Migration Between the Nordic Countries - a Knowledge Flow Perspective

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Migration between the Nordic countries - A Knowledge flow perspective

Ebbe K. Graversen*)

*) The Danish Institute for Studies in Research and Research Policy Finlandsgade 4 DK – 8200 Aarhus N. Denmark

October 2000

Preliminary version to be presented at the 3rd ordinary meeting in the Nordic Group for Mobility Studies in Århus, 9-11th November 2000

Acknowledgements: Financial support from the Nordic Industrial Fund as well as the Danish Institute for Studies in Research and Research Policy are gratefully acknowledged. Mette Lemming has performed valuable research assistance in the project. 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 This information might be outdated but this is not possible to detect in the registers.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.

2 Table 1: Definitions of de facto stay before migration count in the Nordic counties. National rules 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 month Note: 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.

Immigration: A person entering a country is immigrating to the receiving country, i.e. the immigration country. Emigration: A person leaving a country is emigrating from the delivering country, i.e. the emigration country.

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.

3 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. Percent share of total country specific migration in parentheses Receiving Immigration year country 1990 1992 1993 1995 1996 1997 1998 12182 10441 10658 12245 12041 11504 11351 Denmark (30) (24) (25) (19) (22) (23) (22) 2398 . 2047 2182 2378 2518 2349 Greenland (96) (.) (95) (96) (96) (96) (96) 6571 3723 3300 3895 4286 4041 4523 Finland (48) (26) (22) (32) (32) (30) (32) 1958 1893 1680 1769 2261 2396 2616 Iceland (61) (63) (62) (61) (61) (60) (57) 8028 7497 7713 7850 8635 11774 . Norway (31) (28) (24) (31) (33) (37) (.) 18094 7998 7150 8760 8082 8113 9854 Sweden (30) (18) (12) (19) (20) (18) (20) All Nordic 51221 31552 34541 38696 39679 42343 32691 countries (35) (24) (22) (25) (28) (29) (27)

Delivering Emigration year country 1990 1992 1993 1995 1996 1997 1998 10287 7900 7613 9122 9735 9707 10808 Denmark (32) (25) (24) (26) (26) (25) (27) 3687 . 2585 2663 2853 2943 2907 Greenland (99) (.) (99) (99) (99) (99) (99) 4464 3491 3424 4041 4010 4575 5150 Finland (69) (58) (54) (45) (38) (47) (48) 2688 1621 1808 3185 3079 2731 2637 Iceland (70) (51) (62) (74) (75) (70) (72) 11221 5394 4876 6362 6210 6750 . Norway (47) (32) (26) (33) (30) 32) (.) 15255 11738 10975 11020 12074 13965 14242 Sweden (61) (46) (37) (32) (36) (36) (37) All Nordic 49592 30144 33274 38388 39957 42668 37742 countries (52) (36) (36) (37) (37) (37) (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

4 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) Delivering Immigration country (measured by receiving country) country Denmark Greenland Finland Iceland Norway Sweden 4272 2183 342 1418 2782 1927 Denmark (38) (93) (8) (54) (24) (20) 416 4 . 58 1012 3288 Finland (4) (0) (.) (2) (9) (33) 1241 89 50 . 782 346 Iceland (11) (4) (1) (. (7) (4) 2852 45 613 554 . 4293 Norway (25) (2) (14) (21) (.) (44) 2570 28 3518 586 7198 . Sweden (23) (1) (78) (22) (61) (.) All Nordic 11351 2349 4523 2616 11774 9854 countries (100) (100) (100) (100) (100) (100)

Receiving Emigration country (measured by delivering country) country Denmark Greenland Finland Iceland Norway Sweden 3907 2813 395 1301 2932 2445 Denmark (36) (97) (8) (49) (43) (17) 377 31 . 57 353 3472 Finland (3) (1) (.) (2) (5) (24) 1359 60 53 . 408 560 Iceland (13) (2) (1) (.) (6) (4) 3117 18 1366 927 . 7765 Norway (29) (1) (27) (35) (.) (55) 2048 13 3336 352 3057 . Sweden (19) (0) (65) (13) (45) (.) All Nordic 10808 2907 5150 2637 6750 14242 countries (100) (100) (100) (100) (100) (100) Note: Includes all persons moving independent of age. Norway: 1997. Source: Nordic Statistical Yearbook, 1999

5 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 and immigration between the Nordic countries in 1995 Measured by Measured by delivering country (emigration) receiving All Nordic country Denmark Finland Iceland Norway Sweden (immigration) countries Denmark . À. 229 À229 1042 À 1877 À 1730 À 4878 À Finland 250 À182 . À. 17 À 250 À 2168 À 2685 À Iceland À473 À24 . À. Norway À1370 À370 . À. Sweden À1415 À2087 . À. All Nordic À3440 À2710 À countries 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

6 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?

7 Table 5: Nordic immigration by educational level and citizenship in the Nordic countries in 1995 Receiving country Citizenship and educational level Denmark Finland Iceland Norway Sweden Other Denmark PhD Master Bachelor Other tertiary ISCED 3+4 Missing Finland PhD Master Bachelor Other tertiary ISCED 3+4 Missing Iceland PhD Master Bachelor Other tertiary ISCED 3+4 Missing Norway PhD Master Bachelor Other tertiary ISCED 3+4 Missing Sweden PhD Master Bachelor Other tertiary ISCED 3+4 Missing All Nordic countries PhD Master Bachelor Other tertiary ISCED 3+4 Missing 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.

8 Table 6: Nordic emigration by educational level and citizenship in the Nordic countries in 1995 Delivering country Citizenship and educational level Denmark Finland Iceland Norway Sweden Other Denmark PhD Master Bachelor Other tertiary ISCED 3+4 Missing Finland PhD Master Bachelor Other tertiary ISCED 3+4 Missing Iceland PhD Master Bachelor Other tertiary ISCED 3+4 Missing Norway PhD Master Bachelor Other tertiary ISCED 3+4 Missing Sweden PhD Master Bachelor Other tertiary ISCED 3+4 Missing All Nordic countries PhD Master Bachelor Other tertiary ISCED 3+4 Missing 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.

Migration by nationality for the Nordic countries Brain drain/gain?

9 Return migration shares, who returns and with which skills?

Table 7: Nordic immigration by age and citizenship in the Nordic countries in 1995

Receiving country Citizenship and age Denmark Finland Iceland Norway Sweden Other Denmark 20-24 25-29 30-34 35-44 45-54 55-64 65-74 Finland 20-24 25-29 30-34 35-44 45-54 55-64 65-74 Iceland 20-24 25-29 30-34 35-44 45-54 55-64 65-74 Norway 20-24 25-29 30-34 35-44 45-54 55-64 65-74 Sweden 20-24 25-29 30-34 35-44 45-54 55-64 65-74 All Nordic countries 20-24 25-29 30-34 35-44 45-54 55-64 65-74

10 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

Delivering country Citizenship and age Denmark Finland Iceland Norway Sweden Other Denmark 20-24 25-29 30-34 35-44 45-54 55-64 65-74 Finland 20-24 25-29 30-34 35-44 45-54 55-64 65-74 Iceland 20-24 25-29 30-34 35-44 45-54 55-64 65-74 Norway 20-24 25-29 30-34 35-44 45-54 55-64 65-74 Sweden 20-24 25-29 30-34 35-44 45-54 55-64 65-74 All Nordic countries 20-24 25-29 30-34 35-44 45-54 55-64 65-74 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.

11 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 all emigrants to the other Nordic countries Year Country 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

Denmark Greenland Finland Iceland Norway Sweden All Nordic countries Note: 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.

12 Table 10: The labour market attachment for immigrants the first year after immigration. Share of all immigrants from the other Nordic countries Year Country 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

Table 11: Additional education in years for immigrants from the other Nordic countries during the first five years after their immigration Year Country 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

Denmark Greenland Finland Iceland Norway Sweden All Nordic countries Note: 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.

13 Table 12: The average education in years for emigrants to the other Nordic countries the year they emigrate Year Country 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

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.

14 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 Missing Finland 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 Missing Iceland 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 Missing Norway 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 Missing Sweden 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 Missing All 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 Missing 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.

15 Table 14: Intra-Nordic versus inter-Nordic job mobility rates. Into-job rates, pct.

Country and Year mobility type 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 Intra Denmark Inter Intra Greenland Inter Intra Finland Inter Intra Iceland Inter Intra Norway Inter Intra Sweden Inter All Nordic Intra countries Inter 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 the Nordic 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.

16 Table 16: Correlation coefficients between wage differentials and migration rates in the Nordic 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 immigration country 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

17 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)

18 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