




































American Economic & Social Review; Vol. 3, No. 1; 2018  

ISSN 2576-1269   E-ISSN 2576-1277 

Impact Factor: 3.9 

                                            Published by Centre for Research on Islamic Banking & Finance and Business, USA 

 

 

32 

 

Unemployment and Output Growth: Evidence from Upper-Middle-

Income Countries in Sub-Saharan Africa 

 
 

Ihensekhien Orobosa Abraham
 
Ph.D 

Department of Economics, Banking and Finance 

Benson Idahosa University, Benin City, Edo State, Nigeria 

Email: oihensekhien@biu.edu.ng Phone: +2348035843175 

 

 

Aisien Leonard Nosa Ph.D 

Department of Economics, Banking and Finance 

Benson Idahosa University, Benin City, Edo State, Nigeria 

Email: lasien@biu.edu.ng 

 

 

Received: November 6, 2018      Accepted: November 10, 2018           Online Published: November 16, 2018        

 

 

Abstract 

Several studies have found a negative relationship between unemployment rate and output growth rate. But such has 

not been ascertained concerning upper middle-income countries in Sub-Saharan Africa (SSA). Hence this paper 

examined this relationship using Panel Least Squares and Ordinary Least Squares estimation techniques based on 

annual series data from 1991 to 2017. The paper observed that the average output growth rate for upper middle-

income countries in SSA in the period of the study was 6.36% while that of the unemployment average rate was 

15.87%. The results of the panel Least Squares estimation reveals the existence of negative relationships between 

unemployment rate and output growth rate. In the country specific study, results from Botswana, Gabon, Mauritius 

and South Africa shows a positive relationship between unemployment and output growth rates revealing a case of 

non-inclusive growth. However, Equatorial Guinea and Namibia data on unemployment and output growth had 

negative relationships. The counter factual analyses conducted on the unemployment variable in term of some 

percentage reduction indicated that as more persons are employed there will be an increase in output growth. The 

findings, therefore suggests that the  government should  create more jobs based on labour intensive industries in 

upper middle-income countries in SSA, that the ratio of output growth needed to maintain  stable level of 

unemployment rate could be sustained when there are boost in economic activities. Countries in upper middle-

income in SSA  that exhibited positive relationship between unemployment rate and output growth rate should 

concentrate more on how to increase the level of output growth rate through the boost in economic activities. 

Governments of these upper middle-income countries should have good policy mix focused on the reduction of 

unemployment at all levels. 

    

Keywords: Upper middle-income countries, unemployment, output growth, counter factual analysis, Okun’s law.  

 

1. Introduction 

The Sub-Saharan Africa (SSA) consists of all African states that are partially or fully located South of the Saharan 

Desert (United Nations, 2011). The SSA population is currently estimated at 936.1 million people and the SSA 

region is made up of forty eight countries (World Bank, 2018). 

The International Labour Organization (ILO) report for 2017 indicated that the number of unemployed persons 

worldwide will hit over 201 million persons in 2017, with additional 2.7 million persons expected in 2018. The 

survey indicated that the third world countries, especially Africa is expected to be worst hit, where the number of the 

unemployed and poverty are high. The challenges of high unemployment rate and slow output growth are not only 

experienced by the developing countries by however, the developed countries over the years have adopted good 

economic and political policies to reduce the level of unemployment. In the developing countries unemployment 

mailto:oihensekhien@biu.edu.ng
mailto:lasien@biu.edu.ng


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33 

 

challenges does not only constitute a high private cost for the individual, it is a huge cost to the government (Sachis-

i-Marco, 2011; Abel, Bernanke & Croushore, 2008; Ihensekhien & Ovenseri-Ogbomo, 2017). 

Ihensekhien etal (2017) observed that the average GDP growth rate for Low income countries in SSA stood at 3.8 

and the unemployment average rate was 5.9 in the time frame of 1991-2013. There empirical observation agrees 

with that of Okun (1962) that high rate of unemployment has been observed to affect the rate of output growth 

negatively. The unemployment level in a country also determines the economic well-being in the long run.  

The studies of Romer and Weil (1992) revealed that unemployment can be an inhibitor to output growth in a 

country, in terms of deterioration of human capital resulting on a negative effect on output leading to lost of future 

income and saving which are harmful to output growth. 

Obadan and Iyoha (1996) opined that the national economic objectives of any country is the attainment of full 

employment (reduction of unemployment to a minimum level) in order to have rapid output growth over time.  

According to Nkurunziza and Bates (2004) and Ihensekhien (2016) the SSA countries output growth rates was 

observed to be not high enough to make true impact in the pervasive unemployment rates that would enable the SSA 

countries to catch up with other developing countries of the world in the nearest future. 

World Bank (2018) development indicators based on income group classification of countries revealed that the 

following SSA countries are upper middle income countries: Botswana, Gabon, Equatorial Guinea, Mauritius, 

Namibia and South Africa.   Below are some basic economic facts of this upper middle in countries in SSA: 

Botswana is ranked as the 2
nd

 among forty eight of SSA with high income, it has a population of 2.2 million people 

with an average GDP growth rate of 4.52%, average unemployment rate of 18.59%, inflation rate of 2.8%. 

Equatorial Guinea has a population of 1,324,762 million people with an average GDP growth rate of 20.19, average 

unemployment rate of 5.76%, a median age of 22.2 years and her life expectancy at birth is 57.68.  Gabon has a 

population of 1.5 million, inflation rate of -0.01%, average unemployment rate of 18.46%, crime index of 47.69 and 

safety index of 52.3 and GDP growth rate of 2.28%. Mauritius is made up of a population of 1.3 million with 

average GDP growth rate of 5.51 %, average unemployment rate of 8.31% and inflation rate of 1.0%. Namibia has a 

mean unemployment rate of 20.52%, inflation rate of 6.5%, a human population of 2.3million and GDP growth of 

4.18%. South Africa is the second largest economy in SSA; it is an industrialized economy, with a population of 

55.9 million, an average unemployment rate of 23.61 %, inflation rate of 6.3% and a mean GDP growth rate of 

2.45%. South Africa has a safety index of 23.37 that is considered low but with a high quality of life index of 135.57 

(World Bank, 2018).  

The economic conditions of the upper middle income countries in SSA are marred with high incidence of crimes, 

poverty, and low quality of life, severe economic and social costs of all kinds as a result of high rate of 

unemployment. However, the empirical study of Okun’s has been verified in many countries, but this has not been 

verified in upper middle income countries in SSA based on the recent classification of countries into income group 

by the World Bank(2018). Hence, there exists a gap the literature with respect to the relationship between changes in 

unemployment and output growth in the upper middle income countries in SSA.  The statement of the problem and 

the identified research gap led to raised the following objectives of this paper: to evaluate the empirical nexus 

between unemployment and output growth, to ascertain the rate of output growth ratio required to maintain 

minimum level of unemployment rate, also the counter-factual impact of unemployment rate reduction based on 5%, 

7.5%, 10% and so on the output growth.  

The timeframe of the paper covers a period of 1991-2017. The paper is therefore divided into the following sections: 

section one is the introduction, literature review is in section two, section three contains the theoretical framework 

and methodology, section four is the presentation and the analyses of results and section five contains the summary, 

conclusion and recommendations. 

2. Literature Review 

2.1Conceptual Issues 

The International Labour Organization (ILO, 2010) defines unemployed workers as those persons who presently do 

not work but who are willing to work, hence, seeking for a job. The unemployment rate in a country is the number 

of persons that are unemployed and is expressed as the percentage of the total labour force. The term unemployment 

is a stock concept considered at a point in time. Its level rises when inflow that is, the newly unemployed exceed 

outflows, that is people getting new jobs or quitting the labour force altogether. Unemployment is the difference 

between the quantity of labour employed at the going wage levels and working conditions at a given period and the 

quantity of labour not hired at these levels.  Gbosi (1993) defined unemployment as a situation in which citizens 

who are willing to work at the current wage rate are unable to find jobs in a given economic environment.   

Traditionally unemployment can be identified by types due to it cause. Therefore, economists often classified 

unemployment into frictional, structural, classical and demand-deficiency (Keynesian). Frictional unemployment 

occurs from the time it takes an individual to move between jobs; this also results from a normal turnover of labour. 



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People who are unemployed while searching for jobs are referred to be frictionally unemployed. This situation is 

widespread in the Sub-Saharan Africa region due to low wage rates and the problems associated with the issues of 

better- working conditions.  

The concept of economic growth (output growth) according to Todaro (1985) is viewed as a long -term rise in 

capacity to supply increasingly diverse economic goods to its population; this growing capacity is based on 

advancing technology and ideological adjustments that it demands. It is highly believed that economic growth leads 

a given population of a country to enjoy a better standard of living and improved life expectancy. Fogel (1997) 

opined that economic growth refers to rising per-capita income and part of this increased income is translated into 

the consumption of higher quantity and better quality nutrients. Through nutrition, health is measured by life 

expectancy responds to increases in income, reduction in unemployment level that will help reduced poverty in the 

long-run. 

According to Dwivedi (2008) another prerequisite of economic growth is that the national output is composed of 

such goods and services which satisfy the maximum wants of the greatest number of people. For economic growth 

to be genuine, the increase in output must be sustained over a long period. The short-run increase followed by a 

similar decrease in output does not mean economic growth.  

The discovery of a strong empirical relationship between output growth (economic growth rate) and changes in the 

unemployment rate as postulated by Okun’s seminal paper of 1962 has become one of the most consistent 

relationship in macroeconomics (Adachi, 2007). Okun (1962) found that the relationship between unemployment 

and economic growth was both inverse and proportional. This precisely states that, a three percent increase in 

economic growth should result in a one percent decrease in the unemployment rate.  

 The subject of the negative relationship between unemployment rate and economic growth rate as postulated and 

empirically tested by Okun in the early 1960s has evolved from both statistical and empirical relationship that is 

known as empirical law called Okun’s law that predicts a negative relationship between the rate of change in 

unemployment and the rate of change in output growth. 

Okun (1962) postulated that a one percent increase in the output growth rate above the trend rate of growth (or the 

growth in potential output) would lead only to 3 percent in the reduction of unemployment. Reversing the causality, 

a one percent increase in unemployment will mean roughly more than three percent loss in output growth. This 

relationship indicates that the rate of output growth must be equal to its potential growth just to keep the 

unemployment rate constant.  To reduce unemployment, therefore, the rate of output growth must be above the 

growth rate of potential output. (Khemraj, Madrick & Semmler, 2006). 

2.2 Theoretical Literature 

2.2.1 Theoretical Integration between Output Growth and Unemployment 

The debate concerning the theoretical integration between output growth and unemployment is considered as 

something possible and even desirable (Arico, 2001). The theoretical perspective of economic growth and 

unemployment began with the seminal works of Harrod (1939) and Domar (1947), followed by the works of Solow 

(1956) model. The issue of the long-run unemployment was totally ruled out in the neoclassical growth models 

which are seen as a basic tool for investigating economic expansion. In order to have extensive explanation and 

literature on the issues about economic growth and unemployment this could be traced to the studies of Frankel-

Romer on the AK approach to endogenous growth and the second model by Romer based on labour augmented 

where technical knowledge is found to enhance productivity. Endogenous growth and unemployment as used by 

Pissarides (1993) based on the benchmark of Romer (1986) and the neo-Schumpeterian approach to growth and 

employment by Aghion and Howitt (1994). 

2.2.2 Review of Empirical and Methodological Literature 

Table 1: Summary of empirical evidence on the relationship between output growth rate and unemployment rate and 

the methodology adopted. 

S/N Names of 

Authors and 

year of studies 

No. of 

Countries 

Period  Dependent 

variable(s) 

Independent 

variable(s) 

Methodology Okun’s 

Coefficient 

Obtained 

1 Prachowny 

(1993) 

1(United 

States) 

1975Q1-

1988Q4 

Output 

growth gap 

Capacity 

utilization 

gap,  

unemployme

nt gap  

Labour-

supply gap 

OLS(first 

difference 

and 

production 

method) 

-0.62 and -

0.67 



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and  hours 

gap 

2 Weber (1995) 1(United 

states) 

1948Q1-

1988Q4 

Unemployme

nt gap and 

output gap 

Output gap 

and 

unemployme

nt gap 

OLS,ARDL, 

VAR and 

rolling OLS  

-0.32, -0.22 

and -0.26 

3 Moosa (1997) 7(United 

States, 

France,  

Japan, 

United 

Kingdom, 

Canada, 

Italy and 

Germany) 

1960-

1995 

Unemployme

nt gap 

Lagged 

unemployme

nt gap and 

output gap 

OLS ,rolling 

OLS and 

SUR 

-0.49 and -

0.09 

4 Lee(2000) 16 OECD 

countries 

and 

Germany 

1955-

1999, 

1960-

2006 

 Output gap Unemployme

nt gap 

Panel least 

squares(PLS) 

(first 

difference 

and HP filter  

-0.22 

5 Harris & 

Silverstone(2001

) 

 

6( Canada, 

Japan, US, 

,Australia, 

New 

Zealand 

and UK) 

1978Q1-

1998Q3 

Unemployme

nt rate 

Output rate ECM(first 

difference) 

-0.09 and -

0.5 

 

 

 

6 Geldenhuys  & 

Marinkov (2007) 

 

 

 

 

1( South 

Africa) 

1970-

2005 

Output gap Unemployme

nt gap 

HP , BN and 

BP filters  

-0.24,  

-1.09,  

-0.17  

and  

-0.78 

7 Amassoma & 

Nwosa (2013) 

1(Nigeria) 1986-

2010 

Productivity 

growth 

Unemployme

nt, labour 

force, capital, 

inflation and 

government 

expenditure 

Co 

integration 

and ECM 

1.12 

 and  

1.35 

8 Akeju & 

Olanipekun 

(2014) 

1(Nigeria)  1980-

2012 

Unemployme

nt gap 

Output gap Co 

integration 

and ECM 

0.097  

and  

0.069 

9 Adachi (2007) 2( Japan and 

US) 

1969-

2000 

Output unemployme

nt 

OLS(first 

difference) 

-6.18  

and  

-1.81 

10 Tombolo  & 

Hasegawa 

(2014) 

1(Brazil) 1980Q1-

2013Q3 

Unemployme

nt 

Output OLS (first 

difference ) 

 

 

-0.1878  

-0.2055 

11 Kargi (2013) 34 OECD 

countries 

1987- 

2012 

Unemployme

nt 

Output OLS(first 

difference) 

 

-0.27 

12 Boulton  (2010) 10(eastern 

European 

countries) 

1991-

2008 

Real GDP Unemployme

nt 

OLS (first 

difference) 

0.83,  

-4.2, 

 -3.44,  



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Poland, 

Romania, 

Slovakia, 

Slovenia, 

Bulgaria, 

Czech 

Republic, 

Hungary, 

Latvia and 

Lithuania 

-4.54,  

2.71, 

0.26, 

-5.44, 

1.87 

and  

-2.74 

13 Madito & 

Khumalo (2014) 

1(South 

Africa) 

1967Q1-

2013Q4 

Economic 

growth rate 

Unemployme

nt rate 

VECM(first 

difference) 

-0.618 

14 Ho(2002) 1(Macau) 1993-

2001 

Output Unemployme

nt 

OLS(first 

difference) 

-1.6951 

15 Andrei (2009) 1(Romania) 24Q000

Q1-2008 

Output gap  Unemployme

nt gap 

OLS -0.493 

16 

 

Hutengs & 

Stadtmann 

(2012) 

Euro zone  Unemployme

nt 

GDP OLS(first 

difference 

-0.034, -

0.91, -0.75 

and -0.234 

18 Zanin & Marra 

(2012) 

9(Spain, 

Portugal, 

The 

Netherlands, 

Italy, 

Ireland, 

Greece, 

Finland, 

Austria and 

France 

1996-

2009 

 

Unemployme

nt 

Real GDP 

growth  

OLS and 

rolling 

OLS(first 

difference) 

-0.34, -0.14, 

-0.19,-0.05,-

0.31,-0.07,-

0.12, -0.32 

and-0.10 

19 Barreto  & 

Howland (1993) 

1(Japan) 1953-

1982 

Unemployme

nt 

Output 

Output 

Unemployme

nt 

OLS(first 

difference) 

-0.032 

-9.46 

20  Tatoglu (2011) 19 European 

countries 

1977-

2008 

Unemployme

nt 

Output 

Output 

Unemployme

nt 

Panel co 

integration 

and Panel 

ECM 

0.003, 

0.007, 

-0.087, 

-0.075 

 

 

21 

 

 

 

Ozel  & Sezgin 

(2013) 

7{Industrial 

countries(G

7)} 

2000-

2011 

Unemployme

nt rate 

Growth rate 

and 

Productivity 

Panel least 

squares, 

Fixed and 

Random 

effects 

-0.351, 

-0.250 

22 Khemraji ; 

Madrick & 

Semmler  (2006) 

4(US, 

France, UK 

and 

Germany 

1961-

2000 

Output Unemployme

nt 

OLS(first 

difference) 

-9.83, 

-3.12, 

-4.36, 

-5.67 

23 Elshamy  (2013) 1(Egypt) 1970-

2010 

Output Unemployme

nt 

OLS,ECM(G

ap model) 

-0.021 

24 Salman (2012) 1(Sweden) 1993Q1-

2011Q2 

GDP growth 

rate 

Total 

unemployme

nt, Female 

and male 

unemployme

nt 

OLS(first 

difference) 

-0.076, 

-0.084, 

-0.079 



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25 

Ihensekhien 

(2016) 

42(SSA 

countries) 

1991-

2013 

Unemployme

nt 

GDP growth 

rate 

Panel Least 

Squares and 

OLS 

-0.049 

26 Ihensekhien & 

Erhi (2016) 

Nigeria 1991-

2015 

GDP growth 

rate  

Total 

unemployme

nt rate, Youth 

unemployme

nt rate, Male 

unemployme

nt rate and 

Female 

unemployme

nt rate 

OLS 53.45 

1041 

26.23 

14.03 

27 Ihensekhien & 

Asekome (2017) 

23(Low 

income 

countries in 

SSA) 

1991-

2013 

Youth 

unemployme

nt rate 

GDP growth 

rate 

Panel Least 

Squares and 

OLS 

-0.171 

28 Ihensekhien& 

Ovenseri-

Ogbomo (2017) 

23 (Low 

income 

countries in 

SSA) 

1991-

2013 

Total 

unemployme

nt rate  

GDP growth 

rate 

Panel Least 

squares and 

OLS 

 -0.075 

29 Mojica,   & 

Tatlonghari, 

(2017)      

Philippines 

economy  

1990Q3-

2014Q3, 

1990Q3-

2005Q3, 

2005Q3-

2014Q# 

Unemployme

nt rate 

GDP growth 

rate 

OLS -0.85 

 -0.92  

-0.70  

Source: Author’s Compilation 2018 

3. Theoretical Framework and Methodology  

3.1Theoretical Framework  

The relationship between economic growth and the unemployment rate based on theoretical linkage could be traced 

to one school of economic thought or the other. The classical economist’s school of thought believed that the 

connection between economic growth and unemployment is a one-way linkage that exists between the inputs of 

labour to economic growth.  

Kaldor (1967) as cited in Obadan and Odusola (2000) in invoking the Verdoorn’s law states that faster growth of 

output is responsible for a faster growth of productivity.  

The positive relationship that exists between employment and economic growth was also confirmed by Dernburg 

and McDougall (1985). Also from the view of the classical economists referring to Cobb-Douglas production 

function based on the technical links between output and the inputs such as labour and capital. The model indicated 

that the level of labour force assuming other variable is assumed to be constant help to determine the growth rate of 

output. 

From the Keynesian economists’ angle, the issue of output and unemployment is explained in terms of aggregate 

demand. The Keynesians believed that the demand for labour as a case of derived demand. The Keynesian 

theoretical linkages for economic growth and unemployment as analyzed by Hussain and Nadol (1997), Thirlwal 

(1997) and Grill and Zanalda (1995) implies that increase in employment, technological change and investment are 

largely endogenous. 

In a nut-shell, the growth of employment/unemployment is the determinants of long term increase in economic 

growth influenced by the level of unemployment/employment rate of a country. 

The theoretical connection of economic growth and unemployment began with the works of Harrod (1936), Domar 

(1947) and Solow (1956) in their investigation of the issue of the long-run unemployment in influencing the level of 

economic growth. The extention of the Keynesian model could be found in the studies of Okun (19962). 

Theoretically Okun’s law establishes the linkages between economic growth rate and unemployment rate, which he 

ascertained empirically to be negative. Okun’s law is seen as a benchmark for determining the economic well-being 

of a country. 

The economic implication of the Okun’s coefficient is that a 1 % reduction in the unemployment rate would result in 

3 % or more increase in the level of economic growth rate of a country. However, Okun’s law shows clearly a direct 



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link between economic growth rate and the unemployment rate. Hence, to determine a given level of the 

unemployment, what level of economic growth should the policymakers/government expect based on the sample 

periods for a given study. 

3.2 Methodology 

This paper adopted the use of annual data covering a cross-section of six upper middle income countries in SSA as 

classified by the recent development indicators of the World Bank (2018).  The timeframe of this study covers a 

period of 1991-2017. The paper applied the use of annual time series to determine the relationship between changes 

in unemployment rate and output growth rate among the upper middle income countries in SSA inorder to ascertain 

whether Okun’s law is applicable in these countries. Panel Least Squares and the Ordinary Least Squaers estimation 

methods was applied in this paper. The use application of annual data were observed in the studies of Moosa (1997), 

Viren (2001) and Ihensekhien etal (2016 and 2017) 

3.2.1 Model Specification 

Adopted the use of the first difference version of Okun’s, the difference version has been applied in many empirical 

studies due to its purely statistical and simple calculations which can be directly evaluated from the available 

empirical data. (Hilmer & Hilmer, 2014).The studies of Barreto and Howland (1993) revealed that the direction of 

the regression equation, that is the output growth regressed on unemployment or unemployment regressed on output 

growth is ascertained by the researcher’s research question.  Hence, this study Okun’s equation in terms of the first 

difference is stated as:   ttttt eOGROGRUNEUNE   11                                                              (1) 

Inorder to express the cross- sectional nature of the equation (1) above, this equation is respecified as:    

  tititititi eOGROGRUNEUNE ,1,,1,,   
                              (2) 

Where = 1, 2, 3, 4 - - - m, countries. 

t = 1, 2, 3, - - - n, years. 

 Where: UNEi, t = the observed unemployment rate of countries i. 

 tiOGR ,  = the GDP growth rate (Output growth rate) of Upper middle-income countries in SSA. 

   = the intercept, which indicates the average output growth of full-employment output (potential 

output).    = the Okun’s coefficient, which was estimated by Okun to be negative (β<0).  

The term 
   shows the variation in changes in output growth rate as a result of a unit change in 

unemployment rate. 
 

tie ,  = error term.  The error term is assumed to contain some different information such as factors affecting 

the dependent variable that are not used as the independent variables, specification errors, and the issues concerning 

the inherent randomness in human character (Hilmer etal, 2014). 

The equation (2) is re-specified to include logarithms since the study is interested in the percentage change 

in terms of output growth rate and unemployment rate: 

  tititititi eOGROGRUNEUNE ,1,,1,, loglogloglog   
                             (3)

 

The rate of output growth needed for a stable unemployment rate will be determined based on the formula:  Rate of 

output ratio   














                                                (4)

 

Equation (4) indicates the ratio of how much the economy of a country must grow to sustain a stable level of 

unemployment rate.          

The value 


  is the minimum level of output growth needed to reduce the unemployment rate (Knotek, 2007). 

 4. Presentation and Analyses of Results   

 4.1 Presentation of Empirical Results. 

Table 2: Results of Panel Unit Root Tests 

Method (At levels) OGR UNE 

Levin,Lin & Chut**   -5.33(0.000)* -0.069(0.472) 

Im,Pesaran and Shin W-Star -5.38(0.000)* -1.707(0.044) 



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ADF-Fisher Chi-Square 51.39(0.000)* 20.419(0.059) 

PP-Fisher Chi-Square 89.70(0.000)* 11.46(0.490) 

Method (At first difference) OGR UNE 

Levin,Lin & Chut**    -1.050(0.147) 

Im,Pesaran and Shin W-Star  -2.724(0.003)** 

ADF-Fisher Chi-Square  29.787(0.003)** 

PP-Fisher Chi-Square  51.44(0.000)* 

Author’s Estimation Results (2018)  

*/** represents significance at 1% & 5% level. 

The results indicated that the t-statistic values obtained were found to be statistically significant when compared 

with the critical values for decision making on the the hypotheses which was also confirmed by the probability 

values represented in parentheses. Table 2 showed that the unemployment variable was observed not to be stationary 

at levels but was stationary at the first difference hence the variables of output growth and unemployment were 

found to be statistically suitable for further statistical analyses and forecasting purpose. It means that the null 

hypothesis of the presence of non-Ststionarity in the panel data series is rejected. 

Table 3: Panel Least Squares Estimation Results for the overall sample of upper middle-income countries in SSA. 

Unemployment rate (UNE) as the dependent variable and Output growth rate (OGR) as the independent variable.  

Category of Countries AOG

R 

AUN

E 

  
 

t-

stat 

Prob.Val

ue 

R 



1

 
6 Upper middle-income 

countries 

6.36 15.87 16.77

3 

-

0.142 

-

4.05

* 

0.000 118.1 7.04 

5% reduction in UNE  15.08 15.95

4 

-

0.135 

-

4.05

* 

0.000 118.2 7.41 

7.5% reduction in UNE  14.68 15.51

5 

-

0.131 

-

4.05

* 

0.000 118.4 7.63 

10% reduction in UNE  14.29 15.09

6 

-

0.127 

-

4.05

* 

0.000 118.9 7.87 

15% reduction in UNE  13.49 14.25

7 

-

0.120 

-

4.05

* 

0.000 118.8 8.33 

20% reduction in UNE  12.70 13.41

8 

-

0.113 

-

4.05

* 

0.000 118.7 8.85 

50% reduction in UNE  7.94 8.387 -

0.071 

-

4.05

* 

0.000 118.1 14.0

9 

Source: Author’s Estimation Results (2018) 

* represents significance at 1% level. 

Note:  =intercept,  =Okun’s coefficient, R=rate of output ratio= 














 

The estimation results for the upper middle-income countries in SSA based on the first differenced equation  using  

panel data method of panel least Squares was used to determine the relationship between output growth rate (OGR) 

and unemployment rate (UNE). Table 3 indicated that unemployment rate is negatively related to output growth rate 

and the t-statistic value was found to be statistically significant. The Okun’s coefficient for upper middle-income 

countries in SSA indicated the negative relationship of the variables used as shown in table 4.1.2 with Okun’s 

coefficient of -0.142 indicates that a one percent decrease in unemployment led to 0.142 percent increase in output 



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40 

 

growth rate and the needed rate of output growth for stable unemployment for the upper middle-income countries is 

118.1 and the Okun’s inverse (


1
) of 7.04 indicated that as unemployment rate falls by one percent output growth 

would increased by 7.04 percent within the period. However, counter factual analyses were conducted based on 

some percentage reduction in the unemployment rate the result obtained indicated that as more persons are 

employed the level of output would increase. Based on the empirical results obtained as shown in table 4.1.2 using 

the t-statistic and the probability values indicated that Okun’s law is applicable in the upper middle- income 

countries of SSA since it is statistically significant. 

 Hence, this led to the empirical investigation of individual countries that made up the upper middle-income 

countries in SSA to ascertain whether Okun’s law is applicable in these countries; the results are shown in table 4.  

 

Table 4: OLS Estimation Results for Upper Middle - Income Countries in SSA.  Unemployment rate (UNE) as the 

dependent variable and Output growth rate (OGR) as the independent variable. 

Countries AOGR AUNE     t-stat Prob. 

Value 

R AR 



1
 

Botswana 4.52 18.59 18.27 0.072 0.594 0.558 -

253.8 

-9.4 13.88 

Equatorial 

Guinea 

20.19 5.76 5.76 -

0.016 

-0.009 0.992 360 13.3 62.5 

Gabon 2.28 18.46 18.17 0.129 2.201** 0.037 -

140.9 

-5.22 7.75 

Mauritius 5.51 8.31 7.74 0.125 1.113 0.276 -

61.92 

-2.29 8.00 

Namibia 4.18 20.52 20.86 -

0.083 

-0.714 0.482 251.3 9.31 12.05 

South 

Africa 

2.45 23.61 23.43 0.069 0.265 0.793 -

339.6 

-

12.58 

14.49 

Source:  Author’s Estimation Results (2018) 

Where: ** represents significance at 5% level. 

           AUNE= average unemployment rate 

           AOGR= average output growth rate 

            Intercept term 

           = Okun’s coefficient  

            Rate of output ratio ( R  )  














  

          AR= average rate of output ratio for the period of study  

Table 4 contains six upper middle-income countries out of which two of the countries OLS results revealed the 

expected negative relationship between output growth rate and unemployment rate.  However, only one country out 

of the six upper middle income countries had her individual t-statistic value to be statistically significant at 5% as 

reflected in table 4. However, the empirical results in table 4 indicated the non existence of Okun’s law in these 

countries contrary to the panel least squares result. It was observed that the Okun’s coefficients for some of these 

countries had very low magnitude and the results further indicated that Okun’s coefficient varies among countries as 

a result of the level of the influence of the unemployment rate on output growth rate.  

A comparison of the average output growth rate (AOGR) variable for upper middle income countries of 6.36 

revealed that some countries within the upper middle income group falls below the calculated average in countries 

such as Botswana had 4.52, Gabon 2.28, Mauritius 5.51, Namibia 4.18 and South Africa 2.45 except Equatorial 

Guinea that had a high average output growth rate of 20.19. The calculation of the rate of output growth rate needed 

for stable  unemployment rate shows that some countries in the upper middle income group in SSA has to grow at a 

very higher rate as  observed in Equatorial Guinea  and Namibia  this was also revealed in the average  ratio of the 

output growth needed to sustain a minimum level of unemployment rate in these countries,  which implies a serious 

threat to economic, political as well as social interests of these countries due to increasing unemployment situations.   



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41 

 

The issue of the positive relationship regarding empirical signs observed in South Africa, Equatorial Guinea, Gabon 

and Mauritius between output growth rate and unemployment rate follows the argument of saint-Paul (1993), Davis 

and Haltiwanger (1992) while Bean and Pissarides (1993) indicated that the bivariate correlation between output 

growth rate and unemployment rate can be either positive or negative depending on the economic structure and the 

magnitude of growth. The work of Aghion and Howitt (1994) agreed that high rates of economic growth are 

negatively correlated with unemployment and low rates of economic growth are positively correlated with 

unemployment. The issues of the positive empirical sign were also observed in some of the low income countries 

category such as Guinea-Bissau, Guinea, Niger and Zimbabwe these countries were observed to have low economic 

growth rate that could be responsible for such factors as poverty, underutilization of natural and mineral as well low 

human resources development (Ihensekhien &Asekome, 2017). 

5. Summary, Conclusions and Recommendations 

The paper reflects the empirical relationship between unemployment rate and output growth rate in upper middle-

income countries in SSA. Annual data  series covering a time frame of 1991 to 2017 period based on six upper 

middle-income countries in SSA region were evaluated  based on  a balanced panel data series where panel least 

squares was employed and that of the individual countries were the  ordinary least squares techniques were 

employed to test the empirical estimation. The various statistical as well as empirical results were quite revealing 

indicating the inverse relationship between output growth rate and unemployment rate variables in the Panel Least 

Squares result, however, some countries had positive relationships instead of the negative relationships, which 

further indicated the non existence of Okun’s relationship and applicability within some upper middle -income 

countries in SSA. The paper study also shows that the Okun’s coefficients vary across countries in terms of its 

coefficient magnitude. Also a counter factual analyses were conducted based on some percentage reduction in the 

unemployment rate, the empirical evidence indicated the needed to reduced unemployment level in order to boost 

output growth in these upper middle-income countries in SSA. 

From the various findings of the paper, the following are therefore recommend: that the governments of these upper 

middle-income countries should promote more jobs creation in order to boost the level of economic activities in 

these countries that the government should encouraged investment that are based on labour intensive employment 

opportunities. Governments of these upper middle-income countries should have good policy mix focused on the 

reduction of unemployment at all levels. 

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