The Impact of Foreign Aid on Maternal Mortality

Politics and Governance (ISSN: 2183–2463) 2019, Volume 7, Issue 2, Pages 53–67 DOI: 10.17645/pag.v7i2.1835 Article

The Impact of Foreign Aid on Maternal Mortality

Emmanuel Banchani and Liam Swiss *

Department of Sociology, Memorial University of Newfoundland, St. John’s, A1C 5S7, Canada;

E-Mails: eb1043@mun.ca (E.B.), lswiss@mun.ca (L.S.)

* Corresponding author

Submitted: 19 November 2018 | Accepted: 12 April 2019 | Published: 5 June 2019 Abstract

In 2010, the G8 placed renewed focus on maternal health via the Muskoka Initiative by committing to spend an additional

$5 billion on maternal, newborn, and child health before 2015. Following the end of the Millennium Development Goals and the advent of the Sustainable Development Goals, maternal health issues have continued to feature prominently on the global health agenda. Despite these substantial investments of foreign aid over the past decade, there is limited ev- idence on the effectiveness of foreign aid in reducing maternal mortality in low- and middle-income countries (LMICs).

Using data from the Organisation for Economic Cooperation and Development, the World Development Indicators and the Institute of Health Metrics and Evaluation, this study analyzes the effects of aid on maternal health in a sample of 130 LMICs from 1996 through 2015. Our results show that the effects of total foreign aid on maternal mortality are lim- ited, but that aid allocated to the reproductive health sector and directly at maternal health is associated with significant reductions in maternal mortality. Given these targeted effects, it is important to channel more donor assistance to the promotion of reproductive health and contraceptive use among women as it serves as a tool towards the reduction of maternal mortality.

Keywords

family planning; foreign aid; maternal mortality; Muskoka Initiative; reproductive health Issue

This article is part of the issue “Aid Impact and Effectiveness”, edited by Rachel M. Gisselquist and Finn Tarp (UNU-WIDER, Finland).

© 2019 by UNU-WIDER; licensee Cogitatio (Lisbon, Portugal). This article is licensed under a Creative Commons Attribu- tion 4.0 International License (CC BY).

1. Introduction

Recent debates concerning the effectiveness of aid in improving development outcomes have been inconclu- sive (Tilburg, 2015). Aid critics (Easterly, 2006; Moyo, 2009; Winters, 2010) have voiced their concerns that aid is “dead”. They maintain that billions of dollars have been transferred to poor economies with the aim of im- proving living conditions, but the results have always been catastrophic, leaving more than a billion people still living in abject poverty. Despite these concerted ef- forts, there has been limited academic research on the links between foreign aid and maternal mortality reduc- tion in low- and middle-income countries (LMICs; Taylor, Hayman, Crawford, Jeffery, & Smith, 2013).

In the case aid committed to maternal health, the Muskoka Initiative on Maternal, Newborn and Child Health was one such commitment adopted at the G8 summit in 2010. This initiative saw a commitment of

$7.3 billion through 2015 to improve maternal and child health in the world’s poorest countries and to contribute to the achievement of Goal 5 of the Millennium Develop- ment Goals (MDGs). The presumption that aid can com- bat maternal mortality, however, seemed to be based on limited evidence, and this relationship has rarely fea- tured in the global health research agenda.

Given the Muskoka commitments, and support for

the MDGs and Sustainable Development Goals (SDGs),

over the past decade, the donor community has com-

mitted sizeable financial resources to the reduction of

maternal deaths in developing countries. Between 1990 and 2017 and estimated $11.6 billion has been invested in maternal health (Institute of Health Metrics and Evaluation [IHME], 2018). Yet, high levels of maternal mortality are still prevalent in many parts of the world.

It is estimated that in 2015 99% (302,000) of maternal deaths were recorded in LMICs compared to other de- veloped regions of the world (World Health Organization [WHO], UNICEF, UNFPA, & The World Bank, 2015). Given the seeming role for international development assis- tance in combatting this development challenge, it is im- portant to assess the evidence of aid’s efficacy in reduc- ing maternal mortality. As such, this study examines the effect of foreign aid on maternal mortality in LMICs using two-way fixed effects panel regression over the period from 1996 through 2015.

2. Background

Evidence suggests most LMICs were not able to meet the targets of the health-related MDGs of reducing maternal mortality ratio by 75% between 1990 and 2015 (WHO et al., 2015). Indeed, by 2015, the WHO reported an esti- mated decline in global maternal mortality rate (MMR) of 45% in that period to 210 deaths per 100,0000 live births, far short of the 75% reduction goal. Following the MDGs, the SDGs set a target of lowering MMR to 70 per 100,000 live births, as part of SDG 3’s goal to “ensure healthy lives and promote wellbeing for all at all ages”. To this end, several donor countries have pledged their support to in- crease funding towards the reduction of maternal health levels to the countries with the poorest health indicators (Proulx, Ruckert, & Labonté, 2017).

Previous foreign aid research has mainly focused on economic development and poverty reduction with mixed results. For example, Bornschier, Chase-Dunn and Robinson (1978), Dalgaard, Hansen and Tarp (2004), and Arndt, Jones and Tarp (2015) all show that foreign aid has a positive impact on economic growth. In contrast, Durbarry, Gemmel and Greenaway (1998), and Annen and Kosempel (2009) and Easterly (2003) show that for- eign aid has no impact on economic growth. Ekanayake, Cookman and Chatrna’s (2000) study on the effect of for- eign aid in developing countries show that there is no impact. Given the complex relationship between health and development, there is an interest in exploring how investments in people’s overall health in a country con- tribute to economic development. It is argued that if the productive workforce is healthy, they can work meaning- fully towards higher productivity translating into a higher economic growth and development.

While these studies provide an important step in ob- taining empirical evidence of the role of foreign aid on development outcomes, few studies to date have ex- amined the impact of foreign aid on health outcomes such as mortality (Kotsadam, Østby, Rustad, Tollefsen, &

Urdal, 2018). Early studies point to a harmful effect of aid on mortality and health outcomes, specifically in the

case where aid increased the indebtedness of recipient countries (Bradshaw, Noonan, Gash, & Sershen, 1993;

Sell & Kunitz, 1986). Shen and Williamson (1999) find that greater indebtedness—in some cases aid-related—

indirectly increases maternal mortality, but conclude their study with a rallying call to donors, arguing: “It is likely that even a modest increase in aid could substan- tially improve maternal mortality rates if it were spent on improving the access of poor women to health ser- vices” (p. 211).

More recent studies on the impact of foreign aid on mortality have mainly focused on infant or child mortal- ity (Burguet & Soto, 2012; Kotsadam et al., 2018; Mishra

& Newhouse, 2009; Pandolfelli, Shandra, & Tyagi, 2014;

Winkleman & Adams, 2017). Similarly to the economic lit- erature, empirical evidence suggests that the effects of foreign aid on mortality are inconclusive. Many studies highlight the inefficacy or negative effects of aid. For ex- ample, Williamson (2008) find that foreign aid is ineffec- tive in improving overall health. Likewise, Pandolfelli et al.

(2014) find that International Monetary Fund loans and structural adjustment contribute to higher maternal mor- tality in Sub-Saharan Africa. These deleterious effects of structural adjustment on child and maternal mortality are echoed by Thomson, Kentikelenis and Stubbs (2017), Powell-Johnson, Borghi, Mueller, Patouillard and Mills (2006) also find a positive relationship between mortal- ity and Official Development Assistance (ODA). Other re- search is mixed: Mishra and Newhouse (2009) show that total overall aid had no impact on infant mortality, while health aid reduced mortality levels. Still other studies find beneficial effects of aid on mortality rates: Kotsadam et al. (2018) show that aid programming reduces infant mortality for marginalized communities, while Yogo and Mallaye (2015) demonstrate that increased health aid is linked to significant decreases in child mortality.

While few studies have touched on aid’s effect on maternal mortality, there has been a concerted effort to track aid spending in this area. Greco, Powell-Jackson, Borghi and Mills (2008) tracked the flow of health-related aid from 2003 through 2006 and found that aid to mater- nal health did not always go to the most affected coun- tries. This tracking was part of a series of Lancet articles which mapped ODA spending on maternal health but did not analyze its effects on maternal mortality (Arregoces et al., 2015; Grollman et al., 2017; Hsu, Pitt, Greco, Berman, & Mills, 2012; Powell-Johnson et al., 2006).

These studies provide a strong basis upon which to ex- amine the effects of the flow of aid to maternal health.

Considering the significant international attention

paid to the maternal mortality issue by the international

community and donor agencies in recent years, the rel-

ative absence of empirical evidence linking aid and re-

duced mortality is surprising. This study aims to provide

some of this evidence and examine the impact of several

categories of foreign aid spending on maternal mortality

over time. This evidence is important, not only to bet-

ter understand the health effects of aid, but also to ex-

pand the growing literatures linking aid to gender equal- ity outcomes (Grown, Addison, & Tarp, 2016; Pickbourn

& Ndikumana, 2016; Tiessen, 2015).

3. Data and Methods 3.1. Data

Data for this study are drawn from the Organisation for Economic Cooperation and Development (OECD) Credi- tor Reporting System (CRS) database, the World Devel- opment Indicators (WDI) from the World Bank, the IHME database, and Grollman et al.’s (2017) ODA + data set on aid to maternal health.

Our main sample consists of 130 LMICs that were el- igible to receive the various categories of aid between 1996 and 2015. In total, the sample consists of 2,093 country-year observations over that period for which all data was available. Descriptive statistics for our sample are shown in Table 1.

The dependent variable in this study is MMR: the number of maternal deaths in a given period per 100,000 women of reproductive age during the same time pe-

riod (WHO, UNICEF, UNFPA, & The World Bank, 2012).

We test the relationship between aid and MMR using two different data sources for the dependent variable.

The MMR measure in our main analysis consists of MMR data from the WHO and housed in the World Bank’s WDI dataset. As a robustness check, we also repeat our analysis using MMR data from the IHME “Maternal Mortality Estimates and MDG 5 Attainment by Country 1990–2011” dataset (IHME, 2011). The WHO defines ma- ternal death as:

The death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of pregnancy from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes. (WHO ICD-10, 2011, p. 156)

The causes of maternal death according to the WHO can be direct or indirect causes. The direct causes are those resulting from complications of the pregnant state, from interventions, omissions, incorrect treatment, or from a chain of events resulting from any of the above.

Table 1. Sample descriptive statistics, 130 countries, 1996–2015.

Min Mean Median Max SD N Source

Dependent variable

Maternal mortality ratio (MMR)—primary 4.00 289.32 148.00 2650.00 321.69 2093 WDI analysis

Maternal mortality ratio (MMR)—robustness 6.80 294.00 113.50 2592.50 335.29 1709 IHME analysis

Aid measures (per capita)

Total aid (constant 2011 USD) 0.00 68.66 39.95 1257.09 98.73 2093 OECD CRS

Total aid to Health (constant 2011 USD) 0.00 4.14 1.57 170.19 8.94 2093 OECD CRS Total population/reproductive policy and 0.00 2.87 0.80 133.76 7.56 2093 OECD CRS

programming (constant 2011 USD)

Aid to reproductive health 0.00 0.34 0.09 11.83 0.76 2093 OECD CRS

(constant 2011 USD)

Aid to family planning (constant 2011 USD) 0.00 0.16 0.00 5.75 0.41 2093 OECD CRS Total maternal and newborn health aid 0.00 0.57 0.09 12.36 1.10 2093 Grollman

(constant 2013 USD) et al., 2017

Controls

GDP per capita, (constant 2010 USD) 186.66 5414.95 2357.40 72670.96 9666.15 2093 WDI Births attended by skilled health personnel, 5.60 72.28 81.00 100.00 27.06 2093 WDI

percentage, percent

Adolescent fertility rate (births per 3.82 72.17 63.98 218.77 47.62 2093 WDI 1,000 women ages 15–19)

Contraceptive prevalence, modern methods 1.20 35.76 34.50 86.20 20.92 2093 WDI (percent of women ages 15–49)

Instrument

Donor fractionalization-recipient aid 0 0.22 0.25 0.38 0.08 2055 OECD/

probability interaction WB DPI

The indirect causes are those not due to direct obstet- ric causes. Not surprisingly, there is a close association between economic development in a country and its rates of maternal mortality. Figure 1 highlights this re- lationship for our sample countries in 2015, showing that wealthier countries are likely to have lower rates of mortality. Mean MMR in our sample is approximately 289 deaths per 100,000 women, while median MMR is approximately 148. MMR varies significantly across dif- ferent geographic regions within our sample and over time. Figure 2 shows this variability, revealing that over-

all MMR has declined significantly over time, but remains high in certain regions.

Our main independent variables are the annual ODA flows for six categories of aid in millions of constant 2011 USD. The source from the OECD is the net bilateral ODA commitments by the Development Assistance Commit- tee (DAC) donors reported from the CRS. This study con- siders all forms of aid commitments allocated by the DAC donor countries. We consider the effects of six categories of bilateral aid: total aid, total health-related aid, total aid to population/reproduction policy and programming,

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Figure 1. Relationship of sample country GDP per capita and maternal mortality, 2015.

0 2015 2010 2005 2000 1995

400 Mean MMR

600 800

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Lan America & Caribbean Sub-Saharan Africa Europe & Central Asia

South Asia East Asia & Pacific

Middle East & North Africa

Figure 2. Mean maternal mortality ratio by region, 1995–2015.

reproductive health aid, family planning aid, and total aid to maternal and newborn health.

¹

Figure 3 shows how the first five of these categories maps onto DAC aid codes. To account for variation in population size be- tween countries, we convert these ODA data into per capita measures. Our analysis uses the log (base 2) of these measures to account for skewness, meaning that the coefficients for each measure can be interpreted as the marginal effect of a doubling of that type of aid.

Our analysis also accounts for other variables that have an impact on maternal mortality. The other vari- ables included are Gross Domestic Product (GDP) per capita, births attended by a skilled birth attendant, ado- lescent fertility rate, and population using any method of contraception and the total population. Each of these variables is drawn from the World Bank’s WDI databank.

To address missing values in this data we replaced miss- ing data with the most recent year’s non-missing data.

These independent variables are explained below.

GDP per capita: There is a strong negative correlation between a country’s level of national income and mater- nal mortality ratio (Bishai et al., 2016). This relationship has been shown to be robust over time and is evident in Figure 1. Mean GDP per capita in our sample is $5415. In our models, GDP per capita is measured in constant 2010 US dollars and is logged to account for skewness.

Skilled birth attendant: According to a statement by WHO, International Confederation of Midwives (ICM),

and the International Federation of Gynecology and Obstetrics (FIGO), the term ‘skilled attendant’ refers to:

An accredited health professional—such as midwife, doctor or nurse—who has been educated and trained to proficiency in the skills needed to manage normal (uncomplicated) pregnancies, childbirth and the im- mediate postnatal period, and in the identification, management or referral of complications in women and newborns. (WHO, ICM, & FIGO, 2004, p. 1) Traditional birth attendants either trained or not, are ex- cluded from this category of skilled health workers (WHO et al., 2004 as cited in Nanda, Switlick, & Lule, 2005, p. 9).

This measure reflects the percentage of births attended by skilled health personnel, with a mean of 72% of births in countries in our sample over time.

Adolescent fertility rate: The association between maternal mortality and the age at birth of mothers is well- established in the literature (Conde-Agudelo, Belizan,

& Lammers 2005; Nove, Mathews, Neal, & Camacho, 2014; WHO, 2018). In our models, adolescent fertility is measured by the rate of births per 1,000 women aged 15–19 years, and averages 72 births per 1,000 women in our sample.

Modern contraceptive use: We account for contra- ceptive use in our analysis using a measure of the per- centage of women ages 15–49 using at least one mod-

Total Family Planning Aid (DAC Code: 13030) Total Reproducve Health Care Aid

(DAC Code: 13020) Total Populaon & Reproducve Programming/Policy Aid (DAC Code: sum of 13000 series) Total Aid

(DAC Code: 1000)

Total Health Aid (DAC Code: 120 I. 2)

Figure 3. Aid independent variables and corresponding DAC codes.

1The first five categories correspond to the following DAC Sector Codes in the CRS: Total Aid (1000); Health Total (120 I. 2); Total Population and Reproductive Programming and Policy (total of 13000s); Reproductive Health Care (13020); and Family Planning (13030). The final category, total aid to maternal and newborn health, is drawn from the ODA plus dataset presented in Grollman et al. (2017).

ern form of birth control. In our models we use this mea- sure to serve as a proxy measure of reproductive health services and women’s empowerment (WHO, 2011). The mean of modern birth control use in our sample is ap- proximately 34%.

3.2. Analysis

We use a two-way fixed effects panel regression model with both year- and country-fixed effects to analyze the impact of foreign aid on maternal mortality. Including both fixed effects components in our models allows us to account for the influence of correlation within countries over time and the effect of global time trends on mater- nal mortality ratios and all other co-variates. As a result, our models help us predict the effect of aid on change in MMR within countries over time and control for all time- invariant characteristics of a given country. We lag all of our independent measures one-year behind the depen- dent variable to allow for a temporal gap in which the effects of aid might take hold.

²

For example, in our analy-

sis we are predicting the effects of all independent mea- sures in 2000 on MMR in 2001, or the effects of indepen- dent variables in 1996 on MMR in 1997. Finally, we run separate sets of nested models for each of the four aid measures because they are too highly correlated to pro- vide meaningful results if included in a single model.

4. Results

We ran a series of nested models for each aid measure, but in Table 2 we present only the full models for each for the sake of parsimony. Each model includes one of our aid measures, as well as the controls for country-level characteristics. Each of the aid measures is negatively as- sociated with MMRs, but in the case of the Total Aid mea- sure we fail to reject the null hypothesis. The results rep- resent the effect of a doubling of a given type of aid. The strongest effects are seen in total maternal and newborn health aid (from the ODA plus source) and in ODA com- mitted under the reproductive health category, where a doubling predicts a more than 33 death reduction and 26

Table 2. Two-way fixed effects panel regression of maternal mortality on total foreign aid, 1996–2015.

(1) (2) (3) (4) (5) (6)

Aid measures (logged)

Total aid −1.34

Total aid to health −7.12***

Aid to reproductive health −26.07***

Aid to family planning −13.10*

Total aid to population/reproductive −16.41***

policy and programming

Total Maternal and Newborn Health −33.46***

Aid (ODA plus dataset) Controls

Logged GDP per capita, −42.31*** −42.83*** −44.84*** −41.72*** −43.74*** −47.16***

(constant 2010 USD)

Births attended by skilled health −1.06*** −1.08*** −0.93*** −1.04*** −1.10*** −1.03***

personnel, percentage, percent

Adolescent fertility rate (births per 3.66*** 3.63*** 3.53*** 3.59*** 3.44*** 3.41***

1,000 women ages 15–19)

Contraceptive prevalence, modern −1.89*** −1.86*** −1.83*** −1.89*** −1.55*** −1.77***

methods (percent of women ages 15–49)

Constant 649.76*** 661.10*** 679.78*** 644.47*** 683.94*** 716.45***

Observations 2093 2093 2093 2093 2093 2093

Countries 130 130 130 130 130 130

R-Squared 0.70 0.70 0.69 0.70 0.69 0.70

Country FE yes yes yes yes yes yes

Year FE yes yes yes yes yes yes

Notes: * p < 0.05, *** p < 0.001.

2We also tested 2-, 3-, 4-, and 5-year lags and the results were comparable except in the case of one aid measure. Due to the nature of our dataset, the one-year lag maximizes our sample size.

death reduction in MMR respectively. These marginal ef- fects are shown in Figure 4, and indicate that, apart from total aid’s non-significant relationship to MMR, the most modest effect on MMR is for total health aid. Increases in family planning aid and total population/reproductive policy aid also predict reduced MMR.

Our controls for country and society characteristics are all correlated with MMRs at the p < 0.001 level.

A doubling of GDP per capita predicts the sharpest reduc- tion in MMR in all models, while more modest reductions in MMR are associated with increased rates of birth at- tendance by skilled health professionals and contracep- tive prevalence. In contrast, adolescent fertility rates are associated with increases in MMR in all models. The re- sults of these models show that countries with growing economies, improving health systems, more readily avail- able contraception, and decreasing teen birth rates all stand to see reductions in their national MMR over time.

When comparing our main results to those in our robustness checks included in the appendix, we note two differences worth discussing. First, with the change in sample introduced via the instruments in the instru- mental variable analysis (see Appendix Table A1), via the longer lag period (see Appendix Table A2), or via the use of the IHME MMR data which is restricted to the 1996–2011 period, the robustness of our estimate for the effect of family planning related aid on MMR is chal- lenged. In each of the robustness check models, we see that the family planning aid parameters no longer allow us to reject the null hypothesis. The second difference,

seen in Tables A1 and A3, are that with the shorter time- frame and alternate specifications, the total effect of aid on MMR does meet the p < 0.05 level in our robustness checks, suggesting that overall aid is correlated with re- ductions in MMR.

4.1. Robustness Checks

We also conducted a set robustness check models us- ing: (1) instrumental variable models; (2) instrumental variable regressions with five-year averaged aid flows;

(3) five different lag periods for our independent vari- ables; and (4) the alternative measure of MMR from the IHME. Our first robustness check was to reana- lyze our data using an instrumental variable approach (see Appendix, Table A1). Following Dreher and Langlotz (2017) and Doucouliagos, Hennessy, and Mallick (2019), we use an excludable instrument based upon the frac- tionalization of governments in donor countries inter- acted with the probability of recipient countries receiv- ing aid in a given year. We construct this instrument mea- sure using a dyadic donor-recipient aid dataset based on OECD figures used in Swiss and Longhofer (2016). Be- cause foreign aid levels are endogenous to some mea- sures of development and the other independent vari- ables in our model, we control for endogeneity by using a two-stage approach in our instrumental variable models.

In a zero-stage regression, we use OLS to regress our various aid measures on a lag of each aid measure and the five-year lag of donor government fractionaliza-

–40 –30 –20

Effect on Maternal Mortality Rao Logged Total aid (constant 2011 USD)

Logged Total aid to Health (constant 2011 USD)

Logged Total aid to reproducve Health (constant 2011 USD)

Logged Total aid to family planning (constant 2011 USD)

Logged Total populaon/reproducve policy and programming (OECD)

Logged Total Maternal and Newborn Health Aid (OCDA plus dataset)

–10 0

Figure 4. Marginal effect of logged aid on maternal mortality with 95% confidence intervals.

tion interacted with the probability of the recipient coun- try receiving aid from all donors. Because aid levels are closely linked to government competition within donor states (Dreher & Langlotz, 2017), this instrument the level of global aid is fluctuates independently of the con- ditions in recipient countries. Following this zero-stage model, we predict a fitted aid measure that serves as the excludable instrument in the first-stage model. By inter- acting the mean donor fractionalization with the mean probability of each recipient country to receive aid from all donors in a given year, the instrument remains exoge- nous to the MMR variable in the second stage.

In the two-stage IV regression, the aid measure is in- strumented on the fitted aid predicted in the zero-stage models. The IV models also include year and country fixed-effects. The results of the IV models in Table A1 show a similar pattern to our main results below.

The second robustness check tested an alternate specification of our aid measures using a five-year mov- ing average (see Appendix, Table A2). These results are consistent with our main analysis, but with the five-year averages, each of the predicted aid measures is associ- ated with reductions in maternal mortality.

Our third robustness check tested the effect of dif- ferent lag periods between our dependent and indepen- dent variables (see Appendix, Table A2). These results are consistent with our main analysis, but with a longer lag period, the predicted effects of family planning aid no longer attain p-values below the commonly accepted 0.5 threshold.

Our final robustness check was to repeat our analy- sis using the alternative MMR measure discussed earlier (see Appendix, Table A3). These results closely echo our main analysis but, as in the case of Table A1, there are some minor differences of note.

5. Discussion

Our findings show clearly that aid—depending on the sector in which it is spent—has the potential to help re- duce maternal mortality. As Figure 3 highlights, the ef- fects of reproductive health-focused aid or aid targeted specifically at maternal health are stronger than that of total aid or total health aid. Given the narrowed focus of reproductive health-focused aid, it is not unexpected it might reduce maternal mortality more directly. If, for in- stance, reproductive health aid is specifically channeled to the promotion of prenatal and postnatal care includ- ing deliveries (which are crucial in elements in the re- duction of maternal mortality), an increase in reproduc- tive health aid will have a greater likelihood of diminish- ing MMR.

With an equally narrow focus as reproductive health- related aid, what might explain the counterintuitive find- ing we see in the mixed effects of family planning- focused aid between our main analysis and the robust- ness checks? Comparing the relationship between repro- ductive health aid and family planning aid in Figure 5 re- veals relatively low correlation between the two types of aid (Pearson’s R of 0.28 in our sample). This suggests that the same countries receiving significant amounts of reproductive health aid are not necessarily also in receipt of family planning aid and vice versa. Likewise, the bivari- ate relationship of family planning aid to each of adoles- cent fertility, birth control, and MMR reveal very low lev- els of correlation < 0.1 in each case. This implies that, regardless of the intent of family planning-related aid to make contraceptives more widely available, these pro- grams are not necessarily associated with reducing MMR either directly or indirectly through reduced fertility or contraceptive use. Cleland et al. (2006) suggest that un-

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CV14CF95 CF96 CF97 CF98 CF99 CF00

CF02CF04CF05CF03CF06 CF01 CF07CF08 CF09 CF10LK00LK01CF12CF14CF11CF13

LK02LK03LK05LK08LK04LK07LK13LK09LK10LK06LK11 LK12 LK14

TD97

TD98

TD99 TD00

TD01TD02 TD03TD04 TD05TD06TD07TD10TD08TD11TD12 TD09

TD13

CL01CL02CL03CL04CL05TD14 CL06CL07 CL08 CL09 CL10 CL11 CL12 CL13 CL14 CN97 CN98 CN99 CN00 CN01 CN02CN03 CN04 CN05 CN06 CN07 CN08 CN09 CN10 CN11 CN12 CN13 CN14 CO95 CO96 CO97CO98 CO99CO00CO01CO02CO03CO04CO05CO06CO07CO08CO09CO10CO11 CO12 CO13 CO14 KM96 KM97 KM98 KM99 KM00KM03KM01KM02

KM04

KM05KM06KM07KM08KM09KM10KM14KM12KM13 KM11 CG05CG06

CG07 CG08CG09 CG10CG14CG11CD01CG12 CG13 CD02CD03CD05CD06CD07CD04CD09CD08

CD11CD10 CD12 CD13CD14 CR99 CR00CR01 CR02CR03 CR04 CR05 CR06 CR07CR08CR09CR10CR11 CR12 CR13 CR14 CU00CU07CU09CU11CU01CU04CU05CU06CU08CU10CU02CU03 CU12CU13 CU14BJ97BJ96 BJ98

BJ00BJ99 BJ01

BJ02 BJ03BJ04 BJ05

BJ06 BJ07 BJ08 BJ09

BJ11BJ10 BJ12 BJ13 BJ14 DO96

DO97 DO98 DO99DO00 DO01

DO02DO03DO04 DO05DO06

DO07DO08 DO09DO10

DO11 DO12 DO14DO13 EC99EC00

EC01EC02 EC03 EC04EC05 EC06EC07EC09EC08 EC10 EC11EC12 EC13EC14 SV98

SV99 SV00 SV01 SV02SV03SV04 SV05SV06

SV07 SV08 SV09SV11SV10 SV13SV12 SV14GQ00 GQ01 GQ02

GQ04GQ03 GQ05GQ11GQ12GQ06GQ10GQ07GQ09GQ08 GQ13GQ14 ET98ET99ET01ET04ET05ET03ET07ET02ET00ET10ET08ET09ET06

ET11ET12 ET13ET14 ER95 ER96ER97 ER98

ER99 ER00

ER01 ER02 ER03

ER04 ER05

ER07ER06ER08ER09ER10ER11 DJ10 GA00 GA01 GA02 GA03 GA05GA04

GA06 GA07GA09GA12GA08GA11GA13GA10GA14

GE00

GE01 GE02 GE03GE04GE06 GE05

GE07

GE08 GE09

GE10 GE11 GE13GE12 GM00GM01GM02GE14GM03

GM04 GM05GM06 GM07GM11GM08GM09GM10GM12GM13GM14 GH98

GH99GH00 GH01

GH02GH06GH04GH05 GH03

GH07GH11GH10GH08GH09 GH12

GH13 GH14

KI00 KI01 KI02 KI03 KI04 KI05

KI06KI07KI08KI09KI10KI14KI13 KI12 KI11

GT95 GT96 GT97GT98

GT99GT01GT00 GT02GT03

GT04GT05 GT06

GT07GT08 GT10GT09GT11GT12 GT13 GT14 GN99GN00 GN01

GN02 GN03

GN04 GN05 GN06

GN07GN10GN12GN08GN09GN11 GN13GN14 GY00

GY01 GY02

GY03 GY04

GY05

GY06 GY07GY09GY08 GY10 GY11 GY12GY13 GY14 HT96 HT97 HT98

HT00HT99 HT01 HT02 HT03

HT04 HT05 HT06

HT08 HT07 HT09 HT10

HT11 HT12

HT13

HT14

HN96HN97 HN98HN99

HN00HN01

HN02 HN04HN03

HN05HN06

HN07 HN08 HN09

HN10 HN11 HN12HN13

HN14 IN99IN01IN02IN00 IN03IN05 IN06IN08IN09IN11IN14IN10IN12IN13IN04IN07 ID95 ID96ID97 ID98

ID00ID99 ID01ID02ID03 ID04ID05 ID06ID09ID14ID07ID08ID10ID11ID12ID13 IR97 IR98 IR99 IR00IR03IR04IR05IR06IR07IR08IR09IR10IR11IR12IR13IR01IR02 IR14 IQ00IQ01 IQ02IQ03IQ05IQ06IQ07IQ04 IQ08IQ09IQ10

IQ11 IQ12 IQ13IQ14 CI99 CI00 CI01

CI02 CI04CI03 CI05CI06CI07CI10CI09CI12CI11CI08

CI13

CI14 JM97

JM98 JM99JM00 JM01 JM02 JM03 JM04JM05

JM06 JM07 JM08JM10JM11JM09

JM12 JM13

JM14 KZ95 KZ96KZ97 KZ98KZ03KZ06KZ09KZ02KZ04KZ05KZ08KZ10KZ11KZ07KZ00KZ99KZ01 KZ12 KZ13 KZ14 JO97 JO98

JO99 JO00 JO01

JO02 JO03

JO04 JO05JO06

JO07

JO08

JO09 JO10

JO11 JO12

JO13 JO14

KE98 KE99

KE00 KE01 KE03KE02KE05KE04KE06 KE07KE09 KE08

KE10KE14KE12 KE11 KE13 KW96

KW97 KW98 KW99 KW00 KW01 KW02 KW03 KW04 KW05 KW06 KW07 KW08 KW09 KW10 KW11 KW12 KW13

KW14KG97KG98KG99KG03KG06KG09KG10KG14LA00KG04KG05KG08KG07KG12KG02KG13KG01KG00 KG11 LA01

LA02LA03 LA04LA05 LA06LA08LA07LA12LA13LA10LA09LA14LA11 LB96 LB97 LB98 LB99LB01LB00

LB02LB03 LB04 LB05LB06LB09 LB10LB11LB08LB07 LB12LB13 LB14

LS00

LS02LS01 LS04 LS05LS03 LS06LS14LS08LS07LS09LS10LS11LS12 LS13

LR07 LR08

LR09 LR10

LR11 LR12

LR13

LR14

LY99 LY00 LY01 LY02 LY03 LY04 LY05 LY06 LY07 LY08 LY09 LY10LY11LY12 LY13 LY14 MG97MG98 MG99MG00MG01MG02

MG03 MG04MG05 MG06

MG07MG08 MG09MG10MG11 MG12 MG13 MG14 MW00

MW01 MW02MW04MW05MW03

MW06 MW07MW08MW09

MW10

MW11

MW12 MW13

MW14 MY04

MY05 MY06 MY07MY08MY09MY10MY11 MY12MY13 MY14

MV01 MV02

MV03 MV04MV05 MV06MV09MV10MV08MV07MV11 MV12MV13

ML96MV14 ML97ML98

ML99 ML00 ML01

ML02ML03ML06ML05 ML04 ML07

ML09ML10ML08 ML11 ML12

ML14ML13 MR01 MR02

MR03 MR04 MR05MR08MR07MR06

MR09 MR10 MR11

MR12

MR13MR14 MU03MU05MU10MU14MU08MU04MU12MU13MU07MU11MU06MU09MU02 MX97MX98MX99 MX00MX01MX03MX04MX05MX02 MX06 MX07MX08 MX09MX10MX11 MX12 MX13 MX14MN98 MN99MN00 MN01

MN03MN04MN02 MN05MN06MN07MN09MN10MN11MN08 MN12MN13 MD97MN14 MD98

MD99MD13MD07MD06MD09MD03MD04MD01MD02MD10MD05MD08MD12MD11MA95MD00MD14 MA96MA97

MA98 MA99MA00MA01 MA02MA05MA04MA03MA06MA07 MA08MA09MA10 MA11MA12 MA13 MA14 MZ97

MZ98 MZ00MZ99 MZ01

MZ02 MZ03 MZ05MZ04 MZ06 MZ07MZ09MZ08

MZ10 MZ11MZ12 MZ13MZ14 OM95 OM96 OM97 OM98 OM99OM00 OM01 OM02 OM03 OM04 OM05 OM06 OM07 OM08OM10OM09 OM11 OM12 OM13

OM14NA00NA05NA06NA01NA13NA14NA07NA04NP96NA10NA02NA03NA11NA08NA09 NA12 NP97

NP98 NP00NP99

NP01

NP02NP04NP06 NP05NP03 NP07

NP08

NP10NP11NP09 NP12 NP13

NP14

VU95VU96 VU97 VU98 VU99 VU00 VU01 VU02VU03VU04VU05 VU06 VU07 VU08VU09 VU10VU11 VU12 VU13 VU14 NI98

NI99 NI00

NI01 NI02

NI03

NI04NI06 NI05

NI08 NI07 NI10NI11NI09 NI12NI13 NE98NI14 NE99NE01NE00

NE02 NE03 NE04 NE05NE11NE09NE13NE07NE08NE10NE12NE14NE06 NG99 NG01NG00

NG03 NG02 NG04 NG05

NG06NG07PK97NG09NG10NG13NG11 NG12NG14NG08 PK98 PK00PK99 PK01PK02PK04PK03PK05PK06

PK07 PK09 PK08 PK11PK10 PK12 PK14PK13 PA09 PA10 PA11 PA12 PA13PA14 PG97 PG98 PG99 PG00PG01

PG02PG14PG03PG07PG08PG05 PG06PG04PG12PG09 PG10 PG11PG13 PY96PY97

PY98 PY99PY00

PY01

PY02 PY04PY05PY03PY06

PY07PY08 PY09 PY10 PY11PY12 PY13PY14 PE96

PE98PE97 PE99 PE00

PE01 PE02 PE04PE03 PE05PE06

PE07 PE08PE09 PE10PE11 PE13PE12 PE14 PH98 PH99PH00PH01

PH02PH03 PH04 PH05PH06 PH07 PH08PH09PH10 PH11PH12 PH14PH13 GW00GW01GW02

GW03GW04

GW06GW07GW05GW09TL03GW12GW08GW10GW11 GW14GW13 TL04

TL05TL06

TL07 TL08

TL09

TL10

TL11 TL12 TL13

TL14

QA00 QA01 QA02 QA03 QA04 QA05 QA06 QA07 QA08 QA09 QA10 QA11 QA12 QA13 QA14 RW00

RW01RW02RW03 RW04 RW05RW06

RW07RW08RW09 RW10RW11 RW12 RW13 RW14

LC12 LC13 LC14

ST01

ST02 ST03

ST04ST07ST10ST05ST09ST06ST08ST13 ST11 ST12

ST14 SA96 SA97 SA98 SA99 SA00 SA01 SA02 SA03 SA04 SA05 SA06 SA07 SA08 SA09 SA10 SA11 SA12 SA13 SA14 SN97

SN98 SN99 SN00 SN01

SN02 SN03 SN04SN05SN06

SN07SN09SN08 SN10

SN11 SN12 SN13

SN14

SL00SL02SL01 SL03SL06SL05SL04SL07

SL08 SL10SL09

SL11

SL12 SL13

SL14 SG97 SG98 SG99 SG00 SG01 SG02 SG03 SG04 SG05 SG06 SG07 SG08 SG09 SG10 SG11 SG12 SG13 SG14 VN97 VN98 VN99VN00 VN01VN02 VN03 VN04VN05 VN06VN07 VN08 VN09 VN10 VN11 VN12VN14ZA99ZA01ZA02ZA03ZA04ZA05ZA06ZA08ZA09ZA10ZA11SI95SI96SI97SI98SI99SI00SI01SI02SI03SI04SI05SI06SI07SI08SI09SI10SI11SI12SI13SI14ZA07VN13ZA13ZA00ZA12ZA98 ZA14ZW99 ZW00

ZW01 ZW02ZW03ZW04

ZW05ZW06ZW07

ZW08ZW11ZW10 ZW09 ZW12

ZW13 SD06ZW14SD07SD08SD11SD10SD09

SD12SD13 SD14

SR00SR01SR02 SR03 SR04

SR05 SR06

SR07 SR08

SR09SR11SR10 SR12 SR13 SR14SZ03SZ01SZ02SZ00SZ07SZ06SZ04SZ05SZ10SZ09SZ08 SZ11

SZ12SZ13SZ14 TJ00TJ05TJ06TJ04TJ02TJ03TJ01TJ07TJ08

TJ09 TJ11TJ10 TJ12TJ14TJ13 TH00 TH01 TH02 TH03 TH04TH05TH06 TH07 TH08 TH09 TH10 TH11 TH12 TH13 TH14 TG98TG99 TG00TG12TG05TG10TG06TG09TG07TG08TG11TG03TG02TG04TG01TG13TG14 TT00 TT01 TT02TT03 TT04 TT05 TT06 TT07 TT08 TT09 TT10 TT11 TT12 TT13 TT14 AE95 AE96 AE97 AE98 AE99 AE00 AE01 AE02 AE03 AE04 AE05 AE06 AE07 AE08 AE09 AE10 AE11 AE12 AE13 AE14 TN95 TN96 TN97TN98 TN99 TN00TN01TN02TN03TN07TN08TN10TN12TN13TN14TN04TN05TN09TN06TN11

TR98TR99 TR00 TR01

TR02TR03 TR04 TR05 TR06 TR07 TR08 TR09 TR10 TR11 TR12 TR13 TR14TM11TM13TM12TM05TM09TM01TM03TM04TM06TM02TM07TM08TM10TM00 TM14

UG95 UG96 UG97

UG98 UG99UG00 UG01

UG02UG03 UG04 UG05

UG06 UG07UG08UG10UG09

UG11 UG12 UG14UG13

UA99 UA00 UA01 UA02 UA03 UA04UA05 UA06UA07UA09UA08 UA10UA11 UA12UA13 UA14MK11 MK12MK13MK14 EG95 EG96

EG97 EG98

EG99EG00 EG01 EG02 EG03 EG04 EG05 EG06 EG08EG09EG07 EG11EG10 EG12EG13EG14 TZ96 TZ97TZ99TZ98

TZ01TZ00 TZ02 TZ03 TZ04TZ05

TZ06 TZ07TZ08TZ09

TZ10 TZ11 TZ12 TZ13

TZ14 BF00BF99

BF02BF01

BF03BF04 BF05 BF06 BF07BF08

BF09 BF10

BF11 BF12 BF13

UY04UY05UY06UY08UY09UY10UY11UY07BF14 UY12 UY13UY14UZ96 UZ97 UZ98UZ00UZ99 UZ02UZ01 UZ03

UZ04UZ05UZ08UZ09UZ07UZ06 UZ10 UZ12UZ11

UZ13UZ14 VE98 VE99 VE00VE01VE02VE03VE04VE05VE06 VE07VE08VE09VE10VE11 VE12 VE13 WS98VE14 WS99 WS00 WS01 WS02

WS03WS04WS05 WS06 WS07 WS08 WS09YE97YE98WS13WS14WS10WS12WS11 YE99 YE00YE03YE01YE02

YE04 YE05 YE07YE08YE06 YE09

YE10 YE11

YE12YE14YE13 ZM96 ZM97ZM98 ZM99 ZM00

ZM01

ZM02 ZM04ZM03ZM05

ZM06 ZM07ZM09ZM08

ZM10

ZM11 ZM13 ZM12

ZM14

2

0 4 6

0 5 10 15

Aid to reproducve health (constant 2011 USD)

Aid to family planning (constant 2011 USD)

Figure 5. Scatterplot of per capita family planning vs. reproductive health-related aid, sample countries 1996–2014.