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Immigration Patterns from Southern Europe to Germany and Switzerland in response to
expected job prospects and welfare gain: 1990-2013
Farah Hamud Khan
May 2015
Abstract: From the fall of the Soviet Union in 1990 to the financial crisis of 2008-2009, Europe has
undergone major institutional changes that have changed the economies of the member countries, as
well as their labor markets. The Eurozone and the Schengen Area, which includes Switzerland, allow
free movement of legal workers, and therefore polarities in labor markets and standards of living act
as push-pull forces for movement of labor. This paper studies immigration flows from four
Southern European Countries (Greece, Italy, Spain, and Portugal) to Germany and Switzerland from
1990-2013. The data analysis examines to what extend immigration changes according to expected
welfare gains and improved job prospects from moving to the destination countries, and the effect
of the 2008 financial crisis on labor flows is carefully scrutinized.
Farah Hamud Khan, Smith College
Email:[email protected]
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1. Introduction
The political and economic instability created by the cold war and collapse of the Soviet Union after
1989 pushed the European Union (EU) to increase integration, and extend membership to Eastern
European Countries. The formation of the Eurozone in 1990 meant that member states had to
adhere to strict economic and monetary policies (DokosThanos et al., 2013). The reunification of
Germany in 1990 and free movement of workers due to the formation of European Community
(which Spain and Portugal joined in 1992) led to a surge of guest workers from the Southern
European Countries to Western and Northern Europe (Oezcan, 2004). Switzerland, which is not a
part of the Eurozone, experienced a large influx of foreign workers due to rapid economic
development in 1980’s. Between 1991-1991, the Swiss Government altered the immigration system
so as to ease entry of workers from the member states of the European Union only (Messagerelatif à
l’initiativepopulaire, Contrel’immigration de masse, 2012).
The financial crisis of 2008-2009 had asymmetrical effects on the economies of European Countries.
While recession and unemployment levels rose to record levels for many Southern European
countries, levels in Western Europe remained stable. Examples of countries which faced record
levels of unemployment and recession were Greece, Spain, Portugal and Italy. Employment rates in
Germany and Switzerland however remained stable and their economies grew (Bräuninger, Dieter et
al., 2011). Greece for example reported an unemployment rate of 18% in 2011, and Spain an even
higher rate of 21.4% in the same year, while Germany reported a rate of 5.8 % in 2011(Source: The
World Bank DataBank).
Since Eurozone and Switzerland allows the free legal movement of labor from member states of the
European Union (EU), an asymmetric distribution of employment rates within the Schengen Area is
likely to cause labor migration from areas of low employment to areas of high employment. The
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increased labor mobility could act as an equilibrating mechanism reducing unemployment in some
areas and relieving labor shortages in other areas (Bräuninger, Dieter et al., 2011). Unemployment
rates are not the only determinants of immigration because other factors such as cost of living and
wages are also taken into account when making the decision to migrate. Higher standards of living
and higher wages provide economic incentives for migration. Labor migration often occurs because
people want to move to areas where they will be rewarded more for the same amount of work they
do in home countries. Higher wages and higher standards of living act as ‘pull factors for migration’.
Immigration occurs because immigrants want to maximize benefits and therefore while studying the
effects of wages; one must take into account the cost of living in destination countries (SUNY
Levin, Globalization 101, Pull Factors). This paper examines the effect of both unemployment rates
and wage rates (in countries of origin and destination countries) on immigration flows from
Southern Europe to Germany and Switzerland.
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2. Literature Review
The literature review shows that immigration from the Southern Europe countries to Germany has
been steadily increasing since the 1990’s and started to rapidly increase after the 2008 financial crisis.
Bertoli et al. (2013) use an econometric approach to determine that declining economic conditions
in destination countries account for 11-16 per cent of the immigration flows from Greece and
Portugal to Germany. Benjamin and Zimmerman (2013) also verify that there has been a surge in
immigration to Germany after 2009, and the immigrants who have arrived after the Eurozone crisis
are better educated and well trained. Germany is an attractive economic destination because migrant
workers in Germany do not have a hard time finding employment due to the country’s economic
stability (Kim, 2011).
A prime cause of this immigration flow is the large disparity in employment levels in Western and
Southern Europe (Jauer et al., 2014). Bräuninger, Dieter et al.(2011) also examine the effects of
difference in wage rates to explain immigration flows. The authors find that after the financial crisis,
workers from Greece and Portugal immigrate more in response to expected gain in welfare.
Switzerland has been receiving an increasing influx of high skilled and low skilled migrant workers
since the 1980’s (Gerfis, Michael and Boris Kaiser, 2013). Favre (2011) uses data from Statistik
Schweiz to explain the effect of foreign labor inflows on the Swiss wage structure. He also looks at
the history of immigration in Switzerland and how the policy changes in 1990 allowed free
movement of labor across the EU, and as a result immigration from the EU increased directly
(Favre, 2011).
3. Unemployment in Southern Europe:
4
The Eurozone is a compilation of heterogeneous economic regions in different levels of
urbanization. Western and Northern European Countries have had much lower unemployment rates
than Southern European Countries since the 1990’s.For example in 1991, Spain had an
unemployment rate of 15.5 while in Switzerland only 1.7 percent of the population remained
unemployed (The World Bank Databank).
The failure of numerous European banks and stock markets was caused by the 2008 global financial
crisis, and strained the bonds between EU member states threatening their solidarity. Southern
European Countries are much more heavily indebted that their Northern and Western counterparts
after the crisis, due to reckless borrowing at low interest rates inside the Eurozone (Lin, Carol YehYun, et a. 2012l)
Germany: Germany’s unemployment rate has fluctuated in 1990-2005. 6.4 percent of the
population was unemployed and the rate increased and decreased several times before reaching a
rate of 11.2 percent in 2005. The rate climbed down after 2005 and has been decreasing ever since.
In 2013, Germany reported an unemployment rate of 5.4 percent (The World Bank DataBank).
Switzerland:Switzerland had a record low unemployment rate of 0.80 percent in 1990 but the rate
steadily increased reaching 4.1 in 1997. The unemployment rate started falling after 1997 and fell to a
2.5 percent in 2001 before rising again. In 2007, the unemployment rate was 3.60 and it has been
increasing ever since. In 2013, Switzerland reported an unemployment rate of 4.4 percent.
Greece: The Greek economy displayed strong progress in terms of fiscal and monetary reforms in
1990’s which allowed its accession into the European Union (EU) (Lin, Carol Yeh-Yun, et al. 2012l).
For example in 1991, Greece had an unemployment rate of 7.7 percent only, the lowest in the last 25
years. Once guaranteed entry however, the economy became sluggish and the government started to
borrow heavily. For example in 1993, Greece had an annual GDP growth rate of -0.96 percent (The
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World Bank DataBank). There were no structural reforms in the economy, and unemployment
started to rise. Relief came for the labor market with the preparation of the Olympic Games in 2004,
and unemployment rates fell in 2002 and 2003. Greece did maintain an economic growth of 4.27%
in 2002-2007, although most of it was financed by borrowing. Unemployment rates declined steadily
after 2004, coming to a low at 7.8% in 2008(The World Bank DataBank).
The Greek economy remained initially more stable than other Southern European Countries when
the financial crisis hit but could not avoid a recession as global confidence, tourism and shipping
receipts fell drastically. The service sector made up 78.8% of its national output and with the fall in
demand for the service sector, unemployment rates in Greece started to climb steadily (Lin, Carol
Yeh-Yun, et a. 2012l). In 2014, Greece reported an unemployment rate of 26.5%.
Italy: Italy enjoyed dynamic economic growth in the mid 1990’s and was one of the first 11
countries to become a member of the Euro-zone. However an economic downtown started in the
late 90’s and in 2005, Italy had zero economic growth in GDP (Lin, Carol Yeh-Yun, et a. 2012l).
Unemployment rates in Italy after 1990’s have fluctuated but started to fall in and 2004 reached a
low of 6.1 percent in 2006(The World Data Bank). When the economic crisis hit in 2008, the
country suffered from even worse negative economic performance. The sector hit the hardest was
the production sector, and specifically mechanical engineering and small companies were affected
the most in terms of production, productivity and employment. Large sized companies were also
affected by the crisis and so were subcontractors and suppliers. The country reported a negative
GDP growth rate of -5%. 380,000 people were unemployed in the fiscal year of 2008-2009, resulting
in a dramatic rise in the unemployment rates. The unemployment rate climbed to 7.7% in 2009, and
has been increasing ever since. Workers with temporary job contracts were affected the most(Lin,
Carol Yeh-Yun, et al.).
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Portugal:Portugal experienced positive economic growth after joining the European Union in
1990’s. In early 90’s Portugal had relative low levels of unemployment ranging in the 5-6 percent
range. The country’s robust economic growth stopped in 2000, and the economy took a downturn
in 2001-2008. Portugal has since then been one of the worst economies in the Euro zone with lack
of government attention to competition, inflexible labor laws and rising unemployment.
Unemployment rate started to climb after 2004, and stood at 9.2 percent in 2007.
Due to the poor economic conditions preexisting before the financial crisis, the country was
theworst prepared to handle the financial crisis. GDP fell by 2.7% in 2008 to 2009 and
unemployment rose to 10.7 percent in 2009. Much like Greece, Portugal has a huge service industry
which suffered from the lack of global demand in the recession. Poor labor productivity and
insufficient wage moderation also exists in the economy and has given rise to large national account
deficits.
Spain: Of all the members of the Eurozone, Spain was the country most affected by recession. The
unemployment in Spain was much higher than the other Southern European countries when it first
joined the EU. For example in 1990 it had an unemployment rate of 15.5 percent (The World Bank
Databank). Spain’s unemployment began persistently rising through the 90’s from 15.5 percent in
1991. In 1997 the percentage of the labor force unemployed had reached and 18.4 percent. Labor
market conditions improved in early 2000 but in 2007 Spain had already gone into the
recession(even before the crisis started) and unemployment rates started rising again. In 2008, before
the crisis hit, Spain had an unemployment rate of 11.3 percent that increased to 17.9 in 2009. For the
first time in the country’s history, Spain had 4,000,000 million people unemployed and 1.2 million
jobs had been lost in 2008-2009. Unemployment benefits, which are generous in Spain, increased
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dramatically with unemployment. However, a fall in government tax revenue due to a collapse of the
real estate market, lead to a decline in the benefits for the unemployed population.
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4. Migration Flows:
The formation of the European Union and free labor movement laws with Switzerland means that
residents with legal work permit constantly move around for work. In 2004, nearly 6 percent of
Europeans were not citizens of countries in which they reside (Beets and Willekens, 2009). With
polarized labor markets in Europe after the financial crash, migration from areas of low to areas of
high employment was inevitable. In many of the Southern European countries, young workers were
affected the most. Data from 2011 Euro barometer survey indicate that 53% of Europeans aged 1535 wanted to relocated because of lack of employment opportunities in their own country. A
disproportionate amount of these 53 percent where Spaniards (68%), Irish(67%), Greeks(64%), and
Portuguese(57%). Migrant workers in these countries were also severely affected because most
migrant workers tend to work in industries such as construction, manufacturing, hotel and catering,
many of which suffered from the economic crisis (Bräuninger, Dieter et. al, 2011).
Migration to Germany: Most countries in northwestern Europe, including Germany, became
recipients of a large number of immigrants starting from the third quarter of the twentieth century.
Net migration in Germany was positive overall in 1950-2014. Between 1950 and 2010, Germany had
an average of 181000 net migrants per annum, the highest amongst all European Counties (Zincone
et al., 2011). Amongst all the Southern European Countries, Italy had the largest number of citizens
moving to Germany in the 1990’s. In 1991, 38,500 Italians and 28,429 Greeks moved to Germany.
Portugal and Spain had relatively smaller numbers standing at 11,013 and 4863 respectively. For
Greece, the flow of immigrants to Germany decreased through the 90’s and through to early 2000’s.
In 2007, only 7892 Greeks moved to Germany (The World Bank DataBank).
**Migration Data and Charts are displayed in the Data Section at the end of the paper.
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Migration increased to Germany by 40 percent from 2009 to 2011, and it was previously stable at
600,000 per year in 2006-2009. Greece, Italy and Spain were high in the list of countries with most
migrants to Germany, with Greece having 85,378 migrants, Italy 151272 migrants, and Spain 83, 358
migrants in 2009-2011(Bräuninger, Dieter et al., 2011). Despite Germany’s complicated immigration
process, migration from EU-10 countries is slowly increasing and migrants in Germany are not
affected by the economic downturn in Europe because of Germany’s low unemployment rate(Kim,
2011).
Migration to Switzerland: Policy changes in 1990 allowed free movement of labor across the EU,
and as a result immigration from the EU countries to Switzerland increased directly. Switzerland is a
particularly interesting country because it attracts poorly educated workers and highly educated
workers. But unlike that of other developed countries, where highly educated immigrants end up
competing with natives of lower education level, highly educated immigrants in Switzerland obtain
the highly paid positions and compete with natives of their education level(Favre, 2011). Compared
to Germany though, Switzerland received a smaller number of immigrants from Italy, Greece (The
World Bank DataBank). For example in 1991, only 521 Greeks, and 6658 Spaniards moved to
Switzerland. 10,825 Italians and 20,176 Portuguese citizens moved to Switzerland in 1991(The
World Bank DataBank). Total net immigration has increased in Switzerland since 1997 and all 4
Southern European Countries seem to follow that trend (Gerfin and Kaiser, 2011&The World Bank
DataBank). 24.9 percent of the Swiss population was born abroad and 20 percent do not have Swiss
citizenship. This is the highest amongst all European countries (Gerfin and Kaiser, 2011).
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Greece: Greece’s immigration to Germany has been much higher overall than immigration to
Switzerland. Net immigration to Germany decreased from 28,429 immigrants a year to 7,892
immigrants in 2007.After the 2008 financial crisis, net immigration started increasing again.
Immigration to Switzerland followed the same pattern except the rise in net immigrants came much
earlier. Net immigration started to increase around 2001 and has increased consistently since then.
Italy: Italy has had a much higher number of immigrants moving to Germany than Switzerland. The
flow of migrants to Germany steadily increased after 90’s until 1997. In 1997 39, 456 Italians moved
to Germany and this number fell to 18,624 in 2007. Net immigration to Germany has been
increased after 2007 and in 2009 22,235. Immigration to Switzerland has always fluctuated and
immigration to Switzerland actually decreased in 2008-2009 from 10,025 to 8,668.
Portugal: Portugal initially had a higher number of immigrants moving to Switzerland than
Germany. In 1990 20,176 Portuguese moved to Switzerland and 11,013 moved to Germany. Net
immigration to Germany and Switzerland both fell after 1991 but immigration to Germany
experienced a rapid increase in 1994. That is because Portugal and Spain gained full access to the
Eurozone after 1993 (Oezcan, 2004). Immigration to Switzerland decreased till the early 2000’s and
started increasing again after 2003. In 2008-2009, Portugal experienced an increase in immigration to
Germany but a decrease in Immigration to Switzerland.
Spain: Spain, like its Iberian neighbor Portugal, had more immigrants to Switzerland than Germany
in 1991 but that situation began to change. Immigration to Germany from Spain has been increasing
since 1991 whereas immigration to Switzerland decreased from 1991 till 2007 when Spain went into
recession. Immigration to both Germany and Spain increased in 2008-2009 during the Eurozone
crisis.
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5. Wage rates and immigration
For most of the Southern European Countries such as Spain and Greece, where youth
unemployment in very high, minimum wages have a small but significant adverse effect on
employment (Nickell, 1997). The literature shows the unemployment has a significant impact on
migration, and we will assume that differences in wage rates have some effect on immigration
decisions. This paper uses Gross Annual Average Wages as a measure of wage rates. In order to
measure expected welfare effects from moving to a new country, the ratio of the annual average
wages of the destination country to the annual average wages of the country of origin is analyzed
(See Methodology section). The wage rates are measured in 2013 US $ PPP, which means that the
data is comparable for all countries and living costs are taken into account.
Greece: Germany and Greece do not have wage data for 1990 and wage data for Greece starts after
from 1995. Germany/Greece wage ratio is around 1.7 in 1995 and starts to fall from that time and
keeps falling till 2007. After 2007, the ratio rises again and the rise is much sharper after the financial
crisis. In 2013 the ratio stands at 1.7, which means a resident of Germany on average has an annual
wage rate of 1.7X more than a resident of Greece. Switzerland/Greece ratio is higher overall than
Germany/Greece ration. In early 1995 the ratio is around 1.98, but starts to decline. After the euro
zone crisis, in 2007 the ratio rises again, and in 2013 the ratio stands at 2.12 which means that on
average a Swiss resident has an annual wage rate of 2.3X more than a Greek resident.
Italy: Germany/Italy wage ratio steadily increased from 1.06 to 1.22 in 2003. After 2003, the ratio
steadily decreased but the trend continued stopped the Eurozone crisis. In 2013, Germany/Italy
ratio stood at 1.26. Switzerland/Italy wage rate ratio steadily increased from 1.26 in 1990 to 1.56 in
2013.
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Portugal: Like Greece, Portugal is missing wage data until 1995. In 1995, Germany/Portugal ratio is
initially high at 1.9 and starts to decrease until it falls to 1.73 in 2010. After 2009, the ratio increases
again and in 2013 it stands at 1.84. Switzerland/Portugal ratio follows the same pattern but the ratio
is much higher usually in range of 2.
Spain: Germany/Spain ratio increased steadily from 1990 from 1.12 to 1.26 in 2006. After 2006, the
ratio started to decreasebut that started to decrease and the increasing trend picked up again in 2006.
In 2013, the Germany/Spain wage ratio was 1.25. Switzerland/Spain follows the exact same pattern
and like its fellow neighbors the ratio for Switzerland is much higher.
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6. Methodology and Data
In order to investigate the effect of the financial crisis on immigration flows from Southern to
Western Europe, I designed a regression analysis where immigration flows depend on the welfare
gain expected and the improvements in job prospect by immigration(Dieter et al., 2011).
The welfare gain expected is the ratio of Gross Average Monthly wages purchasing power parity,
PPP(2013 US $) of destination to country of origin, for example Gross Average Monthly Wage
(Switzerland):Gross Average Monthly Wage (Germany). The data is collected from OECD. The data
is an average of all wages across the country, and is subject to inequalities and this therefore is not
the most effective measure. For example, Italy may have a higher gross average monthly wage
because there are more millionaires in Italy than there are in Germany. However, workers who move
to Germany may do so as Germany has higher minimum wages for workers in the manufacturing
sector. A more effective measure of welfare gain would have been a comparison of median wages,
since it is not sensitive to inequalities.
An increase in job prospects is captured by the ratio of unemployment rate in the country of origin
to the country of destination, for example, unemployment rate (Greece)/unemployment rate
(Germany). The unemployment rates are obtained from United Nations Economic Commission for
Europe (UNEC) and The World Bank Databank, and cover the time period of 1990-2013.
It must be kept in mind that workers take time to make the decision to migrate, and as a result, we
introduce a time lag of one year into the regression equation. This means that based on the current
year’s job prospects and welfare changes, workers make their migration decision for the next year. I
use a one year time lag specifically following the method from the paper by Bräuninger, Dieter et al.
14
The data for immigration flows from country of origin to destination countries was obtained from
the United Nations Population division database and EUROSTAT (for Switzerland) and OECD.
This data captures total migration flows for example from Greece to Germany in a particular year,
and the data is captured in the time period 1990-2013. The immigration data for both countries is
obtained only from the United Nations Population Division database till 2009 but after 2009 the rest
of the data is taken from EUROSTAT. The data for 1990 immigration flows for both Germany and
Switzerland is taken from the OECD.
One might argue that instead of using total migration flows, we could have used migration flows of
workers only, since we are examining labor immigration.
With immigration flows as the dependent variable and time lagged wage ratios and unemployment
ratios as the dependent variable, the equation becomes
𝑰𝒎𝒎𝒊𝒈𝒓𝒂𝒕𝒊𝒐𝒏 𝒇𝒍𝒐𝒘𝒔 = 𝒂. 𝒘𝒂𝒈𝒆 𝒓𝒂𝒕𝒊𝒐𝒕−𝟏 + 𝒃. 𝒖𝒏𝒆𝒎𝒑𝒍𝒐𝒚𝒎𝒆𝒏𝒕 𝒓𝒂𝒕𝒊𝒐𝒕−𝟏
The immigration flows are from origin to destination. The wage ratio expresses the ratio of ages of
destination to origin, as it captures the ‘expected welfare’ and the unemployment ratio is the ratio of
unemployment rates from origin to destination countries and captures the ‘expected job prospects.
As in standard regression analysis, the magnitude, polarity and significance of a and b will explain
how much of the immigration flows from Southern to Western Europe is due to the expected
welfare gains and expected improvements in job prospects. From the literature review and the
explanations about the effects of unemployment and wage rates on immigration, we would expect a
and b be to be positive.
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7. Descriptive Statistics:
The tables below present the descriptive statistics for the variables used, immigration flows, wage
rate ratios and unemployment rate ratios.
A) Germany
Immigration
mean
Std. deviation
flows(number of
people)
Greece to Germany 17040.52
7303.921
Italy to Germany
30341.59
9716.09
Portugal to
12325.7
8793.408
Germany
Spain to Germany
9465.652
5781.916
Table 1: Descriptive Statistics for Immigration Flows to Germany
min
max
7892
18293
1182
32660
48309
32177
4863
29000
Ratio of
mean
Std. deviation
Wages(Destination/Origin)
Greece to Germany
1.530779
.148391
Italy to Germany
1.1884
.0433515
Portugal to Germany
1.836311
.0594895
Spain to Germany
1.199472
.0469672
Table 2: Descriptive Statistics for Ratio of Wages to Germany
Ratio of
mean
Std. deviation
Unemployment(Origin/Destination)
Greece to Germany
1.668192
1.353313
Italy to Germany
1.257571
.4699973
Portugal to Germany
1.190219
.7626678
Spain to Germany
2.284189
1.210647
Table 3: Descriptive Statistics for Ratio of Unemployment to Germany
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min
max
1.295956
1.06261
1.73511
1.12376
1.763617
1.26391
1.991391
1.262547
min
max
.75
.6732673
.6455696
.8214286
5.3
2.54
3.153846
5.019231
B) Switzerland
Immigration
mean
Std. deviation
min
flows(number of
people)
Greece to
540.2174
382.99
239
Switzerland
Italy to Switzerland 540.2174
382.99
239
Portugal to
11494.3
4744.69
4296
Switzerland
Spain to
2958.217
1809.505
1392
Switzerland
Table 4: Descriptive Statistics for Immigration Flows to Switzerland
Ratio of
mean
Std. deviation
Wages(Destination/Origin)
Greece to Switzerland
1.831703
.1473961
Italy to Switzerland
1.41165
.0870668
Portugal to Switzerland
2.20013
.0577564
Spain to Switzerland
1.428572
.0850374
Table 5: Descriptive Statistics for Ratio of Wages to Switzerland
1581
1581
20176
7507
min
max
1.621744
1.268697
2.107881
1.303816
2.126652
1.569283
2.323859
1.557432
Ratio of
mean
Std. deviation
Unemployment(Origin/Destination)
Greece to Switzerland
3.373475
1.36156
Italy to Switzerland
3.027414
1.864803
Portugal to Switzerland
2.495109
.9490958
Spain to Switzerland
5.208841
3.352199
Table 6: Descriptive Statistics for Ratio of Unemployment to Switzerland
17
max
min
max
2.135135
1.694445
1.694445
2.090909
6.25
11.125
6
19.375
8. Results:
1) Greece to Germany
Greece has a positive uratio coefficient for Germany which means if the ratio of unemployment rates
increases by 0.1 in favor of Germany, 643.2 Greeks will move in Germany the following year. The
P>ItI is 0.000 which means that this coefficient is significant. Similarly if wage ratio increases by 0.1
in favor of Germany, 1654.2 Greek citizens will immigrate to Germany the following year and since
the P>ItI value is 0.001, this coefficient.
The regression is split up into pre-crisis and post crisis periods. For data before 2008, the coefficient
for the uratio is 2367.80 and that for wratio is 25,085. The uratio is not significant but the wratioshows
that if wage ratio had improved by .1 in favor of Germany, 2508.5 Greeks would have immigrated.
For post-regression data uratio is positive with a value of 2271, and wratio is also positive with a value
of 51995. Although they are both insiginificant, this is expected, as there are only 5 observations.
Nonetheless, the data analysis tells us immigration from Greece to Germany is increasing and is
dependent of both prospects of better employment and welfare gain. Greek citizens are more
sensitive to expected welfare gains when it comes to making a decision to move to Germany.
Note: All regression data is displayed in the data section of the paper
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2) Italy to Germany
The coefficient for uratio for Italy to Germany 25056 and is significant which means that if ratio of
wages increase by 0.1 in favor of Germany and 2505.6 Italians will move to Germany. The
coefficient for wratio is negative but it is not significant.
The post and pre-crisis regression equations provide more concrete results than that of Greece. The
uratio coefficient for pre-crisis is 32,047 and that for post crisis is 21,848. Both are significant which
and the numbers show that after the Eurozone crisis Italians were less likely to migrate to Germany
depending on improved job prospects. The flow of migration in respect to job prospects remains
positive, but the magnitude is smaller.
3) Portugal to Germany
The coefficient for uratio of Portugal is positive but not significant. The coefficient for wratio is
11,4570 which shows than an increase in wratio by 0.1 in favor of Germany would lead to 11457
Portuguese migrating in the following year. Portugal has the higher number of residents moving in
response to improvements in welfare.
Portugal has similar missing data problems to Greece, but the post and pre-crisis regressions have
been analyzed nonetheless. Before the financial crisis, Portugal has a wratiocoefficient of 160748,
which is much higher than the wratio for the regressions for the overall time period. After the
financial crisis both the coefficients for wratio and uratio are positive but statistically insignificant. Net
immigration to Germany from Portugal is positive, and dependent on both wage ratios and
unemployment rate ratios between Germany and Portugal.
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4) Spain to Germany
Spain has a positive uratio and wratio coefficient for the overall regression equation and both
coefficients are significant. The uratio coefficient for Spain is 6452 and the variable has a mean of
2.2, which means than an increase in unemployment ratio by 0.1 in favor of Germany will lead to
645.2 Spaniards migrating the following year. The coefficient for wratio is 84206, and similarly
8420.6 Spaniards will move to Germany the next year if ratio of wages increases by 0.1 in favor of
Germany. Overall, Spaniards are responsive to both improvements in job prospects and welfare
gains in Germany but more responsive to welfare gains.
Although none of the regression coefficients for wratio are significant for post and pre-crisis data, it
is interesting to see the change in coefficients after 2007. However the uratio coefficient is 6556 after
the financial crisis and is statistically significant. It is slightly higher than the coefficient for the
overall regression equation. Before the financial crisis, uratio and wratio both have negative
coefficients and after the financial crisis both uratio and wratio are positive. It would be interesting to
examine the change in coefficients if there were more data points.
1) Greece to Switzerland
As we can see from the results, Greece has a negative coefficient for wratio which means that if
wages increase by 0.1 in favor of Switzerland, immigration to Greece will decrease by
192.1. Greece has a positive uratio overall which means that if unemployment in Greece increased
compared to Switzerland, immigration to Switzerland would actually increase. Both the coefficients
for the overall years are significant, as t<0.05. Although this does not match the methodical line of
economic thinking and results of the previous literature, separate results of regression before and
after the Eurozone crash give us very interesting results.
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Before 2008, uratio for Greece has a positive coefficient which is not significant but w ratio has a
negative coefficient which is significant. The wratio coefficient has a value of -901, which is smaller in
magnitude compared to the coefficient of the overall regression equation. However, after the
recession, u ratio has a positive coefficient of -75 and wratio has a negative coefficient of 3184. The
coefficients are not significant, but it is expected because there are not five observations. However it
would be very interesting to see what the results would yield if we could obtain quarterly or monthly
data to increase the number of observations.
2) Italy to Switzerland
The overall regression equation for Italy to Switzerland has positive coefficients for uratio and wratio
but only the coefficient for the wratio is positive. The data shows that if the ratio of wages increased
by 0.1 in favor of Switzerland, 2302 Italians would move to Switzerland. The post and pre-financial
crisis data analysis does not tell us much, since the coefficients are negative.
3) Portugal to Switzerland
Portugal to Switzerland has positive coefficients for uratios and wratios however none of the
coefficients are significant. Portugal has data problems with missing data but has a higher number of
immigrants moving to Switzerland than Germany, so it would be worthwhile to try the data analysis
with more observations.
4) Spain to Switzerland
Spain to Switzerland has both positive coefficients for uratio and wratio but only uratio is significant.
The number tells us that if unemployment ratio changes by 0.1 in favor of Switzerland, 38.7
Spaniards will migrate to Switzerland the following year.
21
Looking at pre and post crisis data, the coefficients for uratio are only statistically significant.
However the coefficient for pre-crisis data is 330 and the done for post crisis data is 1630; there is a
significant increase. This shows that Spaniards migrate to Switzerland in search of better jobs and
the tendency to migrate based on the job prospects has increased since the financial crisis
Using an immigration dependent vairable: Immigration from one year may be dependent upon
immigration from the previous year. In this case, we use an immigrant lagged time variable and test
it out for Spain and Switzerland. The results as shown in the descriptive statistics gives a uratio
coefficient which is not significant, but a wratio of 5314. The time lagged variable has a coefficient of
1.03 and is significant which means that for every spanish citizen moving to Switzerland the
previous year, a new Spanish citizen will move to Switzerland the next year. This could be due to
passing of information, or following immigration trends. We have chosen to use a time variable of
one year but it would be interesting to see how time variables of 2 or 3 years would affect out data,
and how they would affect the data before and after the crisis. Immigration from Spain to
Switzerland was used for this case since it has the maximum number of data point.
22
8. Discussion of data
All four southern European countries having positive migration flows to Germany through 19902013, and Greeks and Spaniards are sensitive to both wage rates and unemployment rates in their
home countries and Germany. Portuguese citizens are sensitive to expected improved welfare gains
and Italians to improved job prospects. Amongst all four countries, Portuguese are the most
sensitive to expected welfare gains from immigrating to Germany, and Italians are the most sensitive
to improved job prospects.
The results for Switzerland are not very clear cut. Spanish citizens are sensitive to both improved job
prospects and expected welfare gains from moving to Switzerland. Greeks also respond to both
improved job prospects and expected welfare gains, but they respond positively to job prospects and
negatively to welfare gains. Italians respond positively only to welfare gains, and the data does not
tell us anything about the Portuguese citizens’ decision to migrate based on improved job prospects
and welfare gains. Spaniards respond more than the Greeks to improved job prospects in
Switzerland, and Italians respond more to welfare gains than Spaniards.
Greek citizens respond much more to improved job prospects in Germany than they do to
Switzerland. They have opposite responses to expected welfare gains for Germany and Switzerland.
Italians show a significant response to welfare gains in Switzerland, than to welfare gains in
Germany. Portuguese citizens show high tendencies to migrate in response to expected welfare gains
in Germany, but not significant migration in response to improved job prospects or welfare gains in
Switzerland. Spaniards respond more in expected welfare gains and improved job prospects in
Germany that they do in Switzerland.
23
Our data analysis shows that immigration is generally dependent on expected welfare and job
prospects and immigration tends to increase after financial crisis because expected welfare and job
prospects increase during that time.
Improvements: The data analysis could be improved by several ways, which have already been
discussed. Greece and Portugal are missing data points, and this could be making a change to the
significance of the coefficients. The data can either be obtained through further research, including
from the countries’ individual databases. The number of observations can also be improved using
quarterly or monthly data instead of annual data.
In order to make this a fair study not subject to income inequalities, we could be using the median
wage instead of average wages. As discussed above, average wages are subject to inequalities, are not
taken into account in our regression. Median wages, on the other hand, provide a more accurate
description of the welfare effect. However one must wonder that when immigrants make a decision
to move in search of welfare, what indicators of welfare do they use? It could be wages earned by
coworkers in destination countries or it could be average wages.
Instead of looking at net migration flows, we could be using flows of workers to capture the
proportion of the population who is most likely to migrate in response to expected increase in job
prospects and improved welfare. Net migration flows include movement of residents for family
reunion purposes, for the purpose of education and reasons other than employment. People who
did not originally migrate for employment purposes might join the labor force, but using the flow of
labor would still be more accurate than using the net flow of migration.
The unemployment data I used from the World Bank is average weighted unemployment rate and
does not distinguish between long term and short term unemployment rates. If the model were to
be run with quarterly or monthly data, one would have to use short term unemployment rates
24
Conclusion:
Our results agree with the literature is that migration from the Southern European to Switzerland
and Germany has increased after the financial crisis. For some countries, my data analysis clearly
shows that effect is due to improved job prospects and expected welfare. For other cases, the data
set is too small to indicate anything. However, many of the authors, whose work I reviewed before
running our model ran into the small problem. Generally speaking, migration flows since 1990 have
not been stable and have fluctuated according to migration policies and economic conditions. In
most cases, residents of Portugal, Greece, Italy and Spain moved to Germany and Switzerland in
hope of better jobs and better wages. There are few exceptions, and the model used in this paper is
very preliminary could be improved and expanded to provide a more comprehensive idea behind the
migration flows from Southern to Western Europe.
25
Data Tables and Charts:
1. Immigration flow Data
Country
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Greece
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Migration to Germany(Number of Residents)
26500
28429
23748
18445
19021
20381
18955
16503
16036
17595
17403
16153
14957
12146
10205
8975
8289
7892
8266
8574
2010
12256
2011
23043
2012
32660
2013
32000
Migration to
Switzerland(Number
of Residents)
.
521
489
437
341
264
281
239
249
260
287
293
319
341
351
352
438
614
659
713
768
1092
1581
1536
Table 7: Immigration Data for Greece
Country
Italy
Italy
Italy
Italy
Italy
Year
Migration to Germany(Number of Residents)
1990
36900
1991
1992
1993
1994
35800
30316
31910
39100
26
Migration to
Switzerland(Number
of Residents)
883
10825
10065
8764
7953
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
48309
46249
39456
35576
34934
33235
28787
25011
21634
19550
18349
18293
18624
20087
22235
23894
28070
36896
47000
6259
4465
4314
4366
5197
4541
4683
5995
5820
5859
5622
5689
8540
10025
8668
10226
10040
12861
15942
Table 8: Immigration Data for Italy
Country
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Migration to Germany(Number of Residents)
7000
11013
10359
13061
26726
30643
32177
26619
18819
14703
11369
9287
7955
6981
5570
27
Migration to
Switzerland(Number
of Residents)
.
20176
18652
14696
12201
9651
6670
4999
4680
4464
4311
4296
8923
12228
13539
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
Portugal
2005
2006
2007
2008
2009
2010
2011
2012
2013
5010
5001
5516
5911
6779
12138
12441
15351
17657
13601
12720
11972
14388
14615
6513
8297
11820
14000
Table 9: Immigration Data for Portugal
Country
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Spain
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Migration to Germany(Number of Residents)
4400
4863
5210
5586
5855
6911
7571
7442
7497
8253
8753
8652
8460
7650
7613
7147
7093
7241
7778
8965
10657
16168
23345
29000
Table 10: Immigration Data for Spain
28
Migration to
Switzerland(Number
of Residents)
.
6658
5084
3990
3416
2567
1802
1518
1435
1392
1490
1544
1837
1819
1752
1639
1669
2139
2492
2622
3384
4354
5929
7507
Charts
The following charts trace migration flows from the 4 Southern European Countries to Germany
and Switzerland. The red line indicates the start of the financial crisis. The red line indicates the
financial crisis of 2008.
Figure 1: Migration from Greece to Germany
Figure 2: Migration from Italy to Germany
29
Figure 3: Migration from Portugal to Germany
Figure 4: Migration from Spain to Germany
30
Figure 5: Migration from Greece to Switzerland
Figure 6: Migration from Italy to Switzerland
31
Figure 7: Migration from Portugal to Switzerland
Figure 8: Migration from Spain to Switzerland
32
11. Regression Data
Greece to Germany
Coefficients
uratio
wratio
1990-2013
6432.198
(7.30)***
16542.15
(2.96)**
1990-2007
2367.86
(0.81)
25085.93
(6.75)***
2008-2013
2271.414
(0.26)
51995.26
(0.53)
1990-2013
25056.01
(5.88)***
-1737.701
(-0.05)
1990-2007
32047.11
(4.29)**
42918.59
(0.88)
2008-2013
21484.72
(0.57)
36753.12
(0.57)
1990-2013
359.0447
(0.21)
114570.1
(6.70)***
1990-2007
-5996.402
(-1.42)
160748.9
(15.66)**
2008-2013
1566.863
(0.31)
24201.31
(0.41)
1990-2013
6452.792
(9.09)***
114570.1
(6.70)***
1990-2007
-1061.867
(-1.00)
160748.9
(15.66)
2008-2013
6456.8
(10.21)*
24201.31
(0.41)
1990-2013
357.7043
(3.59)**
114570.1
(-2.48)**
1990-2007
12.59163
(0.34)
160748.9
(-4.02)**
2008-2013
-75.55179
(-0.19)
24201.31
(0.80)*
1990-2013
1990-2007
2008-2013
Italy to Germany
Coefficients
uratio
wratio
Portugal to Germany
Coefficients
uratio
wratio
Spain to Germany
Coefficients
uratio
wratio
Greece to Switzerland
Coefficients
uratio
wratio
Italy to Switzerland
Coefficients
33
uratio
wratio
713.8489
(1.91)*
23020.49
(2.60)*
401.4021
(1.38)
-1976.392
(-0.23)**
3175.577
(0.55)
48662.42
(1.17)*
1990-2013
2691.591
(1.20)*
23020.49
(1.20)
1990-2007
1476.195
(0.18)
-1976.392
(1.12)
2008-2013
777.2218
(0.63)
48662.42
(0.95)
1990-2013
387.1907
(4.08)***
7291.889
(1.81)*
1990-2007
330.0158
(5.88)***
1744.11
(0.69)
2008-2013
1693.7
(7.62)***
10358.71
(2.13)
1990-2007
-
2008-2013
-
-
-
Portugal to Switzerland
Coefficients
uratio
wratio
Spain to Switzerland
Coefficients
uratio
wratio
Spain to Switzerland with time
Coefficients
uratio
wratio
Time lagged immigration
flow(one year behind)
1990-2013
-31.63
(-0.15)
5314
(1.86)*
1.03
(6.18)***
34
References:
Beets, Gijs, and FransWillekens. "The global economic crisis and international migration: An
uncertain outlook." Vienna Yearbook of Population Research (2009): 19-37.
Bertoli, Simone, Herbert Brücker, and JesúsFernández-Huertas Moraga."The European crisis and
migration to Germany: expectations and the diversion of migration flows." (2013).
Bräuninger, Dieter, et al. "Labour mobility in the euro area." Deutsche Bank Research, Reports on
European integration EU Monitor 85 (2011).
Confé, La. "Message Relatif à L’initiative Populaire «Contre L’immigration De Masse»." 12.098
(2012): 279-332. 7 Dec. 2012.
Dokos, Thanos, et al. Eurocriticism: The Eurozone Crisis and Anti-Establishment Groups in
Southern Europe. No. 13.IAI Working Papers, 2013.
Elsner, Benjamin, and Klaus F. Zimmermann."10 years after: EU enlargement, closed borders, and
migration to Germany." (2010).
Favre, Sandro. " The impact of immigration on the wage distribution in Switzerland." Available at
SSRN 1915067 (2011).
Gerfin, Michael, and Boris Kaiser. The effects of immigration on wages: An application of the
structural skill-cell approach. No. 10-12. Discussion Papers, Department of Economics,
Universität Bern, 2010
"International Migration Database."International Migration Database.OECD, n.d. Web. 10 May
2015.
35
Jauer, Julia, et al. "Migration as an adjustment mechanism in the crisis? A comparison of Europe and
the United States." (2014).
Kim, Anna Myunghee. "Foreign labour migration and the economic crisis in the EU: ongoing and
remaining issues of the migrant workforce in Germany." (2010).
Lin, Carol Yeh-Yun, et al. National intellectual capital and the financial crisis in Greece, Italy,
Portugal, and Spain.Vol. 7.Springer Science & Business Media, 2012.
Nickell, Stephen. "Unemployment and labor market rigidities: Europe versus North America." The
Journal of Economic Perspectives (1997): 55-74.
Oezcan, Veysel. "Germany: Immigration in transition." Country Profiles, Migration Information
Source, Migration Policy Institute, Washington, DC (2004).
"OECD Migration Databases."OECD.OECD, n.d. Web. 10 May 2015.
<http://www.oecd.org/els/mig/oecdmigrationdatabases.htm>.
"Pull Factors."Globalization 101.Suny Levin Institute, n.d. Web.
http://www.globalization101.org/pull-factors/>.
"Statistical Division Website."Statistical Division Website.United Nations Economic Commission
for Europe, n.d. Web. 10 May 2015. <http://www.unece.org/stats/>.
"Your Key to European Statistics." Database.EUROSTAT, n.d. Web. 10 May 2015.
<http://ec.europa.eu/eurostat/data/database>.
"World DataBank."The World Bank DataBank.The World Bank, n.d. Web. 10 May 2015.
<http://databank.worldbank.org/data/home.aspx>.
36
Zincone, Giovanna, RinusPenninx, and MarenBorkert, eds. Migration policymaking in Europe: the
dynamics of actors and contexts in past and present. Amsterdam University Press, 2011.
37
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