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IMPACT OF UNEMPLOYMENT ON NIGERIA’S ECONOMIC GROWTH
(1986-2018)
BY
ABDURRASHEED NASIR ILA
(BU/13C/BS/0966)
A PROJECT SUBMITTED IN PARTIAL FULFILMENT
OF THE REQUIREMENTS FOR THE AWARD OF
BACHELOR OF SCIENCE IN ECONOMICS
TO THE
DEPARTMENT OF ECONOMICS
FACULTY OF MANAGEMENT AND SOCIAL SCIENCES BAZE UNIVERSITY
June, 2020
DECLARATION
I hereby declare that the research work is entirely my effort and all sources of information that
are not original to the study are duly acknowledged in the reference.
................................ ...................................
Name: ABDURRASHEED NASIR ILA Date:
Matric no: BU/13C/BS/0966
i
CERTIFICATION
This is to certify that the work “The impact of Unemployment on the Nigeria’s Economic
Growth” by Abdurrasheed Nasir Ila (BU/13C/BS/0966) has been approved by the Department
of Economics, Faculty of Management and Social Sciences, Baze University, Abuja, Nigeria.
_____________________ ______________
Dr. Abbas Abdullahi Marafa Date
Supervisor
_____________________ ______________
Dr. Badamasi Usman Date
Head of Department, Economics
______________________ ______________
Professor Ostia Agbu Date
Dean, Faculty of Management and Social Sciences
______________________ ______________
External Examiner Date
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DEDICATION PAGE
I will like to dedicate this project to my family who show their support to me and help me to
achieve my goals with all that they can offer.
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ACKNOWLEDGMENT
My special thanks go to my project supervisor who guided me through my research work the
person of Dr. Abbas Abdullahi Marafa. I am also thankful to my parents, brother and sisters, for
their amazing support and encouragement. Also my gratitude goes to my lectures and other staffs
of the University for impacting me one way or the other.
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TITTLE PAGE.................................................................................................................................iDECLARATION.............................................................................................................................ii
CERTIFICATION..........................................................................................................................iii
DEDICATION................................................................................................................................iv
ACKNOWLEDGMENT.................................................................................................................v
TABLE OF
CONTENTS................................................................................................................vi
ABSTRACT...................................................................................................................................vi
Table of ContentsCHAPTER ONE............................................................................................................................1
INTRODUCTION.........................................................................................................................1
1.1 BACKGROUND OF THE STUDY.................................................................................1
1.2 STATEMENT OF THE PROBLEM................................................................................3
1.3 RESEARCH QUESTIONS...............................................................................................4
1.4 OBJECTIVES OF THE RESEARCH..............................................................................4
1.5 RESEARCH HYPOTHESIS............................................................................................4
1.6 SIGNIFICANCE OF THE STUDY..................................................................................4
1.7 SCOPE AND LIMITATION OF THE STUDY...............................................................5
1.8 DEFINITIONS OF TERMS.............................................................................................5
1.9 ORGANIZATION OF THE STUDY...............................................................................6
CHAPTER TWO...........................................................................................................................7
LITERATURE REVIEW............................................................................................................7
2.1 INTRODUCTION............................................................................................................7
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2.2 CONCEPTUAL REVIEW................................................................................................7
2.3 MODELS OF UNEMPLOYMENT................................................................................10
2.4 THEORETICAL REVIEW.............................................................................................11
2.5 EMPIRICAL LITERATURE REVIEW.........................................................................13
2.6 SUMMARY....................................................................................................................16
CHAPTER THREE.....................................................................................................................17
3.1 INTRODUCTION..........................................................................................................17
3.2 RESEARCH DESIGN....................................................................................................17
3.3 METHODS OF DATA COLLECTION.........................................................................17
3.4 MODEL SPECIFICATION AND PROCEDURE OF DATA ANALYSIS..................17
3.5 EXPLANATIONS OF VARIABLE...............................................................................18
3.6 JUSTIFICATION OF METHODS.................................................................................21
CHAPTER FOUR.......................................................................................................................22
4.1 INTRODUCTION..........................................................................................................22
4.2 PRESENTATION AND ANALYSIS OF DATA..........Error! Bookmark not defined.
4.2.1 STATISTICS SUMMARY RESULT.....................................................................22
4.2.2 GRAPHICAL ANALYSIS OF THE TIME SERIES DATA..................................23
4.2.3 ADF UNIT ROOT TEST........................................................................................24
4.2.4 REGRESSION ANALYSIS....................................................................................24
4.2.5 MISSPECIFICATION TESTS....................................................................26
4.2.6 CRITERIA EVALUATION OF ECONOMIC APRIORI EXPECTATION...Error!
Bookmark not defined.
4.2.7 GRANGER CAUSALITY TEST............................................................................28
4.3 HYPOTHESIS TESTING...............................................................................................29
4.4 DISCUSSION OF FINDINGS.......................................................................................29
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CHAPTER FIVE.........................................................................................................................30
5.1 SUMMARY....................................................................................................................30
5.2 CONCLUSION...............................................................................................................31
5.3 RECOMMENDATIONS................................................................................................32
5.4 SUGGESTION FOR FURTHER RESEARCH..............................................................33
REFERENCES............................................................................................................................33
APPENDIX...................................................................................................................................37
CONTACT INFORMATION
Abdurrasheed Nasir Ila
Phone Number: 08068750828
Email: [email protected]
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ABSTRACT
This study examines the effect of unemployment on the Nigeria’s economic growth from 1986 to 2018 using time series annual data on real GDP growth rate, unemployment, inflation and volumes of exports of goods and services, sourced from the publications of the Central Bank of Nigeria, World bank and the International Monetary fund. Three research questions and hypotheses were constructed to guide this study. The study employed Unit root test to determine the order of integration of the variables, the co-integration test was carried out to examine the existence of long run relationship between the variables. Ordinary Least Square (OLS) and Granger Causality techniques were employed to determine the relationship between the variables and its nature. The OLS regression result showed that unemployment had a negative relationship with GDP growth in the economy. Also, the Granger causality tests showed that there exists no casual relationship between the variable.
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CHAPTER ONE
INTRODUCTION
1.1 BACKGROUND OF THE STUDY
Unemployment is mainly viewed as socio-economic and macro-economic problem. It
occurs due to low availability of job spaces or few amounts of jobs that will cater for a growing
population which in turn affects those that are unemployed and those that are employed as well.
The persons that are employed live with the fear of losing their jobs as a result of retrenchment
of workers or generally speaking insufficient job security. The term Unemployment could be
used in regards to any factors of production that has not been properly utilized for production.
Though, in terms of labour, unemployment occurs when people who are capable and willing to
work could not secure a job. Labour that is not fully used in production or operating below its
expected capacity is said to be underemployed. (Anyawuocha, 1993).
Unemployment could be grouped as either voluntary or involuntary. Voluntary
unemployment occurs when a person who is able to work choose not to seek for employment due
to having other means of livelihood. For examples, a person who inherits large amount of money
from someone else, or a business person that is already rich due to his business. As for the
involuntary, it is when a person who is willing and able to work could not secure a job.
Unemployment is viewed worldwide as an economic problem, and also a barrier to social
development. Other than it being a waste of manpower resources, it also promotes the loss of
welfare in the form of lower output thus leading to lower standard of living and hence less
income. Unemployment is a major issue in Africa (Vandemortele, 1991 and Rama 1998)
1
specifically in Nigeria. The importance of preventing the negative effects of unemployment
makes regulating the unemployment problem very essential in most countries that are in a
developing stage. In a study conducted on unemployment in Africa, Okonkwo (2005) listed the
reasons why unemployment takes place. They include; system of education adopted, and the
technique of technology used which could be either capital intensive or labour intensive. The
lack of good education and skills required for having access to credit and capital contributes to
unemployment. Also, the use of mechanical equipments to do a work which is done by labour
creates unemployment. The reason is, if it takes (50) people to finish a job in an hour, with the
help of a machine it is possible to let 5 workers finish the same job in a lesser time, thereby,
leading (45) people lose their jobs thereby lowering the standard of living.
The main factor that pulls down the standard of living in developing countries is the large
amount of unemployment rate relative to the developed countries. Unemployment rate refers to
the percentage of those that are unemployed in the labour force. It is derived by dividing the
number of those that are currently unemployed by the number of people in the labour force of an
economy. The term labour force can be defined as the total number of individuals that have
reached working age, mostly 18 years who are employed and the total number of individuals
who are unemployed, but are currently seeking for jobs.
The effects of unemployment in an economy include; the decline in national output,
lower standard of living, poverty, wastage of human resources, depression, and high crime rates.
These effects create the need to find possible solutions to tackle the problem of unemployment in
Nigeria.
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In order to determine unemployment that exists in an economy, economists’ divides
unemployment into four (4) categories; frictional, seasonal, structural and cyclical
unemployment.
The major factor that determines unemployment in Nigeria is the population growth
increase relative to the stage of development and technological growth of the country. Voluntary
decisions could also lead to unemployment. Voluntary unemployment occurs when individuals
decide not to take a job at a particular wage rate due to one reason or another, and hence remain
unemployed. This problem may be solved by increase of the wage rate and individuals reducing
their expectations.
In order to reduce the issue of unemployment more employment opportunities needs to be
created and also training programs provided in other to give individuals needed skills.
1.2 STATEMENT OF THE PROBLEM
The data from international monetary fund (IMF) and that of national bureau of statistics
reveals that, the rate of unemployment in 2014 was 7.8% while in 2015 it increased to 10.4%.
Furthermore in 2016 it had a higher increase to 14.2% at Q4. Moreover, the data shows that the
rate of unemployment in the urban and rural area was 18.4% and 12.3% respectively in 2016
compared to 10.5% and 25.8% in 2015.
Due to the increasing negative effects posed by unemployment on people and country as a
whole, government has been adopting various policies to help reduce and control the issue of
unemployment, but the problem seems to be increasing rather than it producing positive results.
Accurate policies need to be adopted in order to solve this problem of unemployment. The
statement of the problem is based on the political, social as well as economic effects of
unemployment.
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1.3 RESEARCH QUESTIONS
1. Does unemployment have any relationship with economic growth?
2. Is there any causal relationship between unemployment and economic growth in Nigeria?
1.4 OBJECTIVES OF THE RESEARCH
The broad objective of the study is to examine the impact of unemployment on Nigeria’s
economic growth. To achieve that, the following specific objectives were pursued:
1. Investigate the relationship between the economic growth and unemployment in Nigeria.
2. Determine if growth in the economy has a causal relationship with unemployment in
Nigeria
1.5 RESEARCH HYPOTHESIS
To complete these aims hypothesis are set;
1. The null hypothesis (H0) is;
H0: Unemployment has no relationship with economic growth.
And the study’s alternative hypothesis (H1) is;
H1:Unemployment has a relationship with economic growth.
2. The null hypothesis (H0) is;
H0: Economic growth has no causal relationship with unemployment. And the study’s
alternative hypothesis (H1) is;
H1: Economic growth has a causal relationship with unemployment.
1.6 SIGNIFICANCE OF THE STUDY
The significance of the study is to establish the impact of GDP on unemployment in
Nigeria. In view of the fact that price stability and full employment are two conflicting macro-
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economic goals, the result of this study becomes an important tool in the hands of the policy
makers in Nigeria in order to achieve the two goals simultaneously.
As living standard of a country increases, one of the important macro-economic objectives
is the attainment of full employment. So, unemployment is viewed as a failure caused by the
policy makers. Hence, efforts are made by the government to control the impact of
unemployment in an economy.
The study of unemployment is very important to economics students, policy makers and
also politicians. The study of the unemployment rate of an economy helps in setting up policies
that would help an economy reach a desired level.
1.7 SCOPE AND LIMITATION OF THE STUDY
The scope of this study is focused on the relationship between unemployment and GDP in
the Nigerian economy. The study adopted OLS regression which is focused on a 32 years annual
time series data (1986-2018) that are sourced from the international monetary fund (IMF) and
Nigeria’s central bank statistical bulletin.
1.8 DEFINITIONS OF TERMS
ECONOMY: This is the activities of economic components that comprises of individuals,
Government, households e.t.c, which relates to consumption, productions and exchange of goods
and services in a particular place.
ECONOMIC GROWTH: This refers to the rise in Real GDP. It is the rise in the adjusted
market inflation value of goods and services produced by a country over a given period of time.
Real Gross Domestic Product (GDP): This refers to the annual total adjusted inflation value of
goods and services produce by an economy.
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Interest Rate: It is the rate which is charged by a creditor in percentage over the amount lent
which is paid periodically.
Full employment: This refers to a situation where virtually people who are willing and able to
work are employed.
1.9 ORGANIZATION OF THE STUDY
The study is organized in five (5) chapters. Chapter one introduced the topic by defining
unemployment, describing the types, causes and effects of unemployment. It also
mentioned the objectives, significance and the limitations of the research. Chapter two (2)
does review some literature, past findings and past empirical results. Chapter three (3)
describes the methodology used in this study, describing the model adopted and the
variables that will be used in this research. Chapter four (4) presents the results and
interpretation of the methodology explained in the third chapter, beginning from initial
analysis, regression results and statistical test so as to confirm the validity of the variables.
Chapter five (5) is the final chapter, and it concludes the study by summarizing the
findings, stating the limitations of the study and recommending how the study could be
further enhanced.
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CHAPTER TWO
LITERATURE REVIEW
2.1 INTRODUCTION
In order to accomplish the aim of this research work, it is essential to examine previous
works in this field as it will present us with the background both theoretically and empirically for
evaluating the importance as well as the contributions of this study. The aim of this study is to
identify the relationship between economic growth and unemployment by the use of econometric
analysis.
2.2 CONCEPTUAL REVIEW
In this section the meanings of unemployment will be discussed as well as economic
growth, inflation and volumes of export of goods and services. The types of unemployment will
also be analyzed in this section.
2.2.1 DEFINATIONS
Unemployment:
Unemployment refers to when people who are actively seeking for job but couldn’t secure one.
The unemployed according to international labor organization (ILO) refers to those who are
actively searching for job but not able to find one. Those who are not working and are not
interested to seek for a job are referred to as the ‘inactive’. Whether a person is studying or have
acquired a certain certificate may still be referred to as the inactive as they do not have the
interest to work while they have reach the working age according to his country. Unemployment
also known as unemployment rate in countries like the United States of America refers to the
overall number of the people who are unemployed divided by the total number of the people that
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have reached the working age and not above the working age which. The total numbers of people
that have reach the working age and not above it are referred to as the labor force. The labor
force constitutes both those who are employed and also the unemployed. The age a person needs
to be before he is referred to as a youth which gives a person legal right to work varies between
one country and another. According to the United Nations (UN) a youth is that people whose age
ranges 15-24 years, although in actual fact there is no certain definition of who a youth is. The
reason is as mentioned earlier every country has its own definition which is as a result of their
social, political, institutional or cultural factors (United Nations, 1992). In Africa, it is realized
that there is no specific definition of the youth, for example, in Ghana according to its national
youth policy (2010) those who are between the age of 15 and 35 are regarded as the youth, while
in Ethiopia, persons whose age ranges from 18-29 are regarded as youth. Consequently, In
Nigeria those who are 18 years of age and below 35 are regarded as the youth according to the
national youth policy (2009).
ECONOMIC GROWTH: This refers to the increase in the inflation-adjusted value of goods
and services produced by over a specific period of time by an economy. Thus, in this research,
Real GDP annual growth rate will be used so as to represent economic growth. Economic growth
increase household incomes, creates better job opportunities, increases output as well as reduces
unemployment. Hence, makes every nation desire economic growth as it is the most observed
economic indicator.
INFLATION: this is the average increase in the price level. Also, it is described as an economic
situation in which the rise in the supply of money is greater than the additional output of goods
and services produced in an economy (Hamilton, 2001). It should be understood that the price
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increase of stable foods may have greater effect on the economy than the price increase in
average commodity. Inflation rate is also among the top most observed economic indicator.
VOLUMES OF EXPORTS OF GOODS AND SERVICES: It is the amount of goods and
services being exported by a country. In this research, the annual growth rate of volume of
exports of goods and services is used. Therefore, the percentage variation of the amount of goods
and services exported represents an indicator which helps to ascertain how much a country is
producing. Large volume of exports of goods and services by a country shows that an economy
is efficient which will eventually lead to economic growth.
2.2.2 TYPES OF UNEMPLOYMENT
Frictional unemployment can be defined as the waiting period between losing a job
and finding one. It occurs when demand and supply of labour fails to adjust. This
could be as a result of individuals that are willing as well as able to work again do
not know of the availability of jobs or on the part of the employers, not knowing
that individuals are willing and able to work. Also it occurs because people are
trying to change to another job because of the continuous change in the labour force
and job offers.
Seasonal unemployment is a situation in which people become unemployed during
a certain period of time. When the season returns, their skills are needed again
hereby, they become employed. For example, farmers that plants and harvests
certain crops that grow at certain period of time. Their skills are only needed at that
time.
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Structural unemployment occurs when there is mismatch between the skill levels of
the unemployed and job that is available which could be as a result of demographic
changes or shifts in labour market institutions. This condition is created by
economic variables, like the aggregate demand level and the expected or actual real
wage.
Cyclical unemployment is another type of unemployment in which the economy
tends to lay off workers which could be as a result of aggregate demand changes.
2.3 MODELS OF UNEMPLOYMENT
2.3.1 Philips curve
This is a curve that shows the relationship between inflation rate and unemployment. The
study of wage, inflation and unemployment by Philip's from 1861-1957 contributed greatly to
the development of macroeconomics. Philips understood that there was inverse relationship
between the level of unemployment in an economy and inflation. His theory states that
unemployment increase leads to decrease in inflation rate, and also unemployment rate decrease
leads to a rise of inflation rate in an economy.
2.3.2 Okun's law
Okun's law is one of the most widely accepted theories in Macroeconomics. The major
reason for the study by Okun's (1962) was to make appropriate changes to macroeconomic
policy. It focuses on the link gross domestic product (GDP) has with unemployment. The
authentic work of okun shows that for a 1% decrease in unemployment rate there would be 2%
increase in gross domestic product and 3% increase in gross national product. This relationship
has been studied continually; its accuracy evaluated, and also the dependency level of the
variables between one another. Okun's law shows that in order to avoid unemployment,
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continuous development of the economy must take place. Unemployment and economic growth
have an inverse relationship, in the sense that when unemployment rate increases, it leads to a
decrease in productivity and vice-versa.
2.4 THEORETICAL REVIEW
2.4.1 CLASSICAL THEORY OF UNEMPLOYMENT
In economics, there are different schools of thoughts to which economist belong to. The
way they interpret things, geographical entities and time periods all determines which school of
thought they belong to. The two main schools of thought are Classical and the Keynesian.
The Classical believed that money played an important role in explaining short term
adjustments in national income.
They also believed that high real wage results to unemployment. When there is reduction
in real wage they realise that there is no unemployment except the frictional unemployment in
which a person quits his job in other to start another. More so, they concluded that when there is
demand for high wage by workers without an increase in productivity, it leads to increase in
product price. This increase causes a decline in sales due to increase in production cost which
eventually leads to unemployment as firms do not have enough funds to pay their workers.
2.4.2 KEYNESIAN THEORY OF UNEMPLOYMENT
In 1930s, John Maynard Keynes, a British Economist brought a revolutionized
macroeconomic thinking in which several ideas of the neoclassical was changed. The neo
classical economics believed that, free markets in the short and medium term leads to full
employment unless workers are not flexible in demand of their wages. While Keynes argued
that, the general economic activity is influenced by aggregate demand. The shortage of aggregate
demand would lead to long period of high unemployment.
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In 1936, Keynes made a publication titled general theory of unemployment interest and
money which he analyzed some macroeconomic areas such as unemployment, money supply and
interest.
Keynesian unemployment also known as Cyclical or deficient demand is an
unemployment that takes place as a result of low aggregate demand in an economy. It is from
fluctuations in the business cycle its named was formed. Keynes argued that this unemployment
takes place as a result of insufficient effective demand that lead to decline in demand for goods
and services, decline in production level and wages. This alters the equilibrium hereby causing
high unemployment.
Keynes maintained that employment is a function of effective demand which results to
increase in output thereby generating more income and this income lead to employment.
The Effective demand level is determined by supply functions and aggregate demand.
Keynes put more focus on the aggregate demand function so as to tackle Unemployment
and depression. Thus, he believed that employment is dependent on aggregate demand, which
relies on investment demand and consumption demand.
2.4.3 EFFICIENCY WAGE MODEL OF UNEMPLOYMENT
This is a macro-economic approach that helps to explain unemployment. The model
views that there is a link which exists between productivity of labour and wage rate. According
to the model, productivity of labour and wage rate are said to have positive relationship. The
increase in wage increases labour productivity because during that period, there is high labour
turnover and the employees will work harder in other to avoid being laid off.
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As regard to other firms when there is labour turnover, higher wages are offered in other
not to lose top class workers to other firms. Labour movement tends to reduce productivity,
efficiency or even lead to shut down of business if care is not taken.
Labour turnover shows that, for a firm to be profitable, wages that are higher than that of
the market level should be adopted. Though many firm adopts this strategy. Consequently, this
theory recommends firms to create involuntary unemployment by increasing the wages above
market level. Involuntary unemployment refers to a situation where workers are willing to work
at lower wage than the current one. This unemployment reward employees with an incentive so
as to avoid labour shrinking. This incentive is created by making the cost of being unemployed
high which as a result reflects high unemployment rate.
2.4.4 SEARCH MODEL OF UNEMPLOYMENT
This model argues that unemployment occurs due to workers quitting their jobs in order to
search for more suitable one. It focuses on frictional unemployment.
2.5 EMPIRICAL LITERATURE REVIEW
The general theory of Keynes (1936) held the view that changes in GDP through aggregate
demand realizes changes in the unemployment rate as opposed to the Classical theory which is of
the view that the labour price dictates unemployment. Keynes expressed that equilibrium exists
when the economy is at full employment. He added that unemployment and aggregate demand is
affected by savings and investments relationship. He stated that both savings and investment are
determined by interest rate though they are not mostly equal. An increase in savings rate may
also lead to an increase in investment rate, but if the investments expected rate of return falls, it
will lead to a drop in investment level thereby causing a decline in aggregate demand. The
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decline in demand therefore leads to equilibrium but lower than full employment level. So the
change of GDP caused by aggregate demand changes establishes the level of full employment.
The theory of Keynes believed that GDP increase lead to employment increase until level
of equilibrium is reached. Moreover he stated that, unemployment is caused by low increase of
effective demand and that employment increase is as a result of effective demand presence
(Ewing, 1999). This backups the previous believe that GDP through a change in aggregate
demand establishes level of employment. (BMR, 2011; Hansen, 2013) agreed that economic
growth may lead to unemployment only if the nature of the economy is labour absorptive.
This ascertains that a positive relationship exists between employment level and economic
growth.
In the study of unemployment determinants in Namibia by Eita & Ashipala (2010), they
concluded that a positive relationship exists between employment and overall GDP, employment
and manufacturing sectors GDP but inverse relationship between unemployment and investment.
This means that as investment falls unemployment rises while employment level decreases.
In another study, Rad (2011) observed employment relationship to GDP growth in Jordan. He
understood that with high growth rate, few new productive jobs are created. It was recommended
that for new productive jobs to be created, a change from low value added production and export
to a more sustainable sector by the government needs to take place.
Walterskirchen (1999) also, studied the European (EU) countries economic growth,
employment and unemployment relationship. He used the panel data of all countries and time
series data for each country. He concluded that there was a direct relationship between economic
growth level and employment level. Landmann (2002) found out that there is a direct
relationship between level of productivity and that of employment.
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Biyase& Bonga-Bonga (2007) studied unemployment growth in South Africa via the
Structural Vector Autoregressive (SVAR) technique. They conclude that an increase in output
lead to a little increase in employment which means that there is insignificant unemployment
growth in South Africa.
As regard to Nigeria, Obadan and Odusola (2005) figured that GDP along with
unemployment are inversely related. Also, it was understood that the reaction growth have on
unemployment is different between one sector of the economy and the other. For instance in the
industrial sector, a lot of firms use little labour to attain high production level of output thereby
causing high unemployment.
Previous studies related to employment elasticities:
Ajilore & Yinusa (2011) studied the output growth of employment intensity in Botswana of
various sectors and concluded that low sectoral employment intensity exists in the economy.
This states that a growth increase results from an increase in labour productivity and not labour
employment; this means that the economy is experiencing 'jobless growth.’
This means that growth is not as a result of labour employment but rather labour productivity.
Here the economy is experiencing “jobless growth”.
Furthermore, the study of Osmani (2006) on Asia showed that low employment elasticity
occurs in the manufacturing sector.
Another study by Pini (1997) on Japan and Germany showed that increase in the
employment elasticity’s of growth exists in the two while low elasticity exist in France and
Sweden.
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2.6 SUMMARY
This chapter discuses the economic literature of other past studies done by various economists on
this research topic. This chapter respectively also discussed the theoretical framework of
economic theories to support this research and other economic literature that has analyzed the
impact of unemployment on economic growth in Nigeria.
Furthermore, the conceptual framework discussed the interrelation and dependence of the
different variables in this research. This chapter mainly examined the influence that
Unemployment, inflation and volume of export of goods and services had on the Nigeria’s
economic growth and other important variables of macroeconomics.
The empirical review, Granger Causality Test, OLS regression model were among the
econometric tools and technique used mostly by economists whose works were examined in this
study.
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CHAPTER THREE
RESEARCH METHODOLOGY
3.1 INTRODUCTION
This chapter discus the research design, specification of the model, utilization of data and
also the nature of data used in this research. It discusses the methodology used in explaining the
relationship between Unemployment and the Nigerian economy
3.2 RESEARCH DESIGN
The research uses an analysis called the econometric method. The term econometrics refers
to the use of statistical and mathematical methods to economic data so as to give empirical
content to economic theories. The reason for it to be employed is that it has the ability to give
accurate and meaningful prediction of economic magnitude. So as to achieve this prediction,
ordinary least square estimation of econometric analysis is made used of. The Ordinary least
square method is the calculation of parameters that are unknown in a linear regression model and
because of its properties of best linear unbiased estimator it is employed.
3.3 METHODS OF DATA COLLECTION
In this research the macroeconomic data to be used will be the Nigeria’s annual real
growth of domestic product, unemployment, inflation and volume of exports of goods and
services. The time series data used (from 1986-2018) was sourced from secondary sources:
Central Bank of Nigeria, World Bank and International Monetary fund websites. All data are
collected in Naira.
3.4 MODEL SPECIFICATION AND PROCEDURE OF DATA ANALYSIS
The model is specified as follows:
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GDPG = F (UNEMPG, INF, VEGSG)
Where;
GDPG= Gross domestic product growth
UNEMPG = Unemployment growth
INF = Inflation rate
VEGSG = Volume of exports of goods and services growth
This model is mathematically expressed as:
GDPG =β0 + β₁UNEMPG + β₂INFG + β₃VEGS + UT
Where β0= is the intercept
β₁ - β₃= the explanatory variables coefficient
Ut= Error term
Gujurati (2003) defined the error term Ut as a random variable that has some clearly defined
properties. The error term constitutes of other determinants of unemployment not taken into
consideration by the above model.
3.5 EXPLANATIONS OF VARIABLE
3.5.1 Gross Domestic Product growth (GDPGR)
Gross domestic product (GDP) refers to the market value of the overall final goods and
services manufactured within a country in a giving time. GDP growth, therefore, refers to the
proportion of the variation that a country’s GDP experiences from one given year to another.
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3.5.2 Unemployment growth (UNEMPG)
The term Unemployment rate refers to the percentage of unemployed individuals in a
labour force. It is obtained by dividing the percentage of the unemployed labour force by the
total number of labour force in the economy.
Growth rate, on the other hand, refers to the proportion of variations in the output from one
period to another.
Therefore, the growth rate of unemployment refers to the proportion of the variation in the
unemployment rate from one period to another.
3.5.3 Inflation (INF)
Inflation rate refers to the persistent increase in the average level of prices. Inflation
growth, therefore, refers to the rate of change of the inflation rate from one year to another.
3.5.4 Volume of exports of goods and services growth (VEGSG)
Volume of exports of goods and services refers to the amount of goods and services being
exported by a country. The growth rate of volume of exports of goods and services, therefore,
means the percentage of the variation of the amount of goods and or services being exported by a
country.
These variables employed are considered to be relevant in ascertaining the impact of GDP
on unemployment (UNEMP) on the Nigerian Economy.
3.5.5 METHOD OF ESTIMATION AND EVALUATION OF RESULT
The technique that is adopted here is method of ordinary least square. The main aim of
the ordinary least square is to determine whether the relationship between the variables is
positive or negative and also to find out their statistical level of significance.
19
3.5.6 THE ECONOMIC APRIORI EXPECTATION
Unemployment growth rate is expected to have a negative relationship with Nigeria’s
GDP growth rate as well as Inflation and Volume of Exports of Goods and Services
3.5.7 ECONOMETRIC TESTS
This test uses the final result of a regression so as to analyse it in line with the classical
assumption of the OLS. The tests include; the test for multicollinearity, test for stationarity,
cointegration test, autocorrelation test, heteroskedasticity test and normality test. The
aforementioned tests can be explained briefly below;
a) Test for multicollinearity: The term multicollinearity in statistics refers to the situation
whereby two or more independent/explanatory variables are highly linearly correlated in a
regression model. Perfect correlation exists when the correlation between two explanatory
variables is 1 or -1. It is perfectly positively correlated when the correlation between the two
explanatory variables is 1, and it is perfectly negatively correlated when the correlation between
the two explanatory is -1. No correlation exists when the correlation between the two
explanatory variables is 0. A correlation matrix method would be used for this test.
b) Test for stationary: This test determines whether a variable in a time series data is stationary
or non-stationary. The researcher will make use of the Augmented Dickey Fuller test to
determine the variables stationary or non-stationary status.
c) Test for co-integration: Co-integration test helps determine whether long run correlation
exists among the different variables.
d) Auto-correlation test: The main purpose of this test is to determine if the blunders matching
various observations are uncorrelated; randomness test of the error term. Here, Durbin- Watson
20
technique would be used to conduct the test since it provides more effective result estimates of
all sample size.
e) Heteroskedasticity test: This will help determine whether the explanatory variables error
term of an estimated model has equal variance.
f) Normality test: This would be employed to discover if a random variable is normally
distributed.
3.5.8 NATURE AND SOURCE OF DATA FOR THE RESEARCH
The researcher makes use of 33 year annual data which were sourced from; International
Monetary Fund, World Economic Outlook Database and Central bank of Nigeria statistical
bulletin. The researcher makes use of E-Views 10 software.
3.6 JUSTIFICATION OF METHODS
In this research, quantitative method of analysis was employed so as to approve,
disapprove, or assist the theories of the research discussed in the literature review. Time series
data were also employed in order to provide information of the years covered in this research.
Inferential as well as descriptive statistics were utilized in order to analyze the nature of the data.
The main aim is to analyze whether the data is normally distributed.
The unit root test in this research will be used so as to analyze whether the variables are
stationary or non-stationary as well as, the magnitude of stationarity of the data.
The OLS regression analysis is employed because it is known as best linear unbiased
estimator. This analysis is important as it estimates the relationship between the dependant and
independent variables.
Furthermore, the Granger causality test was employed so as to examine the casual
relationship between the dependent and independent variables.
21
CHAPTER FOUR
DATA PRESENTATION AND ANALYSIS
4.1 INTRODUCTION
The objective of this chapter is to presents the data analysis, results and discussion. To
achieve that, the chapter is divided into 9 parts. Part one covering this introduction. Part two
present the descriptive statistics on the variables. Part three present the unit root test, while part
present the cointegration test. Part five present the OLS test. part six present the Granger
causality results and part 7 presents misspecification test. Furthermore, the hypothesis testing is
presented and the result discussed.
4.2 STATISTICS SUMMARY RESULT
TABLE 4.1 DESCRIPTIVE STATISTICS
GDPGD1 UNEMPGD1 INFGD1 VEGSGD1 Mean 0.001250 0.747187 0.182500 0.668438 Median 0.510000 -0.300000 0.960000 3.070000 Maximum 7.930000 60.37000 32.37000 224.4600 Minimum -12.15000 -83.15000 -43.44000 -198.1600 Std. Dev. 3.827883 21.12576 14.55313 100.4842 Skewness -0.772690 -1.068231 -1.130482 0.161431 Kurtosis 4.889447 10.89213 6.036421 3.444914
Jarque-Bera 7.944281 89.13369 19.10908 0.402917 Probability 0.018833 0.000000 0.000071 0.817537
Sum 0.040000 23.91000 5.840000 21.39000 Sum Sq. Dev. 454.2334 13835.23 6565.602 313009.4
Observations 32 32 32 32
(Source; Author computation using Eviews 10)
The above table of, Unemployment growth, inflation and volume of goods and services.
It shows that the variables contained are 32 in number and only VEGSD1 is positively skewed.
22
Also it can be viewed that all the variables are all higher than 3(THREE). The respective Jarque-
Bera probabilities show that none of the variables are normally distributed except VEGSD1.
4.2.1 GRAPHICAL ANALYSIS OF THE TIME SERIES DATA
TREND ANALYSIS
-4
0
4
8
12
16
1990 1995 2000 2005 2010 2015
GDPG
-40
-20
0
20
40
60
80
1990 1995 2000 2005 2010 2015
UNEMPG
0
20
40
60
80
1990 1995 2000 2005 2010 2015
INFG
-50
0
50
100
150
200
250
1990 1995 2000 2005 2010 2015
VEGSG
FIGURE 1.0 (Source; Author computation using Eviews 10)
Ploting a time series graph it helps in understanding the nature of the series under study.
The 4 variables being studied are examined using the graph above. It can be understood from the
graph above that the variables possess an upward trend respectively. This also shows their
variance constancy and means reverting over time. ADF UNIT ROOT TEST
Unit root tests were conducted using Augmented Dickey Fuller and the result is presented
in Table 4.2:
23
Table 4.2 Unit Root Results
Variable LEVELS 1st DIFFERENCE ORDER OF INTEGRATION
T-Statistics Probability T-Statistics ProbabilityGDPG -2.964062 0.1574 -7.618485 0.0000 I(1)
UNEMPG -5.883721 0.0002 -6.481199 0.0001 I(0)INF -3.012181 0.1480 -4.379425 0.0091 I(1)
VEGSG -5.404890 0.0007 -5.049873 0.0018 I(0)(Source; Author computation using Eviews 9)
The above table shows that at level, 2 variables are non stationary so 1st differencing was
carried out in order to solve this problem. The result of the first differencing table shows that all
the variables are stationary as their respective probabilities are less than 0.5.
4.2.2 COINTEGRATION TEST
The above cointegration result (Trace) indicates 2 cointegrating eqn (s) at the 0.05 level which
denotes rejection of the hypothesis at the .05 level. While the second result (maximum
Eigenvalue) shows that there is no cointegration at the 0.05 level denoting the rejection of the
hypothesis at the 0.05 level.
4.2.3 REGRESSION ANALYSIS
The results obtained from regression analysis after differencing are presented in the table
below.
TABLE 3.0 OLS Multiple Regression Analysis Results
24
Dependent Variable: GDPGMethod: Least SquaresDate: 06/19/20 Time: 12:29Sample (adjusted): 1987 2018Included observations: 32 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
C 6.045904 1.056545 5.722332 0.0000UNEMPGD1 -0.027623 0.032995 -0.837179 0.4096
INF -0.053009 0.040746 -1.300943 0.2039VEGSGD1 -0.006091 0.007068 -0.861761 0.3961
R-squared 0.115727 Mean dependent var 4.975313Adjusted R-squared 0.020983 S.D. dependent var 3.922370S.E. of regression 3.881000 Akaike info criterion 5.666531Sum squared resid 421.7405 Schwarz criterion 5.849748Log likelihood -86.66450 Hannan-Quinn criter. 5.727263F-statistic 1.221474 Durbin-Watson stat 1.030591Prob(F-statistic) 0.320287
(Source; Author computation using Eviews 10)
A) UNEMPGD1
The result above shows that; there exists a negative relationship between GDPG and
UNEMPG. The coefficient of UNEMPGD1 -0.027623 denotes that a unit increase in
unemployment will lead to a decrease in GDPGD1 by -0.028.
B) INF
Holding other factors constant, inflation growth will continue to grow at a trend of 0.2039 units.
Between GDPG and INF there exists a negative relationship. Also a unit increase in INF will
lead to a decrease in GDPG by -0.053.
C) VEGSGD1
There is a negative relationship between GDPG and VEGSD1. As the coefficient of VEGSD1 is
-0.006091. This indicates a unit increase in it will lead to a decrease in GDPGD1 by -0.007108
25
4.2.4 MISSPECIFICATION TESTS
I) Coefficient of determination (R²): This is a measure of goodness of fit of the population
regression line overall. It shows the percentage of the variation in the dependent variable
explained by the independent variable. The coefficient of determination (R²) lies between 0 and
1. The more it approaches 1, the better the goodness of fit.
From the Eviews result above,
R² 0.12 0r 12% which shows a poor fit in the regression line overall This explains that
approximately 12% of the total variations in the dependent variable (GDPGROWTH) are
explained by changes in independent variables of the estimated model. This suggests that the
estimated model has poor fit.
(II) Autocorrelation Test
In order to determine autocorrelation, the following hypothesis is set
H₀: There is No Serial Correlation of Error Term (α=5%)
Hᴀ: There exist Serial Correlation of Error Term (α=5%)
From the above B-G test, the null hypothesis is accepted as the p-value of F-statistic is less than (0.05) significance level. This means that the research concludes existence of autocorrelation in the model.
26
(III) Heteroscedasticity Test:
Since the P-value is greater than (0.05) significance level, the table conclude that the variance of
the error terms is constant (Homoscedastic).
(IV) Multicollinearity Test:
This test shows the perfect linear relationship that exists among the independent and explanatory
variables. Here, correlation matrix is employed.
Table 5.0 Multicollinearity result
Covariance Analysis: OrdinaryDate: 06/19/20 Time: 13:40Sample: 1986 2018Included observations: 33
Correlation GDPG INF UNEMPG VEGSG GDPG 1.000000
INF -0.241512 1.000000UNEMPG -0.087616 -0.215642 1.000000VEGSG -0.091019 0.408313 -0.159698 1.000000
(Source; Author computation using Eviews 9)
Multicollinearity does not exist as all correlation coefficients are less than 0.8.
Multicollinearity only exist by the rule of thumb when the coefficient is greater than 0.8.
4.2.5 GRANGER CAUSALITY TEST
Table 6.0 Granger Causality Result
27
Pairwise Granger Causality TestsDate: 06/18/20 Time: 16:57Sample: 1986 2018Lags: 2
Null Hypothesis: Obs F-Statistic Prob.
INFG does not Granger Cause GDPG 31 2.97662 0.0685 GDPG does not Granger Cause INFG 1.03327 0.3700
UNEMPG does not Granger Cause GDPG 31 0.79391 0.4627 GDPG does not Granger Cause UNEMPG 1.29015 0.2923
VEGSG does not Granger Cause GDPG 31 1.35070 0.2766 GDPG does not Granger Cause VEGSG 0.56431 0.5756
UNEMPG does not Granger Cause INFG 31 0.76523 0.4754 INFG does not Granger Cause UNEMPG 1.57027 0.2271
VEGSG does not Granger Cause INFG 31 1.45143 0.2526 INFG does not Granger Cause VEGSG 2.37033 0.1133
VEGSG does not Granger Cause UNEMPG 31 0.32294 0.7269 UNEMPG does not Granger Cause VEGSG 0.79549 0.4620
(Source; Author computation using Eviews 10)
This test is employed in order to analyse and estimate the casual relationship that exists
between variables. The null hypothesis is rejected when the P-value is less than 0.1 and when F-
statistics is greater than 3.
In the above table, all the independent variables have no casual relationship with the
dependent variable. Therefore, none of the regressors have impact on the dependent variables as
all their P-values are greater than 0.1.
4.3 HYPOTHESIS TESTING
HO: Unemployment has no significant impact on GDP growth of Nigeria
The result obtained from the OLS regression shows that the unemployment rate of
Nigeria had no significant impact as the probability value (0.4096) which it possesses is greater
than 0.05 (Therefore accepting the null hypothesis). Furthermore, the P-values of inflation
(0.2039) and volume of exports of goods and service (0.3961) were all greater than 0.05
(therefore establishing the null hypothesis to be accepted for both.
H0: Economic growth has no causal relationship with unemployment in Nigeria
28
The result of the Granger Causality shows that Unemployment growth has a probability of
(0.4627) to economic growth, this means that the null hypothesis cannot be rejected as its P-
value is greater than 0.05. Also, the economic growth shows no causal relationship with
unemployment, as its probability value (0.3206) is greater than 0.05. Also the P- values of INFG
(0.0685) and VEGS (0.2766) shows no causal relationship with unemployment.
4.4 DISCUSSION OF FINDINGS
This chapter presented, interpreted and analyzed the study’s data. The ordinary least square
multiple regression model results shows that the unemployment data has a positive significant
impact with the economic growth of Nigeria. This contradicts the apriori expectation of the
research.
Furthermore the inflation rate has a positive impact on the nigeria’s GDP which has also
contradicts a apriori expectation. This has also contradicted the norm where normally as GDP of
a country rises, it is expected that the inflation rate falls or be at a standstill.
Also, the volume of exports of goods and services shows a positive significant impact on
the economy’s growth rate. This means that when the nation continue to indulge in exports of
goods and services the economy will eventually grow and thereby causing investors to come in
and invest in the country.
The Granger casualty test though shows that there no casual relationship exist between the
independent variables and the dependent variable. The finding of this study on unemployment
has contradicted the Okun’s law discussed in the literature review of this study.
29
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMENDATIONS
5.1 SUMMARY
Nigeria’s ability to provide for its population does seem to diminish with time although,
having strong fiscal ability which results from extraction and sale of oil. The level of
unemployment in Nigeria has been confirmed to increase every year, while the neighbouring
states have shown a different result even though there exists lower resources in the region.
Nigeria continues to have significant development or increasing the welfare of its people except
that it enhances the chance for graduates to secure jobs. The absence of the ability to do that for
the graduates leaves Nigeria with little or no chance to grow. Hence it can be understood that
high productivity results to having global share of power for Nigeria and its citizens. The
problem of unemployment does keep growing in Nigeria while having in the labour force
approximately 3 million people (mainly youth) coming into the labour market every year. It
should be known that those who constitute this population are not necessarily uneducated or
from rural areas rather they are well educated and reach the standard of employment for
developed countries as well as those who can have great impacts on developing countries.
Nigeria’s low productivity and underemployment comprises a strong cycle which explains the
prevalent poverty in the country. Generally, unemployment has affected the Nigerian youths
from every socio-economic group, ranging from the highly educated to less educated, but strikes
more from the fractions of low income background. It is understandable from the above that
unemployment hinders Nigeria’s progress in many ways. Apart from waste of economic
resources, it does pose danger for political stability (Ipaye, 1998). Unemployment indeed is an
30
economic problem and calls for prompt attention in other to address the socio economic
problems that accompanies it.
5.2 CONCLUSION
The task to fight the increasing state of unemployment is mainly the task of the policy
makers and the managers of the Economy. The negative rise in unemployment rates in an
economy is a major problem that any economy should not risk having. Its effect can be seen in
Nigerian economy where the implication is prominent and are traced mostly to the low or no
availability of jobs for energetic youths. Thus, the need to tackle this problem should be the
major goal of the economy. Definitely, the government takes the leading position where it
provides the economy with a conducive environment that enables many unemployed Nigerians
and those who will enter into the labour force secure jobs, but it should also be noted that the
government should not be left alone to fight this problem. Conclusively from the research work,
it is understood that GDP is not considerable significant for unemployment. Consequently,
conclusion was arrived that GDP constitute a role that it is significant to unemployment but that
which has insignificant levels the macro economic factors of the Nigerian economy.
Unemployment is a serious issue for fixed income investors. It results from the rapid change in
technology, Ups and down in the business cycle, seasonal changes which may affect different
industries either the sails or demand of products and services or the ability for an individual to
work or find a job. Unemployment has presented a great impact (over 60%) on the creation of
Nigerian GDP (relying on whether unemployment increase or decreases) annually under the
years studied. The continuous increase of the unemployment rate in Nigeria has significantly
impacted the in growth of the Nigerian GDP throughout the years. Unemployment plays a role
that an increase in it will create a drawback in the economy and vice-versa. There exist and
31
inverse relationship between GDP and unemployment in the years under study. This study
reveals that among others, capacity utilization is a significant variable of unemployment in the
Nigerian economy. Corrupt practices, inconsistent and lack of macroeconomic policies have
contributed immensely in the increasing rate of unemployment.
5.3 RECOMMENDATIONS
a. Establishment of valid economic policy for the control of unemployment. Government
policies and programs geared towards training youths in various skills and businesses should be
proactive and pragmatic in meeting the dynamic and constant changing business environment
given the current state of the economy.
b. Unemployment can be reduced significantly by the Public Sector Reforms. These reforms
should be emphasized so as to increase human resource development and also utilization of
effective resource.
c. People should not be dependent of the government as this is an idea which is not right. Rather,
they should be self employed by starting a good business.
d. The government should provide its citizen with stable electricity which will enable businesses
to run smoothly which will attract foreign investors in to the economy.
5.4 SUGGESTION FOR FURTHER RESEARCH
This study employed the method of ordinary least square in its analysis; other econometric
techniques other than OLS like: Vector Autoregression Model (VAR), Vector Error Correlation
Model (VECM), e.t.c maybe used to confirm and further the study. Other statistical analysis may
also be employed as well.
32
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36
APPENDIX
DATA PRESENTATION
YEAR GDPG UNEMPG INF VEGSG
1986 1.90 5.3 6.25 -22.05
1987 0.17 7 11.77 202.41
1988 6.23 5.3 34.21 12.14
1989 6.66 4.5 49.02 197.19
1990 11.6 3.5 7.90 -0.97
1991 -0.55 3.1 12.20 37.91
1992 2.19 3.4 44.57 51.82
1993 1.57 2.7 57.14 16.14
1994 0.26 2 57.42 -5.00
1995 1.87 1.8 72.73 212.48
1996 4.05 3.4 29.29 25.63
1997 2.89 4.5 10.67 34.56
1998 2.50 3.5 7.86 -31.13
1999 0.52 17.5 6.62 34.16
2000 5.52 13.1 6.94 117.53
2001 6.67 13.6 18.87 -8.57
2002 14.60 12.6 12.88 14.90
37
2003 9.50 14.8 14.03 35.68
2004 10.44 13.4 15.00 1.22
2005 7.01 11.9 17.86 32.49
2006 6.73 12.3 8.22 72.91
2007 7.32 12.7 5.40 -12.44
2008 7.20 14.9 11.58 39.28
2009 8.35 19.7 12.54 -21.07
2010 11.26 21.1 13.74 80.48
2011 4.89 17 10.83 25.79
2012 4.28 77.37 12.23 -3.59
2013 5.39 -5.78 8.50 -21.74
2014 6.31 -21.24 8.05 24.09
2015 2.65 14.78 9.01 0.09
2016 -1.62 48.61 15.70 11.53
2017 0.81 30.56 16.50 8.74
2018 1.94 29.21 12.09 -0.66
(Sources: CBN 2018 Annual statistics, National Bureau of statistics and IMF statistics)
HISTOGRAM
38
Dependent Variable: GDPGD1Method: Least SquaresDate: 12/05/19 Time: 14:49Sample (adjusted): 1987 2018Included observations: 32 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
C 0.033243 0.685251 0.048512 0.9617UNEMPGD1 -0.036477 0.033008 -1.105101 0.2785
INFGD1 7.28E-05 0.052403 0.001389 0.9989VEGSGD1 -0.007108 0.007576 -0.938239 0.3561
R-squared 0.075056 Mean dependent var 0.001250Adjusted R-squared -0.024045 S.D. dependent var 3.827883S.E. of regression 3.873630 Akaike info criterion 5.662730Sum squared resid 420.1403 Schwarz criterion 5.845947Log likelihood -86.60368 Hannan-Quinn criter. 5.723461F-statistic 0.757370 Durbin-Watson stat 2.681626Prob(F-statistic) 0.527469
GDPGD1 UNEMPGD1 INFGD1 VEGSGD1 Mean 0.001250 0.747187 0.182500 0.668438 Median 0.510000 -0.300000 0.960000 3.070000 Maximum 7.930000 60.37000 32.37000 224.4600 Minimum -12.15000 -83.15000 -43.44000 -198.1600 Std. Dev. 3.827883 21.12576 14.55313 100.4842 Skewness -0.772690 -1.068231 -1.130482 0.161431 Kurtosis 4.889447 10.89213 6.036421 3.444914
Jarque-Bera 7.944281 89.13369 19.10908 0.402917 Probability 0.018833 0.000000 0.000071 0.817537
Sum 0.040000 23.91000 5.840000 21.39000 Sum Sq. Dev. 454.2334 13835.23 6565.602 313009.4
Observations 32 32 32 32
39
Pairwise Granger Causality TestsDate: 06/18/20 Time: 16:57Sample: 1986 2018Lags: 2
Null Hypothesis: Obs F-Statistic Prob.
INFG does not Granger Cause GDPG 31 2.97662 0.0685 GDPG does not Granger Cause INFG 1.03327 0.3700
UNEMPG does not Granger Cause GDPG 31 0.79391 0.4627 GDPG does not Granger Cause UNEMPG 1.29015 0.2923
VEGSG does not Granger Cause GDPG 31 1.35070 0.2766 GDPG does not Granger Cause VEGSG 0.56431 0.5756
UNEMPG does not Granger Cause INFG 31 0.76523 0.4754 INFG does not Granger Cause UNEMPG 1.57027 0.2271
VEGSG does not Granger Cause INFG 31 1.45143 0.2526 INFG does not Granger Cause VEGSG 2.37033 0.1133
VEGSG does not Granger Cause UNEMPG 31 0.32294 0.7269 UNEMPG does not Granger Cause VEGSG 0.79549 0.4620
0
2
4
6
8
10
12
-12.5 -10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
Series: ResidualsSample 1987 2018Observations 32
Mean -1.67e-16Median 0.266004Maximum 8.027535Minimum -11.92180Std. Dev. 3.681428Skewness -0.861890Kurtosis 5.316077
Jarque-Bera 11.11417Probability 0.003860
40
41
-4
0
4
8
12
16
1990 1995 2000 2005 2010 2015
GDPG
-40
-20
0
20
40
60
80
1990 1995 2000 2005 2010 2015
UNEMPG
0
20
40
60
80
1990 1995 2000 2005 2010 2015
INFG
-50
0
50
100
150
200
250
1990 1995 2000 2005 2010 2015
VEGSG
Null Hypothesis: D(GDPG) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=8)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -7.618485 0.0000Test critical values: 1% level -4.284580
5% level -3.56288210% level -3.215267
Null Hypothesis: D(INFG) has a unit rootExogenous: Constant, Linear TrendLag Length: 8 (Automatic - based on SIC, maxlag=8)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -6.481199 0.0001Test critical values: 1% level -4.416345
5% level -3.62203310% level -3.248592
Null Hypothesis: D(UNEMPG) has a unit rootExogenous: Constant, Linear TrendLag Length: 4 (Automatic - based on SIC, maxlag=8)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -4.379425 0.0091Test critical values: 1% level -4.339330
5% level -3.58752710% level -3.229230
Null Hypothesis: D(VEGSG) has a unit rootExogenous: Constant, Linear TrendLag Length: 3 (Automatic - based on SIC, maxlag=8)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -5.049873 0.0018Test critical values: 1% level -4.323979
5% level -3.58062310% level -3.225334
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