Female Genital Cutting and Education: Causal evidence from Senegal

Transcription

1 Female Genital Cutting and Education: Causal evidence from Senegal Jorge García Hombrados * February 15, 2018 THIS IS AN EARLY DRAFT PREPARED FOR SUBMISSION TO THE 2018 EEA- ESEM MEETING IN COLOGNE. METHODS AND RESULTS MAY CHANGE. PLEASE DO NOT CITE. Abstract This study investigates the causal effect of female genital cutting (FGC) on education through exploiting across ethnic-group variation in exposure to a law that in January 1999 banned the practice of FGC in Senegal. The results show that, in a context where girls are cut during infancy and early childhood, experiencing FGC reduces significantly the years of education and the probability of ever attending school of the girls. The analysis of mechanisms suggests that households react to the increase in the cost of FGC caused by the introduction of the anti-fgc legislation through abandoning the practice of FGC and compensating uncut girls with larger levels of educational investments to avoid potential losses in the marriage market. On the other hand, the results show that the effect on education is not driven by any lasting health effect of FGC. * Department of Social Policy, London School of Economics 1

2 1 Motivation Defined as the ritual cutting of some or all of the external female genitalia for reasons unrelated with health 1, UNICEF (2016) estimates that more than 200 million women worldwide are affected by female genital cutting (FGC). The practice of FGC is particularly widespread among many ethnic groups in West Africa, where most girls are cut during their infancy or early childhood (Yoder and Wang, 2013). The circumcisions are usually conducted by traditional practitioners with little knowledge of female anatomy using crude unsterile instrument and without anaesthetics (UNICEF, 2013). Indeed, health complications such as bleeding (median 32%), urine retention (median 31%), genital tissue swelling (median 15%) or problems with wound healing (median 13%) are frequent during the practice of FGC (Berg et al., 2014). Although the causal health and economic effects of FGC remain unexplored, different studies show that this practice is associated with negative psychological and reproductive health outcomes (Berg et al., 2014; Wagner, 2015; Mulongo et al., 2014) and with better marriage market outcomes (Wagner, 2015). However, no previous study investigates the link between FGC and educational. In this study, I use the introduction of the Senegalese FGC ban in January 1999 as a natural experiment to investigate the causal effect of FGC on educational outcomes. Using a difference-in-difference strategy comparing girls from ethnic groups for which the practice of FGC is deeply rooted in tradition with girls from ethnic groups where FGC was never practiced, the analysis shows that the anti-fgc law led to a significant reduction in the probability of experiencing FGC. The exogenous variation in the probability of being cut generated by the introduction of the law is then used to estimate the causal effect of FGC on educational outcomes. The results of the study suggest that girls that experienced FGC are significantly less likely to ever attended school and receive on average 1.8 years of education less. The results are robust to different falsification tests ruling out the possibility that the estimates are simply capturing anticipation effects or pre-law differences in FGC trends across ethnic groups. The analysis of mechanisms suggest that this effect is not driven by girls experiencing FGC having worse health. Instead, I find that, in line with the anthropological and economic literature that understand FGC and education as pre-marital investment that raise the value of girls in the marriage market, households react to the increase in the cost of FGC caused by the introduction of the anti-fgc legislation through abandoning the practice of FGC and raising the level of educational investments received by uncut girls to avoid potential losses in the marriage market. The paper makes three main contributions to the literature. Firstly, the study adds to the body of evidence examining the lasting effects of FGC, providing the first empirical evidence on the effect of FGC on educational outcomes. Secondly, the paper is also related with the 1 2

3 emerging literature that investigates whether legal changes can be effective instruments to address harmful practices deeply rooted in tradition in many developing countries, an aspect that has recently gathered the attention of researchers and policy makers. Third, the results of the study provide key insights on how FGC is closely linked to marriage market and how FGC decisions are sensitive to economic incentives. The study is structured as follows. Section 2 presents the conceptual framework. Then, section 3 discuss some key aspects about the practice of FGC in Senegal and describes the law that banned its practice. Next, I introduce the data used in the analysis in section 4 and the empirical strategy in section 5. Section 6 presents the main results of the study and examines their robustness to different falsification tests. Section 7 investigates different mechanisms through which FGC could affect educational outcome. Section 8 concludes. 2 Conceptual framework FGC could affect educational investments through different mechanisms. Firstly, FGC may foster school drop out through lastingly affecting the physical and mental health of girls. Although the literature is not homogeneous, some studies suggest that FGC is associated with negative physical health outcomes. In their reviews of the literature, Berg et al. (2014) and Berg and Unerland (2013) find that FGC is associated with menstrual problems and urinary tract infection, painful sexual intercourse and difficult labour during delivery. On the other hand, the meta-analyses conducted in these studies show no correlation between FGC and HIV prevalence, infertility or obstetric haemorrhage. The authors of the reviews also point out that the methodological rigour of included studies vary substantially and while some of these studies rely on large sample sizes and adjust for observable sources of confounding (see for example WHO (2006), Jones et al. (1999) and Larsen (2002)), others use small samples and poor methodological designs. In a more recent study not included in the review, Wagner (2015) examines the consequences of FGC using nationally representative information from 13 countries and more than 100,000 women. The study shows that, once the author account for unobservable differences at the village level and adjust for key individual characteristics, FGC has limited health consequences. Although the author finds some effect of FGC on the prevalence of sexually transmitted illnesses, vaginal discharge and genital sore, the results also highlight no effect of FGC on BMI, weight, hemoglobin, amenorrhea and menstruation. Regarding the potential effect of FGC on psychological health, Mulongo et al. (2014) synthesizes the existing empirical evidence concluding that although more research is needed, existing studies provide suggestive evidence of a positive association between FGC, post-traumatic stress and affective disorders. Taken together, the existing evidence on the health consequences of FGC is inconclusive and therefore, it is in principle not possible to dismiss poor health outcomes as a potential channel of impact of FGC on education. Secondly, FGC could impact educational investments through affecting marriage market 3

4 outcomes. On the one hand, in contexts where the practice of early marriage is linked to the high value of girls purity in the marriage markets (Wahhaj, 2015; Moghadam, 2004) and where FGC is believed to reduce sexual desire and prevent pre-marital sex 2, FGC could reduce the cost of monitoring girls sexual activity. Thus, parents of cut girls might be more willing to delay marriage, which could eventually lead to higher levels of education (Field and Ambrus, 2008). On the other hand, since both FGC and education are both positive and strong determinants of women s marriage market outcomes (Wagner, 2015; Ashraf et al., 2016), one may also argue that FGC could crowd out other pre-marital investments including educational investments. Thus, parents may react to an increase in the cost of FGC caused by the ban through abandoning this practice and investing more in girls education to reduce potential losses of uncut girls in the marriage market. 3 Female Genital Cutting in Senegal and the introduction of the Law The practice of FGC is widespread in West African countries, where its prevalence ranges between 3% in Niger and 99% in Guinea. In Senegal, approximately 25% of women aged declared having undergone FGC (28TooMany, 2015). The practice is deeply rooted in the tradition of many ethnic groups such as the Soninke, Mandinke, Diola and the Pular, while it is absent among the Wolof, the largest Senegalese ethnic group, and among the Serer. Unlike countries like Kenya, Egypt or Tanzania, FGC in Senegal is mainly conducted during infancy or early childhood. In this sense, Yoder and Wang (2013) show that in this West African country, 61% of the cuts occur before the girls turn one year old and excisions after early childhood are infrequent. The WHO defines four types of FGC depending on the degree of invasiveness of the excision. The Type I or cloridectomy is the partial or total removal of the clitoris. Type II FGC or excision consists in the partial or total removal of the clitoris and the labia minora, with or without excision of the labia majora. Type III or infabulation is the more aggressive practice, and it consists on the narrowing of the vaginal opening through the creation of the covering seal. Type IV includes other harmful procedures to the female genitalia for non-medical procedures. Although most FGC conducted in Senegal could be classified as type II FGC, type III cuttings are also existent among a small share of Soninke and Maninke girls (28TooMany, 2015). Regardless of the specific FGC type, most of the FGC conducted in Senegal are performed by traditional practitioners with little knowledge 2 One form of FGC, known as infabulation, consists in narrowing the vaginal opening through the creation of a covering seal. This covering seal prevents vaginal intercourse and is typically broken the wedding night by the husband. 4

5 of female anatomyusing crude unsterile instrument and without anaesthetics (UNICEF, 2013; Berg et al., 2014). Although the evidence on the long-term health effects of FGC is not conclusive 3, the medical literature documents that severe health complications such as genital tissue swelling or problems with wound healing during circumcisions are frequent. Increasingly aware of the health risks and discriminatory nature of this practice, tackling this practice has been at the top of Senegal s policy agenda for decades. The flagship measure of the Senegalese government against the practice of FGC was the approval of the Law No that banned FGC and sanctions those who provokes sexual mutilations or gives instructions for their commission with six months to five years of prison, or hard labor for life if cutting results in death. The law was enacted the 29th of January 1999, following the anti-fgc speech of the US first lady Hillary Clinton in Senegal and 10 months of intense anti-fgc campaign led by different Senegalese civil society organizations. Qualitative evidence suggest that the law was particularly effective in communities where the practice of FGC had been actively contested while in more traditional communities the law may have drove the practice underground (Kandala and Komba, 2015). 4 Data The main analysis of the paper is conducted using the 2016, 2015, 2014, 2012 and 2010 cross-sectional rounds of the Senegalese Demographic and Health Survey (DHS). DHS are nationally representative surveys that include individual and household level modules that collect rich information on health and demographic characteristics. They have been implemented in more than 100 low- and middle-income countries across the world for more than three decades and the high quality of these datasets is examined in Pullum (2008). DHS datasets typically include information on basic demographic and educational outcomes for every member of the household. Furthermore, information on different health outcomes is provided for a subsample of the household members, which vary in every survey. Unlike previous rounds of the survey, the DHS datasets include for every girl aged 0-49 years old individual level information on whether the girl experienced FGC. On the other hand, anthropometric and basic health information such as the incidence of anemia is only collected for children younger than 5 years old, and information on marital status is only available in these surveys for individuals aged 15 or older. In total, the 2016, 2015, 2014, 2012 and 2010 Senegalese DHS datasets include information from 25,256 households. The analysis is however focuses in the 32,827 women born from January 1990 that by the time of the survey were at least 7 years old. I restrict the analysis to women born from 1990 because the accuracy of the information on date of birth is likely 3 See for example Wagner (2015) 5

6 larger among relatively younger girls. However, the selection of the exact date is arbitrary and in the analysis, I examine the robustness of the results to the use of a largest sample of women. The restriction of the analysis to those girls at least 7 years old has a twofold objective. First, this is the legal age at which children should start the school in Senegal. Second, since the vast majority of cuttings occur during girls infancy and early childhood, setting the threshold at the age of 7 years avoids the possibility that the reduction in the prevalence of FGC is simply capturing the fact that girls are yet to be cut by the time of the survey. Summary statistics for the sample of women included in the analysis are reported in table 1. The age of women in the sample ranges between 7 and 26 years old and the average number of years of schooling for these girls is 3 years. Indeed, 36% of girls in the sample never attended school. Furthermore, the descriptive statistics show that cut girls, that are the 32% of the sample, are not a random sample of the Senegalese female population. They are overall poorer and older than uncut girls and more likely to live in rural areas. Cut girls are also slightly more likely to report never being in school although differences between them in terms of level and years of education are not statistically significant at conventional confidence levels. Table 1: Summary statistics: FGC women Non-FGC women Full sample (N= 10,546) (N= 22,281) Standard Diff (FGC N Mean deviation Min Max Mean Mean - Non-FGC) Age 32, *** Year of birth 32, *** Never in school (0/1) 32, * Years of education 32, Level of education (0-5) 32, Wealth index 32, *** Rural 32, *** Wolof 32, *** Poular 32, *** Serer 32, *** Mandingue 32, *** Diola 32, *** Soninke 32, *** Not a Senegalese 32, *** Other 32, *** 6

7 5 Empirical strategy The main challenge for the estimation of the causal effect of FGC on educational outcomes is the potential endogeneity in the link between these two variables arising from measurement error in the FGC status and the existence of omitted variables driving both FGC decisions and educational investments. On the one hand, most studies examining FGC rely on self-reported status, which might be imperfectly reported due to social stigma. On the other hand, some unobservable household and individual variables such as attitudes towards tradition could eventually affect both educational outcomes and FGC variables. In both situations, an analysis based on the adjusted statistical association between FGC and educational outcomes should not be interpreted as the causal effect of FGC on educational outcomes. In order to address the endogeneity in the link between FGC and educational outcomes, the study exploits across-ethnicity variation in exposure to the Senegalese law that banned FGC in Senegal. More specifically, I use a difference-in-difference strategy exploiting the sharp reduction in the prevalence of FGC for girls born after the introduction of the anti- FGC law that belong to ethnic groups where the practice of FGC was traditional relative to girls from ethnic groups where FGC was never practiced as a source of exogenous variation in the probability of experiencing of FGC. The first stage of the proposed analysis is therefore assessing whether women born after the introduction of the law that belong to ethnic groups for which the pre-law prevalence of FGC was higher experienced larger reductions in their probability of undergoing FGC. To test this hypothesis, I estimate the following regression: FGC ikrt = α 0 +α 1 P OST t LawIntensity k + α 2 LawIntensity k + α 3 Y earbirth t + α 4 EthnicGroup k + α 5 Region r + α 6 Region r Y earbirth t + α 7 X i + µ ikrt (5.1) where F GC ikrt indicates whether girl i from the ethnic group k living in region r and born during year t undergone FGC. P OST t is a dummy variable that is equal to 1 if the girl is born after the introduction of the FGC ban (January 1999) and the variable LawIntensity k measures the pre-law average incidence of FGC among the ethnicity k. Y earbirth t, EthnicGroup k and Region k are vectors of dummy variables that indicate the year of birth, ethnic group and region of residence of the girl. X i is a vector of control variables including girl and household level characteristics and µ ikrt is the error term. The interaction term P OST t LawIntensity k is the variable of primary interest in the regression. The parameter α 1 measures the differential change in the prevalence of FGC after the introduction of the law for ethnic groups with higher and lower pre-law levels of FGC. Ultimately, the parameter α 1 measures the effect of the degree of exposure of the law (larger 7

8 among ethnicities with a higher pre-law prevalence of FGC) on the probability of experiencing FGC. In order to account for differential trends in FGC over time across Senegal, the specification includes regional time trends. Standard errors are clustered at the DHS cluster level. In the second stage of the analysis, I exploit the variation in the prevalence of FGC caused by across-ethnic group variation in exposure to the law to estimate the effect of FGC on educational outcomes. Using a 2SLS estimator, I estimate the following regression: Years Education ikrt = β 0 + β 1 F GC ikrt + β 2 LawIntensity k + β 3 Y earbirth t + β 4 EthGroup k + β 5 Region r + β 6 Region r Y earbirth t + β 7 X i + u ikrt (5.2) where Y earseducation ikrt measures the years of education of girl i from the ethnic group k living in region r and born during year t and F GC is the predicated probability of FGC estimated from equation 5.1. The parameter of first interest is β 1, that yields the causal effect of FGC on years of education. The validity of the empirical strategy presented in this section relies on two main conditions. First, those ethnic groups with a higher pre-law prevalence of FGC should have experienced larger reductions in the prevalence of FGC. In order to meet this condition, the parameter α 1 in equation 5.1 should be large and statistically significant. To avoid a problem of weak instrument, the literature set the threshold of F>10 for the coefficient of the instrumental variable (Bound et al., 1995; Angrist and Pischke, 2008). Second, the evolution of the prevalence of FGC across cohorts born before the introduction of the law should be the same across the different ethnic groups. The latter assumption would be violated if for example the prevalence of FGC started dropping for those cohorts of girls born before the introduction of the law. The existence of pre-law parallel trends across ethnic groups is examined in section Results The main estimates of the study examining the link between exposure to the FGC ban, FGC prevalence and educational outcomes are provided in table 2. The results reported in columns one, three and five of the table correspond to the estimates of the reduced form and first stage regressions, assessing the effect of the degree of exposure to the law on educational outcomes and on the prevalence of FGC. The coefficients for the variable Intensity P ostlaw in these regressions show that women from ethnicities with higher pre-law incidence of FGC experienced larger reductions after the introduction of the law in the probability of undergoing FGC and larger improvements in terms of years of education, 8

9 educational levels and probability of ever attending school. The coefficients are particularly large for the first stage regressions. The estimates reported in columns 3 and 5 suggest that women born after the introduction of the law from an ethnic groups that cut the 100% of the women born before the law would experience a reduction in the prevalence of FGC of percentage points. This reduction is statistically significant at the 1% significance level and largely satisfy the relevance condition (F>10). The sharp reduction in the prevalence of FGC in Senegal among those girls born after the introduction of the anti-fgc law is also evident in figure 1. Figure 1: Education and FGC over time 9

10 Table 2: Impact of Female Genital Cutting on Education: OLS IV IV Panel A: Years of Education (1) (2) (3) (4) (5) (6) Years Years Prevalence Years Prevalence Years Education Education FGC (0/1) Education FGC (0/1) Education Intensity P ostlaw 0.312* *** *** ( 0.172) ( 0.016) ( 0.018) FGC *** ** * ( 0.077) ( 0.761) ( 1.034) Regional Dummies Yes Yes No No Yes Yes Regional time trends Yes No No No Yes Yes N 32,668 32,668 32,668 32,668 32,668 32,668 Panel B: Level of Education (0-5) (1) (2) (3) (4) (5) (6) Level of Level of Prevalence Level of Prevalence Level of Education Education FGC (0/1) Education FGC (0/1) Education Intensity P ostlaw 0.142** *** *** ( 0.057) ( 0.016) ( 0.018) FGC *** *** ** ( 0.025) ( 0.243) ( 0.349) Regional Dummies Yes Yes No No Yes Yes Regional time trends Yes No No No Yes Yes N 32,668 32,668 32,668 32,668 32,668 32,668 Panel C: Never in school (0/1) (1) (2) (3) (4) (5) (6) Never in Never in Prevalence Never in Prevalence Never in School School FGC (0/1) School FGC (0/1) School Intensity P ostlaw * *** *** ( 0.024) ( 0.016) ( 0.018) FGC 0.091*** 0.409*** 0.261* ( 0.012) ( 0.091) ( 0.144) Regional Dummies Yes Yes No No Yes Yes Regional time trends Yes No No No Yes Yes N 32,827 32,827 32,827 32,827 32,827 32,827 Note: All the regressions include as control variables a vector of year of birth dummies, a quadratic polynomial for age at survey, a vector of Ethnic group dummies, a dummy indicating whether a women is born after the introduction of the law and a variable indicating average pre-law incidence of FGC for the ethnicity of the woman. Standard errors in parentheses are clustered at the survey cluster level.***p<0.01;**p<0.05;*p<0.1 Column 2 reports the results of the naive association between FGC and educational outcomes. The coefficient for the variable FGC is negative and statistically significant at the 10

11 1% significance level, showing that conditional on age, year of birth, ethnic affiliation and place of residence, women that experience FGC receive lower levels of education and are less likely to attend school. However, as discussed in section 5, this statistical association should be interpreted with caution because the link between FGC and education could be driven by unobservable preferences and attitudes that could confound the statistical association. In order to overcome this endogeneity, I exploit the variation in the prevalence of FGC generated by across-ethnic group variation in the degree of exposure to the law using a 2SLS estimator. The results of the second stage regressions estimating the causal effect of FGC on educational outcomes are reported in columns 4 and 6. The estimates reported in column 6, which include regional time trends, suggest that experiencing FGC decreases the number of years of education by 1.8 (p<0.1) and the level of education by 0.8 points (p<0.05) and increases the probability of never being in school by 26 percentage points (p<0.1). When the first and second stage equations are estimated without regional time trends, the coefficients of interest do not change much for years and level of education, although the statistical significance for these coefficients is larger when regional time trends are omitted. On the other hand, the coefficient of the effect of FGC on the variable that measures whether the girl never attended school is significantly larger when the equations are estimated without regional time trends. 6.1 Robustness checks The previous section shows that girls that experience FGC achieved worse level of education and are less likely to ever attend school. In this section, I check the robustness of the results to different placebo tests. First, it is possible that the evolution of the prevalence of FGC across cohorts was already different among those cohorts of girls born before the introduction of the FGC ban. This would happen for example if the sharp reduction in the prevalence of FGC among ethnic groups where this practice was traditional started already for those girls born before the introduction of the law (anticipation effects). In this case, the effects estimated in the previous section could be capturing pre-existing differences in the trends of FGC across different ethnic groups. In order to examine this possibility, I run the analysis setting falsely the introduction of the law in 1995 (rather than 1999) and limiting the analysis to those women born before the introduction of the true law in The main results of the study would be compromised if the estimates of the effect of exposure to the law on the prevalence of FGC in this analysis show significant effects. The results of this falsification test are reported in columns 1 and 2 of table 3, and they confirm that the effect of FGC on education identified in section 6 is not driven by differences in terms of pre-law FGC trends across ethnic groups, which is the key identification assumption of the empirical strategy used in this study. The results of this placebo test are also consistent with the graphs presented in 11

12 figure 1 that show the evolution of the prevalence of FGC for women born before and after the introduction of the law. Table 3: Robustness checks: Female Genital Cutting and Education. Placebo: law Placebo: Pre-law in 1995 Sample of men period from 1980 Panel A: Years of Education (1) (2) (3) (4) (5) Prevalence Years Years Prevalence Years FGC (0/1) Education Education FGC (0/1) Education Intensity P ostlaw *** ( 0.026) ( 0.203) ( 0.016) FGC * ( ) ( 0.650) Regional Dummies Yes Yes Yes Yes Yes Regional time trends Yes Yes Yes Yes Yes N 14,433 14,433 25,939 45,388 45,388 Panel B: Level of Education (0-5) (1) (2) (3) (4) (5) Prevalence Levels of Levels of Prevalence Levels of FGC (0/1) Education Education FGC (0/1) Education Intensity P ostlaw *** ( 0.026) ( 0.070) ( 0.016) FGC ** ( ) ( 0.217) Regional Dummies Yes Yes Yes Yes Yes Regional time trends Yes Yes Yes Yes Yes N 14,433 14,433 25,939 45,390 45,390 Panel C: Never in school (0/1) (1) (2) (3) (4) (5) Prevalence Never in Never in Prevalence Never in FGC (0/1) School School FGC (0/1) School Intensity P ostlaw * *** ( 0.026) ( 0.030) ( 0.016) FGC *** ( ) ( 0.097) Regional Dummies Yes Yes Yes Yes Yes Regional time trends Yes Yes Yes Yes Yes N 14,538 14,538 26,067 45,674 45,674 Note: All the regressions include as control variables a vector of year of birth dummies, a quadratic polynomial for age at survey, a vector of Ethnic group dummies, a dummy indicating whether a women is born after the introduction of the law and a variable indicating average pre-law incidence of FGC for the ethnicity of the woman. Standard errors in parentheses are clustered at the survey cluster level.***p<0.01;**p<0.05;*p<0.1 12

13 Figure 2: Education and FGC over time (from 1980) Second, I estimate the effect of the law on educational outcomes among boys. Although we cannot rule out the possibility that the effect of the law on the FGC status of the girls has some spillover effects on the educational investments that receive their male siblings, the effect of the law on the education of the boys, if any, would be arguably smaller than for girls. The results of this analysis are reported in column 3 of table 3 and show that the law does not seem to have any effect on years of education or levels of education for boys. On 13

14 the other hand, exposure to the law seems to have a negative effect on the probability of never being in school for boys, statistically significant at the 10% significance level. Finally, since restricting the sample to those girls born from 1990 was to some extend arbitrary, I test the robustness of the results to the expansion of the pre-law period to girls born from The results of this analysis are reported in columns 4 and 5 of table 3 and show that the magnitudes of the effects of FGC on educational outcomes are overall smaller than those found when the pre-law period is limited to those girls born from However, the results are still statistically significant at conventional confidence levels. The evolution of educational outcomes and FGC prevalence for this extended sample of girls are graphically displayed in figure 2. 7 Mechanisms Section 6 shows that experiencing FGC has a negative effect on educational outcomes and that this effect is robust to different falsification tests. In this section, I investigate two mechanisms through which FGC could affect negatively educational outcomes. First, in a context where both education and FGC are investments that improve marriage market outcomes for girls (Wagner, 2015; Ashraf et al., 2016), FGC may crowd out educational investments. If the ban raised the cost of FGC, households may trade off the practice of FGC with educational investments to avoid losses in the marriage market for uncut girls. In order to test this mechanism, one would ideally need to test the effect of FGC on educational investments for a subsample of households for which FGC does not improve marriage market outcomes for girls. Although the DHS Senegalese datasets lack information on perceived benefits of FGC practice, I investigate this mechanism through exploring the heterogenenous effects of FGC on education for different samples that differ in terms of the value of FGC in the marriage market and the extent to which educational investments are constrained. First, I examine whether the effect of FGC on education is different in wealthier and poorer households. An smaller effect of FGC on education in wealthier households, where the investments in education would be less constrained and households might invest in girls education regardless of whether they are cut, would be consistent with this mechanism. Second, I explore whether the effect of FGC on education is different in rural and urban areas. Because the value of FGC in the marriage market is higher in rural areas (28TooMany, 2015), a larger effect of FGC on educational outcomes in rural areas would be consistent with the hypothesis that the causal reduction in the level of education that received girls that underwent FGC is driven by a crowding out effect of FGC on educational investments received by the girls. The results of this analysis are reported in table 4. In line with the predictions of this hypothesis, the coefficients reported in columns 7 and 8 show that while the effects of FGC on educational outcomes are strong in rural areas, the magnitudes are smaller and 14

15 statistically indistinguishable from 0 at conventional confidence levels in urban areas. The results reported in columns 1 to 4 show that the magnitude of the coefficients measuring the effect of FGC on educational outcomes among the two wealthiest quintiles are small and positive for educational level and years of education. On the other hand, the coefficients have the expected sign and are larger among the poorest three quintiles than among the whole sample, although they are only statistically significant for the variable educational level. Taken together, the results of the analysis by wealth and location are consistent with the hypothesis that the effect FGC on educational investments is driven by parents abandoning FGC and investing in the education of girls that cannot be cut to avert potential losses in the marriage market. Table 4: Impact of Female Genital Cutting on Education: Heterogenous effects Poor sample Non-poor sample Urban sample Rural sample Panel A: Years of Education (1) (2) (3) (4) (5) (6) (7) (8) Prevalence Years Prevalence Years Prevalence Years Prevalence Years FGC (0/1) Education FGC (0/1) Education FGC (0/1) Education FGC (0/1) Education Intensity P ostlaw *** *** *** *** ( 0.022) ( 0.028) ( 0.028) ( 0.024) FGC ** ( 1.453) ( 0.972) ( 1.017) ( 1.738) N 23,943 23,943 8,725 8,725 11,860 11,860 20,808 20,808 Panel B: Level of Education (0-5) (1) (2) (3) (4) (5) (6) (7) (8) Prevalence Level of Prevalence Level of Prevalence Level of Prevalence Level of FGC (0/1) Education FGC (0/1) Education FGC (0/1) Education FGC (0/1) Education Intensity P ostlaw *** *** *** *** ( 0.022) ( 0.028) ( 0.028) ( 0.024) FGC ** *** ( 0.500) ( 0.320) ( 0.346) ( 0.621) N 23,943 23,943 8,725 8,725 11,860 11,860 20,808 20,808 Panel C: Never in school (0/1) (1) (2) (3) (4) (5) (6) (7) (8) Prevalence Never in Prevalence Never in Prevalence Never in Prevalence Never in FGC (0/1) School FGC (0/1) School FGC (0/1) School FGC (0/1) School Intensity P ostlaw *** *** *** *** ( 0.022) ( 0.027) ( 0.028) ( 0.024) FGC ** ( 0.209) ( 0.118) ( 0.142) ( 0.252) N 24,040 24,040 8,787 8,787 11,921 11,921 20,906 20,906 Note: All the regressions include as control variables a vector of year of birth dummies, a quadratic polynomial for age at survey, a vector of Ethnic group dummies, a dummy indicating whether a women is born after the introduction of the law and a variable indicating average pre-law incidence of FGC for the ethnicity of the woman. Standard errors in parentheses are clustered at the survey cluster level.***p<0.01;**p<0.05;*p<0.1 However, FGC may also have an effect on education through affecting lastingly the health 15

16 of girls. Although the existing evidence on the lasting health effects of FGC is mixed 4, severe complications during the cut are not rare and most of the evidence suggest an effect of FGC on the prevalence of sexually transmitted diseases. The most straightforward way to test the health mechanism would be re-estimating equations 5.1 and 5.2 using health outcomes as dependent variables in the second stage equations. However, the datasets used in the main analysis do not provide health information on anthropometric measures, incidence of anemia and diarrhea for girls older than 5 years old implying that we do not observe key health outcomes for girls born before the introduction of the anti-fgc law. To cope with this limitation, we also use in the analysis Senegalese DHS data for the rounds 2008, 2005 and 1997 and the 2008 and 2006 rounds of the MIC survey. These datasets include information on health outcomes for girls born before and after the introduction of the FGC ban. On the other hand, the additional DHS databases do not include information on FGC for young girls, preventing the estimation of equation 5.1 and 5.1. Thus, in order to test the health mechanism and once we proved in the previous section the effect of exposure to the FGC ban on the prevalence of FGC, I estimate the following reduced form regression: Health ikrt =α 0 + α 1 P OST t LawIntensity k + α 2 LawIntensity k + α 3 Y earbirth t + α 4 EthnicGroup k + α 5 Region r + α 6 Region r Y earbirth t + α 7 X i + µ ikrt (7.1) where Health ikrt indicates the health status of girl i from the ethnic group k living in region r and born during year t. I use different health variables including BMI, weight, height, anemia, prevalence of diarrhea and whether the girl has a health card. In this equation, α 1 yields the effect of the degree of exposure to the FGC ban on health outcomes. If the parameter α 1 is small and statistically insignificant, the effect of FGC on education is arguably not driven by any effect of FGC on health. The results of this analysis are reported in table 5. The coefficients that measure the effect of the law on health outcomes such as diarrhea, anthropometry or anemia are all statistically indistinguishable from 0 at conventional confidence levels. Although the analysis shows no effect of the law on general health outcomes, the young age of most women born after the introduction of the ban hampers the assessment of the effect of the law on sexual reproductive health outcomes. Indeed, one may argue that the effect of FGC on education could be caused by FGC teenage girls dropping from school due to poor sexual reproductive health, which might not correlate with the health outcomes analyzed. However, the fact that FGC has also a large impact on ever attended school dismisses the possibility that the effect of FGC on education is entirely driven by a poor reproductive health among girls that experienced FGC. 4 See for example Wagner (2015) 16

17 Table 5: Impact of Female Genital Cutting Ban on Health Outcomes and Investments: (1) (2) (3) (4) (5) (6) BMI Weight Height Anemia Diarrhea Health card Intensity P ostlaw ( ) ( ) ( ) ( 0.063) ( 0.029) ( 0.045) Regional Dummies Yes Yes Yes Yes Yes Yes Regional time trends Yes Yes Yes Yes Yes Yes N 12,114 14,735 14,630 15,950 20,561 19,258 Note: All the regressions include as control variables a vector of year of birth dummies, a quadratic polynomial for age at survey, a vector of Ethnic group dummies, a dummy indicating whether a women is born after the introduction of the law and a variable indicating average pre-law incidence of FGC for the ethnicity of the woman. Standard errors in parentheses are clustered at the survey cluster level.***p<0.01;**p<0.05;*p<0.1 8 Conclusions This study makes three main contributions to the literature. Firstly, through showing that the introduction of a FGC ban in Senegal reduced significantly the prevalence of FGC and increased girls education, the study contributes to the thin literature that investigates the use of legal reforms as instruments to tackle harmful practices deeply rooted in tradition. Furthermore, since the practice of FGC is still not regulated in many of the developing countries where it is widely practiced (28TooMany, 2015), the results of the study provide evidence supporting the introduction of anti-fgc legislation in countries aiming to address this harmful tradition. Secondly, the study documents for the first time in the literature the causal effect of FGC on education, showing how women that experienced FGC received less educational investments. The effect is interpreted in a context in which education and FGC are pre-marital investments that improve marriage market outcomes for girls, and parents compensate girls that cannot be cut with educational investments to avoid potential losses in the marriage market. Thirdly, the study provides important insights about the close link between FGC and marriage markets through illustrating how educational investments and parental decisions about cutting young girls respond to increases in the cost of FGC. References 28TooMany (2015). Country Profile: FGM in Senegal. Technical report, 28 Too Many. 17

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