Preliminary version: Please do not quoteVersion 2.08
Migration between the Nordic countries
- A Knowledge flow perspective
By
Ebbe K. Graversen*)
*) The Danish Institute for Studies in Research and Research PolicyFinlandsgade 4DK – 8200 Aarhus N.Denmark
October 2000
Preliminary version to be presented at the 3rd ordinary meeting in the Nordic Group for Mobility Studies inÅrhus, 9-11th November 2000
Acknowledgements: Financial support from the Nordic Industrial Fund as well as the Danish Institute forStudies in Research and Research Policy are gratefully acknowledged. Mette Lemming has performedvaluable research assistance in the project.
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1. Introduction
Mobility of persons across national borders have for long been a high priority research area. A long
discussion of the net value of migration has dominated the agenda. Theoretically, there is no clear
conclusion on the optimal migration. However, several studies have tried empirically to validate or
calculate the effects. The aim of this study is to amend to the latter part and increase the
knowledge of the people migrating between the Nordic countries. Through a comparison of the
register data available in all the countries a more detailed picture can be drawn of the migration.
Hence, an account of the brain drain, brain gain and brain circulation can be fulfilled.
Usually, register data can give a full and detailed description of the emigrants with a national
citizenship when they leave the country. However, the emigrants with other citizenships have
usually not a full track in the registers if they for example immigrated to the country only a few
years earlier. In such a case, the registers would only contain information on these few years and
not items as for example educational levels, skills, and work careers previous to the immigration. In
general the registers will not contain this information for immigrants. However, for national citizens
returning to the country, the information at the emigration time is available. This information might
be outdated but this is not possible to detect in the registers. A use of register data from all the
Nordic countries can give aggregated answers to the non-available information mentioned above.
The registers can give information on the persons that leaves the country and what they have been
doing when present in the registers. Combining the information from the register data in two
countries, information on the knowledge stock and previous career for immigrants from the other
country as well as the added knowledge stock and career track for the persons returning or
emigrating to the other country. Especially, the combination of information from register data in two
countries can determine the added knowledge obtained by returning persons, i.e. the brain gain of
return migration and the increase in the knowledge stock obtained from brain circulation.
2. Definition of migration in the Nordic countries
The Nordic countries have different rules for registration of migration. Basically, a movement from
one country to another is required. However, the period of intended stay in another country before
a migration is recorded in the statistical registers differs between the countries, see Table 1.
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Table 1: Definitions of de facto stay before migration count in the Nordic counties. Nationalrules and the UN recommendation
Country Time of intended stay before registration as migrant
Denmark 3 month until 1991, 6 month after 1991
Norway 6 month
Sweden 12 month
Finland 12 month
Iceland 12 month
UN recommendation 12 monthNote: Since 1991, the intended stay has to be at least 6 months before migration between the Nordic (and only these)countries counts in the national migration registers, cf. Grundström (1993).Source: Grundström (1993).
These differences in the definition of migration will result in a relatively higher numbers of
migrations in Denmark and Norway compared to the other Nordic countries. However, Grundström
(1993) suggests adjusting the migration figures to individuals who actually stays more than 12
months in the “new” country. Using register data from 1989, he makes the migration figures
comparable between the Nordic countries and finds that the Danish figures overestimate the 12-
month figures for migration by approximately 40%. The similar bias is close to 10% for the other
Nordic countries. Looking at the net migration, the Danish net migration is 30% to high, the
Norwegian 60% to high, the Finnish 15% to high and the Swedish 7% to high.
In order to secure comparable statistics on migration, the migration measure need to be defined as
a 12 month of de facto stay in the country. No matter whether the period of interest covers time
before and after 1991, 12 month of de facto stay is the best statistical measure to use1. The same
measure can also be used for migration statistics between the Nordic countries and the rest of the
world in order to extend the present analysis with comparable studies. The fact that the register
data in the Nordic countries are annually also supports the use of a 12-month rule. Similarly, most
countries report migration figures annually. Hence, all figures based on register data and reported
in the present analyses are based on year-to-year comparisons. Migration requires that the person
leaves or comes into the population from one year to the next.
1 Grundström (1993) refers, that the UN recommends the following definitions of immigration: Long-term immigrants:more than 12 months. Short-term immigrants: less or equal 12 months.
Immigration: A person entering a country is immigrating to the receiving country, i.e. theimmigration country.Emigration: A person leaving a country is emigrating from the delivering country, i.e. theemigration country.
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3. Aggregated migration figures from Nordic Statistical Yearbook
The total number of persons moving between the Nordic countries is given in the Nordic Statistical
Yearbook. Table 2 gives the figures for selected years in the 1990s. A large fraction of the persons
moving comes back a few years later, i.e. return migration, cf. Pedersen (1996).
Table 2: Registered number of migrants between the Nordic countries over time. Percentshare of total country specific migration in parentheses
Immigration yearReceivingcountry 1990 1992 1993 1995 1996 1997 1998
Denmark12182(30)
10441(24)
10658(25)
12245(19)
12041(22)
11504(23)
11351(22)
Greenland2398(96)
.(.)
2047(95)
2182(96)
2378(96)
2518(96)
2349(96)
Finland6571(48)
3723(26)
3300(22)
3895(32)
4286(32)
4041(30)
4523(32)
Iceland1958(61)
1893(63)
1680(62)
1769(61)
2261(61)
2396(60)
2616(57)
Norway8028(31)
7497(28)
7713(24)
7850(31)
8635(33)
11774(37)
.(.)
Sweden18094(30)
7998(18)
7150(12)
8760(19)
8082(20)
8113(18)
9854(20)
All Nordiccountries
51221(35)
31552(24)
34541(22)
38696(25)
39679(28)
42343(29)
32691(27)
Emigration yearDeliveringcountry 1990 1992 1993 1995 1996 1997 1998
Denmark10287(32)
7900(25)
7613(24)
9122(26)
9735(26)
9707(25)
10808(27)
Greenland3687(99)
.(.)
2585(99)
2663(99)
2853(99)
2943(99)
2907(99)
Finland4464(69)
3491(58)
3424(54)
4041(45)
4010(38)
4575(47)
5150(48)
Iceland2688(70)
1621(51)
1808(62)
3185(74)
3079(75)
2731(70)
2637(72)
Norway11221(47)
5394(32)
4876(26)
6362(33)
6210(30)
675032)
.(.)
Sweden15255(61)
11738(46)
10975(37)
11020(32)
12074(36)
13965(36)
14242(37)
All Nordiccountries
49592(52)
30144(36)
33274(36)
38388(37)
39957(37)
42668(37)
37742(39)
Note: Includes all persons moving independent of age.Source: Nordic Statistical Yearbook, 1999.
The difference between the total number of immigrants and emigrant between the Nordic countries
in Table 2 also shows that some of the persons are missing either in the immigration account or in
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the emigration account. Theoretically, the total should be equal but in practice difference up to
1,500 persons per year is found in Table 2. There also seems to be some correlation between the
migration numbers and the national business cycle measured by for example the unemployment
rate.
The citizenship of the immigrants and emigrants are interesting. Nordic Statistical Yearbook 1999
shows that more than 50% of all emigrants have national citizenships. When and whether they
return and what they do when they are abroad is the key element in the present analyses. Nordic
Statistical Yearbook 1999 illustrates the distribution of the immigrants and emigrants by country for
1998. The figures are referred in Table 3.
Table 3: Immigration and emigration between the Nordic countries by country in 1998(Column percent in parentheses)
Immigration country (measured by receiving country)Deliveringcountry Denmark Greenland Finland Iceland Norway Sweden
Denmark4272(38)
2183(93)
342(8)
1418(54)
2782(24)
1927(20)
Finland416(4)
4(0)
.(.)
58(2)
1012(9)
3288(33)
Iceland1241(11)
89(4)
50(1)
.(.
782(7)
346(4)
Norway2852(25)
45(2)
613(14)
554(21)
.(.)
4293(44)
Sweden2570(23)
28(1)
3518(78)
586(22)
7198(61)
.(.)
All Nordiccountries
11351(100)
2349(100)
4523(100)
2616(100)
11774(100)
9854(100)
Emigration country (measured by delivering country)Receivingcountry Denmark Greenland Finland Iceland Norway Sweden
Denmark3907(36)
2813(97)
395(8)
1301(49)
2932(43)
2445(17)
Finland377(3)
31(1)
.(.)
57(2)
353(5)
3472(24)
Iceland1359(13)
60(2)
53(1)
.(.)
408(6)
560(4)
Norway3117(29)
18(1)
1366(27)
927(35)
.(.)
7765(55)
Sweden2048(19)
13(0)
3336(65)
352(13)
3057(45)
.(.)
All Nordiccountries
10808(100)
2907(100)
5150(100)
2637(100)
6750(100)
14242(100)
Note: Includes all persons moving independent of age. Norway: 1997.Source: Nordic Statistical Yearbook, 1999
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The share of Danes immigrating from Denmark to Denmark and emigrating similarly, illustrates the
differences in definitions of migration, e.g. Table 1. However, the figures also illustrates that the
major mobility across borders are either historically determined, Iceland and Greenland versus
Denmark, or caused by short distances, i.e. neighbour country in combination with business cycle
variations, i.e. Finland versus Sweden and Norway versus Sweden.
4. Detailed migration figures from national register data – Do the stocks and
flows match across borders?
A first item to analyse is whether the stock of migration matches between the countries when the
registers are used for the Nordic countries. Such a quality check validates the results presented
later in the paper. Table 4 shows the figures for the Nordic countries. First, the stock is persons
aged 20 to 70 years old. Second, only year-to-year movements counts, i.e. the definition
recommended by UN is used. Hence, the figures do not and are not intended to equal the absolute
figures found in Tables 2 and 3 although the distributions in percent is expected to be similar.
Overall, the figures are similar in size although they do not match exactly. Similarly, the figures do
not reveal whether the persons summing to the totals are the same persons on each side. Hence,
the actual figures might be larger than the numbers revealed although they need to be fairly
precise since there only are few people missing, i.e. disappearing, in the registers.
Table 4: Register based migration figures for the Nordic countries. Emigration andimmigration between the Nordic countries in 1995
Measured by delivering country (emigration)Measured byreceivingcountry(immigration)
Denmark Finland Iceland Norway SwedenAll Nordiccountries
Denmark . �. 229 �229 1042 � 1877 � 1730 � 4878 �
Finland 250 �182 . �. 17 � 250 � 2168 � 2685 �
Iceland �473 �24 . �.
Norway �1370 �370 . �.
Sweden �1415 �2087 . �.
All Nordiccountries �3440 �2710 �
Note: Only 12 month of registered stay counts in the table. Figures for other years are given in Appendix 2.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
Whether the net migration is positive or negative is difficult to determine from Table 4. However,
there are such high an agreement in the figures that it can be determined with some care. A more
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serious problem is the difference between immigration and emigration figures that theoretically
should measure the same individuals. Hence, exact numbers may be somewhat misleading.
Looking instead at the broader lines in the figures, the migration numbers do lie close to each
other. So, with some caution, the highest number of the two must describe reality best since the
probability for to few registrations considerably exceeds the probability for to many registrations.
However, both migration measures are conservative in the sense that they are probably both
measuring to few movement compared to reality. Some persons move without registering their
move even though it is mandatory according to the national laws. Only in the cases where the
individuals are employed or in connection with the social and educational systems abroad, they
need affirmative registration.
Changes when EU membership, economic crises etc (business cycle and shock correlations)
Where does register information on migrants fail? Does it matter?
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Table 5: Nordic immigration by educational level and citizenship in the Nordic countries in1995
CitizenshipReceiving countryand educationallevel Denmark Finland Iceland Norway Sweden Other
Denmark PhD Master Bachelor Other tertiary ISCED 3+4 MissingFinland PhD Master Bachelor Other tertiary ISCED 3+4 MissingIceland PhD Master Bachelor Other tertiary ISCED 3+4 MissingNorway PhD Master Bachelor Other tertiary ISCED 3+4 MissingSweden PhD Master Bachelor Other tertiary ISCED 3+4 MissingAll Nordic countries PhD Master Bachelor Other tertiary ISCED 3+4 MissingNote: Figures for other years are given in Appendix 2.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
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Table 6: Nordic emigration by educational level and citizenship in the Nordic countries in1995
CitizenshipDelivering countryand educationallevel Denmark Finland Iceland Norway Sweden Other
Denmark PhD Master Bachelor Other tertiary ISCED 3+4 MissingFinland PhD Master Bachelor Other tertiary ISCED 3+4 MissingIceland PhD Master Bachelor Other tertiary ISCED 3+4 MissingNorway PhD Master Bachelor Other tertiary ISCED 3+4 MissingSweden PhD Master Bachelor Other tertiary ISCED 3+4 MissingAll Nordic countries PhD Master Bachelor Other tertiary ISCED 3+4 MissingNote: Figures for other years are given in Appendix 2.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
Migration by nationality for the Nordic countries
Brain drain/gain?
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Return migration shares, who returns and with which skills?
Table 7: Nordic immigration by age and citizenship in the Nordic countries in 1995
CitizenshipReceiving countryand age Denmark Finland Iceland Norway Sweden Other
Denmark 20-24 25-29 30-34 35-44 45-54 55-64 65-74Finland 20-24 25-29 30-34 35-44 45-54 55-64 65-74Iceland 20-24 25-29 30-34 35-44 45-54 55-64 65-74Norway 20-24 25-29 30-34 35-44 45-54 55-64 65-74Sweden 20-24 25-29 30-34 35-44 45-54 55-64 65-74All Nordic countries 20-24 25-29 30-34 35-44 45-54 55-64 65-74
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Note: Figures for other years are given in Appendix 2.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
Table 8: Nordic emigration by age and citizenship in the Nordic countries in 1995
CitizenshipDelivering countryand age Denmark Finland Iceland Norway Sweden Other
Denmark 20-24 25-29 30-34 35-44 45-54 55-64 65-74Finland 20-24 25-29 30-34 35-44 45-54 55-64 65-74Iceland 20-24 25-29 30-34 35-44 45-54 55-64 65-74Norway 20-24 25-29 30-34 35-44 45-54 55-64 65-74Sweden 20-24 25-29 30-34 35-44 45-54 55-64 65-74All Nordic countries 20-24 25-29 30-34 35-44 45-54 55-64 65-74Note: Figures for other years are given in Appendix 2.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
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Migration (and return migration) by age (over time). Comments.
Is it possible to determine whether the migration results in a net brain gain?
5. Labour market attachment and educational gains for migrants
The previous section analysed how precise the migration measures are when register data is used
and compared. These figures validate the quality of these data sources but they do not add
anything new to the knowledge regarding the migrants. However, register data have additional new
and breaking information regarding the migrants. Register data allows for example, a full track of
the migrants before and after the migration. Hence, a more fully picture of the value-added of
migration can be drawn. Both initial and added labour market experience as well as the stock and
amount of additional education adds to the discussion of brain gain, brain drain and brain
circulation from migration.
Table 9: The labour market attachment for emigrants in the year of emigration. Share of allemigrants to the other Nordic countries
YearCountry
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Denmark
Greenland
Finland
Iceland
Norway
Sweden
All NordiccountriesNote: Labour market attachment is measured as being employed or not in the first week of November.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
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Table 10: The labour market attachment for immigrants the first year after immigration.Share of all immigrants from the other Nordic countries
YearCountry
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Denmark
Greenland
Finland
Iceland
Norway
Sweden
All NordiccountriesNote: Labour market attachment is measured as being employed or not in the first week of November.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
Table 11: Additional education in years for immigrants from the other Nordic countriesduring the first five years after their immigration
YearCountry
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Denmark
Greenland
Finland
Iceland
Norway
Sweden
All NordiccountriesNote: Years of education is measured according to the definitions of the ISCED code.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
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Table 12: The average education in years for emigrants to the other Nordic countries theyear they emigrate
YearCountry
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Denmark
Greenland
Finland
Iceland
Norway
Sweden
All NordiccountriesNote: Years of education is measured according to the definitions of the ISCED code.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
6. Migrating persons versus non-migrating persons
An even more detailed picture of the migrants comes from an analysis where the behaviour of the
migrants is compared to the non-migrating persons. The differences show where the dynamics of
the migration is changing and where it is becoming a trend. For example the ICT sector dynamic is
of high interest these days.
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Table 13: The migration distributed by sectors in 1995 (emigration) and 1996 (immigration),pct.
Country and sector Emigration (1995) Immigration (1996)
Denmark Higher Education Institutions and R&D Institutes Information and Communication Technology Agriculture, mining, manufacturing, utilities and construction Trade, hotels, restaurants, transport, financial
intermediation and other services Other community services MissingFinland Higher Education Institutions and R&D Institutes Information and Communication Technology Agriculture, mining, manufacturing, utilities and construction Trade, hotels, restaurants, transport, financial
intermediation and other services Other community services MissingIceland Higher Education Institutions and R&D Institutes Information and Communication Technology Agriculture, mining, manufacturing, utilities and construction Trade, hotels, restaurants, transport, financial
intermediation and other services Other community services MissingNorway Higher Education Institutions and R&D Institutes Information and Communication Technology Agriculture, mining, manufacturing, utilities and construction Trade, hotels, restaurants, transport, financial
intermediation and other services Other community services MissingSweden Higher Education Institutions and R&D Institutes Information and Communication Technology Agriculture, mining, manufacturing, utilities and construction Trade, hotels, restaurants, transport, financial
intermediation and other services Other community services MissingAll Nordic countries Higher Education Institutions and R&D Institutes Information and Communication Technology Agriculture, mining, manufacturing, utilities and construction Trade, hotels, restaurants, transport, financial
intermediation and other services Other community services MissingNote: Figures for other years are given in Appendix 2.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
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Table 14: Intra-Nordic versus inter-Nordic job mobility rates. Into-job rates, pct.
YearCountry andmobility type 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
DenmarkIntraInter
GreenlandIntraInter
FinlandIntraInter
IcelandIntraInter
NorwayIntraInter
SwedenIntraInter
All Nordiccountries
IntraInter
Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
Table 15: Correlation coefficients between business cycle and the migration rates in theNordic countries 1988-97
Country Immigration Emigration
Denmark
Greenland
Finland
Iceland
Norway
Sweden
All Nordic countries
Note: The business cycle is approximated by the inverse unemployment rate.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
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Table 16: Correlation coefficients between wage differentials and migration rates in theNordic countries 1988-97
Country Immigration Emigration
Denmark
Greenland
Finland
Iceland
Norway
Sweden
All Nordic countries
Note: The wage differentials are calculated as the average purchasing power parity, PPP, wage rate in the immigrationcountry over the equivalent wage rate in the emigration country.Source: Register data from the Nordic countries. Finland: Age 20-74. Denmark: Age 20-70.
Can structural changes explain the observed patterns?
Is push or pull effects dominating?
7. Conclusion
How usable is register data to analyse migration?
Comparability among measures from the countries
What does the data tell about additional education, labour market experience and sector relations?
Is the push or pull effects dominating?
Does the migration result in brain gain, brain drain or brain circulation?
Firm mobility/migration; may it be of interest in future studies?
References:
Fischer Peter A. and Thomas Straubhaar. 1996. Migrations and Economic Integration in the Nordic
Common Labour Market. Anniversary Issue: 40 Years of the Nordic Common Labour Market.
Nord 1996:2. Nordic Council of Ministers, Copenhagen
Grundström, Curt. 1993. Report on Nordic immigrants and migration. Statistical Reports of the
Nordic Countries, 64 (Nordisk indvandrar- och migrationsrapport. Nordisk statistisk
skriftserie, 64.) Nordic Statistical Secretariat, Copenhagen
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Pedersen, Peder J. (eds.). 1996. Scandinavians without Borders - Skill Migration and the
European Integration Process. In Eskil Wadensjö (eds.). The Nordic Labour Markets in the
1990’s, Part 2. Elsevier, Amsterdam
Emerek Ruth, Per Vejrup-Hansen and Søren Leth-Sørensen. 1991. IDA - en integreret database
for arbejdsmarkedsforskning. Hovedrapport. Danmarks Statistik. (IDA - an integrated data
base for labour market research. Main report. Statistics Denmark. In Danish)
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Appendix 1: Register information in the IDA-database, an example
The IDA database constructed by Statistics Denmark in the mid and late 1980s is an Integrated
Database for Labour Market Research (IDA in Danish), c.f. Emerek et al (1991). It is constructed to
facilitate the work with the register data with the aim to encourage the amount of research projects
using it. The database has merged information on the entire population (the person register) and
all firms (the business register). The data is quality proved and error corrected to a certain level.
The database contains unique links between the persons and their work places. Among a long list
of variables already included in the database, additional variables can be added by request. The
only limitation on the use of the database is that it is maintained and owned by Statistics Denmark.
Hence, access and use is costly and limited.
Among the variables added to or already present in the database used for the present analyse is:
• Emigration/Immigration country
• Date for movement
• Citizenship today and original citizenship
• Indirectly, return migration (50% return in 3 years time, cf. Pedersen (1996))
• Citizenship of cohabitant/husband/wife, and their original citizenship
• Usual battery of back-ground variables like
• Age, gender, education, family type, children, labour market attachment
• Mobility of all kind; primary and secondary work place, geographical address, country of
residence, formal and informal educational level, labour experience, household
composition, changes in firm/work place, spouses mobility
Appendix 2: Additional migration tables