Fertility and Education in a Longitudinal Perspective: Africa

Transcription

1 Paper prepared for the IUSSP Seminar Mumbay, January 2013 Past and Present. Revisiting the Demographic Transitions in the South Through Individual Longitudinal Data. Fertility and Education in a Longitudinal Perspective: Africa By Michel Garenne (1,2,3) [Draft] Affiliations: (1) Institut de Recherche pour le Développement (IRD), UMI Résiliences, Paris, France (2) Witwatersrand University, School of Public Health, Johannesburg, South Africa (3) Institut Pasteur, Epidémiologie des Maladies Emergentes, Paris, France Updated: October 26, 2012 Words: 2250 Abstract: 170 Tables: none Figures: 2 Contact: Michel.Garenne@pasteur.fr 1

2 Abstract The study builds on a reconstruction of cohort trends in level of education of women born since 1900 in 34 countries of sub-saharan Africa. It relates long term trends in level of education with long term trends in fertility for the whole period, for urban and rural areas separately. The DHS surveys conducted between 1990 and 2010 provided all the data, for levels and trends in education and for fertility levels and trends. Results indicate a very weak relation between trends in level of education and trends in female fertility. Both the onset and the speed of the fertility transition in Africa seems largely independent from levels and trends in education of fertile women, and this is true in urban areas as well as in rural areas. This finding based on longitudinal data contrasts with cross-sectional evidence relating period fertility with current level of education, where the relationship is straightforward. The discussion focuses on the complex relationships between longitudinal and cross-sectional data, and the nature and dynamics of the contemporary fertility transitions in African countries compared with those in Europe of the past. Key Words: Fertility Transition; Fertility decline; Longitudinal analysis; Level of education; Economic development; sub-saharan Africa 2

3 Introduction The fertility transition in Europe was a long and gradual process, lasting on average some 60 to 80 years, sometimes much more as was the case in France. The main modes of fertility control were traditional methods of contraception, in particular withdrawal (coitus interruptus) and spouse separation. Decisions about limiting family size were taken by married couples, within the family circle, and the state did not interfere with these behaviours. Comprehensive demographic studies documented the European fertility transition, in particular the Princeton Fertility Project. Among the main results of these studies was the lack of correlation between fertility trends and socio-economic factors. The fertility transition could occur at high or low level of income, at high or low level of urbanization, at high or low level of education, although most European populations were largely literate when the transition started. There were no thresholds in any socio-economic variable that was necessary for the transition. If countries starting their transition late (Ireland, Albania) were somewhat poorer than average, they underwent the same process at others which were more advanced. The comparison between France and the United Kingdom is probably the most convincing piece of evidence of the large independence between the fertility transition and economic development: England and Wales was more advanced than France in any socio-economic variable in the 18 th and 19 th century, but France started its fertility decline some 150 years before. [Coale & Watkins 1986; Van de Walle & Knodel 1980] Fertility decline in developing counties has a different rationale. It was mainly induced by outside interventions, from the state or from Non-Governmental Organizations (NGO s), which are bodies external to the married couple. The main modes of birth control were modern methods of contraception, such as the Intra-Uterine-Device (IUD), male and female sterilization, and various hormonal methods (pills, injectables, implants). Therefore, the dynamics of fertility decline could be influenced by a variety of factors, many of them external to the social dynamics within countries, in particular the financing of family planning programs from international organizations and foreign countries. Of course, with a few notable exceptions, people were free to accept -or reject- contraceptive methods, and this behaviour could be influenced by social factors. However, the history of the past 60 years shows that modern methods of contraception were most often welcome by people, independently of their social status and of the level of development of their own countries. [Casterline 1999; United Nations, 2007] 3

4 Sub-Saharan Africa is no exception to this general pattern, and family planning has reached virtually all places over the past 60 years. Of course, the up-take of modern contraception varies in time and space in Africa, and contraceptive prevalence tends to be lower than in Latin America and in Asia. Firstly, most African countries started to control their fertility later than most other developing countries; secondly the speed of fertility decline is somewhat slower than elsewhere; and thirdly the dynamics of fertility decline are quite different in urban and rural areas. All these dynamics seem highly related to family planning programs: in places where they were implemented early and efficiently, fertility decline appeared early and was fast, whereas in places where access to modern contraception remained limited or difficult, in particular in remote rural areas, fertility decline was late, slow, or sometimes had not yet started. [Blacker 2007; Caldwell et al. 1992; Caldwell 1994; Camlin et al. 2004; Cleland et al and 2007; Cohen 1998; Gaisie 1996; Garenne & Joseph 2002; Garenne et al. 2007; Garenne 2008; Gould & Br own 1996; Kirk & Pillet 1998; Lestaeghe & Jolly 1995; Lindstrom & Woubalem 2003; Mbacke 1994; Mostert et al. 1988; Moultrie & Timaeus 2003; Ngom & Fall 2005; Ross et al. 2005; Shapiro & Gebreselassie 2008; Shemeikka et al. 2005; Swartz 2003; UN-ECA 2001; van de Walle & Foster 1990] The relationship between fertility level and level of education was studied in numerous occasions, including in Africa, but essentially in a cross-sectional perspective. All these studies indicate that during the course of the transition, more educated women have lower fertility (i.e. are more advanced in the transition) than less educated women at a given point in time. [Adamchak & Ntseane 1992; Bongaarts 2010; Caldwell 1980; Caldwell et al. 1992; Casterline 1985; Castro-Martin 1995; Chimere-Dan 1993; Cleland & Rodríguez 1988; Cochrane 1979; Garenne 2012; Jejeebhoy 1995; Kravdal 2002; Lloyd et al. 2000; NRC 1999; Rose 1995; Rustein 2002; Shapiro 2011; Singh & Casterline 1985; United Nations 1995] An open question remains for better understanding the dynamic processes: whether the level of education, particularly low in Africa, played or did not play- a role in these fertility dynamics. Is a medium or high level of education a pre-requisite for fertility decline? Is the fertility transition faster when the level of education is higher? The aim of this paper is to explore the relationship between fertility transition and changes in modern education in Africa. The approach is essentially a longitudinal perspective, and different from the classical cross-sectional approach which invariably shows a high correlation between level of education at time (t) and fertility level. Indeed, as was the case in 4

5 Europe in the late 19 th and early 20 th century, cross-sectional differentials do not imply causality in a longitudinal perspective. This paper addresses this issue in a systematic way, by exploring the dynamics in fertility levels and in level of women s education in 34 sub-saharan countries from 1950 to Data and Methods The data utilized for this study were provided by the Demographic and Health Surveys (DHS) and related surveys conducted on the same model: AIDS Indicators Surveys (AIS) and Service Provision Assessments surveys (SPA). Data on level of education were drawn from the individual files of 79 DHS, 4 AIS, and 1 SPA. These surveys provide the level of education of all residents in the surveyed households, by age and sex, which allow one to reconstruct female cohort levels of education. Data on fertility level were drawn from the women s files of 92 DHS surveys. These surveys provide full maternity histories of women aged years at time of survey, which allow one to reconstruct cohort and period levels of fertility. Altogether, the fertility and education data cover some 34 countries in sub-saharan Africa for the period. Period level of education For computing the period level of education, the cohort level of education was first calculated from individual data for all yearly cohorts born between 1900 and The level of education was calculated as the Average Years of Schooling (AYS). Then, an age pattern of fertility was calculated and fitted with a spline curve, following the method proposed by Schmertmann [2003]. Lastly, the period level of fertility was computed as the product of the cohort female level of education by the age pattern of fertility. This value provided the precise period level of education of women who delivered. All these calculations were done for each of the 34 countries, for each calendar year from 1950 to 2005, and for urban and rural areas separately. More details on the method can be found elsewhere. [Garenne, 2012] 5

6 Period level of fertility For computing the period level of fertility, the age specific fertility rates were calculated for each of the 10 years preceding each survey. Overlapping years from different surveys were combined by adding corresponding births and person-years. Age specific fertility rates were added up to age 40, then extrapolated to TFR by applying a standard age pattern of fertility (90% of total fertility occurred before age 40). Here again, all the calculations were completed for each of the 34 countries, for each calendar year from 1950 to 2005, and for urban and rural areas separately. More details on the method can be found elsewhere. [Garenne, 2008] Relationship between trends in fertility and trends in education Once the series were fully reconstructed, the relationship between the fertility transition and changes in level of education was investigated by simple cross-tabulations and correlations. For each country and for each area of residence, the date of the onset of fertility decline was identified, when applicable (rural areas of a few countries have not yet started their fertility decline). Then the speed of the fertility transition was calculated as the first derivative on time, that is the decline in mean number of children per woman per decade. These data were correlated with the level of education of delivering women and with the change in level of education over the period of fertility decline. Results Level of education and onset of fertility decline The dates of onset of fertility decline ranged from 1955 to 1987 for urban areas (all 34 countries), and from 1965 to 2000 for rural areas (for 29 countries, since 5 countries were excluded). The average level of education was 2.7 AYS at time of onset of fertility decline in urban areas (year 1971 on average), and 1.7 AYS at time of onset of fertility decline in rural areas (year 1981 on average), which are very low values. At these levels of education, a majority of women are still illiterate or have not completed primary school (77% in urban areas, 86% in rural areas). The correlation between level of education and the time of onset of 6

7 fertility decline was negative and significant, meaning that countries with higher level of education had an earlier fertility transition. The correlation coefficient was in urban areas, and in rural areas. However, the overall correlation hides large differences by country. For instance, even at low level of education (say AYS= 2), the time lag between dates of onset of fertility decline of earlier and later starters could be as high as 30 years. If most early starters (onset < 1965) had a relatively high level of education (AYS > 4), this was not the case for Rwanda, urban (onset in 1963, AYS = 2.3), and a few others. Likewise, if most countries with very low level of education in started late (after 1980), some started somewhat earlier, as Niger, urban (onset in 1972, AYS= 0.5). On average, an increase in 3 years in AYS leads to a 12-year earlier onset of fertility decline, which corresponds on average to improvements in education made over 33 years in Africa. Above all, this correlation seems to mean that countries which were more advanced in the development of their education systems were also more advanced in family planning and in their fertility transition. (Figure 1) Level of education and speed of fertility decline The speed of fertility decline ranged from 0.49 to 2.0 children per decade in urban areas, and from 0.14 to 2.3 children per decade in rural areas. There were no significant correlations between the speed of fertility decline and the level of education of mothers at time of onset: coefficient of correlation = 0.02 in urban areas and 0.11 in rural areas, none being significantly different from zero. If anything the correlation coefficient was slightly negative, meaning that countries with higher level of education had a rather slower transition, probably because they started earlier. Even at low level of education one could find a fast fertility decline, as in Ethiopia, urban (level of education= 1.1 AYS; speed= 1.9 children per decade), and even at high level of education one could find a slow fertility decline, as in Congo-Kinshasa (level of education= 5.0 AYS; speed= 0.7 children per decade). This result might seem surprising at first glance, but it clearly indicates that numerous factors other than education operate to speed-up or slow-down the fertility transition. (Figure 2) 7

8 Discussion Longitudinal versus cross-sectional This study shows above all that very different conclusions could be reach while considering longitudinal data rather than cross-sectional data. Indeed, all DHS surveys show that the gradient of fertility level by mother s level of education is strong and always negative, meaning that more educated women have a lower fertility at a given point in time. But this does not imply that countries with higher level of education have a different behaviour than others. Indeed, if the fertility transition occurs the same way in all social groups defined by level of education, but with a time lag, the cross-sectional data will reveal fertility differentials at any point in time during the transition, whereas the phenomenon remains the same for all social groups, and in particular the speed of the transition. In this case, one is likely to find a negative correlation with the timing of the transition, but not with the speed, as shown by empirical data. Timing of the transition and family planning programs The timing of the fertility transition in Africa seems mostly determined by the installation of family planning programs and family planning clinics. There is no documented case of fertility decline without- or preceding- modern family planning in African countries, with the exception of populations of European origin living in Southern Africa, who followed a European pattern of fertility control. Family planning with modern methods of contraception was introduced gradually in Africa, firstly through a small group of private practitioners, then by family planning clinics ran by NGO s affiliated to IPPF or similar organizations, then by national family planning programs. It is clear that more countries with a higher level of education, which were also the most advanced socially and economically, tended to have an earlier onset of centres providing modern contraception, and this is probably why they also had an earlier onset of fertility transition. However, even countries with low level of education started to control their fertility whenever family planning was introduced. Caldwell and colleagues argued for a long time that fertility decline would not occur in Africa until the level of education is high enough, at least with universal primary schooling. [Caldwell 1980] This argument was largely speculative and based on cross-sectional data. In contrast, longitudinal data showed the opposite, that is that both processes are largely 8

9 independent. Increasing level of education is determined by investments in schools and teachers, mainly from national sources, whereas fertility decline is determined by investments in family planning, mainly from international sources. Both may occur at about the same time, but not necessarily. Both may be proportional, following wide range social policies, but both may be independent, especially when financing for family planning comes mainly for foreign sources. This study revealed that despite different dynamics and different rationale in Africa compared with Europe, still the relationship between fertility decline and socio-economic factors, such as level of education, remained loose in Africa, as was the case in Europe. The fertility transition started in Europe when primary education was becoming almost universal, whereas it started in Africa at much lower levels. This is one more piece of evidence of the large independence between the two processes, whatever the rationale of the fertility dynamics. 9

10 Acknowledgment The author would like to acknowledge the support of USAID, ORC-Macro and ICF- International to the studies on trends in level of education and on trends in fertility in sub- Saharan Africa. 10

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14 Figure 1. Correlation between date of onset of fertility decline and level of education of fertile women in , 34 African countries Date of onset Average Years of Schooling in

15 Figure 2. Correlation between speed of fertility decline and level of education of fertile women at onset, 34 African countries Speed (TFR per decade) Average Years of Schooling at onset of fertility decline 15