Can Migration Decisions be Affected by Income Policy Interventions? Evidence from Finland

Abstract

Haapanen M. and Ritsilä J. (2007) Can migration decisions be affected by income policy interventions? Evidence from Finland, Regional Studies 41, 339–348. Using Finnish micro-level data, this paper maps out whether migration decisions can be affected by income policy interventions. The analysis focuses on individuals living in peripheral regions and distinguishes peripheral migration from growth-centre migration. In support of the human capital hypothesis, the estimation results imply that migration decisions can be affected by income policy interventions. For example, an intervention that would increase an individual's expected disposable income by 10%, given that he/she does not move to a growth-centre region, would decrease his/her probability of growth-centre migration by approximately 12%. However, the impact appears to be modest compared, for example, with the impact of education on migration.

Haapanen M. et Ritsilä J. (2007) La décision de migrer, est-elle influée par des politiques des revenus ponctuelles? Des preuves finlandaises, Regional Studies 41, 339–348. A partir des données microéconomiques finlandaises, cet article cherche à élaborer si, oui ou non, la décision de migrer est influée par des politiques des revenus ponctuelles. L'analyse porte sur les individus qui habitent les régions à la péripherie et distingue la migration à la périphérie de la migration aux pôles de croissance. Pour soutenir l'hypothèse du capital humain, les estimations laissent supposer que la décision de migrer peut être influée par des politiques des revenus ponctuelles. Par exemple, une politique ponctuelle qui augmenterait de 10% le revenu disponible individuel escompté, donné que l'individu n'est pas obligé de migrer à un pôle de croissance régional, diminuerait d'environ 12% la probabilité qu'il migrerait à un pôle de croissance régional. Cependant, l'impact semble faible par comparaison à l'impact de l'éducation sur la migration, par exemple.

Migration Revenu Politique ponctuelle Choix de destination

Haapanen M. und Ritsilä J. (2007) Lassen sich Migrationsentscheidungen durch politische Maßnahmen hinsichtlich des Einkommens beeinflussen? Belege aus Finnland, Regional Studies 41, 339–348. In diesem Beitrag wird mit Hilfe finnischer Daten auf Mikroebene untersucht, ob sich Migrationsentscheidungen durch politische Maßnahmen hinsichtlich des Einkommens beeinflussen lassen. Die Analyse konzentriert sich auf Personen in peripheren Regionen, wobei zwischen einer peripheren Migration und einer Migration zu Wachstumszentren unterschieden wird. Aus den Ergebnissen der Schätzung geht hervor, dass sich Migrationsentscheidungen durch politische Maßnahmen hinsichtlich des Einkommens beeinflussen lassen, was die Hypothese des Humankapitals unterstützt. Wenn sich zum Beispiel durch eine Maßnahme das voraussichtliche verfügbare Einkommen einer Person um 10% erhöht, sofern diese Person nicht in ein Wachstumszentrum zieht, sinkt die Wahrscheinlichkeit einer Migration dieser Person in ein Wachstumszentrum um ca. 12%. Allerdings mutet die Auswirkung auf die Migration beispielsweise im Vergleich zur Auswirkung von Bildung eher bescheiden an.

Migration Einkommen Politische Maßnahmen Wahl des Zielorts

Haapanen M. y Ritsilä J. (2007) ¿Se puede influenciar en las decisiones de migración mediante medidas políticas sobre ingresos? El ejemplo de Finlandia, Regional Studies 41, 339–348. Con ayuda de datos de Finlandia a nivel micro, en este estudio analizamos si las políticas sobre ingresos pueden influir en las decisiones sobre emigración. Este análisis se centra en individuos que viven en regiones periféricas y hace una distinción entre la migración periférica y la migración hacia centros de crecimiento. Respaldando la hipótesis de capital humano, los resultados de las estimaciones indican que las medidas políticas sobre ingresos pueden influir en las decisiones sobre migración. Si, por ejemplo, mediante una medida política los ingresos previstos y disponibles de una persona aumentaran un 10%, a condición de que esta persona no se trasladase a un centro de crecimiento, su probabilidad de migración a un centro de crecimiento disminuiría aproximadamente un 12%. Sin embargo, este impacto parece ser modesto si lo comparamos por ejemplo con el impacto de la educación en migración.

Migración Ingresos Medidas políticas Elección del destino

Keywords:

• Migration
• Income
• Policy interventions
• Choice of destination

Acknowledgements

The authors gratefully acknowledge financial support from the Academy of Finland and Yrjö Jahnsson Foundation. The authors wish to thank Hannu Tervo, Kari Hämäläinen, Brigitte Waldorf, Arnaud Chevalier and two anonymous referees for useful comments and suggestions on this paper.

Notes

1. For a discussion of urbanization in general, see Williamson (1988), Lucas (1997) and United Nations (1999).

2. For prior evidence on the impact of expected earnings on migration, see Falaris (1987) for Venezuela and Islam and Choudhury (1990) for Canada. These authors find a positive and significant impact of expected income gain on migration.

3. This implies that the individual moves (j = 1, 2) only if the net gain from migration (ln PV _ij − ln PV _i0) is greater than zero and selects that destination region for which ln PV _ij is maximized.

4. Taylor's first-order expansion, f(θ) ≈ f ^′(θ₀) + f (θ₀) (θ − θ₀), at point θ₀ = 0 is ln (1 − θ _ij ) ≈ ln (1 − 0) , because θ < 1.

5. The present value of expected disposable income is approximated with predicted disposable income just after migration (see the Appendix for details).

6. The sample selection correction variables λ _ij are defined as: , where φ is the standard normal density function; Φ⁻¹ is the inverse of the standard normal distribution; and P _ij is the predicted probability of alternative j computed from a reduced-form multinomial logit model that include all variables in X _i and Z _i (see equations 5 and 6) (Lee, 1983; Falaris, 1987).

7. The predicted value can be calculated as: ln ˆ W _ij = X _i β _j . Similarly, Ŵ _ij = exp(X _i β _j + σ _j  ²/2), where σ _j  ²> is the estimated variance of the error term v _ij in equation (5). The result follows from the expected value properties of log-normal distributions (e.g. Mood et al., 1974, p. 117).

8. Note that the error term ϵ _ij is not exactly Gumbel-distributed, since it is a linear function of the Gumbel error term (ξ _ij ) and the normal error term (ω _ij ). Fortunately, the assumption is defensible since both distributions have somewhat similar shapes (Vijverberg, 1995). A similar assumption has been made previously (Lee, 1983; Vijverberg, 1995).

9. Due to ‘Iron Law of Economics’, measurement errors are likely to bias the parameter estimates toward zero (Cameron and Trivedi, 2005).

10. Random parameters logit models can be estimated by maximizing a simulated log-likelihood function (for a discussion, see Stern, 1997). In this study, to reduce simulation error, the simulations are based on Halton draws (Train, 2003). A more advanced treatment of the measurement errors would have required the use of panel data (Carroll et al., 1995). Due to data limitations, this was left for a further study.

11. Data from 84 subregions were used. The subregion of Åland was excluded as it has many distinctive characteristics (including self-regulation, isolated geographical location and a Swedish-speaking majority). One limitation of the data set is that it does not allow one to use households as the unit of analysis because it is unknown which individuals belong to the same households. However, there is a wide range of household variables that should control for the dependencies in the migration decision-making.

12. The regional classification into growth-centre regions and peripheral regions was formed using information on the net migration rates and population figures: a region is classified as a growth-centre region if it had a positive net in-migration rate and its population was larger than 50 000 inhabitants in 1995. The division is not sensitive to population size.

13. An annual income greater than €1000 was considered positive. The income threshold is necessary in order to obtain meaningful income measures. Self-employed, retired and foreign-born individuals were excluded from the sample as the factors determining their incomes are likely to differ from those applicable to the rest of the population. In addition, those who were students in 1995 were excluded from the sample.

14. For the impact of taxation and the public sector on migration, see Islam (1989), Charney (1993), and Westerlund and Wyzan (1995) (also equations 1 and 2).

15. Note, however, that the choice of commuting may also reflect high personal costs of migration in the first place (Eliasson et al., 2003).

16. The present authors also did not find any significant impact of municipal taxation on the migration propensity of individuals. Hence, highly insignificant and small coefficients were omitted from the final model. This result is expected because differences in taxation are fairly small between regions in Finland and thus interregional tax competition seems limited.

17. In practice, income policy interventions could be implemented, for example, through exemptions of some kind from personal income taxation.

Additional information

Notes on contributors

Mika Haapanen

Email: [email protected]

Jari Ritsilä

Email: [email protected]