Content uploaded by Sara Dungaj
Author content
All content in this area was uploaded by Sara Dungaj on Jul 30, 2022
Content may be subject to copyright.
High-Skilled Migration, Main Causes, and its Potential Long-Term Economic
Implications: Evidence from Albania
By
Sara Dungaj
Submitted to
Central European University
Department of Economics and Business
“In partial fulfilment of the requirements for the degree of Master of Arts in
Economic Policy in Global Markets”
Supervisor
Kata Orosz
Vienna, Austria
2022
2
Abstract
High-skilled workforce migration has become a dominant pattern of
international migration and a contemporary challenge for many developing economies.
Considering that outward mobility of skilled workers’ effects on migrant-sending countries is
still unexplored in the literature, studies on economic implications from an origin country
perspective are limited. Therefore, this research paper aims to explore the leading causes of
high-skilled migration in Albania and its potential economic implications for the country’s
development in the long run. Our study is based on a qualitative research method and provides
a comprehensive country-level analysis of education and labor market conditions, the role of
skills/occupational mismatch, and youth unemployment trends, which altogether add to the
outmigration of the young workforce. In the first part, the study results suggest that labor
underutilization (caused by existing occupational and skills mismatch) and low wages are the
main driving forces of high-skilled migration. Based on the migration-development theoretical
models used in this paper and the poor economic performance of Albania observed for the last
three decades, our findings suggest that the skilled labor shortages due to huge emigration flows
represent a significant loss to the Albanian labor market and can negatively affect the socio-
economic development and productivity level of the country.
Key Words: Unemployment, occupational/skills mismatch; labor underutilization, skilled
migration; human capital
3
Acknowledgments
I am honored to finalize my academic journey at Central European University and
fulfill all my obligations as a student through this research paper. I have always believed that
knowledge through education is the most powerful tool for human beings to make it safely
through life. Therefore, I want to thank Central European University and the Romani Studies
Program for generously supporting my biggest dream to study at one of the most prestigious
universities in Europe. My deepest regards go to my thesis supervisor Kata Orosz for her kind
support and guidance during my thesis writing process and for her excellence and
professionalism in teaching at CEU. Furthermore, I am more than grateful to my family, who
stands behind all my academic and personal life achievements. Finally, I want to thank my life
partner, Albi, for making these last three years at CEU unforgettable.
4
Table of Contents
Introduction ........................................................................................................................................... 7
1. Literature Review
1.1 Workforce Migration and its Potential Causes ......................................................................... 10
1.2 Review of main drivers of highly skilled workforce migration ................................................. 11
1.2.1 Role of occupational and skills mismatch ...................................................................... 12
1.3 Potential impact of workforce migration on the “home” country’s economy ............... 13
1.4 Review of successful mitigation policies across countries ............................................ 15
2. Overview of secondary data on educational, employment, and migration trends in Albania
2.1 Youth unemployment and occupational/skills mismatch in Albania ......................................... 20
2.2 Workforce migration trends in Albania and its main drivers ..................................................... 28
3. Comparative analysis on migration - development indicators in Albania and other Western
Balkan countries
3.1 Remittances, FDIs and Technology Inflows .............................................................................. 37
3.2 Return Migrants ......................................................................................................................... 40
3.3 Human Capital and Labor Market Indicators............................................................................. 41
3.4 Potential Long-term Economic Implications of High-skilled Migration in Albania ................. 42
4. Conclusion and Recommendations ................................................................................................ 47
References
5
List of Tables
Table 1. Summary of Economic Impacts of High-skilled Migration on Source Countries
Table 2. Conditions to participate in Skills Mobility Partnerships
Table 3. Main components of the Young Professionals Agreement (YPA)
Table 4. Number of graduates at each educational level, 2016-2021
Table 5. Registered jobseekers by gender, education level and age group
Table 6. Number of students enrolled in tertiary education by fields of study
Table 7. ETF Indicators of Vertical Mismatch (Provisional Data, 2021)
Table 8. Top five industries and skill losses in Albania due to net migration flows
Table 9. Main economic trends in Albania 2017-2021
List of Graphs
Graph 1. India Personal remittances, received (current US$)
Graph 2. Albania- Gross tertiary education enrollment rate in %, 1991-2020
Graph 3. Albania - Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO
estimate), 1991-2020
Graph 4. Distribution of employment by economic sector (in %)
Graph 5. Unemployment of total labor force with advanced education (in%)
Graph 6. International migrant stock at mid-year by gender, Albania 1990-2020
Graph 7. Percentage distribution of the international migrant stock by age and year, Albania 1990-
2020
Graph 8. Number of emigrants, immigrants, and net migration in Albania
Graph 9. FDI net inflows and Remittances to Albania (BoP, current $), 1992-2020
Graph 10. Current account balance, Net national savings (current $), 2002-2020
Graph 11. ICT goods imports, Commercial service imports (in %)
6
List of figures
Figure 1. Active enterprises by economic activity, 2020
Figure 2. Graduated by field of study, 2020
Figure 3. Unemployment rate by age groups, Albania 2020-2021
Figure 4. Migration of partially migrant households by level of attained education, 2019
Figure 5. Top reasons of the Albanian emigrants for selecting the destination country (in %)
Figure 6. Potential migration by economic sector and profession (in %)
Figure 7. Average years of schooling vs. GDP per capita (PPP based), 2000 to 2017
Figure 8. GDP per capita vs. Daily median income (PPP based), 2010 to 2017
Figure 9. Capital investment as % of GDP
Figure 10. Ranking in imports and exports of high technology in Western Balkans, 2021
Figure 11. Stock of Western Balkan countries’ migrants abroad
Figure 12. Labor market and human capital indicators
7
Introduction
During the last two decades, Albania has been characterized by high levels of
workforce migration. Compounded by a challenging transition into the labor market of the
tertiary level graduates, this trend is considered a severe threat to human capital accumulation
and the economic growth of the country in long term. Although high-skilled migration has
become a contemporary issue in many regions, the scholarly debate tends to treat this issue
mainly from an advanced economy perspective, highlighting the potential economic benefits
of attracting and retaining a skilled workforce. Meanwhile, long-term economic implications
for migrant-sending countries are still under-explored and therefore, receive little policy
attention from the affected countries' governments.
In this paper, we make use of international migration theories and brain drain
literature to bring a qualitative research analysis that is based on country-level findings, reports
on labor market developments, and other secondary data on youth unemployment dynamics,
occupational/skills mismatch, and migration trends. This method helped us to conduct a
comprehensive study on the potential impact that skilled migration could have in the Albanian
economy and labor market development. For instance, in the Western Balkans region, we
observe that the youth unemployment rate is twice as high as that of the working-age population
(aged 15–64), and unemployment rates for those with tertiary levels of education are
surprisingly higher than for those with lower secondary levels of education (World Bank,
2018). This means that increasing levels of educational attainment are not leading to higher
employment rates for graduates. Gallup's latest surveys on net emigration between 2011 and
2019 in Albania, reveal that about 79% of young people want to leave the country particularly
due to the challenging transition into the labor market. Meanwhile, the Vienna Institute for
International Economic Studies (wiiw) reports that in the last decade, brain drain in Albania
represented 40 percent of the migration flows, with 30 percent of them having a vocational
education level. This group of outbound migrants is mainly concentrated in Germany, Italy,
Greece, and the US. As could be expected, Albania ranked fourth globally regarding high-
skilled workforce migration rates for the last two decades (OECD, 2020).
Therefore, the aim of this research paper is to primarily investigate the factors
driving the high rates of skilled workforce migration in Albania, and then explore the economic
implications of this type of migration for the Albanian economy in long-term. The research
8
question aimed to address is: What are the long-term economic implications of high-skilled
workforce migration caused by the occupational mismatch in Albania? Our hypothesis is that
high-skilled migration in Albania is mostly caused by labor and skills shortages and low wages
– these two factors could drive the young workforce in two directions: either in career paths
different from their educational background and qualifications; or in search of better
employment opportunities abroad. The methodology used for our analysis is qualitative
research on education, labor market developments and migration trends in Albania,
incorporating empirical secondary data for the last three decades. Combined with a relevant
literature review on skills mismatch and some documentary research in this area, our
comprehensive analysis results are consonant with endogenous growth models that consider
human capital as a crucial asset in ensuring economic growth of a country. Therefore, our
findings suggest that the skilled labor shortages due to emigration represent a significant loss
to the Albanian labor market and can negatively affect the socio-economic development and
productivity level of the country.
The relevance of this study stands in the fact that it provides additional evidence to
the existing literature and also informs affected governments and policymakers on the long-
term economic implications of brain drain episodes in countries facing similar problematics.
This contribution should serve as an incentive for undertaking immediate measures with
respect to the negative consequences (such as skilled labor force shortages) that large migration
flows are generating; and creating policy instruments that would avoid (or at least mitigate) the
extent to which brain drain affects migrant-sending countries’ economy.
The paper is organized as follows. The first chapter brings an overview of the
scholarly debate regarding the potential causes of workforce migration, and high-skilled
migration in particular. This is followed by an in-depth discussion on occupational and/or skills
mismatch as a major driver of highly skilled workforce migration, and then we provide an
overview of policies that have been introduced in other countries to mitigate the long-term
negative impacts of highly skilled workforce migration. Chapter two provides secondary data
on youth unemployment, the extent of occupational and/or skills mismatch and workforce
migration trends in Albania and its main determinants. Chapter three provides a comparative
analysis on migration-development nexus through an overview of economic performance
indicators in Albania and other Western Balkans countries. Lastly, we provide a discussion on
the potential long term economic implications of skilled migration in Albania. Chapter four
9
presents main findings and the last chapter concludes with some final comments, and a set of
recommendations for Albania on mitigating this problem.
10
1. Literature Review
1.1 Workforce Migration and its Potential Causes
Workforce migration is defined as the movement of people seeking work
opportunities outside their country of birth for at least one year (UN Migration Agency, IOM).
In literature, theories on international migration have been categorized based on the factors
influencing it, such as sociological, economic, geographical, and institutional factors (Bijak,
2006); and the level of migration: micro, meso and macro level (Faist & Faist 2000; Hagen-
Zanker 2008; Hammar et al. 1997). The neo-classical economic theory of international
migration suggests that wage differentials between countries are the main driver of labor
migration. Based on this model, the migration propensity for workers moving from low-wage
countries towards high-wage countries is significantly high (Massey et al., 1993). Harris and
Todaro (1969) also pointed out that the workforce decision to migrate is highly influenced by
the availability of job opportunities abroad and expected income differentials in host countries.
Accordingly, this group of migrants would not return to their country of origin as long as they
would be benefitting from higher wages, and better career prospects in the host country
(Massey et al., 2002).
This micro-level model is challenged by the New Economics of Labor Migration
(NELM) theory, which provides a new approach to migration, by considering it not only as an
individual decision but rather as a collective decision of households (meso-level factors) to
make use of other labor resources and enhance their economic well-being; decisions that can
be highly influenced by labor market failures in their origin country as well (Massey et al.
1993; Taylor 1999). However, the Dual Labor Market Theory introduced by Michael J. Piore
(1979) suggests a controversial model to international migration, by implying that workforce
migration is mainly attributable to external economic factors, such as labor demands of
industrialized modern societies (known as pull factors in receiving-countries), rather than low
wages and high unemployment in sending-countries (known as push factors). Lastly, the
emerging empirical literature finds that apart from economic factors and income differentials,
political and institutional factors (such as corruption and poor governance) in origin countries
may also have a strong influence on the desire to migrate (Ashby 2010; Baudassé, Bazilier and
Issifou 2018; Naghsh Nejad and Young 2016).
11
Based on these theories and models, we observe that is both internal and external
economic factors that drive international labor migration and provide key insights when it
comes to understanding the root causes of this prominent and complex issue.
1.2 Review of main drivers of highly skilled workforce migration
As demonstrated above, supply-push factors in origin countries, followed by
demand-pull factors in host countries are equally important for analyzing cross-national border
movements of individuals seeking better economic opportunities. In this study, our focus is on
South-North migration (from poorer to richer countries) of the highly skilled workforce.
Although there is no pre-agreed definition of the high-skilled migrants in the academic
literature, we define the high-skilled workforce migrants, as individuals of working age who
attain some form of tertiary education and are able to cross international borders and integrate
into another nation-state’s labor market.
According to Rapoport et al. (2012) high-skilled migration has become a dominant
pattern of international migration, considering it as the major aspect of globalization. Several
theoretical analyses find that the propensity to migrate for high-skilled individuals is
substantially higher than for the low-skilled ones (Sjaastad, 1962; Borjas, 2000; Wildasin,
2000). This type of migration is mainly observed in regions with discernible socio-
demographic inequalities, such as countries having more high-skilled jobs than workers, higher
wages, inclusive migration policies, and higher economic output; features that clearly open the
path for skilled migration (Martin, 2017).
The migration hump paradox (Zelinsky 1971; Martin et al. 1996) suggests that
early-stage economic growth and development of poor countries (such as increased salaries,
free trade policies, foreign direct investments inflows) can also contribute to the increase in
outmigration rates through the increased mobility to move of the workforce. More specifically,
the increased socio-economic well-being would highly incentivize the out-migration of those
who find limited employment opportunities or career prospects in the home country. However,
as Clemens (2014) stated, this relationship between economic development and migration has
an inverted-U shape, meaning that migration propensity rises only during the early stage of
development, and falls when these countries reach the upper-middle income level. In his view,
12
a decrease in international migration can be anticipated only when the upper middle-income
status has been achieved.
1.2.1 Role of occupational and skills mismatch
The problem with limited job opportunities and unemployment of the skilled
workforce opens the debate on skills and labor market mismatch that we consider as the main
driver of the highly skilled migration in Albania. According to the International Labor
Organization (ILO), skills mismatch is a discrepancy between skills required by employers and
skills possessed by the potential workforce. However, the concept of skill mismatch is very
broad and can be used to describe vertical mismatch (over-education, under-education, over-
skilling, and under-skilling) - skill gaps, skill shortages (unfilled and hard-to-fill vacancies) -
the field of study (horizontal) mismatch - and skill obsolescence (lack of up-to-date knowledge
or skills). In this sub-section, we analyze the skills mismatch role in workforce migration at a
country level.
The empirical literature on education and occupation mismatches shows that a higher
education system failing to prepare quality graduates with relevant skills for the labor market
needs produces an under-skilled workforce (known as skill obsolescence) unable to adequately
function in the marketplace (Berlingieri & Erdsiek 2012; Farooq 2011). Consequently, this
group of workforce either remains unemployed, works in job positions that require lower levels
of formal qualifications (occupational and skills mismatch) or seeks better employment
opportunities abroad. This form of mismatch is found to be more persistent in transition
economies, whose higher education institutions still struggle with inferior quality education
(Kiersztyn, 2013).
However, a skills mismatch problem might emerge also from labor market
conditions that are unrelated to the quality of education systems. For instance, skills shortages
and difficulties to fill vacancies at a firm level could be due to low wages, poor working
conditions being offered, or ineffectiveness of the firm recruitment process (Brunello, 2021).
As regards the role of labor market conditions on workforce migration, in a study concerning
Central and Eastern Europe (CEE) countries, Kureková (2013) finds a strong relationship
between unemployment and outmigration rates in a country, arguing that unaddressed labor
13
market mismatches can potentially lead to higher out-migration rates. These results were
obtained through a regression analysis on the rate of out-migration and specific aspects of CEE
countries’ welfare systems relevant to migration decisions of workers, including the effect of
education systems and skill mismatches on young migrants, for the 2004 - 2007 period.
At large, a highly skilled and matched workforce is a prerequisite for a country’s
ability to innovate and for its healthy long-term growth (World Bank 2018). In case this
condition is not met, outmigration is the only best solution for high-skilled individuals dealing
with such labor market insecurities (Kureková, 2013). However, as Handel et al. (2016) noted,
skills development alone is not enough when it comes to ensuring economic growth. Fostering
job creation for the high-skilled is similarly crucial to ensure that the capabilities of the
country’s workforce are fully utilized.
1.3 Potential impact of skilled workforce migration on the “home” economy
The scholarly debate on international migration and brain drain is divided into 1)
conventional models, which in general represent a pessimistic view on skilled migration effects
for source countries, and 2) contemporary models that highlight the potential positive effects
of circular migration on human capital formation. The first group of international migration
models have suggested that the reallocation of the skilled workforce produces either neutral or
negative effects in terms of growth, development, and productivity for source countries (Grubel
and Scott 1966; Johnson 1967; Berry and Soligo 1969). Accordingly, when a country’s
economy is highly dependent on the number of educated people, brain drain episodes may
reduce the average productivity level of that country (Miyagiwa,1991).
Furthermore, if education of the out-migrated high-skilled was to be funded by the public
budget and not compensated through remittances or returned migrants, the source country
would experience a fiscal deficit, followed by other domestic labor market distortions such as
labor force shortages, informational imperfections, and technological externalities (Bhagwati
and Hamada 1974; McCulloch and Yellen 1977). In the long run, a continuation of brain drain
episodes implies that shortages in skilled human capital can significantly decrease the value of
average productivity in source countries (Mountford, 1997). As such, receiving remittances
with no return of skilled workers can also put origin countries’ economic growth at high risk
(Martin, 2017).
14
Meanwhile, contemporary models introduce a more balanced view on brain drain
and human capital formation, by arguing that under certain circumstances gains from high-
skilled migration can be higher than costs in origin countries (Mountford 1997; Beine et al.,
2001 and 2003; Stark 2005). This view is mainly evidence-based and focuses on various
channels such as remittances, return migration, human capital formation, and network effects
on trade, FDI flows, technology adoption, etc. For instance, according to an early study
concerning international migration to Western Europe during the 1960s and 1970s, regular
remittance flows played a significant role for the national accounts of sending countries coming
from labor migrants. These flows contributed to the provision of several development funds
such as capital resources for migrants’ family businesses and funded basic consumption needs
including healthcare and education (Castels, 2000). Other empirical studies also argue that
skilled migration can have a positive social impact through stimulating educational enrollment
levels and increasing the number of individuals seeking higher wages and better job prospects;
this, in turn, contributes to increased human capital accumulation and faster growth for
developing countries (Beine et al., 2001; Barre´ et al., 2003; Schiff, 2005; Lucas, 2005; Stark
et al., 2007). Recent evidence from the literature shows that due to the global increase in
educational attainment levels, the stock of human capital in developing countries has indeed
remained unaffected by the outmigration of skilled individuals (Rapoport, 2016).
Table 1. Summary of Economic Impacts of High-skilled Migration on Source Countries
Positive impacts
Negative impacts
Easing effect on the domestic market excess
supply of labor by reducing unemployment
Loss of skilled human capital and reduced
quality of economic output
Remittances inflow (increased incomes,
improved human development outcomes and
foreign exchange)
Reduced growth and productivity in the home
country
Technology inflows, investments, and venture
capital from diasporas
Lower return from investments in public
education and disincentives to invest locally
Potential increase in trade flows between
sending and receiving countries
Potential increase in income disparities in the
home country may induce a ‘culture’ of
migration
Induced domestic investment in education and
human capital accumulation
Loss of fiscal revenue from taxation of workers
15
Potential return of skilled workforce may
increase human capital, skills transfers, and
links to foreign network
Remittances may diminish over time and may
be potentially affected by inflationary pressures
Data Source: Migration and Development (2005), by Sriskandarajah, D. and the Institute for Public Policy
Research
At large, theories on international migration suggest that the economic implications
of high-skilled migration largely depend on the socio-economic conditions, growth, and
development trends in origin countries; making it a highly complex, multidimensional, and
network-oriented phenomenon (Massey et al., 1993; Khosravi, A. et al., 2020). Accordingly,
this type of migration could be either beneficial (by creating opportunities, sources of ideas,
knowledge and skills, communications, and networks) or detrimental (imposing various
constraints on socio-economic development due to human capital shortages). On that account,
scholars recommend moving beyond the narrow conceptualization of brain drain and focusing
more on the wide migration-development nexus (namely brain gain and circular migration) and
its positive impacts on both home and destination countries (Haas, 2005; Agbiboa, 2012).
1.4 Review of successful mitigation policies across countries
According to the IOM World Migration Report, as of 2020 the number of
international migrants was estimated to be almost 281 million globally, 60 million more than
in 2010. Approximately, two-thirds were labor migrants, from whom 73 percent were of
working age (between 20 and 64 years). This group of migrants comprised 3.6 percent of the
global population in 2020, compared to 2.8 percent in 2000 and 2.3 percent in 1980. As reported
by the 2021 Global Migration Indicators, over half of all migrant workers are concentrated in
three regions: Europe (24.2%), Northern America (22.1%), and Arab States (14.3%). Countries
that host the largest immigrant populations are the United States with immigrant population at
over 50 million, Germany with the second highest population at 15 million, and Saudi Arabia,
the third highest at over 13 million; while India, Mexico and China are ranked as countries with
the largest number of emigrants living abroad (UN DESA, 2020). As such, the top five
remittance recipient countries in 2020 were India, China, Mexico, the Philippines, and Egypt,
highlighting India as the largest recipient since 2008 and US as the largest source country for
remittances (World Bank, 2021).
16
Migration outflows affect these migrant-sending countries in various forms, mainly
through changes in labor supply availability and changes in productivity. According to Katseli
et al. (2006), the severity of migration shocks affecting income and productivity levels in
migrant-sending countries, critically depend on the skill composition of the domestic labor
force and its effective substitutability; credit market conditions; and migrants’ characteristics
(i.e., age, gender, rural, urban). Meanwhile, Lowell et al. (2001) suggest that policy responses
should focus on three channels: return, restriction, or recruitment. Apart from these three, they
also emphasize long-term responses to brain drain through resourcing policies (or diaspora
options) along with retention policies (such as building educational institutions and addressing
skills shortages in the long run).
For instance, Skills Mobility Partnerships (SMP) initiative is an integral part of the
EU Pact on Migration and Asylum with third countries encompassing government-to-
government agreements on linking migration, education, and training. These partnerships aim
to address skills needs mostly in origin countries through multinational firm global trainee
schemes, youth exchange programs, study scholarships and provision of seasonal work abroad.
For the program to be beneficial to origin countries (beyond remittances), these partnerships
are built on some pre-conditions that are summarized in the table below:
Table 2. Conditions to participate in Skills Mobility Partnerships
Origin country
Destination country
Conditions for the
programme to be
beneficial to the origin
country (beyond
remittances)
1. Training for origin and
destination countries’ needs
according to common standards
allowing for transferability of
skills
2. Training enhances
employability at origin
3. Some trainees either return or
never migrate
1. Return migration
2. Recognition of skills
acquired abroad upon
return
3. Demand for skills
acquired abroad at origin
4. Indirect transfers
(e.g.trade, technology)
Data Source: OECD Migration Policy Debates, 2018
Global Skills Partnership (GSP) is an innovative form of SMPs, that aims to combat
brain drain episodes in source countries. This form of partnership is an ex-ante agreement
17
between two governments deciding on how to share the costs and benefits of skilled migration
in a way that creates human capital in the origin country, meets the needs of the destination
country, and does not restrict workers' freedom of movement. The main feature of the GSP is
the “dual track” model, which offers a ‘home’ track for non-migrants, and an ‘away’ track for
potential migrants. Trainees who choose the ‘home’ track, after training decide to reintegrate
into the local labor market, with improved skills and higher earning potential; meanwhile those
who choose the ‘away’ track have the right to migrate safely and legally in the destination
country that financed/provided their training.
One example of a ‘dual track’ partnership (also called the Origin Training Approach)
is the agreement between the German development agency GIZ (Gesellschaft für Internationale
Zusammenarbeit) and the Kosovo government. Based on this agreement, GIZ is entitled to
create new training institutions (or work with the existing ones) in Kosovo, and the target
trainees are both potential migrants and non-migrants. In this agreement, Kosovo’s role would
be to contribute to the establishment these training institutions in the capital Pristina and
provide vocational training for two groups of individuals: those who plan to migrate and work
in Germany, and for the ones who want to (re)integrate into the local labor market. This two-
sided approach allows for creation of skills at higher standards and faster human capital
accumulation in the origin country, especially if the participating trainees decide to stay in
Kosovo. The Origin Training model is currently under development and is expected to have a
positive impact to the origin country’s capacities in terms of productivity.
A similar form of partnership is the Young Professionals Agreement (YPA),
established between Switzerland and Tunisia with the aim to address existing labor market
shortages in Switzerland and enhance the skills and employability of Tunisian youth. In close
collaboration with International Organization for Migration (IOM), this initiative offers short-
term traineeship/internship opportunities for young Tunisian professionals in Switzerland's
private sector companies and supports their job placement process after their return in Tunisia.
As such, YPA has four main components summarized in the table below:
18
Table 3. Main components of the Young Professionals Agreement (YPA)
1. Developing partnerships between Tunisian and
Swiss private sector companies, Tunisian career and
employment centers and universities and diaspora
organizations to strengthen mechanisms for search,
selection and placement of young qualified Tunisians
for the trainee positions in Swiss companies.
2. Strengthening capacities of Tunisian career
guidance centers, employment agencies and TVET
institutions to provide career orientation, training, job
search and predeparture preparation and orientation
services to young Tunisians to increase their
employability in Switzerland.
3. Diaspora participation - developing mechanisms
and forms of diaspora participation in implementation
of the Young Professional Agreement.
4. Promoting awareness and enhancing knowledge
among the Tunisian and Swiss private sector on the
benefits of skills mobility partnerships,
implementation of Young Professional Agreement
Data Source: Skills Mobility Partnership: Making Migration Work for Sustainable Development (Phase III), UN
Migration, 2021
Considering that this is also a recent agreement, the expected outcomes from an origin country
perspective would consist of reduced youth unemployment, less irregular emigration, and
higher economic development for Tunisia (UN Migration, 2021).
As observed, these partnerships can take different forms depending on the approach
that may be most effective for a given country of origin. Evidence from a non-EU country such
as India has shown that the Indian government's ongoing efforts to take advantage of well-
educated workers and capitalize on the skills and training acquired abroad have significantly
facilitated the way for migrants to send remittances or return to India and contribute to the
economy (Migration Policy Institute, 2022).
According to the World Bank database, India received USD 87 billion in remittances
through formal channels in 2021, ranking the United States as the main source (over 20 percent)
of these funds. This is a sixfold increase in remittances to India since 2001, mainly driven by
the support from the diaspora and economic recoveries in countries of destination (Migration
19
Policy Institute, 2022). Non-Resident Indians’ (NRIs) savings in India have also been an
important source for economic growth.
Data Source: World Bank Database, 2021
These funds increased significantly when the Indian government started to issue
special bonds to attract NRIs and others to invest billions of dollars in the country's economy
from 1991 to 2000. Followed by the economic liberalization in the 1990s, as the high-skilled
migration increased, remittance flows became an integral part of the Indian economy by
helping the country in generating more jobs internally, strengthening national savings,
increasing capital accumulation and investments, including business growth, technology
transfers, and tourism.
0
1E+10
2E+10
3E+10
4E+10
5E+10
6E+10
7E+10
8E+10
9E+10
1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
Graph 1. India Personal remittances, received (current US$)
20
2. Overview of secondary data on educational, employment,
and migration trends in Albania
2.1 Youth unemployment and occupational/skills mismatch in Albania
Since the early 1990s, the Albanian economy has been characterized by high
unemployment rates and challenging labor market transitions for the young high-skilled in
Albania. Despite the progressive increase in tertiary education enrollment rates throughout the
years, youth unemployment remained consistently high (see graphs below). If we look at these
trends in more detail, the gross enrollment ratio in tertiary education peaked at 60 percent in
2014 and slightly decreased in the following years. However, the upward trend in tertiary
enrollment rates, in general, did not reflect higher employment rates for the young high-skilled,
as the latter continues to fall between the 30-40 percent range (Graph 3).
Data Source: World Bank Database, 2021
Recent data provided by the World Bank database show that nearly 30.3 percent of
the young population aged 15-24 years old was reported unemployed in 2020, indicating an
increase of 3.3 percent compared to the 2019 ILO modeled estimates. Meanwhile, the number
of graduates obtaining a secondary/tertiary education level for the last two years is also lower
than the number of graduates in the 2016-17 academic year (see Table 4). The latter can be
explained by a shrinking of the university-going age cohort (as suggested by the increase in the
median age of the population from 33 to 38 years), which may be a result of low fertility rates
and large emigration flows. During the 2011-2020 period it is estimated that on average, 42
0
10
20
30
40
50
60
70
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
Graph 2. Albania- Gross tertiary education
enrollment rate in %, 1991-2020
0
10
20
30
40
50
60
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
Graph 3. Albania - Unemployment, youth total (%
of total labor force ages 15-24) (modeled ILO
estimate), 1991-2020
21
thousand people emigrated every year for better work opportunities, education, and health care
(INSTAT, 2020).
Table 4. Number of graduates at each educational level, 2016-2021
Data Source: Administrative data from Ministry of Education and Sport and the Ministry of Finance and Economy,
Albania
However, the National Employment Service estimates show that the number of registered
jobseekers obtaining a tertiary education level over the past 5 years has progressively increased
(see Table 5). A similar trend is observed for the 21-34 age cohort, while unemployment by
gender remains notably higher for female registered jobseekers.
Table 5. Registered jobseekers by gender, education level and age group
Data Source: National Employment Service, Annual average of registered jobseekers in Albania
ISCED-
2011
Academic years
2016-17
2017-18
2018-19
2019-20
2020-21
Graduated of :
1+2
Basic education
36.546
37.795
34.982
33.618
32.179
3
Upper secondary:
36.436
35.278
34.021
31.662
31.136
Professional only
4.281
4.189
3.807
4.862
3.831
5-8
Tertiary:
35.388
34.331
34.891
32.889
32.690
Bachelor only
20.423
20.108
18.696
17.585
17.650
Year
2017
2018
2019
2020
2021
Registered jobseekers by gender
Male
42.386
35.535
33.702
39.274
42.294
Female
47.394
39.151
37.228
43.647
45.125
Registered jobseekers by education level
With primary education
50.250
42.676
39.582
46.420
48.752
With secondary education
34.260
27.102
26.062
29.803
30.834
With tertiary education
5.270
4.908
5.286
6.698
7.833
Registered jobseekers by age group
16-19 years old
2.096
1.575
2.279
2.660
2.357
21-34 years old
23.148
18.650
18.594
23.527
26.136
35 years old and over
64.536
54.459
50.057
56.733
58.927
Total registered jobseekers
89.780
74.686
70.930
82.921
87.419
22
In this section, we explore the main drivers of high unemployment rates among youth
by looking at the available disaggregated data on the number of tertiary graduates by fields of
study, along with the extent to which this supply fits with the national labor market demand by
sectors of the economy.
National statistics on the distribution of employment in Albania by economic sector
(see Graph 4), show that since 2016 the service sector has had the largest number of active
employers. (43.43 percent as of 2019), followed by the agricultural sector (36.42 percent) and
industry (20.15 percent). As of 2020, the small-medium enterprises (SMEs) in the service
sector (with 50+ employees) contributed to 48.5 % of total employment in the country - with
the Municipality of Tirana having the largest number of enterprises (INSTAT, Structural
Survey of Enterprises 2020).
Data Source: Statista, 2022
As shown in Graph 4, services sector has been rising steadily due to flows in foreign direct
investments (FDIs), concentrated mainly in energy sector, construction, textile industry, trade
and services, nutritive-agriculture industry (INSTAT 2020).
0,00
5,00
10,00
15,00
20,00
25,00
30,00
35,00
40,00
45,00
50,00
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Graph 4. Distribution of employment by economic sector (in %)
Agriculture Industry Services
23
Figure 1. Active enterprises by economic activity, 2020
Source of data visualization: INSTAT Structural Survey of Enterprises 2020
According to the Structural Survey of Enterprises conducted by INSTAT in 2020 (see
Figure 1), the largest employers in the labor market offer jobs in farmer activities, trade, tourism
(accommodation, food service activities) and other services (such as government activities,
transport, finance, and communication). Considering the four sectors of the economy
1
, we see
that these economic activities of the national labor market fall mainly into the primary and
tertiary sector of the economy.
After analyzing the demand side of the national labor market, now we look at the
supply side, namely the number of students enrolled and graduated by field of study. As we
can observe from the Table 6, a considerable share of the Albanian students chooses to
1
Primary sector is the "extractive" industry, including agricultural activities, mining, forestry, grazing, hunting,
fishing, and quarrying. Secondary sector is comprised of manufacturing industries, energy, processing, and
construction jobs; while the Tertiary sector refers to the commercial services such as retail and wholesale trade,
transportation and distribution, restaurants, clerical services, media, tourism, insurance, banking, health care,
and law etc. The Quaternary sector of the economy consists of intellectual activities associated with
technological innovation, government, arts and culture, libraries, scientific research, education, and information
technology. Source: What Are Four Sectors of the Economy? (reference.com)
24
concentrate mainly on Business Administration and Law, Engineering and Communication,
and Healthcare-related fields of studies.
Table 6. Number of students enrolled in tertiary education by fields of study
According to: "Fields of Education and Training ISCED-F 2013" Manual. Note: S1, S2, S3 and S4 stand for
primary, secondary, tertiary, and quaternary sectors of the economy. Data Source: Administrative data from
Ministry of Education and Sport
For the 2019-20 academic year, there were 32,889 students graduated from tertiary education,
from whom 21,481 were female students (comprising over 65 percent of the total number of
graduate students in tertiary education). “Business, Administration and Law” had the largest
number of students with 29 percent or over a quarter of the total number of graduates, followed
by “Engineering, production and construction” and “Health and welfare”. The least preferred
field is "Agriculture, forestry, fishing and veterinary" with only 3 percent of the total number
of students enrolled (INSTAT, 2020). According to INSTAT, the decrease in the total number
of students attending higher education is more pronounced in the fields "Natural sciences,
mathematics and statistics" and "Agriculture, forestry, fishing and veterinary". On the other
hand, the number of students in the field of "Health and Welfare" increased by 5 percent.
Academic year
2017-18
2018-19
2019-20
2020-21
2021-22
Field of Study
Education (S4)
10.689
10.062
9.062
8.367
8.085
Arts and humanities (S4)
15.441
14.348
12.537
10.972
9.536
Social sciences, Journalism, and Information (S3)
12.259
14.086
11.397
10.277
9.204
Business administration and Law (S3)
30.233
33.447
32.732
31.173
32.227
Natural sciences, Mathematics and Statistics (S4)
6.325
7.060
5.962
4.924
4.553
Information and Communication Technologies (S4)
8.228
10.016
8.883
8.341
8.458
Engineering, Manufacturing, and Construction (S2)
18.730
20.019
20.775
20.537
22.555
Agriculture, Forestry, Fisheries and Veterinary (S1)
4.564
4.999
4.158
3.458
2.770
Health and Welfare (S3)
19.837
20.727
20.199
21.195
22.130
Services (S3)
3.088
4.279
4.559
4.553
4.362
Total
131.833
139.043
130.264
123.797
123.880
25
Figure 2. Graduated by field of study, 2020
Source of data visualization: Ministry of Education, Sport and Youth, INSTAT
As such, most of the Albanian students choose degrees that match jobs pertaining
mainly to the secondary and tertiary sectors of the economy (the latter is the biggest sector
offering employment). Therefore, based on the distribution of employment by sector data in
Graph 4 and data on educational attainment by field of study in Figure 2, we can conclude that
youth labor supply for the agricultural and industrial sectors is limited, implying a labor
undersupply on these sectors and an oversupply for the services sector. The latter can
potentially lead to unemployment/labor underutilization or skills mismatch for this particular
labor force.
Data Source: World Bank Database, 2020
Overall, this evidence on the number of graduates with educational backgrounds not
matching the available labor market demand might also explain the growing number of
0
5
10
15
20
25
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Graph 5. Unemployment of total labor force with
advanced education (in%)
26
registered jobseekers by education level in recent years (as seen in Table 5) and the constant
high unemployment rate for those with advanced education (see Graph 5). As illustrated in the
graph above, the unemployment of those with advanced education for the period 2007-2019
reached its highest level (19.2 percent) in 2015. In the same year, World Bank data shows that
the total youth unemployment rate reached another record high (39.8 percent) after that of 1992
(48.3 percent). As could be expected, nearly 67,000 Albanian nationals applied for economic
asylum, in 2015 (Gedeshi, 2020). As such, Albania ranked fourth among the top countries
regarding the number of asylum seekers in the EU, mainly in Germany (OECD, 2019). We
analyze migration trends in more detail in the next section. In short term, the discrepancy
between supply and demand is likely to generate either higher unemployment rates for
graduates or push them into gaining practical experience in jobs requiring different skills and
qualifications than the acquired ones.
Table 7. ETF Indicators of Vertical Mismatch (Provisional Data, 2021)
% of mismatched labor
force aged 15-24
2016
2017
2018
2019
Albania
Over-skilled - High
50.9
54.4
57.7
41.4
Over-skilled - Medium
12.0
8.6
8.2
4.5
Over-educated
17.8
19.9
20.6
13.0
Under-educated
20.8
21.2
21.4
26.9
Source: ETF, 2021a. Youth Disengagement and Skills Mismatch in the Western Balkans
Note: ETF empirical estimations are based on a modal educational level in a given occupational ISCO-08 group
in each country, using the most detailed level information available (i.e. ISCO-08 1/2/3 digit-level data), fully
harmonized with ILO recommendations.
Provisional data from the European Training Foundation (ETF) report for the Western
Balkan countries show that in 2016, half of the tertiary graduates (50.9 percent) in Albania
were employed in semi-skilled occupations, that require lower levels of formal qualifications
than the acquired ones (see Table 7). Similarly, 12 percent of upper/post-secondary graduates
have held elementary jobs. Based on these two values, we see that nearly two-thirds of the
young Albanians were mismatched in 2016. More specifically, the over-educated individuals
are those having a formal educational level that is above the average (ISCED) level required
for a certain occupation in the country. Likewise, the under-educated individuals are those who
hold jobs for which the modal value in a certain occupation in the country is typically above
27
their (ISCED) level of education. In 2019, 40 percent of graduates in Albania were labor
market-mismatched (or employed in jobs that require lower levels of formal qualifications
compared to the acquired ones). Accordingly, the report finds that such imbalances are
generated not only by the incoherent policies of education systems but also by the poor quality
and relevance of educational programs in addressing social inclusiveness goals, the absence of
career guidance and work-experience gaining programs; and lastly by ineffective labor market
matching services in the country (ETF, 2021b).
Based on this evidence, we observe a downward mismatch trend for the over-skilled
workers, and an upward trend for the under-skilled workers, which overall, might suggest an
increasing demand for higher/highly skilled workers in Albania. This disparity between supply
and demand for labor, on one hand, implies that higher education institutions in Albania are
neither building employable skills, nor maximizing students’ earnings potential and labor
market outcomes in general. On the other hand, it can also suggest a failure of the labor market
matching system and an urgent need for job creation in fields for which there is an oversupply
of labor. According to a World Bank report (2018), there is evidence of both quality problems
in education systems and weak labor market matching system between employers and the
education system. Based on the “Skills Towards Employment and Productivity Employer
Survey” (STEP Employer Survey), conducted between April and October 2017 with 600
Albanian registered firms in 2016, employers are generally satisfied with the outcomes of the
Vocational Education Training (VET) system; however, based on their assessment, young
graduates who qualify for high-skilled jobs, lack up-to-date knowledge and practical skills.
Furthermore, these SMEs ranked the inadequately educated workforce as their top third
business obstacle, due to the inability of absorbing the increasing number of graduates.
The STEP Employer survey findings suggest that employers do not partner with
educational institutions on training programs, as the Albanian SMEs and education systems are
isolated from one another. Regarding their recruitment processes, firms generally rely on
informal channels such as friends, family, and networks, due to employers’ distrust in the
quality of the education system and the value of a diploma (World Bank, 2018). The latest
country progress report by the European Commission (2021) also confirms the persistence of
skills mismatches in the country and highlights the need for adequate monitoring tools on labor
market needs and business requirements. The report also suggests that due to COVID-19-
related lockdowns and distance learning, the pre-existing skills and education gaps might have
deepened further.
28
2.2 Workforce migration trends in Albania and its main drivers
In the last three decades, Albania has been experiencing massive migration flows,
on both internal and international levels. In the historical context, these flows peaked in three
periods of time, with the first wave occurring right after the fall of the dictatorship in March
1991. During this period, more than 24,000 unauthorized Albanians left the country and landed
on Italy's shores. According to UNFPA (1997: 3), from 1990 to 1995, the number of emigrants
represented 11 % of the total Albanian population. The severe socio-economic crisis and civil
unrest that characterized the country in 1997-1998, sparked a second major outflow of migrants
towards Italy and Greece. While the third migration wave (also called the “invisible” flow)
happened during the Kosovo war crisis in 1998-1999 when a considerable number of Albanians
started to seek asylum in several EU member states (mainly in Italy, the UK, Germany, and
Belgium). This outward mobility towards a better future in other countries continues to prevail
to this day, albeit in more sophisticated forms. Followed by the 2015 surge in asylum seekers
towards Europe, emigration flows in Albania were mainly driven by extreme poverty and
unemployment – factors that encouraged more than one-third of Albania's population to leave
the country in the last three decades.
Data Source: United Nations Department of Economic and Social Affairs. International Migrant Stock 2020.
As reflected in Graph 6, as of 2020, the upward trend of these outflows since the
1990s brought the total number of Albanian emigrants to 1,250,451 with a higher prevalence
,,
200 000
400 000
600 000
800 000
1 000 000
1 200 000
1 400 000
1990
1995
2000
2005
2010
2015
2020
1990
1995
2000
2005
2010
2015
2020
1990
1995
2000
2005
2010
2015
2020
International migrant stock at mid-year both sexes combined, males and
females
Graph 6. International migrant stock at mid-year by gender, Albania
1990-2020
29
among men. According to the Albanian Diaspora in Figures (2020) publication by INSTAT,
this number could be as high as 1,684,135 individuals.
If we look at the disaggregated data on the international stock of migrants by age
and years (see Chart 7), we notice that for the years 1990-1995 (columns in blue and orange),
over 20 percent of the international migrant stock was composed of individuals from the 30-39
age group.
Data Source: United Nations Department of Economic and Social Affairs. International Migrant Stock 2020.
Starting from the 2000s onwards, the percentage of international migrant stock aged 15-39 is
notably higher compared to older age groups. In general, the percentage of international
migrant stock aged 15-34 has remained at constant levels throughout the 2000-2020 period;
while the percentage of international migrants older than 34 years old has decreased over years.
Largely, these trends suggest a higher migration prevalence among young age groups in
Albania.
0,0
10,0
20,0
30,0
40,0
50,0
60,0
70,0
15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+
% of international migrant stock
Distribution of international migrant stock by age (column) and year
Graph 7. Percentage distribution of the international migrant stock by age
and year, Albania 1990-2020
1990 1995 2000 2005 2010 2015 2020
30
As of 2022, Albania has the world’s highest migration rates, relative to its
population, respectively, -4.888 migrants per 1,000 people, a 0.18 percent increase from 2021
(INSTAT, 2022).
Data Source: INSTAT (2021)
As shown in the graph above, there is a negative net migration rate
2
, meaning that the number
of emigrants leaving the country is significantly higher than the immigrants’ inflow, especially
in the last two years. Respectively, the number of immigrants in 2021 was 9,195 and the
number of emigrants was 42,048 people – an increase in the absolute value of net migration
from -16,684 in 2020 to -32,853 inhabitants in 2021. This two-fold increase in emigration from
2020 to 2021 seems to be an outlier as the number of emigrants has been steadily decreasing
since 2011.
As noted by INSTAT in the National Household Migration (NHM) survey in 2019,
when unemployment increases and income from the informal sector drops, migration outflows
tend to surge – considering international migration as the main coping mechanism against
poverty and social exclusion in Albania. This evidence might partially explain the increase in
the net migration rate from 2020 to 2021 in terms of unemployment, as the largest national
employment contributors (namely trade and tourism services) were the most affected sectors
by the COVID-19 pandemic (European Commission Albania 2021 Report). Data from the
2
The net migration rate indicates the difference between the number of immigrants (people coming into a
country) and the number of emigrants (people leaving a country) throughout the year.
-40000
-30000
-20000
-10000
0
10000
20000
30000
40000
50000
60000
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Graph 8. Number of emigrants, immigrants and net migration in Albania
Emigrants Immigrants Net Migration
31
National Labor Force Survey, indicate that unemployment rates in Albania increased sharply
in the second quarter of 2020 and the first quarter of 2021 (12.5 percent and 12.6 percent,
respectively) compared to the last quarter of 2019 (INSTAT, 2022). The unemployment rate
during 2020-2021 was highest among the 15-24 age group (see Figure 3).
Figure 3. Unemployment rate by age groups, Albania 2020-2021
Data Source: INSTAT, Labor Force Survey
The NHM Survey (2019) observed the main migration movements of the Albanian
population who have changed their place of residence from 2011 to 2019, including a sample
of more than 20,000 households. Findings from a response rate of 79 per cent, revealed that
the “socio-demographic structure of the 2011-2019 migration population is mainly composed
of youth, unemployed, with a lower education and professional level than the general
population, in search for better prospects for themselves and particularly for their children”.
The main factor explaining this socio-demographic composition of migrants is the high
unemployment rate, underemployment, and low income from any job in the formal and
informal sectors. Almost 36 percent in this group are often long-term unemployed. The survey
also finds that “unemployment is higher for youth, and among those working 34 per cent carry
out unskilled and low-paid work in the informal sector, which generates not only emotional
stress but also uncertainties about the future. While 53 percent of members belonging to this
group have completed only the compulsory nine-year education, do not have a profession, and
carry out unqualified jobs”.
In all, the survey findings suggest that the share of low-skilled emigrants is higher
than the high-skilled ones. As illustrated in Figure 4, international migration was higher for
32
individuals with primary and secondary, while most of the tertiary-educated individuals chose
to move within the country. As of 2020, it is estimated that 40 percent of the last decade's
migration outflows from Albania were comprised of secondary and tertiary educated
individuals (WIIW, 2020).
Figure 4. Migration of partially migrant households by level of attained education, 2019
Source of data visualization: National Household Migration (NHM) survey, 2019
However, the Potential Migration Survey (2018) observes that in the last decade it
is employed with higher education and higher incomes in Albania that have a higher desire to
emigrate compared to low-skilled and lower incomes individuals. Although economic
conditions continue to be major push factors (56 percent in 2018 compared to 65 percent in
2007), the survey finds that ‘better education prospects’ and ‘no future perspectives in Albania’
are the new emerging push factors of emigration outflows. This evidence suggested a general
dissatisfaction of the respondents with the education system (the third-ranked among the push
factors), low wages, social protection, and healthcare system in Albania (see Figure 5).
33
Figure 5. Top reasons of the Albanian emigrants for selecting the destination country (in %)
Source of data vizualization: The Center for Economic and Social Studies (CESS), Potential migration survey,
2018
In all, the report highlights that high unemployment rate, underemployment, low
income from jobs in both formal and informal sectors poor living conditions, limited social
protection and debts – remain the main driving forces of workforce migration for both
unemployed/unskilled and employed/high skilled in Albania. This evidence shows that
unemployment is not the only factor encouraging thoughts of emigration, nor does employment
alone does not prevent migration. Low wages, work conditions, and little prospects for the
future are also major driving forces of workforce outmigration in Albania.
As regards to the potential migration by economic sector and profession (see Figure
6), the survey results indicate a high propensity to migrate for those working in call centers (85
percent), healthcare (83 percent), trade services (67 percent) and construction (56 percent). In
general, this evidence indicates a strong link between unemployment, underemployment
(mismatched workforce), and skilled migration.
Figure 6. Potential migration by economic sector and profession (in percent)
Source: The Center for Economic and Social Studies (CESS), Potential migration survey, 2018
34
Almost similar observations were reported by the World Bank and LinkedIn Big Data
3
(2018),
according to which, Higher Education and Information Technology and Services could be the
most affected industries by skill losses due to net migration flows in Albania (see Table 8).
Note: The net gain or net loss in skills is a normalized migration rate among LinkedIn users, computed as the net
gain or loss of members from another country with a given skill divided by the number of LinkedIn members with
that skill in the target (or selected) country, multiplied by 10,000.
Data Source: 2018. "World Bank LinkedIn Digital Data for Development" by World Bank Group & LinkedIn
Corporation, licensed under CC BY 3.0.
However, considering that these (subjective) findings do not represent official measurements
of the population at large, we integrate into our analysis, average years of schooling, GDP per
capita, and daily median income (all Purchasing Power Parity based), followed by a
comparative analysis of these indicators in destination countries of the Albanian emigrants.
This approach would allow us to illustrate more clearly the link between wage/income gaps
and skilled migration at a country level.
3
Results from a Big Data collaboration between the World Bank and LinkedIn, a social media platform focusing
on professional networking and career development with hundreds of millions of members from more than 100
countries. These data are based on self-reported (subjective) information and not on objective measurements
of skills and represent the demographics and behaviors of LinkedIn users and not the population at large.
Table 8. Top five industries and skill losses in Albania due to net migration flows
Industry
Net loss
Skill
Net loss
Tele-communications
-323
Computer Networking
-3072
Banking
-330
Web Development
-2746
Higher Education
-498
Development Tools
-2297
International Affairs
-290
Data Storage Technologies
-2194
Information Tech & Services
-339
Tele-communications
-1691
35
Figure 7. Average years of schooling vs. GDP per capita (PPP based), 2000 to 2017
In figure 7, we observe GDP per capita in current USD and average years of
schooling per country from the Barro and Lee dataset. As the plot shows, income per capita
increases after 9-10 years of schooling - except when economic downturns happen (such as the
2008 financial crisis effects in Greece and Italy). It is worth noting that despite similarities in
average years of schooling between Albania and Italy, GDP per capita (or returns on education)
in Albania has remained significantly low, probably due to the closed economy past. However,
this implies the high level of GDP per capita for individuals with less than 10 years of schooling
could be a major pull factor for low-skilled Albanians toward Greece and Italy. Meanwhile,
the top position of Germany in both indicators suggests that their returns to education could be
above the income level one could expect given the average years of schooling - a fact that
clearly explains why Albanian tertiary graduates choose Germany as their main destination
country. Historically, this outward mobility trend towards countries with higher returns on
human capital has mostly been characterized by high-skilled students and professionals seeking
better career prospects and a higher standard of living. Such was the case with the worldwide
migration of healthcare professionals to developed countries (Buchan, 2008).
36
Figure 8. GDP per capita vs. Daily median income (PPP based), 2010 to 2017
As regards the income differentials i.e. daily median income and GDP per capita in
these countries, it can be inferred that the standard of living in Germany, Italy, and Greece is
substantially higher than that of Albania (see Figure 8). We choose to compare the median
household income as its value is not affected by the income of wealthy households and provides
a more accurate estimate of the available income of the majority of households in these
countries.
To conclude, based on the evidence provided in this chapter, we find that persistently
high youth unemployment rates, low returns to education (i.e. low wages), and huge income
differentials between Albania and migrants’ destination countries are the major driving forces
of skilled emigration in the country. These driving forces incline nearly 79% of young
individuals in Albania to convey a strong desire to leave the country (Gallup’s World Poll
Survey, 2021). This survey ranked Albania in fourth place out of 152 countries in regard to
potential youth emigration rates. A similar trend is observed in all Western Balkans countries
where high-skilled outmigration has been steadily rising and is directed towards countries with
higher returns on human capital (ETF, 2021).
37
3. Comparative analysis on migration - development indicators in
Albania and other Western Balkan countries
To capture the long-term economic implications of the high-skilled migration for
Albania, we collected secondary data on main economic development trends in the country and
provide a comparative analysis on how these indicators have changed over time and varied
over the Western Balkan (WB) region. According to the Migration Observatory Collected
Publications (2019), the mass migration outflows from WB countries, especially from Bosnia
and Herzegovina and Albania have contributed to several socio-economic patterns such as
demographic decline, aging population, brain drain, and economic stagnation. In this context,
we study the outward mobility effects in long run, by analyzing secondary data on remittances,
FDIs, high technology inflows, return migrants, and other human capital development
indicators to assess the contribution of each on GDP growth, income, and impact on the
national labor market. This approach would allow us to explore more in-depth the migration-
development nexus at the country level for Albania.
3.1 Remittances, FDIs and Technology Inflows
As discussed earlier in the literature review part, emigration's impact on
development could be either positive by creating a virtuous cycle (a triple win outcome for the
origin and destination countries, and for migrants themselves) or negative by creating a vicious
cycle of human capital shortages, lower average productivity, and potential economic
stagnation for sending countries.
In order to capture the long-term economic implications of the outward mobility of
the high-skilled workforce, the first indicator that we observe is remittances inflow from
migrants residing abroad and foreign direct investments in the country for the 1992-2020
period. According to World Bank data (see Graph 9), the average value of remittances for
Albania during the 1992-2020 period was 877.03 million U.S. dollars with a minimum value
of 150 million U.S. dollars in 1992 and a maximum value of 1595.87 million U.S. dollars in
2008. Remittances have been among the most significant economic resources to help migrants’
families in Albania (Barjaba, 2021). However, since 2009 these inflows show a downward
trend and a slight increase from 2018 onwards. In 2020 remittances flow reached 1185.52
38
million U.S. dollars, representing 9.9 percent of Albania's nominal gross domestic product
(GDP).
Despite the significant share of remittances in GDP, remittances do not contribute
sufficiently to the country's economic development, as the overall investment levels in Albania
declined from 24.5% of GDP in 2015 to 22.9% of GDP in 2020 (Bank of Albania, 2021). A
similar trend can be observed in Foreign Direct Investments inflows (FDIs), which in 2013
surpassed the value of remittances, with a slight decrease in 2020. Considering that remittances
and FDI inflows enter the balance of payments, they are important indicators for overall
economic growth. As shown in the graph below, until 2006, emigrants contributed, on average,
four times more compared to foreign direct investors in the national economy. After 2010, this
situation changed in favor of FDIs as remittances from emigrants were, on average, 1.3 times
lower than FDIs (World Bank, 2021).
Data Source: World Development Indicators, 2021
This was due to the severe 2008 financial crisis, and the subsequent reduction in income and
high unemployment rates in two main host countries of Albanian migrants, namely Greece and
Italy.
However, these involuntary returnees are likely to have less development impact
compared to the return of skilled migrants due to the absence of good economic conditions -
this resulted in the failure of using return migrants’ capital for investments (Gedeshi, 2018).
As regards migrant returnees, a joint study by IOM and INSTAT in 2014, showed that only 8
percent of the Albanian surveyed returnees had invested in at least one project. The other 92
percent did not invest due to “insufficient capital/financial recourses required to start a
business, no prior plan to invest, and lack of experience and training in investment”. As such,
$-
$500.000.000
$1.000.000.000
$1.500.000.000
$2.000.000.000
Graph 9. FDI net inflows and Remittances to Albania
(BoP, current $), 1992-2020
FDI Remittances
39
nearly one-third of the Albanian returnees wanted to remigrate for better economic prospects
abroad (INSTAT and IOM, 2014).
Source of data visualization: World Bank and wiiw Report, 2020
If we make a comparison of capital investments value in Albania and other Western
Balkans (WB) countries with similar migration trends (see Figure 9), we observe that as of
2020, Montenegro and North Macedonia have the highest capital investments in the region,
followed by Serbia, Bosnia and Herzegovina and Albania.
In terms of technology imports and exports, Albania ranks 130th, and Montenegro
ranks 113th. Meanwhile, Serbia (64th), Bosnia and Herzegovina (51st), and Macedonia's (50th)
rankings are lower compared to Albania, suggesting a slow development of innovation and
technology sector in high ranked countries, and a negative impact on services, business, and
all other economic sectors (Open Data Albania, 2021).
40
Figure 10. Ranking in imports and exports of high technology in Western Balkans, 2021
Source of data visualization: Open Data Albania (ODA), 2021
3.2 Return Migrants
In general, outward mobility from WB countries is one of the highest in Europe,
with a total stock of migrants close to 4.6 million as of 2019 (UN Statistics, 2019). According
to World Bank and wiiw Report (2020), EU countries have absorbed more than 75% of
migrants from the WB region, especially Germany.
Figure 11. Stock of Western Balkan countries’ migrants abroad
Source of data visualization: UNDESA, Population Division, 2019
However, return migration to Western Balkan countries is a dynamic process, which
peaked in two periods: the first was after the end of the armed conflicts in Kosovo in 2000, and
the second inflow during the global economic crisis and the subsequent high unemployment in
destination countries, in 2009-2013 (Migration Observatory Collected Publications, 2019).
According to the INSTAT-IOM survey (2014), during this period, around 134,000 migrants
41
returned to Albania. Meanwhile, return migration in the 2016-2018 period, was characterized
by the voluntary return of asylum seekers from EU countries such as Germany, Austria, and
other countries. We are limited in providing further information on all returnees’ profiles of
Albania due to the lack of disaggregated on the socio-economic characteristics of the last
decade returnees, their skills, and previous employment in host countries. A similar limitation
stands for the number of returnees to other WB countries, and their skills level due to
administrative lack of sources on registering migrants departure/return. In this context, we
cannot establish a link between return migrants and their contribution to the country’s
economic development.
3.3 Human Capital and Labor Market Indicators
The last indicators that we observe are human capital and labor market developments
for the 2000-2020 period. For this analysis we make use of the World Bank and wiiw empirical
report (2018-2020) on the relationship between migration and the above-mentioned indicators,
by employing a system of equations that account for the effects of labor market variables and
human capital on migration and vice versa. As such, the report provides key insights on skilled
migration implications to employment, wages, human capital formation and national labor
utilization for WB countries compared to EU15. One of the main findings of the report is the
observed anomality of the high labor underutilization level despite the increasing levels of
human capital – proxied by average years of schooling (see Figure 12). Here, labor
underutilization is used as an indicator of the country’s capability to utilize its human capital
(ILO, 2013).
42
Figure 12. Labor market and human capital indicators
Another important finding of the report is the determinant role of human capital gaps
in explaining outward mobility. More specifically, gaps in human capital employability and
poor labor market conditions may act as a push factor for highly skilled workers in origin
countries, especially toward countries with higher returns on human capital. Wage gaps also
have an important impact on driving outmigration, as the sensitivity of working age population
to wage differences and working conditions in EU countries is very high. This pattern is
observed in all five Western Balkans countries, including Albania.
As regards emigration effects on national labor markets, the study suggests that there
is a positive impact of migration on narrowing the gaps in labor underutilization, and a much
stronger positive effect of migration in labor force participation. The latter is explained by the
composition of migrants, whether they come from the inactive or unemployed group of
workers. Accordingly, this finding suggests that in the Western Balkans’ countries migration
may occur more frequently among those who have a job, compared to those who are
unemployed or inactive.
43
Regarding migration impact on the WB region human capital, the report finds both
positive and negative effects of migration with respect to human capital gaps. As such,
migration happening in a country with narrow human capital gaps would lead to human capital
formation over time - highlighting that labor market conditions are more important in
explaining human capital gaps than migration itself. In other words, reducing human capital
gaps would not necessarily lead to less outmigration, as the highly educated/skilled workforce
reacts more strongly to the huge gaps in wages and working conditions between destination
countries and home country. As Mara (2019) noted, the high labor underutilization rate in all
the WB countries, coupled with low earnings and poor labor market conditions, could
discourage potential return migrants from investing home and makes better work opportunities,
higher earnings, and life prospects abroad the main pull factors of skilled migration.
3.4 Potential long-term economic impact of high-skilled migration in Albania
In this section, we provide a comprehensive discussion on the long-term economic
implications of skilled workforce migration which are based on the current economic trends of
the country and the migration – development theoretical frameworks that we have seen in the
first chapter.
Table 9. Main economic trends in Albania 2017-2020
Data Source: World Bank, 2022
As can be seen in Table 9, the Albanian economy is characterized by a large share
of the population living below the national poverty lines. Over the past 17 years, poverty
headcount ratio at national poverty lines reached a maximum value of 25.4 in 2002, and a
Indicator Name
2017
2018
2019
2020
Poverty headcount ratio at national poverty lines (%
of population)
23,4
23
21,8
..
GDP growth (annual %)
3,8
4,0
2,1
-3,9
Exports of goods and services (% of GDP)
31,5
31,5
31,3
23,1
Imports of goods and services (% of GDP)
46,6
45,2
44,9
37,8
Revenue, excluding grants (% of GDP)
25,7
25,4
25,1
..
Current account balance (% of GDP)
-7,5
-6,7
-7,9
-8,8
Share of youth not in education, employment or
training, total (% of youth population)
26,2
26,6
25,8
..
44
minimum value of 12.4 in 2008. Meanwhile the Gross Domestic Product (GDP) growth in
2020 turned to a negative value, indicating a contraction in the country’s economy, probably
due to COVID-19 economic shocks. The most important sector contributing to GDP is services
(60 percent) with banking, communications, and tourism; manufacturing industry (20 percent),
and agriculture (20 percent) which is mostly dominated by small family-owned farms and
employs nearly half of the labor force (INSTAT, 2022).
Data Source: World Development Indicators, 2021
In terms of expenditures, household consumption is the main component of GDP (78
percent), followed by gross fixed capital formation (26 percent), and government expenditure
(11 percent). As regards net exports of goods and services, they account for -18 percent of total
GDP (exports 35 percent and imports 53 percent) indicating a large trade deficit (INSTAT,
2022). Additionally, the ongoing current account balance deficit and negative net national
savings in Albania, imply large amounts of government debts to GDP, and downward trend of
national wealth (see Graph 10).
Regarding education, unemployment, and migration trends, at large, we have seen that
the number of registered jobseekers obtaining a tertiary education level over the past 5 years
has progressively increased, while the upward trend in tertiary enrolment rates did not reflect
higher employment rates for the young high-skilled. The share of youth not in education,
employment or training also remains at constant high levels, suggesting a high human capital
underutilization (based on Table 9 data). Taking into consideration the negative net migration
rates in the last two years and the strong desire to migrate among young skilled, Albanian
$-3.000.000.000
$-2.000.000.000
$-1.000.000.000
$-
$1.000.000.000
$2.000.000.000
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Graph 10. Current account balance, Net national savings
(current $), 2002-2020
Current account balance (BoP, current US$)
Adjusted savings: net national savings (current US$)
45
economy and development could be at high risks in terms of human capital accumulation and
productivity.
As regards the number and profile of return migrants, the only evidence available that
we have has shown that most returnees are low-skilled and unqualified workers who have been
denied asylum in EU countries or were left unemployed due to the severe effects of the
economic crisis on the host countries’ economies. Regarding FDIs, the last decade increase in
these flows, could represent a promising source for the long-term economic development of
Albania. Unlike remittances, these flows can contribute to higher investment levels by
foreigners and more technology transfers between countries. In terms of imports and exports
of high technology, we find that Albania still scores low compared to other countries in the
WB region. However, there is a significant increase in the value of Information and
communication technology goods imports (ICT goods) and commercial service imports, in the
last four years (see Graph 11).
Data Source: World Development Indicators, 2021
After providing the overview on the main economic performance indicators, the paper
concludes on the long-term economic implications of high-skilled migration in Albania. As the
international migration theories suggested, economic implications of high-skilled migration
largely depend on the socio-economic conditions, growth, and development trends in origin
countries. Based on our qualitative analysis and the socio-economic conditions in Albania
(such as the shrinking of the university-going age cohort, high labor underutilization and skills
gaps, outward mobility of semi-skilled and high-skilled individuals, slow development of
0
5
10
15
20
25
% of total imports
Graph 11. ICT goods imports, Commercial service imports (in
%)
ICT goods imports (% total goods imports)
Computer, communications and other services (% of commercial service imports)
46
innovation and technology sector, negative current account balance and net savings and trade
deficit) we argue that skilled migration represent a huge loss to the current development of the
country, translated into human capital shortages, loss of skilled human capital and reduced
quality of economic output, reduced growth and productivity, lower return from investments
in public education, potential increase in income disparities and loss of potential fiscal revenue
from taxation of workforce.
As such, high out-migration rates in Albania are not only a symptom of the
malfunctions in education systems and labor market matching system, but also a cause of the
slow economic growth and development. In other words, these long-term economic
implications take the form of a vicious cycle and the only beneficiaries of this phenomenon
continue to be host countries and migrants themselves. As long as the Albanian government
does not create sufficient incentives to attract remittances, encourage investments/emigrants
returns and make full use of the skilled workforce by job creation, the international migration
of the skilled workforce would result in detrimental effects on the country’s economic
development in the long run.
Therefore, based on the current economic trends, labor market indicators in the WB
region, and the above analysis of migration-development channels in Albania, we conclude
that it is difficult to see an optimistic scenario for the domestic economic growth in the
upcoming years. However, we found a significant lack of data on the country level, which
limited our study only to the available evidence. A further investigation on this topic would be
crucial to provide the full picture of migration dynamics and implications at a country level.
Based on all the data that we could get, we highlight that the main drivers of skilled emigration
in Albania are labor underutilization (including occupational and skills mismatches) and wage
differentials with EU countries. These migration drivers comprise a range of negative effects
in the form of a vicious cycle of human capital shortages, lower productivity, brain drain, and
economic stagnation. The only beneficiaries of this phenomenon continue to be host countries
and migrants.
47
4. Conclusions and Recommendations
This qualitative research paper aimed at exploring the main drivers of high-skilled
migration in Albania and the economic implication for the country’s development in long-term.
Initially we looked at the reasons behind the growing number of registered jobseekers by
education level in recent years and the constant high unemployment rate for those with
advanced education. Our findings suggest that these trends could be explained by the large
number of graduates with educational backgrounds not matching the available labor market
demand. Another important observation is that of labor market imbalances generated by the
poor quality and relevance of educational programs, absence of career guidance and work-
experience gaining programs, and lastly by ineffective labor market matching services in the
country.
Additionally, the downward mismatch trend observed for the over-skilled workers, and
an upward trend for the under-skilled workers, suggest an increasing demand for higher/highly
skilled workers in Albania. This disparity between supply and demand for labor, on one hand,
implies that higher education institutions in Albania are neither building employable skills, nor
maximizing students’ earnings potential and labor market outcomes in general. On the other
hand, it also suggested a failure of the labor market matching system and an urgent need for
job creation in fields for which there is an oversupply of labor.
Regarding the increase in the net migration rate from 2020 to 2021 in Albania, it can
be explained by the COVID-19 economic shocks and the subsequent increase in unemployment
rate. The largest national employment contributors (namely trade and tourism services) were
the most affected sectors by the COVID-19 pandemic. Similarly important are the
underemployment factor and low income from any job in the formal and informal sectors, in
terms of explaining the socio-demographic characteristics of the 2011-2019 migration
population. From these observations, we also found that in the last decade it is employed with
higher education and higher incomes in Albania that have a higher desire to emigrate compared
to low-skilled and lower incomes individuals. This evidence suggested a general dissatisfaction
of the respondents with the education system (the third-ranked among the push factors), low
wages, social protection, and healthcare system in Albania.
In general, we observe that unemployment is not the only factor encouraging thoughts
of emigration, nor does employment alone prevent migration. It is worth noting that
48
differentials in returns to human capital between Albania and EU countries, could be major
pull factors mainly for low-skilled Albanians irrespective of the average years of schooling.
Therefore, our qualitative analysis based on secondary data evidence, concludes that
persistently high youth unemployment rates, low returns to education (i.e. low wages), and
huge income differentials between Albania and migrants’ destination countries are the major
driving forces of skilled emigration in the country. This pattern is observed in all five Western
Balkans countries, including Albania.
As regards emigration effects on national labor markets, there could be a short-term
positive impact of migration on narrowing the gaps in labor underutilization, and a much
stronger positive effect of migration in labor force participation. The latter is explained by the
composition of migrants, whether they come from the inactive or unemployed group of
workers. Accordingly, this finding suggests that migration in Albania is likely to occur more
frequently among those who have a job, compared to those who are unemployed or inactive.
When it comes to emigration impact on human capital formation and accumulation,
there are both positive and negative effects. As noted by wiiw studies, if migration occurs in a
country with no significant human capital (skills) gaps, it will lead to human capital formation
over time - highlighting that labor market conditions are more important in explaining human
capital gaps than migration itself. Given that Albania is characterized by large human capital
gaps in terms of skills mismatches and labor underutilization, migration is more likely to cause
human capital loss. Therefore, reducing human capital gaps would not necessarily lead to less
outmigration, as the highly educated/skilled workforce reacts more strongly to wage gaps and
working conditions between home and destination country.
As regards other migration - development indicators, we could partially observe
remittances inflow, transfer of technology, trade flows and to a lesser extent return migration.
Overall, we find that despite the significant share of international migrants’ stock and
remittances sent to the national account over the years, international inflows do not contribute
much to the country's economic growth as most of it goes for individual consumptions. The
lack of good socio-economic conditions and insufficient financial resources are hampering the
remittances' contribution to investment levels and overall GDP. However, FDIs represent a
promising source for the long-term economic development of Albania, as these flows imply
higher investment levels by foreigners and more technology transfers between countries.
49
Based on the overall analysis of the current economic performance of the country
and potential migration-development channels in Albania, there is no optimistic scenario for
domestic economic growth in the upcoming years. The ongoing high out-migration rates and
its long-term economic implications comprise a range of negative effects that take the form of
a vicious cycle of human capital shortages, low productivity, brain drain, and economic
stagnation. The only beneficiaries of this outward mobility continue to be host countries and
migrants themselves. As long as the Albanian government does not create sufficient incentives
to attract remittances, encourage investment, create migrant return policies and make full use
of the skilled workforce within the country, the persistent migration of the skilled workforce
would result in detrimental effects on the country’s economic development. However, given
the data limitations on the country level, we suggest a further investigation on this topic as it is
crucial to provide the full picture of migration dynamics and implications at a country level.
Regarding our recommendations on preventing human capital loss and attract more
remittances inflows, we believe that the successful Skills Mobility Partnership programs
between Kosovo and Germany, could be a practical and beneficial solution to linking education
with quality training in Albania and short-term employment abroad. This would allow for better
skills and higher technology transfers to Albania, and at the same time encourage a higher labor
participation in the domestic labor market. Another form to attract more investment from
emigrants or encourage return migration is by making more financial resource available to the
potential investors with a migration background and incentivizing savings with high interest
rates. These two approaches were found to be important sources for the economic growth of
India and Kosovo.
50
References
Ashby, Nathan J. (2010), Freedom and International Migration. Southern Economic
Journal: July 2010, Vol. 77, No. 1, 49– 62. Wiley Online Library
Barjaba K. (2000) Contemporary patterns in Albanian migration, South-East Europe Review,
3(2): 57–64.
Barjaba, J. (2021). Remittances to Albania: Before and after the COVID-19 Pandemic.
Remittances Review. London, UK, 6(1), pp. 41–54. doi: 10.33182/rr.v6i1.965.
Barjaba, K., Barjaba, J. (2015), Embracing Emigration: The Migration-Development Nexus
in Albania, MPI, Migration Policy Institute
Barré, Rémi (dir.) ; et al. Diasporas scientifiques : Comment les pays en développement
peuvent-ils tirer parti de leurs chercheurs et de leurs ingénieurs expatriés ? Nouvelle édition
[en ligne]. Marseille : IRD Éditions, 2003
Baudassé, T., Bazillier, R., Issifou, I. (2017). Migration And Institutions: Exit And Voice
(From Abroad)?, Journal of Economic Surveys, 10.1111/joes.12212, 32, 3, (727-766). Wiley
Online Library
Beine M, Docquier F and Rapoport H (2003) Brain Drain and LDCs’ Growth: Winners and
Losers, IZA Discussion Paper No. 819, Bonn: Institute for the Study of Labor (IZA)
Beine, M., Docquier, F., Rapoport, H. (2001). Brain drain and economic growth: theory and
evidence. Journal of Development Economics, volume 64.
Bhagwati, JN. & Hamada, K. (1974). The brain drain, international integration of markets
for professionals and unemployment: a theoretical analysis, Journal of Development
Economics, pp 19–24.
Brunello, Giorgio & Wruuck, Patricia. (2021). Skill shortages and skill mismatch: A review
of the literature. Journal of Economic Surveys. 35. 10.1111/joes.12424.
Brzozowski, Jan, Brain Drain or Brain Gain? The New Economics of Brain Drain
Reconsidered (October 22, 2008).
Buchan, J. (2008). Migration of health workers. Cahiers de sociologie et de demographie
medicales, 48 2, 246-52.
Castles, S. (2000), International Migration at the Beginning of the Twenty-First Century:
Global Trends and Issues. International Social Science Journal, 52: 269 -281.
Cedefop (2018). Insights into skill shortages and skill mismatch: learning from Cedefop’s
European skills and jobs survey. Luxembourg: Publications Office. Cedefop reference series;
No 106.
Daniel Egiegba Agbiboa (2012): Offsetting the Development Costs? Brain drain and the role
of training and remittances, Third World Quarterly, 33:9, 1669-1683
Docquier, Frédéric, and Hillel Rapoport. (2012). "Globalization, Brain Drain, and
Development." Journal of Economic Literature, 50 (3): 681-730.DOI: 10.1257/jel.50.3.681
51
European Commission (2018), Albania 2018 Report, European
Commission, https://ec.europa.eu/neighbourhood-enlargement/sites/near/files/20180417-
albania-report.pdf
European Commission Working Document. (2021). Albania 2021 Report.
Gallup World Poll. (2011-2019). Migrants' Desire to Move Again Hinges on Where, How
They Live
Gëdeshi I., King R. (2018) Research Study on Brain Gain, Reversing Brain Drain with
Albanian Scientific Diaspora. Tirana: UNDP.
Gedeshi, I., King, R. (2020). Albanian returned asylum seekers: Reintegration or re-
emigration?
Görlich, Dennis; Stepanok, Ignat; Al-Hussami, Fares (2013): Youth unemployment in Europe
and the world: Causes, consequences and solutions, Kiel Policy Brief, No. 59, Kiel Institute
for the World Economy (IfW), Kiel
Groizard, J. and Llull, J. (2006), ‘Skilled migration and growth. Testing brain drain and
brain gain theories’, DEA Working Papers 20, University of the Balearic Islands,
Department of Applied Economics, Majorca, Spain
Grubel, H. & Scott, A. (1966). The international flow of human capital, American Economic
Review, 56(2), 1966, pp 268–274.
Haas, H.G. (2005). International migration, remittances and development: myths and
facts. Third World Quarterly, 26, 1269-1284.
ILO (2018). International Labour Organization, https://www.ilo.org/ilostat/.
INSTAT, IOM (2014) Return Migration and Reintegration in Albania. Tirana: Institute of
Statistics/International Organization for Migration.
Instituti i Statistikave, (2018). Anketa Tremujore e Forcave të Punës. INSTAT:
http://www.instat.gov.al/media/4288/atfp-t1-2018.pdf
Instituti i Statistikave, (2018). Structure of Earnings Survey. INSTAT:
http://www.instat.gov.al/media/7703/anketa-e-struktur%C3%ABs.pdf
International Organization for Migration (IOM). (2021). The 2021 Global Migration
Indicators Report.
IOM, INSTAT and CESS (2021). National Migration Household Survey
Jennissen, R. (2004). Macroeconomic determinants of international migration in Europe.
Clinical Chemistry - CLIN CHEM.
Khosravi, A. Bidkani, S. M.M., & Mir, S.A. (2020). Elite migration and its relationship to
development: Opportunities and challenges for policymakers. Education Strategies in
Medical Sciences, 12, 8-18.
King R. (2003). Across the sea and over the mountains: documenting Albanian migration,
Scottish Geographical Journal, 119(3): 283–309.
52
King R. (2018) Is migration a form of development aid given by poor to rich countries?
Journal of Intercultural Studies, 39(2): 114–128.
King R., Vullnetari J. (2009) Remittances, return, diaspora: framing the debate in the context
of Albania and Kosovo, Southeast European and Black Sea Studies, 9(4): 385–406. 35.
Kureková, L. (2013). Welfare Systems as Emigration Factor: Evidence from the New
Accession States. JCMS: Journal of Common Market Studies, 51(4), 721-739. IMI Working
Papers, 2011
Kurekova, M. Lucia. (2011). The Effects of Structural Factors in Origin Countries on
Migration: The Case of Central and Eastern Europe. IMI Working Papers, September 2011,
Landesmann, M. and S. Leitner (2015), ‘Intra-EU Mobility and Push and Pull Factors in EU
Labor Markets: Estimating a Panel VAR Model’, wiiw Working Paper No. 120.
Lee, Jong-Wha and Hanol Lee. (2016). Human Capital in the Long Run. Journal of
Development Economics, vol. 122, pp. 147-169.
Barro, R., Jong-Wha L. (2013). A New Data Set of Educational Attainment in the World,
1950-2010. Journal of Development Economics, vol 104, pp.184-198.
United Nations Development Programme. (2018). Human Development Report (2018
Statistical Update).
Leitner M., Sandra. (2021). A Skill-specific Dynamic Labor Supply and Labor Demand
Framework: A Scenario Analysis for the Western Balkan Countries to 2030. Commissioned
by European Training Foundation, The Vienna Institute for International Economic Studies
Louka T. Katseli, Robert E.B. Lucas and Theodora Xenogiani. (2006) Effects Of Migration
On Sending Countries: What Do We Know? OECD Development Centre Working Paper No.
250.
Lowell, Briant Lindsay & Findlay, Allan. (2001). Migration of highly skilled persons from
developing countries: impact and policy responses. International Migration Papers. 44.
Lucas, R E B (2005) International Migration Regimes and Economic Development, Study
commissioned by the Expert Group on Development Issues (EGDI), Swedish Ministry for
Foreign Affairs and Edward Elgar
Maghnouj, S., et al. (2020), OECD Reviews of Evaluation and Assessment in Education:
Albania, OECD Reviews of Evaluation and Assessment in Education, OECD Publishing,
Paris.
Mara, I., and Landesmann M. (2021). Interrelationships between Human Capital, Migration
and Labor Markets in the Western Balkans: An Econometric Investigation. Commissioned by
European Training Foundation, The Vienna Institute for International Economic Studies
Maryam Naghsh Nejad, Andrew T. Young. (2016). Want freedom, will travel: Emigrant self-
selection according to institutional quality, European Journal of Political Economy,
10.1016/j.ejpoleco.2016.06.002, 45, (71-84),
53
Massey D, Durand J, Malone N. Douglas S. (2002). Beyond Smoke and Mirrors: Mexican
Immigration in an Era of Economic Integration (New York: Russell Sage Foundation, 2002).
Pp. 199. ISBN 0 87154 589 6. Journal of American Studies, 37(1), 135-177.
Massey, D. S., Arango, J., Hugo, G., Kouaouci, A., Pellegrino, A., & Taylor, J. E. (1993).
Theories of International Migration: A Review and Appraisal. Population and Development
Review, 19(3), 431–466.
Michael A. Clemens. (2014). "Does development reduce migration?" Chapters, in: Robert
E.B. Lucas (ed.), International Handbook on Migration and Economic Development, chapter
6, pages 152-185, Edward Elgar Publishing.
Mountford,A. (1998). ‘Can a brain drain be good for growth in the source economy?’,
Journal of Development Economics, 53(2), 1997, pp 287–303; and JP Vidal, ‘The effect of
emigration on human capital formation’, Journal of Population Economics, 11(4), 1998, pp
589–600.
Muharremi, O., Madani, F., Pelari, E. (2013). The Development of the Service Sector in
Albania and Its Future. Mediterranean Journal of Social Sciences.
OECD (2019) International Migration Outlook 2019. Paris: OECD Publishing
OECD (2022), Employee compensation by activity (indicator). doi:10.1787/7af78603-en
(Accessed on 03 June 2022)
Our World in Data. (2022) Average median income vs. GDP per capita, 2017. International
Comparison Program - World Bank, World Development Indicators - World Bank, Eurostat-
OECD PPP Programme
Our World in Data. (2022) Average years of schooling vs. GDP per capita, 2017.
International Comparison Program - World Bank, World Development Indicators - World
Bank, Eurostat-OECD PPP Programme
Parkins, N. C. (2010). Push and pull factors of migration. American Review of Political
Economy, 8(2), 6.
Philip M. (2017). Merchants of Labor: Recruiters and International Labor Migration. Print
ISBN-13: 9780198808022. Published to Oxford Scholarship Online: August 2017.
Pulaha, K., Mustafaraj, A., Osmanaj, E., Hazizaj, A. (2020). Raporti Kombëtar Rinia në
Shqipëri 2020, CRCA/ECPAT Albania, 2020.
Regional Cooperation Council (RCC). (2021). Labour Markets in The Western Balkans
Ruchi S. (2022). Origin of World’s Largest Migrant Population, India Seeks to Leverage
Immigration (Washington, DC: Migration Policy Institute, March 9, 2022).
Sela, E. (2016). Problems of Youth Employment in Albania. International Journal of
Humanities and Social Science Invention ISSN (Online): 2319 – 7722, ISSN (Print): 2319 –
7714 www.ijhssi.org ||Volume 5 Issue 8. PP.04-0
Sriskandarajah, D. (2005). Migration and Development. [A Paper Prepared for the Policy
Analysis and Research Programme of the Global Commission on International
Migration.]. Grand-Saconnex: Global Commission on International Migration.
54
Stark, O. and Fan, C. S. (2007), Losses and Gains to Developing Countries from the
Migration of Educated Workers: An Overview of Recent Research, and New Reflections.
Discussion Paper 7121, University of Bonn, Centre for Development Research (ZEF).
Thaut, L. (2009), EU Integration & Emigration Consequences: The Case of Lithuania.
International Migration, 47: 191-233.
Todaro, M. Paul. (1969). A model of labor migration and urban unemployment in less
developed countries. The American Economic Review, vol. 59, pp. 138-148.
UNECE Statistical Database, compiled from national and international official
sources(OECD, EUROSTAT, CIS).
United Nations Department of Economic and Social Affairs, Population Division (2020).
International Migration 2020 Highlights (ST/ESA/SER.A/452).
United Nations Department of Economic and Social Affairs, Population Division (2020).
International Migrant Stock 2020. Copyright © 2020 by United Nations, made available
under a Creative Commons license CC BY 3.0
Vienna Institute for International Economic Studies (wiiw). (2020). Wage Developments in
the Western Balkans, Moldova and Ukraine
Weinar, A., Klekowski von Koppenfels, A. (2020). Highly Skilled Migration: Concept and
Definitions. In: Highly-Skilled Migration: Between Settlement and Mobility. IMISCOE
Research Series. Springer, Cham.
Wolfgang E., Krieger, T. Volker M. (2010). Education, unemployment and migration,
Journal of Public Economics, Volume 94, Issues 5–6, 2010, Pages 354-362, ISSN 0047-2727
World Bank and Vienna Institute for International Economic Studies (wiiw). (2020). Western
Balkans Labor Market Trends 2020
World Bank, (2018). Western Balkans Demand for Skills in Albania. An analysis of the Skills
Towards Employment and Productivity Survey
World Bank. (2021). Resilience Covid-19 Crisis through a Migration Lens. Migration and
Development Brief 34. May 2021
Zelinsky, W. (1971). The Hypothesis of the Mobility Transition. Geographical Review, vol.
61, No. 2, pp. 219–249.
