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The Annals of Regional Science

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01.03.2014 | Original Paper

Regional clustering of human capital: school grades and migration of university graduates

verfasst von: Sofia Tano

Erschienen in: The Annals of Regional Science | Ausgabe 2/2014

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Abstract

The spatial distribution of human capital plays a fundamental role for regional differences in economic growth and welfare. This paper examines how individual ability indicated by the grade point average (GPA) from comprehensive school affects the probability of migration among young university graduates in Sweden. Using detailed microdata available from the Swedish population register, the study examines two cohorts of individuals who enrol in tertiary education. The results indicate that individual abilities reflected by the GPA are strongly influential when it comes to completing a university degree and for the migration decision after graduation. Moreover, there is a positive relationship between the GPA and the choice of migrating from regions with a relatively low tax base and a relatively small share of highly educated people in the population, while individuals with higher GPA tend to stay at a higher rate in more flourishing regions.

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This is consistent with the theory of compensated wage differentials.

91 % of the parents stay in the same LMA as when the individual attended high school and 87 % as when the individual was 6 years of age.

The data in this study has restrictive public use. For detail description on the database, see Bonita et al. (2011).

Singles are defined as non-married or cohabitating without children. The data does not allow for a distinction between cohabitating couples without children and single households.

90.1 % are registered as singles at age 25. Two years later, the percentage has decreased to 82.1 %, indicating that couple formation at a large extent happens later for the highly educated.

All students are entitled to benefits. A part of the benefits does not constitute a loan and is usually claimed by all individuals engaged in higher education.

At least two years of post-secondary education are recognized as university degrees.

The per capita tax base increased on average by 10 % and the share of highly educated by 8 % . Further, the standard deviation of the regional variables increased.

Only one interaction variable is estimated in each specification due to multicollinearity.

This means that variables that seem to effect only one outcome are included in both equations e.g. parents’ education which does not directly influence the probability of migration.

The correct prediction for both dependent variables in this model is roughly 60 %. Failing to predict correctly for both equations only happens in 4 % of the cases. The percentage of corrected predictions does not change between different specifications.

The exception is for the GPA estimate when including the interaction effects, where there is a significant difference between the cohorts on the 5 % level.

This is due to space issues; the estimates are available upon request.

This is at least true when not including an interaction variable, and when included the total, marginal effects must be calculated to see the full effect of the regional variables.

The results of these specifications can be found in Appendix Table 9.

This sample only includes university students. However, this group is the one with the highest GPA in the country and also the most mobile group, so it should reflect the trend of GPA flows.

Table 6

Change in the distribution of GPA by type of region for cohort 1974

Region\(^{\mathrm{{a}}}\)	GPA quartile 1	GPA quartile 2	GPA quartile 3	GPA quartile 4
Urban centres	-3.4	-0.1	1.1	1.8
University towns	3.7	0.5	-1.1	-3.0
Other cities/towns	-0.3	-0.7	-0.1	1.0
Rural areas	0	0.1	-0.1	0.2

\(^{\mathrm{{a}}}\) For definitions, see Appendix Table 9

Table 7

Change in the distribution of GPA by type of region for cohort 1976

Region\(^{\mathrm{{a}}}\)	GPA quartile 1	GPA quartile 2	GPA quartile 3	GPA quartile 4
Urban centres	-2.1	-0.1	1.1	0.6
University towns	2.9	0.9	-0.7	-3.1
Other cities/towns	-1.0	-1.0	-0.3	0.6
Rural areas	0	0.1	-0.1	0.1

\(^{\mathrm{{a}}}\) For definitions, see Appendix Table 9

A similar division of region types can be found in Jauhiainen (2008). Bjerke (2012) uses a division of growth and declining regions, where the growth regions coincide to a large extent with the LMA: s that has a University or College.

Parameter results for the alternative specification can be shown upon request.

Compare e.g. the parameter estimates of the highly educated in the migration equation between columns 1 and 2 in Table 2.

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Titel: Regional clustering of human capital: school grades and migration of university graduates
verfasst von: Sofia Tano
Publikationsdatum: 01.03.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: The Annals of Regional Science / Ausgabe 2/2014
Print ISSN: 0570-1864
Elektronische ISSN: 1432-0592
DOI: https://doi.org/10.1007/s00168-014-0599-z

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