Nathalie Ferrière
email: nathalie.ferriere@sciencespo-aix.fr.

Camille Noûs

Kathleen Brown

Jose De Sousa

Calumn Hamilton

Rozenn Hotte

Joris Muller

Filling the "decency gap"? Donors' reaction to US policy on international family planning aid

Keywords: Family planning, Foreign Aid, Mexico City Policy, Donor coordination

I study the impact of US allocation of family planning aid on other donors. Family planning provides representative insights into donor interactions. One donor, the US, dominates the sector but has changing policies on family planning due to domestic debates on abortion. Using the Mexico City Policy and exposure to this policy as an instrument, I find that other donors do not react to US policy changes in the short term, but two years later step in accordingly. This suggests that while some donors clearly intend to compensate for US policy, competition and herding behavior still operate; however, this may be mitigated in the short run.

Introduction

According to the United Nations Population Fund (UNFPA), one in two pregnancies in lowand middle-income countries is unwanted [START_REF] Bearak | Unintended pregnancy and abortion by income, region, and the legal status of abortion: estimates from a comprehensive model for 1990-2019[END_REF]. This leads to a gap between desired fertility rate and actual fertility rate, despite the 60% of such pregnancies that end in abortions. Lack of birth control negatively impacts the well-being of women and children [START_REF] Chari | The causal effect of maternal age at marriage on child wellbeing: Evidence from india[END_REF] and is slowing the fertility transition in some countries, particularly in Sub-Saharan Africa. While fertility is influenced by preferences, women's choices, and household bargaining [START_REF] Doepke | Women's empowerment, the gender gap in desired fertility, and fertility outcomes in developing countries[END_REF][START_REF] Rossi | Strategic choices in polygamous households: Theory and evidence from senegal[END_REF]), access to family planning programs (FP) may play a key role [START_REF] Casterline | Unmet need for family planning in developing countries and implications for population policy[END_REF]. 1 Different international conferences have emphasized the importance of family planning (Cairo, 1994;London, 2012;Nairobi, 2019), and access to safe, voluntary family planning is one target of the Sustainable Development Goals (SDG 3.7). Numerous studies have demonstrated the effectiveness of family planning in reducing both fertility and desired fertility [START_REF] Robinson | The global family planning revolution: three decades of population policies and programs[END_REF][START_REF] Bongaarts | Trends in fertility and fertility preferences in sub-saharan africa: the roles of education and family planning programs[END_REF]. 2Yet in 2020, an estimated 218 million women seeking to avoid pregnancy were still not using safe and effective family planning methods. In developing countries, family planning programs rely heavily on foreign assistance. In 2018, international donors contributed an estimated 48%, domestic governments 35%, and consumers 17%. There are large disparities across countries, with donor contributions representing 10% of total family planning expenditure in Bangladesh, 41% in Myanmar, and 61% in Kenya. 3 . However, funds are not always reliable, being subject to the whims of donors and their capacity to coordinate and compensate for withdrawal or decreased contributions from other donors. The family planning sector can be considered a case representative of donor coordination. Firstly, all international conferences on population and development, as well as some donors and international organizations, emphasize the negative consequences of unmet family planning needs. Secondly, providing access to a contraceptive method is a common aspect of aid projects regardless of the funders, reducing the inter-donor heterogeneity of projects and facilitating substitution between projects. These two factors should promote inter-donor coordination in this sector, as pointed out by the 2005 Better Aid Agenda. In this context, an effective way to coordinate would be to implement a division of labor that avoids duplications and ensures better access to contraceptives. However, the literature shows that in practice, there is a long way to go before coordination becomes a reality [START_REF] Nunnenkamp | Donor coordination and specialization: did the paris declaration make a difference?[END_REF][START_REF] Nunnenkamp | Aid fragmentation and donor coordination in uganda: A district-level analysis[END_REF]. 4Importantly, the family planning sector is largely dominated by one donor, the United States (US). Since 1990, the US has accounted for approximately 49% of disbursements. The second-largest donor, the United Kingdom, has only provided 10% of family planning aid over the same period. As the primary funder of family planning and HIV activities worldwide, the US policy agenda and funding levels have a significant impact on global sexual and reproductive health (SRH) activities. Due to their dominant role as a donor, the US allocation of aid to specific countries likely affects aid flows from other donors. In addition, the identity and size of the donor tend to be important factors [START_REF] Kilby | World bank lending and regulation[END_REF][START_REF] Steinwand | Compete or coordinate? aid fragmentation and lead donorship[END_REF][START_REF] Humphrey | China in africa: Competition for traditional development finance institutions[END_REF]. 5Building on the literature on donor coordination and on the competitive use of development finance, my paper analyzes how other donors adjust their allocation of family planning aid in reaction to the US allocation. This question is critical as "the US foreign policy on family planning has undergone several important changes over the last 40 years" (van der Meulen Rodgers, 2018) resulting in significant variations in their family planning aid. Therefore, the way donors cooperate/interact with the US will critically affect the possibility of limiting family planning aid volatility for recipient countries and the detrimental effects of a lack of funds for women. 6The theoretical literature provides arguments for both positive and negative reactions to changes in aid allocation. For example, [START_REF] Bourguignon | The Hard Challenge of Aid Coordination[END_REF]'s framework involves a trade-off between aid effectiveness and political independence. Coordination, such as division of labor, can increase aid effectiveness but reduce national autonomy in dealing with aid recipient countries. Substitution occurs when the emphasis on aid effectiveness is greater than the emphasis on political independence. As discussed in [START_REF] Davies | Darlings and orphans: Interactions across donors in international aid[END_REF]), the reaction to changes in aid allocation by other donors may be dynamic and vary over time. They find empirically that donors' reactions differ more in the short term than in the long term because of information signals. A donor's allocation indirectly provides information on the recipient's needs. Regarding the changes in the US aid allocation related to domestic debates on abortion, the US has argued that the funding decrease is necessary to avoid financing abortions abroad. This argument has been criticized by other donors, particularly European donors, who call for the "decency gap" to be filled [START_REF] Assembly | Working Papers 2003 Ordinary Session (fourth Part) 25[END_REF]. This could be interpreted as donors placing more emphasis on aid effectiveness and less on political independence in the short term, particularly as the topic has been widely publicized by the media and non-governmental organizations (NGOs). However, in the long run when the topic is less salient, the trade-off could again be favorable to national autonomy and competition against other donors. Additionally, the literature distinguishes between donors' reactions according to certain characteristics. Large donors tend to place more emphasis on their political independence than small donors [START_REF] Annen | Donor competition for aid impact, and aid fragmentation[END_REF], making small donors more likely to react negatively to changes in US aid allocation in the short term.

In the long term, or even in the short term when competition among donors matters more, herding effects may be more common [START_REF] Frot | Herding in Aid Allocation[END_REF][START_REF] Davies | Darlings and orphans: Interactions across donors in international aid[END_REF][START_REF] Zeitz | Emulation or differentiation? china's development finance and traditional donor aid in developing countries[END_REF][START_REF] Ferrière | To give or not to give? how do other donors react to european food aid allocation[END_REF].

To determine if and how other donors react to the US allocation of family planning aid, I employ an instrumental strategy using two sources of variation, in line with the empirical literature on aid [START_REF] Nunn | US Food Aid and Civil Conflict[END_REF][START_REF] Dreher | Aid, china, and growth: Evidence from a new global development finance dataset[END_REF]. First, I utilize exogenous timevariation induced by US domestic debates on abortion between Democrats and Republicans that are not linked to international concerns or recipient-related considerations. The US foreign policy on family planning has been driven over the last 40 years by the successive rescinding and reinstating of the Mexico City Policy (MCP). The MCP was first implemented by President Reagan in 1984. It directs US agencies, including USAID, to withhold funds from non-US non-governmental organizations that provide abortion-related services. Since 1984, the policy has been a symbol of the Republican Party and is only active during Republican administrations. Second, I exploit cross-sectional variation in a country's vulnerability to these changes, which is measured by the proportion of years in which a country receives family planning aid from the US when the MCP is not active, interacted with the share of family planning aid channeled by those non-US NGOs affected by the policy. The results indicate that the short-term response to US policy is different from the long-term response.

In the short term , the "decency gap" and the public good count most, overriding political costs, autonomy or competition with other donors. However, in the long term, two or three years later, donors tend to increase their allocation to compensate for the US. In the short term , the "decency gap" is important, and donors place more emphasis on the public good rather than on political costs, autonomy or competition with other donors.

However, this stepping up to support aid effectiveness is not enough to offset the impact of the Mexico City Policy on developing countries. Bilateral reactions support this mechanism, as small donors respond negatively in the short term but either do not respond or respond positively in the long-term. Conversely, large donors, for whom competition with other donors and political autonomy are more important, respond positively even in the shortterm. Additional results also support this mechanism. Donors geopolitically close to the US and donors competing with the US for trade tend to follow the trend of the US allocation, as do donors with some restrictions on abortion. The positive response in the long term is more pronounced in recipient countries where abortion is restricted. This provides new evidence that donors' responses depend not only on the type of aid but also on donor identity and size.

My findings contribute to several literatures. These results complement the empirical literature on donor interactions and their dynamics, underlining the need to look at reactions at different times. While previous work finds positive reactions in the short term, here, given the specific reason for US withdrawal from the family planning sector, I do not find reactions in the short run. However, in the long run, a crowding-in effect appears. How other donors interact strongly affects the interest donors take in donor coordination, alignment, and specialization [START_REF] Mascarenhas | Do donors cooperatively fund foreign aid?[END_REF] and thus, the actual donor coordination policy that could improve aid effectiveness. Second, aid is shown to be determined not only by the strategic and economic needs of donor countries [START_REF] Alesina | Who gives foreign aid to whom and why?[END_REF][START_REF] Fuchs | Why Donors of Foreign Aid Do Not Coordinate: The Role of Competition for Export Markets and Political Support[END_REF] but also partly by domestic politics and party ideologies [START_REF] Tingley | Donors and Domestic Politics: Political Influences on Foreign Aid Effort[END_REF][START_REF] Brech | Donor ideology and types of foreign aid[END_REF][START_REF] Dreher | The allocation of german aid: Selfinterest and government ideology[END_REF][START_REF] Greene | Domestic politics and changes in foreign aid allocation: The role of party preferences[END_REF]. Finally, my findings raise questions about aid allocation at the sectoral level, providing evidence of specific determinants of aid provision [START_REF] Lewis | Environmental aid: Driven by recipient need or donor interests?[END_REF][START_REF] Kuhlgatz | Food Aid Allocation Policies: Coordination and Responsiveness to Recipient Country Needs[END_REF][START_REF] Fink | Determinants of international emergency aid-humanitarian need only?[END_REF].

The remainder of the paper proceeds as follows. Section 2 provides an overview of US family planning aid and of the anecdotal evidence on how other donors react to the US. Section 3 describes the data and details the identification strategy and estimating equations. Section 4 discusses the results and explores the mechanisms, while section 5 concludes.

Family Planning Aid

US Family Planning Aid

In 1961, the Foreign Assistance Act stipulated that the US should assist developing countries in controlling population growth [START_REF] Blanchfield | Abortion and family planning-related provisions in us foreign assistance law and policy[END_REF]. Family planning was among the types of activities USAID could pursue. Starting from the mid-1960s, the budget for population control activities was multiplied by 10 relative to the beginning of the 1960s. At that time, voluntary family planning was perceived as a way to "improve health, family stability, greater individual opportunity, economic development." USAID's strategy for delivering family planning relied mainly on private organizations, especially NGOs, particularly in countries with no bilateral assistance programs.7 During the 1970s, the USAID budget devoted to population control programs increased. Since, the US has consistently been one of the largest donors supporting international population assistance worldwide. In 1973, 47% of its funds were spent on contraceptives and delivery of family planning services [START_REF] Fox | American population policy abroad: The mexico city abortion funding restrictions[END_REF], and the US remains by far the largest donor in family planning programs today. Starting from 1990, according to the Institute for Health Metrics and Evaluation (IHME), they have provided 49% of the total aid allocated to the sector, to an average 67 recipient countries every year.

For the recipient country, the average amount allocated is about 5,100,000 constant 2020 US dollars per year.

The most important change in US family planning assistance policy occurred during the UN Population Conference in August 1984, with the adoption of the Mexico City Policy (hereinafter MCP). President Reagan issued an executive order restricting family planning funding (The White House Office of Policy Development, 1984). It required that recipients of US funds cease all abortion activities -abortion, promotion of abortion, or lobbying for a change in abortion legislation -even those conducted with non-US funds. Organizations receiving US family planning aid were required to certify in writing that they did not, and would not while the funding agreement held, perform or actively promote abortion as a method of family planning. The MCP made no distinctions for countries where abortion is legal and only applied to foreign NGOs and funds provided by USAID. 8 Since it was not retroactive, the policy's full funding impacts could be delayed by several years. The MCP was active until the election of Bill Clinton, who rescinded it on January 22, 1993, allowing USAID to fund organizations that performed abortion-related activities using other funds. The MCP marked a clear distinction between Democrat and Republican parties: it was reinstated by all Republican presidents and rescinded by all Democratic presidents thereafter. 9

The MCP's repercussions were quickly documented after its first adoption. [START_REF] Camp | The impact of the mexico city policy on women and health care in developing countries[END_REF] provided a first qualitative analysis showing its negative impact on organizations and family planning activities, although few large organizations were affected in 1987. Population Action International documented the effect of the policy's reinstatement by the Bush Administration. By 2002, the MCP had ended shipments of USAID-donated contraceptives to 16 developing countries. Leading family planning agencies in another 13 countries were ineligible for USAID contraceptives because they refused to abide by the restrictions [START_REF] Pai | The global gag rule and contraceptive supplies[END_REF].

In 2020, the State Department released a Review of the Implementation of the Protecting Life in Global Health Assistance Policy (the extended MCP under the Trump Administration) [START_REF] Pompeo | Review of the implementation of the protecting life in global health assistance policy[END_REF]. The review showed that a minority of organizations decided to do without U.S. global health assistance in the light of the policy's requirements, but did not provide the amount of funds involved.

8 According to Camp (1987, p41) the 1985 decision taken by the Reagan administration "has been to stifle opposition and to create obstacles to a legal challenge. [. . . ] Shifting the burden of the restrictions to foreign NGOs weakened the grounds for legal challenge, since such organizations may not have standing in U.S. courts. The shift may have also deterred certain prestigious AID grantees, such as major U.S. universities and teaching hospitals that might have mounted a successful challenge had their academic freedom at home been more directly attacked."

9 It also caused wide debate in Congress, especially when Congress was not aligned with the President. For instance, family planning funds were blocked for nine months in 1995 and the MCP was reinstated legislatively for one year from October 1999 to September 2000.

INSERT FIGURE 1 HERE

It could be argued that the US had only decided to change its methods of channeling family planning aid, focusing on governmental channels, or that a majority of foreign NGOs agreed to the terms of the MCP. However, figure 1provides evidence of a decrease in family planning aid when the MCP was active (periods in gray). A.1 in appendix A shows that the share of family planning aid in total development aid is decreasing during Republican terms, in terms of commitments. 11 In addition, the number of recipients is lower (53) when the MCP is implemented than when it is not (83). 12 10 Data comes from the Development Asssistance for Health Database of the IHME that covers the period 1990-2020. Data are presented in more detail in section 3.

11 As expected, the pattern is more pronounced for commitments than for disbursements. The period covered by CRS-OECD data is 2000-2020, with better accuracy on sectoral allocation starting 2005 and not 1990-2020 as for the IHME database. A figure for disbursements is provided in online appendix A.1.

12 In on-line appendix A, I investigate the determinants of US family planning aid by running a regression including a dummy equal to one when the MCP is active. Table A.1. provides the results. The US allocates less family planning aid when the MCP is active. However, aid is also partly driven by needs related to reproductive and sexual activities: the higher the prevalence of HIV, the larger the amount of US aid. I also observe a non-linear relationship between fertility rate and US aid allocation.

Other Donors' Family Planning Aid

Figure 1 also shows the overall evolution of family planning disbursements by other donors, with a pattern relatively similar to the US pattern. Four relatively important donorsthe United Kingdom (UK), Germany, the Netherlands, and the Bill and Melinda Gates Foundation (BMGF) -contribute more than 5% each between 1990 and 2020. 13 Those donors provide aid to fewer countries than the US (from 14 on average for the Netherlands to 66 for the BMGF) and operate smaller projects. The average amount allocated yearly to recipient countries is between 500,000 and 1,300,000 2020 constant US dollars for the four largest donors. However, their participation has evolved differently. While the UK and the Netherlands have been constant in providing family planning aid, Germany has decreased its family planning aid budget since 2000 and the BMGF has increased its participation over time. For smaller donors, the average number of recipient countries is about 7, with a yearly average of about 275,000 2020 US dollars allocated to each. Some donors attempted to compensate by adjusting their funds to the US allocation, mainly in reaction to MCP reinstatement in 2001. Nevertheless, according to a report from the European Parliamentary Assembly, they were not able to bridge the entire gap. The report stresses the leading role of Nordic European countries, Germany and the Netherlands. Poul Nielson, the European Union (EU) Commissioner for Humanitarian and Development Aid, summarized the spirit of European donors' reaction to the Bush administration's reinstatement of the MCP when he said that Europe should fill the "decency gap" [START_REF] Assembly | Working Papers 2003 Ordinary Session (fourth Part) 25[END_REF]. The report also underlined the increase in European donor funding experienced by UNFPA in 2002 in reaction to the decrease from the US. The report concluded that "the continuing challenge is, however, to build on this goodwill and not just to sustain but to continue to increase this support". The extension of the MCP in 2017 led to stronger reactions from other donors. The European Commission explicitly stated its intention to "remain 13 Each other donor represents less than 3% of total family planning aid.

alert on this issue and if it finds that there is a funding gap, it will look into possibilities for stepping-up the assistance to health and gender-based violence projects provided that sufficient funding is available" (European Commission, 2017). Sweden decided to stop providing support to reproductive and sexual health programs run by groups complying with the MCP provisions [START_REF] Reuters | Swedish aid agency to halt funds for supporters of u.s. anti-abortion 'gag rule[END_REF]. The Netherlands created a new fund, She Decides, to replace the money lost to family planning organizations under the MCP. The launching conference brought together 50 governments and 450 people. However, European parliamentary members' discussions show some divergence in opinion among and within member states.

While most criticized the US decision in March 2017 during a debate on the MCP, a German member reminded the parliament that abortion is not under EU jurisdiction and that in some EU countries it remains an offence, while a French member called for US national sovereignty to be respected when financing foreign NGOs 3 Data and Empirical Strategy

Data on family planning aid

The Institute for Health Metrics and Evaluation database (IHME, 2020) provides estimates of health spending from four sources -government, out-of-pocket, prepaid private, and Development Assistance for Health (DAH) -for 195 countries from 1990 through 2020. It defines DAH as the financial and in-kind contributions from major development agencies to low-and middle-income countries to maintain or improve population health. The database relies on annual reports, budget documents, and project disbursement records reported by different international development agencies like CRS-OECD, the World Bank, the Global Fund, and large philanthropic entities. IHME also tracks the agencies responsible for disbursing the funds. Data only cover disbursements, not commitments. The IHME database disaggregates reproductive and maternal health (RMH) into family planning, other maternal health, and human resources. Aid is allocated to the family planning sector if the project description contains at least one of the following words: fertility, family planning, FP, birth control, family size, IPPF (international planned parenthood), planned parenthood, abortion, birth spacing, condom, IUD, vasectomy or tubular ligation.14 I chose these data rather than the CRS-OECD data usually used for sector analysis on aid allocation because they provide better period coverage, starting in 1990 rather than 2005. In addition, the definition of family planning is narrower than the corresponding code for the CRS-OECD data (code 13020 and 13030) and better fits the definition used by the US when funding family planning projects.

EU funds are reallocated to European members weighted by their contribution to the total EU budget, and the EU is only seen as an implementing agency. However, the allocation of EU aid is normally independent of the member states. Hence I reconstruct aid from the EU by combining all aid channeled through the EU in the data. For member states, I subtract these funds from their allocation.

An observation is an aid flow from one donor to a recipient country in a given year through a given channel (bilateral, various multilateral organizations, US NGOs and Foundations, international NGOs). I construct a panel of 25 donors (excluding the US) and 106 recipients, running from 1990 to 2018, choice of time period being driven by the availability of family planning aid data. 15 It includes all recipients and donors who receive or give, for at least one year, family planning aid. Aid is measured in thousands of constant 2020 US dollars.

General Specification

The baseline specifications estimate bilateral family planning aid disbursements from donor d to recipient r in year t as a function of recipient characteristics X r,t-1 and donor-recipient characteristics X dr,t-1 . The control variables are drawn from the existing literature and described below. I then include family planning aid from the US, F P AU S r . The reaction of other donors to the US allocation can vary between short and long term. I change the timing of the US aid allocation, moving from an immediate reaction to a reaction three years later, thus estimating four different regressions. 16

F P A drt = β k 1 F P A U Srt-k + β k 2 X drt-1 + β k 3 X rt-1 + λ k dt + λ k dr + k drt (1)
The dependent variable F P A drt is the logarithm of bilateral family planning aid from donor d to country r at time t. To deal with zero values, I apply the sine hyperbolic transformation.

Aid is measured in thousands of constant 2020 US dollars. F P A U Srt-k is the log of bilateral disbursed family planning aid from the US to the country r at time t -k, with the same transformation. I consider the short-term reaction occurs at time t and t -1 while the long-term reaction occurs at time t -2 and t -3.

For the recipient country, I include GDP per capita rt-1 and population rt-1 (in log) to control for wealth and size. Following [START_REF] Asiedu | Determinants of Foreign Aid in Family Planning: How Relevant is the Mexico City Policy[END_REF], who investigate the determinants of family planning aid, I control for female fertility rate and its square, one objective of family planning aid being a reduced fertility rate. I also include the adolescent fertility rate because some donors may focus more on reducing early pregnancies. According to UNFPA, family planning could reduce poverty, the spread of HIV/AIDS, and maternal mortality. Hence I also control for poverty rate, female life expectancy, the incidence of HIV in the 15-49 population age (number of new cases), the prevalence of HIV in the same population (total number of existing cases), and maternal mortality rate. These data come from the World Development Indicators. 17 In addition to these variables, as aid allocation tends to depend on 16 Another way to look at the dynamic effects is to include different lags on the US allocation of FP aid in the same regression. However, given the instrumental strategy described later, I choose a specification where the US allocation's different lags are introduced one by one. Results are similar and provided in in appendix B.

17 For maternal mortality rate and poverty rate, data before 2001 come from the official MDG Indicators website. Last-known figures are imputed for missing years. The sample is reduced by 33% when economic controls are included, by 48% when health controls are included in addition. the recipient's political situation [START_REF] Burnside | Aid, Policies, and Growth[END_REF], I include a democracy index (Polity IV database).18 Finally, to measure political ties, I include the voting alignment between donor and recipient at the UN General Assembly, a widely used indicator. It is measured as the absolute difference in their ideal points, calculated by [START_REF] Bailey | Estimating dynamic state preferences from united nations voting data[END_REF]. 19I allow time effects to differ across donors with donor-year fixed-effects, λ dt . This accounts for donor-specific trends in the family planning aid budget or for electoral cycles that can affect the allocation of aid [START_REF] Tingley | Donors and Domestic Politics: Political Influences on Foreign Aid Effort[END_REF]. λ dr is the donor-recipient fixed effects that catch time-invariant features such as colonial links, distance, or sharing a common language.

The coefficient of interest, β k 1 , is the estimated effect of the FP allocation by the US in country r k years before on the FP allocation of donor d in country r at time t. A positive coefficient indicates that, on average, if the US increases its family planning aid to a specific country r, it increases the amount of family planning aid from donor d to the recipient country k years later. By contrast, a negative coefficient suggests that other donors step in and compensate. Given that the budget cycle is not the same in all countries and that, short term, donors can either react to an announcement of disbursements (t) or wait to observe the disbursements through DAC-OECD data for instance (t -1), I consider t and t -1 as short-term reactions.

F P A U Srt-k is endogenous. First, donors may react to shocks for which I do not have reliable data or which I do not observe at all. For instance, in 1994, the Cairo International Conference on Population and Development emphasized the integral linkages between population and development and focused on meeting the needs of individual women and men, rather than on achieving demographic targets. As a consequence, "family-planning promotion has dropped steadily down the list of international development priorities" according to [START_REF] Cleland | Family planning: the unfinished agenda[END_REF]. Nor can I control carefully for all changes in recipient policies regarding population control, abortion, or reproductive health that might affect a donor's allocation, leading them either to support these policies or to withdraw their support. Depending on the reactions, the OLS will be downward-or upward-biased. Second, there is a problem of reverse causality: the US may also react to other donors' allocations.

Instrumental Strategy

To provide causal evidence of donors' interactions, I develop an instrument for the US allocation based on a natural experiment, the rescinding and reinstatement of the Mexico City Second, in some countries, US family planning aid is mainly channeled through official governments, while in other countries the US relies more on non-US NGOs. These latter countries should be more affected by the policy, as the MCP only prohibits funding aid to non-US NGOs performing abortion-related activities. I compute shareN GO r as the share of US FP aid channeled through NGOs during the Obama term. I do not include the Clinton Administration because of less reliable data on channels before 2000. 22 The difference in pattern between periods of active/inactive policy seems to be more pronounced in highlyexposed countries, in line with how the policy is likely to affect aid allocation. 23 I make use of this over-time and cross-section heterogeneity in provision of and recipients of US family planning aid. Hence the reform should have a greater effect, in absolute terms, on countries that have often received family planning aid when the policy is inactive. In addition, the policy should also have a greater effect on countries where aid is often channeled by non-US NGOs. Figure 2 shows the evolution of US FP aid to highly-and little-exposed countries for the indicator of vulnerability.

INSERT FIGURE 2 HERE

It is worth noting that the MCP treatment may capture more than just the policy's direct impact on aid procurements. All the rhetoric about abortion and family planning may also affect other donors' reactions. Not only does the MCP cut funds, but it provides a new reference model of family planning assistance that now excludes some activities and puts less emphasis on family planning. The way I define the instrument prevents me from disentangling the two effects; I can only examine the overall effect of the MCP and of any other policy changes correlated to the MCP and impacting US FP aid. In the end, F P A U Srt-k

22 Ideally, these two indicators would be computed before any MCP implementation. However, data are not available before 1984. The second-best option would have been to compute both indicators before each reinstatement. For instance, by using the probability of receiving FP aid from the US and the share channeled through non-US NGOs during the Clinton mandate for the Bush and Obama period and by computing the same indicators during the Obama period for the Trump and Biden mandates. However, the channel is not well recorded before the 2000s and when the information is lacking, the bilateral channel is recorded. The best option seems to be to compute the channel share during the Obama period and the probability of receiving FP aid over all the rescinding periods.

23 See Figure B.2 in on-line appendix.

instrumented by the contemporaneous instrument γ k 1 M CP t-k * F P r * shareN GO r . Thus the first-stage equation is the following, where k varies from 0 to 3 depending on whether I focus on short-or long-run reactions.

F P A U Srt-k = γ k 1 (M CP t-k * F P r * shareN GO r ) + γ k 2 X drt-1 + γ k 3 X rt-1 + λ k dt + λ k dr + k drt-k (2)
I expect a negative coefficient for the instrument. Aid to countries that often receive family planning aid from the US through non-US NGOs will be disproportionally decreased when the MCP is reinstated.

An obvious concern is that this instrument may violate the exclusion restriction: the probability of receiving US family planning aid may directly affect the amount of aid allocated by other donors because of particular connections between recipient and donor countries.

However, the second-stage regression controls for the effects of the probability of receiving US family planning aid, through the inclusion of recipient-donor fixed effects. Given this control, interacting that probability with the exogenous variable yields an exogenous instrument under the assumption of parallel trends [START_REF] Bun | Ols and iv estimation of regression models including endogenous interaction terms[END_REF][START_REF] Goldsmith-Pinkham | Bartik instruments: What, when, why, and how[END_REF].

The identifying assumption is that aid allocation from other donors in countries with differing probabilities of receiving US family planning aid via non-US NGOs will not be affected differently by changes induced by the change in US foreign policy, other than via the impact of US aid allocation, controlling for recipient-donor-and donor-region-year -fixed effects.

Causal inference using the interacted instrumental variable relies on the assumption that conditional on the controls, the interaction between (lagged) US policy activation and a

Results

Short-and Long-term Reactions

Table 1 presents This confirms that the implementation of the MCP has more than just a rhetorical effectit affects US funding.

The key results are shown in part C. I estimate the average treatment effect on the complier population, here the countries for which US family planning aid is affected by the MCP. I find that donors to these recipient countries tend not to react significantly to the US FP allocation in the short term (columns 1-2). However, in the long term (column 3-4), donors crowd in regarding the US allocation; the effect is significant at a 10 percent level.27 Hence, for MCP-affected countries, this supply effect is neither reinforced nor compensated for by other donors immediately. However, the effect is reinforced with a two-and three-year lag.

On average, a 1% decrease in US FP aid induces a 0.1% decrease in donor d aid. 28The dynamics of the reaction can be interpreted in two ways. The first is that donors need some time to adjust to actual disbursement by another donor. For instance, after MCP reinstatement in January 2017, the international summit "She Decides" was launched in April 2017 but obtained funds until October 2017 and funded new projects often starting in 2018 or 2019. In addition, donors need to observe the actual US allocation to adjust their own allocation. However, this argument is not the preferred interpretation. Indeed, previous literature [START_REF] Mascarenhas | Do donors cooperatively fund foreign aid?[END_REF][START_REF] Kuhlgatz | Food Aid Allocation Policies: Coordination and Responsiveness to Recipient Country Needs[END_REF][START_REF] Davies | Darlings and orphans: Interactions across donors in international aid[END_REF][START_REF] Ferrière | To give or not to give? how do other donors react to european food aid allocation[END_REF] has found significant and positive interactions among donors in the short term (contemporaneous or with one lag). Contrary to these findings, here donors only react to the US in the long run. The theoretical frameworks on donors' competition by [START_REF] Bourguignon | The Hard Challenge of Aid Coordination[END_REF] and [START_REF] Annen | Donor competition for aid impact, and aid fragmentation[END_REF] provide interesting insights for a second interpretation. They both consider the trade-off between aid effectiveness, with aid as a public good, and competition or political independence in aid allocation. When donors put more weight on aid effectiveness, they are more likely to substitute for each other or not to react to others' allocation. Conversely, when donors value competition or their political independence more, we should observe complementarity. Here, MCP implementation could be seen as changing the weight donors give to aid effectiveness. As a reaction to the policy, donors adopt a more positive attitude to family planning aid and its effectiveness. As a result, the trade-off is less in favor of competition, which means that donors do not react to the US allocation. However, with time, the competition effect resurfaces and in the long term, donors again react positively to the US allocation.

Exploring the Mechanisms

Bourguignon and Platteau (2015) and [START_REF] Annen | Donor competition for aid impact, and aid fragmentation[END_REF] provide additional arguments that can be tested to support this second interpretation. First, they point out that small donors tend to put more weight on aid effectiveness (due to different mechanisms) while large donors compete more and are more reluctant to abandon their political independence on aid allocation. In that case, small donors should be more likely than large donors to compensate for the US allocation in the short run, and large donors less likely to change their behavior both short and long term. Second, donors in economic competition over the recipient country should be more likely to react positively to the US allocation and less likely to change their behavior over time. Third, donors geopolitically aligned with the US may be more reluctant to compensate for the US. In that case, we should not observe differences between the short-and long-run reactions. Fourth, if aid effectiveness matters, the fact that the MCP is perceived as an anti-abortion policy may drive donors to compensate for the decreased US allocation only in countries where abortion-related activities are allowed.

Finally, donors whose own abortion laws are more restrictive should be less likely to react to the US allocation, perceiving the US policy change more positively.

Large and Small Donors

To examine the different large and small donor reactions and their dynamics, I look at bilateral reactions. In the baseline specification, I interact the US allocation with a dummy for each donor and do the same for the instrument. 29 This yields the following second-stage equation, where the coefficients of interest are β dk 1 :

F P A drt = 25 d=1 β dk 1 F P A U Srt-k * donor d + β k 2 X drt-1 + β k 3 X rt-1 + β k 4 X drt-1 * F P r * shareN GO r + β k 5 X rt-1 * F P r * shareN GO r + λ k dt + λ k dr + drt (3)
Results are plotted in figure 3. 30 The inclusion of 25 donors and interaction with the instrument lead to a strong decrease in the K.-P F-Stat; the presence of weak instruments cannot be excluded. Results should be analyzed bearing this in mind. Donors in bold are large family planning aid donors, representing over the period more than 1% of total family planning aid (including US aid) and more than 5% of non-US aid. Green squares represent the short-term reaction while blue triangles represent the long-term reaction.

INSERT FIGURE 3 HERE

As expected, large donors react positively and significantly to the US family planning aid allocation both short and long term. Contrastingly, most small donors do not react to the US allocation, while some small donors compensate for the US allocation in the short run.31

In the long term, only Canada and Finland continue to significantly compensate for the US; other small donors no longer react significantly. Except for the Netherlands, we always observe a shifting to the right consistent with the idea that, in the long run, donors readjust their trade-off in favor of competition and react more positively to the US allocation.

Economic Competition

The literature on aid allocation shows that donors allocate aid preferably to where they have trade interests [START_REF] Berthélemy | Bilateral Donor's Interest vs. Recipients' Development Motives in Aid Allocation: Do All Donors Behave the Same?[END_REF]. Hence, strategic donor behavior and economic competition for commercial advantages from a recipient country may affect the reaction to the US allocation. In particular, donors who share with the US extensive economic interests in a country are more likely to compete with the US. In such cases, donors should react positively to the US allocation, as the trade-off between aid effectiveness and political/economic costs is in favor of the economic costs. However, donors can legitimately be expected not to react to the US allocation in countries where they have less economic interests and do not directly compete with the US. To test this hypothesis, I construct an indicator of export competition that varies over donor and recipient. 32 Next, for each recipient, I divide the donor sample into two groups: those engaged in low export competition with the US and those with high export competition. Results are shown in figure 4. Where commercial competition is low, donors do not react to the US allocation either short or long term. In contrast, where commercial competition is high, donors crowd in regarding the US allocation in the long run but do not react significantly in the short run. In both cases, the groups' reactions differ significantly; on average, donors react more to the US allocation where commercial competition is high.

This result is consistent with the hypothesis that, in the short term, donors focus more on aid effectiveness but that having economic interests at stake mitigates their reaction.

INSERT TABLE 4 HERE

32 Following [START_REF] Fuchs | Why Donors of Foreign Aid Do Not Coordinate: The Role of Competition for Export Markets and Political Support[END_REF], the indicator of export competition between donor d and the US in recipient country r at time t is defined as M in(X drt ,X U Srt ) M ax(X drt ,X U Srt ) with X representing the share of exports to recipient r in donor country d's total exports. I next keep the maximum value of this indicator over the period analysis. Export data come from COMTRADE. This analysis excludes the BMGF.

Proximity to the US

Similarly, more US-aligned governments could be expected to be reluctant to allocate more family planning aid to countries whose US allocation has decreased. Such a reaction might be interpreted as acting in defiance of the US and could be politically costly. I construct a proxy of geopolitical alignment with the US based on the minimum share of UN General Assembly resolutions on which the donor and the US vote similarly. I divide my donor sample into two groups depending on whether their proxy is higher or lower than the median value. This heterogeneity analysis excludes the EU and the BMGF as donors because UNGA voting patterns cannot be constructed for them. Results are shown in figure 4. Donors who are less geopolitically aligned with the US do not react significantly to the US family planning aid allocation in both the short and the long run. On the contrary, geopolitically aligned donors react significantly and positively to the US allocation and even more in the long run.

Abortion laws and aid effectiveness

If aid effectiveness matters, we should observe different reactions depending on whether abortion is totally legal in the recipient country. Indeed, the MCP could be perceived as an anti-abortion policy. In that case, donors may decide to compensate for the decrease in the US allocation only in countries tolerating abortion-related activities. The consequences to other countries could be perceived as less worrying: there would be no impact on program funding and the type of projects provided, and donor competition and political independence in aisd llocation would matter more. To investigate this mechanism, I use the abortion law index produced by the Center for Reproductive Rights (2020) in 2020, which ranges from 1 (totally prohibited) to 5 (on request). I construct a dummy equal to 1 when abortion is available on request (5), the situation in 28% of recipient countries. Results are shown in figure 4. I do not observe statistically significant differences between the two groups' short-term reactions. However, differences in long-term reactions are statistically significant at 10% between the two groups of recipient countries. Donors only crowd in regarding the US allocation in countries where abortion is restricted, meaning that family planning aid involving abortion programs may be impacted by the MCP.

Finally, it may not be only the recipient country's abortion laws that matter, but the donor country's laws too. Countries restricting abortion may have less incentive to step in and compensate for the US allocation decrease as they partly share the same values regarding abortion. Conversely, countries where abortion is available on request may have more incentive to defy the US. Based again on the index produced by the Center for Reproductive Rights (2020) adjusted following some manual research on abortion legislation, I construct two groups of donors: 8 donor countries where abortion is unrestrictedly available on request (with certain termination time limits) and 17 donor countries where abortion law provides restrictions. 33 Donor countries permitting abortion on request never react significantly to the US allocation, suggesting that they do put more weight on family planning aid than on competition with the US. In contrast, the positive reaction observed in the long run is driven by donors with some legal constraints on abortion, suggesting that they consider competition with the US more important than aid effectiveness. However this result is less salient than the results on economic competition and geopolitical proximity, as an equal reaction from both groups cannot be rejected at 10% significance level.

To sum up, the differences between short-and long-run effects are mainly driven by readjustments in the reactions of donors with economic and political interests related to the US or the recipient country. While some concern is shown regarding the impact of reduced family planning aid on abortion laws both in recipient and donor countries, donors' reactions differ less than when economic considerations are involved. 33 For instance, Germany is classified by the Center for Reproductive Rights (2020)as a country where abortion in on request. However, abortion is actually illegal, but not punishable during the first 12 weeks of pregnancy under the condition of mandatory counseling. I thus classify Germany among countries with abortion restrictions. Abortion law is not under EU jurisdiction, but as some member states prohibit abortion, the EU is also classified in the group with restrictions. Given some statements by Melinda Gates, the BMGF is also classified in the group with restrictions (see for instance: https://wng.org/sift/melindagates-abortion-is-not-womens-healthcare-1617422262). The classification is explained in the online appendix.

Shifting the channels

The launch of specific trust funds and reports from the European Commission on commitments from European countries suggest that donors may change their behavior not necessarily regarding the amount allocated but regarding the channel through which aid is allocated. Donors can thus signal their disapproval of the MCP without increasing their budget and therefore without directly opposing the US. If there is such a signal effect, I expect the reaction to be negative for aid channeled through multilateral organizations and NGOs but positive for aid provided directly to the recipient government. To investigate this mechanism, I run a similar estimation but focusing first on strictly bilateral aid and second on aid channeled through multilateral agencies and NGOs. I find no differences in reactions according to whether aid is channeled bilaterally or through other channels (table 2).

INSERT TABLE 2 HERE

Reinstatement and Rescinding

The result may hide heterogeneous donor reactions depending on whether the US rescinds or reinstates the MCP. Indeed, donors might not react in the same way to the dominant player's withdrawal or entry in terms of competition. Reinstatement highlights the consequences of lack of family planning aid and thus aid effectiveness. There is almost no qualitative documentation on how other donors react to the rescinding of the MCP, which attracts less media coverage. Donors may want to publicize the fact that they are compensating for US withdrawal, but to conceal any such compensatory action when the US provides funding again.

Second, if, when the MCP is reinstated, donors decided to step in and developed partnerships with NGOs, they might be less likely to stop funding projects when the MCP is rescinded.

In that case, they would react to reinstatement but not to rescinding. Thus we should distinguish between reactions to turning the policy on/off. Finally, European donors were more vociferous in condemning the reinstatement by the Trump administration. It could be that donors only react to the US allocation when the decrease in aid is perceived as critical. Table 3 provides the estimates for each administration change. Columns 1-2 cover the reinstatement in 2000 (Clinton to G.W. Bush), columns 3-4 the rescinding in 2008 (G.W. Bush to Obama), and columns 5-6 the reinstatement in 2016 (Obama to Trump). Although results are no longer statistically significant at 10%, it seems that reactions to a reinstatement are weaker than reactions to a rescinding, suggesting that the "decency gap" effect is partly at play.

INSERT TABLE 3 HERE

Aggregate coordinated response

On average, in the short run donors do not compensate for a decreased US family planning aid allocation. However, the response may be coordinated at the aggregate level in the short run, before a return to business as usual. In that case, some donors would give more to some recipients and other donors would give more to other recipients. If a donor d only gives more to some recipients r with no change in what is given to other recipients, this would increase the variance in aid and thus hinder identification of short-term reactions. To test this mechanism, I collapse non-US donors as a single donor. I also collapse aid from one donor at the world level to look at how a donor d gives globally as a function of what the US gives globally. 34 Results from columns 1-4 show that the null result in the short run does not hide any aggregate coordinated response from other donors through any division of labor. Results from columns 5-8, even though the reactions are no longer significant, show in the short run a negative correlation between budget donors and the US budget at t or t -1, while the correlation between the budget of donor d at time t and the US budget at time t -2 or t -3 is positive35

INSERT TABLE 4 HERE

Placebo Tests

To assess the strength of the instrument, I look at changes in administration rather than MCP history. There may be reactions even after an election that does not affect the status of the MCP. As both Presidents G.W. Bush and Obama were re-elected, I can run two placebo tests. Redefining the MCP as equal to one during their second mandate, I run regressions covering the whole period of their presidency. Table 5 shows the results: as expected, the estimate is not significant. The IV strategy is not relevant (the K.-P. F-Stat is really low and the first-stage estimate is no longer significant) for the Obama terms but remains relevant for the Bush terms. 36 This may be partially explained by the fact that the PEPFAR fund to combat HIV and AIDS was launched in 2003 and extended in subsequent aid programs, providing a large aid flow for reproductive health starting 2004/2005. Results are therefore not driven by a change in the US administration alone. As an additional placebo test, I also look at the impact of future US disbursements on other donors' current disbursements. As expected, the effect is not significant. 37

INSERT TABLE 5 HERE

Robustness Analysis

I now check the robustness of the 2SLS estimates. Estimates are provided in table 6, with the baseline estimates in the first column. In each column, the two estimates correspond to two distinct regressions depending on the lag adopted for US FP aid.

INSERT TABLE 6 HERE

I first test the sensitivity of the results to the definition of the sample of recipients and donors. 38 The PEPFAR fund to combat HIV and AIDS was launched by the US in 2003 and targeted 15 countries. Those countries received extensive US aid to fight HIV and AIDS, part of these funds being reserved for contraception and thus linked to family planning. This could have affected the allocation of family planning aid differently. To rule out the possibility that results are driven by that specific sample of recipients, I estimate the equation excluding those countries and find that the results are robust. In the IHME database, non-zero values under $500 000 are indicated by dashes. Thus we do not know the actual amount allocated if the flow is lower. In the baseline regressions, where I used values rounded to thousands, those flows are rounded to zero. To investigate the sensitivity of the results, I replace those flows with a flow equal to $500 000. Columns (3) and (4) investigate the robustness when I only replace US FP aid and when both US and other donors' aid are replaced. I continue to find no reaction in the short term and long-term crowding-in. I next apply a broader definition of family planning aid in column ( 5), looking at the whole reproductive and maternal health sector (RMH). As expected, the K.-P. F.-Stat is lower than before. The estimate is larger but remains non-significant in the short run, while it is still positive and significant in the long run. This result suggests that the MCP may affect not only the allocation of family planning aid but also, due to an imperfect definition of family planning, the allocation of reproductive and maternal health in general. One reason may be that projects on family planning and maternal health are generally implemented together by the same implementing agencies. In column (6), I include region-year fixed effects in the baseline equation to flexibly control for all region-specific changes in family planning needs that may arise over time at regional level (economic crisis, spread of specific diseases such as Zika) and also account for any global or even region-specific changes in US foreign policy. The short-run reaction is now significant at a 10% level, suggesting that some readjustments may occur at regional level in the short run.

I next test the sensitivity of the results to the choice of a specific database. To do so, I use CRS-OECD data from 2005 to 2019. These data cover sectoral allocation of aid by the same donors, except the BMGF, which is not recorded. The instrument is defined in a similar way but the definition of non-US NGOs is noisier, as the origin of the NGOs is unknown. I compute the share of aid channeled by NGOs, affecting the accuracy of the instrument.

For disbursements, I first focus on family planning alone (purpose code 13020 and 13030) in column (FP) and next on reproductive health and population policy (sector code 130) in the next column, while for commitments I only look at family planning. The K.-P. F.-Stat is very small and weak instruments cannot be excluded. The results are not significantly different from 0 at the 10% level.39

Conclusion

The family planning sector provides useful insights into donor interactions, especially how donors react to the dominant player, here the US. US foreign policy on family planning has led to large variations in both US funding and rhetoric, and has been scrutinized by other donors. Some of these donors have officially stated that they will compensate for decreased US aid.

Exploiting variations arising from the Mexico City Policy to causally infer how other donors react to the US allocation, I find no reaction in the short term but crowding-in by donors in the long term. The absence of reaction in the short run, robust to different specifications, can be explained by the moral impact from a US policy perceived as an anti-abortion policy and condemned by numerous donors in Europe. While this effect is enough to trigger a negative reaction in the short run from small donors, who are more likely to care about aid effectiveness, it is not enough for large donors. In the long run, the compensation effect is not large enough to avoid herding behavior, more pronounced where there is geopolitical proximity with the US or economic competition. Non-restrictive abortion laws in either the donor or the recipient country attenuate the herding behavior. In the end, this means that women in the country prohibiting or restricting abortion are even more negatively impacted by the reinstatement of the MCP. Access to contraception is likely to be reduced because of lack of funds, and they do not have access to safe abortion. Other donors' short-and long-term reactions to the US allocation also underline the potential negative consequences of globally relying heavily on one donor. If this donor drastically changes policy, the consequences may include volatility and large losses of funds for recipient countries not covered by other donors, or even worse. In 2017, the Trump Administration extended the MCP to the fight against HIV/AIDS, where the US plays an even more dominant role than in family planning aid. Other donors have not publicly reacted as strongly as with family planning aid, suggesting that the likelihood of compensation is even lower for HIV/AIDS (not tested here). If donors are not able to compensate for this withdrawal, it could have negative implications for the spread of HIV/AIDS. For policymakers in recipient countries, the take-away message is that dependency on one dominant donor per sector needs to be reduced. (

Figures and Tables

) (2) (3) (4) (5) (6) (7) (8) k = 0 k = 1 k = 2 k = 3 k = 0 k = 1 k = 2 k = 3 1

  10 Its effect was most obvious just after the election of G.W. Bush in 2000: between 2001 and 2004, there was a sharp decrease in family planning aid. Starting in 2005, family planning aid increased again, mainly due to the creation of the President's Emergency Plan for AIDS Relief (PEPFAR) in 2003. This fund focuses on combatting HIV/AID, but devotes some action to family planning. Arguably, Republican donors will be more reluctant to finance development abroad because they are more sceptical about aid. Using data from the Development Assistance Committee of the Organization for Economic Cooperation and Development (DAC-OECD), I can exclude at a one percent level the hypothesis that annual average official development aid differs under a Republican president, and similarly under a majority Republican Congress, over the period 1984-2021. Based on Creditor Reporting System data from the OECD (CRS-OECD), figure

  Policy described above. The changes induced by the policy are driven by domestic debates on abortion and are not related to any changes in recipient countries' needs or in other donors' foreign policy. I use this exogenous time variation -from the point of view of other donors and recipients -in the US allocation as an instrument for the family planning aid allocated by the US. To do so, I create a dummy, M CP t , equal to one when the MCP is active at time t. It covers all the years when a Republican was president plus 1995 and 2000, when the Congress was Republican and succeeded in reinstating the MCP in a reduced version. To identify a causal effect, I need to introduce cross-country variation. I use the fact that the policy does not affect all recipient countries uniformly. 20 Not all recipients suffer the same funding loss, because of two factors. First, like all donors, the US tends to allocate larger aid grants to frequent FP aid recipients. I compute F P r as the percentage of years of inactive MCP during which a country receives US FP aid.21

  country's receiving US family planning aid through non-US NGOs only affects allocation from other donors through the US family planning aid allocatiThe identifying assumption is that aid allocation from other donors in countries with differing probabilities of receiving US family planning aid via non-US NGOs will not be affected differently by changes induced by the change in US foreign policy, other than via the impact of US aid allocation, controlling for recipient-donor-and donor-region-year -fixed effects. Causal inference using the interacted instrumental variable relies on the assumption that conditional on the controls, the interaction between (lagged) US policy activation and a country's receiving US family planning aid through non-US NGOs only affects allocation from other donors through the US family planning aid allocation. on. For different trends to affect the results, these trends across countries with differing probability of receiving US family planning aid through non-US NGOs would have be correlated with US changes of administration for all other donors, which is unlikely. 24 Nevertheless, I also interact all control variables with the vulnerability indicator (F P r * shareN GO r ) to capture any such effects in the first and second stages.Another concern with this assumption is that MCP reinstatement or rescinding may affect allocation from other donors through its influence on overall US foreign policy, since it also means a new President was elected. As a robustness check, I include region-year fixed effects in the baseline equation to flexibly control for all region-specific changes over time, thereby taking into account any global or even region-specific changes in US foreign policy. In that case, to violate the exclusion restriction, these changes would need to have systematically different within-region effects on family planning aid allocation from other donors in a way correlated with a country's receiving US family planning aid.Finally, a Democrat administration (or other donors) could arguably anticipate MCP reinstatement and artificially increase their funds for family planning projects a year before the US election. Between 1990 and 2019, two Republican presidents were elected. Both times the expected result was the election of the Democrat incumbent, which reduces the likelihood of strategic behavior a year before the election.

  the main results on the potential reaction of other donors to the US allocation for the 1990-2019 period. Columns 1-4 only include recipient's characteristics as controls in order not to exclude the EU and the BMGF reactions. Columns 5-8 include bilateral determinants. As a consequence, the EU and the BMGF are excluded from the regressions. Columns 1-2 and 5-6 report short-term reactions, indicating the other donors' reactions to the contemporaneous US allocation (column 1) and to the US allocation one year earlier (column 2). Columns 3-4 and 7-8 provide long-term reactions, showing the other donors' reactions to the US allocation respectively two or three years earlier.INSERT TABLE 1 HEREPanel A shows OLS results. The US allocation to recipient r, whatever the lag (0 to 3), is positively correlated to the allocation of donor d to the same recipient at time t. The coefficient is stable whatever the timing of the reaction we are interested in. These results are more likely to be biased due to endogeneity. I employ the IV strategy detailed previously to account for reverse causality and other potential sources of endogeneity.25 Panel B presents reduced-form estimates, replacing the US allocation with lag k by the instrument with the same lag.25 Panel C shows the second stage of the regressions estimated with 2SLS, while I provide the corresponding first-stage results in panel D.The first-stage estimates show the expected negative sign. All estimates are significant.When the MCP is active, countries that are regular recipients of US FP aid usually channeled through non-US NGOs receive disproportionately less US FP aid than other countries. The K.-P. stat ensures that the instrument is strong enough. F P r * shareON G r vvaries between 0 and 0.86, with an average of 0.36. For the average recipient country, an active MCP reduces by between 71 and 100% the amount of family planning aid allocated by the US.26

  0

Figure 1 :Figure 2 :

 12 Figure 1: Aid disbursement for family planning from the US and other donors (1990-2020) Note: Gray periods are years when Mexico City Policy is active.

Figure 3 :

 3 Figure 3: Bilateral reactions to US family planning aid allocation Note: This figure reports the 2SLS estimates of interest obtained for k of 1 or 2 (baseline) and for each donor (2SLS regression with interaction terms as in equation 3) with the same lags. The figure includes 90% confidence intervals. The dependent variable is the allocation of donor d to recipient r at time t. Estimates directly represent the reaction of donor d to the US FP aid allocation one and two years later. Regressions include a donor-year and donor-recipient fixed effect and are controls for recipient characteristics and controls interacted with vulnerability to the MCP. K.-P. F-Stat for the regression with one-and two-year lags are respectively 3.538 and 3.291.

  The indicators of US proximity and abortion in the donor country vary at the donor level, the abortion in recipient country indicator only varies across recipients, while the economic competition indicator varies at the donor-recipient pair level. Controls and FE as in table 1. The K.-P. F-Stat for regression with oneand two-year lags are respectively 44.07 and 38.58 (economic competition), 44.22 and 41.14 (US proximity), 34.46 and 33.81 (abortion in recipient country), 44.23 and 41.14 (abortion in donor country).

	Baseline
	Economic competition
	Low
	High
	US Proximity
	Low
	High
	Abortion in recipient country
	Restricted
	Not restricted
	Abortion in donor country
	Some restrictions
	On request
	-.1	0	.1	.2	.3
		t-1	t-2
	Figure 4: Heterogeneity analysis

Note: This figure reports the estimates of interest obtained for k of 1 or 2 (baseline) and for different heterogeneity analyses (regression with interaction terms) with the same lags. The figure includes 90% confidence intervals. The dependent variable is the allocation of donor d to recipient r at time t.

Table 2 :

 2 Panel A: OLS Estimates -Independent Variable: USFPaid rt-k Reduced Form Estimates -Ind. Var.: FP r * shareNGO r * MCP t-k First-Stage Estimates -Ind. Var.: FP r * shareNGO r * MCP t-k Dependent variables in lines, independent variables in columns. The lag used for US FP aid and the instrument is given at the top. Coefficients are reported with standard errors clustered at recipient and donor level. A hyperbolic sine transformation is applied to aid variables. Columns (5) to (8) exclude the EU and the BMGF for the regression, as bilateral controls are not defined for them. Controls rt-1 include: GDP pc. in log, population size in log, poverty rate, life expectancy at birth, incidence and prevalence of HIV, fertility rate and it square, adolescent fertility rate, maternal mortality rate, Polity2 index and the same controls interacted with F P r * shareN GO r . Controls drt-1 include UN proximity and its interaction with F P r * shareN GO r . * * * p < 0.01, * * p < 0.05, * p < 0.1 Reactions through aid channeled bilaterally or not bilaterally One observation is a donor-recipient pair and a year. Coefficients are reported with standard errors clustered at recipient and donor level. Aid data come from IHME database. A hyperbolic sine transformation is applied to aid variables. Controls and FE as in table 1. * * * p < 0.01, * * p < 0.05, * p < 0.1

	FPAid drt	0.011 *	0.009 *	0.011 * *	0.012 * *	0.012 *	0.009 *	0.011 *	0.012 *
		(0.006)	(0.005)	(0.005)	(0.005)	(0.006)	(0.005)	(0.006)	(0.006)
	Panel B: FPAid drt -0.015 -0.072	-0.219 * * -0.249 * * -0.034	-0.066	-0.204 *	-0.208 *
		(0.088)	(0.083)	(0.105)	(0.110)	(0.092)	(0.092)	(0.114)	(0.114)
			Panel C: 2SLS Estimates -Independent Variable: USFPaid rt-k
	FPAid drt	0.006	0.030	0.086 *	0.101 * *	0.014	0.026	0.080 *	0.084 *
		(0.036)	(0.035)	(0.042)	(0.045)	(0.038)	(0.037)	(0.045)	(0.046)
	Panel D: USFPAid drt-k -2.421 475 * * *
		(0.238)	(0.257)	(0.281)	(0.279)	(0.236)	(0.267)	(0.290)	(0.286)
	Obs.	74200	74200	71550	68900	64358	64358	62489	60399
	Donor-Rec. pairs 3350	3350	3325	3300	3069	3069	3048	3026
	Recipient	106	106	106	106	106	106	106	106
	K-P. F-Stat	103.5	88.45	82.28	78.73	106.0	88.14	77.14	74.72
	Cragg-Donald F 1976.8	1821.6	1855.9	1707.4	1733.1	1692.7	1591.0	1479.4
	Donor-Rec. FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
	Donor-Year FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
	Controls rt-1	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
	Controls drt-1	No	No	No	No	Yes	Yes	Yes	Yes
	Table 1: Donors' reaction to US FP aid allocation (1990-2019) -Baseline results

* * * -2.416 * * * -2.546 * * * -2.474 * * * -2.427 * * * -2.511 * * * -2.551 * * * -2.Notes: Notes: One observation is a donor-recipient pair and a year. Coefficients are reported with standard errors clustered at recipient and donor level. Aid data come from IHME database. A hyperbolic sine transformation is applied to aid variables. Controls and FE as in table 1. * * * p < 0.01, * * p < 0.05, * p < 0.1 Notes:

Table 3 :

 3 Reactions to a change of administration: IV estimates F P A rt is total family planning aid received by recipient r at time t from non-US donors. F P A dt is total family planning aid allocated by donor d at time t. U SF P A (r)t is US FP aid allocated to recipient r at time t in columns 1-4 and global US FA aid allocated at time t in columns 5-8. In columns 1-4, an observation is a recipient and a year. In columns 5-8, an observation is a recipient and a year. Coefficients are reported with standard errors clustered at recipient level in columns 1-4 and robust in columns 5-8 (because of too few clusters). Aid data come from IHME database. A hyperbolic sine transformation is applied to aid variables. In columns 5-8, controls t-1 are the average value of the control variable over recipients at time t. * * * p < 0.01, * * p < 0.05, * p < 0.1

		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
			As one donor			As one recipient
			Dep. Var.: FPA rt			Dep. Var.: FPA dt
	USFPAid (r)t	0.156				-1.130
		(0.130)				(0.898)
	USFPAid (r)t-1		0.130				-0.576
			(0.155)				(0.610)
	USFPAid (r)t-2			0.468 * * *				1.489
				(0.164)				(1.002)
	USFPAid (r)t-3				0.443 * * *				1.054
					(0.148)				(0.831)
	Obs.	2968	2968	2862	2756	700	700	675	650
	K-P. F-Stat	100.9	86.20	80.16	76.69	62.12	121.3	24.78	35.04
	Recipient or Donor FE Yes Yes No Yes Yes Yes Yes Yes Yes No No No Yes Yes Yes Yes

Notes:

Table 4 :

 4 Aggregate coordinated response and global response to US family planning aid Bush Administration Obama Administration Future US aid 2SLS Estimates -Dep. Var.: FPA drt Stage Estimates -Dep. Var.: FPA drt-kFP r * shareNGO r * Placebo t-2 -7.204 * * * P lacebo t is a dummy equal to one when t is equal to or greater than 2005 for column 1-2 (Bush Administration) and equal to or greater than 2013 for column 3-4 (Obama Administration). The period of analysis is 2001-2008 for columns 1-2 and 2009-2016 for columns 3-4. For the dependent variable of the firststage equation, k corresponds to the same lag as the instrument. In the last column, k = -1. One observation is a donor-recipient pair and a year. Coefficients are reported with standard errors clustered at recipient and donor level. Aid data come from IHME database. A hyperbolic sine transformation is applied to aid variables. Controls as in table 1. * * * p < 0.01, * * p < 0.05, * p < 0.1 : An estimate corresponds to a regression. In the first six columns, data used are from the IHME database. In the last three columns, CRS-OECD data are used (coverage period is only 2005-2019). Column (Baseline) provides the baseline estimates, like Panel C in columns (2) and (3) of table 1. PEPFAR excludes countries targeted by the PEPFAR fund launched in 2003. One observation is a donor-recipient pair and a year. The third column provides estimates when all US flows below 500 000$ are replaced by 500 000$ (RU SF P Aid rt-1 and RU SF P Aid rt-2 ). The fourth column (Round) provides estimates when all flows below 500 000$ are replaced by 500 000$. In column RMH/IHME data, FP aid is replaced by all maternal and reproductive health aid. In column RYFE, I include region-year fixed effects in addition to donor-year and donor-recipient FE. Column FP/CRS-OECD data concern disbursed aid from sector 13020 and 13030 of CRS-OECD data while column RMH/CRS-OECD data concern sector 130 "Population Policies". In the last column, disbursements are replaced by commitments for FP aid. Coefficients are reported with standard errors clustered at recipient and donor level. A hyperbolic sine transformation is applied to aid variables. Controls as in table 1. * * * p < 0.01, * * p < 0.05, * p < 0.1 First-stage -Dep. Var : US Family planning aid US FP aid rt US FP aid rt-1 US FP aid rt-2 US FP aid rt-3 MCP t * FP r * shareONG r Notes: One observation is a donor-recipient pair and a year. Coefficients are reported with standard errors clustered at recipient and donor level. Aid data come from IHME database. A hyperbolic sine transformation is applied to aid variables. The table only shows the first-stage estimate of column (4) of table B.1. Number of observations and statistics are provided in table B.1. B.1.Table B.2: Donors' reaction to US FP aid allocation (1990-2019) -First-stage estimates of dynamic reaction

	USFPaid rt-1	-0.00997		-0.306
		(0.0181)		(0.418)
	USFPaid rt-2		0.00255		-0.0183
			(0.0117)		(0.334)
	USFPaid rt+1					0.00724
						(0.0302)
			First--0.536
		(1.011)		(0.421)
	FP r * shareNGO r * Placebo t-1		-6.730 * * *		-0.437
			(0.910)		(0.501)
	FP r * shareNGO r * MCP t+1					-2.574 * * *
						(0.252)
	Obs.	18550	15900	18550	15900	71550
	Donor-recipient pair	2825	2800	2825	2800	3325
	Recipient	106	106	106	106	106
	K-P. F-Stat	54.66	50.77	0.760	1.621	104.7
	Donor-Recipient FE	Yes	Yes	Yes	Yes	Yes
	Donor-Year FE	Yes	Yes	Yes	Yes	Yes
	Controls rt-1	Yes	Yes	Yes	Yes	Yes
		Table 5: Placebo tests

Notes:

Notes* * * p < 0.01, * * p < 0.05, * p < 0.1

It is worth noting that the UNFPA defines family planning as the information, means, and methods that allow individuals to make informed decisions about when to have children. This includes a wide range of contraceptive options, including pills, implants, intrauterine devices (IUD), surgical procedures, barrier methods, and non-invasive methods such as the calendar method and abstinence. It also includes abortion as well as information on how to become pregnant voluntarily.

[START_REF] Miller | Family planning program effects: Evidence from microdata[END_REF] for a literature review on the effects of family planning on fertility.

Source: http://progress.familyplanning2020.org/finance

Both theoretical and empirical studies have shown that a lack of coordination, which leads to aid fragmentation, can hinder aid effectiveness and have negative political consequences[START_REF] Knack | Donor fragmentation and bureaucratic quality in aid recipients[END_REF][START_REF] Bigsten | International coordination and the effectiveness of aid[END_REF].

 5 The literature on individual charitable giving also sheds light on why donors may react differently to different donors.[START_REF] Andreoni | Leadership giving in charitable fund-raising[END_REF] highlights the importance of leadership gifts -large donations made by one single person -as they provide a legitimation effect. The leader is sending a signal about the recipient, which later givers will follow. This aspect could be relevant to a dynamic reaction.

It has been shown that for development aid, aid volatility tends to be growth-reducing in recipient countries[START_REF] Arellano | The dynamic implications of foreign aid and its variability[END_REF] or can lead to internal conflict[START_REF] Nielsen | Foreign aid shocks as a cause of violent armed conflict[END_REF].

More than other components of population programs, family planning service projects draw upon the private sector(United States Congress House, 1986).

For additional details on database construction and allocation to each sector, the IHME provides an annual review and an on-line appendix (http://www.healthdata.org/policy-report/financing-global-health-2019-tracking-health-spending-time-crisis).

 15 The list of donors and recipients is provided in the on-line appendix. Data starts in 1990 but is not fully recorded in 1990 for some donors, especially regarding channel or recipient countries. Data for 2019 and 2020 are not disaggregated at recipient level but only given globally.

Sample size is reduced by 49% when economic, health, and political controls are included.

This variable is not defined for the EU and for the Bill and Melinda Gates Foundation. For the EU, a weighted average of member states' alignment would have been possible. However, there is no clear way to define the weight of each member state, especially since

with the appointment of the first High Representative of the Union for Foreign Affairs and Security Policy. Hence I adopt a conservative position and do not define voting alignment between the EU and a recipient at the UN General Assembly. When this variable is included, the sample size is reduced by 58% relative to the case with no controls.

This type of instrument is type of instrument is commonly used in the aid literature[START_REF] Werker | How is Foreign Aid Spent? Evidence from a Natural Experiment[END_REF][START_REF] Nunn | US Food Aid and Civil Conflict[END_REF][START_REF] Dreher | The effects of foreign aid on refugee flows[END_REF][START_REF] Dreher | Aid, china, and growth: Evidence from a new global development finance dataset[END_REF].

Figure B.1 in appendix B represents the annual total amount of aid allocated to highly-exposed countries and little-exposed countries.

In this analysis, there is no pre-period in which to test the parallel trend, as the MCP was first implemented in 1984. The setting is a specific one, with the policy switched on/off several times over the period of analysis.

For instance, in column (3) USFPAid rt-3 is instrumented by M CP t-3 * F P r * shareN GO r .

Computation based on column (1) of Panel D in table 1.

There are a lot of zeros in the data, so the relevant reaction might be at the extensive margins. However, donors were concerned about money, not about recipients not receiving US aid. Results at the extensive margins show no significant reactions (online appendix, table D.1.

In appendix B, tableB.1 shows the results from a single regression covering all lagged US allocation. Results remain similar, with no significant reaction in the short run and a significant and positive reaction in the long run. The total effect over the period is positive and significant.

Another approach would have been to run separate regressions for each donor, but in that case the change in reactions might partly have been explained by variations in the estimates for the other controls. Results are similar and provided in online appendix.

For readability, I only plot the coefficient for the regressions with a one-and two-year lag. The pattern is similar when I include contemporaneous and three-year lag regressions. Results are provided in online appendix.

A noteworthy exception is France, which behaves like a large donor even though classified as a small family planning donor. In total development aid terms, France is a relatively large donor.

In this regression, in order to instrument the US allocation, I need to exclude year fixed effects. The instrument only varies according to whether the MCP is active or inactive. Thus, there is a greater risk of confounding factors and the causal interpretation of the reaction is less relevant.

More precisely, a unilateral test leads to the conclusion, at a 10% level, that the donor's reaction to the aid allocated by the US at time t is negative and positive for aid allocated at time t -2 and t -3. For t -1, the null hypothesis cannot be rejected.

A better placebo test would have been to look at a false rescinding of the MCP in 1989, when there was a change in President (Reagan to Bush), as the President remained a Republican and the MCP remained active. Unfortunately, data are not available before 1990.

Under the assumption that the MCP does not affect other US aid budgets through a balancing effect and the less realistic assumption that Republicans and Democrats use a similar sectoral allocation structure (except for family planning) in relative terms, allocations by other donors to sectors not related to reproductive health could serve as placebo tests. They should not be affected by the US allocation of family planning aid if there is no substitution across sectors from other donors, except to keep the development assistance budget constant. As a consequence, under those specific assumptions, there should be no reactions in other sectors in the short run and some reactions in the long run. Results not shown here suggest that those assumptions are not realistic and that reallocation across sectors may occur.

I replicate the regressions with US family planning aid lagged by one and two years, each time excluding one donor and one recipient. Thus, I run 2650 additional regressions. The estimates are not really sensitive to the exclusion of some donors or recipients; they maintain the same order of magnitude. For the specification with US FP aid lagged by two years, only 0.3% of the regressions provide an estimate not significant at the 10% level. 25% of the estimates of interest have a level of significance of between 5 and 10%. For the specification with US FP aid lagged by one year, the estimate is never significant at the 10% level.

The online appendix also provides robustness checks followingChristian and Barrett (2022). Firstdifference estimation shows that donors do not react significantly in the short run; in the long run, the two-year lag effect is no longer significant at the 10% level but the three-year lag effect is positive and significant at 5%.

Camille Noûs embodies the collegial nature of our work, as a reminder that science proceeds from disputatio and that the building The project leading to this publication received funding from the French government under the "France 2030" investment plan managed by the French National Research Agency (reference:ANR-17-EURE-0020) and from Excellence Initiative of Aix-Marseille University -A*MIDEX. I would like to thank

Data Availability

The data underlying this article are in Harvard Dataverse. https://doi.org/10.7910/DVN/4PWQ9X.

A Appendix A: US family planning aid and US aid