DETERMINANTS OF THE ALBANIAN LABOR FORCE PARTICIPATION
RATE THROUGHOUT THE TRANSITION PERIOD
ARMELA HASMUÇA
THESIS PRESENTED TO EPOKA UNIVERSITY
IN FULFILLMENT OF THE REQUIREMENTS FOR THE MASTER DEGREE
EPOKA UNIVERSITY
JUNE 2016
APPROVAL PAGE
Student Name and Surname: Armela Hasmuca
Faculty
: Faculty of Economics and Administrative Sciences
Department
:
Thesis Title
: Determinants of the Albanian Labor Force Participation
Rate Throughout the Transition Period
Date of Defense
: 20 June 2016
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 in Banking and Finance.
Assoc. Prof. Dr. Eglantina Hysa
Supervisor
I certify that this thesis satisfies all the legal requirements as a thesis for the degree of
Master of Science in Banking and Finance.
Assoc. Prof. Dr. Ugur ERGUN
Head of Department
EXAM BOARD OF THESIS
Thesis Title
: Determinants of the Albanian Labor Force Participation Rate
Throughout the Transition Period
Author
: Armela Hasmuca
Qualification
: Master of Science
Date
: 20 June 2016
Members
Prof. Dr. Gungor Turan
……………………….
Assoc. Prof. Dr. Eglantina Hysa
……………………….
Assoc. Prof. Dr. Ugur Ergun
……………………….
i
DETERMINANTS OF THE ALBANIAN LABOR FORCE
PARTICIPATION RATE THROUGHOUT THE TRANSITION
PERIOD
ABSTRACT
Albania’s labor market has restructured significantly during the 26 year period
between 1989 and 2015. After the fall of the communist regime, Albania had a
considerably low rate of labor force participation, especially among females. A
descriptive comparative analysis of secondary demographic and socio-economic data
revealed two main dynamics for the female labor force participation rate throughout the
transition to a market economy. First, this rate increased during economic crises and
decreased immediately after the recessions ended, known as the “added-worker” effect.
Second, the analysis confirmed the “U-shaped curve” theory for the female labor force.
A further regression analysis demonstrated that child care, education, civil status, and
life expectancy were determinants of these determinants for the Albanian female
population. In contrast, the age effect was one of the main drivers of male labor force
participation. Its determinants were age, employment in the manufacturing sector, and
wage in the industry level. The modern microeconomic theory of fertility was partially
confirmed in the Albanian labor market. The study provided evidence for the
intertemporal substitution hypothesis as well. Finally, this study concludes that the
Albanian labor market has experienced dynamic adjustments to the market economy
similar to those in the South East European countries. There is also evidence of support
for classical theories. The labor market reveals evidence of the process of adjustment to
market-driven allocation. The determinants of the male, female, and total labor force
participation rates show a similar pattern and tendency of convergence. The final part of
this paper provides several implications for policy.
ii
Keywords: ILO; WB; LPRF; labor force participation rate; employment rate;
iii
ABSTRAKTI
Tregu i punës në Shqipëri është ristrukturuar në mënyrë të konsiderueshme gjatë
periudhës 26 vjeçare në mes të 1989 dhe 2015. Pas rënies së regjimit komunist,
Shqipëria kishte një normë të konsiderueshme të ulët të pjesëmarrjes së fuqisë punëtore,
veçanërisht tek femrat. Ndermjet nje analize përshkruese dhe krahasuese të të dhënave
dytësore demografike dhe socio-ekonomike zbulohen dy dinamikat kryesore për
shkallën pjesëmarrjes se femrave në fuqinë punëtore gjatë periudhes se tranzicionit drejt
ekonomisë së tregut te lire. Së pari, kjo normë është rritur gjatë krizës ekonomike dhe ka
rënë menjëherë pas recesioni përfundoi, i njohur si efekti "added-worker". Së dyti, kjo
analize konfirmon "U-shaped curve" teorine për forcën femërore te punës. Një analizë e
mëtejshme e regresionit tregon se kujdesi për fëmijët, arsimi, gjendja civile, dhe
jetëgjatësia ishin përcaktuesit e treguesve për popullsinë femërore shqiptare. Ndersa per
meshkujt, efekti i moshes ishte një nga faktoret drejtues kryesorë të pjesëmarrjes së
meshkujve në fuqinë punëtore. Përcaktuesit e saj ishin mosha, punësimi në sektorin e
ndertimit dhe pagave në nivel të industrisë. Teoria moderne mikroekonomike e fertilitetit
është konfirmuar pjesërisht në tregun shqiptar të punës. Studimi ofron gjithashtu dëshmi
për hipotezën e zëvendësimit intertemporal. Së fundi, ky studim konstaton se tregu
shqiptar i punës ka përjetuar ndryshime dinamike në ekonominë e tregut të ngjashme me
ato te vendeve te Evropës Juglindore. Ka edhe dëshmi te cilat mbështesin teorite klasike.
Behen te ditura provat të procesit të përshtatjes se tregut te punës ne shpërndarjen në
tregun e lire. Përcaktuesit e mashkull, femër, dhe normat e përgjithshme të pjesëmarrjes
në forcat e punës tregojnë një model të ngjashëm dhe tendenca e konvergjencës. Pjesa e
fundit e e ketij punimi ofron disa masa dhe rregulla per tu ndermarre.
Fjale Kycët: ILO; BB; LPRF; Shkalla e pjesëmarrjes së fuqis
iv
DECLARATION
I hereby declare that this Master’s Thesis titled “Determinants of the Albanian Labor
Force Participation Rate Throughout the Transition Period” is based on my original
work except quotations and citations which have been duly acknowledged.
I also
declare that this thesis has not been previously or concurrently submitted for the award
of any degree, at Epoka University, any other University or Institution.
Armela Hasmuça
June 20, 2016
v
Table Of Contents
ABSTRACT ..................................................................................................................... .I
ABSTRAKTI…………………………………………………………………………. ..II
TABLE OF CONTENTS…………………………………………………………. ..... III
TABLE OF TABLES………………………………………........................................ IV
TABLE OF FIGURES…………………………………………………...……………VI
DEFINITIONS…………………………………………………………………...…...VII
CHAPTER I: INTRODUCTION ……………………………………………… .......... 1
Background ................................................................................................................... .1
Research Question And Importance .............................................................................. .2
CHAPTER II: LITERATURE REVIEW………………………………………...….. . 4
Introduction ................................................................................................................... .4
Labor Supply In Albania ................................................................................................ 4
Labor Supply During The Communist Regime ......................................................... 4
Labor Supply During The Transition Period ............................................................. 8
Labor Supply Today ................................................................................................. 13
Assumption................................................................................................................... 20
CHAPTER III: METHODOLOGY ……………………………………………. ....... 21
Data .............................................................................................................................. 21
Research Strategy ......................................................................................................... 21
Limitations And Problems ........................................................................................... 24
CHAPTER IV: DATA ANALYSIS………………………………………………… .. 25
Labor Force Participation Rate At Present ................................................................... 25
Gender Differences Between 1990 And 2008.............................................................. 27
Change In The Female LFPR Over 20 Years .............................................................. 29
vi
Regression Analysis For LFPR .................................................................................... 31
Total Labor Force Participation Rate ....................................................................... 31
Male Labor Force Participation Rate ....................................................................... 33
Female Labor Force Participation Rate .................................................................... 34
Final Remarks………….…………. ……………………...…………………...…………….35
CHAPTER V: CONCLUSIONS AND RECOMMENDATIONS……………….... . 37
REFERENCES ………………………………………………………………...... ........ 39
Appendix A: Regression Analysis………………………………………….. ............. 43
Appendix B: Demographical Data…………………………………………….…......46
Appendix C: Remittances…………………………………………………................. 51
Appendix D: Regional Data……………………………………………………..... .... 52
vii
LIST OF TABLES
Table 1: Employment in transition economies (1990=100). ........................................... 14
Table 2: Reasons for nonparticipation in the labor market. ............................................. 16
Tables 3a, 3b, 3c: Summary of predictors’ coefficients, SE coefficients, T-value, and Pvalue and analysis of variance for the total Labor Force Participation Rate.................... 43
Tables 4a, 4b, 4c: Summary of predictors’ coefficients, SE coefficients, T-value, and Pvalue and analysis of variance for the male Labor Force Participation Rate. .................. 44
Tables 5a, 5b, 5c: Summary of predictors’ coefficients, SE coefficients, T-value, and Pvalue and analysis of variance for the female Labor Force Participation Rate. ............... 45
Table 6: Life expectancy for males and females over the period 1950-2015. ................. 46
Table 7: Number of male and female students enrolled in the total, public, and private
higher education from 1994 until 2013. ........................................................................... 46
Table 8: The average wage in total and for each of the main industries over the period
1997-2014......................................................................................................................... 48
Table 9: Minimal age and required years of social insurance paid for each of the
categories for the male population. .................................................................................. 49
Table 10: Minimal age and required years of social insurance paid for each of the
categories for the female population. ............................................................................... 50
Table 11: Urban and rural population and the number of people employed in the
agricultural sector for years 1995-2010. .......................................................................... 50
Table 12: Correlation of the level of remittances with the other variables included in the
regression equation for the total LFPR. ........................................................................... 51
Table 13: Employment in transition economies (1990=100), ranked by data of 1994. .. 52
Table 14: Employment in transition economies (1990=100), ranked by data of 2000. .. 52
Table 15: Male Labor Force Participation Rate for 2008, 2012, and 2014 for East
European and Central Asian countries. ............................................................................ 53
viii
Table 16: Female Labor Force Participation Rate for 2008, 2012, and 2014 for East
European and Central Asian countries. ............................................................................ 53
ix
TABLE OF FIGURES
Figure 1: Labor Force Participation Rate in Albania in the years 1989-2015. ............... 12
Figure 2: Male Labor Force Participation Rate for 2014 for East European and Central
Asian countries. ................................................................................................................ 15
Figure 3: Female Labor Force Participation Rate for 2014 for East European and
Central Asian countries. ................................................................................................... 15
Figure 4: Labor Force Participation Rate in 2008 based on gender differences. ............ 25
Figure 5: Male participation rate 1990 and 2008. ........................................................... 27
Figure 6: Female participation rate 1990 and 2008. ....................................................... 29
Figure 7: Relationship between female LFPR and economic development (GDP)........ 30
Figure 8: Labor Force Participation Rate of females from 1989 until 2009. .................. 30
Figure 9: Number of births in the country over the period 1994-2015. .......................... 47
Figure 10: Average age of marriage for males & females over the period 1990-2015. . 47
Figure 11: Remittances in Albania in current US$ (billions) from 1992 till 2009. ........ 51
x
ACRONYMS AND ABBREVIATIONS
EU
European Union
IBRD
International Bank for Development and Reconstruction
ILO
International Labor Organization
INSTAT
Institute of Statistics (Republic of Albania Institute of Statistics)
ISSH
Institute of Social Insurance in Albania
LFPR
Labor Force Participation Rate
UN
United Nations
WB
World Bank
xi
DEFINITIONS
Labor market
The processes of labor allocation in an economy, that is, the
methods by which employers fill vacancies and workers find jobs,
as well as the internal allocation of labor within businesses,
households, and other economic organizations.
Labor force
The proportion of the population in each age group who are
economically active as employers, self-employed, employees, and
unemployed. This is an indicator of the proportion of the
population who are eligible and available for work.
The working age
population
The population aged 15-64 years
Employed
All the persons who have worked even for one hour with a
respective salary or wage during the reference week. As employed
are considered also all persons who were receiving a salary or
wage while they were in training during their work.
Unemployment
The inability of workers who are ready, able, and willing to work
to find employment. Unemployment is usually expressed as a
percentage of the labor force.
Labor force
participation rate
The ratio between the active population (employed and
unemployed) and the working age population.
Employment rate
The proportion of employed 15-64 years old and working age
population.
1
CHAPTER I: INTRODUCTION
Background
Communism in Albania ended twenty six years ago. One of the most affected
areas was the country’s economy. The whole structure of the economic system changed.
This included both the macroeconomic and microeconomic levels. On the
macroeconomic level, the government ceased to be the planner of every economic
aspect, and on the microeconomic level, individuals were free to search for different
ways and areas of employment. Albania moved to the market allocation of labor. The
labor market was greatly affected by these events and changes in this market also drove
the transition of the economy. The following decades continued to shape this market.
Today, it is one characterized by a relatively young average age population. One can
recognize several trends emerging due to changes in demographics. They include
increase in tertiary education, decrease in fertility rates, longer life expectancy, changes
in marriage and divorce rates, and so on. Some other factors are the level of GDP,
average wage, and employment in specific sectors. This study attempts to identify the
determinants of labor force participation rate in Albania and the major trends that have
emerged throughout the transition to the market economy.
The allocation of labor had a different form during the communist regime in
Albania from its present structure. During the previous regime, central planning was
implemented by the government in the entire economic system. This implies that the
government planned every part of the Albanian economy, including the labor market.
Excessively high labor participation rates characterized this system. After the collapse of
communism, central planning was ended, and the government started to implement the
free market concepts and principles. The labor market started to function through the
guidance of the “invisible hand,” as Adam Smith called it. A visible evidence of this
change was the vast emigration toward the developed countries. Furthermore, a high
number of females exited the labor market at the beginning of the transition period and
2
started reentering only in the recent years. The decline in the social security from the
government was another consequence of the change in the political system. This has
resulted in a significant decrease in the number of births, which has also diminished the
labor force participation rate of the male population. Finally, the two decades that have
passed since communism collapsed have caused several changes in the country’s labor
market and have shaped it into the market-like arrangements found today.
Research Question and Importance
This study attempts to identify the determinants of the labor participation rate in
Albania throughout the transition period with a focal point on female and male rates. The
transition period has shaped the labor market of several post-communist countries,
including Albania. Thus, labor market dynamics have emerged which represent an
opportunity for interesting field research. Similar studies have been conducted in other
transition economies; however, there are no studies at the moment that have been
conducted on the Albanian labor market and its change throughout the transition period.
Lastly, this study concludes that several dynamics of this market resemble those of the
classical theoretical background, while others represent unique tendencies. Furthermore,
there are different factors that determine the male, female, and total labor force
participation in Albania. The final question is: Do these trends fit within the theoretical
background, and what are the determinants of the Albanian male, female, and total labor
force participation rate in the new market economy environment?
The analysis of the labor force participation rate in Albania is important for
several constituencies. First, it is important for the policy makers to know what the
major dynamics in the labor market are and what determines the participation in the
market. Identifying the factors is necessary when the government aims at increasing the
labor force participation rate in the country, especially as a way to increase well-being,
3
reduce expenditures for retirement, or lessen the dependency burden. This is even more
important when making a gender distinction in the labor market. More specifically, the
government can improve the educational system accordingly by targeting resources on
key segments of the labor force.
In addition, both domestic and foreign investors would find the study relevant.
This refers to both current and prospective investors. They have the opportunity to
analyze the labor market trends and to apply the findings to their future plans for
investment. The study is useful for the international organizations and institutions such
as International Monetary Fund and World Bank. The findings are helpful in planning
and organizing different programs that these organizations implement in Albania. The
study represents substantial help in several programs in poverty eradication, educational
improvements, or other labor-related areas. It might also assist the European Union
organizations in the process of Albanian integration into the EU. The supply of this
market is a great part of the integration process and policies.
Finally, the labor market in Albania is of great importance in the country’s
economy. It affects the lives of every Albanian in the country and the development of
the economy as a whole. The identification of the determinants of the labor force
participation rate and the major trends that have emerged throughout the transition
period are of significant importance. Thus, the study is beneficial to several groups of
people, both within the country and outside it.
4
CHAPTER II: LITERATURE REVIEW
Introduction
Several factors influence the supply and demand in the labor market. Among
them demographics plays a major role. For example, the increasing role of women in the
labor market since the beginning of the transition period shapes the labor supply.
Another one is migration and its significant impact on labor supply. Other trends
emerged during the past decades, which have shaped the format of the labor market.
Above all, each of the components is highly impacted by the policies that the country
adopts and the market forces in a market economy. Thus, there are many factors that
need to be taken into consideration when analyzing the labor market in general, and
labor supply in specific.
Labor Supply in Albania
The labor markets had a distinctive form under the Stalinist model, which
Albania adopted in 1961 (Lavigne, 1999). This greatly influenced the labor supply in the
country. Furthermore, the transition period had its catastrophic events, such as the
emergence and collapse of the pyramid schemes and the move to privatization. Finally,
all of the trends that emerged throughout these periods formed the labor supply in
Albania to what it is today.
Labor Supply during the Communist Regime
The command economy took held in Albania at the end of World War II. Before
the communist regime came to power, Albania was an agricultural country which had
started industrialization primarily with Italian capital. Once World War II ended, the
communist party took over the country’s leadership and forbade any foreign capital,
which could have accelerated growth in a country that was rather promising
5
economically. At the same time, it stopped any entrepreneurial activity as well (Kaser,
2004). The government monopolized all of the resources in the country. It focused
chiefly on mining and industry by giving it a 51.7% share compared to 9.8% in 1938
(Kaser, 2004). This made an inefficient use of resources as Albania had little potential
for heavy industry. Thus, the living standards remained low.
The basis of any communist economy was communal ownership. Private
property was considered a threat to a person due to its ability to exploit. Therefore, the
means of production were taken under the control of the state which dictated the actions
to be taken with each of them, i.e. full employment (O’Neil, 2005). One of these factors
of production was labor, which was subject to central direction. Through central
planning, unemployment was officially eliminated. This implied that the labor supply
during the communist regime was the same as the labor force (Rutkowski, 2006). In
other words, the Albanian population that actually participated in the labor market was
roughly the same as the working age population. Unemployment was illegal.
Several problems emerged during the communist system, especially related to the
labor supply. As unemployment was nonexistent, overstaffing was the option through
which full employment was made possible (Rutkowski, 2006). This meant that firms
were employing more than they actually needed. They had every incentive to hoard
workers; firms were overmanned by a factor of three to ten times what a market
economy would predict. The results were low labor productivity and low wages
(Rutkowski, 2006).
The Education System: Human Capital Mismatch.
The inefficient use of the factors of production spread over labor as well. On the
one hand, the government invested greatly in the education of the population. Once the
communists came into power, they had as an objective to completely abolish illiteracy.
At first the education resembled the Soviet system based on Marxist-Leninist ideology
6
(US Library Congress, n.d.). As the relations between Soviet Union and Albania started
to erode, the educational system was changed as well.
Despite the changes, the government reached its goal of abolition of illiteracy by
late 1980s. The achievements in education were immense. Enrollment in education
increased from fewer than 60,000 in 1939 to more than 750,000 in 1987. Furthermore,
almost half of the students (47%) were females. The percentage of those who continued
to secondary education increased to 73%, and in all the villages this number was higher
than 55% (US Library Congress, n.d.). These statistics show that education developed
during the communist period, at least in terms of literacy. In addition, the difference
between male and female education was minuscule. As a result, women had a high
potential to participate in the labor market. Another point to notice is the even
distribution of education between rural and urban areas.
However, the preparation of this labor force is debatable. The fact that there was
no illiteracy in the country does not necessarily make the labor force highly-skilled or
competitive. The Albanian government used the Soviet model in education, too. This
included not only the structure, but also the textbooks, the staff, and all the other aspects
(US Library Congress, n.d.). Once the relations with this block were broken, Albania –
almost completely isolated from the rest of the world – had little choice in the
educational process and model. Researchers argue that Albania ceased to produce
reliable statistics in the 1980s (Kaser, 2004), and, thus, only estimates can be made to
support the argument.
Many researchers, though, doubt the quality of the education that the communist
regime provided. The impact on human capital – and thus, productivity – is seen as
essential. This applies not only to the case of Albania, which interrupted the Stalinist
model, but also to the countries that continued it. According to Boeri (2001), “if the
quantity of education – that is, the coverage – was far less satisfactory than had been
thought at the outset, the quality of education was even worse” (p.18). He continues his
argument by saying that communists, contrary to common perception, were not good
7
human capitalists. The highly-specialized skills that the labor acquired during the
communist period did not help in the process of accommodation to the changes in the
structure of the economy (Boeri, 2001). Hence, the non-transferability of skills, rather
than the coercive power, reduced the level of mobility in the labor force. The central
planning system, thus, misallocated labor in two ways: overstaffing and human capital
weakness.
The Inefficient Labor Supply.
On the other side, the communist regime provided little incentive for its labor
force. Once the relations with the Soviet Union were interrupted in 1961, Albania relied
on the support from the People’s Republic of China. One of the policies that Albania
adopted from the Chinese regime was the attempt to minimize the wage differentials
between manual and non-manual workers. The results of this wage compression were
little difference among all the workers; rewards and privileges were solely for those in
the Party functionaries (Kaser, 2004). The regime argued that differences in
accomplishment were to be rewarded, but the ideology constrained policies into leveling,
or the elimination of incentives for differences (Gregory & Stuart, 2004). This provided
perverse incentives to develop one’s skills or to improve the quality of the performance.
Instead, workers focused on meeting the daily norms in terms of quantity.
Despite inefficiency, the central planning shaped the labor supply in Albania in
two other aspects as well: low productivity and low mobility. As mentioned before, the
resources in the country were allocated in those areas where Albania did not have any
comparative advantage. Due to its persistent isolation, the leadership in the country
feared any attack, and thus, it focused on heavy industry and defense (Austin, 2010).
This misallocation affected the efficiency of labor (Mytkolli & Qirici, 1995). At the
same time, shortage of food caused the labor force to be less productive. The
government controlled every aspect of the economy, including labor allocation. Workers
8
were assigned which occupational or geographical area they were to work in. Boeri
(2001) argues, however, that this was to a lower level than what is usually thought.
Instead, the narrowly-based skills that the laborers acquired constrained their mobility to
specific geographical and occupational areas.
Labor Supply during the Transition Period
Wrong Skills in the Wrong Sector
The fall of the communist regime in Albania was followed by social unrest and a
chaotic situation, both politically and economically. The changes that took place after
the collapse of the regime affected the labor market to a great extent, and the labor
market itself affected the options in the transition, too. The GDP decreased drastically
and a great number of the state-owned companies ceased functioning, while many others
were closed (Mytkolli & Qirici, 1995). Therefore, the most dramatic effect of the
collapse of the planning economy was the immediate increase in unemployment.
According to the Transition Report 2001 from EBRD (2001) employment in the
private sector in Albania increased from 3.8% of the total employment in 1992 to 78.6%
in 1996, only 4 years later. It continued increasing to 82.2% in 2000 (as cited in Gregory
& Stuart, 2004). Aghion and Blanchard (1994) explained the changes that happened in
the labor market by what is known as the models of Optimal Speed of Transition [OST].
These models explain that at first there was a rapid period of adjustment in the economy,
during which job creation was slow. Old industries shed workers, but new firms were
scarce and did not create new jobs. In addition, this period was highly influenced by how
high the level of unemployment was. If the level of unemployment was low, higher
unemployment enhanced the process of job creation. Otherwise, the higher level of
unemployment would hinder or even destroy this process (Aghion & Blanchard, 1994).
The optimal solution proposed by them consisted of the closing of the state owned sector
and the facilitation of the newly privatized sectors (as cited in Walsh, 2000) which
9
would affect the labor demand. Thus, one possible result was reallocation of the labor
force from the public to the private sector.
Another possible result was the fall in the labor force participation rate from its
artificially high levels during the command economy. Åslund (2002) argues that
unemployment increased after the collapse of the communist regime. Still, this increase
was not at the same level as western countries expected. “The end of chronic
overstaffing” (Åslund, 2002, p.328) resulted in lower labor force participation rate, but it
did not bring a higher increase in unemployment than by an average of half a percent
among the East European countries. Many workers simply exited the labor force
entirely.
While the common belief is that education was among best in the communist
countries (O’Neil, 2005), it was not distributed among the labor force, at least not
evenly. Commander (2007) supports Boeri (2001) that the legacy of the communist
period into the transition one has been a labor force with asset-specific skills and a
corresponding lack of labor-market flexibility. This is seen as the basis of the persistence
in unemployment and the immediate increase in non-participation (Commander, 2007).
Nonetheless, Åslund (2002) emphasizes that this was partly due to the process of market
adaptation. In the transition period the labor force had the choice to withdraw from the
market. This applied especially to “women with small children and old-age pensioners”
(Åslund, 2002, p.330). Many simply exited the labor force.
In the Albanian market, the legacy of the communist period on the labor supply
became more visible. The newly-privatized industries required skills that were in short
supply (Pema, 2004). The allocation of the resources in the economy started to shift
from the heavy industry to the service sector and agriculture. In 1990 the industry sector
accounted for 40% of the GDP while this share fell to 19% in 1998. These changes were
respectively from 25% to 30% for the agricultural sector and from 33% to 50% for the
service sector (European Training Foundation [ETF], 2006). New skills were required
for a market-oriented, service-based economy.
10
Migration, Informality, and Illegal Activities.
A key adjustment mechanism in the labor market was out-migration. The low
demand for labor gave rise to high levels of migration. Although labor supply had been
quite fixed throughout the communist period, afterwards the labor force showed high
mobility both within the country and outside. Some estimates from the EU show that
around 600,000 people – about one third of the labor force – left the country (Austin,
2010). Some others argue that as many as 1,000,000 did so (ETF, 2006). The numbers
are debatable as migration was mainly illegal, but the picture is quite clear. In a country
with a present population of less than 3.5 million, that represents a high percentage of
the population. There were several reasons why the Albanian workers migrated to other
countries. One of them was the large gap in wage levels between Albania and other
neighboring EU countries. In addition, they did not see any possibility of near
improvement in the economy in general, and specifically the labor market (Mytkolli &
Qirici, 1995). The main problem with the high level of emigration was the brain drain.
The population that migrated was considerably young, mostly skilled, and highly
flexible (Pema, 2004). This implied that the labor supply in the country was quite
inadequate for the new firms that started to operate and invest in Albania.
Another characteristic of the Albanian labor supply during the transition period
was the enlargement of the informal sector. This was especially true in the credit sector
as the banks were not able to keep up with the demand for credit (Austin, 2010). Some
estimates of the informal economy are as high as 50-60% (as cited in Olters, n.d.). Thus,
a large number of the population was employed in the informal sector, which might be
an explanation for the low level of “official” labor force participation rate.
11
Female Unemployment and Population Growth
Unlike the other post-communist countries, Albania experienced an increase in
the female unemployment throughout the transition period. During the communist
regimes, female LFPRs were significantly high – close to 80% of the labor force – and
the gender gap in employment was relatively low (Rutkowski, 2006). Throughout the
transition period, rates of participation in the labor market fell for both groups; still, for
males even more. The fact that the heavy industries were the ones most hurt by the
collapse of communism explains this phenomenon (Rutkowski, 2006). The increase of
the service sector in the market caused the manual work to be less demanded and the
new sector used the availability of female laborers.
The increase demand for female labor applies to Albania as well. Figure 1 shows
the overall level of LFPR in the country from 1989 till 2015, and also in specific for
males and females. Although during communism there was full employment of both
males and females, the data shows that this was not the case for the transition period. At
the beginning of the transition period less than half of the female labor was active in the
economy. Many authors point at the social policies as the main reason for this decrease.
According to Gregory & Stuart (2004), one of the most remarkable characteristics of the
communist regime was the implementation of social policies which provided a “safety
net” for the population. This net included among others
12
Labor Force Participation Rate
Rate
90.0
85.0
80.0
75.0
70.0
65.0
60.0
55.0
50.0
45.0
40.0
35.0
Total
Years
Male
Female
Figure 1: Labor Force Participation Rate in Albania in the years 1989-2015.
Source: INSTAT and ILO (2016).
“unemployment benefits, medical care, and pensions for the elderly” (Gregory & Stuart,
2004, p. 486). Goodsee (2004) supports the argument by saying that one of the reasons is
the decrease in states’ provision for child care, and other programs to help relieve the
double burden of women. The governmental budget experienced immense constraints
after entering the transition period. This cut the social benefits for families and thus
encouraged the birth rate to decline to a great extent. Only by having fewer children
could the double burden on females be made easier. In this way, they could afford to be
part of the active labor force in the country.
After a quick increase around mid ‘90s, this percentage continued to decrease to
levels below 40% during the later years. This is understandable with the civil unrest that
was happening in the country after the collapse of the pyramid schemes in 1996. Only
after 2006, the female participation in the labor market started to increase and it went
back close to the level of 1995 (INSTAT, 2016a; ILO, 2016). Baslevent and Onaran
13
(2003) explain similar patterns in Turkey through the “added worker effect” (as cited in
International Bank for Reconstruction and Development [IBRD], 2009, p.10). According
to this concept, those who were economically inactive before the downturn chose to
participate in the labor market during the recession in order to compensate for the
possible actual decrease of income in the household.
Furthermore, the birth rate decreased steadily throughout the transition period.
One would expect that a lower female participation rate would be associated with a
higher fertility rate. The classical microeconomic theory of fertility sees children in the
light of opportunity cost (Bjoras, 2005). Nevertheless, there are other aspects that are
related to the fertility rate beside the female participation rate. A deeper analysis of these
factors provides a clearer picture of the labor force participation rate throughout the
transition period in Albania.
Labor Supply Today
Many argue the transition period in Albania has ended. The EBRD Transition
Report 2010 shows that Albania has made positive changes in the transition to the
market economy in all four areas (European Bank for Reconstruction and Development
[EBRD], 2015). Others say that it is still present as Albania does not have a wellfunctioning market economy yet. Nonetheless, a clear distinction must be made between
the transition period, which started in 1991, and the situation today – 26 years later. The
labor supply has changed significantly throughout this period and several trends have
emerged.
Regional comparisons.
When looking at Figure 1, one might be surprised by the considerably low labor
force participation rate in Albania, after the end of the communist regime and at the
beginning of the democratic one. However, comparisons between countries in the region
14
show that Albania was at average levels of the employment rate throughout this period.
Table 1 illustrates that Albania had employment rates that fit within the range of those of
South East European countries.
Country
1990
1994
2000
Albania
100
81.50
74.90
Bulgaria
100
79.10
71.80
Romania
100
92.20
77.60
Croatia
100
77.10
77.60
Bosnia and Herzegovina
-
-
-
FYRO Macedonia
100
78.10
61.50
Serbia and Montenegro
100
89.30
82.60
Slovenia
100
82.50
84.50
Planned Economies average
100
84.27
74.77
SEE average
100
82.83
75.79
Former Yugoslavia average
100
81.75
76.55
Table 1: Employment in transition economies (1990=100). Source: United Nations
Economic Commission for Europe, Economic Survey of Europe, 2002, No.2 (as cited
in Arandarenko, 2004).
A rank of the countries from Table 1 (as shown in Appendix D) according to data
of 1994 and 2000 places Albania on the 4th place each time. Nevertheless, distinctions
emerge when comparing more recent data specifically about LFPR and by differentiating
between the female and the male labor force. Figure 2 illustrates Albania’s rank among
countries in Eastern Europe and Central Asia according to male LFPR.
Albania has a slightly lower LFPR (65.6) for its male population than the median
(68.2) that is Latvia. The chart illustrates that the Albanian male labor market is similar
to other countries in the region. It even has a higher participation rate than some EU
countries such as Romania, Poland, Belarus, and Bulgaria. Still, this is true only for the
male LFPR.
15
Male LFPR 2014
85.0
80.0
75.0
65.6
Rate
70.0
65.0
60.0
Kyrgyz Republic
Kazakhstan
Tajikistan
Turkmenistan
Uzbekistan
Georgia
Armenia
Russian Federation
Turkey
Azerbaijan
Latvia
Lithuania
Macedonia, FYR
Ukraine
Albania
Romania
Poland
Belarus
Bulgaria
Serbia & Montenegro
Bosnia and Herzegovina
50.0
Moldova
55.0
Country
Figure 2: Male Labor Force Participation Rate for 2014 for East European and
Central Asian countries (ILO estimations). Source: World Bank statistics database
(2016).
A different picture can be seen for the female LFPR.
Figure 3 shows a different position for the female labor force. Albania clearly has a
lower LFPR (41.3) than the median (50.2). Thus, it is important to analyze the
determinants of the labor force participation rate in Albania not only for the total
population, but also on a gender distinctive basis.
16
Female LFPR 2014
75.0
70.0
65.0
60.0
Rate
55.0
50.0
45.0
41.3
40.0
35.0
Lithuania
Latvia
Kazakhstan
Ukraine
Russian Federation
Belarus
Azerbaijan
Moldova
Bulgaria
Georgia
Armenia
Poland
Romania
Serbia & Montenegro
Tajikistan
Kyrgyz Republic
Albania
Uzbekistan
Macedonia, FYR
Turkmenistan
Bosnia and Herzegovina
25.0
Turkey
30.0
Country
Figure 3: Female Labor Force Participation Rate for 2014 for East European and
Central Asian countries (ILO estimations). Source: World Bank statistics database
(2016).
Some determinants can be identified through the Living Standard Measurement Survey
conducted by INSTAT with almost 15,000 households in Albania. According to this
survey for 2008, some of the reasons why the labor force is economically inactive are
education, childcare, retirement, and a perception of absence of chances to acquire a job
position. Table 2 provides more details regarding the main reasons why people chose not
to search for a job, i.e. drop out of the labor force.
17
Sex
Male
Female
Main reasons did not look for job
Count
Count
Housewife
-
1225
In retirement
1039
1009
Student / pupil
543
540
Believe that don't have any chance to get a job
169
188
Handicapped
164
164
Do not want to work
50
60
Waiting for busy season
28
29
Awaiting recall by employer
19
17
Have already found a job which will start later
22
9
In military service
16
-
Other
79
116
Total
2688
2798
Table 2: Reasons for nonparticipation in the labor market. Source: INSTAT, Living
Standard Measurement Survey 2008, (2011).
Theoretical background.
Furthermore, classic theory identifies several determinants of labor force
participation rate. According to the modern economic analysis of the fertility decision, a
household’s fertility depends not only on incomes, but also on prices. This theory treats
children just as another commodity and considers the expenses for them in terms of the
opportunity cost of expenses for other goods. Moreover, a higher number of children in a
household requires a lower number of working hours. The fertility rate for a family, thus,
decreases as the wage rate increases. This is especially true for women, whose wage rate
correlates negatively with the number of children they have (as cited in Bjoras, 2005).
Bjoras (2005) further analyzes the differences between economically active
males and females in the labor market by what is known as the intertemporal substitution
hypothesis. According to this hypothesis, “A person will work few hours in those
18
periods of the life cycle when the wage is low and will work many hours in those periods
when the wage is high” (Bjoras, 2005, p.73). Thus, the highest rates of LFPR are present
among the middle-aged population. In addition, there is a difference between males and
females. The increase of LFPR for males throughout the life cycle is steeper than for
females who tend to exit the labor market due to childbearing.
The increasing role of women in the world, however, is a factor that surely
augments the labor supply in the market. There are different factors that have caused this
increase in the role of women. One of them is related to the raise in wages. Theory
shows that an increase in the wage rate causes an increase in the labor supply of women.
That is self-explanatory when viewing labor in terms of opportunity cost. The higher the
wage rate, the higher the opportunity cost for women who do not work (Bjoras, 2005).
Thus, the greater will be the incentive for them to enter the labor market. There is also
another factor that has caused women to be more attracted to this market. This factor is
related to the role of labor laws that provide a better working environment and better
social protection for women today.
Classical theorists identify several trends in the labor force participation of
women. One of them is related to the increase of married women in the labor force. As
the opportunity cost of not participating in the labor market increases, more and more
women choose to be economically active (Bjoras, 2005). Furthermore, according to
Mammen and Paxson (2000), there is a U-shaped relation between the LFPR of females
and the economic development of a country (as cited in Bjoras, 2005). As the economy
of a country develops, females participate less in the labor market. However, later on
they reenter the market due to the opportunity cost effect. Finally, education is another
determinant of this variable. The higher the education for females, the greater is their
participation in the labor market.
This is not the case for males, though, whose labor force participation rate is
affected by other determinants. The male LFPR is determined by what is known as the
age effect (Bjoras, 2005). According to Ehrenberg and Smith (2006), the career cycle of
19
male laborers is more compressed. There is a notable decrease in the participation rate of
younger and older males.
The minimum retirement age also plays a major role in the LFPR of a country,
especially for that of the older generations. Since 1993, the Albanian government has
persistently increased the minimum retirement age for both men and women. This is
considered as another important factor in this market by labor economists (Bjoras,
2005). Taking into consideration the increasing life expectancy of the Albanian
population, this factor needs to be considered when analyzing the determinants of the
LFPR. It is especially important as it represents a governmental goal because it will
reduce the state’s costs for pensions.
Labor Supply Gender Differences.
Albania is characterized by a relatively young population. The average age in
2001 was 32.5 years old (INSTAT, 2015a). Furthermore, a simple analysis of the
Albanian population demographics in terms of age reveals a high percentage of the
population between 15 and 49 are among the first groups. Over 30% of the population is
aged from 15 to 24. Over 45% of the population is between 35 and 49 years old
(INSTAT, 2015a). These numbers are quite similar when compared for gender
differences. On the other hand, the fertility rate is at low levels. Data from Albania
Demographic and Health Survey 2008-2009 from INSTAT shows a fertility rate of 1.6
in Albania, while CIA estimates a rate of 1.47 for 2015. The fertility rate is higher in the
rural areas, as one would expect, than in the urban ones. So is the labor supply. Still, the
differences are fairly small, around 10% (INSTAT, 2015a).
A final distinction in the labor supply determinants is related to education. The
above-mentioned survey shows that the Albanian population is quite well-educated.
Several differences emerge, however, between males and females. About 10% more
females have primary education, while almost 11% more males have secondary,
20
professional, or technical education. The percentage for university or higher education is
slightly higher for females with a mean of both groups around 12.75% (INSTAT,
2015a).
Determinants of LFPR and similar studies.
The body of literature emphasizes some identifiable trends and determinants for
the labor force participation rate in the economy of a country. The level of development
of the economy is one of the main predictors, especially for the female labor force
participation rate. Age of marriage and education also have an impact. Furthermore,
indicators of fertility and life expectancy are important in the determination of the LFPR.
Finally, the age cohorts play an essential role as well.
The International Bank for Development and Reconstruction (2009) conducted a
similar study in Turkey to analyze the distinctively female LFPR in the country. The
study takes a socio-economic approach to the issue by also identifying the cultural
influence. The study analyzes education, fertility rates, wage levels, retirement, sociocultural factors, and civil status as determinants of the low – less than 30% – female
LFPR in Turkey. Their study indicates that urbanization and the change in rates of
employment in the agricultural sector are two crucial predictors as well.
Assumption
Finally, communism and the transition period have shaped the LFPR of the
Albanian population to what it is today. Studies have been conducted to analyze the
trends of the LFPR in other countries. However, there is a need for further similar
analysis in the Albanian labor market. No study has previously focused on the trends and
determinants of LFPR in the Albanian economy. Therefore, this study attempts to give a
clearer picture about this market, its determinants, and what the present trends are. This
21
is the labor market of a country that was the most closed economy in the world several
decades ago. Today this emerging market economy has serious aspirations for European
Union membership.
CHAPTER III: METHODOLOGY
Data
This study uses standard labor market statistics. Secondary data was collected
from the Albanian Institute of Statistics, International Labor Organization, World Bank,
and United Nations. The data about the LFPR was collected from INSTAT and ILO. The
timeframe of this data is 1989 to 2014. Furthermore, the study uses the information
provided by the Labor Force Survey of 2008. This survey was conducted by INSTAT
and includes responses from almost 19,000 participants from different regions in
Albania. The demographic data related to urban population and rural population;
marriage rate, divorce rate, number of births, and childcare services; basic education; life
expectancy, and age groups was collected from INSTAT. This study uses also another
survey conducted by INSTAT. That is the Living Standard Measurement Survey 2008
which refers to data from almost 15,000 households. Some of the data about the
economic indicators were derived from INSTAT as well. They include: GDP,
employment rates in the agricultural sector, employment in manufacturing industry,
average wage, and wage in industry. The number of the economically active population
for both males and females divided by age cohort is derived from the ILO and UN
databases. Finally, the data regarding remittances in Albania and the regional
comparisons is retrieved from the World Bank.
Research Strategy
22
The first part of the research consists of the analysis of the LFPR in Albania in
2014 in order to determine some of the main trends that have emerged throughout the
transition period. A deeper analysis of these trends contributes to a better understanding
of the determinants of LFPR. The focus is mainly on gender differences between the two
rates of the economically active part of the population. The second part is based on the
differences that have emerged between 1990 and 2015 among the male and female age
groups that participate in the labor market. The third part analyzes the patterns of the
total LFPR and the female LFPR over the 25 years period. Finally, the regression
analysis shows the determinant factors of the LFPR for the total, female, and male
population.
The regression analysis follows with the respective regression equations for the
total LFPR, the male LFPR, and the female LFPR. More details for this analysis are
provided in Appendix A.
The regression equation for the total Labor Force Participation Rate is
LFPR_TMF = 314 - 0.0000578 GDP (million_leks) - 2.48 Marriage_rate(1000inh)
+ 0.000271 Births - 0.000684 Basic.EdT - 0.000431 T44-64
(**)
(***)
+ 0.00149 Avg.Wage - 0.3587 Life.exp.T
(**)
(P-value significant * at 10%, ** at 5%, and *** at 1%)
Where:
LFPR_TMF is the Labor Force Participation Rate for the total population.
GDP(million_leks) is the Gross Domestic Product in million Albanian Leks.
Marriage_rate(1000inh) is the marriage rate for 1000 inhabitants.
Births is the number of births in total.
Basic.EdT is the total of the population enrolled in basic education.
T44-64 is the total population aged between 44 and 64.
23
Avg.Wage is the average wage.
Life.exp.T is the average life expectancy of the total population.
Each of the independent variables is on an annual basis. The regression equation covers
99.9% of the data as the R-sq (adj) suggests.
The regression equation for the male Labor Force Participation Rate is
LFPR_M = 53.22 + 0.00095 MEA20-24 + 0.00031 MEA25-44 - 0.00099 MEA45-65
(**)
(***)
- 0.000088 GDP (million_leks) - 0.208 EMPs_manuf.ind + 0.000269 Wag.Indu
(**)
(P-value significant * at 10%, ** at 5%, and *** at 1%)
Where:
LFPR_M is the Labor Force Participation Rate of the male population.
MEA20-24 is the male economically active population of age 20 to 24.
MEA25-44 is the male economically active population of age 25 to 44.
MEA45-65 is the male economically active population of age 45 to 65.
GDP(million_leks) is the Gross Domestic Product in million Albanian Leks.
EMPs_manuf.ind is the employment rate in the manufacturing industry.
Wag.Indu is the average wage in the industry sector.
Each of the independent variables is on an annual basis. The regression equation covers
98.3% of the data as the R-sq (adj) suggests.
The regression equation for the female Labor Force Participation Rate is
LFPR_F = 243 + 0.98 Avg.Marr.ageF + 3.84 Marriage_rate(1000inh) + 0.15 Div_rate
-1.89 Life.exp.F + 0.000155Ed.F - 0.000222F25-44 - 0.000066F65- 0.00043 Child.Kindg.T
24
(*)
(P-value significant * at 10%, ** at 5%, and *** at 1%)
Where:
LFPR_F is the Labor Force Participation Rate of the female population.
Avg.Marr.ageF is the average marriage age of the female population.
Marriage_rate (1000inh) is the marriage rate for 1000 inhabitants.
Div_rate is the rate of divorce measured as per 100 marriages.
Life.exp.F is the average life expectancy of the female population.
Ed.F is the number of the female students enrolled in the higher education.
F25-44 is the female population aged between 25 and 44.
F65- is the female population aged 65 and above.
Child.Kindg.T is the total number of children enrolled in the kindergarten programs.
Each of the independent variables is on an annual basis. The regression equation covers
94.4% of the data as the R-sq (adj) suggests.
Limitations and Problems
One of the limitations is related to the fact that no similar study has been
conducted previously in Albania. Therefore, it is hard to compare this study to other
similar studies in the country. Another limitation is related to the timeframe of the data.
It might be hard to observe substantial trends over a 25 year period. The absence of
available and reliable statistics about Albania prior to the transition period limits
research to this time period. Still, this study is focused on analyzing the trends that have
emerged from 1989 to 2015. Finally, this study does not take into account the informal
economy which is relatively high in Albania. This affects the level of the LFPR to a
great extent, as this rate includes only official employment and unemployment.
Also, INSTAT, after the publication of the revised population estimates for the
years 2001-2014 in May 2014, which reflected the population changes derived by the
25
Population and Household Census 2011, has revised the Quarterly Labour Force Survey
time series. There is a significant change in the demographic information as regards to
the structure of population and households, which in turn has had its impact on the
change of the labour market indicators starting from the first quarter of 2012 to the first
quarter of 2014. That is the reason why in the thesis is done analysis for different time
frame periods during these 25 years in order to see the changes.
CHAPTER IV: DATA ANALYSIS
Labor Force Participation Rate at present
Data from the Labor Force Survey 2008 shows the presence of differences in the
LFPR of males and females. The following chart portrays the change throughout the life
cycle in the LFPR for both males and females.
26
LFPR in 2008 (gender based)
0.9
0.8
0.7
Rate
0.6
0.5
0.4
0.3
0.2
0.1
A
21 ge
To
25 tal
To
29 tal
To
33 tal
To
37 tal
To
41 tal
To
45 tal
To
49 tal
To
53 tal
To
57 tal
To
61 tal
To
65 tal
To
69 tal
To
ta
l
0
Age
Male
Female
Figure 4: Labor Force Participation Rate in 2008 based on gender differences.
Source: INSTAT, Labor Force Survey 2008, (2010).
The phenomenon that Bjoras (2005) identifies in the LFPR over the life cycles is
present in the Albanian population as well. Both males and females have lower LFPR at
the beginning and at the end of their career period. The reasons behind this phenomenon
are related to the wage rates at these periods of one’s career. Furthermore, there are
differences between the male and female LFPR. The male labor participation curve is
steeper at the beginning of the life cycle. It continues to grow steadily, at least until the
age of 33 in which it reaches a rate of over .80. It reaches its climax at the age of 48 with
a labor force participation rate of almost .90. The actual decline starts after the age of 53
and the rate is lower than .85.
27
The situation is different among the female labor force. There is a major increase
in the labor participation rate until the age of 26, although it is lower than that of males.
After this age, in which the labor force participation rate is almost .53, the rate of
increase declines significantly. Thus, the curve has a horizontal tendency. This
phenomenon is explained by the fact that close to this age, many females experience
childbearing. Males, on the other side, cannot exit the labor market due to this
experience. On the contrary, they are more inclined to remain in the labor market as they
might be the only ones to provide for the household. Hence, the gap between the two
groups increases.
After the age of 35, there is an augment in the LFPR of females, at a small rate of
increase though, until its climax at 48 years of age with a rate of almost .80. The female
rate remains at relatively higher levels until the age of 55 while that of males has already
started declining after the climax.
One might at first be surprised by the decline in the LFPR after the age of 58 for
females and after the age of 63 for males. This might seem paradoxical especially
considering the longer and increasing life expectancy among both groups. The life
expectancy for the last few years has been between 77 and 78 for females and 72 and 73
for males. However, the Albanian legislation reflects a possible explanation. In 1993, the
Albanian government adapted Law no. 7703 for social security according to which the
minimal age of pension is going to increase gradually throughout the next three decades
(Institute of Social Insurance in Albania [ISSH], 2011). The minimum age for males and
females in 2008 is respectively 63 and 58, which is the same age as the one after which
both curves decline steeply.
Gender Differences between 1990 and 2014
Data from the ILO show that there is a change in the LFPR between 1990 and
2008 for males and females respectively. On the one hand, males entered the labor force
28
later in 2008 than they did in 1990, as the difference in trend lines show. Nonetheless, at
the age of 25-29 there is a reverse effect. Males between 25 and 59 years old participate
at a higher rate in the labor market than they did 18 years earlier, as Figure 5 illustrates.
After this age, they exited the labor market at a faster rate than they did in 1990.
Male Participation rate 1990 and 2008
1990
100
2008
90
Trend '08
80
Trend '90
Rate
70
60
50
40
30
20
10
+
65
-6
4]
-5
9]
[6
0
Age category
[5
5
-5
4]
[5
0
-4
9]
[4
5
-4
4]
[4
0
-3
9]
-3
4]
[3
5
[3
0
-2
9]
[2
5
-2
4]
[2
0
[1
5
-1
9]
0
Figure 5: Male participation rate 1990 and 2008. Source: ILO (2011).
The change in the LFPR among males of different age groups in 1990 and 2008
also supports the classical dynamics in labor economics. The labor force participation
rate has decreased among young and old Albanian males throughout these 18 years. This
is explained by the fact that more of them continue in higher education, need to
participate in the labor market at a greater extent during their middle age, and can exit
the labor market at an earlier age. Their need for greater participation in the labor market
during their middle age can be explained by the fact that they are supporting their
29
children in education and are contributing to greater savings and pension incomes. It also
supports the intertemporal substitution hypothesis (Bjoras, 2005) as during this age they
will experience peak earnings.
A greater difference is noticed among the female participation rate, as Figure 6
shows. The differences in the trend lines are similar to those of the male participation
rate. Still, there is relatively a greater difference of females participating in the labor
market in 2008 from those of 1990. The more recent ones enter the labor market at a
later age, but they are more active in the economy throughout their middle age.
Furthermore, the change observed among the female laborers also supports the
classical theory for their entrance into the labor market. The considerable increase in the
number of female students explains the delay participating in this market. The increase
from 1994 to 2008 has been by more than 2.5 times (INSTAT, 2011). The number of
female students over this period highly correlates (-.944) with the number of births,
which has been decreasing immensely over the past decades from 72,179 in 1994 to
36,251 in 2008. In addition, the marriage age for women has also increased over the past
decades. All these three factors explain the decrease in the LFPR among young females.
They also explain the increase in the later part of life cycle as the lower number of
children demands less child care service and allows higher participation of women in the
labor market.
30
Female Participation rate 1990 and 2008
1990
70
2008
Trend '08
60
Trend '90
Rate
50
40
30
20
10
[1
51
[2 9]
02
[2 4]
52
[3 9]
03
[3 4]
53
[4 9]
04
[4 4]
54
[5 9]
05
[5 4]
55
[6 9]
064
]
65
+
0
Age category
Figure 6: Female participation rate 1990 and 2008. Source: ILO.
Change in the female LFPR over 20 years
Data about female participation in the labor market strongly supports the
theoretical background of the relationship between economic development and LFPR of
females. As Mammen and Paxson (2000) explained, the Albanian supply of female labor
is in a U-shaped trend as the economy develops (as cited in Bjoras, 2005).
This trend can also be noticed when examining the change in the female LFPR in
time, as Figure 8 shows. The initial labor market adjustment to the market economy in
Albania explains the steep decrease in the LFPR of females at the beginning of the
1990s. However, the U-shaped curve is more visible after the announcement in 1996 that
the pyramid schemes were bankrupt. As the economy started to recover after the1997
turmoil, females could again afford to exit the labor market.
31
Female LFPR
60.0
Rate
55.0
50.0
45.0
40.0
250,000
450,000
650,000
850,000
1,050,000 1,250,000
GDP
Figure 7: Relationship between female LFPR and Gross Domestic Product. Source:
Data collected from INSTAT, (2010).
32
LFPR Female 1989-2009
65.0
60.0
Rate
55.0
50.0
45.0
40.0
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
20
07
20
09
35.0
Years
Figure 8: Labor Force Participation Rate of females from 1989 until 2009. Source:
ILO (2011).
The increase in the average wage after 1997, explains the decrease in the female
LFPR in the first few years. Later on, as the opportunity cost of not participating in the
labor market increased, more females decided to be economically active.
An immediate decrease after 2008 might point to another explanation of the
change in the female LFPR. As Baslevent and Onaran (2003) explain, the significant
increase, and the decrease afterward, in this indicator both in 1996 and 2008 might be
due to the “added worker effect” (as cited in IBRD, 2009, p.10). In 1996 the turmoil of
the pyramid schemes shook the economy and in 2008 the perception of worldwide
financial crisis emerged in the country. In addition, the level of remittances decreased
during both of these years (World Bank, 2011). Each of these events encouraged the
female population to be active in the market. Once they were over, the female LFPR
decreased again.
33
Regression Analysis for LFPR
Total Labor Force Participation Rate
Dependent Variable: LFPR_TMF
Method: Least Squares
Date: 06/19/16 Time: 15:20
Sample (adjusted): 1997 - 2013
Included observations: 17 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
MARRIAGE_RATE
GDP_MIL_ALL
BIRTHS
BASIC_EDUCATION
T44_64
AVE_WAGE
LIFE_EXP_TOTAL
313.8311
-2.481676
5.78E-05
0.000271
-0.000684
-0.000431
0.001490
-0.358723
96.11239
1.566584
3.57E-05
0.000267
0.000278
0.000122
0.000510
1.197955
3.265251
-1.584132
1.619809
1.016110
-2.460551
-3.522587
2.924561
-0.299446
0.0098
0.1476
0.1397
0.3361
0.0361
0.0065
0.0169
0.7714
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.851083
0.735259
2.520729
57.18668
-34.43337
7.348062
0.003978
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
62.91176
4.899092
4.992161
5.384262
5.031137
2.199954
The model shows that the number of individuals with basic education (and no
higher education) negatively influences the LFPR of the total population. This fits within
the expectations given that those individuals who have invested more into education are
more likely to participate in the labor market in order to obtain more of their investment.
This variable is also highly significant, at 95% of confidence. Furthermore, the total
number of individuals in Albania aged 44-64 affects the total LFPR negatively. The
individuals in this age category are either retired or very close to retirement; as such,
they are less likely to be active in the labor market. Also, given the weak employee’s
protection policies in Albania and the fact that this age category is very likely to be
34
removed from employment and substituted with younger, more effective employees, this
might discourage Albanians aged 44-64 to exit the labor market once they might be
removed from employment. This variable is highly statistically significant, at 99% level
of confidence. Albania has a relatively young population with an average of 32.5 years
(as cited in INSTAT, 2011); thus, the employers can actively seek to employ the
younger share of the population. The average wage in the country positively affects the
total LFPR. This fits within the expectations for the model given that a higher average
wage encourages individuals to be more active in the labor market. This variable is also
highly statistically significant, at 95% level of confidence. The other indicators of the
regression show that it has a good explanatory power. R-squared and Adjusted Rsquared are significantly high. This means that the model explains about 73%-85% of
the changes in the dependent variable. Furthermore, the F-statistic and the respective
Prob (F-statistic) show that with a great confidence the null hypothesis that at least one
of the variables has a coefficient that is equal to 0 can be rejected.
The basic education of the total population negatively influences the LFPR. This
is supported by the fact that higher education has become a priority in the labor market
as a proxy for skills. As the number of urban population increases in Albania, job
opportunities become scarce in the cities. Thus, those who prefer to partake in the labor
market are more focused on tertiary education rather than the primary one. Furthermore,
this is supported by the steep decline in the LFPR of both males and females as they
approached the minimum pension age. The last factor in the equation that negatively
influences LFPR is life expectancy of the total population. The massive number of
people that retire early, who represent a significantly high public budget cost might be a
possible explanation for this phenomenon. They would still be counted as part of the
labor force as they are within the age frame of 15 to 64, but they are not part of the
active labor force.
Finally, there is another component that is not included in the equation, but
which highly correlates with most of the factors mentioned above. This is the level of the
35
remittances. According to the correlation table provided in Appendix C, the remittances
level correlates positively with most of the factors that influence the total LFPR
negatively (besides the average wage). This potentially explains some of the trend in the
LFPR. The increasing level of remittances over the last two decades has happened
simultaneously as the participation rate has decreased. People can afford to exit the labor
market, especially those at a younger age as their parents might work abroad, and those
at an older age as their children might work abroad. Both of these groups would have
remittances as part of their income, besides wage.
Male Labor Force Participation Rate
Dependent Variable: LFPR_MALE
Method: Least Squares
Date: 06/19/16 Time: 16:54
Sample (adjusted): 1997 2014
Included observations: 18 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
MEA20_24(-3)
MEA_25_44(-2)
MEA45_65
GDP_MIL_ALL
EMPS_MANUF_IND(2)
WAGE_INDUSTRY
53.22418
0.000952
0.000310
-0.000992
8.84E-05
163.2075
0.000369
0.000371
0.000312
3.49E-05
0.326114
2.580259
0.836159
-3.175973
2.532048
0.7505
0.0256
0.4209
0.0088
0.0279
-0.208703
0.000269
0.162049
0.000486
-1.287902
0.553467
0.2242
0.5910
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.903860
0.851419
2.261960
56.28110
-35.80078
17.23599
0.000052
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
74.11667
5.868184
4.755642
5.101898
4.803386
2.553127
36
The regression equation provided in Chapter III for the male LFPR strongly
supports the classical dynamics as shown by Ehrenberg and Smith (2006). There is a
negative relationship between the male economically active population of 20-24 years
old and the male LFPR. The number of males aged 20-24 three years ago positively
influences the present labor force participation rate of males. This means that this
category of males is more likely to be active in the labor force market after three years.
This is coherent given that an Albanian male aged 20-24 years is most likely pursuing
his education; after three years, he has completed his education and is actively seeking
employment. Therefore, a high number of males aged 20-24 at present will lead to a
higher LFPR after three years. This variable is also statistically significant at 95%. The
opposite is true for the number of males aged 45-65. This variable affects the present
LFPR negatively. This is due to the fact that these individuals are either retired or are
very close to their retirement and a higher number of males aged 45-65 at present will
provide a lower LFPR after two years. This variable is of high statistical significance
(99%). Another statistically significant variable is the Gross Domestic Product in
Albania. An increase in the GDP leads to an increase in the LFPR of males. An
improvement of the macroeconomic conditions in the country will lead to more
employment opportunities and higher wages; as a result, the individuals will be more
actively searching a job and participating in the labor market. The variable is also highly
statistically significant (95%). The other indicators of the regression show that it has a
good explanatory power. R-squared and Adjusted R-squared are significantly high. This
means that the model explains about 85%-90% of the changes in the dependent variable.
Furthermore, the F-statistic and the respective Prob (F-statistic) show that with a great
confidence the null hypothesis that at least one of the variables has a coefficient that is
equal to 0 can be rejected.
37
Female Labor Force Participation Rate
Dependent Variable: LFRP_FEMALE
Method: Least Squares
Date: 06/19/16 Time: 16:56
Sample (adjusted): 1994 2015
Included observations: 22 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
AVE_MARR_AGE_FEM
ALE
MARRIAGE_RATE
DIVORCE_RATE(-2)
LIFE_EXP_FEMALE
EDU_FEMALE
F25_44(-2)
F45_65(-3)
CHILD_KINDG_T(-3)
243.1577
110.1034
2.208450
0.0458
0.983364
3.842654
0.156261
-1.891082
0.000155
-0.000222
-6.61E-05
-0.000430
3.559182
2.043970
0.876205
1.185183
0.000353
0.000432
0.000464
0.000243
0.276289
1.879995
0.178338
-1.595603
0.439298
-0.512305
-0.142450
-1.764624
0.7867
0.0827
0.8612
0.1346
0.6677
0.6170
0.8889
0.1011
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.456878
0.122649
4.259978
235.9163
-57.31343
1.366962
0.295924
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
52.16364
4.548003
6.028494
6.474829
6.133637
1.961143
The female LFPR is predicted by different factors from the male one. The
marriage rate positively affects the female LFPR in Albania. This means that as the
number of marriages per 1000 inhabitants increases, there is a higher likelihood for
females to partake into marriages. This can be viewed in two perspectives. On the one
side, married females have a lower likelihood to participate in the labor market given
their family responsibilities and maternal duties. On the other side, married females
nowadays in Albania are less encouraged from the government to leave the labor market.
Given the higher family demands for income, married females are more likely to partake
in the labor market. This is contradicted by the female ages variables, respectively
number of females aged 25-44 and 45-65. They both affect the female LFPR negatively,
38
though none of them is statistically significant. Since both of these variables are used in
lags, this might be an indicator that females in Albania tend to go into retirement early.
However, such conclusions go beyond the scope of this study and need further research.
The number of children in the child care three years ago affects the present LFPR
negatively. An increase in the number of children in the kindergarten has a negative
impact in the current LFPR of females. This variable is statistically significant at 90%.
The number of females with high education also affects the LFPR of females positively.
This fits within the expectations of the model as the better educated a female is, the more
likely she is to actively participate in the labor market. Still, the variable is not
statistically significant. The other indicators of the regression show that its explanatory
power could be improved. R-squared is fairly high. This means that the model explains
about 50% of the changes in the dependent variable. Furthermore, the F-statistic and the
respective Prob (F-statistic) show that other variables should be considered in order to
improve the model’s explanatory power.
CHAPTER V: CONCLUSIONS AND RECOMMENDATIONS
Finally, the trends in the Albanian labor market show some features of a typical
post-communist country going through transition and some other features typical of
more-adjusted economies. Most of the countries with a similar background have had a
decrease in the labor force participation rate of their population from very high levels to
ones comparable with the EU countries, especially for the female LFPR. This has not
been the case for Albania where the rate of the economically active female population
remains low. However, this study reveals that the trends are similar to economies that
have converged and adjusted to the market system. This shows that the Albanian labor
market is adjusting to market conditions and converging to regional ones like the South
East Europe. The more important question is whether this adjustment to the market
39
economic system is over. The labor force responds to the incentives provided in the
market, and these incentives fit within the theoretical background. Hence, the study
concludes that the labor force has reallocated into the market economy.
There are several policies on which the government could focus in order to
improve the LFPR of both females and males in the country. One reason that explains
the low level of LFPR in the country is the high and increasing level of remittances. A
potentially additional one is the high level of informality. Thus, the government could
increase this rate through active labor market policies that encourage entrance into the
formal economy. Besides the increase in the LFPR, the results would include a
significant improvement in the level of tax revenue, but this topic goes beyond this
study.
Furthermore, the government could improve the LFPR in the country through
policies that encourage the positive determinants of the total, male, or female labor force
participation rate. For example, an improvement in childcare would considerably
increase the number of the economically active female population. Also, an
improvement in housing policies would potentially encourage greater mobility. In
addition, a focus in the employment in the manufacturing industry would increase the
LFPR of the male population. This would also result if wages in industry, in general,
were raised as well. This is especially true due to the increasing trend of reservation
wages as a result of increasing remittances. The use of several policies that encourage
development in the industry sector could be a way to achieve this goal. Finally, a deeper
analysis would be necessary to suggest better policy strategies. This is an area that other
studies could research further.
40
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Appendix A
Regression Analysis
Total Labor Force Participation Rate
Dependent Variable: LFPR_TMF
Method: Least Squares
Date: 06/19/16 Time: 15:20
Sample (adjusted): 1997 2013
Included observations: 17 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
44
C
313.8311
96.11239
3.265251
0.0098
MARRIAGE_RATE
GDP_MIL_ALL
BIRTHS
BASIC_EDUCATION
T44_64
AVE_WAGE
LIFE_EXP_TOTAL
-2.481676
5.78E-05
0.000271
-0.000684
-0.000431
0.001490
-0.358723
1.566584
3.57E-05
0.000267
0.000278
0.000122
0.000510
1.197955
-1.584132
1.619809
1.016110
-2.460551
-3.522587
2.924561
-0.299446
0.1476
0.1397
0.3361
0.0361
0.0065
0.0169
0.7714
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.851083
0.735259
2.520729
57.18668
-34.43337
7.348062
0.003978
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
62.91176
4.899092
4.992161
5.384262
5.031137
2.199954
Source: Regression analysis of collected data through the use of E-Views.
Male Labor Force Participation Rate
Dependent Variable: LFPR_MALE
Method: Least Squares
Date: 06/19/16 Time: 16:54
Sample (adjusted): 1997 2014
Included observations: 18 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
MEA20_24(-3)
MEA_25_44(-2)
MEA45_65
GDP_MIL_ALL
EMPS_MANUF_IND(-2)
WAGE_INDUSTRY
53.22418
0.000952
0.000310
-0.000992
8.84E-05
-0.208703
0.000269
163.2075
0.000369
0.000371
0.000312
3.49E-05
0.162049
0.000486
0.326114
2.580259
0.836159
-3.175973
2.532048
-1.287902
0.553467
0.7505
0.0256
0.4209
0.0088
0.0279
0.2242
0.5910
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.903860
0.851419
2.261960
56.28110
-35.80078
17.23599
0.000052
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
74.11667
5.868184
4.755642
5.101898
4.803386
2.553127
Source: Regression analysis of collected data through the use of E-Views.
MEA20_24(-3) – the number of males aged 20-24 (third lag)
45
MEA_25_44(-2) – the number of males aged 25-44 (second lag)
MEA45_65 – the number of males aged 45-65
GDP_MIL_ALL – GDP in millions of Albanian Leke
EMPS_MANUF_IND(-2) – LPRF of males in the manufacturing industry (second lag)
WAGE_INDUSTRY – average wage (industry)
Female Labor Force Participation Rate
Dependent Variable: LFRP_FEMALE
Method: Least Squares
Date: 06/19/16 Time: 16:56
Sample (adjusted): 1994 2015
Included observations: 22 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
AVE_MARR_AGE_FEMAL
E
MARRIAGE_RATE
DIVORCE_RATE(-2)
LIFE_EXP_FEMALE
EDU_FEMALE
F25_44(-2)
F45_65(-3)
CHILD_KINDG_T(-3)
243.1577
110.1034
2.208450
0.0458
0.983364
3.842654
0.156261
-1.891082
0.000155
-0.000222
-6.61E-05
-0.000430
3.559182
2.043970
0.876205
1.185183
0.000353
0.000432
0.000464
0.000243
0.276289
1.879995
0.178338
-1.595603
0.439298
-0.512305
-0.142450
-1.764624
0.7867
0.0827
0.8612
0.1346
0.6677
0.6170
0.8889
0.1011
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.456878
0.122649
4.259978
235.9163
-57.31343
1.366962
0.295924
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
52.16364
4.548003
6.028494
6.474829
6.133637
1.961143
Source: Regression analysis of collected data through the use of E-Views.
The dependent variable is the Labor Force Participation Rate of Females in Albania. The
independent variables are:
AVE_MARR_AGE_FEMALE – average marriage age of females in Albania
MARRIAGE_RATE – rate of marriages in Albania (per 1000 inhabitants)
DIVORCE_RATE(-2) – divorce rate in Albania (per 1000 inhabitants) – second lag
LIFE_EXP_FEMALE – female life expectancy
EDU_FEMALE – number of females that have high education in Albania
46
F25_44(-2) – number of females in Albania aged 25-44 – second lag
F45_65(-3) – number of females in Albania aged 45-65 – third lag
CHILD_KINDG_T(-3) - number of children in the kindergarten – third lag
APPENDIX B
Life expectancy
81.00
80.00
79.00
78.00
77.00
76.00
75.00
74.00
73.00
72.00
71.00
70.00
69.00
68.00
67.00
Years
Years
1950 – 1951
1951 – 1956
1960 – 1961
1979 – 1980
1980 – 1981
1984 – 1985
1985 – 1986
1986 – 1987
1987 – 1988
1988 – 1989
1989 – 1990
Total
53.5
57.8
64.9
69.5
70.2
71.5
71.9
72.0
72.2
72.4
72.2
In year
Male
52.6
57.2
63.7
67.0
67.7
68.7
68.7
68.8
69.4
69.6
69.3
Female
54.4
58.6
66.0
72.3
72.2
74.4
75.5
75.5
75.5
75.5
75.4
Females
2014
2012
2010
2008
Females
Males
2006
2004
2002
2000
1998
1996
1994
1992
`
1990
Years of life
Demographical Data
47
Table 6: Life expectancy for males and females over the period 1950-2014. Source:
INSTAT (2011).
Years
1994 /
95
1995 /
96
1996 /
97
1997 /
98
1998 /
99
1999 /
00
2000 /
01
2001 /
02
2002 /
03
2003 /
04
2004/0
5
2005/0
6
2006/0
7
2007/0
8
2008/0
9
2009/1
0
2010/1
1
2011/1
2
2012/1
3
2013/1
4
Total
numbe
r of
studen
ts
28331
30086
34257
35902
38502
40125
40859
42160
43600
53014
63257
74157
86178
90202
93206
122326
134877
158963
172561
173819
Tota
l
male
1341
0
1391
4
1488
1
1553
5
1547
0
1609
5
1579
0
1603
6
1642
0
2016
8
2512
9
3083
2
3731
2
3928
3
4059
6
5443
9
6015
9
7045
1
7620
2
7552
7
Total
Femal
e
Total in
public
Educati
on
Male in
public
educati
on
Female
in
public
educati
on
Total in
private
educati
on
Male in
private
educati
on
Female
in
private
educati
on
14921
28331
13410
14921
-
-
-
16172
30086
13914
16172
-
-
-
19376
34257
14881
19376
-
-
-
20367
35902
15535
20367
-
-
-
23032
38502
15470
23032
-
-
-
24030
40125
16095
24030
-
-
-
25069
40859
15790
25069
-
-
-
26124
42160
16036
26124
-
-
-
27180
43600
16420
27180
-
-
-
32846
52609
19976
32633
405
192
213
38128
62274
24696
37578
983
433
550
43325
72465
30081
42384
1692
751
941
48866
82099
35384
46715
4079
1928
2151
50919
80696
34291
46405
9506
4992
4514
52610
79795
34123
45672
13411
6473
6938
67887
98917
42755
56162
23409
11684
11725
74718
107523
46315
61208
27354
13844
13510
88512
124413
52349
72064
34550
18102
16448
96359
139034
59213
79821
33527
16989
16538
98292
142707
59146
83561
31112
16381
14731
48
Table 7: Number of male and female students enrolled in the total, public, and
private higher education from 1994 until 2010. Source: INSTAT (2011).
Births
90,000
80,000
Series
1
Number of births
70,000
60,000
50,000
40,000
30,000
20,000
10,000
0
Years
Figure 9: Number of births in the country over the period 1994-2014. Source:
INSTAT (2016).
49
Years
Average age of marriage
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
Series2
Series1
20.021.022.023.024.025.026.027.028.029.030.031.0
Age
Figure 10: Average age of marriage for males and females over the period 19902014. Source: INSTAT (2016).
Economic
Activity
1997
1998
1999
2000
2001
2002
Year
2003
2004
2005
2006
2007
2008
Industry
Construction
9,411
10,792
12,203
13,230
14,839
15,882
18,286
19,200
20,200
21,950
24,735
31,174
8,340
10,617
10,936
12,489
13,416
15,014
15,017
16,055
17,361
19,184
32,085
42,424
Transport and
communication
9,350
11,744
14,503
16,225
18,124
23,434
27,030
27,439
28,144
31,360
36,518
38,106
Trade
Services
Total
8,819
9,653
10,901
10,889
12,856
13,924
14,120
15,711
17,561
20,677
27,301
32,217
7,814
11,856
10,718
13,012
13,140
14,453
18,159
17,574
18,517
19,869
23,636
27,951
9,063
10,894
12,118
13,355
14,820
16,541
18,522
19,039
19,993
21,842
27,350
27,951
Table 8: The average wage in total and for each of the main industries over the
period 1997-2008. Source: INSTAT (2011).
50
Men
Category I
Years
Age
1993
1994
1995
1996
1997
1998
1999
2000
2001
01.07.2002 - 30.06.2003
01.07.2003 - 30.06.2004
01.07.2004 - 30.06.2005
01.07.2005 - 30.06.2006
01.07.2006 - 30.06.2007
01.07.2007 - 30.06.2008
01.07.2008 - 30.06.2009
01.07.2009 - 30.06.2010
01.07.2010 - 30.06.2011
01.07.2011 - 30.06.2012
01.07.2012 - 30.06.2013
01.07.2013 - 30.06.2014
01.07.2014 - 30.06.2015
01.07.2015 - 30.06.2016
01.07.2016 - 30.06.2017
01.07.2017 - 30.06.2018
01.07.2018 - 30.06.2019
01.07.2019 - 30.06.2020
01.07.2020 - 30.06.2021
01.07.2021 - 30.06.2022
01.07.2022 - 30.06.2023
2023 and later
50
50
51
51
52
52
53
53
54
54
55
55
56
56
57
57
58
58
59
59
60
60y 6m
61y
61y 6m
62y
62y 6m
63y
63y 6m
64y
64y 6m
65y
Category II
Years of Age
work
20
55
20
55
21
56
21
56
22
57
22
57
23
58
23
58
24
59
24
59
25
60
25
60y 6m
26
61y
27
61y 6m
28
62y
29
62y 6m
30
63y
31
63y 6m
32
64y
33
64y 6m
34
65y
35
35
35
35
35
35
35
35
35
35
Category III
Years of Age
work
25
60
25
60
26
60
27
60
28
60
29
60
30
60
31
60
32
60
33
60y 6m
34
61y
35
61y 6m
35
62y
35
62y 6m
35
63y
35
63y 6m
35
64y
35
64y 6m
35
65y
35
35
Years of
work
25
25
26
27
28
29
30
31
32
33
34
35
35
35
35
35
35
35
35
51
Table 9: Minimal age and required years of social insurance paid for each of the
categories for the male population. Source: Albanian Legislation (and the changes
made accordingly) from Law no. 7703, date 11.05.1993 till Law nr. 10070, date
05.02.2009 (ISSH, 2014).
Women
Years
1993
1994
1995
1996
1997
1998
1999
2000
2001
01.07.2002 - 30.06.2003
01.07.2003 - 30.06.2004
01.07.2004 - 30.06.2005
01.07.2005 - 30.06.2006
01.07.2006 - 30.06.2007
01.07.2007 - 30.06.2008
01.07.2008 - 30.06.2009
01.07.2009 - 30.06.2010
01.07.2010 - 30.06.2011
01.07.2011 - 30.06.2012
01.07.2012 - 30.06.2013
01.07.2013 - 30.06.2014
01.07.2014 - 30.06.2015
01.07.2015 - 30.06.2016
01.07.2016 - 30.06.2017
01.07.2017 - 30.06.2018
01.07.2018 - 30.06.2019
01.07.2019 - 30.06.2020
01.07.2020 - 30.06.2021
Category
Category II
Category III
I
Age
Years of Age
Years of Age
Years of
work
work
work
45
15
50
20
55
20
45
15
50
21
55
21
46
16
51
22
55
22
46
17
51
23
55
23
47
18
52
24
55
24
47
19
52
25
55
25
48
20
53
26
55
26
48
21
53
28
55
28
49
22
54
30
55
30
49
23
54
32
55y 6m 32
50
24
55
34
56y
34
50
25
55y 6m
35
56y 6m 35
51
26
56y
35
57y
35
51
27
56y 6m
35
57y 6m 35
52
28
57y
35
58y
35
52
29
57y 6m
35
58y 6m 35
53
30
58y
35
59y
35
53
31
58y 6m
35
59y 6m 35
54
32
59y
35
60y
35
54
33
59y 6m
35
55
34
60y
35
55y 6m
35
56y
35
56y 6m
35
57y
35
57y 6m
35
58y
35
58y 6m
35
52
35
01.07.2021 - 30.06.2022 59y
35
01.07.2022 - 30.06.2023 59y 6m
60y
35
2023 and later
Table 10: Minimal age and required years of social insurance paid for each of the
categories for the female population. Source: Albanian Legislation (and the changes
made accordingly) from Law no. 7703, date 11.05.1993 till Law nr. 10070, date
05.02.2009 (ISSH, 2014).
APPENDIX C
Remittances
Figure 11: Remittances in Albania in current US$ (billions) from 1992 till 2009.
Source: World Bank (2015).
Correlation with other variables
Remittances
GDP
Marriage_rate
Births
Basic.Ed.T
T44-64
Ave.Wage
Life.exp.T
Correlation
0.942
-0.74
-0.916
0.663
0.982
0.96
0.802
53
Table 12: Correlation of the level of remittances with the other variables included
in the regression equation for the total LFPR. Source: Correlation analysis of
collected data through the use of Minitab.
APPENDIX D
Regional Data
Rank by 1994
1
2
3
4
5
6
7
8
9
10
11
Country
Croatia
FYRO Macedonia
Bulgaria
Albania
Former Yugoslavia average
Slovenia
SEE average
Planned economies average
Serbia and Montenegro
Romania
Bosnia and Herzegovina
1990
100
100
100
100
100
100
100
100
100
100
-
1994
77.10
78.10
79.10
81.50
81.75
82.50
82.83
84.27
89.30
92.20
-
2000
77.60
61.50
71.80
74.90
76.55
84.50
75.79
74.77
82.60
77.60
-
Table 13: Employment in transition economies (1990=100), ranked by data of 1994.
Source: United Nations Economic Commission for Europe, Economic Survey of
Europe, 2002, No.2 (as cited in Arandarenko, 2004).
Rank by 2000
1
2
3
4
5
6
7
8
9
10
11
Country
FYRO Macedonia
Bulgaria
Planned economies average
Albania
SEE average
Former Yugoslavia average
Croatia
Romania
Serbia and Montenegro
Slovenia
Bosnia and Herzegovina
1990
100
100
100
100
100
100
100
100
100
100
-
1994
78.10
79.10
84.27
81.50
82.83
81.75
77.10
92.20
89.30
82.50
-
2000
61.50
71.80
74.77
74.90
75.79
76.55
77.60
77.60
82.60
84.50
-
Table 14: Employment in transition economies (1990=100), ranked by data of 2000.
Source: United Nations Economic Commission for Europe, Economic Survey of
Europe, 2002, No.2 (as cited in Arandarenko, 2004).
54
Male LFPR
2008
2012
2014
Europe and Central Asia
47.4
43.3
45
Moldova
58.3
57.2
57.4
Bosnia and Herzegovina
62.4
59.1
59.2
Serbia & Montenegro
61.9
58.8
59.2
Bulgaria
61.6
62.7
63.4
Belarus
63.0
64.8
64.9
Poland
64.1
64.7
65.1
Romania
66.0
65.4
65.6
Albania
65.7
66.6
67.1
Ukraine
67.6
67.3
67.6
Macedonia, FYR
Lithuania
63.6
66.3
67.7
70.4
67.1
68
Latvia
67.7
68.9
70.3
Azerbaijan
70.0
70.8
70.8
Turkey
70.8
71.4
71.8
Russian Federation
69.0
72
73.1
Armenia
Georgia
73.3
74.7
75.5
73.7
75.2
75.9
Uzbekistan
75.2
76.5
77.3
Turkmenistan
75.6
76.9
77.4
Tajikistan
75.8
77.5
78.2
Kazakhstan
77.6
79
80
Kyrgyz Republic
Table 15: Male Labor Force Participation Rate for 2008, 2012, and 2014 for East
European and Central Asian countries. Source: World Bank statistics database
(2016).
Female LFPR
2008
Europe and Central Asia
Turkey
24.5
Bosnia and Herzegovina
32.4
Moldova
40.8
Macedonia, FYR
42.6
Serbia & Montenegro
45.35
Albania
45.9
Turkmenistan
46.5
Bulgaria
48.7
Uzbekistan
47.5
Poland
46.7
2012
29.4
34.1
37
42.9
43.65
45
46.7
47.8
47.9
48.9
2014
29.3
34.2
38.1
43.2
43.75
44.8
47.1
48
48.2
48.9
55
Romania
Belarus
Ukraine
Armenia
Latvia
Lithuania
Kyrgyz Republic
Georgia
Russian Federation
Tajikistan
Azerbaijan
Kazakhstan
48.1
49.6
52.2
48.2
55.1
51.8
54.8
55.3
56.9
58.1
60.9
66.4
48.5
49.9
53
53.9
54.5
55.8
55.7
56.2
57
58.7
62.5
67.5
49
50.3
53.5
54.5
55.2
56
56.3
56.8
57.1
59.1
63.1
67.9
Table 16: Female Labor Force Participation Rate for 2008, 2012, and 2014 for East
European and Central Asian countries. Source: World Bank statistics database
(2016).