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Spatial Aspects of the Rise of Nonmarital Fertility Across Europe Since 1960: The Role of States and Regions in Shaping Patterns of Change

Aspects spatiaux de l’augmentation de la fécondité hors mariage en Europe depuis 1960: Le rôle des États et des régions dans l’élaboration de modèles de transformation

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Abstract

This article investigates the role of states and regions in shaping spatial patterns of nonmarital fertility in Europe since 1960 using a dataset of 497 European subnational regions and smaller countries. Almost all regions registered substantial nonmarital fertility increases over the last 50 years. Prior research has shown that in the first half of the twentieth century states played a dominant role in drawing the demographic map of Europe (Watkins, From provinces into nations: demographic integration in Western Europe 1870–1960. Princeton University Press, Princeton, 1991). As a result, subnational regional variation decreased, while differences between countries increased. In this article, we investigate whether states continue to play such a dominant role in delineating patterns of nonmarital fertility between 1960 and 2007. We find that variation in nonmarital fertility levels increased as a whole across Europe, and states continued to be important for determining these patterns. However, the role of states relative to regions declined in the latest period examined (1990 and 2007). Possible explanations for the changes include increased supranational integration, for example, within the European Union, and decentralisation within states leading to increases in variation in subnational contextual conditions.

Résumé

Cet article étudie le rôle des États et des régions dans l’élaboration des modèles spatiaux de fécondité hors mariage en Europe depuis 1960 à l’aide d’un ensemble de données de 497 régions infranationales et petits pays européens. Presque toutes les régions ont enregistré de substantielles augmentations de fécondité hors mariage au cours des 50 dernières années. Une précédente recherche a montré qu’au cours de la première moitié du 20ème siècle, les États ont joué un rôle prédominant dans l’établissement de la carte démographique de l’Europe (Watkins, From provinces into nations: demographic integration in Western Europe 1870–1960. Princeton University Press, Princeton, 1991). En conséquence, la variation infranationale régionale a diminué tandis que les différences entre les pays ont augmenté. Dans cet artiche, nous examinons dans quelle mesure les États continuent à jouer ce rôle prédominant dans la définition des modèles de fécondité hors mariage entre 1960 et 2007. Nous constatons que les niveaux de fécondité hors mariage ont augmenté dans l’ensemble de l’Europe et que les États continuent à jouer un rôle important dans la détermination de ces modèles. Toutefois, le rôle des États par rapport aux régions a diminué au cours de la dernière période étudiée (1990 et 2007). Les explications possibles des changements incluent la croissance de l’intégration supranationale, par exemple au sein de l’Union Européenne, et la décentralisation au sein des États, engendrant une augmentation de la variabilité des conditions contextuelles infranationales.

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Notes

  1. When we refer to states in this article, we mean sovereign states as, e.g. defined in the first article of the Montevideo Convention. This definition does not include federated states such as the German Länder or the Belgian regions. When talking about the national, supranational or subnational level, this is done in reference to sovereign states, also including those which are not dominated by one single nation.

  2. When we refer to regions in this article, we mean subnational regions within European states. In Watkins’ publications these were called provinces.

  3. Supranational harmonisation may also reduce within-country variation in countries with region-specific family legislation.

  4. The Baltic States are treated as one state in the period 1960 until 1990 and as separate ones in the cross section of 2007.

  5. For some countries, for which data at these cross-sectional years is not available, we draw on data from preceding or succeeding years (see Appendix Table 5 for an overview over all deviations).

  6. The population size of the 292 NUTS-2 regions (excluding Turkey), for example, ranged in 2007 from 26,923 to 11.6 Mio, with 24 % of the regions having populations below the 800,000 threshold, used to differentiate between NUTS-2 and NUTS-3 regions.

  7. We also run our calculations on the smaller NUTS-2 dataset, which delivered very similar findings. This assures us that our choice has no substantial effect on the results.

  8. In Poland, for example, the first-level administrative division changed from 22 regions prior to 1974 to 49 regions in the period 1975–1998, before it was reduced to 16.

  9. The areal interpolation method we use is areal weighting (Goodchild and Lam 1980), which is based on the assumption that the occurrence of marital and nonmarital births is constant across space within the source regions, for which we have data available. This is a strong assumption, as it is unlikely that the population is homogenously distributed across space, nor can we expect that the nonmarital birth ratio is constant across each source region. However, the potential error emerging from the estimation is largely dependent on the geographic detail of the source regions, and the geographic detail of the target regions, for which the estimations are produced. The higher the geographic detail of the source regions in comparison to the target regions, the smaller the potential error emerging from the estimation procedure. As we have for almost all countries for which we carry out estimations very detailed source data available, we decided not to use more complex estimation methods such as, e.g. the EM algorithm (see Gregory 2002). In order to derive the estimates we apply a spatial intersection, in which we intersect a GIS-polygon file with border and area information on the source regions with the one of the target regions (Goodchild and Lam 1980). With this we obtain a GIS-dataset with smallest common polygons (also called zones of intersections) that enable us to reconstruct the values for the target regions.

  10. Results for the marital fertility ratio are not presented in this article.

  11. This might create a bias, since regions divided by sea could be closely connected with high levels of communication and movement; for example, Kent, England and Pas-de-Calais, France. However, due to lack of data, we are unable to use any other measures to create alternative specifications.

  12. For the USSR, only data at the level of the Soviet Republics is provided for 1960, 1975 and 1990. For Romania, no regional data is available for 1975 and 1990.

  13. The Statistical Office of Kosovo uses three categories to distinguish births by marital status: marital (59.6 % in 2008) extramarital (40.4 %) and illegitimate (0.1 %) (Statistical Office of Kosovo 2009, p. 15). Extramarital refers to births outside marriage, in which paternity has been accepted. If only the illegitimate births would be considered nonmarital, Kosovo would have levels comparable to Albania.

  14. It is important to note that the contribution of each country to the variation also depends on the number of regions in the country. However, as we already use a standardised measure, we did not want to add another layer of standardisation by dividing the values by the number of regions.

  15. The values for the country configuration 1960–1990 are similar for all countries that did not experience a change in their set-up.

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Acknowledgments

We kindly thank Jean-Michel Decroly for giving us access to his data collection from the Atlas de la Population Européenne-project (Decroly and Vanlaer 1991). Furthermore, we would like to thank Anne Hiller for her work on the MPIDR Population History GIS Collection and Sigrid Gellers-Barkmann for her data support. Gratitude is also expressed to Hilde Bras, Sandra Krapf and members of the Nonmarital Fertility network for comments on earlier versions of this article. Last but not least, we would like to thank the anonymous reviewers for their valuable comments and suggestions.

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Authors and Affiliations

  1. Max-Planck-Institute for Demographic Research, Konrad-Zuse-Straße 1, 18057, Rostock, Germany

    Sebastian Klüsener & Nora Sánchez Gassen

  2. Social Statistics & Demography, Social Sciences, University of Southampton, Southampton, SO17 1BJ, UK

    Brienna Perelli-Harris

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  1. Sebastian Klüsener
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Correspondence to Sebastian Klüsener.

Appendix

Appendix

See Tables 4 and 5.

Table 4 Time-constant regions including estimation procedures
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Table 5 Countries for which cross-sectional data deviates from the cross-sectional year
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Klüsener, S., Perelli-Harris, B. & Sánchez Gassen, N. Spatial Aspects of the Rise of Nonmarital Fertility Across Europe Since 1960: The Role of States and Regions in Shaping Patterns of Change. Eur J Population 29, 137–165 (2013). https://doi.org/10.1007/s10680-012-9278-x

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