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ABSTRACT
More educated, more mobile? Evidence from post-secondary education reform. Spatial Economic Analysis. This paper examines the causal impact of the level of education on within-country migration. To account for biases resulting from selection into post-secondary education, it uses a large-scale reform within the higher education system that gradually transformed former vocational colleges into polytechnics in Finland in the 1990s. This reform created quasi-exogenous variation in the supply of higher education over time and across regions. The results based on multinomial treatment effects models and population register data show that, overall, polytechnic graduates have a significantly higher probability of migrating than vocational college graduates, although the estimates vary, for example, by gender, field of study and region.
摘要
更多教育、更能流动？高等教育改革的证据。空间经济分析。本文检视教育程度对于国内迁徙的因果影响。为了解释由选择进入高等教育所导致的偏见，本文运用芬兰在九Ｏ年代开始，逐渐将过往的技职学院改制为理工大学的高等教育系统中的大规模改革。此一改革随着时间在各区域的高等教育供给中，创造了半外在的变异。根据多项式处理效应模型和人口登记数据的结果显示，普遍而言，理工大学的毕业生较技职学院的毕业生而言，显着有更高的比例进行迁徙，尽管该评估会随着诸如性别、学习领域和区域而有所改变。
RÉSUMÉ
Plus qualifié, alors plus mobile? Des résultats provenant de la réforme de l’éducation post-secondaire. Spatial Economic Analysis. Cet article cherche à examiner l’impact causal du niveau de l’éducation sur la migration à l’intérieur des pays. Pour tenir compte du biais dû à la sélection pour l’éducation post-secondaire, on se sert d’une importante réforme au sein du système d’enseignement supérieur et qui a progressivement transformé les anciens collèges d’enseignement professionnel en polytechnics (à savoir, instituts universitaires de technologie) en Finlande au cours des années 1990. Cette réforme a fini par une variation quasi-exogène quant à l’offre d’enseignement supérieur sur le temps et à travers les régions. Les résultats, qui proviennent non seulement d’un modèle multinomial des effets de traitement mais aussi des données d’un registre de population, montrent que, tout bien considéré, la probabilité que les diplômés des polytechnics vont se déplacer dépasse celle des diplômés des collèges d’enseignement professionnel, bien que les estimations varient, par sexe, par domaine d’études et par région, entre autres.
RESUMEN
¿Más educados, más móviles? Evidencia de la reforma en la educación superior. Spatial Economic Analysis. En este artículo analizamos el impacto causal del nivel de educación en la migración dentro de un país. Para explicar los sesgos que ocurren en la selección para la enseñanza postsecundaria, se utiliza una reforma a gran escala en el sistema de educación superior de Finlandia que transformó gradualmente los antiguos institutos de formación profesional en escuelas politécnicas en la década de los noventa. Esta reforma creó una variación casi exógena en la oferta de educación superior con el tiempo y en todas las regiones. Los resultados basados en modelos de efectos de tratamiento multinomial y datos del registro de la población muestran que, en general, los graduados de escuelas politécnicas presentan una probabilidad significativamente mayor de emigrar que los graduados de los institutos de formación profesional, aunque las estimaciones varían, por ejemplo, en función del sexo, el campo de estudio y la región.
PALABRAS CLAVES:
ACKNOWLEDGEMENTS
The authors thank Stefano DellaVigna, Paul J. Devereux, Kari Hämäläinen, Christopher Jepsen, Viktor Venhorst, and the seminar participants at: the Regional Studies Association European Conference in Tampere, Finland, 2013; the Faculty of Economics, University College Dublin, Ireland, 2013; the XXXth Summer Meeting of Finnish Economists, Jyväskylä, Finland, 2013; and the Labour Institute for Economic Research, Helsinki, Finland, 2013, for helpful comments.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the authors.
ORCID
Mika Haapanen http://orcid.org/0000-0003-2964-3352
Petri Böckerman http://orcid.org/0000-0002-5372-2985
Notes
1 Consistent with Schwartz (Citation1973), Faggian and Franklin (Citation2014) find for the United States that the distance required for a move is less of a deterrent for (college-bound) students with a higher quality of human capital than those with a lower quality of human capital.
2 Prior literature has demonstrated that student migration is also related to the quality of educational institutions and local labour market conditions (Ciriaci, Citation2014; Dotti, Fratesi, Lenzi, & Percoco, Citation2013). Dotti et al. (Citation2013) find that the attractiveness of the region for those who enrol in a university is linked to the prospects of job vacancies for graduates. Ciriaci (Citation2014) highlights that students are not only attracted by high-quality universities but also that the migration rates after graduation are lower among graduates from high- than low-quality universities.
3 NUTS = Nomenclature des Unités Territoriales Statistiques.
4 The migration rates are computed as the total rates over the six-year follow-up period, instead of being presented as annual averages over the six-year period.
5 The matriculation examination is a national compulsory final exam taken by all students who graduate from high school. The answers for each test are first graded by teachers and then reviewed by associate members of the Matriculation Examination Board outside the schools. The exam scores are standardized so that their distribution is the same every year.
6 Multinomial treatment effects models and the linear IV models produce qualitatively similar results.
7 We also estimated logit migration models that included both the level of education dummies and our instrument. The coefficient for the instrument was close to zero (0.004) and highly insignificant (p = 0.619; providing additional support for exogeneity).
8 We also estimated standard errors using different assumptions (Huber–White robust and clustering on graduation-region-by-year cells), but we report the most conservative (i.e., the largest) standard errors.
9 For example, Weiss’s (Citation2015) IV estimates of ever moving to another region are two to three times as large as the ordinary least squares (OLS) estimates.
10 As reported in Table S4 in the supplemental data online, the results are qualitatively similar when we estimate the models with linear IV instead of using the preferred multinomial treatment effect model.
11 This is contrary to the findings for UK university graduates, where female graduates are generally more geographically mobile than male graduates (Faggian et al., Citation2007).
12 The estimate for Uusimaa should be interpreted with some caution because the Hansen J-test rejects the null hypothesis of the validity of the instrument for this specific subsample.
13 LAU = local administrative unit.
14 We also conducted several additional analyses which are reported in Tables S8–S10 in the supplemental data online. For example, our results are robust for the inclusion of additional variables to the set of controls (e.g., a person’s own earnings or family characteristics and the region of secondary education).