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Recent changes in the spatial organisation of European fertility: Examining convergence at the subnational and transnational level (1960-2015)

Modifications récentes de lorganisation spatiale de la fécondité européenne : Étude sur la convergence à léchelle infranationale et transnationale (1960-2015)
Mathieu Buelens

Résumés

Depuis la fin des années 1960 d’importantes modifications des comportements familiaux et de la composition des ménages ont eu lieux en Europe, notamment en ce qui concerne la fécondité. Les données récentes prédisent en moyenne un enfant de moins par famille que celles de 1960. Si des théories telles que la deuxième transition démographique permettent une compréhension satisfaisante de ces modifications ainsi que de leur causes, elles se reposent essentiellement sur des analyses comparatives entre pays ce qui néglige la dimension spatiale. Or il existe des variations spatiales à la fois entre pays et au sein des pays. Elles résultent de différences de rythmes dans les changements sociétaux. Cet article s’intéresse à un des aspects clé de la modification des comportements fécond en cartographiant les taux de fécondité à un niveau infranational (NUTS-2) en Europe entre 1960 et 2015. Cela permet de questionner la vraisemblance d’une convergence de la fécondité européenne et de suggérer les éléments ayant modifié la distribution spatiale de la fécondité.
Cet article révèle comment la fécondité européenne a connu des évolutions
spatialement différenciées au cours des 55 dernières années. Les résultats montrent que seule une faible convergence se dessine au niveau Européen. Cependant, et malgré que les spécificités infranationales persistent, une certaine convergence est à l’œuvre au sein de quatre ensembles supranationaux. L’évolution temporelle de la distribution spatiale de la fécondité attire l’attention sur un changement de structure spatiale la plus pertinente pour expliquer l’organisation spatiale de la fécondité. Alors que les états tenaient le plus grand rôle en 1960, une division du continent en quatre groupes supranationaux est désormais plus pertinente. Sur base de ces résultats, sont présentés les facteurs pressentis pour avoir mené à une telle organisation spatiale au vue de l’extension spatiale de leur rayon d’action. Ces facteurs sont susceptibles d’avoir joué un rôle important dans les transformations récentes des comportements féconds.

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1 Introduction

1Empirical research on recent family and household transformations too often uses cross-country comparisons as only aggregated level [Lesthaeghe, 2010 ; Pinnelli, Hoffmann-Nowotny and Fux, 2001]. There are two major reasons for that: one is the easier access to large dataset of comparable national data than subnational data, the second is the assumption that little variation in family behaviours subsists within country in later phases of the second demographic transition (SDT). However such approach has major bias including the tendency of to consider national contexts responsible for the variations observed [Snyder, 2001]. Moreover the presupposition of homogeneous family behaviours within countries remains contested [Coleman, 2002]. With a sole focus on fertility, authors of the Princeton European fertility project highlighted differences within countries until the mid-twentieth century (see also Ogórek (2012) and Strömmer (1969)). Many others have proved these differences last in more recent trends for instance in Belgium [Costa, Eggerickx and Sanderson, 2011], Czechia [Šprocha and Šídlo, 2016], France [Desplanques, 2011], Italy [Franklin and Plane, 2004 ; Vitali and Billari, 2017], Romania [Jemna and David, 2018], etc. However reviewing these researches leave many questions unanswered because of the focus on a single country at the time. Such approach may induce country-specific condition bias but mostly difficulties to generalise the results [Snyder, 2001].

2Hence geographical knowledge on fertility level is limited and fragmented. Boyle (2003) and Compton (1991) have deplored the lack of geographical perspectives in research on contemporary fertility in the West. Both authors however praise the relevance of such perspective for the understanding of fertility trends, considering place (or living environment) influences fertility decision-making. For instance, to identify the (subnational) regions precursor and resistant to fertility innovations would enable a better understanding of the origins of these innovations and their diffusion processes.

3In the attempt to overcome this lack, this article answers several question on spatial structures and dynamics of contemporary changes relating to fertility. It exposes whether spatial variations (still) exist, at what spatial level are they the most striking and how did they change.

1.1 Contextualisation

4Before delving into subnational analysis, the following graphs summarise recent changes in European fertility at the national level as reported in the literature [Burkimsher, 2015 ; Festy, 1979 ; Frejka and Sobotka, 2008 ; Sardon, 2009].

Figure 1a-1d: Total Fertility Rate in selected countries

Figure 1a-1d: Total Fertility Rate in selected countries

Note: Supranational data for five years periods

Source: Human Fertility Collection (national data) and United Nations Population Division (supranational data)

  • 1 Weighted average based on 28 EU countries plus Iceland, Liechtenstein, Norway, and Switzerland (the (...)

5According to the Total Fertility Rate (TFR) the average1 European fertility level decreased from 2.58 children per woman in 1960 to 1.46 in 2000, and then increased slightly in the early twenty-first century. During the same period the world average halved, going from approximately 5 to 2.5 children per woman. The more gradual decline in Europe is related to its earlier start. Compared with the previous century, the recent trends in Europe are relatively small fluctuations of fertility at low levels.

6Based on Figure 1, these fluctuations could be organised in phases. First, after the baby boom in the late 1950s to early 1960s, fertility went into steep decline in Northern and Western Europe (cf. France, Great Britain, Norway and Germany in Fig. 1 a-b). TFR dropped by around 1.1 children per woman over a period of 15 years. After that, fertility levels remained roughly stable in these parts of the continent for the rest of the century. Ten years later (mid-1970S), in a second phase, Southern European fertility started to decrease more sharply. These declines only slowed in the 1990s (see Fig. 1 c). In a third phase, countries then under communist rule experienced substantial drops in the 1990s (see Fig. 1 d).

7Since its low around 2000, European TFR has experienced a (slight) increase (+0.12 children per woman between 2000 and 2015), yet European fertility remains far under the generation replacement level. Here as well groups of countries expose three phases. In the late 1980s, way before the rest of Europe, TFR start rising in Norway and the other Nordic countries. Northern Europe has thereby consistently presented above-average fertility for the last 30 years. Through most of the 2000s the European average was pushed upward by increases in France (since the mid-1990s), the UK (mostly in the 2000s), and other Western and Southern European countries. Similar trends also took place in CEE countries where fertility bounced back after the 1990s drop.

8However, since 2008 approximately, rises have slowed in many Eastern European countries and even reversed in most Northern and Western European countries. However this last decade TFR are increasing in Romania, Czechia, Germany and Austria though TFR in German-speaking countries has remain relatively stable and low over the past 35 years (around 1.4 children/woman).

1.2 Previous research at the subnational level

9Beside the country-specific conditions they detail, researches on fertility trends at the subnational level mentioned above are greatly valuable for this research. They highlight interactions between spatial (regional) and temporal (or cohort) effects. Fertility changes are happening unevenly within countries. Differences are particularly striking between core and peripheral areas [Walford and Kurek, 2016] or between settlement size [Kulu, Vikat and Andersson, 2007].

10Yet in the past, converging trends within countries were reported. Particularly by Decroly (1994) and Coale and Watkins (1986) who also used subnational and transnational geographical approach in order to understand the changes in European fertility. During their periods of observation (up to 1960 or the late 1980s) they record converging trends within individual nations, likely to result from national integration and influence of state level factors. At a wider level, both authors also discuss a certain supranational organisation. Watkins (1990) whose study covers almost an entire century (1870-1960) expects the integration to the European Union (EU) to diminish the relevance of nation-states in shaping converging demographic behaviours as she expects the role of supranational bodies to rise in the future. Decroly, whose studies cover both western and eastern sides of the Iron Curtain, studies the increasing organisation of fertility along that political division [Decroly, 1994 ; Decroly and Grasland, 1992].

  • 2 NUTS (Nomenclature of Territorial Units for Statistics) is an EU-regulated system of hierarchical s (...)

11More recently authors have also report a converging trends of fertility level within countries although they are not able to state if such increasing integration of localities into higher-level bodies is made in favour of national, supranational or continental level [Basten, Huinink and Klüsener, 2012 ; Vachuška, 2018]. Indeed, these researches focus on too few countries and countries that are too similar to control for specific conditions at those levels. Researches on fertility trends at the subnational level for a vast number of countries are the only ones able to answer such question. The few reporting figures after the 1980s do not observe any clear converging trend in western Europe, while the East is characterised by a general fertility decrease [Buelens, 2013 ; Duchêne et al., 2004 ; Kurkin, 2010]. Unfortunately such result is only valid for the turn of the century as each of these studies uses similar data sets, starting from 1991 and covering (at best) two decades for consistent NUTS-2 units2.

12Knowledge is thus here again fragmented as no study bridges fertility trends dating from the start of the broader family transformations with those reported during these transformations. Once done it will be possible check hypotheses based on the here above literature review. I will measure the extend of the converging trend across Europe, test whether or not convergence within nations continues, report how the end of communist rules in Central and Eastern Europe (CEE) and the enlargement of the EU has changed the spatial organisation of fertility, and size the influence of different spatial structure in recent fertility transformations.

2 Methodology

2.1 Analysis strategy

13Between-nation comparisons of subnational units from different countries appears as the only solution to gain control over national-level idiosyncrasies and historical, ecological, and cultural country-specific conditions [Fox, Klüsener and Myrskylä, 2019 ; Snyder, 2001]. Subnational level is necessary to explore beyond national averages and thereby makes it possible to test homogeneity within countries. Moreover subnational level is the only one able to prove observations made at the national level are truly attributable to national context. The method raises several challenges including finding a method able to measure spatial organisation of fertility and how it has change over the last decades. Mapping fertility distribution across time and space is used as exploratory analysis to hypothesis on the spatial structures likely to have influence fertility transformations. It exposes major spatial and temporal discontinuities without preconceptions on the relevance of any spatial level. Then, in order to measure the effect of these spatial structures on fertility level, I analyse the variance in different groups with a method traditionally used in multilevel logistic modelling. In some ways it is as if I was building empty (or unconditional) models with data relating to spatial units instead of individuals. This allows a variance decomposition that shows how much of the total heterogeneity between European regions is due each spatial structures. I repeat this analysis at different dates to measure how the effects of these spatial structures gain or lose influence on the spatial variations of fertility.

2.2 Data

14This methodology demands an original data set covering multiple countries, at a comparable spatial level and with coherent spatial units over time. The difficult data gathering process explains the rarity of such approach in the existing literature or the limited number of country (usually one) for a limited period. It also forces to use only the most commonly available indicator such as the total fertility rate (TFR). Although TFR is computed on figures from a specific date, its trend when covering a long enough period gives an idea of the completed fertility and thereby information on the number of children and family size.

  • 3 All overseas countries and territories as well outermost regions of EU but the Canary Islands have (...)

15I’ve been able to collected subnational data for 22 European countries or 277 (NUTS-2 level) regions3. Data at the national level is provided for an additional 21 countries. The latter are either relatively small and considered as NUTS-2 regions in their entirety (Estonia, Luxembourg, etc.), or are much larger but only serve contextual proposes on exploratory analysis (Russia, Turkey, etc.).

16I collected data as follows:

  • Data from before 1990 is courtesy of J-M Decroly, who collected and computed subnational demographic data (including TFR) from national statistics offices for 1960, 1980, and 1988.

    • 4 For instance figures marked as 2010 are based on the average of the 2009, 2010, and 2011 figures. T (...)

    For more feasibility and comparative reasons with Decroly’s work, I only present data for 1990, 2000, 2010, and 2015. However these figures are based on three-year averages to smooth potential statistical hazards.4 - EUROSTAT dataset provides TFR for NUTS-2 regions since 1990, but there is a high number of missing values that must be completed for some countries/regions/years. In the data appendix I specify the solutions used when Eurostat data were not available. In general, I used age-specific fertility rates (ASFR) provided by national statistics offices to compute TFR. In case ASFR were also not available I used five years age groups fertility rates or computed them based on the number of births by age of the mother and the number of women by age.

    • 5 In the NUTS system, countries have the right to change their subdivisions every three years. Many e (...)
    • 6 Reconstructed spatial units correspond to the NUTS-2 regional subdivision for 2016 (except for the (...)

    Because neither NUTS regions nor Decroly’s spatial units are consistent with time5, I had to reconstruct spatially consistent regions throughout the whole period.6 Each spatial grid was based on official administrative breakdowns and thereby was depending on the borders changes of subnational divisions.

3 Exploratory analysis

17Spatial distributions of fertility in 1960, 1980, 1990, 2000, 2010, and 2015 are juxtaposed in Fig. 2. Coherent colour scale through the whole period highlights the decrease European fertility experienced. With period fertility rates, European families on average would count one fewer child in 2015 than in 1960. Hence the highest TFRs in 2000 (>2, for example in Brussels, Ireland, and Iceland) and 2015 (in France and Ireland) are lower than the 1960 average. In contrast a fertility rate of under 1.4 children per woman was seen only in very specific places in 1960 (i.e., capital cities in CEE) but spread to nearly half the regions on the continent by 2000 and remained quite common in Southern Europe, Poland, and Slovakia in 2015.

Figure 2: Total Fertility Rates in European regions

Figure 2: Total Fertility Rates in European regions

Source: Eurostat unless stated otherwise in the data appendix

3.1 A slight tendency toward convergence

18Despite a general decrease, subnational variations of fertility in the EU and EFTA countries persist. As shown in Fig.3, variations in TFR only diminished sparingly between 1960 and 2015. The extend of the converging trend as measured by standard deviation (σ) is misleading as the average fertility (μ) is decreasing during the same period. The coefficient of variation (which takes the moving averages into account) reveals that the heterogeneity between European regions only decreased by a fifth compared to its 1960 level, and this decrease is mostly due to the most recent trends (between 2010 and 2015). Convergence also fails to appear inevitable as regional fertility diverge between 1960 and 1988. This uncommon trend mostly concerns extremes values as inter-quartile range (which only considers the middle-half of the values) diminished during the same period. These results undermine the convergence of fertility between European countries expected by some[Coleman, 2002 ; Roussel, 1992].

Figure 3: European subnational Total Fertility Rates statistics

Figure 3: European subnational Total Fertility Rates statistics

Note: 100 for the 1960 values

Source: own calculation

3.2 Role reversal between central and peripheral regions

19In 1960, as apparent on Fig. 2, the highest fertilities where seen on the edges of the European continent: Ireland in the west (TFR >3.75), coastal Norway and Finnish Lapland in the north (>3.3), along the USSR border in the east, while in the south a good third of the Italian, Portuguese, and Spanish regions present TFRs of above 3 children per woman. To that list could be added the southern Balkans with TFR above 6 in Albania and Kosovo. Even within countries TFR are gradually increasing towards these peripheral areas. High fertility in 1960 usually reflects later start of the (first) demographic transition.

20With time high fertilities in peripheral regions wear off and spatially uneven upturn pursues changing the geography of European fertility. Hence in 1980, the Scandinavian and Finnish regions have joined those of (West) Germany, Switzerland, and the northern half of Italy as the least fertile. But low fertility in Nordic regions does not last long as it increases in the 1980s and 2000s. On the contrary, in European Mediterranean countries, the sharp decreases beginning in the mid-1970s set subcontinental fertility at durable low levels (see Fig. 1 c). Low levels in the East are very common after 1990, and until now the region still displays under average TFR. Consequently, a clear continental division appears in the early twenty-first century: on one hand northwestern countries present a TFR of between 1.6 and 2; on the other, TFR is rather around 1.4 for the rest of the continent. Within this second group little to no difference is observed between subnational TFRs in Central Europe and those of Italy or Spain (all only slightly above 1 child per woman). This division, previously named the “Western European fertility divide” [Klüsener, Neels and Kreyenfeld, 2013], clearly follows national borders.

21The opposite trends in fertility result in the European average having changed very little between 1990 (1.65) and 2015 (1.57). However, the spatial distribution has been radically modified. Correlations between regional distributions at the beginning and the end of the period studied is very limited (15%). Correlation would even give more credit to an inversion of spatial distribution between 1980 and 2015 (-6%) than a continuity. This means that changes were rapid and radical, especially in regions that previously were the most fertile. Hence it seems that the factors that delayed the start of the demographic transition had little impact in slowing down the process once engaged. Finally this also supports a generalisation, at the continental level, of the reversing relationship between fertility and economic development found between regions within several countries (considered one at the time) [Fox, Klüsener and Myrskylä, 2019]. Lately, higher and/or increasing fertility is characteristic to core economic regions.

3.3 Vestiges of high fertility in Southeastern Europe

  • 7 The zone is most probably continuous via the neighbouring Ukrainian region of Transcarpathia sharin (...)
  • 8 Compared to Yugoslavia for zone b.
  • 9 TFR above 6.7 in Albania and Kosovo in 1960.

22Two large transnational zones work against the “Western European fertility divide” and the reversing relationship between fertility and economic development : one zone (a) stretches from east Slovakia and northeast Hungary to northern Romania,7 and the other (b) is formed around Montenegro, Kosovo, and Albania. Both zones typically contain the least urbanised areas of their countries8 and are more loosely integrated into the international trade economy. Despite considerable decline of fertility in these zones, TFR remain high (for European standards) either resulting from relatively good preservation of past high levels (zone a), either vestiges of previously very high fertility levels (zone b)9.

4 Convergence within nations?

4.1 Differences within states exist and have been quite stable since 1980

23The research acknowledges the persistence of subnational differences in fertility, even if these differences are low in absolute terms. Differences are generally smaller within than between countries, however in most country homogenisation did not progress significantly. Converging trends only appears clearly from (within countries) coefficient of variations for the 1960-1980 period in about half the countries considered. So, influence of subnational factors did not disappear with the strengthening of national or supranational contexts; rather, their effects are combined with higher spatial level factors.

24Many differences within countries are consistent in time, such as the north-to-south diminishing gradient in Finland, the north-to-southwest one in France, the east-to-west one in Slovakia, the higher fertility in the Geest regions of Lower Saxony and Swabia compared to the rest of (West) Germany, the higher fertility in the Highlands and on the islands compared to the rest of Scotland, the difference between low fertilities in Holland and province of Groningen in opposition to higher fertility in Friesland and Flevoland in the Netherlands, etc. (see Fig. 2). This suggests explanations deeply rooted in the past, which is supported by other researches on current fertility behaviours [Basten, Huinink and Klüsener, 2012 ; Castiglioni and Vitali, 2019], researches on past behaviours and the first demographic transition (see the Princeton project mentioned above or Lesthaeghe and Wilson (1982)) and researches linking both past and present transitions [Lesthaeghe and Neels, 2002 ; Lesthaeghe and Lopez-Gay, 2013]. These researches expose distributions of fertility that resonate with subnational linguistic, cultural, and religious specificities or with contrasts in material and economic conditions that may even have faded or disappeared since.

4.2 Increasing homogeneity but diverging subnational trends

  • 10 Former Yugoslavian republics (now independent countries) are also less coherent than the continent (...)

25In 1960, Italy, Hungary, Romania and Portugal were the only countries with subnational units less coherent than those of the whole of Europe taken together. Only in Italy did this last until 1990.10 TFR were the lowest the northwest (1.74) and getting higher towards south ( up to 3.25). However, between 1980 and 2010 Italian regions experienced opposite trends. In the north TFR decreased slightly in the 1980s and then increased for two decades, resulting in positive changes for the 30 years period: +0.3 child per women (or +22%) in the Aosta Valley, +0.36 (or +30%) in Emilia-Romagna, etc. In the south, the decrease was greater, lasted longer, and was followed by a more modest upturn, resulting in the TFR losing more than 40% of its 1980 level in Basilicata and Calabria (–0.8 child per woman). Therefore national coherence in fertility increased and the north–south gradient soften; yet at the same time the changes led to the most and least fertile regions switching positions. Similar trends happened for instance in Spain, Poland and Portugal leading in the latter to a 60% diminution of subnational variations between 1960 and 1990 but a 200% increase since.

4.3 Lower fertility in urban areas

  • 11 Counter-examples exist: for instance in the NUTS-2 regions including Brussels or Birmingham, TFR ar (...)

26In countries where NUTS-2 units dissociates urban from rural regions, lower fertility is generally observed in the former. This is valid throughout time and space, despite very different national fertility averages and politico-economic contexts [Decroly et al., 1991]. It suggests an urban specificity acting as a determinant factor to pull down local fertility. In the maps above (Fig. 2) examples include Germany’s biggest Stadtstaaten (Berlin and Hamburg); capital city regions like Bucharest, Budapest, (inner) London, Prague, and Vienna; and regions mostly containing urban areas like Attiki (around Athens), Community of Madrid, Hovedstaden (including Copenhagen), Metropolitan Area of Lisbon, southwestern Bulgaria (including Sofia), etc. 11Fertility level in urban regions also evolved differently over the last five and a half decades. Compared with the rest of their respective countries, these urban areas experienced a lower loss in TFR (in absolute and relative terms) or even an increase.

5 European fertility increasing spatially organised at the supranational level

  • 12 Figures based on 21 countries made up of a minimum of four NUTS-2 units.

27Based on the here above observations and the literature review I decided to test the significance of the following geographic structures in European fertility distribution: (former) political blocs dividing the continent along the Iron Curtain; groups of countries sharing strong cultural, political and economic characteristics; individual countries; and metropolitan areas. Proportions of variance between subnational units within these structures is plotted on Fig. 4.12

Figure 4a: Relevance of geographic structures in the spatial organisation of European subnational TFR

Figure 4a: Relevance of geographic structures in the spatial organisation of European subnational TFR

Source: own calculation

Figure 4b: Relevance of geographic structures within each other in the spatial organisation of European subnational TFR

Figure 4b: Relevance of geographic structures within each other in the spatial organisation of European subnational TFR

Source: own calculation

28Variations are increasingly organised by country. Since 1960 at least, the national level has been the single most significant level for rendering NUTS-2 variations in fertility. Its growth is largely due to the (seemingly) converging trends in Italy, Romania, Portugal and Central European countries. Converging trends within nations can be supported by modelled cultural homogeneity, action of similar family policies and other welfare state measures. Indeed, policies that affect people’s fertility behaviours the most are state dependant [Basten, Huinink and Klüsener, 2012 ; Decroly and Grasland, 1992 ; Klüsener, Perelli-Harris and Sánchez Gassen, 2013 ; Watkins, 1990].

  • 13 The groups of countries are adapted from Pinnelli, Hoffmann-Nowotny and Fux, (2001) however with Ge (...)

29However, countries are a subdivision of the supranational groups, themselves a subdivision of the two political blocks. Relevance of the national level is thus in part due to the relevance of the broader groups. Fig. 4-b presents the part of regional variance strictly associated with each geographical structures between 1960 and 2015. Hence if in 2010, division in countries is associated with almost 90% of the NUTS-2 variation in fertility, it shows an overwhelming part of that is due to a division in just five groups of countries presenting strong common features (religiosity, welfare state system, etc.): Northern Europe; Western Europe, Southern Europe, CEE and German-speaking Europe.13 If subnational units within nations are getting more homogeneous, only some national borders matter: those delimiting the five supranational groups (hence the “Western European fertility divide”). Differences between regions of a country are actually more important than differences between countries of the same group. It argues in favour of an increasing relevance of supranational factors in fertility transformations. This idea has previously only been hypothesised based on national level data [Neyer, 2003].

Figure 5: Subnational TFR convergence in Europe and in supranational groups

Figure 5: Subnational TFR convergence in Europe and in supranational groups

Note: 100 for the TFR variance between NUTS-2 regions across Europe in 1960
Based on 21 countries (made up of a minimum of four NUTS-2 units). Central and Eastern: Bulgaria, Czechia, Hungary, Poland, Romania, Slovakia. German-speaking: Austria, Germnay (East and West), Switzerland. Nordic: Denmark, Finland, Norway, Sweden. Southern Europe : Greece, Italy, Portugal and Spain. Western: Belgium, France, the Netherlands, the United-Kingdom.

Source: own calculation

30Fig. 5 compares converging trends within supranational groups with that across Europe (cf. Fig. 3). Unsurprisingly supranational groups appear to be more homogeneous than the continent as a whole. Southern Europe is the least homogeneous group, until the 1980s it hosted simultaneously some of the most and least fertile regions on the continent. But variations eventually diminish in each groups much quicker than across the whole continent. In 2010 the average variation within country is even greater than between subnational units of most supranational groups. In the last five-year period (2010–2015) a new trend appears. While convergence of European fertility accelerates, it cannot be related to a major converging trend in groups tested here. To the contrary, variations are even strongly increasing in CEE. Re-emerging diversity of fertility behaviours was expected after the collapse of the communist regimes with national level data [Sobotka, 2003]. Considering subnational data, the diversity in fertility level only starts emerging two decades later.

31Two additional spatial structures are tested in Fig. 4 a-b. While political blocs were not a relevant form of spatial organisation of fertility in 1960, Europe became increasingly organised around the East–West divide until 1988. At that time fertility in regions under communist regimes was much higher than in the West. Relevance of this divide quickly decreases after the end of communist rule in CEE. The metropolitan specificity tested here was barely relevant in 1960, and not at all after that. This may come as contradiction with most capital city regions presenting lower fertility than their neighbouring regions (see section 4.3). It may be caused by the poor delineation of metropolitan regions in the NUTS grid.

5.1 Supranational impact on fertility transformations

32The changing geography reported here above suggests that (new) determinants influencing fertility levels have emerged, strengthened, or faded over the 55 years covered by this analysis. The increasing organisation in five supranational groups suggests stronger significance of supranational determinates. Literature presents at least three factors that corroborates the spatial structures exposed in the previous sections. This section aims a better understanding of their supranational scope of action.

a) Institutional and cultural proximity

33Most cross-country studies on family behaviours gather countries into groups based on their proximity and similarities. These similarities are usually defined by shared institutional (political) structures or cultural idiosyncrasies (see Neyer, 2003; Pinnelli et al., 2001). For instance, Nordic countries are often group for sharing a common welfare-state model characterised by stronger redistribution than in other welfare states. Specific institutional characteristics induce sociological specificities and reversely. Hence the Nordic model both stems from and perpetuates high employment among women and a more equal gender division of labour at home than in other European countries [Forssén, 2000 ; Tsuya, 2003]. These characteristics participate to the early start of family transformations in Nordic societies, and ultimately led to more childbearing-friendly contexts, hence the current higher fertility.

34To the contrary, Southern Europe present very low fertility (around 1.3 for the last 25 to 30 years). Here as well the fertility behaviours may be, at least partly, explained by cultural specificities. Unlike societies influenced by state-encouraged equal opportunities (in the north) or strong individualistic values (in the west), ‘Mediterranean Europe’ has been described as a supranational group sharing a central position of the family in society [Arpino and Tavares, 2013 ; Fux, 2008]. This ‘familistic’ culture is deeply rooted in the past [Reher, 1998] and strengthened by Catholicism and the religion’s position as an important social institution [Dalla Zuanna, 2004]. This shared cultural idiosyncrasies influence social institutions and policies, both largely family-based in Southern European countries. Altogether it produces a fairly rigid family formation process. In modern (material) context, the requirements for family formation have become more difficult to fulfil, hence the delayed and low fertility in Southern Europe.

b) Political regime and regime changes

35East Germany is a good example to show how political regimes influence fertility. The area experienced multiple regime changes over the recent decades. From figures comparable to West Germany in 1960, TFR in East Germany rose to levels comparable to Czech regions in 1980, also under communist regimes at the time (see Fig. 1). However, in the late 1980s social and political changes led to a sharp drop in fertility (TFR halved over a period of four years). TFR in former East Germany then gradually increased to reaches West German levels with which it now shared the same federal-level political context (see Fig. 1). In some ways East Germany acted as a frontrunner as similar drops to very low levels occurred in CEE in the 1990s at the time of their regime change. The sum of all those national regime changes belonging to the same chain of events influence supranational spatial organisation of family transformations. The fertility declines did not modify spatial disparities between or within CEE countries.

36Political regimes influence fertility trough different ways. Under state socialism, fertility in CEE was kept high (around 2 children per woman) thanks to relatively favourable childbearing conditions among other things. Some authors argue fertility was maintained at artificially high levels despite a second demographic transition already afoot [Kharkova and Andreev, 2000]. Women’s social position and working conditions participate to this favourable condition, but it changed with the transfer of political power, the dismantling of command economies, and emerging economic constraints resulting in greater uncertainty. Indeed, the challenges of transitioning to the new capitalist system led to the end of guaranteed lifelong employment, a reduction of the female labour force activity, a decline in state supports for families, an increasingly difficult reconciliation of work and family life, the privatisation of the housing sector, a steep drop in standards of living, and in many countries, a rise in poverty. In this new context, old demographic regimes were no longer (artificially) sustained and new constraints fuelled postponement of birth and fertility reduction (see Bhaumik & Nugent, 2002; Kotowska et al., 2008; Sobotka, 2003).

c) Economic downturns

37Fig. 1 shows that European fertility rose for most the 2000s, until a sudden tailing off. In most countries, 2008 is the pivotal year where TFR trends switch from steady growth to stabilisation or even going into decline. The suddenness and synchronicity of these trends point to the influence of a transnational event. That year, European economies were going through a recession originating in the collapse of the US real-estate market. In an increasingly integrated (European) economy, economic downturns have become a supranational phenomenon. The 2008 economic downturn resulted in greater economic uncertainty, which itself may have caused a (temporary) drop in TFR because of people postponing their fertility plans to a brighter tomorrow. Small declines of short duration with limited effect on cohort fertility levels were demonstrated in most research looking at the relationship between economic recession and fertility in the developed world [Sobotka, Skirbekk and Philipov, 2011].

  • 14 For instance Davalos and Morales (2017) found that economic crisis has opposite effects on fertilit (...)

38However, if consequences of economic downturns vary by age, education, and social and employment status, they also vary spatially which is too often overlooked in demographic research.14 Despite being an integrated economy, Europe present strong regional inequalities in terms of economic structure, job market, labour force and broader position on the global economy. Fragmentation of the European area between ‘core’ and ‘(semi-)peripheries’ [Petrakos, 2008] is very likely to induce spatially uneven imprint of economic downturn on fertility behaviours. Hence the difference in time needed to recover pre-2008 TFR levels in German speaking countries and in Southern European countries (see Fig. 1).

6 Discussion and conclusion

39Trying to answer Boyle’s call for more geographical perspective in fertility research (2003), this article studies how spatial structures of fertility changed over time. Its originality lies in the dataset used, both subnational and transnational. Indeed previous studies are limited to differences between socio-economic groups or regions within a single country or cross-country comparisons. This specificity has several advantages for a better understanding of spatial dynamics: it allows a control over many place-specific conditions, makes it possible to test homogeneity within countries and consequently prove whether or not observations made at the national level are truly attributable to national context such as presupposed by cross-country analyses.

40Because it uses aggregate-level data, this research could have been exposed to modifiable areal unit problems. However, reconstructing consistent spatial units since 1960 enhances the robustness of the analysis and made it possible to observe the changes in the responsibility of selected spatial structures in the variations of fertility. This way, the research reports the spatial dynamics of fertility changes during a 55-years period during which major changes affected family behaviours and household composition.
When it comes to explanations on the impacts of fertility determinants on the highlighted spatial structures, some may view the lack of more quantitative research as a limitation. Indeed do not add predicators to the unconditional model thus not completing a full multilevel analysis. Therefore I’m only able to discuss, not measure, the influence of fertility determinants already exposed in the literature. This methodology has been induced by the difficulty of the data gathering process. Further quantitative analyses (requiring additional data) would complete this work but would have to consider the multicollinearity of many fertility determinants.
Although, this research focused on fertility levels only, with no data to consider other aspects of family and household transformations, its
comparison with studies focusing on broader aspects is interesting. For instance, in an analysis of the role of states in the rise of nonmarital fertility in Europe since 1960, Klüsener, Perelli-Harris, et al. (2013) found increasing regional variation. This alternative spatial dynamic suggests fertility and non-marital fertility do not answer to the exact same set of determinants. However the authors reveal a declining role of states (in relative terms) between 1990 and 2007. My results add credit to their hypothesis of this decline being a consequence of an increasing integration into supranational-level spaces.

41Several conclusions can be drawn from this research.

42First, in relative terms, no significant convergence of fertility level took place across Europe with the major transformations in family and household. Despite a general decrease in fertility since 1960, variations between European regions remain as wide in 2010 than 50 years before. However spatial distribution gets increasingly organised, specifically in four supranational groups: the northwestern countries, German-speaking countries, southern countries, and CEE countries. These areas are as coherent as the country they gather, but their differences with each other mark clear spatial discontinuities. Hence the spatial dynamics of fertility distribution not only changed from an organisation based on the regional level to one based on nations as previously exposed [Watkins, 1990]. Since 1960 this continuing trend is mostly due to convergence in supranational groups. Hence the results suppose fertility determinants with supranational scope of action are gaining importance.

43Another striking result is the reversing relationship between economic development and fertility in spatial distribution of European fertility during the 1960-2015 period. While peripheral regions of the continent presented the highest European fertilities in 1960, they now display very low TFR. Family transformations changes some local fertility boosting factors of the old demographic regime into fertility restraining factors in the new one. Examples include greater conservatism and highly family-centred culture which ceased to have a positive influence on fertility in southern Europe and works against the acceptance of new demographic behaviours. The reversing spatial relationship may also result in part from changes of the local-factors. For instance, state supports and favourable context in communist ruled countries maintained relatively high fertility in CEE, characteristic of the old regime. But necessity for adaptation to the dramatic change of political and economic contexts accelerates people’s transformations of fertility behaviours.

44This research partly recognises cross-country comparisons method for studying European fertility. However, it seems national factors are no longer the drivers of fertility transformation. Rather, state is the structure that has the tools to (in)voluntarily influence fertility in response changing supranational contexts. Spatial distribution of fertility is increasingly organised at the supranational level. Nevertheless, subnational differences persist meaning local determinants are (still) relevant as well. of fertility.

45For future researches, comparisons of national averages should not be the only methodology used for understanding recent fertility trends in Europe. Spatial researches going beyond the national level, embracing subnational diversity in a transnational area and using multi-scalar approaches would help shed light on the diversity of determinants influencing family and fertility transformations.

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Annexe

* : Human Fertility Collection

Country

Year

Note

Austria, Belgium, Iceland, Lithuania, Luxembourg

No missing values

Bulgaria

1960-1988

Data provided at a lower level than the NUTS-2 regions. NUTS-2 data are computed when gathering the smaller regions (averages weighed by the total population).

Croatia

Considered subnational for 1960-1990 data.

1990

*

Cyprus

1960

No data

Czechia

1960-1988

Beside CZ01 and CZ02, data are provided for regions that don't correspond with NUTS regions. 2016 NUTS-2 regions are reconstructed based on the proportion of their spatial extension covered by the old regions.

1990

Actually 1992

Denmark

1960-1988

NUTS-2 regions didn't exist. 2016 NUTS-2 regions are reconstructed based on the proportion of their spatial extension covered by groups of the old amter (23 in 1960; 15 in 1980 and 1988).

1990 & 2000

NUTS-2 regions didn't exist. To reconstructed NUTS-2 data I compute weighted average based on lower level regions (Amter for TFR in 1989-1990-1991 and 1999-2000-2001 and provinces for population of 15-44 years women in 2006). Both Amter and provinces data comes from Statistics Denmark. NUTS-2 regions result mostly from merging of a few amter but some amter were split into different NUTS-2 regions. For them I based my calculation on the proportion of their spatial extension. Perfect solution is difficult to achieve as even some municipalities were split into different NUTS-2 regions.

Estonia

*

Finland

1960-1988

Some of the 12 Läänit experienced border changes but overall are comparable with the current 19 NUTS-3 regions. To reconstruct consistent NUTS-2 data, Läänit data are merged (with averages weighted by the total population) despite the boder changes.

France

1960-1988

Data provided at the Départements level which are equal to NUTS-3 regions (exect around Paris and in Corsica for 1960 howevere with no impact on NUTS-2 regions). NUTS-2 data results from averages weighed by the total population.

Germany

1960

In West Germany: some Regierungsbezirke do not correspond with NUTS-2 regions. To reconstruct consistent NUTS-2 data, Regierungsbezirke are merged for NUTS-2 regions DE 94; A2; B1; B3; or merged to form regions with small border differences (DE91 and DE93). I assigned Kassel Regierungsbezirk data to DE73 and an average based on Darmstadt and Wiesbaden Regierungsbezirke for both DE71 and DE72. Within Baden-Württemberg (DE 11;12;13;14) border differences are not considered. Averages are weighed by the total population.

1980

In West Germany: the Regierungsbezirke in Hesse do not correspond with NUTS-2 regions. I assigned Kassel Regierungsbezirk data to DE73 and Darmstadt one to both DE71 and DE72.

1960-1988

In East Germany: the 15 Bezirke are merged into 7 regions comparable with the NUTS-2 regions despite small border differences. For Berlin : eastern and western parts of the city are considered together despite belonging to different states and political bocks. Averages are weighed by the total population.

1990

I multiply 1988 data with 0,987* for NUTS-2 in (former) East Germany and 1,025* for those in the West. These factors represent the ratios of TFR change in the two (former-)states between 1988 and 1990.

2000

Based on ASFR of 2002

2010

Based on ASFR. For DED4 and DED5: based on ASFR of 2011 and with no consideration for the small border change between them.

Greece

1960

Except for EL 43;54;61;62 data are provided for regions that don't correspond with NUTS regions. Values are equally attributed to smaller level regions (Nomoi) constitutive of the 1960 regions. To reconstructed NUTS-2 data I compute average based on these Nomoi (weighed by the population in 1980). Transfers from small settlements of Peloponnesus to Attiki is not considered.

1980 & 1988

Data provided at the Nomoi level which are equal to NUTS-3 regions (except in Attiki however with no impact on NUTS-2). NUTS-2 data results from averages weighed by the total population.

1990

Actually 1991

Hungary

1960-1988

Data provided at a level corresponding with the NUTS-3. Regions are merged (with averages weighed by the total population).

1990

For HU11 and HU12 regions: I multiply 1988 data with the ratio of TFR change in the broader HU1 region between the two dates.

2000 & 2010

For HU11 and HU12 regions: differences between the two regions is an average of the differences from 1988 and 2015. I multiply this with the TFR in the broader HU1 region in 2000 and in 2010.

Ireland

1990

Computed based on the number of births and the number of women between 15-49 years. Data from Central Statistics Office Ireland.

Italy

1960-1988

Data provided at a level corresponding with NUTS-3. NUTS-2 data results from averages weighed by the total population.

1990 & 2000

For ITH5 and ITI3 regions: actually 1991 and 2001. Small border change between the two regions is not considered.

Latvia

1990

Data from "Evolution démographique récente en Europe" [Council of Europe, 2002].

Liechtenstein

1960-1988

No data

Malta

1960-1988

*

the Netherlands

1960 & 1980

Flevoland didn't exist as a province yet. Figures are based on the differences compared with Overijssel in 1988. I multiply this with the ratio of TFR change in Overijssel between 1988 and 1960 or 1988 and 1980.

1988

Data for Flevoland comes from Statistic Netherlands

1990

Computed based on the number of births and the number of women between 15-50 years. Data received by Statistics Netherlands.

Norway

1960-1988

Data provided at a level corresponding with NUTS-3. NUTS-2 data results from averages weighed by the total population.

Poland

1960

Some of the 22 Voivodeships experienced border changes but overall they are comparable with with the 16 NUTS-2 regions once the cities of Warsaw, Lodz, Krakow, Wroclaw and Poznan are merged with their surrounding region and the Voivodeship of Szezecin and Koszalin are merged together to form PL42. Averages are weighed by the total population.

1980 & 1988

The 49 Voivodeships are merged into 16 regions comparable with the NUTS-2 ones despite border differences. Averages are weighed by the total population except for PL84 and PL62. For better reconstruction, these regional averages are based on the proportion of their spatial extension covered by the old regions.

1990

Actually 1991

Portugal

1960-1988

Some of the 18 disctricts experiended borders changes but overall they are comparable with the current 23 NUTS-3 regions. To reconstruct consistent NUTS-2 data, district data are merged (with averages weighted by the total population) despite the boder changes. For better recontruction, Sebtubal population is split between PT18 (10%) and PT17 (90%).

1990

Actually 1991. The border change is not considered (transfer of subregiões from PT17 to PT16 and PT18).

Romania

1960

Data provided for 17 Regiunea which are merged into 8 regions comparable with the NUTS-2 ones despite border differences (in each of them but RO11 and RO21). Averages are weighed by the total population.

1980 - 1988

Data provided at the Judete level which correspond with NUTS-3 regions. NUTS-2 data results from averages weighed by the total population. For for the region around Bucharest (RO32) : 1980 data in 1980 results from an average between the total population of Bucharest and 20% of that of Ilfov. For 1988 : it results from an average between Bucharest (80%) and the surrounding Judet (20%).

1990

I multiply 1988 data by the ratio of TFR* change at the national level between 1988 and 1990.

Spain

1960-1988

Data provided at a level corresponding with NUTS-3. NUTS-2 data results from averages weighed by the total population.

Sweden

1960-1988

Data provided for 24 Lan which after merging correspond with NUTS-3 regions. NUTS-2 data results from averages weighed by the total population.

Switzerland

1960-1988

Data provided at a level corresponding with NUTS-3. NUTS-2 data results from averages weighed by the total population.

1990

Actually 1991

Slovakia

1960-1988

Supposingly no difference in TFR between SK01 and SK02

1990

I multiply 1988 data by the ratio of TFR* change at the national level between 1988 and 1990.

Slovenia

Considered subnational for 1960-1990 data.

United Kingdom

1960

Data provided for 70 Counties among which only some correspond with NUTS-2 regions. To reconstruct consistent NUTS-2 data, Counties are merged to form regions similar or closely comparable with 2013 NUTS-2 regions. Averages are weighed by the total population. Many NUTS-2 regions contains sections of the old Counties. For better reconstruction, some counties were split and their sections integrated to different NUTS-2 regions. For the splits I assume TFR was coherent across the counties and use the 2015 population distribution for weighed averages. However for regions around Birmingham, Manchester and Liverpool, I assume the TFR was not coherent in the counties. Based on the difference between Central Clydeside conurbation (including Glasgow) and its surounding regions I expect higher fertility in the urban sections. I thus add 0,1 child per women to UK D3; D7 and G3.

1980 & 1988

I assigned Greater London TFR to Outer London. Inner London data based on the differences compared with the broader region in 1960.

1990

I multiply 1988 data with1,009* for NUTS-2 in England and Wales; 0,941* for Northern Ireland and 0,993* for NUTS-2 in Scotland. These factors represent the ratios of TFR change 1988 and 1990.

2000 & 2010

Based on ASFR of women between 15 and 50 years old (provided by Office for National Statistics). For London : actually 2001

2015

For London (UKI1 and UKI2) : based on ASFR of smaller regions. Average weighed by population of 15-44 years women. In Scotland, UKM2 and UKM3 data are based on ASFR of women between 15 and 50 years old (provided by the Office for National Statistics).

Belarus, Bosnia-Herzegovina, Montenegro, Russia, Serbia, Ukraine

*

Kosovo

1960-1980

*

1988

Actually 1987*

1990-2010

No data

2015

Actually 2016

Moldovia

*

1960

Actually 1961

North Macedonia

1990

*

Turkey

1960-1990

United Nation Population Division

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Notes

1 Weighted average based on 28 EU countries plus Iceland, Liechtenstein, Norway, and Switzerland (the four EFTA countries).

2 NUTS (Nomenclature of Territorial Units for Statistics) is an EU-regulated system of hierarchical subdivisions of European countries. It uses existing national administrative subdivisions.

3 All overseas countries and territories as well outermost regions of EU but the Canary Islands have been excluded from the analyses. The second-order regions (NUTS-2) are designed to encompass on average between 800,000 and 3 million inhabitants. However, even if the NUTS system is supposed to subdivide countries into units of comparable population size, some NUTS-2 regions (especially in Spain, France, and Italy) are considerably larger. Weight analyses by population size reduces this bias.

4 For instance figures marked as 2010 are based on the average of the 2009, 2010, and 2011 figures. This also provided a way to consider trustworthy data from national censuses (usually taking place in 1991, 2001 and 2011) in the averages.

5 In the NUTS system, countries have the right to change their subdivisions every three years. Many ended up doing so between 1990 and 2015, especially Denmark, Finland, Portugal, and the UK.

6 Reconstructed spatial units correspond to the NUTS-2 regional subdivision for 2016 (except for the UK, Poland and Ireland where they correspond to the 2013 subdivision). Croatia, Latvia and Slovenia are considered at the national level, and London regions correspond to the ones of 2010. For consistency I also use current national borders thorough the period.

7 The zone is most probably continuous via the neighbouring Ukrainian region of Transcarpathia sharing important historical and demographical similarities.

8 Compared to Yugoslavia for zone b.

9 TFR above 6.7 in Albania and Kosovo in 1960.

10 Former Yugoslavian republics (now independent countries) are also less coherent than the continent in general until 2010 but are considered separately in this research.

11 Counter-examples exist: for instance in the NUTS-2 regions including Brussels or Birmingham, TFR are consistently higher than in their surroundings. Much of this apparent contradiction derives from the highly varying delineation of NUTS-2 regions in European countries and the great differences in demographic behaviours in city centres compared with that in the suburbs [Buelens, 2019 ; Kulu, Boyle and Andersson, 2009 ; Wanner, 2000].

12 Figures based on 21 countries made up of a minimum of four NUTS-2 units.

13 The groups of countries are adapted from Pinnelli, Hoffmann-Nowotny and Fux, (2001) however with Germany, Austria and Switzerland in a group of their own such as proposed by Frejka and Sardon (2006) or Neyer (2003).

14 For instance Davalos and Morales (2017) found that economic crisis has opposite effects on fertility in the wealthiest and poorest regions of Colombia. Unfortunately in Europe within country differentiated consequences have not been examined, including by studies using subnational data (such as Matysiak et al., 2018)

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Table des illustrations

Titre Figure 1a-1d: Total Fertility Rate in selected countries
Légende Note: Supranational data for five years periods
Crédits Source: Human Fertility Collection (national data) and United Nations Population Division (supranational data)
URL http://journals.openedition.org/eps/docannexe/image/12255/img-1.png
Fichier image/png, 166k
Titre Figure 2: Total Fertility Rates in European regions
URL http://journals.openedition.org/eps/docannexe/image/12255/img-2.jpg
Fichier image/jpeg, 116k
URL http://journals.openedition.org/eps/docannexe/image/12255/img-3.jpg
Fichier image/jpeg, 116k
URL http://journals.openedition.org/eps/docannexe/image/12255/img-4.jpg
Fichier image/jpeg, 112k
URL http://journals.openedition.org/eps/docannexe/image/12255/img-5.jpg
Fichier image/jpeg, 104k
URL http://journals.openedition.org/eps/docannexe/image/12255/img-6.jpg
Fichier image/jpeg, 108k
Crédits Source: Eurostat unless stated otherwise in the data appendix
URL http://journals.openedition.org/eps/docannexe/image/12255/img-7.jpg
Fichier image/jpeg, 108k
Titre Figure 3: European subnational Total Fertility Rates statistics
Légende Note: 100 for the 1960 values
Crédits Source: own calculation
URL http://journals.openedition.org/eps/docannexe/image/12255/img-8.png
Fichier image/png, 35k
Titre Figure 4a: Relevance of geographic structures in the spatial organisation of European subnational TFR
Crédits Source: own calculation
URL http://journals.openedition.org/eps/docannexe/image/12255/img-9.png
Fichier image/png, 41k
Titre Figure 4b: Relevance of geographic structures within each other in the spatial organisation of European subnational TFR
Crédits Source: own calculation
URL http://journals.openedition.org/eps/docannexe/image/12255/img-10.png
Fichier image/png, 35k
Titre Figure 5: Subnational TFR convergence in Europe and in supranational groups
Légende Note: 100 for the TFR variance between NUTS-2 regions across Europe in 1960 Based on 21 countries (made up of a minimum of four NUTS-2 units). Central and Eastern: Bulgaria, Czechia, Hungary, Poland, Romania, Slovakia. German-speaking: Austria, Germnay (East and West), Switzerland. Nordic: Denmark, Finland, Norway, Sweden. Southern Europe : Greece, Italy, Portugal and Spain. Western: Belgium, France, the Netherlands, the United-Kingdom.
URL http://journals.openedition.org/eps/docannexe/image/12255/img-11.png
Fichier image/png, 43k
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Mathieu Buelens, « Recent changes in the spatial organisation of European fertility: Examining convergence at the subnational and transnational level (1960-2015) »Espace populations sociétés [En ligne], 2022/1 | 2022, mis en ligne le 01 mars 2022, consulté le 19 mai 2022. URL : http://journals.openedition.org/eps/12255 ; DOI : https://doi.org/10.4000/eps.12255

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Mathieu Buelens

PhD Student / Teaching assistant, Université libre de Bruxelles
matbuele[at]ulb.ac.be, CP 130/02, 50 Av. F. D. Roosevelt, 1050 Brussels - Belgium

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Espace Populations Sociétés est mis à disposition selon les termes de la licence Creative Commons Attribution - Pas d'Utilisation Commerciale - Pas de Modification 4.0 International.

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