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How much does geography contribute? Measuring inequality of opportunities using a bespoke neighbourhood approach

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Abstract

To what extent an individual is successful in a variety of outcomes is the result of multiple factors such as (but not limited to) parental background, level of education, discrimination and business cycles. Factors like these also indicate that the success in life can be attributable to factors that both take individual-level merits into account but also to structural factors such as discrimination and contextual effects. Over the last decades, a growing interest in decomposing and categorising factors that affect the life chances of individuals has led to the formation of inequality of opportunity as a research field. This paper builds upon this growing literature, which amounts to quantify the contribution of factors that lie beyond the control of individuals to the total inequality observed in different spheres of life. Using rich Swedish longitudinal register data, we are able to follow individuals over time and their educational attainment during upbringing and later labour market outcomes. In difference from other inequality of opportunity studies, we make use of an egocentric neighbourhood approach to integrate the socio-economic composition of the parental neighbourhood in an inequality model and illustrate its contribution to the total inequality in both outcomes quantitatively. Using multilevel regression analyses, we show that the parental neighbourhood is highly influential in educational attainment and remains so for market outcomes even years after exposure.

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Notes

  1. Source: https://www.scb.se/Grupp/Hitta_statistik/Regional%20statistik/Kartor/_Dokument/SKL-Kommungrupp.pdf.

  2. Kriging was conducted in ARCInfo using the ordinary spherical semivariogram method, \(\hbox {k}=12\)

  3. see Jusot et al. (2013) for other approaches

  4. Multilevel regression showed a negative association with the disposable income of individuals and their parental education. To correct this, we used a classification that sorted municipalities by the degree of industrialisation, population density, commuting and remoteness

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Authors and Affiliations

  1. Department of Economics, Abdullah Gül University, Sumer Campus, 38030, Kayseri, Turkey

    Umut Türk

  2. Department of Social and Economic Geography, Uppsala University, Box 513, SE-751 20, Uppsala, Sweden

    John Östh

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  1. Umut Türk
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  2. John Östh
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Correspondence to Umut Türk.

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Türk, U., Östh, J. How much does geography contribute? Measuring inequality of opportunities using a bespoke neighbourhood approach. J Geogr Syst 21, 295–318 (2019). https://doi.org/10.1007/s10109-019-00297-z

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  • DOI: https://doi.org/10.1007/s10109-019-00297-z

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