Spatial continuities and discontinuities in two successive demographic transitions: Spain and Belgium, 1880-2010

This is a study of how the synergisms between cultural and structural factors, which played a major role during the historical fertility and nuptiality transition (first demographic transition or FDT), have continued to condition demographic innovations connected to the “second demographic transition” (SDT). The continuity or discontinuity from the “first” to the “second” demographic transition is studied for spatial aggregates over more than a century in two national contexts, i.e. Belgium and Spain. Special attention is paid to the role of successive secularization waves in shaping the geographical patterns of both transitions. The study also shows that the maps of the two aspects of the SDT, i.e. the “postponement” and the “non-conformism” transitions respectively, are shaped by different determinants. Explanations are offered using the “Ready, Willing, and Able” paradigm, which allows us to uncover the different conditioning and limiting factors involved. The “non-conformist” transitions (control of marital fertility during the FDT and rise of cohabitation and non-conventional family formation during the SDT) more closely mirror the history of secularization and the “Willingness” condition, whereas the fertility postponement aspect of the SDT mainly reflects female education and employment, or the “Readiness” condition. This generalization holds in both countries. However, in Belgium spatial continuity from FDT to SDT is connected to stable patterns of secularization, whereas in Spain it is linked to long standing differences with respect to female literacy and education. 1 Emeritus professor Vrije Universiteit (VUB), and Royal Academy of Sciences, Brussels. Support for his work in Barcelona came from AGUAR, Generalitat de Catalunya. E-mail: [email protected]. 2 Centre d’Estudis Demogràfics, Edifici E2, 08193 Bellaterra, Spain. Lesthaeghe & Lopez-Gay: Spatial continuities and discontinuities in two successive demographic transitions 78 http://www.demographic-research.org 1. Background Several books and articles belonging to the so-called “Princeton Fertility Project” (especially: Livi-Bacci 1971, 1977, Lesthaeghe 1977, Lesthaeghe and Wilson 1986) are often cited as “cultural” corrections or complements to the classic economic and structural interpretations that dominate studies of historical fertility decline. One of the sources of inspiration (if not the main one) of the Princeton Fertility Project was without doubt William Leasure’s doctoral dissertation (1962) on the Spanish fertility transition. In this thesis Leasure showed that the classic indicators of urbanization and industrialization largely failed to account for the regional diversity in Spain’s fertility decline, and that regional and linguistic particularisms prevailed. This convinced A. J. Coale that it would be worthwhile to extend this Spanish investigation to the rest of Europe. The “Princeton Project” gradually emerged as a result, not as a cohesive project with preconceived objectives, but as a mere collection of empirical contributions from a variety of authors. Most of the research belonging to the Princeton project was performed during the late 1960s and through the 1970s, and several other and similar investigations were conducted during the following decades, including major further major studies on Spain and Prussia (e.g., Reher and Iriso-Napal 1989, Galloway et al. 1994, Galloway 2009). Roughly 30 years after the completion of the Princeton studies, new demographic features have emerged with respect to household formation and fertility, and these are by now often collectively referred to as the “Second demographic transition” (SDT) (Lesthaeghe and van de Kaa 1986). The SDT has two main dimensions: (i) the “postponement transition”, referring to the upward shifts in ages at marriage and at first and subsequent births, and (ii) the “non-conformism transition”, pointing at the growth of unconventional forms of household formation (rise of cohabitation, of fertility among cohabitants, of single parent households, of same sex households, and of reconstituted families based on cohabitation). The succession of two waves of demographic innovation, referred to here as the first and second demographic transitions (FDT and SDT), begs the question of longterm spatial continuity (e.g., Lesthaeghe and Neels 2002). More specifically, the question is addressed as to whether or not the leading regions during the FDT innovation would also be the leading ones at the onset of the SDT. Spatial continuity from FDT to SDT would be testimony as to the persistence of such long-term regional subcultures, whereas discontinuity would be pointing at new and recent developments in the structural and cultural determinants of the SDT 3 . 3 It should be stressed that at no point do we extrapolate the results of our correlation analysis from the aggregate to the individual level. Hence, the “automatic” label of “ecological fallacy”, often mindlessly attached to all spatial analyses, would be misguided in this instance. Furthermore, a spatial analysis is, of Demographic Research: Volume 28, Article 4 http://www.demographic-research.org 79 In order to study the nature of cultural-structural synergisms over time and space, use will be made of A. J. Coale’s set (1973) of preconditions for innovation, otherwise known as the “Ready, Willing, and Able” trio (RWA). The empirical data will come from two countries: Belgium and Spain. Both countries are characterized by a high degree of both socio-economic and cultural (linguistic and political) heterogeneity, and hence they are ideal settings for studying regional (dis)continuities in demographic developments. Furthermore, we shall pay special attention to a reconstruction of the spatial aspects of secularization in both countries, as these are intimately linked to the willingness condition in the RWA framework. To sum up, the three objectives are: (i) to contribute to studies of historical continuity of demographic patterns; (ii) to obtain historical insights into the “genesis” of the SDT; (iii) to use the Boolean nature of the RWA paradigm to explain both continuities in some features and discontinuities with respect to others. 2. The RWA model of innovation and diffusion of new behavioral forms At the end of the Princeton European Fertility Project that studied the historical fertility and nuptiality transitions, A.J. Coale (1973) came up with a succinct and catchy formulation of the three preconditions for a demographic transition to occur. This clearly superseded the more detailed narratives offered by the Princeton project’s various country studies, but caught the gist of their findings. Firstly, according to Coale, any new form of behavior must yield benefits that outweigh the costs or disadvantages. If there is no such economic advantage (= “Readiness” or R), then that new form of behavior will not be attractive and there will not be a breakthrough. Secondly, the new form must be “legitimate”, i.e. it must be culturally and ethically acceptable. If the new form of behavior runs counter to prevailing beliefs or to religious or moral rules, then the condition of “Willingness” (=W) will not be met. Thirdly, there must be adequate means (e.g., of a technical or legal nature) to implement the new form. This is the course, not the only way to look at historical change, but, in our opinion, still a salient one. Firstly, regions have long histories and traditions or subcultures that developed over centuries, and as such they transcend the life span of individuals. Secondly, if firms or institutions can be compared, so can other aggregates such as geographical ones, provided that the results are interpreted at that level. Thirdly, it is not because some theoretical paradigms, such as rational choice theory in sociology or neo-classic micro-economics, have shifted the attention to the individual-level decision making process, that all social science research should become “atomistic” too, and thereby lose out dramatically on historical richness. Lesthaeghe & Lopez-Gay: Spatial continuities and discontinuities in two successive demographic transitions 80 http://www.demographic-research.org “Ability” condition (=A). The three preconditions must be met jointly for a success S (i.e. a breakthrough of a new behavioral form) to occur: S = R AND W AND A or S=RWA where AND is the logical “and” or conjunction. Any failure of satisfying merely one of the three conditions results in an overall failure, i.e., there will be no adoption or breakthrough or transition to that new behavioral form. In other words, there are three necessary conditions, but a single one is not sufficient. The model is not one with separate, additional effects, but a Boolean one focusing on synergistic combinations instead (cf. Ragin 1987). The RWA model can be specified at the micro level as well, and this will bring out a few extra features dealing with the dynamics of innovation processes in general and of demographic transitions in particular (Lesthaeghe and Vanderhoeft 1999). These will be explained now in greater detail. We assume that any individual or household i would have its own set of three scores for, respectively, Ri, Wi, and Ai. These scores range in intensity from zero to unity. Zero then means: no perceived advantage at all (R=0), not acceptable on moral, religious, or other cultural grounds (W=0), and no means of implementation (A=0). Unity corresponds to: numerous advantages completely outweigh any disadvantages (R=1), perfectly morally and culturally acceptable (W=1), and no technical or legal barriers (A=1). A score of 0.5 corresponds to a point of indecision. The condition for a success is satisfied when all three scores move beyond that mid-way point, and are hence larger than 0.5. Another way of stating this is that each individual or household has a minimum score MINi which is the smallest of the three component scores Ri, Wi, or Ai: MINi= Minimum(Ri,Wi,Ai) Hence, any actor will only adopt a new form of behavior if his MINi > 0.5. The collection of individual scores obviously forms three distributions, respectively, for R, W, and A, but the collection of individual minima will add a fourth distribution. This MIN distribution will of course depend on the location and shapes of the R, W, and A distributions, but its mean will always be lower than that of the other three. The example in Figure 1 clarifies this point (cf. Lesthaeghe and Vanderhoeft 1999). Demographic Research: Volume 28, Article 4 http://www.demographic-research.org 81 Figure 1: RWA model – examples of the location of the Ri, Wi, and Ai distributions together with that of the distribution of their minima (MINi) Note: Location of W (left), R (middle), and A (right) at one point in time (second example) and location of the distribution of the minimum (Ri, W i, Ai) (= dotted line). Note: Location of W (left), R (middle), and A (right) at one point in time (third example) and location of the distribution of the minimum (Ri, W i, Ai) (=dotted line). Lesthaeghe & Lopez-Gay: Spatial continuities and discontinuities in two successive demographic transitions 82 http://www.demographic-research.org In the first example, several cases have passed the 0.5 score on R or W or A, but nobody satisfies the RWA configuration where all three conditions are being met simultaneously. This can be seen from the distribution of minima, which does not have an upper tail that has moved beyond the 0.5 value. In the second example most actors know about proper ways of implementing the new form of behavior so that the distribution of A has already shifted to the right on the 0-1 intensity scale. With respect to readiness, the modal category is undecided (score 0.5) with half the population still not seeing a decisive advantage. But the majority in this example considers the new form of behavior as ethically or culturally unacceptable. The distribution of the scores that are the smallest of the previous three is located quite a bit further to the left than any of the other three distributions and only a small fraction has crossed the 0.5 point. Hence, few people have made a transition to a new form of behavior. In this example non-willingness obviously contributes disproportionately to the lower minima, and is therefore a dominant bottleneck factor or inhibitor. During a process of change, all four frequency distributions move from the low end to the high end of the intensity scale on the horizontal axis, with the distribution of the minima always trailing behind. The R, W, and A distributions can follow their own pace, and as they shift their variances will also tend to expand. At the outset variances are low since the vast majority has low scores on all distributions, and at the end of the transition variances will again diminish as more and more persons end up with high scores for every precondition. Mid-way, variances are the highest, and the same holds for the distribution of minima. Moreover, it is likely that at that time the MIN distribution also comes close to adopting a bell-shaped curve. If this occurs, then our RWA model will produce a growth curve of adopters of new behavioral forms that closely resembles Verhulst’s logistic curve (elongated S-curve). Many innovations and their diffusion, from gothic cathedrals to engines, from epidemics to rumors, follow such a logistic growth curve. Furthermore, the logistic curve for an older innovation tends to taper off and reach a saturation-level of no further expansion when new and better technologies or innovations start growing and replacing it. Also, the latest innovation can entirely wipe out the older pattern, and in this instance there is a new transition. And, if such transitions succeed each other, there is no problem with numbering them as a simple means of identification. So far we have treated the shifts in the distributions of R, W, and A as independent. This is not likely to hold. Structural or materialist determinists, for instance, would commonly argue that R is the leading condition and that W and A are mere lagging derivatives. In this view, material conditions change first and people adjust their behavior to such new circumstances and opportunities. Subsequently both morality and technology will come under increasing pressure to adapt as well. There are, of course, numerous examples where other sequences hold. Breakthroughs in Demographic Research: Volume 28, Article 4 http://www.demographic-research.org 83 contraceptive and reproductive technology, for instance, have opened up avenues for new interventions, and in this case A is the leading condition. Similarly, some cultures may have no objections to many forms of contraception and commonly accept abortion, and then the W-distribution will not be trailing behind the other two. To sum up, the sub-model with R being the leading condition and with cultural and/or technological lags may be frequently encountered, but it is by no means the only possibility. For each of the three diffusion patterns with respect to R, W, and A, we should expect there to be at least one focus of initial innovation from which the diffusion occurs until it meets social barriers. These barriers can be social class distinctions, cultural obstacles (e.g., religious differences), or communication barriers (e.g., linguistic borders). From that point on, socio-economic, cultural, and spatial variables observable at the macro level (e.g., for spatial units) will emerge as determinants of the process of differential spa t ia l diffusion (cf. Bocquet-Appel and Jakobi 1996). To sum up: at present we have a model of innovation based on Coale’s initial model of three preconditions and capable of producing a logistic growth curve for any new form of behavior. Each of the three preconditions can be “individualized” and translated back to the macro-level in the form of shifting distributions. Moreover, these shifts and especially differences in the pace of the shifts can be linked to mechanisms of social and spatial diffusion of the “contagion” type, in which network contacts are essential. Then social group and/or geographical patterns emerge in which innovating groups or regions lead the way, and in which others follow depending on the strength of various types of barriers. Such barriers can exist with respect to any of the three preconditions, but since the MIN-distribution in the RWAmodel is the crucial one, it suffices for only one of the three preconditions to be obstructed for the diffusion of the new behavioral form to be stopped or delayed at such a social or spatial barrier. This has important consequences: 1. Those in the vanguard of a transition must score high on all three conditions and this will set them apart from the others, for whom at least one condition is not being met. 2. Conversely, if one of the three distributions substantially lags behind the others, then many MIN-scores will be determined by the bottleneck condition, and the best correlates of the outcome will be indicators of that barrier. The final outcome of the use of the RWA model is that it expects both structural and cultural factors to emerge as correlates. The RWA specification leaves little room for disciplinary debates of the type “economics versus culture” (cf. Lesthaeghe 1998), or, by extension, for squabbles between economics, sociology, or political science. Lesthaeghe & Lopez-Gay: Spatial continuities and discontinuities in two successive demographic transitions 84 http://www.demographic-research.org Any one of these three can come up with strong “correlational” results, but the irony is that “victory” for a discipline can be claimed following the identification of a type of regressor (e.g., economic, structural, cultural...) with the largest and most significant coefficients, when in fact such statistical predictors could merely identify the slowest moving condition in an innovation and diffusion process 4 . The earlier types of analysis with “the buck stops at socio-economic structure” in sociology and social history and the subsequent “cultural turn” in the social sciences (see Sewell 2005, esp. chapters 1 and 2) just lead from one form of reductionist fallacy to another. The RWA model simply recognizes that processes of social change are the outcomes of (i) socio-economic structures with their specific configurations of opportunities and constraints AND (ii) of the adaptive capacity of cultural scripts of legitimation, AND (iii) of policies affecting the technical and legal environments. The AND is again the logical conjunction, and the factors that cause leads and lags over time can vary widely. Some configurations are remarkably recurrent ones, but others can indeed be totally “historically idiosyncratic”. 3. From the FDT to the SDT: The Belgian example revisited There are several reasons for revisiting the issue of historical spatial continuity in Belgium. The first one is that we now possess many more SDT indicators than could be used in the 2002 Lesthaeghe and Neels article. We owe this to Neels’ fertility reconstructions of 2006 for both cohorts and cross-sections on the basis of the 1990 census, and to the Gadeyne et al. reconstruction of cohabitation trends and differentials starting from a retrospective question in the 2001 census. The second reason is that Neels (2006) showed that the Belgian SDT has two components with different spatial patterns: marriage postponement and premarital cohabitation followed the older historical pattern of demographic innovation, but fertility postponement did not. Also, in the US there was a partial disconnection in the spatial incidence of the fertility postponement and the non-conformity dimensions of the SDT, respectively (Lesthaeghe and Neidert 2006). More specifically, the states in the lower half of the two distributions were the same, but those at the vanguard differed: the North Atlantic states were the leading ones with respect to fertility postponement, whereas several western and Pacific states were leaders with respect to cohabitation. 4 An example will elucidate this point. Suppose that everyone satisfies the R condition, but many would not satisfy the W and/or A conditions. The correlates of the outcome would be connected to W and A and not to R, since this is a constant. The fact that the R condition is already satisfied is of paramount importance for the subsequent development of the process (necessary condition), but indicators of R will not be significant in any correlation analysis, and they are likely to be dismissed as “unimportant”. Demographic Research: Volume 28, Article 4 http://www.demographic-research.org 85 Before turning to statistical analyses of the Belgian data, a short digression is necessary to elucidate the secularization history of the country. This history contains a few features that are essential to the understanding of the role of the W-factor and its relation to socio-economic structural determinants. 3.1 The three secularization waves in Belgium: 1750-1970 As in much of Western Europe, the first signs of secular, rationalist thinking emerged with the Enlightenment during the second half of the 18 th century. It was essentially an elite phenomenon (e.g., in Freemason lodges), but capable of being one of the driving forces of the Brabant Revolution of 1789, or the first attempt at establishing Belgian independence. This first wave of secularization gained much wider popular support during the French Revolution, and many urban parishes, especially in Liège, failed to observe the marriage ban during the so-called “closed periods” of Lent and Advent. Also, during the Napoleonic period and the period of reunification with the Netherlands (1815-1830), Catholicism remained under state control, but this did not imply that the secular ideas had penetrated in all regions of the country. As became very clear at the time of the Belgian independence in 1830 and with the concomitant Catholic restoration, numerous areas in the Dutch-speaking northern half of the country had remained staunchly loyal to Catholic clergy and doctrine. The early map of this first secularization wave can be constructed on the basis of the degree of non-observance of the marriage ban during Lent and Advent, i.e. the period of 40 days before Easter and the similarly “closed” period prior to Christmas (see maps 1, 2, and 3 for quintiles). The Napoleonic Civil Code had made a civil marriage obligatory and a church marriage optional. This remained so after Belgian independence, and hence the Catholic marriage ban was no longer an impediment for freethinkers or for couples in need of a “shotgun” wedding. The index used here is simply the percentage of marriages in March (approximation for Lent) and December (idem for Advent) divided by 2/12, or the proportion that would be observed without marriage seasonality. Hence, this MLA index equals 100 if no marriage ban is being observed, and becomes a much smaller number if the Church rules are being respected. For instance, during the last decade of the Austrian occupation the MLA index often comprised between 5 and 15 in Flemish parishes and around 20 in Walloon ones, meaning that the number of marriages was less than one fifth of the expected number for two months in the absence of seasonality. After the French takeover these indices typically increase to 30 50, and even exceed 100 for a few years in Liège (Lesthaeghe 1991: 276-279). Lesthaeghe & Lopez-Gay: Spatial continuities and discontinuities in two successive demographic transitions 86 http://www.demographic-research.org Map 1: Marriages during Lent and Advent (MLA-index) in Belgian arrondissements, 1841-1847 (quintiles) As the MLA map with quintiles shows for the period 1841-1846, the impact of the first secularization wave is markedly stronger for the Walloon or francophone arrondissements (see appendix, map A 1, for their identification) of the southern half of the country than for the Flemish ones to the north. Even more strikingly, the degree of non-observance of the ecclesiastic marriage ban is pronounced in many strictly rural Walloon arrondissements, with those of Arlon, Bastogne, Virton, and Neuchâteau having higher MLA values than the emerging industrial arrondissements of Charleroi and Mons. Similarly, other Walloon rural arrondissements match the Charleroi value, and these are Waremme, Nivelles, and Philippeville. A correlate of this rural secularization in Wallonia is the strong allegiance to the Liberal party, which did not only represent the freethinkers among the higher bourgeoisie, but also those among the wealthier artisans and farmers. By contrast there was no such strong rural Liberal support in Flanders, and only in the larger towns of Antwerp and Ghent was there a militant secular presence. A major point of dispute in the initial Belgian “two pillar” Demographic Research: Volume 28, Article 4 http://www.demographic-research.org 87 system (Catholic versus Liberal) was the staunch competition between the Catholic schools and the secular state or municipal schools. Jesuit and episcopal colleges of secondary education and the Catholic University of Louvain (reopened in 1830) produced the elites for the Catholic pillar, whereas the State universities of Ghent and Liège and the small Free(thinker) university of Brussels remained secular strongholds. After 1860 a third “pillar” was added, corresponding to the rising importance of the Socialist Party. This generated a second secularization wave in all major industrial and urban areas as well. The MLA map for 1860-1865 clearly shows how the three major Walloon industrial arrondissements (Mons, Charleroi, Liège) and the arrondissement of Brussels have MLA values in excess of 60, which is already indicative of a major weakening of the ecclesiastic ban. By 1881-1884 only five Walloon arrondissements have values below 60, whereas there are only two Flemish ones with values above 60. Map 2: Marriages during Lent and Advent (MLA index) in Belgian arrondissements, 1860-1865 (quintiles) Lesthaeghe & Lopez-Gay: Spatial continuities and discontinuities in two successive demographic transitions 88 http://www.demographic-research.org The double origin of secularization in Belgium before 1900 not only implies a leading position for Wallonia, but also that both rural and industrial or urban arrondissements are present in the upper half of the secularization distribution. In other words, there is only a modest positive correlation between secularization and industrialization/urbanization, which is a statistical bonus (low multicollinearity) when it comes to measuring the separate effects of secularization versus industrialization/urbanization upon, for instance, the speed of the marital fertility decline (Lesthaeghe 1977: 196-220; Lesthaeghe and Wilson 1986: 261-292). Map 3: Marriages during Lent and Advent (MLA index) in Belgian arrondissements, 1881-1884 (quintiles) Until the 1960s the map of secularization remains very stable in Belgium, as can be gleaned from the correspondence between the MLA map for 1881-1884, the map of the secular vote (% Socialist + Communist + Liberal) in 1919 (first elections based on universal male suffrage), the map for the secular vote in 1958, i.e. at the time of the last 1881-