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Determinants of Fertility During the Fertility Transition in Estonia: A Spatial Analysis

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Abstract

The Princeton European Fertility Project famously studied the determinants of fertility transition using geographical data. The project, however, received criticism for using high-level spatial units that hide much of the variation within. Additionally, although the project underlined the importance of neighbourhood influence through linguistic and cultural similarities, the spatial aspects were not comprehensively studied. This article investigates fertility determinants during the second half of the fertility transition in Estonia, a country with one of the earliest transitions in Europe. We study the completed cohort fertility of married women born between 1875 and 1894 in Estonia at the lowest-level of municipalities. Given the spatial nature of the data, spatial Durbin models are used in addition to the OLS model. The results show that demographic, cultural, educational, economic and spatial influences were all important in determining the level of fertility during the transition.

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Source: Same as in Fig. 2. Base map: Same as in Fig. 2

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Source: Same as in Fig. 2. Base map: Same as in Fig. 2

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Notes

  1. The third being that the organised religion must also explicitly state the expected behavioural norms with respect to fertility.

  2. The micro-level data was mostly destroyed after the results were compiled.

  3. Child-woman ratio is a ratio between the number of children under age 5 and the number of women aged 15–49.

  4. We are unable to compute a child-woman ratio for married women from the published census results, since marital status is aggregated for the population aged 15 and more. Micro-level data was destroyed during the Second World War.

  5. The individual records were opened to people alive and living in Estonia from 1926–1944. Thus, women who had died or emigrated beforehand were not included in the Register. This is possibly also a source of bias.

  6. This could be seen from the trends in the rate of illegitimacy and also from the comparison of infant mortality rates between legitimate and illegitimate children. From 1926, the illegitimacy rate, as well as the infant mortality rate for illegitimate children increases considerably.

  7. An opened individual record was not automatically transferred to a new municipality for the most part. This means that internal migration during the 1930s is also partly unregistered in the Family Register data. If the individual record was copied and sent to another municipality, however, the old record was closed with the explicitly stated reason. Thus, we can leave aside such records, and conclude that there are no duplicate records in the study.

  8. The under-registration of infant deaths is the primary concern with historic demographic data. If such deaths are under-registered, the number of children born is underestimated as well.

  9. While the mean number of children is computed on the basis of individual records for 88,004 women born 1875–1894, the child mortality variable is based on records for 75,480 women. The reason for this difference is that the full dates for birth and death for all children are required in order to compute this variable. Thus, we have excluded women with any missing or low-quality information regarding dates. We explore this issue further in the section on robustness checks.

  10. The maximum and minimum values for mean number of children for women aged 35–49 recorded during the 2011 census were 1.47 and 2.9. The standard deviation was 0.27. Number of municipalities was 226.

  11. These are computed based on 1000 simulations with the impacts() command of the spatialreg package.

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Acknowledgements

This work was supported by the Estonian Research Council grant (PSG669). We thank anonymous reviewers for helpful comments and suggestions on this article. We also thank Alexis Comber for advice regarding multiscale GWR models and Veiko Berendsen for help with data.

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  1. Estonian Institute for Population Studies, Tallinn University, Tallinn, Estonia

    Mark Gortfelder & Hannaliis Jaadla

  2. Cambridge Group for the History of Population and Social Structure, Department of Geography, University of Cambridge, Cambridge, UK

    Hannaliis Jaadla

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Gortfelder, M., Jaadla, H. Determinants of Fertility During the Fertility Transition in Estonia: A Spatial Analysis. Spat Demogr 11, 5 (2023). https://doi.org/10.1007/s40980-023-00116-6

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