, Better Life for Rural Women
Programme, among others, may have also accounted for the decline. The intensification and expansion of the
informal sector activities could also be an important factor during this period. Besides the consistent view of the
CBN's annual reports on this issue, the evidence from DPC (2000) also shows that the informal private sector
expanded in scope of activities and in pattern of employment, with more graduates participating in the sector.
Available data also suggest that unemployment rates vary by rural-urban residence, education, age,
professional classification and states. Evidence from Table 3 shows that the average annual rate of unemployment
was higher in the urban areas than in the rural areas for each year between 1984 and 1997. The influx of rural
dwellers into the urban centres in search of better employment opportunities could have accounted for the observed
pattern.
The dynamics of the linkage between educational status and the unemployment rate in Nigeria is of crucial
importance. In the 1970s, the people most seriously affected by unemployment were those with no schooling or
those with primary education. As shown in Table 4, "no schooling" category accounted for 22.6 and 65.4 percent of
the unemployed in 1974 and 1976, respectively, while the primary school leavers correspondingly accounted for
64.3 and 26.5 percent. The incidence of unemployment on these categories of people declined very significantly in
the 1980s and 1990s. The severity of this problem varies according to
Table 4: Composite, Urban and Rural Distribution of Unemployed by Educational Level December 1993 to
December 1997 (Per Cent).
Educational
No. Schooling
Primary
Secondary
Post Secondary
All Levels
Level
Composite
1974
1976
1983
1985
Dec. 1990
Dec. 1992
22.6
65.4
7.1
22.6
12.2
19.1
64.3
26.5
43.5
23.9
22.9
10.4
11.8
0.3
48.7
51.1
60.9
65.6
0.3
0.0
0.2
3.3
4.0
4.9
100.0
100.0
100.0
100.0
100.0
100.0
15
Note:
Sources:
The Data for Primary for the period 1974 - 1985 contained below primary and primary education
levels.
The figures for 1974 - 1985 were compiled from Ige, C. S. (1986:20) "Unemployment in Nigeria:
Spatial and Sectoral Patterns and Trends," Annual Conference of the Nigerian Economic Society
1986, Kaduna, May 13 - 16, pp. 20, while those for 1990 and 1992 were obtained from FOS
(1997:101). The data for 1993 - 1997 were compiled from Federal Republic of Nigeria: The
Economic and Statistical Review , The National Planning Commission, Abuja (1996 - 1998 issues)
residential classification. For instance, while the problem was more severe for the "no schooling" rural dwellers, the
primary school leavers residing in urban centres had a greater burden than their rural counterparts. In contrast, the
incidence of unemployment on secondary school and post secondary school leavers increased very substantially
during the period.
The evidence from the educational classification is further reinforced by the evidence from the registered
unemployed. As shown in CBN (1997: 170 and 171), more than 90.0 percent of the registered unemployed belong
to the lower level workers. The number of this category of people registered with the Ministry of Employment,
Labour and Productivity rose from 11,732 in 1970 to 23,239 in 1975 and 256,623 in 1980. The figure however
declined thereafter. In contrast, the number of registered unemployed professionals which dropped from 518 in
1970, to a mere 135 in 1978, rose very remarkably from 1984. It rose from 2,514 in 1984 to 16,293, 22,206 and
32,942 in 1988, 1992 and 1995, respectively. This represents 1.8, 12.3, 19.7 and 28.7 percent of the total registered
Dec. 1993
Dec. 1994
June 1995
Dec. 1996
Dec. 1997
17.2
13.3
16.2
48.0
21.1
17.9
13.2
13.4
10.8
11.8
60.9
68.7
59.5
52.8
46.2
4.0
4.8
5.8
18.4
20.9
100.0
100.0
100.0
100.0
100.0
Urban
Dec. 1993
Dec. 1994
June 1995
Dec. 1996
Dec. 1997
15.3
16.3
17.7
6.8
13.4
17.7
17.2
18.8
11.9
16.8
60.0
71.8
58.3
62.7
48.3
7.6
4.7
5.2
18.6
21.5
100.0
100.0
100.0
100.0
100.0
Rural
Dec. 1993
Dec. 1994
June 1995
Dec. 1996
Dec. 1997
17.6
14.8
9.4
20.4
22.8
17.9
12.3
16.8
10.6
10.7
61.1
68.0
65.4
50.7
45.7
3.4
14.9
8.4
18.3
20.8
100.0
100.0
100.0
100.0
100.0unemployed people, as opposed to an annual average of 1.7 percent between 1970 and 1978.
16
The demographics of unemployment is shown in Table 5. Unemployment has been unevenly distributed
across the age groups with young people bearing the burden of unemployment. As shown in the table, the
unemployed persons are mostly youths aged 15 - 24 years. The proportion of this category of unemployed
fluctuated between 41.6 and 70.4 percent during 1993 - 1997 period. It recorded an annual average of 56.3 percent
during the period. This observation is a reconfirmation of the dominance of secondary school leavers among the
unemployed, since most of them fall into this age group. Another prominent age group is 25 -44. It is worrisome to
observe that while the percentages of other groups unemployed have been declining consistently over time, those of
this group have been on the upward trend. This perhaps portends the widening gap between the output produced by
the tertiary institutions and the skill requirements of the labour market. The rising trend of graduate unemployment,
as observed by many analysts, may have contributed very significantly to the rising wave and sophistication of
crime in the country (e.g. Albert, 2000). As also shown in Table 5, an inverted U-shaped trend is observed for the
age group 45 - 59, with 1995 recording the peak of 13.8 percent. The current wave of self-employed activities may
have partly accounted for this observation. The inclusion of age group 60 - 64 in the current labour force statistical
survey
Table 5:
Unemployment by Age Groups (1993 - 97)
(Per Cent)
Source: Compiled and Calculated from FOS: Annual Abstract of Statistics 1998.
is an advancement on the previous exercises. The inclusion of this set of people will reduce, to some extent, the
wide gap between the published unemployment rate and the actual one. The exclusion of this group in the past led
to serious underestimation of unemployment.
In recent times, attempts have been made to characterize unemployment by its duration (long and short
term unemployment). The increase in duration of unemployment represents the most serious labour market
15-24
25-44
45-49
60-64
1993
69.0
25.2
5.8
N.A
1994
70.4
21.0
8.6
N.A
1995
57.5
28.7
13.8
N.A
1996
42.9
46.0
11.1
N.A
1997
41.6
49.7
6.0
2.7
Annual Average
1993-97
56.3
34.1
9.1
-development. Long term unemployment has become a chronic problem in Nigeria (Okigbo, 1986; Oladeji, 1994).
17
As pointed out by Oladeji (1994), 75.5 and 13.61 percent of those sampled in the Graduate Employment Tracer
Study of the Manpower Board in 1986 has been unemployed for 13 - 34 and 25 - 30 months, respectively. Only
10.8 percent were unemployed for the duration of 1 - 12 months. This type of unemployment has been linked to job
transition patterns. This approach emphasizes hiring people from the public sector by the private sector, or between
firms, than from the unemployed people. It thereby makes the pool of the unemployed to be increasingly
homogenous. The risk attached to long- term unemployment has been well acknowledged in the literature (e.g.
Okigbo, 1986; Alhson and Ringold, 1996). The longer an individual is unemployed, the more difficult it is to find
work. It is therefore important to put up active labour market programmes for this category of people.
The national unemployment rates mask the peculiarities of the states. For instance, states such as
the Old Bendel, Imo, Rivers and Cross Rivers generally experienced very high unemployment rates as
opposed to the low rates experienced in Niger, Katsina, Kwara and Kano. Rural unemployment was
common in Borno and Kwara States while Anambra, Lagos, Plateau, Sokoto, Ogun and Oyo mostly
experienced high urban unemployment rates. (See FOS (1985:112-123) and FOS (1990:269-270) for
details). An important feature of this approach is the gender structure of unemployment. As shown in
Table 6, about 19 states (including Abuja) of the Federation clearly indicate higher female unemployment
rates, with twelve of them from the northern part of the country. This perhaps indicates that more females
are now interested in paid employment. An important feature of female unemployment is that, this period
coincided with the time of high female criminality. As pointed out by Oloruntimehin (2000), since 1980s,
female criminality has not only increased in number but has also become more serious and significant
over the years. The existence of this linkage therefore calls for an urgent attention to female
unemployment in the country.
The incidence of underemployment or disguised unemployment has been acknowledged in the
literature as a serious constraint to economic progress. In fact, its effects could be worse than those of
open unemployment (Raheem, 1993). FOS (1997) considers underemployment as a reflection of the
extent to which some human resources are rendered potentially idle.
This problem has contributed significantly to the widening gap between the reported and actual
unemployment in Nigeria. Underemployment has been particularly high in the country. In 1984, 7.1 and
21.1 percent was recorded for the urban and rural areas, respectively. This later rose to 11.2 (urban) and
28.7 (rural) percent in 1992. As shown in Table 7, underemployment rates were higher in the rural areas
than the urban centres. In almost all the cases, the rural underemployment rate is twice the rate of urban
18
underemployment. Besides, irrespective of the place of residence, female underemployment has been
higher than that of their male counterparts. The predominance of full housewives in the labour force may
partly account
19
Table 6: Unemployment Rates By States in Nigeria (1991 and 1993)
Source: National Population Commission (1998): 1991 Population Census of the Federal Republic of Nigeria; Analytical
Report at the National Level, Abuja. The figures for 1993 were obtained from FOS (1997): Socio-
Economic Profile of Nigeria 1996, Lagos , p. 102.
Table 7: Under-employment Rates in Nigeria (1984 - 1996)
Year
Urban
Rural
Male
Female
Total
Male
Female
Total
December 1984
December 1992
September 1993
June 1996
1997
7.1
9.5
17.3
8.9
NA
8.1
14.3
18.0
14.1
NA
7.1
11.2
16.4
11.2
9.8
21.1
27.8
20.0
20.0
NA
25.3
30.4
24.9
20.6
NA
21.1
28.7
21.8
20.6
10.7
Source: Compiled from FOS (1997: 103). The data for 1997 were sourced from CBN: Annual Report and Statement of
Accounts , 1997.
States
1991
1993
Both Male and Female
Male
Female
Male and Female
Unemployed
Population
Unemployed
Rate
Unemployed
Population
Unemployed
Rate
Unemployment
Population
Unemployment
Rate
Unemployment
Rate
Abia
Akwa-Ibom
Adamawa
Anambra
Bauchi
Benue
Borno
Cross Rivers
Delta
Edo
Enugu
Imo
Jigawa
Kaduna
Kano
Katsina
Kebbi
Kogi
Kwara
Lagos
Niger
Ogun
Ondo
Osun
Oyo
Plateau
Rivers
Sokoto
Taraba
Yobe
Abuja
Nigeria
79,335
76,021
31,589
49,322
32,425
30,129
23,526
50,534
64,824
56,030
77,707
92,792
18,772
46,331
39,580
21,734
8,160
47,655
11,135
92,825
16,622
15,053
42,086
13,728
20,208
33,500
176,214
11,401
13,861
9,544
8,900
1,311,603
9.0
9.2
5.1
4.8
3.2
3.6
3.1
7.8
7.2
7.6
7.0
11.8
3.1
5.0
3.0
2.8
1.7
6.6
1.8
3.7
2.5
1.4
2.9
1.6
1.3
3.9
12.6
1.1
3.2
2.7
6.8
4.7
37,856
40,999
21,522
21,778
21,413
21,506
15,197
29,680
38,992
35,592
34,828
42,663
14,023
30,400
28,799
16,074
5,841
27,323
5,718
53,171
11,522
8,067
23,246
7,255
11,122
22,236
102,529
7,611
10,249
6,693
5,910
753,909
8.3
9.9
5.0
3.8
2.5
4.3
2.7
8.4
8.5
8.8
6.1
10.3
2.6
4.1
2.5
2.3
1.5
7.3
1.8
3.6
2.2
1.5
3.3
1.8
1.5
3.6
13.1
0.9
3.2
2.3
5.6
3.4
41,479
35,022
10,067
27,544
11,012
8,623
8,329
20,854
25,832
20,434
42,879
50,129
4,749
15,931
10,981
5,660
2,319
20,332
5,417
39,654
5,100
6,986
18,840
6,473
9,086
11,324
73,685
3,790
3,612
2,851
2,990
548,794
9.7
8.5
5.3
6.0
7.5
2.5
4.5
7.0
5.9
6.2
7.7
13.4
6.9
9.4
5.8
7.0
3.3
5.8
1.8
3.8
3.4
1.3
2.5
1.3
1.2
4.9
12.0
2.8
3.1
5.0
11.3
5.3
4.2
5.4
1.5
2.8
1.0
1.2
0.5
3.4
5.9
5.1
3.5
9.1
0.2
3.6
1.3
0.5
0.6
2.8
0.7
2.8
0.5
1.7
1.1
1.6
1.3
1.4
7.4
0.1
0.9
0.2
4.2
-
20
for the higher rate of female underemployment. A large proportion of unpaid family workers as a share of active workers
which was estimated by the World Bank (1999: 285) at 23.5 percent could also be a factor contributing to the bourgeoning
rate of underemployment in Nigeria. To further reinforce the reason for higher female under-employment, we decompose the
unpaid family workers-active workforce ratio into gender classification. The females constituted 14.9 percent as opposed to
8.6 percent for male.
The rates of underemployment also vary across the states. For instance, in 1993 high rates of
underemployment featured in Enugu (5.74%), Ondo (3.50%), Sokoto (5.12%), Adamawa (4.80%) and Taraba
(4.61%). States with less than 1 percent underemployment rate were Delta, Abia, Cross Rivers, Oyo, Kaduna, Kogi
and Niger. Female underemployment was also serious in the following states. Jigawa (10.4%), Sokoto (10.13%),
Taraba (7.5%), Adamawa (7.13%) Enugu (5.4%) and Bauchi (5.15%) (FOS, 1997).
The seriousness of the unemployment problem has attracted government attention over the years.
Employment generation featured prominently in the past medium-term National Development Plans (1962 - 1985).
This led to the establishment of several government parastatals (whose primary objective was to create employment
opportunities) in addition to the creation of institutions such as the Industrial Training Fund (ITF), to drastically
reduce the problem of underemployment. The adoption of Structural Adjustment Programme also ushered in the
National Directorate of Employment (NDE) whose primary responsibility was to generate employment
opportunities with emphasis on the development of entrepreneurship and self employment. Besides NDE, other
programmes, with employment implications, established by the government include: the Directorate of Food, Roads
and Rural Infrastructure; the Better Life for Rural Women/Family Support Programme; the Development of Small-
Medium Scale Enterprises; the Raw Materials Research and Development Council; the Peoples' Bank of Nigeria and
the Community Banks. The current poverty alleviation programme also focuses on the unemployed. In spite of
these efforts, unemployment remains a grave problem in Nigeria.
3.3
Trend Analysis of Productivity and Unemployment
A review of the existing descriptive analysis of the linkage between productivity and unemployment shows
some degree of variations. Maddison (1982) showed that the growth of total employment since 1970 paralleled that
of real GDP in industrial countries. They both accelerated and decelerated in the same direction. By implication,
productivity and unemployment are inversely related. Schaik and Groot (1997) also presented the European
countries' experience of high growth of industrial productivity with unprecedented low rates of unemployment in the
21
1950s and 1960s. Grilli and Zanalda (1995) also observed that growth of total employment maintained a positive
relationship with real GDP in developing countries between 1960s and 1980s. In contrast, Krugman (1994) found
no visible pattern among some developed countries between productivity and unemployment. Some countries with
the best unemployment performances turned out to be the worst productivity performances. What is the pattern of
relationship between productivity and unemployment in Nigeria? A brief highlight of the stylized facts is provided
below.
A cursory look at Figure 2, shows that for most part of the period of analysis, unemployment and
productivity moved in opposite direction. For instance, between 1981 and 1990, periods of high rate of
unemployment were associated with period of declining/low productivity. Labour productivity was relatively higher
between 1990 and 1996 than what obtained in the 1980s, and the unemployment rate declined up to 1995. The wide
gap between unemployment and productivity between 1991 and 1996 tends to suggest that productivity and
employment were correlated during the period.
The trend analysis seems to suggest an inverse relationship between unemployment and productivity, thus
supporting a positive linkage between employment growth and higher productivity. However, it is difficult to use
this type of analysis to determine the direction of causality between the variables, hence one cannot clearly show
which of the theoretical postulates holds in the Nigerian situation. This, therefore, informs the use of causality tests
as is done inthe next section.
IV.
EMPIRICAL LINK BETWEEN PRODUCTIVITY AND UNEMPLOYMENT IN
NIGERIA
4.1
Methodology
The existence of correlations in descriptive analysis may not necessarily imply causality as two variables
may show some correlations even when they are not directly related. It might be possible that they share the same
trend from a third variable i.e. an external factor may influence the two variables in the same way. The use of
causality tests, therefore provides the opportunity to carry out a more scientific analysis of the issues in question. As
argued in the literature, the use of causal hypotheses makes scientific analysis more determinate and the resulting
conclusions more specific.
22
23
Figure 2
24
The commonly used causality tests in econometric modelling are Granger and Sims tests. While the former
uses the lagged values of a particular variable to explain the behaviour of another variable, the latter uses lead
values. The loss of degrees of freedom often associated with the use of the Sims approach makes its application
restricted in econometric analysis. Hence this study employs the Granger causality test.
The standard Granger causality test examines whether past changes in one variable, X (say, productivity)
help to explain the current changes in another variable Y (e.g. employment/unemployment), over and above the
explanation provided by past changes in Y. If, otherwise, then one concludes that X (productivity) does not Granger
cause Y (employment/unemployment). To determine whether causality runs in the other direction, from Y to X (or
employment/unemployment to productivity), one simply repeats the experiment, but with X and Y interchanged.
.....(5)
y_t = SUM from { i=1 } to { k } "_i { Y } _ { t-i } + SUM from { i=1 } to { k } beta_t~X SUB {t-i} +~epsilon _t
.....(6)
X_t = SUM from { t=1 } to { k } { 1_i } X _ { t-i } + SUM from {t=1 } to {k } { (_t } Y_ { t-i } + V_t
The above scenario may be given in a Granger causality sense thus:
where y and x could stand for either of the variables under consideration (productivity,
employment/unemployment). If ß i = ß2 = ..... = ß k = 0 then, x does not Granger cause y, hence, we accept the null
hypothesis. The same applies to equation 6.
The use of Granger causality test is an important scientific way of determining the direction of causation.
However, determining the nature of the relationship is outside its scope. This, therefore, informs the fitting of
simple regression equations, with a view to making the conclusions and policy deductions more determinate and
focussed. Depending on the outcome of the Granger causality tests, a bivariate model is fitted with any of the
variables (productivity or unemployment) serving as the dependent variable and the other serving as the explanatory
variable, with an adjustment mechanism of one lag and a disequilibrium term. The simplicity of this model does not
warrant an explicit specification here.
The data for this analysis were obtained from many sources: FOS, Annual Abstract of Statistics (various
issues) and Social Statistics in Nigeria (various issues); CBN, Statistical Bulletin (various issues) and Nigeria: Major
Economic, Financial and Banking Indicators , April 1997; ILO, Employment Policy Strategy Formulation Mission to
25
Nigeria , 1996, and International Labour Statistics and World Bank: African Development Indicators , World
Development Indicators (various issues) and World Tables (various issues).
4.2
Empirical Results
The Granger Causality tests carried out examine the direction of relationships between productivity and
employment, and productivity and unemployment. In order to get a clearer picture of the structure of production
and employment, the economy is divided into three sectors: agriculture, industry and services. However, the non-
availability of public data on the services sector unemployment could not allow us to consider the services sector in
the analysis. The results of the Granger Tests are in Table 8.
Evidence from productivity and employment linkage shows bi-causal relationships in all the cases except in
the agricultural sector. This evidence tends to reject the neoclassical framework for productivity and employment
linkage, which proposes a unidirectional relationship running from employment to output. As shown in Table 8, bi-
causal relationships exist between industrial employment and industrial productivity. However, this could not be
established in the agricultural sector. The rejection of the existence of a feedback relationship running from the
sector's employment to productivity could be due to the prevalence of redundant workers in the sector. The
historical antecedent of the sector tends to support the result. For instance, the sector constituted the largest sectoral
employment in the country. As pointed out by ILO (1996), the sector employed 71.7, 60.0, 60.7 and 59.8 percent of
the total workforce in 1960, 1980, 1990 and 1996, respectively. Thus, given the subsistent nature of the sector's
production, the tendency of diminishing marginal productivity seems operative. Thus, increased productivity in the
sector may not require additional employment but rather an optimal utilization of the existing underutilized
resources such as labour and land.
Evidence from productivity and unemployment linkage shows that a unidirectional relationship exists
between national labour productivity and national unemployment. The direction of causation runs from total
productivity to unemployment (Table 8). By implication, historical and current level of labour productivity clearly
predict the level of national unemployment in Nigeria. The Granger causality test however shows the direction of
causation but not the nature of the relationship. This is, however, remedied with the regression results in Table 9.
This Table shows that higher current national labour productivity tends to result in the absorption of more workers,
26
thereby reducing the level of unemployment. The relationship is established at 5.0 percent significance level.
However, arising from additional labour absorption that accompanied increased labour productivity, the law of
marginal productivity, ensues, hence the level of labour absorption declined in the next quarter. Albeit, this
relationship is not statistically significant. Expectedly, the cummulation of unemployed people over time tends to
exert some positive influence on the current level of unemployment.
Table 8: GRANGER CAUSALITY TESTS
Productivity and Employment
F-
Probability
Remark
Statistic
Total Employment (TE) ----> Total Productivity (TP)
Total Productivity (TP)----> Total Employment (TE)
Agricultural Productivity(AP) ----> Agricultural Employment (AE)
Agricultural Employment(AE) ----> Agricultural Productivity (AP)
Industrial Productivity (IP) ----> Industrial Employment (IE)
Industrial Employment (IE) -----> Industrial Productivity (IP)
9.44
7.08
5.45
2.20
5.25
19.68
0.00
0.00
0.00
0.12
0.00
0.00
Accept
Accept
Accept
Reject
Accept
Accept
Productivity and Unemployment
Total Productivity (TP) ---> National Unemployment (NU)
National Unemployment (NU) -----> Total Productivity (TP)
Industrial Productivity (IP) -----> Urban Unemployment (UU)
Urban Unemployment (UU) -----> Industrial Productivity (IP)
Agricultural Productivity (AP) -----> Rural Unemployment (RU)
Rural Unemployment (RU) -----> Agricultural Productivity (AP)
4.19
1.81
3.79
12.67
1.19
0.43
0.02
0.17
0.02
0.03
0.02
0.08
Accept
Reject
Accept
Accept
Reject
Reject
The direction of causation between industrial labour productivity and urban unemployment is established to
be bi-directional (Table 8). In contrast with what obtained under national labour productivity, evidence from the
industrial sector tends to imply the use of less labour for producing the same volume of output. For instance, one
percent increase in labour productivity raises the unemployment rate by 0.8 percent (Table 9). This relationship is
established at 1.0 percent level of significance. Perhaps resulting from the lower labour cost, the consequent
reduction in commodity price generates an increase in demand. Thus, following the accelerator principle, additional
27
labour is employed in the next quarter. This is evident in the relationship between current level of urban
unemployment and the last quarter productivity level7.
The relationship between agricultural productivity and rural unemployment could not be clearly
established. This finding suggests that the rural unemployment problem has a life of its own and is not simply part
of a generalized deterioration in agricultural performance. Besides, Table 9:
Regression Results
Variables
Constant
Total Productivity ()TP)
Total
Unemployment
()TU)
0.01
(0.25)
-0.56
Urban
Unemployment
()UU)
-0.02
(-2.58)*
Rural Unemployment
()RU)
0.01
(1.82)***
(-1.92)**
)TPt-1
)TUt-1
Industrial Productivity ()IP)
)IPt-1
)UUt-1
Agricultural Productivity()AP)
)APt-1
)URt-1
0.28
(1.05)
0.89
(13.07)*
0.82
(3.33)
-0.62
(-2.64)
-0.35
(-1.24)
-1.85
(-3.49)*
3.05
(4.22)*
2.89
(3.26)*
ECM(-1)
-0.02
(-3.97)*
0.16
(3.24)*
-2.08
(-2.35)*
7
The existence of bi-causal relationship between industrial labour productivity and urban unemployment
suggests the existence of simultaneity bias. Thus, using instrumental variable estimation
technique, we regressed urban unemployment rate on industrial productivity. The
unemployment rate is positively related to productivity. However, the relationship is not
statistically significant.
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Note:
TP = Total Productivity; IP = Industrial Productivity; AP = Agricultural Productivity; ECM (-1) = Error
Correlation Factor; Adj. R2 = Adjusted R2 and D. W. = Durbin-Watson Statistic. Also, *, ** and ***
indicate that the variables are significant at 1, 5 and 10 percent, respectively.
the evidence also tends to suggest that rural underemployment may be more important to agricultural production
than rural unemployment. In spite of this, we fitted an equation to examine the impact of agricultural productivity
on rural unemployment. Evidence from Table 12 shows that higher labour productivity results in more employment.
The labour intensive nature of this sector gives more credence to this relationship. And following the cobb-web
theory, an increase in agricultural production in excess of demand creates a glut in the subsequent year thereby
resulting in laying-off of workers in the subsequent period. Thus, the lagged value of labour productivity raises the
unemployment rate in the subsequent period.
The statistics associated with the models (e.g. adjusted R2, F-statistic and D. W.) are well behaved.
V.
POLICY IMPLICATIONS OF THE FINDINGS AND CONCLUSIONS
The analysis presented above established some stylized facts about productivity and unemployment in
Nigeria. It is clearly evident that productivity is low in Nigeria. Unemployment, on the other hand (when combined
with underemployment) is very high. Evidence from the analysis of productivity and employment linkage shows bi-
causal relationships in all the cases, except in the agricultural sector. The evidence therefore rejects the neo-classical
framework for productivity and employment linkage. The results of the relationship between productivity and
unemployment are mixed. The results show that bi-causal relationships exist in the industrial sector while a
unidirectional relationship (running from productivity to unemployment) is established at the national level.
However, no linkage is established in the agricultural sector, thereby suggesting that rural unemployment, in most
2
Adj. R
0.77
0.35
0.61
F-Statistic
70.52*
9.09*
24.92*
D.W.
1.75
2.01
2.43cases, may not arise from the generalized deterioration in agricultural performance.
29
The results also show that contrary to the general expectation that an increase in productivity leads to a
reduction in employment (particularly, where there is no compensating increase in overall demand), labour
productivity is followed by labour absorption at the current level, at both the national level and agricultural sector.
This relationship, particularly in the agricultural sector follows the traditional cobb-web theory. The opposite
however exists when a lagged value is incorporated. The evidence from the industrial sector supports the general
notion, where employers use less labour to accomplish the same volume of output as productivity rises. Meanwhile,
following the accelerator principle, additional labour is absorbed in the next period.
Some policy implications are discernible from the findings. Since more employment means more income
for the poor, which in turn implies a greater demand for locally produced basic consumption goods, it is imperative
for government to ensure growth and development of the rural and small-scale urban sectors. This should consider,
very seriously, encouraging people to establish more labour-intensive small scale enterprises which have the
propensity to create more jobs and higher incomes. This programme, if well implemented, could reverse the rural-
urban drift which has seriously affected the urban employment. However, in order to achieve this goal, a
complementary policy of removing factor-price distortions and promoting labour-intensive technologies of
production may be required. As a corollary to this, industrial policy can be directed at supporting industries with
high growth potential in order to combine the benefits of rising productivity with the net generation of new jobs.
Appropriate incentive structures should be designed for investors participating in this programme.
In line with our finding from the industrial sector, while acknowledging the benefits of economic
competition, it should however be confined to relative productivity rather than be allowed to spread into destructive
wages and cost cutting exercises. While this is a sacrifice from the part of the private sector, public investment
should also be directed at improving productivity and supporting job creation. This involves programmes to raise
workers' skills and investment to improve infrastructure as well as create the enabling environment for enterprises to
strive.
One major finding is that productivity and unemployment are inversely related. This suggests the need for
policies to enhance productivity. Critical among these include:
recent developments have shown that human investment is an important factor in any country's
productiveness. In fact, there exists a level of human investment at which the productivity rate attains its
30
minimum. Thus, the need to put in place a systematic manpower development programme (especially the
skill acquisition type) both in the public and private sectors is imperative;
the institutionalization of adequate penal and reward system is a sine-qua-non to improved productivity.
Sequel to this is the need to adopt a satisfactory income policy. This income policy should meet certain
requirements deemed commensurate with the levels of maximum utilization of labour input; and
government should create appropriate enabling environment to promote a sustained effective aggregate
demand in order to maintain the required level of domestic production.
31

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