Labor Market Dynamics in Albania
by
Mabela Ismailaga, BA
Thesis submitted for the degree of Master of Science
Department of Banking and Finance
Epoka University
December 2014
Approval Page
Thesis Title
:
Labor Market Dynamics in Albania
Author
:
Mabela Ismailaga, BA
Qualification
:
Master of Science
Program
: Banking and Finance
Department
: Banking and Finance
Faculty
:
Economics and Administrative Sciences
Thesis Date
:
December 2014
I certify that this thesis satisfies all the legal requirements as a thesis for the degree of Master
of Science (MSc)
Assist. Prof. Dr. Urmat Ruskulov
Head of Department
I certify that I have read this study that is fully adequate, in scope and quality, as a thesis for
the degree of Master of Science (MSc)
Prof. Dr. Güngör Turan
Supervisor
ii
Exam Board of Thesis
Thesis Title
:
Labor Market Dynamics
Author
:
Mabela Ismailaga, BA
Qualification
:
Master of Science
Date
:
December 2014
Members
(Title, Name and Signature)
……………………….
(Title, Name and Signature)
……………………….
(Title, Name and Signature)
……………………….
iii
Abstract
This thesis analyzes empirically the co-integrating relationship between unemployment and
GDP in the Albanian economy in 1991-2013. Since one of the variables used in this master
thesis are non-stationary and present a unit root, Johansen’s co-integration technique has been
applied. This methodology has allowed for obtaining of a co-integrating relationship among
variables in the long run. The co-integration results provide evidence of a unique cointegrating vector. In other words, in the long-run in Albania, GDP and unemployment have
moved together in the inverse direction in the long run.
Key Words: unemployment, GDP, Johansen co-integration test, Albania.
iv
Abstrakt
Kjo teze analizon nga pikepamja empirike marrdhenien ko-integruese midis papunesise dhe
prodhimit te brendshem bruto (PBB) per ekonomine shqiptare ne vitet 1991-2013. Duke qene
se variablat ne kete teze jane jo-stacionare dhe shfaqin rrenje-njesi, eshte zbatuar teknika kointegruese e Johansen. Kjo metodologji ka lejuar perftimin e nje marredhenieje ko-integruese
midis variablave. Rezultatet e ko-integrimit deshmojne ekzistencen e nje vektori unik kointegrues. Me fjale te tjera, ne periudhen afatgjate ne Shqiperi, papunesia dhe PBB kane
levizur se bashku ne drejtim te anasjelle.
Fjalet Kyçe: papunësia, PBB, testi ko-integrues Johansen, Shqiperia
v
Dedication
I would like to dedicate this humble piece of work
to My Beloved Parents
for their endless love, support and encouragement.
Thank you for inspiring me to follow my dreams.
vi
Acknowledgements
I cannot express enough thanks to Prof.Dr. Gungor Turan, for his unconditional help,
guidance and patience and being always there for my questions.
My completion of this paper could not have been accomplished without the support of my
family and FSVC – thank you for allowing me time away from you to research and write.
For all my beloved ones, my heartfelt thanks.
vii
Declaration Statement
1. The material included in this thesis has not been submitted wholly or in part for any
academic award or qualification other than that for which it is now submitted.
2. The program of advanced study of which this thesis is part has consisted of:
i) Research Methods course during the undergraduate study
ii) Examination of several thesis guides of particular universities both in Albania and abroad
as well as a professional book on this subject.
Mabela Ismailaga
December 2014
viii
TABLE OF CONTENTS
APPROVAL PAGE .................................................................................................................. II
EXAM BOARD OF THESIS ................................................................................................. III
ABSTRACT ............................................................................................................................ IV
ABSTRAKT ............................................................................................................................. V
DEDICATION ........................................................................................................................ VI
ACKNOWLEDGEMENTS ................................................................................................... VII
DECLARATION STATEMENT ........................................................................................ VIII
TABLE OF CONTENTS ........................................................................................................ IX
LIST OF TABLES .................................................................................................................. XI
LIST OF FIGURES ............................................................................................................... XII
LIST OF GRAPHS .............................................................................................................. XIII
LIST OF ABBREVIATIONS .............................................................................................. XIV
LIST OF PUBLICATIONS BY THE CANDIDATE ........................................................... XV
LIST OF APPENDIX .......................................................................................................... XVI
INTRODUCTION.................................................................................................................... 1
CHAPTER 1. LITERATURE REVIEW ............................................................................... 2
CHAPTER 2. ALBANIAN LABOR MARKET ................................................................... 4
2.1 Long-Run Growth and Labor Market Trends ...................................................................... 5
2.2 Employment Developments ............................................................................................... 10
2.3 Employment and fertility rate ............................................................................................ 12
2.4 Unemployment developments ........................................................................................... 13
2.5 Brain drain and migration .................................................................................................. 15
2.6 Determinants of unemployment ......................................................................................... 18
2.6.1 Unemployment and Gender ........................................................................................ 18
2.6.2 Unemployment and age .............................................................................................. 20
2.6.3.Unemployment and education .................................................................................... 20
2.7 Strategic priorities for employment and skills development ............................................. 22
ix
CHAPTER 3. AN EXAMINATION OF THE LONG RUN RELATIONSHIP
BETWEEN UNEMPLOYMENT AND GDP………………………………………….….23
3.1 Model and data specification……………………………………………………….……23
3.2. Descriptive statistics………………………………………………………………….…23
3.3 Johansen co-integration test……………………………………………………………..27
3.4. Granger causality Test…………………………………………………………………..34
CONCLUSION ..................................................................................................................... 35
x
List of Tables
Table 1: Descriptive statistics of unemployment and real GDP series………………………………..25
Table 2: Estimation equation output of regression (unemployment and real GDP at levels)…………25
Table 3: Stability diagnostic/Recursive estimate (OLS only) /CUSUM Test………………………...26
Table 4: Estimation equation output of regression………………………………………...……….....26
Table 5: Stability diagnostic/Recursive estimate (OLS only) /CUSUM Test………………………...27
Table 6: ADF Unit Root Test of Unemployment (Level and First Differences)……………………..28
Table 7: ADF Unit Root Test of GDP (Level)………………………………………………………..31
Table 8: Johansen Co-integration Test Results………………………………………………………..33
Table 9: Pair wise Granger Causality Test Results……………………………………………………34
xi
List of Figures
Figure 1: The evolution of GDP, aggregate employment and productivity…………….…6
Figure 2: Employment and output share across sectors…………………………………...6
Figure 3: Labor force participation rate …………………………..……............................9
Figure 4: Employment rate……………………………………………………………….11
Figure 5: Employment according to sectors……………………………………………...12
Figure 6: Fertility rate…………………………………………………………………….13
Figure 7: Average monthly salary in state sector & fertility rate…………………………13
Figure 8: Unemployment Rate……………………………………………………………14
Figure 9: Registered unemployment by age group……………………………………….14
Figure 10: Average monthly wage by occupations in public sector……………………...15
Figure 11: Average monthly wage & minimum wage……………………………………15
Figure 12: Net migration………………………………………………………………….17
Figure 13: Unemployment by gender…………………………………………………….19
Figure 14: Unemployment rate according to age groups…………………………………20
Figure 15: Employed in the state sector according to education level……………………22
Figure 16: Histogram and statistics of real GDP series……………………………….…..24
Figure 17: Histogram and statistics of unemployment series……………………………..25
xii
List of Graphs
Graph 1: Bar graph showing female labor force participation ……………………….……..10
Graph 2: Bar graph showing male labor force participation ………………………………..10
Graph 3: Real GDP and unemployment series in Albania1991-2013……………………….23
Graph 4: Unemployment and real GDP series in Albania, 1991-2013, scatter diagram…….24
xiii
List of Abbreviations
EMA
European Movement Albania
EU
European Union
GDP
Gross Domestic Product
LFS
Labor Force Survey
INSTAT
Institute of Statistics
MACB
Mean age child bearing
TFR
Total fertility rate
CEDAW
The Convention on the Elimination of All Forms of Discrimination
against Women
EEC
East European Countries
xiv
List of Publications by the Candidate
Author:
Mabela ISMAILAGA
Co-Author:
Gungor TURAN
Title:
Labor market dynamics in Albania
Pages:
476-485
Year:
2013
Conference Publication Name:
ICES`13
City:
Tirana
Publisher:
Epoka University
ISBN No:
978-9928-135-09-4
Author:
Mabela ISMAILAGA
Title:
INFLATION AND NOMIMAL INTEREST RATES
Year:
2011
Conference Publication Name:
ISCON 2011
City:
Tirana
Publisher:
Epoka University
ISBN No:
xv
List of Appendix
Appendix: INSTAT Data for Johansen Co-integration test
xvi
Introduction
Since 1990’s, Albania has gone through tremendous changes from a communist regime to a
democratic one. During this process, most of the state-owned properties were privatized.
Albeit during the communist regime Albania was a production-based economy, in the
democratic era it revamped in a service-based economy. This led to increase in labor force
and a decline in unemployment. Another prominent influence in the Albanian labor market
was also the development of foreign investments. Many foreign corporations launched to the
fore, factories in Albania which helped locals get employed. Although the democracy
amplified many facets, there were also detriments which directly affected the commonalty.
One of them was emigration, where it is reported that more than 2 million Albanians left their
home country to quest better life standards in Italy, Greece, Germany and USA. The majority
of the men residing in the south of Albania, aged 18-30 emigrated in Greece and got
employed in the construction industry. Back in their homes they left their old relatives which
were out of the labor market force, thus producing a strong imbalance.
Within the last decade there has been an increase in demand for the Albanian labor market,
with two strong factors altering it. To begin with, most of Albanian teenagers are
multilingual, being able to grasp new languages with less effort, and last but not least the
average salaries in Albania are 3 times lower when compared to the region. Many Italian,
Greek and German companies have outsourced most of their work in Albania (especially
telecommunication), thus shrinking their costs and boosting their profits.
This master thesis examines the labor market in three profound chapters. In this first chapter,
an insight of different empirical papers and their findings are analyzed as relate to the
Albanian labor market. Chapter 2 analyzes the labor market in Albania more in depth and the
main determinants that affect the unemployment. Chapter 3 concludes with the research
methodology, regression model, data specification, ADF unit root tests, Johansen cointegration test and Granger causality test to understand the relationship between
unemployment and real GDP in the long run in Albania.
1
Chapter 1
Literature Review
Labor market is central to an economy as labor is one of the main factors of production,
therefore unemployment is of great concern to economists and the economy state
(Kydland, 1995). Albania is a country that has undergone a process of transformation,
and for an economy in transition as also stressed by Mark (1997), it is anticipated to have
a reduction of employment share in the state sector, and a rise in the private sector. In an
economy with limited or no experience in the job searching, lack of efficient programs to
provide references and trainings for employees, have all pushed labor force participation
lower. The difficulty to estimate the relation between the labor productivity and the
working hours, as pointed by Kydland and Prescott (1982), led to discussions and
theories in relation to labor markets, like the ones from Hansen (1985), Rogerson (1988)
and McGrattan (1994). This phenomenon is similar to the case of Russia which
transitioned to a market economy. As also Mowla (2011) emphasizes, job search is
essential in the labor market. The main factors which alter it are the intensity and the
tactics to search for a job. As Smirnova (2003) points out, sometimes only searching for
a job is not sufficient, on the contrary it is the intensity to search for it.
In several publications there are a number of search methods exhibited (Masague, 2008;
Smith, 2003; Brown &Taylor 2008). Nonetheless they fall in two main groups; informal
and formal search methods. Each group has its own allies and opponents. Informal
methods are less costly and more socially oriented, emphasized by Koning, (1997),
whereas in some other countries, like England, which are regulated, the formal methods,
like official labor offices are favored more when it comes to job search (Gregg &
Wadsworth, 1996). In Albania, several labor offices were established in some major
cities, in 1999, in order to ease the job- search process. Consecutively through these
offices unemployment benefits are carried out (Pema, 2010).To some extent, the informal
ways are preferred to those people who require lower skill requirements. As Paik (2008)
mentioned, internet has played a vital role worldwide. Via integrated websites now many
people can quest for different jobs online, filter the results according to their
2
preferences and take advantage of the job supply online. Nonetheless several studies have
shown that there is no proven evidence that unemployed people who seek for job
opportunities online, have become employed more quickly than the ones who search via other
means (Kuhn & Skuterud, 2004).When carrying out an analysis of the labor market in the
Albania, the available information is scarce, since Albania has a transition history, which in
turn has grown informal sector, resulting in an arduous process of finding reliable source of
information and data (Pema, 2010). As it turns out from later data, there has existed and still
does a gap between the unemployed female and male citizens. Different literature sources
have theorized that usually females do not actively seek for a job as males do (Tasci, 2008;
Lilja &Torp, 2002). Nevertheless there are some plausible reasons to explain the gap; like the
job search methods, marriage as emphasized by Bowen and Doyle (2004), marital status, and
abdicating during the search period. By any means, women are more efficient in the jobsearch process (Werbel & Mcelory2003).
Having swapped to a free market economy, many factors changed in the socio-economic
environment in Albania. Albania during the communist regime did not have candid family
planning policies, and since at that time it already had a high fertility rate this was not
deemed as necessary (Gjonça et al., 2008). Contrarily at that time there were several health
policies which aimed to reduce the mortality rates, which in turn hiked the fertility rate
further (Gjonça et al., 2006).After the fall of the communist regime, Albania’s fertility rate
slumped substantially and apart from migration and other social and economic factors,
Albania has got a steady fertility rate, which in the long run must be either addressed by the
right policies to be maintained at such level, or increase. Following the trade liberalization,
Albania was continuously affected by internal and external migration. By no means,
internally it was characterized by rural-urban moves. The industrialization prompted
significant changes, with the population living in extreme poverty and being prone to
illnesses, mentioned by Skendi (1956), with tuberculosis as the most common (Gjonça,
2001).
The relationship between output growth and unemployment can also be interpreted by the
theory of macroeconomic fluctuations. The assumption that unemployment restricts growth
was later opposed by the rationale that recessions stimulate efficiency gains which makes less
efficient firms exit the market. In the other side this creates space for more efficient firms
which cause faster output growth (Caballero and Hammour, 1994). However Muscatelli and
Tirelli (2001) assume that another force which explains the negative relationship between
growth and unemployment is also the fact that higher growth means that firm’s profits will
3
increase by opening new vacancies, which leads them do the latter thus lessening
unemployment. Nonetheless this view is challenged by Zagler (2003), who claims that in the
long run unemployment and economic growth are positively correlated which is in
disagreement with Okun’s law. Whereas in the short-run the dynamics remains consistent
with Okun’s law, where unemployment falls as output rises. However Aghion and Howitt
(1994) support the idea that long run economic growth can derive from increase in
knowledge. Advancement in knowledge is exhibited through industrial innovations which are
achieved through automation, skills-obsolescence and technological advancement which are
all likely to increase job destruction in the long run.
CHAPTER 2
ALBANIAN LABOR MARKET
Chapter 2 attempts to explain the long run growth in the Post-Communist period. Labor
market in Albania during the last decade has seen significant improvements in employment
rates. According to the 2013 Labor Force Survey (LFS), labor force participation rate was
59.9 percent (70,2 percent-males and 50,4 percent–women). Social determinants of
unemployment along with limitations like gender, age and education are further explained in
Section 2.6. Compared to 2012, the total number of employed people declined by 11.2
percent (LFS, 2013). Despite unemployment rate has declined, as of 2013 the male
unemployment rate was higher than female unemployment rate respectively 17.5 percent and
13.2 percent (LFS, 2013).Total employment is dominated by the agricultural sector (44.6
percent), and the services sector (37.9 percent) (LFS, 2013). Given the transition to a market
economy in the early 1990s, Albania experienced low economic growth. Privatization of
state-owned companies, which is further described in section 2.1, was poorly planned since
the very beginning. When the financial crisis hit, Albania was not very vulnerable, since it
was not very exposed to international markets. Informal employment in Albania remains
high. Several studies have provided numbers from 30 percent to 60 percent which measure
the extent of informal employment in Albania (Mihes et al., 2011).Nevertheless informal
employment is more common in rural areas, where labor inspection is not very eminent.
(Mihes et al., 2011). As described further in this chapter regulation is very important, since
over or under regulation can affect the informal employment. Envelope wages are very
widespread in Albania, where in order to avoid paying higher taxes employers register the
4
employees at minimum wage, and pay the other share of the salary in cash (Baliu, 2008).
This is an alarming fact which has serious implication in the tax revenues of a country. The
chapter closes with strategic priorities for employments and skills development.
2.1 Long-Run Growth and Labor Market Trends
Albania used to be one of the fastest-growing European economies, which has significantly
boosted its economic fundamentals in establishing a prolific market economy in less than 25
years. The transition to a market economy caused the restructuring of the economy (Fischer
et al., 1996). Despite the overall output slump at the beginning of year 90s the decline was
mostly felt in heavy industry and mining sectors (Gjipali, 2007). Cross-country analysis
shows that market regulation, which bolsters fair and orderly markets at prices which reflect
the fundamental values, is an important factor in financial development. Labor market
regulations improve the employment situation and protect workers to achieve labor market
efficiency.
Given that each market consists of a buying and selling process- labor market which
essentially buys and sells peoples’ services- requires careful regulation. Labor market
regulations cannot be taken as models from developed countries to be implemented in
developing countries given the limited resources of the latter. The policymakers must take
into consideration also the impact of such regulations in the country’s specific conditions.
However one of the main challenges that remain is to avoid over-and under regulation which
could cause social and economic unrest (Betcherman, 2014). It is important to come up with
an adequate level of regulation which helps labor force but at the same time does not put
businesses in hardship. Albania currently has unemployment protection schemes but lacks
court sections specializing in labor disputes (Doing business-World Bank).
5
Figure 1. The evolution of GDP, aggregate employment and productivity.
Source: Gjipali, A comparative analysis of labour market during transition in Central and EEC with a focus in
Albania, accessed on 21 March 2015
As it can be observed from Figure 1 data (as a measure of their value to 1989) in Albania the
GDP growth and employment have followed opposite path. Despite Albania has followed an
upward trend, its economic growth lags behind compared to other South Eastern European
(SEE) countries. The growth in productivity can be explained by looking more in-depth in the
developing sectors. Agriculture continues to be one of the most important sectors which
generates employment and income and represents around 20% of GDP while accounting for
about half of total employment (World Bank). However sectors like services and construction
(Figure 2) represent a higher share in output level compared to the agriculture, but they
contribute a small share in employment (Gjipali).
Figure 2. Employment and output share across sectors.
Source: Gjipali, A comparative analysis of labor market during transition in Central and EEC with a focus in
Albania, accessed at 21 March 2015
The fall of communism in the early 90s negatively affected the economic growth with the
decrease of GDP of around 27.7 percent (Themeli, 2012). By the end of year 1990 the
economic policies in Albania aimed maintaining macroeconomic stability and poverty
6
reduction while preserving fiscal consolidation by reducing the public debt and budget deficit
(Shijaku & Gjokuta, 2013). GDP grew on average by 9% during the first four years of
transition, mainly supported by migrants' remittances. These important financial flows from
the migrants continued to be the main source of financing the trade deficit. The current
account increased as a consequence of high savings (Themeli, 2012). The emergence of
Ponzi schemes between 1993-1997, which attracted the majority of the population by
promising high return with little to no risk to investors, hit the economy hard. Following their
collapse in 1997, the GDP fell by 10 percent and inflation escalated to 40 percent (Musaraj &
Sullivan, 2014). The Ponzi schemes other than creating an overall negative effect in the
economy also resulted in general public mistrust in the financial institutions. Nevertheless,
the economy recouped rapidly with a growth rate of real GDP in 1998 to 8.6 percent. Before
the global financial crisis elevated, Albania was growing at real growth rates of 6 percent
(World Bank). The collateral damage was felt in poverty and increase of unemployment.
Privatization, the process of reallocation of resources from the public sector to the private has
played an important role in the economic growth. Privatization allies argue that it can provide
an array of significant improvements. In Albania the sector privatization was implemented in
1998. Unfortunately this process was poorly-planned since the very beginning (Cano, 2009).
Nevertheless, governmental efforts to strengthen this movement and help plan a privatization
policy, unfortunately the result of this process was biased by the high level of corruption and
governments private interests (Papajorgji, 2014). As a result, the privatization process did not
bring the desired effect and did not translate in improved efficiency.
Despite low-income countries were not very vulnerable to the financial crisis as the
developed countries, its impact was shown in rise of bad credit and declining interest rates in
markets. First wave of the financial crisis had a very low initial impact which later became
stronger as reflected in economic growth slowdown, contagion fears through Greece and also
the fiscal performance. The economic growth stagnated at remarkable at rates of 3.3 percent
in 2009 (Kota, 2009). Despite Albania is trying to progress it still has a long way towards
renewed economic strength.
One of the main characteristics of Albania is its youthful population; with 69 percent of its
population part of the working group (15-64 year old). As of 2013 the labor force in Albania
was 1,175,919 people. Total employment was prevailed by the agriculture sector which as of
2013 amounted 44.6percent of the total and the service sector 37.9 percent (LFS, 2013). In
addition to the existing unemployment size in Albania, it still remains difficult to estimate
7
exact number of unemployed people due to the informal market, which according to the LFS
in 2013 it amounted 43 percent of the total employment in the non-agricultural sector. The
unemployed registered citizens have declined, and in the same time also the gap between the
unemployed females and males. Nonetheless the number of employed men remains still
higher than that of females, thus signaling inequality among men and women. A main
provider for the employment level is the agricultural private sector, which in turn requires
unskilled labor. The labor force participation rate is lower for younger part of the population
(15-39) and higher for the older group of the population (30-64). The low participation rate
for the younger part of the population can be attributed to the young people who attend
school. However the unemployment tendency for group ages of 15-19 has steadily decreased
over time. Albania labor market has several defining characteristics, which also have impacts
on the economy as whole, such as migration. The total number of returned migrants in
Albania since 2001 is 139.827, a phenomenon which was partly influenced by the impact of
the Greek crisis (Census, 2011).
Albania has gone through a process of massive changes, from a centrally planned economy to
a market economy. After the communist regime, unemployment increased to a large extent.
The main sectors that underwent development were trade and construction sector, which
apart from “gender specific factors” have contributed to the gap between employed women
and men. These are sectors which require men labor force, without casting aside also the
gender discrimination. During the transition period after the collapse of communism, there
was a massive decline for the females participating in the labor market. This can be attributed
mainly to the communism period, where females were forced to work due to social pressure
and with the transition to a market economy, many females chose not to work, dedicating
themselves to the raise of their children.
8
Male
66.9
49.5
2007
61.7
45.7
2008
64.9
46.2
2009
Female
64.0
46.9
2010
67.9
52.9
2011
66.2
49.7
2012
61.8
44.3
2013
Figure3.Labor force participation rate from INSTAT data accessed, 15 November 2014.
One the main important feature of the Albanian Labor Market is the gap that exists between
the employed males and females. In principle Albania provides on its legal framework, the
principle of equal treatment and against gender discrimination, which appears different from
the true reality. After year 1990 until 1996 the main employer of the labor market was the
agricultural sector. The non-agricultural sector comprised a little share of the Albania
employment. The private sector mainly encompassed construction and manufacturing sector,
whereas the public sector was primarily for health and education. Several studies and surveys
have explained the difference between female and male employment rates. Certain sectors
within the private sector required more male-labor force than female; like construction and
manufacturing. Due to the higher principles of gender equality in the public sector than on the
private sector, the number of employed women is higher on the public sector. Another
phenomenon noticed is the fact that women usually get lower employment rates (salaries)
than men, with the same education level. To understand such anomaly, one must be aware of
many other factors that influence such number. Apart from the discriminatory tradition of the
system and being a patriarchal economy, factors like; marital status, women taking care of the
family and also gender discrimination make females accept lower employment rates.
According to INSTAT data, females’ employment rate is lower than in the rural areas, and
this happens mainly from the high level of migration that has happened lately from rural to
urban areas, emerging of sectors that require male labor force and also the termination of
industrial activities.
9
Graph 1.Bar graph showing female labor force participation from INSTAT accessed, 15 November
2014.
Over the past few years, female’s participation in the labor force has decreased. Apart of
gender discrimination which is described in the later section more thoroughly, there is
females’ willingness and past history to be more involved in caring and house activities.
Graph 2. Bar graph, showing male labor force participation from INSTAT accessed, 15 November 2014.
At the same time, male labor force participation has followed the same trend and this can be
associated by the increase of male participants in the informal market and also immigration.
According to INSTAT, a vast majority of Albanian males aged 18-30 (approx. 300,000500,000) have immigrated abroad during the last decade, and are now working on their
respective countries.
2.2 Employment Developments
The restructured economy change in 1990’s led to a decrease in the employment in the public
sector. This decline was attributed to the mass privatization of state owned enterprises which
during the communist regime were centralized. The most affected industries were the
industrial sector, especially the extraction of minerals, metallurgy, chemical industry, textiles
10
and other similar industries. However during the same period there was a vast increase in the
services sector despite most of the labor force were men.
From 2002 to 2005 more than 80 percent of the total number of employed registered
individuals was in the private sector. Most of the communist countries have experienced the
same increase in the private sectors after transitioning to a capitalistic market. Albania prior
to 1990 had no private sector and by 1994 had more employed individuals in the private
sector than any other transition counties of the same region. This was caused from the rapid
privatization of the agricultural sector, a process which was finished by 1993.
Male
57.3
57.0
54.0
43.4
2007
Female
58.6
55.9
56.6
51.0
45.3
39.4
2008
38.9
2009
39.5
2010
43.7
38.4
2011
2012
2013
Figure 4.Employment rate from INSTAT data accessed, 06 November 2014.
The number of employed people in the private sector is continuously increasing compared to
the public sector. The agricultural private sector consists the biggest number of registered
people employed whereas the non-agricultural sector has been increasing in the recent years
and moving towards the service-oriented sector.
11
800,000
700,000
600,000
500,000
400,000
300,000
200,000
100,000
0
State Sector
Non-agricultural
private sector
Private
Agricultural
Sector
200020012002200320042005200620072008200920102011
Figure 5. Employment according to sectors with INSTAT data accessed, 06 November 2014.
2.3 Employment and fertility rate
An important indicator that affects the development of a country through the population size
is the fertility rate. Albania, a country inheriting patriarchal elements from the past, has
always had a high fertility rate. In 1960 this rate was 5.96. During years 1970 emphasis was
also put on education. As also stated by Gjonca, et al., (2008), market liberalization, notably
during 1967, the year when Albania forbade religion, young girls could attend school freely.
Undoubtedly education is directly linked with fertility rate, where education growth has
brought fertility reduction. In different countries there does exist a well-known phenomenon,
which shows that total fertility rate (TFR) is directly proportional to the mean age of child
bearing (MACB). In periods with high fertility rate also MACB has been high, precisely
about 31.7. Until the 2000s in Albania these two indicators lowered at the same pace with
MACB reaching 27.7. But ever since, the fertility rate has declined, in 2011 it was 1.52 albeit
MACB has hovered at 28. After 1990, with the liberalization of the market, fertility rate
declined substantially, even though population was not yet introduced by that time to
concepts such as abortion and contraception. Important factors which affect the contraction of
fertility rate are the level of salaries, remittances and unemployment. Given the increase in
wages, it shows welfare and decrease of the fertility rate. As there might be no direct
evidence of link between these two variables, it relates to education too. It was noted that
fertility rate is dependent also to the degree of education. For the first child there is no
change, while in the case of a third child, this varies greatly according to education degree,
where for women with lower education , there is a higher tendency for a third child . With the
market liberalization, another change was the mass migration of population regardless of
education level. This led to male-female ratio imbalance, and it is yet another factor that has
affected fertility. Unemployment and especially a low level of female participation in the
12
labor force have widely influenced the decision to have a second or a third child. As different
developed countries try to adopt policies to increase fertility, Albania, has always managed to
maintain high record rates. However this is a condition that requires vigilance to be held at
these levels, or to increase in the near future if deemed necessary.
Figure 6. Fertility rate from World Bank database accessed, 18 June 2014.
60,000
2.5
50,000
2
40,000
1.5
30,000
1
20,000
0.5
10,000
0
0
Monthly salary
Fertility Rate
Figure 7.Average monthly salary in state sector and fertility rate with data from INSTAT accessed, 18 June
2014.
2.4 Unemployment developments
The regime change called for added consideration at the unemployment level. Since there
isn’t a reliable statistical database, to perform an analysis of unemployment market, this
paper will rely on the limited data available and also from the LFS for the Albania Labor
market in the recent years. There are also other factors which make it further challenging to
13
potentially identify the exact number of unemployed people. The informal sector which has
increased, along with the high level of unemployment is the most important component;
agriculture has created obstacles for the proper identification of unemployment. Agriculture
accounts for about half of total employment in Albania, but unfortunately lack of the
necessary equipment’s and know-how, have made this sector constitute a very small part of
GDP. The highest level of unemployment was recorded in early 1992, at the nascent of the
market economy at that time, which amounted to about 26 percent. The first decline occurred
in 1997 at the level of approximately 14 percent. The other increase in 2002-2003 was about
17 percent. In 2011 it was 13.3 percent. The most rewarding professionals are managers, who
are rewarded with salary totaling approximately ALL 82,000 in 2013, when the minimum
wage was ALL 22,000. As expected, private sector wages in different profession sare twice
as high as those in the state sector.
Male
Female
15.9
15.8
14.3
12.2
2007
12.5
13.7
2008
12.2
2009
12.6
2010
17.5
13.6
14.4
14.5
13.2
12.1
2011
2012
2013
Figure 8.Unemployment Rate from INSTAT data accessed, 06 November 2014.
500000
400000
35 years old
300000
20-34 years old
200000
15-19 years old
100000
Total
0
2000200120022003200420052006200720082009201020112012
Figure 9.Registered unemployment by age group from INSTAT data accessed, 06 November 2014.
14
100,000
80,000
Managers
60,000
Professionals
40,000
Technicians
20,000
Clerks
Workers
0
Figure 10.Average monthly wage by occupations in public sector, 2000-2013 from INSTAT data accessed, 06
November 2014.
60,000
50,000
40,000
30,000
Average monthly wage
20,000
Official minimum wage
10,000
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
0
Figure 11.Average monthly wage & minimum wage from INSTAT data accessed, 06 November 2014.
2.5 Brain drain and migration
Human capital is one of the most important elements in the economic development of a
country and thus requires special consideration by the policy makers. Albania is a country
which is dominated by a young population with a mean age of 30 year old. The regime
change, embraced by the cultural and economic changes influenced in massive migratory
movements. Despite continuing population growth after World War II until 1989 by more
than 2% in a year, it was shortly overshadowed by the massive number of people, almost
600,000) who left the country as thus reducing the total population by 3.5% (INSTAT, 2002)
(Calogero et al., 2006).
The arduous economic transformation and political instability, after the shift of the regime
brought great migration of population towards developed western capitalist countries.
Albania is has experienced massive emigration movement, especially after the period of the
transition of systems. During the rule of the Turkish Empire mass immigration was directed
toward Italy. Then amid years 1940-1945, around 19,000 people who were against the
communist regime migrated. During the communism period in Albania, international
15
migration was prohibited by law, and internal migration was limited. After the fall of the
communist regime, in the absence of migration policies, Albania experienced large internal
and international migration movements (Calogero et al., 2006). From rural areas,
approximately 900,000 people migrated to urban areas. This led the population number to
shrink in rural areas by nearly 13 percent. In July 1990, approximately 5,000 people entered
into the Italian, German and French embassies in Tirana and asked for visas. By the end of
the year 1990-1991 roughly 38,000 Albanians had emigrated to Greece and Italy (Migration
in Albania-Population and Housing Census, 2001).
For the last 10 years (Figure 5) the number of employed individuals in the private agricultural
sector has declined substantially. Undergoing transition process, Albania was opened to a
new labor market and per se the political and economic situation were challenging, thus
increasing immigration level especially to the nearest countries like Italy and Greece. The
main sector that experienced highest decline after the transition was the public sector which
did not match an increase of employment in the private sector. But it raises inevitable
question how migration and the flow of remittances would affect employment for the family
members left behind on the home country. Inflows in the home country (remittances) would
have an adverse effect on individuals’ willingness to work (Funkhouser, 1992; Tiongson,
2001). The left behind family members would now be provided the necessary funds for living
and thus would instead choose not to work. But data from past history have shown that
remittances have positively impacted self-employment.
During the past 20 years, emigration resulted in massive "brain drain" in Albania. Brain drain
is the migration of high skilled workers for higher pay and conditions. According to a report
by the European Movement Albania (EMV) (2010), brain drain is a permanent loss of a vital
driving force of any country. This migration tendency is noticed mainly at the younger
portion of the population, of which young people with primary education are the main group
of people who want to migrate and comprise 55 percent of the total population. 34 percent are
the proportion of young individuals with a tertiary education who want to migrate. The main
reasons are the hardship to be part of labor force for the people having only primary
education and inability of the supply to meet demand in the labor market. General migration
and brain drain toward more developed countries are motivated by factors such as better
employment opportunities, qualitative education and a better socio-economic position.
Brain drain has a negative impact; both on a developed and a developing a country. Albania
the case of a developing country showed that brain drain can have long term negative effects.
Unfair treatment of different economic status is another reason that causes brain drain. The
16
majority of people working nowadays are graduates holding also a PhD degree. Albania,
during its early years after transition lacked research methods and tools, and this can be also
attributed to drain of the skilled labor working abroad. This rate has declined considerably
after year 2000. Improvements on the education conditions, research institutions and a better
economic situation impeded skilled workers migration.
100000
0
-100000
-200000
-300000
-400000
-500000
Figure 12. Net migration from World Bank database accessed, 15 November 2014.
Aiming for further improvement and emphasizing brain gain, several laws and decisions were
amended by the Council of Ministers. Different steps were undertaken with the purpose of
attracting back to home country skilled workers. Improving living conditions, setting up
research centers in universities, backing them financially, providing incentives for working
on the public sector and participating even more in the economic and political life of Albania,
comprise the steps that aimed to tackle migration and return of the highly qualified people.
Nevertheless such advancement, there remains necessity to undertake greater actions to
enable the return of ambitious labor. The incentives and amendments in laws and decision
pertained mainly to the public sector not to the private, and such move cannot be considered
as highly successful. Among other deficiencies to absorb the skilled labor, remains the fact
that even though there have been positive economic and politic changes, Albania still lacks
opportunities for such individuals. Competition which is the main driver of development, in
Albania is missing. Fair competition which could promote their return certainly doesn’t exist.
Individuals usually adhere to informal methods of finding a job and unfortunately this still
relies on political viewpoints especially in the public sector. This in turn brings insecurity and
makes the job heavily dependent on political changes. So given Albania’s aspirations to be
part of the big developed European family, policymakers should bear in mind that such big
milestones can only be achieved by investing more on human capital and take the right safety
17
buffers, decisions and policies that would generate brain gain. Labor is among the main
factors of production, and skilled labor would certainly mean greater and speedy
development. Improvements shall be made to accommodate labor force and specific
strategies need to be carefully compiled and followed, to provide a competitive and effecting
working environment both in the public and private sector.
2.6 Determinants of unemployment
The following sections describe the determinants of unemployment along with social
limitations like gender, age and education. Although it is not difficult to find credible reasons
why women decide not to work, over the last decade despite the unemployment rate has
declined the gender unemployment gap has widened. Population distribution and the
demographic changes with the population aging remain a challenge for the years ahead.
Dependency ratio for older people has increased considerably thus exerting social hardship in
the anticipated decades. Education wise the education level used to be much lower for the
private sector rather than for the public sector. Over the last decade the significance of
education is reflected in undertaking various social reforms which are further described
below.
2.6.1 Unemployment and Gender
Besides positive changes that Albania’s economy has experienced, various indicators have
not moved in the same line. The financial crisis involved also Albania, by worsening of some
of the main indices; such as employment. Gender inequality is a very debatable topic in
Albania, because inequality among women and men has always existed in several sectors, in
particular in the work place. For the last decade despite the decline in the unemployment rate,
the gap between unemployed women and men has increased. The decline in the economic
activity for women from year 2006 to year 2007, showed a decline in the employment rate for
all gender groups notably for women. It particular it was noted that gender discrimination
happens in rural areas and is most common among less educated individuals.
Employment rate for women has declined substantially reaching in 2004, 38.3 percent,
whereas for males having reached to 60.1 percent. In the agricultural sector which represents
a great share for total employment, women self-employed comprise 52 percent compared to
men who constitute 45 percent and such phenomenon gives an insight on the informal
employment (Duka et al., 2005). Despite the education and university enrollment is higher for
18
women, this is not reflected at the employment rate. Such contributors can all be linked to old
tradition ties and also lack of decision making power within the household.
In light of the fact that women in Albania are the group most vulnerable to discriminatory
labor practices, it is of great importance to take a series of measures to tackle such problems
in the labor market. There are a number legal and regulatory framework documents which
anticipate the implementation of specific measures for gender empowerment; “The strategy
on gender equality” adopted by the EU Commission, “Convention on the Eliminations of All
Forms of Discriminations against Women”(2010), law no. 9970 “On gender equality in the
society” (2008) and law No. 7961 “On the Code of Labor” (1995).Convention on the
Elimination of All Forms of Discrimination against Women, ratified in Albania on 11 May
1994, which is widely assumed as an international bill for the rights of women. The
Convention provides the basis for realizing equality between women and men through
ensuring women's equal access to, and equal opportunities in, political and public life -including the right to vote and to stand for election -- as well as education, health and
employment. States parties agree to take all appropriate measures, including legislation and
temporary special measures, so that women can enjoy all their human rights and fundamental
freedoms (UN General Assembly, The Convention on the Elimination of All Forms of
Discrimination against Women [CEDAW], 1979).
Law 9970 “On gender equality in the society” regulates fundamental issues of gender
equality in public life, the protection and equal treatment of women and men, equal
opportunities and chances to exercise their rights, as well as their participation and
contribution in the development of all social fields (On gender equality in the society,
2008).Law No. 7961 of July 12, 1995 “On the Code of Labor” where precisely Article 115 it
stipulates quality between sexes in terms of reward (On the Code of Labor, 1995).
120000
110000
100000
90000
Meshkuj
80000
Femra
70000
60000
Figure 13.Unemployment by gender from INSTAT data accessed, 15 November 2014.
19
2.6.2 Unemployment and age
For statistical purposes for the LFS, the Albanian population as per age was divided in three
main categories; 15-19 years, 20-34 years and over 35 years old. By the beginning of the last
decade the group that faced the highest unemployment rates were the young individuals aged
from 15-19 years old. Lack of the proper policies and inability to match the supply with the
demand, brought underutilization of skills and shortage in supply. Hence it is necessary
clearing away the social and economic obstacles to create working places for this age group
and their full skill employment. During the last 10 years, the total unemployment has
declined for all group ages and in particular for age 20-34 years old. The Ministry of Labor
together with Tirana Municipality has cooperated through a World Bank project to improve
the quality of training services by different institutions, both governmental and private.
As a result of the age distribution of the population, demographic changes remain a challenge
for the decades ahead. Dependency ratio for older people in 2013 rose to 17.2 percent from
12 percent and this will exert pressure in the coming decades. Thus, this will put pressure on
the productive population which will have to cover dependents, posing a number of
challenges in education, labor market and social policies.
Figure 14.Unemployment rate according to age groups, 2007- 2010: INSTAT accessed, 15 November 2014.
2.6.3. Unemployment and education
The legal framework for regulation of the education system encompasses two main laws.
Law no. 7952, date 21.6.1995 “Law on the Pre-university Education System” which indicates
education in the Republic of Albania as a national priority, aims spiritual emancipation,
20
material progress and social development of the individual. The higher education system is
regulated by Law no. 8461 dated 25.02.1999.
Secondary education, gymnasium is a very important stage of the Pre-university Education
and involves youth aged from 14 to 18 years. Observing unemployment to the education
level; for population with primary and secondary education overall unemployment in Albania
has decreased. Taking into consideration the unemployment rate for people with high
education level, the rate has steadily decreased in the first 4 years, but then hiked again. This
can be attributed to different facets, such as the high number of students enrolling
universities, which in turn represents the relatively high demand for high positions.
Among other considerations it is worth noting the employed people in the state sector
according to the education level. Roughly this number has decreased from year 2000 to 2011.
The number of people with primary education employed in the state sector has halved. People
with a secondary education have decreased, while with university degrees have increased.
This tells the decrease of number of employed in the state sector can be largely attributed to
the decrease of the ones with primary and secondary education.
Related to education, nevertheless the non-agricultural sector seems to have had a small share
of the labor market for many years, the education level used to be much lower for the private
sector rather than for the public sector. It is important to stress that in order to have a sense of
changes, priority must be put to education programs and a substantial improvement of
education system quality must take place. Unfortunately sustainable economic growth that
market the 8-year period 2000-2008, was not accompanied by rise in employment and human
capital development.
Roughly there has always existed a positive relationship between education and employment.
Over the last decade the importance of education is reflected in undertaking various reforms
in education, salary increase for teachers, curriculums review, administration of exams at the
end of secondary education and recently shutting down of private universities after
inspections found doubtful diploma awards. Individuals with a lower level of education are
more likely to be unemployed than those with secondary education (high school) and
university. The employment rate for people with lower level of education was 53.5 percent,
for those with secondary education (high school) were 57.4 percent and for university
graduates was approximately 67 percent (LFS, 2012).
21
100000
80000
60000
Primary Education
40000
High school
20000
Tertiary Education
0
Figure 15. Employed in the state sector according to education level from INSTAT data accessed, 15 November
2014.
2.7 Strategic priorities for employment and skills development
On June 23, 2013 a new government was appointed in Albania. On June 24th of 2014
European Union (EU) foreign ministers decided to grant the EU Candidate Status to Albania,
followed by the European Commission recommendation. The new elected government in
order to address unemployment issues introduced its “Employment and Skills Strategy” for
year 2014-2020 which is accompanied by an Action Plan (2014).The overall goal of the
Strategy is to promote quality jobs and skills opportunities for all Albanian women and men
throughout the lifecycle. This will be achieved through coherent and concerted policy actions
that simultaneously address labor demand, labor supply and social inclusion gaps. The
Employment and Skills Strategy centers on four strategic priorities, as follows:
a. Foster decent job opportunities through effective labor market policies
b. Offer quality vocational education and training to youth and adults
c. Promote social inclusion and territorial cohesion
d. Strengthen the governance of the labor market and qualification systems(Ministry
of Social Welfare and Youth, Employment and Skills strategy 2014-2020, 2014).
22
CHAPTER 3
AN EXAMINATION OF THE LONG RUN RELATIONSHIP BETWEEN
UNEMPLOYMENT AND GDP
This chapter is organized as follows: the regression model and data specification performed
in the study; descriptive statistics of the variables; Johansen co-integration tests the cointegration of unemployment and real GDP by carrying out a univariate analysis.
3.1 Model and data specification
Consider the following regression equation model performed in this study:
UNEMP= α + β1GDP + ε
(1)
Where α represents the intercept, β1represents the estimated regression coefficient, ε is the error
term. The dependent variable in equation (1) is unemployment (UNEMP) and (GDP)
represents the real GDP growth.
The data consist of yearly unemployment and real GDP data obtained from World Bank
database (http://data.worldbank.org/, accessed: 18Nov 2014 for 1991-2013 time interval) for
Albania. All tests are performed by using E Views7 statistical program.
3.2. Descriptive statistics
The following Figures and Table 1 represents descriptive statistics of the variables.
Graph 3: Real GDP and unemployment series in Albania1991-2013
30
20
10
0
-10
-20
-30
-40
92
94
96
98
00
02
UNEMP
04
06
GDP
23
08
10
12
Graph 4: Unemployment and real GDP series in Albania, 1991-2013, scatter diagram
20
10
GDP
0
-10
-20
-30
12
14
16
18
20
22
24
UNEMP
Figure 16: Histogram and statistics of real GDP series
6
Series: UNEMP
Sample 1991 2013
Observations 23
5
4
3
2
1
0
12
13
14
15
16
17
18
19
20
24
21
22
23
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
16.41739
14.30000
22.70000
12.40000
3.807487
0.537826
1.648393
Jarque-Bera
Probability
2.859540
0.239364
Figure 17: Histogram and statistics of unemployment series
12
Series: GDP
Sample 1991 2013
Observations 23
10
8
6
4
2
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
3.539611
5.700000
13.30000
-29.58900
9.020546
-2.375540
9.151140
Jarque-Bera
Probability
57.89222
0.000000
0
-30
-25
-20
-15
-10
-5
0
5
10
15
Table 1: Descriptive statistics of unemployment and real GDP series
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
UNEMP
16.41739
14.30000
22.70000
12.40000
3.807487
0.537826
1.648393
GDP
3.539611
5.700000
13.30000
-29.58900
9.020546
-2.375540
9.151140
Jarque-Bera
Probability
2.859540
0.239364
57.89222
0.000000
Sum
Sum Sq. Dev.
377.6000
318.9330
81.41104
1790.146
Observations
23
23
Table 2.Estimation equation output of regression (unemployment and real GDP at levels)
Dependent Variable: UNEMP
Method: Least Squares
Date: 03/16/15 Time: 10:18
Sample: 1991 2013
Included observations: 23
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
GDP
16.14190
0.077832
0.860548
0.090528
18.75769
0.859757
0.0000
0.3996
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
0.034002
-0.011998
3.830259
308.0886
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
25
16.41739
3.807487
5.606683
5.705422
Log likelihood
F-statistic
Prob(F-statistic)
-62.47686
0.739181
0.399632
Hannan-Quinn criter.
Durbin-Watson stat
5.631516
0.813572
Estimation Command:
=========================
LS UNEMP C GDP
Estimation Equation:
=========================
UNEMP = C(1) + C(2)*GDP
Substituted Coefficients:
=========================
UNEMP=16.1418954615+0.0778322357279*GDP
Table 3: Stability diagnostic/Recursive estimate (OLS only)/CUSUM Test (unemp and real
GDP)
15
10
5
0
-5
-10
-15
-20
94
96
98
00
02
04
CUSUM
06
08
10
12
5% Significance
Table 4.Estimation equation output of regression (unemployment
at first differences and GDP at level)
Dependent Variable: DUNEMP
Method: Least Squares
Date: 03/16/15 Time: 10:33
Sample (adjusted): 1992 2013
Included observations: 22 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
GDP
0.538703
-0.095058
1.046138
0.141483
0.514944
-0.671871
0.6122
0.5094
R-squared
Adjusted R-squared
S.E. of regression
0.022072
-0.026824
3.586957
Mean dependent var
S.D. dependent var
Akaike info criterion
26
0.059091
3.539796
5.478994
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
257.3253
-58.26893
0.451410
0.509354
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
5.578179
5.502359
3.032903
Estimation Command:
=========================
LS DUNEMP C GDP
Estimation Equation:
=========================
DUNEMP = C(1) + C(2)*GDP
Substituted Coefficients:
=========================
DUNEMP = 0.538702648534 - 0.0950581501224*GDP
Table 5: Stability diagnostic/Recursive estimate (OLS only)/CUSUM Test (dunemp and real
GDP)
15
10
5
0
-5
-10
-15
1994
1996
1998
2000
2002
CUSUM
2004
2006
2008
2010
2012
5% Significance
3.3 Johansen Co-Integration test
Time series data display a variety of behavior. The main reason why it is important to know
whether a time series is stationary or non-stationary before one embarks on a regression
analysis is that there is a danger of obtaining apparently significant regression results from
unrelated data when non-stationary series are used in regression analysis. Such regressions
are said to be spurious (Hill et al., 2008). Before analyzing the co-integrating relationship
between unemployment and real GDP, it is important to carry out a univariate analysis. The
economic series like those of unemployment and real GDP tend to possess unit roots. The
27
presence of unit roots in the underlying series points towards the non-stationary of the
underlying series. If both the independent and the dependent variables show the presence of
unit roots, the regression results do not hold much meaning. This is referred to as spurious
regression, whereby the results obtained suggest that there are statistically significant
relationships between the variables in the regression model, when in fact all that is obtained is
the evidence of contemporaneous correlation rather than a meaningful causal relation. The
problem of spurious regression is compounded by the fact that the conventional t- and Fstatistics do not have standard distributions generated by stationary series; with nonstationary, there is a tendency to reject the null in both cases and this tendency increases with
sample size (Gül & Acıkalın, 2008).The stationary of each series was investigated by
employing the unit root tests developed by Dickey and Fuller. The test consists of regressing
each series on its lagged value and lagged difference terms. The number of lagged differences
to be included can be determined by the Akaike information criterion (Hill et al., 2008).
Table 6 reports the Augmented Dickey–Fuller test statistics under the null hypothesis of a
unit root. This table also presents the number of lagged difference terms included in the
regression. The hypothesis of unit root against the stationary alternative is not rejected at 5
percent levels for unemployment variable with or without deterministic trend. ADF test of
unemployment variable gives unit root at level. Therefore, first differences of that variable
are taken and it is shown that unemployment data are stationary now. Hence, it has been
concluded that these variable are integrated of order 1.
Table 6: ADF Unit Root Test of Unemployment (Level
and First Differences)
Null Hypothesis: UNEMP has a unit root
Exogenous: Constant
Lag Length: 1 (Automatic - based on SIC, maxlag=4)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t
t-Statistic
Prob.*
-1.233516
-3.788030
-3.012363
-2.646119
0.6396
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(UNEMP)
Method: Least Squares
Date: 03/16/15 Time: 10:28
Sample (adjusted): 1993 2013
Included observations: 21 after adjustments
28
Variable
Coefficient
Std. Error
t-Statistic
Prob.
UNEMP(-1)
D(UNEMP(-1))
C
-0.237974
-0.384204
3.818920
0.192923
0.210833
3.260712
-1.233516
-1.822312
1.171192
0.2332
0.0851
0.2568
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.325363
0.250404
3.041772
166.5428
-51.54037
4.340515
0.028949
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-0.128571
3.513281
5.194321
5.343539
5.226705
1.930231
Null Hypothesis: UNEMP has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 1 (Automatic - based on SIC, maxlag=4)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-2.438451
-4.467895
-3.644963
-3.261452
0.3514
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(UNEMP)
Method: Least Squares
Date: 03/16/15 Time: 10:29
Sample (adjusted): 1993 2013
Included observations: 21 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
UNEMP(-1)
D(UNEMP(-1))
C
@TREND(1991)
-0.723298
-0.199784
16.00483
-0.346154
0.296622
0.214276
6.675617
0.169315
-2.438451
-0.932364
2.397505
-2.044436
0.0260
0.3642
0.0283
0.0567
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.458500
0.362941
2.804160
133.6763
-49.23215
4.798086
0.013391
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
Null Hypothesis: D(UNEMP) has a unit root
29
-0.128571
3.513281
5.069728
5.268685
5.112907
1.704617
Exogenous: Constant
Lag Length: 0 (Automatic - based on SIC, maxlag=4)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-7.893472
-3.788030
-3.012363
-2.646119
0.0000
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(UNEMP,2)
Method: Least Squares
Date: 03/16/15 Time: 10:29
Sample (adjusted): 1993 2013
Included observations: 21 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(UNEMP(-1))
C
-1.502448
-0.119001
0.190341
0.672828
-7.893472
-0.176867
0.0000
0.8615
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.766317
0.754018
3.083238
180.6208
-52.39242
62.30690
0.000000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-0.147619
6.216641
5.180231
5.279709
5.201820
2.026217
Null Hypothesis: D(UNEMP) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic - based on SIC, maxlag=4)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-7.664840
-4.467895
-3.644963
-3.261452
0.0000
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(UNEMP,2)
Method: Least Squares
Date: 03/16/15 Time: 10:29
Sample (adjusted): 1993 2013
Included observations: 21 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(UNEMP(-1))
C
@TREND(1991)
-1.505027
0.069871
-0.015735
0.196355
1.539566
0.114623
-7.664840
0.045384
-0.137279
0.0000
0.9643
0.8923
30
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.766562
0.740624
3.166069
180.4319
-52.38144
29.55412
0.000002
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-0.147619
6.216641
5.274422
5.423640
5.306806
2.021435
Table 7 reports the Augmented Dickey–Fuller test statistics under the null hypothesis of a
unit root for GDP variable. The hypothesis of unit root against the stationary alternative is
rejected at 5 percent levels for real GDP variable with or without deterministic trend. ADF
test of unemployment variable does not give unit root at level and it is shown that gdp data
are stationary.
Table 7: ADF Unit Root Test of GDP (Level)
Null Hypothesis: GDP has a unit root
Exogenous: Constant
Lag Length: 0 (Automatic - based on SIC, maxlag=4)
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-6.362000
-3.769597
-3.004861
-2.642242
0.0000
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(GDP)
Method: Least Squares
Date: 03/16/15 Time: 10:50
Sample (adjusted): 1992 2013
Included observations: 22 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
GDP(-1)
C
-0.809539
4.351910
0.127246
1.236264
-6.362000
3.520212
0.0000
0.0022
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.669285
0.652749
5.375901
578.0062
-67.17061
40.47505
0.000003
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
Null Hypothesis: GDP has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 3 (Automatic - based on SIC, maxlag=4)
31
1.404048
9.122833
6.288237
6.387423
6.311603
2.411171
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
t-Statistic
Prob.*
-5.280108
-4.532598
-3.673616
-3.277364
0.0024
*MacKinnon (1996) one-sided p-values.
Warning: Probabilities and critical values calculated for 20 observations
and may not be accurate for a sample size of 19
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(GDP)
Method: Least Squares
Date: 03/16/15 Time: 10:51
Sample (adjusted): 1995 2013
Included observations: 19 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
GDP(-1)
D(GDP(-1))
D(GDP(-2))
D(GDP(-3))
C
@TREND(1991)
-2.510223
1.037704
0.439286
0.221146
19.25472
-0.431895
0.475411
0.340840
0.192117
0.110802
4.497289
0.200533
-5.280108
3.044548
2.286562
1.995870
4.281405
-2.153735
0.0001
0.0094
0.0396
0.0673
0.0009
0.0506
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.784892
0.702158
4.074564
215.8270
-50.04519
9.486936
0.000547
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-0.368418
7.466001
5.899494
6.197738
5.949969
2.182808
On the basis of the above-mentioned unit root tests, performed the Johansen’s co-integration
test to see whether any combinations of the variables are co-integrated. This approach uses a
maximum likelihood procedure that tests for the number of co-integration relationships and
estimates the parameters of those co-integrating relationships (Hill et al., 2008).
LR test statistics and critical values are shown in Table 8.The results suggest that there is a
co-integrating relationship between unemployment rate and GDP at the 5% significance
level. In other words, a long-run stable relationship between unemployment rate and GDP
exists. This indicates that unemployment and GDP have moved together in the long run in
Albania.
32
Table 8:Johansen Co-integration Test Results
Date: 03/16/15 Time: 10:24
Sample (adjusted): 1993 2013
Included observations: 21 after adjustments
Trend assumption: Linear deterministic trend
Series: UNEMP GDP
Lags interval (in first differences): 1 to 1
Unrestricted Cointegration Rank Test (Trace)
Hypothesized
No. of CE(s)
Eigenvalue
Trace
Statistic
0.05
Critical Value
Prob.**
None *
At most 1
0.717435
0.114540
29.09541
2.554617
15.49471
3.841466
0.0003
0.1100
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized
No. of CE(s)
Eigenvalue
Max-Eigen
Statistic
0.05
Critical Value
Prob.**
None *
At most 1
0.717435
0.114540
26.54080
2.554617
14.26460
3.841466
0.0004
0.1100
Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Cointegrating Coefficients (normalized by b'*S11*b=I):
UNEMP
-0.032544
0.297177
GDP
0.198968
-0.021277
Unrestricted Adjustment Coefficients (alpha):
D(UNEMP)
D(GDP)
-1.213045
-6.286046
1 Cointegrating Equation(s):
-0.796459
0.686264
Log likelihood
-109.6194
Normalized cointegrating coefficients (standard error in parentheses)
UNEMP
GDP
1.000000
-6.113892
(0.91423)
Adjustment coefficients (standard error in parentheses)
D(UNEMP)
0.039477
(0.01952)
D(GDP)
0.204571
(0.03501)
33
3.4 Granger causality test result
Table 9 presents the results of Granger causality test. The results of the co-integration test
have been confirmed by Granger causality test results. Because of P value is 0.0522, “GDP
does not Granger Cause UNEMP” is rejected. Therefore, there is a one-way causality from
GDP to unemployment in the long-term in Albania.
Table 9. Pair wise Granger Causality Test Results
Date: 03/16/15 Time: 10:57
Sample: 1991 2013
Lags: 2
Null Hypothesis:
GDP does not Granger Cause UNEMP
UNEMP does not Granger Cause GDP
Obs
F-Statistic
Prob.
21
3.57035
0.78046
0.0522
0.4749
34
CONCLUSION
Labor market reallocation is a characteristic of transition economies like Albania. In Albania
the labor force participation and employment has been lower for women than men.
The employment rate in general has followed a downward trend; nonetheless working women
continue to lag behind men. An ominous trait of the Albanian labor market is the fact that a
remarkable portion of the youth are not doing a job search consistently due to discouragement
of the current economic and political situation taking place. The country lacks employment
opportunities, making even harder the possibility of finding a job. In order to promote
employment as well development, Albania needs many specialized programs and
professional structures, to permeate the demand and supply of labor. Albania lacks
institutional support to uphold and encourage unemployed people. This paper analyzed
empirically the co-integrating relationship between unemployment and GDP in the Albanian
economy. Since one of the variables are non-stationary and present a unit root, Johansen’s cointegration technique has been applied. This methodology has allowed for obtaining of a cointegrating relationship among these variables. The co-integration results provide evidence of
a unique co-integrating vector. This indicates that unemployment and GDP have moved
together in the inverse direction Albania.
35
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APPENDIX
Data for Johansen test, real GDP and unemployment from World Bank database
years
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
unemp
GDP
14.30000019
18.29999924
22.70000076
22.29999924
21.79999924
19.5
21
19.29999924
19.70000076
13.5
22.70000076
13.19999981
12.69999981
12.60000038
12.5
12.39999962
13.5
13
13.80000019
14.19999981
14.30000019
14.69999981
15.6
-29.58899767
-7.2
9.6
8.3
13.3
9.1
-10.2
12.7
10.1
7.3
7
2.9
5.7
5.9
5.5
5
5.9
7.7
3.3
3.5
3
1.299987206
1.300052716
39