After having stalled in the 1990s, fertility in Rwanda resumed its downward trajectory between 2005 and 2010. The total fertility rate declined from 6.1 to 4.6 and modern contraceptive use increased. However, it is unclear which determinants lay behind the previous stall and the recent strong drop in fertility. This paper contributes to an ongoing debate on the impact of social upheavals on fertility decline. We use a decomposition analysis, focusing on the change in characteristics and reproductive behaviour of women and their contributions to levels of fertility during 1992–2000 and 2000–2010. Results show that due to widowhood and separation the proportion of women who were married decreased between 1992 and 2000, but their fertility increased in the same period due to replacement fertility and an unmet need for family planning. After 2000, postponement of marriage and lower infant mortality contributed to lower fertility, but the most important effect is the overall lower fertility due not only to improved family planning provision but perhaps also to the sensitizing campaigns of the Rwandan government.
Rwanda is a recent success story of rapid fertility decline in Sub-Saharan Africa. The total fertility rate (TFR) dropped from 6.1 children per woman in 2005 to 4.6 in 2010. The use of modern contraception among women living in a union increased from 10 to 45% in the same period. This impressive decline came after a period of stalled fertility levels in the 1990s, like many other countries in Sub-Saharan Africa [
A detailed analysis of the causes that contributed to changes in fertility in Rwanda, and the extent of their impact, is beyond the scope of this paper. We focus rather on changes in the composition (endowments) of the female population and in their reproductive behaviour (effects) and the contributions of both sources to the level of fertility. We will distinguish two periods in the analysis: the period of limited change in the TFR, using available data from the Rwanda Demographic and Health Surveys of 1992 and 2000, and the period of the recent decline, for which we use the RDHS of 2000 and 2010. To present a clear picture of the changes in the effect of selected explanatory variables on fertility, we use a decomposition analysis. This method allows a comparison between two different periods. It also expresses the contributions of all the included explanatory variables in terms of changes in composition and in terms of the change in the effects of those characteristics [
The Rwandan context differed substantially during the two periods under study. The 1990s are on record as a black page in Rwanda’s recent history, marked by civil war, genocide, mass movements of refugees, and economic deterioration. The first decade of the new millennium can be characterized by an impressive improvement and recovery of the political and economic situation of the country. For that reason we start with an overview of the relevant background followed by a presentation of the theoretical framework based on results from other studies on the relation between changes in socioeconomic contexts and fertility.
Rwanda is still a poor country with an economy based on agriculture. Its Human Development Index, however, improved impressively from 0.313 in 2000 to 0.425 in 2010. During the 1980s and 1990s the country’s development was hampered by political tensions, environmental stress, and economic deterioration. The Rwandan civil war and genocide (1994) came not out of the blue but were rooted in the country’s historical, colonial, political, and economic experience. Conflicts were already in place before the achievement of Independence in 1962 (after the 1959 revolution, when Hutu deposed the Tutsi elite, thousands of Tutsi were killed and hundreds of thousands fled the country for the first time. Again in 1963 and 1973 large numbers of Tutsi became exiles as a result of ethnic violence and oppression. These refugees were the so-called “old-case load of Rwandans living in exile,” as defined during the negotiations in Arusha in the early nineties) and have continued ever since [
Economic stress characterised the prelude of the social upheaval. During the late 1980s Rwanda suffered from a severe economic crisis that deteriorated the living conditions of its people. That profound economic crisis has been linked with the decline of fertility between 1983 and 1992, when the total fertility rate fell from 8.3 to 6.2 and the desired family size from 6.3 to 4.2 children per woman [
After the war and genocide in 1994, food production fell drastically, the public service infrastructure of the country was severely disrupted, and large numbers of the population were on the move. Around two million Rwandans (political leaders, the army, the “Interahamwe” civilian militia, and ordinary civilians who participated in the killings of Tutsi and even some kidnapped women) sought protection in refugee camps in neighbouring countries, while another million became internally displaced persons [
The gravity of all these disruptive events had far-reaching consequences in other fields of society and politics as well as those related to demography. Firstly, the composition of the population by sex and age had changed. The Rwandan society feminized as substantially more men than women died in battle actions or fled the country [
Secondly, the population policy that started after 1981 under donors’ pressure to tackle the high rate of population growth (family planning was not among the priorities of the Habyarimana regime [
The fundamental change in Rwandan development began in 2000-2001 with the creation of Vision 2020, through a broad-based, participatory consultative process. The development strategy presented as Vision 2020 aimed at the reconstruction of the nation, its social capital, and its regional and global integration, which were seen as mandatory for sustainable development [
In general theories on fertility decline, fertility is linked to gradual, fundamental, and structural changes in a society. Disrupting events like wars and revolutions can have a temporary, disruptive effect on the course of the decline as is shown in analyses using historical or contemporary data. Examples of a temporary drop in births followed by a rebound shortly after the disrupting events as a result of the reunification of spouses and of resumed celebrations of marriages leading to more conceptions in the year after are found in cases all over the world [
After the disrupting events or in case the turmoil continues for a longer period, the fertility level can follow various courses. The fertility decline might stall or even go in an opposite direction as observed among Iranian and Palestinian couples in the cases of conflicts in the Middle East [
The impact of a social upheaval on demography depends on the phase of the crisis. During each stage of the conflict demographic behaviour will be influenced by voluntary as well as involuntary forces. Randall [
We assume that actual fertility levels are an outcome of fertility preferences and fertility control and that the severe social upheavals in Rwanda that occurred in the early nineties affected both. Following Caldwell [
Most births in Rwanda occur in formal unions; births outside wedlock are rare. Consequently, the disruption of family cohesion, deferred marriages, or separations due to death or migration as a result of the disturbing events have played an important role in decreasing the fertility during or shortly after 1994 as the proportion of married couples decreased. The breakdown of reproductive health facilities will have an opposite effect, just as coerced sexual intercourse. Early marriages [
Fertility preferences will also change in the wake of disruptive events. Probably as a result of the loss of children or other family members during the 1990s, the desired family size increased temporarily. The change in ideal number of children women would like to have during their reproductive life between 1992 and 2000 is particularly the result of higher percentages of women wanting five children or more as this proportion went, respectively, from 33.5% to 51.6% (RDHS 1992, 2000). The sensitizing campaign by the Rwandan government proclaimed three children as the ideal family size. The effects of such campaign are hard to measure, but the fact is that the proportion of women whose ideal number is five children or more decreased substantially to 12.5% in 2010.
This may end up changing the actual fertility.
We used three Rwanda Demographic and Health Surveys (RDHS) of 1992, 2000, and 2010 that include data on women aged 15 to 49 years old. The quality of DHS data in collaboration with Macro International has greatly improved since the 1980s and all the country reports have tables on data quality assessment [
We excluded women aged 15–19 from the analysis as they were either too young or not sexually active to change the general trend in actual fertility outcomes. The remaining samples included 5079 women for RDHS 1992, 7694 women for RDHS 2000, and 10708 women for RDHS 2010.
In defining the outcome variable we started with the total number of pregnancies that occurred during the 24-month period prior to the surveys which resulted in a birth and the pregnancies recorded at the moment of the interview. However, the low number of women who had more than one pregnancy in these two years led us to transform this dependent variable into a dummy variable of either yes or no (experience of a pregnancy during 24 months before the interview) as an indicator of actual fertility.
The explanatory variables of interest that are likely to influence the number of pregnancies women had in this period are marital status, whether or not the woman experienced the death of one or more children, the number of living children they had before our observation period, and the contraceptive use at the moment of the interview. Woman’s age, education, and place of residence were used as control variables. All these variables are used in order to decompose the changes in fertility between the two periods and isolate the contribution of the change in the composition of the population from the change which is due to shifts in the behaviour of the population.
As we are interested in identifying characteristics that may explain the difference in actual fertility between 1992 and 2010 in Rwanda, the appropriate technique is the decomposition analysis. We used the Oaxaca decomposition model in STATA (version 11.2). This method allows the decomposition of changes over time in levels of an outcome variable into those due to differences in observable characteristics (
The Oaxaca module in STATA enables us to distinguish clearly the part of the difference in actual fertility between 1992 and 2000 on the one hand and 2000 and 2010 on the other hand explained by compositional effects (endowments), by behavioural effects (coefficients), and by combined interaction effect.
Tables
Percentage of women aged 20–49 according to selected characteristics and change between 1992 and 2000 and between 2000 and 2010, respectively.
Variable | Category | 1992 | 2000 | Change | 2000 | 2010 | Change |
---|---|---|---|---|---|---|---|
Marital status | Never married | 15.3 | 14.6 | −0.7 | 14.6 | 23.0 | +8.4 |
In a union | 72.0 | 62.1 | −9.9 | 62.1 | 63.2 | +1.1 | |
Widowed | 5.2 | 10.7 | +5.5 | 10.7 | 6.9 | −3.8 | |
Separated | 7.4 | 12.6 | +5.2 | 12.6 | 6.8 | −5.8 | |
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Child mortality | None | 83.1 | 76.7 | −6.4 | 76.7 | 91.5 | +14.8 |
One or more | 16.9 | 23.3 | +6.4 | 23.3 | 8.5 | −14.8 | |
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Number of living children 24 months prior to the interview | 0–2 | 51.9 | 56.7 | +4.8 | 56.7 | 59.2 | +2.5 |
3 | 12.4 | 12.0 | −0.4 | 12.0 | 12.3 | +0.3 | |
4 | 10.8 | 10.2 | −0.6 | 10.2 | 10.6 | +0.4 | |
5+ | 25.0 | 21.0 | −4.0 | 21.0 | 17.9 | −3.1 | |
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Contraceptive use | Not using | 82.7 | 90.4 | +7.7 | 90.4 | 64.2 | −26.2 |
Folkloric/traditional | 6.6 | 5.2 | −1.4 | 5.2 | 4.2 | −1.0 | |
Modern | 10.7 | 4.4 | −6.3 | 4.4 | 31.7 | +27.3 | |
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Woman’s age | 20–24 | 24.5 | 24.5 | 0 | 24.5 | 25.2 | +0.7 |
25–29 | 20.6 | 20.5 | −0.1 | 20.5 | 23.3 | +2.8 | |
30–34 | 20.3 | 16.3 | −4.0 | 16.3 | 17.0 | +0.7 | |
35–39 | 14.6 | 15.4 | +0.8 | 15.4 | 13.3 | −2.1 | |
40–44 | 12.1 | 13.4 | +1.3 | 13.4 | 10.8 | −2.6 | |
45–49 | 7.8 | 9.9 | +2.1 | 9.9 | 10.4 | +0.5 | |
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Education level | No education | 42.9 | 34.5 | −8.4 | 34.5 | 18.9 | −15.6 |
Primary | 49.7 | 54.2 | +4.5 | 54.2 | 67.1 | +12.9 | |
Secondary/high | 7.4 | 11.3 | +3.9 | 11.3 | 13.9 | +2.6 | |
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Place of residence | Urban | 6.2 | 16.1 | +9.9 | 16.1 | 15.0 | −0.9 |
Rural | 93.8 | 83.9 | −9.9 | 83.9 | 85.0 | +2.1 | |
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Total | 100% | 100% | 100% | 100% | |||
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Number of women | 5079 | 7694 | 7694 | 10708 |
Percentage of women that were pregnant in the last 24 months and odds ratios by selected characteristics (1992, 2000, and 2010).
Variable |
Category |
1992 | 2000 | 2010 | 2000/1992 | 2010/2000 |
---|---|---|---|---|---|---|
% | % | % | OR | OR | ||
Marital status | Never married | 6.1 | 5.4 | 8.8 | 0.89 | 1.63 |
In a union | 52.2 | 59.6 | 38.7 | 1.14 | 0.65 | |
Widowed | 13.0 | 11.4 | 7.7 | 0.88 | 0.68 | |
Separated | 21.8 | 19.8 | 22.4 | 0.91 | 1.13 | |
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Woman’s child mortality experience | None | 40.0 | 39.6 | 28.0 | 0.99 | 0.71 |
One or more | 45.2 | 47.8 | 34.0 | 1.06 | 0.71 | |
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Number of living children 24 months prior to the interview | 0–2 | 42.3 | 44.8 | 32.8 | 1.06 | 0.73 |
3 | 49.3 | 45.5 | 29.7 | 0.92 | 0.65 | |
4 | 42.0 | 41.2 | 22.1 | 0.98 | 0.54 | |
5+ | 33.3 | 30.7 | 17.4 | 0.92 | 0.57 | |
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Contraceptive use | Not using | 43.7 | 41.6 | 31.3 | 0.95 | 0.75 |
Folkloric/traditional | 33.4 | 41.8 | 27.5 | 1.25 | 0.66 | |
Modern | 23.4 | 41.0 | 23.0 | 1.75 | 0.56 | |
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Age | 20–24 | 39.1 | 43.4 | 30.1 | 1.11 | 0.69 |
25–29 | 53.3 | 56.9 | 41.3 | 1.07 | 0.73 | |
30–34 | 51.1 | 53.0 | 35.9 | 1.04 | 0.68 | |
35–39 | 41.9 | 41.4 | 25.0 | 0.99 | 0.60 | |
40–44 | 25.7 | 27.0 | 15.3 | 1.05 | 0.57 | |
45–49 | 8.6 | 6.5 | 2.5 | 0.76 | 0.38 | |
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Education level | No education | 41.1 | 39.3 | 26.5 | 0.96 | 0.67 |
Primary | 42.0 | 43.8 | 30.9 | 1.04 | 0.71 | |
Modern | 31.7 | 37.4 | 19.9 | 1.18 | 0.53 | |
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Place of residence | Urban | 33.0 | 36.4 | 24.4 | 1.10 | 0.67 |
Rural | 41.4 | 42.5 | 29.3 | 1.03 | 0.69 | |
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Total number of women | 5079 | 7694 | 10708 |
During the period of the genocide and its aftermath changes occurred in the marriage and cohabitation patterns.
The percentage of women being widowed or separated is much higher in 2000 than in 1992 and the percentage of women in a union, which are more at risk of becoming pregnant, is much lower. These changes are expected to have a negative effect on total fertility rates. After 2000 the composition of the female population according to marital status changed again. Most striking is the increase in percentage of never married women, which is due to the skewed sex ratio and a practice of later marriage.
Based on the fact that the procreation behaviour of a couple may be influenced by mortality experience [
The change in percentages of women using contraception also changed remarkably during the two study periods. The use of contraception was still limited in 1992, but the situation deteriorated further and in 2000 only a very limited number of women used effective modern methods. However in 2010 (Table
The percentage of women being pregnant in the last 24 months prior to the date of the interview did hardly change between 1992 and 2000 in line with the expected stall in fertility decline in this period. Yet, there are marked differences in behaviour between categories. The (smaller) category of women in a union had far higher odds of being pregnant in 2000 than in 1992 (the odd ratio is 1.14—see Table
The effect of losing children also changes over time. Women that had lost at least one child in the seven years before 2000 have higher odds to be pregnant again at the time of the interview in 2000 than the same categories in 1992 and 2010. This might indicate that the cause of the death (more violent deaths in the period of the genocide, few violent deaths after 2000) affects the decision of replacement.
A striking result is the change in percentage of pregnant women that use contraceptives. In 1992 the ones that use a method (in particular modern method) have lower odds of being pregnant. Yet in 2000 there is no difference in actual fertility between women that are not using and those that were using contraception regardless of the type of method applied. In 2010 contraceptive use is much more effective again in avoiding pregnancies, leading to a double effect on actual fertility of both wider (Table
For the period between 2000 and 2010 there is a remarkable change in terms of actual fertility as the number of pregnancies in the last 24 months for all women went down (all odd ratios are lower than 1) except for never married women and for separated women. This fact may indicate that social control on fertility behaviour is diminishing. A more in-depth analysis using a multivariate decomposition may bring more clarity in the contribution of each explanatory variable in terms of compositional or behavioural effects.
The overall difference in actual fertility between 1992 and 2000 displays a relatively limited increase from 40.9 to 41.6 percent (the logit model produces proportions rather than percentages. We multiplied all coefficients by 100 for ease of interpretation and refer to it as percentages). The difference in the mean between the two years is very small and not significant. However, this is a composite of a negative effect of the net compositional change and a positive effect of the net behavioural change. Stated differently, if the composition of the female population had remained the same between 1992 and 2000, fertility would have been 2.5 percent-points higher. If the behaviour had not changed, fertility would have been 5 percent-point lower. The latter effect is partly compensated by the interaction between the endowments and the coefficients (Table
Mean value of fertility predicted between 1992 and 2000.
Overall | Coef. (×100) | Sig. |
---|---|---|
Group 1: 2000 | 41.553 | 0.000 |
Group 2: 1992 | 40.865 | 0.000 |
|
||
Total difference | 0.688 | 0.459 |
Difference due to endowments | −2.543 | 0.000 |
Difference due to coefficients | 4.948 | 0.000 |
Difference due to interaction | −1.717 | 0.000 |
A closer look at the (multivariate) parameters reveals which categories contribute most to the opposing shift in actual fertility between the years.
The category of currently married women displays the highest share in explaining the fertility gap from endowments (Table
Contribution of selected explanatory variables to the gap in actual fertility outcomes between 1992 and 2000.
Endowments | Coefficients | Interaction | ||||
---|---|---|---|---|---|---|
Coef. (×100) | Sig. | Coef. (×100) | Sig. | Coef. (×100) | Sig. | |
Marital status | ||||||
Never married | 0.226 | 0.273 | −0.114 | 0.867 | 0.004 | 0.867 |
In a union | −2.764 | 0.000 | 4.701 | 0.027 | −0.478 | 0.004 |
Widowed | 0.007 | 0.960 | −0.255 | 0.281 | −0.196 | 0.265 |
Separated | 0.137 | 0.183 | −0.070 | 0.784 | −0.036 | 0.787 |
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Child mortality | ||||||
No death | 0.031 | 0.522 | −3.397 | 0.007 | 0.194 | 0.006 |
One or more | 0.031 | 0.522 | 0.690 | 0.007 | 0.194 | 0.006 |
Living children | ||||||
0−2 | −0.147 | 0.026 | −1.959 | 0.116 | −0.136 | 0.130 |
3 | 0.004 | 0.655 | 0.158 | 0.624 | −0.003 | 0.728 |
4 | −0.001 | 0.921 | 0.250 | 0.392 | −0.011 | 0.507 |
5+ | −0.166 | 0.007 | 0.045 | 0.944 | −0.005 | 0.944 |
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Contraceptive use | ||||||
Not using | 1.002 | 0.000 | −6.837 | 0.000 | −0.474 | 0.001 |
Folkloric & traditional | 0.023 | 0.321 | −0.202 | 0.325 | 0.032 | 0.348 |
Modern methods | 0.717 | 0.000 | 1.216 | 0.001 | −0.530 | 0.001 |
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Age | ||||||
20−24 | 0.001 | 0.997 | 1.473 | 0.086 | 0.000 | 0.997 |
25−29 | −0.021 | 0.868 | 0.923 | 0.126 | −0.004 | 0.868 |
30−34 | −0.432 | 0.000 | 0.078 | 0.878 | −0.011 | 0.878 |
35−39 | 0.008 | 0.521 | −0.347 | 0.366 | −0.013 | 0.496 |
40−44 | −0.152 | 0.055 | −0.067 | 0.859 | −0.005 | 0.860 |
45−49 | −0.744 | 0.000 | −0.624 | 0.172 | −0.122 | 0.138 |
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Intercept | 8.616 | 0.002 |
Controlled for education and place of residence.
After controlling for the endowment effect, the coefficient effect becomes more pronounced (Table
The coefficient effect of child mortality is negative for those not having lost children and positive for the ones that did, indicating that without the (violent) deaths fertility would have been lower and that replacement was more common in the period leading to 2000.
The comparison between the level of actual fertility in 2000 and the one in 2010 displays a completely different structure with an overall drop in fertility of 13 percent-points due to the endowment effects and the coefficient effects plus negative interaction effects of the two (Table
Mean value of fertility predicted between 2000 and 2010.
Overall | Coef. (×100) | Sig. |
---|---|---|
Group 1: 2010 | 28.549 | 0.000 |
Group 2: 2000 | 41.553 | 0.000 |
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||
Total difference | −13.004 | 0.000 |
Difference due to endowments | −5.226 | 0.000 |
Difference due to coefficients | −3.213 | 0.000 |
Difference due to interaction | −4.566 | 0.000 |
As regards endowment effects (Table
Contribution of selected explanatory variables to the difference in actual fertility outcomes between 2000 and 2010.
Endowments | Coefficients | Interaction | ||||
---|---|---|---|---|---|---|
Coef. (×100) | Sig. | Coef. (×100) | Sig. | Coef. (×100) | Sig. | |
Marital status | ||||||
Never married | −2.552 | 0.000 | 0.635 | 0.275 | 0.353 | 0.255 |
In a union | 0.350 | 0.147 | −6.532 | 0.006 | −0.112 | 0.161 |
Widowed | 0.119 | 0.074 | 0.223 | 0.600 | −0.075 | 0.588 |
Separated | −0.112 | 0.147 | 0.515 | 0.156 | −0.227 | 0.153 |
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Child mortality | ||||||
No death | −0.478 | 0.000 | 2.907 | 0.015 | 0.539 | 0.012 |
One or more | −0.478 | 0.000 | −0.884 | 0.015 | 0.539 | 0.012 |
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Living children | ||||||
0–2 | −0.136 | 0.007 | 6.500 | 0.001 | 0.273 | 0.009 |
3 | −0.001 | 0.762 | −0.114 | 0.679 | −0.003 | 0.737 |
4 | 0.007 | 0.488 | −0.649 | 0.023 | −0.024 | 0.440 |
5+ | −0.134 | 0.004 | −0.869 | 0.113 | 0.126 | 0.110 |
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Contraception use | ||||||
Not using | −1.821 | 0.000 | 7.856 | 0.002 | −2.187 | 0.000 |
Folkloric & traditional | 0.037 | 0.048 | 0.226 | 0.163 | −0.042 | 0.184 |
Modern method | −0.903 | 0.045 | −0.573 | 0.001 | −3.411 | 0.000 |
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Age | ||||||
20–24 | 0.152 | 0.328 | −0.464 | 0.532 | −0.012 | 0.592 |
25–29 | 0.536 | 0.000 | −0.272 | 0.608 | −0.036 | 0.599 |
30–34 | 0.077 | 0.226 | 0.112 | 0.759 | 0.005 | 0.770 |
35–39 | 0.011 | 0.658 | 0.672 | 0.067 | −0.086 | 0.117 |
40–44 | 0.309 | 0.000 | 0.560 | 0.157 | −0.105 | 0.179 |
45–49 | −0.171 | 0.373 | −0.598 | 0.204 | −0.025 | 0.484 |
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Intercept | −13.457 | 0.000 |
Controlled for education and place of residence.
Regarding the coefficient effects between 2000 and 2010 we see that there is an overall shift towards lower fertility (the intercept is −13.5). Opposed to the period 1992–2000 the women in a union are now much less inclined to become pregnant. The large drop in fertility was even larger in this group. The replacement effect also switches, indicating that women tend less to remedy the loss of a child by another pregnancy in 2010 compared to 2000, which is consistent with the opposed finding in the period 1992–2000.
There are two major exceptions to the overall drop in actual fertility, women that have less than three children and the ones not using contraception. It certainly looks that not using modern contraceptives in 2010 is a deliberate choice among those that want to get pregnant. The much lower coefficient effect among those having three children or more might indicate that the sensitizing campaign of three children as the ideal has found “fertile” grounds.
The Blinder-Oaxaca decomposition model originates from analyses of the wage gap between men and women [
Although the proportion of currently married women decreased between 1992 and 2000 (−9.9%) their fertility increased in the same period. This can only partly be attributed to the decrease in the use of modern contraceptive as a result of voluntary behaviour or of unmet need for family planning as the government’s efforts were focused on peace, repatriation, rehabilitation, and reconciliation, and programs for family planning were abandoned. Yet even after controlling for these effects we found behavioural change towards higher fertility in this period. We speculate that pronatalist attitudes were more common in 2000, which is supported by the higher ideal family size in this year.
Things changed after 2000 when the government decided to involve all the legislative and administrative authorities from the Senate to the level of the village in their sensitizing campaign and reproductive health policies. This shift is reflected in the behaviour of the people. By 2010 fertility was revised downward and having large families was little by little relegated as outdated behaviour. The declining fertility among married women and the low fertility that characterises women that have more than two living children support the idea that the combination of raising awareness and providing reproductive health services has been successful limiting the high population growth in Rwanda.
Mortality experience appears to be differentially related to the actual fertility. It appears that women that lost one or more children between 1992 and 2000 engaged more in replacing their loss than the ones that experienced that event between 2000 and 2010. We speculated that the cause of the loss might enter the decision of replacement, yet the overall decrease in mortality level after 2000 might also have made people more confident about the survival of their offspring and thus focus more on the quality of children than the quantity.
The results in this paper add to the theoretical debate on the impact of upheavals on fertility especially in the early phase of fertility decline. Our contribution shows the multidimensionality of this relation. On the one hand deaths, mass migrations, and refugee flows led to widowhood and separation and thus to less intercourse and pregnancies. On the other hand the high level of child mortality, the destruction of health facilities, and lack of supply of reproductive services contributed to higher fertility in the aftermath of the war and genocide. Yet the combined effects of these were not sufficient to explain the stall in fertility decline in this period. Other behavioural responses that contribute to higher fertility, probably the changing attitudes towards the ideal family size, should be taken into account as well.
This is even more pertinent in our analyses of the period after 2000/2005, when the fertility decline seems to have resumed its downward course. The lower level of child mortality and the revitalisation of (reproductive) health facilities can only account for part of the very rapid decline in actual fertility. Shifts in behaviour turned out to be more important than changes in the structure in explaining this decline. This could be related to the strong campaign to limit family size but might also be an effect of the social, economic, and political stability in the country. Decomposition analyses proved to be an effective instrument in detailing this multidimensionality, even if it does not provide direct insight into the causes of the behavioural change.
The authors declare that there is no conflict of interests regarding the publication of this paper.
The authors express their gratitude to the Hewlett Foundation and The Netherlands Organisation for Scientific Research for their financial support (Grant no. W07 40 202 00) and to Tom Pullum of Macro International for his useful comments on the first draft.