Abstract

Despite recent strong interest in the link between fertility and subjective well-being, the focus has centered on developed countries. For poorer countries, in contrast, the relationship remains rather elusive. Using a well-established panel survey—the Ethiopian Rural Household Survey (ERHS)—we investigate the empirical relationship between fertility and life satisfaction in rural Ethiopia, the largest landlocked country in Africa. Consistent with the fertility theories for developing countries and with the sociodemographic characteristics of rural Ethiopia, we hypothesize that this relationship varies by gender and across life stages, being more positive for men and for parents in old age. Indeed, our results suggest that older men benefit the most in terms of life satisfaction from having a large number of children, while the recent birth of a child is detrimental for the subjective well-being of women at reproductive ages. We address endogeneity issues by using lagged life satisfaction in ordinary least squares regressions, through fixed-effects estimation and the use of instrumental variables.

Introduction

Despite a general decline across the world, fertility remains very high in sub-Saharan African countries, where it hovers much above the replacement level and correlates with high poverty (Birdsall and Griffin 1988). Several explanations address the central question of why parents in this area still have so many children. One recurrent theme centers on adults’ perceived gain from having children. The traditional economic theory of fertility (i.e., Becker’s (1960) “New Home Economics” (NHE)), the value-of-children (VoC) approach (Hoffman and Hoffman 1973; Hoffman et al. 1978), and intergenerational wealth flows theory (Caldwell 1982; Willis 1982) all explain the persistence of high fertility by recognizing that having a large number of children is perceived as a value because children represent a source of both labor and support as they grow up, thereby mainly benefitting older parents.

In addition to their tangible values, children also bring about intangible values across parents’ life stages. This feature has spurred a series of studies measuring the potential gain from childbearing through reported life satisfaction and evaluating the costs and benefits of children in terms of economic outcomes. This line of studying fertility behavior, however, concerns predominantly developed countries (e.g., Aassve et al. 2012; Myrskylä and Margolis 2014; Nomaguchi and Milkie 2003; Pollmann-Schult 2014), and to a much lesser extent developing countries, partly because high-quality panel surveys are not available for developing countries as they are for developed countries. Still, considering fertility through the lens of subjective well-being in poorer areas makes a great deal of sense. For instance, if social and cultural norms prescribe large families (e.g., Bongaarts and Bruce 1995; Voas 2003), then children’s multidimensional value in developing countries cannot easily be captured by objective measures only. Self-reported subjective well-being instead potentially does so, helping to explain the puzzle of high fertility being associated with lower parental economic well-being.

The picture is further complicated by the uneven bargaining power between partners when it comes to fertility behavior (e.g., Ashraf et al. 2014; Rasul 2008; Voas 2003). Fathers may be the ones perceiving—and reaping—the benefits of grown-up children as envisaged by the economic theory of fertility, the VoC approach, and intergenerational wealth flows theory. Drawing on this background, our study aims to establish how much parents benefit from children in terms of life satisfaction within a single developing country, here represented by rural Ethiopia. The main research question is twofold. First, we ask whether fertility positively or negatively affects subjective well-being in a poor, rural environment. Second, we assess the extent to which this relationship varies by gender and across different life stages.

The context plays an important role in this study. According to World Bank data, the rural population over the period 2011–2015 corresponded to 80 % to 82 % of the total population in Ethiopia, overall the second-most populous African country (almost 100 million in 2015) and the country with the highest population growth in the world (with a yearly rate of 2.5 % in 2014, World Bank data).1

With a total fertility rate (TFR) of 5.5 children per woman in 2011 and 6.0 in 2005, according to Ethiopia Demographic and Health Survey (DHS) (CSA and ICF 2012; CSA and ORC Macro 2006), rural Ethiopia lends itself well to our analysis. According to DHS data (CSA and ICF 2012), in 2011 the TFR difference between rural and urban Ethiopia was substantial (5.5 children per woman on average vs. 2.6, respectively), and the same difference held for contraceptive use among married women (23.4 % in rural Ethiopia vs. 52.5 % in urban Ethiopia. Rural Ethiopia is characterized by extremely weak social security schemes (e.g., Overbye 2005); cultural norms dictating a large family size (Pankhurst 1992); patrilineal formal and informal institutions (Mabsout and Van Staveren 2010); poor knowledge about contraception and low uptake (Beekle and McCabe 2006; Mesfin 2002); and very limited household bargaining power of women (Dercon and Krishnan 2000a), who also reported a mismatch between desired and observed fertility (CSA and ICF 2012).

On the basis of the theoretical elements and the specific features of the context described earlier, we hypothesize that fertility in rural Ethiopia plays a major role in the parents’ subjective well-being, although with differences by gender and across life stages. Specifically, we expect that a large family size is related to greater well-being at later life stages of the parents, while childbirth events might not generate an immediate positive effect. We also hypothesize that the total number of children would positively affect men’s, but not women’s, subjective well-being. We test these hypotheses by looking at the effect of fertility on parents’ subjective well-being (measured in this study by overall life satisfaction), separately for men and women, for different age groups and controlling for objective and perceived poverty. We study the effect of both the number of children ever born and recent childbirth on life satisfaction for parents in their reproductive ages. For older parents, we explore only the influence of the number of children ever born on life satisfaction.

Besides being highly relevant both from a demographic and development point of view, rural Ethiopia has the clear advantage of being surveyed by the Ethiopian Rural Household Survey (ERHS). This survey includes repeated measurements of life satisfaction over time, life events, and major socioeconomic variables at the individual level, which are crucial for our empirical analysis. Fixed-effects and instrumental variables (IV) regression techniques enable us to identify the effect of both the number of children and recent births while mitigating endogeneity problems commonly encountered in this strand of literature.

The Background

From Traditional Theories of Fertility to Subjective Well-being

High fertility levels in developing countries have been traditionally explained in the light of Becker’s (1960) NHE or according to the VoC approach. These two theoretical frameworks share the idea that individuals evaluate costs and benefits from having children and that this evaluation drives reproductive choices.

The NHE relies on the assumption that the couple’s demand for children depends on a rational valuation of the costs and benefits associated with children relative to other utility-enhancing goods (Becker 1960). Financially constrained households in developing countries may lower the cost of a child by optimally adjusting childcare and work time, or benefitting from children’s labor beginning from a young age instead of investing in children’s education (Becker 1991). In this perspective, high fertility might be explained by the fact that low-income parents decide to favor “quantity” over “quality” of children. Specifically, they tend to have more—but less-educated—children, with the expectation to receive labor input and assistance. If this is the case, childbearing events might not generate an immediate increase in the well-being of the parents. Conversely, having a large number of children might increasingly foster well-being as time goes by because the benefits provided by children, as envisaged by Becker (1960), increase as children grow up. This is consistent also with Caldwell’s theory of net intergenerational wealth flows, postulating economic benefits going from younger to older generations in high-fertility contexts (Caldwell 1978; Willis 1982).

Preferences for children depend also on cultural factors, such as tradition, religion and values. The VoC approach provides insight on the satisfactions (values) and costs (disvalues) associated with children (Hoffman and Hoffman 1973).2 In poorer countries, the instrumental values of children—such as housework, financial help, or old age insurance—may appear more important than immaterial values, such as emotional rewards and psychological appreciation (Bulatao 1981; Hoffman et al. 1978; Nauck 2005, 2007). Because the instrumental values of children can emerge only when they are sufficiently old to offer material help, the VoC approach would predict that children in developing countries increase the well-being of parents mainly when they grow up.

These theoretical considerations suggest that the role children play in parents’ well-being derives from several dimensions, which consequently challenge the traditional ways of measuring well-being. Many dimensions are tangible and objective, and therefore easy to measure through traditional income or consumption-based proxies. Others are instead immaterial, possibly driven by cultural conformity or emotional rewards, and therefore are not fully identifiable through those objective indicators. Consequently, analyzing fertility behavior through the lens of subjective well-being holds much promise as clearly manifested through the numerous studies on fertility and subjective well-being over recent years. Most of such studies have relied on high-quality and long-running panel surveys available mainly for developed countries, capturing countries with different welfare constellations, but where typically fertility is very low. In general, this strand of literature tends to argue that parents are not necessarily happier than nonparents (e.g., Di Tella et al. 2003; Hansen 2012; Peiró 2006; Plagnol and Huppert 2010). However, the relationship between fertility and parents’ well-being strongly depends on the social, political, and cultural characteristics of the country. There are systematic differences across fathers and mothers (e.g., Kohler et al. 2005) by marital status (e.g., Nomaguchi and Milkie 2003), economic status (e.g., Pollmann-Schult 2014; Stanca 2012), national income (Cetre et al. 2016), welfare provision and social benefits for the parents (e.g., Aassve et al. 2012, 2015), and birth order (Myrskylä and Margolis 2014). Moreover, older parents (at the time of childbirth) tend to report higher subjective well-being (Myrskylä and Margolis 2014).

In contrast to this burgeoning literature, very little is known about this relationship in developing countries. To the best of our knowledge, there are only two such studies, both relying on the World Values Survey (WVS). Margolis and Myrskylä (2011), considering an aggregated set of developing countries, found that happiness decreases monotonically with number of children for those aged 20–39, but the relationship flattens out for people older than 39. This finding—that fertility in developing countries fosters well-being only of older parents—provides empirical support to our hypotheses on the intertemporal consequences of fertility behavior. Nevertheless, what is valid for a large and heterogeneous group of developing countries in the WVS may not apply to a specific and extremely deprived context, such as rural Ethiopia. In a cross-sectional study on the socioeconomic determinants of subjective well-being, Peiró (2006) showed that in Nigeria, having three children promotes parents’ happiness, whereas either lower- or higher-order births do not have significant effects on financial satisfaction or life satisfaction. Given the lack of an in-depth analysis on fertility and subjective well-being within a single high-fertility context, our study on rural Ethiopia—relying on panel data—is the first to close this gap in the literature.

High Fertility in Rural Ethiopia

Parents in rural Ethiopia have good reasons to maintain a high demand for children. Even though having an increasing number of children is positively associated with poverty, the costs of raising a child are low, and children are considered a reliable labor force (Aassve et al. 2006). Indeed, both female and male children help in household agricultural activities and other duties, although their tasks vary by age and gender. Moreover, older boys can be hired out to other households in need of labor (Kiros and Kertzer 2000). In contexts with a weak social security system, children are also considered as part of parents’ old age insurance. Ethiopia is no exception. For private-sector employees, pensions were offered only starting from 2011 (before, since 1963, pensions were accessible only to public employees), and no government pension is available for self-employed individuals (Alemu 2015; Bailey and Turner 2002; ISSA 2013; Overbye 2005). As of this writing, most peasants and farmers lack the qualifying conditions for a private pension: for example, a contract and a regular salary. All these arguments are consistent with the qualitative study by Fitaw et al. (2004), who reported that among rural Ethiopians, the main reason for desiring more children was that children constitute an important source of help in old age. As suggested by Caldwell (1986), men are likely to benefit from the investment in childbearing more than women: male household heads expect children to contribute to agricultural activities instead of helping women with household chores.

Persistent high fertility also creates a normative pressure. In a qualitative study of two rural Ethiopian communities, Lavers (2008) noted that cultural conformity is likely to be a major motivating factor in childbearing choices, which indeed suggests that having a large family strengthens parents’ social status (Pankhurst 1992) and reinforces and maintains high fertility. However, studies have also reported important gender differences in terms of fertility preferences (Alvergne et al. 2013; Bhargava 2007), suggesting that the observed reproductive behavior is more a result of men’s preferences than of women’s.

Frequently in developing countries, if women desire fewer children than their partners (Westoff 2010), they are unable to translate their preferences into contraceptive behavior (Rasul 2008; Voas 2003). Indeed, for women in African countries, unwanted childbearing is higher than in the rest of the developing world (Günther and Harttgen 2016). Short and Kiros (2002) argued that Ethiopian women tend to have a preference for two sons and two daughters, and once this is obtained, they prefer to limit further births. Evidence from a study of the southern region of Ethiopia suggests that women who are more empowered in terms of schooling, paid employment, and age proximity with their husband prefer fewer children (Hogan et al. 1999). Rural Ethiopian men, instead, have more pronounced pronatalist attitudes (Short and Kiros 2002). Husbands’ opposition to contraception (Beekle and McCabe 2006), together with wives’ weak household bargaining power (Dercon and Krishnan 2000a; Mabsout and Van Staveren 2010), may explain the mismatch between desired and observed fertility (CSA and ICF 2012; CSA and ORC Macro 2006). Ethiopian couples are not likely to use contraceptives as long as only women have preference for limiting and spacing fertility (Mesfin 2002). Consistent with that notion, an experiment recently carried out in Zambia showed that when women could conceal the decision to use contraception from their husbands, fertility was lower (Ashraf et al. 2014).3

In this complex setting, the National Population Policy (NPP) of Ethiopia (Office of the Prime Minister 1993) addressed the issue of persistent high fertility in 1993, emphasizing the role of fertility and population for poverty reduction. One of its objectives was decreasing the TFR from an average of 7.7 children per woman in 1993 to no more than 4.0 children by the year 2015. This goal, however, has not been reached in rural Ethiopia.

Data and Variables

Data Set

We use the last two waves of the Ethiopian Rural Household Survey (ERHS, years 2004 and 2009), a longitudinal survey on rural households belonging to four Ethiopian regions (Hoddinott and Yisehac 2011): Amhara; Oromya; Southern Nations, Nationalities and People’s Region (SNNPR); and Tigray. The survey started in 1989, but it reached the current geographical coverage only in 1994 (Wave 1), with the inclusion of additional villages, reaching a total of 1,477 households. Between 1994 and 2009, seven rounds took place; we select the last two because they are the only ones providing information on subjective well-being. The sample size in Wave 6 (2004) was 1,389 households. When merging Wave 7 (2009) with Wave 6 (2004), we matched 1,148 cases, with a loss of 17 % of cases.4 The household questionnaire was completed partly by the household head and partly by his or her partner (if any), with subjective self-reported well-being data collected for both partners. In a small minority of cases, other individuals resident in the household and knowledgeable about household activities (such as the household head’s child, son or daughter in-law, sibling and brother- or sister in-law) were interviewed in place of the household head. We excluded these cases from the regression analysis. Respondents answering to well-being and other subjective questions also provided other general information for the household and its members. Given the subjective feature of our main variable of interest (i.e., life satisfaction), we retained only those observations where the same individual is interviewed in both waves. This cleaning procedure generated a loss of 162 of 1,148 households (14 %). The resulting sample was 968 households in which 1,293 individuals answered to the life satisfaction question in each wave.

The questionnaire does not directly ask information on fertility histories. However, these histories could be easily reconstructed by exploiting the entire set of waves with consistent roster cards (1994–2009). We therefore identified the original structure of the household (in 1994), mapped household changes that occurred during the waves (e.g., people who left the household or died), and built retrospective fertility histories starting from 1994. This implies that respondents above a certain age may have had (at an early age) some children who already moved away permanently from the household in 1994 and could not be counted. For this reason, we cut the upper age at 60 (as reported in 2009) for the whole sample. If individuals older than age 60 in 2009 (i.e., older than age 45 in 1994) were not excluded, we would have underestimated the number of children for parents aged 60 and older in 2009. Through this sample, we reduce measurement error and produce conservative estimates of the effect of the number of children ever born on subjective well-being.5 After the data-cleaning procedure and the age cut at 60, the sample contained 1,023 observations (53 % women).

Variables

Our dependent variable is a life satisfaction question: “Suppose we say that the top of a ladder represents the best possible life for you and the bottom represents the worst possible life for you. Where on the ladder do you feel you personally stand at the present time?” The bottom of the ladder is anchored to a value of 0, and the top has a value of 10.6 We treat the scale as cardinal because life satisfaction scores can be almost equally treated as ordinal or cardinal (Ferrer-i-Carbonell and Frijters 2004). In this case, simple linear models can be used in place of ordered latent response models (Van Praag and Ferrer-i-Carbonell 2006).

Our key independent variable is fertility, intended both as the number of children ever born and the presence of birth events between survey waves. The remaining covariates (see Table 1 for descriptive statistics of the variables) are individual characteristics and household characteristics. Among the former, we have partnership status (a dummy variable taking a value of 1 if the respondent has a coresident partner) and education (a dummy variable taking a value of 1 if the respondent went to school), which are both shown to influence subjective well-being and fertility. More specifically, being in a partnership has been generally reported to increase happiness (Kohler et al. 2005), and it plays a role in reproductive success in rural Ethiopia (Gibson and Mace 2007). Education is largely adopted as a proxy for socioeconomic status, and it is among the determinants of contraceptive uptake (Alvergne et al. 2013).

Health status is an important dimension of subjective well-being, too. However, it correlates also with fertility behavior. For instance, childbearing at young age and limited birth spacing increase health risks for both mothers and their children (Bongaarts and Potter 1983). In addition, parents with health impairments may benefit from grown-up children as support in their daily labor and household activities. For these reasons, we include in our estimates an index for physical limitations, portraying the inability to perform five activities: (1) standing up after sitting down, (2) sweeping the floor, (3) walking 5 km, (4) carrying 20 l of water for 20 m, and (5) hoeing a field for a morning. The response values to these items for the activities extend from 1 (activity is easily performed) to 4 (activity cannot be performed at all). The index, built as a sum of the tasks, thus spans from 5 (if the individual can easily perform all the five activities) to 20.

Important variables associated with subjective well-being and fertility are those reflecting the respondent’s economic conditions. More specifically to this study, as suggested by the NHE, high fertility can be an optimal response to high poverty: children in developing countries are perceived as long-term investments (Becker 1960, 1991) and vehicles of wealth transmission across generations (Caldwell 1978; Willis 1982). At the household level, we rely on a set of objective measures of poverty, which are commonly used in the related literature (e.g., Peiró 2006): (1) household per capita food expenditure (in logarithm in the econometric models); (2) total size in hectares of the land acquired by the household (proxy for household wealth in Ethiopia; Dercon and Krishnan 2000a); (3) the number of loans opened in the year preceding the interview and still outstanding; and (4) the unavailability of any kind of shared or private toilet, including flush toilet, pit latrine, and pan or bucket. According to the Ethiopian Constitution (Article 40(3)), the rural land laws of 1997 (proc. 87/1997) and 2005 (proc. 456/2005), and the regional land laws, all urban and rural land is property of the State and the Ethiopian people. Rural land cannot be owned; however, any person, independent of gender, above age 18 who wants to engage in agricultural activities may have access to land in his or her area of residence (Ambaye 2015). Consistent with this, in our 2004 data, approximately 60 % of the plots had been acquired by the household thanks to allocation from the public authority (the peasant association), and another 30 % of the plots had been acquired through inheritance or as a gift from the family. The profits provided by the land, therefore, derive from land cultivation and sale of agricultural produce.

Furthermore, we add a subjective measure of poverty: the adequacy perception index, which is built as the mean of three items on reported adequacy in food, housing, and healthcare for the household. Although subjective, adequacy has been recognized as a valid measure of poverty in developing countries (Pradhan and Ravallion 2000) because it captures the perceived position of the individual in the society with respect to the close reference group. What classifies an individual as poor or rich might well be socially determined (Scitovsky 1978) and dependent on the desired standards of living (Sen 2001). It is therefore important to consider a more comprehensive measure of poverty besides the aforementioned objective income and wealth proxies. In addition, this index also accounts for the unobservable role of financial satisfaction, which is an important component of fertility decisions and life satisfaction (Stanca 2012).

We also control for the religion (Muslim, non-Protestant Christian, Protestant, and other religions) because fertility in rural Ethiopia is also influenced by religious norms affecting the spread of contraception (Alvergne et al. 2013). Other covariates are dummy variables respectively assessing the presence of sociopolitical and household shocks in the two years preceding the interview. In the ERHS questionnaire, a shock is defined as “an event that led to a serious reduction in your asset holdings, caused your household income to fall substantially or resulted in a significant reduction in consumption.” The respondents had to declare whether and when they witnessed a series of different shocks. We define sociopolitical shocks as referring to imprisonment; discrimination for political, social, or ethnic reasons; land redistribution; confiscation of assets; forced or banned migrations; forced contributions or arbitrary taxations; and contract defaults on sales and purchases. On the other hand, we define the theft of household cash, crops, and livestock; theft or destruction of inputs and tools for production; the death or illness of a member of the household; and divorce and disputes with family members or neighbors on land and assets as household shocks. Climate and agricultural shocks are not taken into account because of very limited variability at the village level. The inclusion of the shock variables in our analysis allows us to control for the idiosyncratic effects of income volatility on household risk sharing (Dercon and Krishnan 2000a), consumption and poverty (Dercon and Krishnan 2000b), and net welfare losses due to the lack of insurance and protection measures (Dercon 2004). Traditional theories of fertility (see the section, High Fertility in Rural Ethiopia) suggest that all these factors may relate to fertility and subjective well-being, thereby generating omitted variable bias if not accounted for.

Analytic Strategy

We first model the relationship between fertility and life satisfaction through ordinary least squares (OLS) regressions and panel fixed effects. Standard errors have been clustered at village level throughout. We run the models separately for individuals during their reproductive years (younger than 45 for women, younger than 50 for men) and beyond their reproductive years (ages 45–60 for women, and ages 50–60 for men). We rely on age thresholds already present in studies on fertility (e.g., Kohler et al. 2005) but also coherent with the literature on men’s age-related infertility (Harris et al. 2011), and especially with fertility as reported in our data. To maintain the same sample size across all the models, we run regressions only on individuals without missing values on the independent variables.

The model specification depends on the age range considered. When considering respondents in their reproductive age—that is, women younger than 45 and men younger than 50, fertility is measured both in terms of the number of children ever born and the presence of birth events taking place between survey waves. For older respondents (women aged 45–60, men aged 50–60), fertility is defined as the number of children ever born.

Accordingly, we first estimate the following model for younger respondents with standard OLS at Wave 2:
$LifeSati=β0+β1N_childreni+β2newborni+∑jβjXij+εi,$
1

where N_children is the number of children ever born, newborn is a dummy variable equal to 1 if the respondent reported a birth event in the last five years, and X is the set of socioeconomic and demographic variables described in the preceding section.

We then exploit the panel feature of the data by reestimating the model in Eq. (1) with panel fixed effects (Waves 1 and 2) as specified in the following Eq. (2):
$LifeSatit=β0+β1N_childrenit+∑jβjXijt+αi+εit.$
2

The fixed-effects regression removes the individual unobserved (time-invariant) characteristics (αi), which may otherwise affect the probability of having an additional child, the reported levels of subjective well-being, or both.

We then regress life satisfaction on the number of children for older respondents—that is, men aged 50–60 and women aged 45–60—by estimating the following equation:
$LifeSati=β0+β1N_childreni+∑jβjXij+εi.$
3

Results

Estimation results for Eq. (1) are reported in columns 1–4 of Table 2 for women and Table 3 for men.

The results demonstrate that having a new child between the two waves (2004–2009) negatively affects women’s life satisfaction. This result is robust to the inclusion of the adequacy perception index, capturing the respondent’s perceived lack of access to basic needs (column 3, Tables 2 and 3).

The negative effect of the newly born child is robust also to the addition of the lagged level of life satisfaction (column 4, Tables 2 and 3). The inclusion of this variable has two advantages. On the one hand, lagged life satisfaction captures the unobserved socioeconomic and psychological factors influencing both the decision to have a child and later-life satisfaction (e.g., satisfaction with the partner and, more generally, with the household, latent financial conditions, and personality traits). On the other hand, lagged life satisfaction reduces the potential bias in the estimated effect of a new child deriving from respondents’ heterogeneity in their initial life satisfaction levels (Kim and Hicks 2015). Lagged life satisfaction is included only in Model 4 of Tables 2 and 3 because the potential bias due to uncontrolled drivers of a new birth refers only to young respondents. However, results do not change if lagged life satisfaction is included in all models of Tables 2 and 3. (Results are reported in Table S4 in Online Resource 1.) As a further robustness check, we reestimate the models in columns 3–4 of Tables 2 and 3 by also adding the sociodemographic and economic controls measured at the previous wave. The inclusion of these controls further mitigates the potential endogeneity in having an additional child, which may derive from sample heterogeneity in terms of initial conditions. Regression results, reported in Table S3 in Online Resource 1, are consistent with the main findings.

Estimation results for Eq. (2) are reported in Table 4 separately for women (columns 1–2) and men (columns 3–4). We exclude here the dummy variable used in previous estimates to capture the effect of a new birth (i.e., Birth event in the last five years). Because fixed effects are equivalent to first-differences models when the time dimension of the panel is 2 (as in our case), the effect of a new child is absorbed in the coefficient of the variable Number children ever born. Hence, this coefficient can be interpreted as the effect on respondent’s life satisfaction of the change in the number of children between two waves. As shown in columns 1–2 (Table 4), the negative effect of a new birth on women’s life satisfaction is robust to the dynamic fixed-effects estimation, although the same effect for men is not (columns 3–4, Table 4).

OLS estimates for Eq. (3) reported in columns 5–6 of Tables 2 and 3 provide support to our hypotheses, with a positive relation between the number of children and life satisfaction being significant only for men.7

In order to understand to what extent economic conditions explain the association between parenthood and life satisfaction, we reestimate the main models excluding variables capturing the respondent’s economic characteristics. With respect to the effect of children ever born on subjective well-being, results are reported in Table S1 in Online Resource 1 and are consistent with our main findings in Tables 2 and 3. For what concerns fixed-effect models, results show that the effect of birth events on life satisfaction is not significant (see Table S2 in Online Resource 1). This result is not surprising given that the childbirth effect is estimated across all economic groups, thus hiding heterogeneity in economic conditions that would influence the relationship between fertility and subjective well-being. With respect to how this source of heterogeneity correlates with fertility behavior, among the considered economic variables, household food expenditure and number of outstanding loans are positively and significantly affected by the birth of a child for young respondents. In addition, the unavailability of any type of toilet (our proxy for low level of wealth) is negatively and significantly correlated with the presence of newborn children.8 The positive childbirth effect on food consumption is consistent with the economic literature suggesting that in poor countries, the constraints on per capita expenditure in food are usually relaxed in large families because of household economies of scale in the consumption of other goods (Deaton and Paxson 1998; Gan and Vernon 2003; Lanjouw and Ravallion 1995). An increase in the number of outstanding loans among respondents with recently born children highlights the large financial costs often associated with childbearing (Fawcett 1983). Wealthier respondents are more likely to bear these costs, as reflected by the negative association between toilet unavailability and newborn children. However, when the heterogeneity is removed by including economic controls (as we do in our main models), the effect of childbirths on women’s well-being is negative and significant. Moreover, the robustness of the fertility effects to the inclusion of the adequacy perception index implies that the potential correlation between perceived poverty and the life satisfaction (both are subjective measures) does not lead to biased estimates.

In sum, our estimates remain significant when we control for socioeconomic variables capturing respondents’ objective financial conditions, health status, and the subjective perception of poverty. This piece of evidence implicitly suggests that differences in economic status do not alter the positive (negative) value that old men (young women) attribute to children.9

Instrumental Variable Estimates

The main findings suggest a negative relationship between a newborn child and life satisfaction of women in reproductive ages, whereas the number of children positively affects older men’s subjective well-being. The first result is not likely to be driven by omitted variable bias because it is robust to the introduction of lagged life satisfaction as a proxy of other potential unobserved variables influencing life satisfaction and fertility decisions as well as to a fixed-effects estimation controlling for individual’s unobserved time-invariant characteristics. Apart from potential measurement error in the variables of interest, the second finding might be admittedly subject to reverse causality problems and omitted variable bias. First, the relationship between fertility levels and life satisfaction can be modeled not only in a direction going from the first to the second, as we do in our regressions, but also in the opposite way: that is, happy households produce more children (Kim and Hicks 2015). Second, with respect to omitted variable bias, the observed correlation between life satisfaction and number of children can be driven by past or present unobserved characteristics influencing both variables, which would lead to a spurious correlation between the two. Such unobserved variables may be, for instance, personality traits, satisfaction with the partner, past marital history, or household composition.

To address these endogeneity issues, we perform an IV regression of the models in column 5 of Tables 2 and 3 (Eq. (3)). Specifically, we estimate the following equations for older respondents (men aged 50–60, women aged 45–60):
$N_childreni=α0+α1FirstChildMalei+∑kαkXik+ηi$
4
$LifeSati=β0+β1N_children¯i+∑jβjXij+εi.$
5

We follow the two-stages estimation as in the standard IV strategy. In the first stage (Eq. (4)), we instrument the number of children ever born with a dummy variable equal to 1 if the firstborn’s sex is male, and we control for the k (k < j) sociodemographic characteristics that are plausibly fixed over time (i.e., sex, schooling, and religion). Then, in the second stage (Eq. (5)), we regress life satisfaction on the predicted values of the number of children from the first stage (the orthogonal component) and control for the larger set of the j sociodemographic and economic characteristics used in the previous specifications. Because the first stage produces predicted values of the endogenous variable (number of children) exploiting only exogenous variation in that variable (captured by its correlation with the instrument), the second stage delivers unbiased estimates of the effects of family size on life satisfaction.

The use of firstborn’s sex as an instrument has been well established in the related literature on fertility in developing and developed countries (e.g., Cruces and Galiani 2007; Lee 2008). More specifically to our context, the sex of the firstborn drives subsequent births because of the son preference in Ethiopia. Parents whose first child is a boy are likely to have fewer children than parents whose first child is a girl (because the latter would need to have more children to ensure having sons). Boys in rural Ethiopia may be hired out to other households needing labor support starting from age 7 (Short and Kiros 2002), the patrilineal inheritance rules are unfavorable to women (Dercon and Krishnan 2000a), and giving birth to sons has traditionally had a rewarding social value in rural areas (Pankhurst 1992). In addition, infant mortality—higher for male than for female children (84 vs. 63 deaths per 1,000 live births in rural Ethiopia in 2011, according to Ethiopian DHS data)—may reinforce parents’ preferences for sons. This behavior also appears in our data because a negative and significant correlation between number of children ever born and firstborn’s gender is present. The average number of children for respondents aged 50–60 is six if the firstborn’s gender is male and more than seven if it is female (a statistically significant difference under the two-sample Wilcoxon rank-sum test; z = 2.988, and p value = .0028).10 The IV results reported in Table 5 also confirm this correlation. This table separately reports first-stage estimates for number of children (Eq. (4)) and second-stage estimates for life satisfaction (Eq. (5)). The first-stage estimates (columns 1, 3, 5, and 7 in Table 5) show that, all things being equal, couples with a male firstborn have a smaller family size. The second-stage IV estimates for Eq. (5) confirm the positive and significant effect of the number of children ever born on male respondents’ life satisfaction.

Discussion

In this study, we analyze the relationship between subjective well-being and fertility in rural Ethiopia, addressing the important issue of why poor regions are still accompanied by high fertility rates. Traditional theories of fertility— the NHE (Becker 1960, 1991) and VoC (Bulatao 1981; Hoffman and Hoffman 1973; Hoffman et al. 1978), and theory of intergenerational wealth flows (Caldwell 1982)—justify this preference in the light of the intrinsic and instrumental value children have for parents at different life stages, suggesting that the initial costs of childbearing may be compensated by later benefits from grown-up children and by the social rewards associated with having a large family. Along this line of thought, and consistent with more recent results on the link between fertility and subjective well-being, we hypothesize that a large family size would foster well-being at parents’ later life stages, but childbirth events would not generate an immediate positive effect. Because fertility behavior in developing countries is influenced by gender inequality, we expect that the benefits of grown-up children accrue mainly to old men, whereas young women bear the costs associated to childbearing. By exploiting the two most recent waves of the ERHS, we test these hypotheses by approaching the issue separately for men and women and for different age groups, and by considering how the number of children ever born and new birth events relate to parents’ life satisfaction. We find a positive relationship between the number of children ever born and life satisfaction of men aged 50–60. We also find that having had at least one new child in the five years before the interview negatively affects reproductive-aged women’s life satisfaction. Estimates are robust to the inclusion of objective and subjective poverty indicators and other socioeconomic controls. These results largely confirm what Margolis and Myrskylä (2011) found for the subset of developing countries in the WVS data: namely, that having a child worsens subjective well-being of younger parents, but the effect is reversed for older parents. Our analysis builds on previous research and well-established theories by providing robust results through the in-depth analysis of longitudinal data of a single developing country. In addition, it sheds light on gender asymmetries in the fertility-happiness relationship.

This study shows that despite the association between having a large number of children and higher poverty—as many studies before us have shown—the life satisfaction of fathers with many children is higher than the life satisfaction of fathers with few children. Subjective well-being in this sense portrays the multidimensional value of children to parents in addition to their objective influence on the economic sphere. As such, this study reconciles to some extent the conundrum of why families in developing countries have many children even though they bring about higher poverty. Ethiopian parents perceive the cost of having a child as compensated by long-run benefits of different types—for instance, labor assistance in agriculture, uncertainty reduction, old-age support, and social status. Margolis and Myrskylä (2011) argued that the positive link between happiness after age 40 and children is strongest in countries where old-age support depends mostly on the family, attesting to children as a long-term investment in well-being. This may straightforwardly apply to developing countries. Our gender-specific results, however, support the hypotheses that only men consider children to be a valuable investment in a life cycle perspective, whereas women mainly bear the costs of childbirth, including the physical risk associated with pregnancy and delivery. The latter is particularly relevant in Ethiopia, which is still striving to improve maternal health, the most problematic among the eight Millennium Development Goals for this country (Mekonnen and Mekonnen 2003; Woldemicael and Tenkorang 2010). In fact, Ethiopia has the lowest proportion of births attended by skilled healthcare personnel among all the African countries. For the periods 1990–1999 and 2000–2009, only about 5 % of births were attended by skilled healthcare personnel (United Nations 2011). These different implications of childbearing for men and women are consistent with women’s preference for fewer children compared with men, which in turn is reflected by Ethiopian women’s unmet need for contraception (27.5 % women in rural Ethiopia 2011 and 34 % in total Ethiopia in 2005, according to Ethiopian DHS data).

Interestingly, if we consider these results valid for other similar contexts, the value of children in developing countries has not substantially changed in the last decades. Already in 1986, Caldwell argued that mainly men receive the benefits of the investment in childbearing because children tended to contribute to agricultural activities instead of helping women with household chores. Given the adverse effect of childbirth on women’s well-being, it is not surprising that women tend to prefer fewer children than men (CSA and ICF 2012). Yet, birth rates per woman are still high in rural Ethiopia. Societal characteristics go a long way in explaining this pattern. In a context where men enjoy high household bargaining power because of cultural traditions (Pankhurst 1992), gendered societal institutions (Mabsout and Van Staveren 2010), and larger relative wealth and customary rules on divorce settlement (Dercon and Krishnan 2000a), having a(nother) child is likely to be driven by men’s preferences (Beekle and McCabe 2006). Moreover, conformity to social norms on ideal family size helps explain individual fertility decisions (Lavers 2008) because male Ethiopian household heads are more likely to place significant weight on having a large number of children, traditionally recognized as a vehicle for high social status (Pankhurst 1992).

Nonetheless, there are important caveats to our study. Because of the lack of questions on life satisfaction in the previous waves of the data set, we could not disentangle the cohort from the age effect—that is, from the effect of the perceived value of children for older men. It might also be that older men had more children than their current younger counterparts when they were young, perhaps because of unobserved contextual and normative local dynamics in the past. Consequently, older men enjoy their children more. Whereas this is a limitation of our study, it calls for further research on this aspect of fertility and well-being in developing countries through the use of panels with several waves. However, this limitation refers only to the analyzed relationship between children ever born and subjective well-being, and hence it does not weaken our result on the effect of a recently born child on life satisfaction.

Concluding, as long as local cultural traditions endorse large family size and men attribute high instrumental and immaterial value to their grown-up children—and the use of contraception is decided by husbands—fertility rates are not likely to decrease very soon in rural Ethiopia. Our findings suggest the argument often found in more qualitative studies: namely, that addressing the issue of high fertility means a massive change in fathers’ attitudes toward childbearing and an improvement in women’s conditions in terms of schooling, job participation, and partnership quality, given that these three characteristics are associated with a preference for fewer children (Hogan et al. 1999). At the same time, female empowerment might help alter the current eclipsing of women’s preferences for a lower number of children by their husbands’ preferences. In contexts where old-age support is better provided by the offspring than by institutions, high fertility may be functional to parents’ well-being in a life cycle perspective. Therefore, at the government level, expanding the social security system could partially diminish the fathers’ need for children as old-age insurance providers while providing easier access to formal healthcare services would improve women’s subjective well-being after childbirth.

Acknowledgments

The authors gratefully acknowledge financial support from the European Research Council under the European ERC Grant Agreement no StG-313617 (SWELL-FER: Subjective Well-being and Fertility, P.I. Letizia Mencarini).

Notes

2

According to the original framework, parents have children in order to satisfy nine values or needs: affection and primary group ties, stimulation and fun, expansion of the self, acquisition of adult status and social identity, achievement and creativity, morality, economic utility, power and influence, and social comparison.

3

Women were offered free access to contraceptives and assistance from a family planning nurse through a voucher, either received in private or in the presence of the husband. In the former case, women were much more likely to ask for (concealable) contraception and much less likely to report undesired births afterward. Because rural Ethiopian men are more pronatalist than women (Short and Kiros 2002), Ethiopia is likely to share with other African countries (such as Zambia) the same asymmetries in the intracouple bargaining regarding fertility.

4

Considering the difficulties in collecting data in a rural area of a developing country, panel attrition in our data does not seem remarkable. We nevertheless account for potential attrition bias by weighing all estimates by the inverse of the estimated probability of attrition (inverse probability weighting (IPW)). Results are robust to this check; see Online Resource 1 for further details. Consider also that the use of the IV mitigates the effects of attrition bias in linear regression models.

5

We repeat the IPW analysis (see footnote 3) to account for a potential source of bias due to selection on the age cut-off. Results are robust to this check; see Online Resource 1 for further details. Consider, however, that the potential measurement error is addressed also through the IV approach.

6

The question is very similar to the Cantril Ladder (Cantril Self-Anchoring Striving Scale, Cantril 1965). The literature uses both the terms “life evaluation” and “life satisfaction” to refer to the Cantril Ladder (e.g., Cummins 1995; Deaton and Stone 2014).

7

Results do not change if we consider women aged 50–60 or 55–60. Results are available upon request.

8

These results are obtained through a fixed-effects regression of our economic variables on the number of children ever born plus additional controls (coresident partner, schooling, physical limitations, and shocks), separately for young men and women and with standard errors clustered at the village level. Results are available upon request.

9

We also explored the effect of children’s gender. None of our findings change significantly when accounting for the differential role of the children’s gender on parents’ subjective well-being. We ran this robustness check by (1) replacing the number of children variable in the regressions in columns 5–6 of Tables 2 and 3 with two different variables capturing the number of daughters and the number of sons; and (2) replacing the dummy variable for a newly born child in columns 1–4 of Tables 2 and 3 with two dummy variables separately accounting for whether the respondents had a male or a female child in the last five years (the omitted category being no newborns). Regression results are available from the authors upon request. This result provides further support to the exclusion restriction when we implement the IV approach.

10

Potential weak-instrument problems are addressed in Online Resource 1.

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