Doing Well by Doing Good: The Impact of Foreign Aid on Foreign Public Opinion

Electronic copy available at: http://ssrn.com/abstract=2361691

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Doing Well by Doing Good:

The Impact of Foreign Aid on Foreign Public Opinion*

Benjamin E. Goldsmith† Yusaku Horiuchi‡ Terence Wood§

First Draft: February 20, 2012

Last Update: January 31, 2014

Word Count (Text): 10,303

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!* Earlier drafts were presented at the Annual Conference on the 2011 Workshop on the

Frontiers of Statistical Analysis and Formal Theory of Political Science (Tokyo, Japan,

January 6-7, 2011), a workshop on empirical political analysis at the Australia National

University (Canberra, Australia, May 10, 2012), the Second Annual General Conference

of the European Political Science Association (Berlin, Germany, June 21-23, 2012), the

Fifth Oceanic Conference on International Studies (Sydney, Australia, July 18-20, 2012),

and in a seminar at Dartmouth College (Hanover, USA, October 12, 2012). We thank

Geoff Brennan, Steve Brooks, Alison Cumming Thom, Linda Fowler, Michael Herron,

Kosuke Imai, Mike Miller, Jo Spratt, Carrie Steel, Matt Winters, Ippei Yamamoto, and

other participants of the above workshops, conferences, and seminars for useful

comments. We also thank Gallup Inc. for providing us their data. † Associate Professor, Department of Government and International Relations, the

University of Sydney. Email: [email protected]. ‡ Associate Professor and the Mitsui Chair in the Study of Japan, Department of

Government, Dartmouth College. Email: [email protected]. § Ph.D. Candidate, School of International, Political and Strategic Studies, the Australian

National University. Email: [email protected].

Electronic copy available at: http://ssrn.com/abstract=2361691

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Abstract

Does foreign aid extended by one country improve that country’s image

among populations of recipient countries? Using a multinational survey,

we show that a United States aid program targeted to address HIV and

AIDS substantially improves perceptions of the U.S. Our identification

strategy for causal inference is to use instrumental variables measuring the

magnitude of the HIV/AIDS problem in aid recipient countries. Our

finding implies that in addition to its potential humanitarian benefits,

foreign aid that is targeted, sustained, effective, and visible can serve an

important strategic goal for those countries that give it: fostering positive

perceptions among foreign publics. By doing good, a country can do well.

Keywords: foreign aid, U.S. foreign policy, HIV, AIDS, PEPFAR, public

opinion, instrumental variables

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Competition between major powers such as the United States (U.S.) and China for

favorable perceptions in global public opinion is increasingly evident today and likely to

be a pivotal feature of the emerging international order (Friedberg 2010; Gill and Huang

2006; Kurlantzick 2007; Nye 2004; Shambaugh 2008). These countries are eager to

develop positive images of themselves among foreign publics, because such images are

considered important for achieving a range of objectives in foreign relations (Bustamante

and Sweig 2008; Goldsmith and Horiuchi 2012; Nye 2004). Among potential tools states

may use to win hearts and minds abroad, foreign aid is often claimed to be effective

(American Political Science Association 2009).1

In the context of this intensifying competition for positive images among global

publics, in 2003, under the Bush Administration, the U.S. established a foreign aid

program called the President’s Emergency Plan for AIDS Relief (PEPFAR), which has

been provided to more than 80 developing countries. Its declared objectives include

stopping the spread of HIV and AIDS, supporting the treatment of people suffering from

HIV and AIDS, and mitigating the indirect consequences of the epidemic.2

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!1 States may use other tools, such as public diplomacy, for the same reason (Goldsmith

and Horiuchi 2009). In this paper, we use the term “foreign aid” (or simply “aid”) as a

synonym for Official Development Assistance as defined and measured by the

Organisation for Economic Co-operation and Development’s Development Co-operation

Directorate. Importantly, this definition does not include military aid.

2 Funding for PEPFAR was re-authorized in 2008 and it has continued to receive support

under the Obama administration, although in a modified form integrated into a broader

plan for improving global health outcomes, and with funding levels no longer increasing.

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As then Secretary of State Condoleezza Rice emphasized in her speech at the

release of the Fifth Annual Report to Congress on PEPFAR on January 12, 2008, the U.S.

government believes that PEPFAR has contributed not only to addressing global health

problems but also to improving the U.S. image among publics in recipient countries. Yet,

while claims such as this are common, they appear to be based on speculation or

anecdotal evidence. Empirically, work on the impact of aid – and more specifically,

PEPFAR – on public opinion is scarce. There is little available systematic evidence

suggesting that foreign aid improves donor image amongst populations of countries

receiving the aid.

In this article, we provide compelling evidence that PEPFAR has, indeed,

positively affected how publics in recipient countries regard the U.S. We emphasize two

key implications of this finding.

First, it suggests what types of aid, under what conditions, might be effective in

influencing foreign public opinion about the donor. Specifically, our theory is that foreign

aid that is targeted, sustained, effective, and visible is more likely to affect mass opinion.

Recent studies suggest that aid can be effective at encouraging economic growth in

recipient countries, although such positive findings remain contested (for example,

Doucouliagos and Paldam 2013). Specifically, they suggest that aid promotes economic

growth, under certain conditions, at the national (Arndt et al. 2010; Dalgaard and Tarp

2004; Wright 2010) or global (Headey 2008) levels; and that the effects of aid are

observable over multi-year time periods (Headey 2008; Minoiu and Reddy 2010). While

much of the existing empirical debate focuses on the economic impacts of foreign aid,

our refined theory of aid effectiveness sheds light on the comparatively under-

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investigated area of aid’s impact on public opinion in recipient countries. This has

practical ramifications for international relations, because, as Goldsmith and Horiuchi

(2012) show, changes in public opinion within Country B about Country A can influence

Country B’s foreign policy behavior toward Country A.

Second, if foreign aid programs have such political ramifications, we suggest a

possible virtuous circle or race-to-the-top dynamic for the emerging global order. As

great powers, especially the U.S. and China, are increasingly constrained by the costs that

militarized conflicts would impose on their trade and investment interests, they may

increasingly seek to pursue their international interests through currying favor among

foreign elites and publics. Foreign aid is an obvious potential tool for this. If targeted,

sustained, effective, and visible aid gives the best chance of influence, this may compel

great powers to actually do good, and to be seen to be doing so, in order to do well in

their global competition for influence.

Despite the importance of understanding this sort of impact of foreign aid on

public opinion in recipient countries, there have not been many empirical investigations

on this topic. This is likely in part due to a methodological challenge researchers

inevitably encounter when answering the question of whether an aid program like

PEPFAR actually affects opinion about a donor in recipient countries. This difficulty

arises because donors never allocate foreign aid across countries at random. Therefore,

causal estimates based on naïve regression analysis are likely to be biased due to the

possibility that a donor may determine the amounts to be allocated to individual countries

based partly on existing public opinion about the donor in these recipient countries or, as

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much of the existing literature suggests, based on other political or strategic

considerations, which are typically unobservable or difficult to measure.

In this paper, we tackle this methodological problem and present systematic new

evidence. Specifically, our identification strategy for causal inference is to use

instrumental variables measuring the magnitude of the HIV/AIDS problem in aid

recipient countries. These instruments are strongly correlated with the amount of

PEPFAR funding allocated across countries, but are likely to be uncorrelated with

unobserved heterogeneity (conditional on a set of observable pre-treatment covariates).

By using a large multinational survey with a battery of questions, we also undertake

multiple placebo tests and examine whether the treatment variable has a significant effect

only on public opinion about the U.S. but not on public opinion about other countries.

The results of our analysis show that PEPFAR substantially improves perceptions

of the U.S. in recipient countries, and they are robust to model specifications. Our finding

implies that in addition to its potential humanitarian benefits, under certain conditions,

foreign aid can serve an important strategic goal for those countries that give it: fostering

positive perceptions among foreign publics. By doing good, a country can do well.

Does Foreign Aid Affect Foreign Public Opinion?

There exist a range of reasons why countries give foreign aid. It may be given

altruistically to improve economic and social well-being in developing countries, as

advocated by Sachs (2005) and practiced to a significant extent by some Northern

European countries (Berthélemy 2006; Gates and Hoeffler 2004; Hoeffler and Outram

2011). Alternatively, foreign aid may be used as a tool of direct leverage over political

elites to advance commercial or foreign policy goals important to the donor (Alesina and

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Dollar 2000; Browne 2006, Chap. 6; Dreher et al. 2008; Dreher et al. 2011; Kuziemko

and Werker 2006; Radelet 2006; Vreeland 2011; Wang 1999). Finally, foreign aid may

be provided at least in part in the hope of creating favorable public perceptions of the

donor in recipient countries.

The purpose of this paper is to examine the effectiveness of the latter objective of

foreign aid, for the case of PEPFAR. In doing this, we complement the existing

literatures on aid effectiveness, which examine whether aid delivers development benefits

to recipient countries (for example, Arndt and Tarp 2010; Burnside and Dollar 2000;

Dalgaard and Tarp 2004; Doucouliagos and Paldam 2013; Dreher et al. 2008b; Feeny and

de Silva 2012; Headey 2008; Miniou and Reddy 2010; Mekasha and Tarp 2013; Mishra

and Newhouse 2009; Rajan and Subramanian 2008) and whether aid delivers direct geo-

strategic benefits to donors (for example, Dreher and Strum 2012; Milner and Tingley

2013; Nowak-Lehmann et al. 2009; Vreeland 2011).

Theoretically, it is plausible that by instilling gratitude in those it helps or through

promoting an image of positive action, compassion and generosity, foreign aid may

create or strengthen positive perceptions of donor nations in recipient countries. But there

are also reasons to suspect that foreign aid could be an ineffective tool of influence

(Adelman 2011; Lindsay 2011). Recipients may be unaware of the origins of the aid they

receive; the donor’s motivations might be seen as primarily self-serving; the positive

feelings associated with aid may be too small to shift perceptions shaped by more salient

and dramatic foreign policy behavior; or aid programs may simply fail to work and,

therefore, fail to sway people’s opinions in the absence of obvious improvements to their

quality of life.

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To date there are only a limited number of empirical studies examining these

theoretical possibilities. Furthermore, they are often based on single cases and

consequently tend to suffer from a lack of generalizability, or do not fully control for

confounding factors that might render their conclusions invalid. In the following, we

summarize the literature before providing further details on PEPFAR and discussing its

potential as a means of fostering improved opinion.

The Existing Literature

Most of the existing studies that examine aid’s impact on opinion have been within-

country case studies. They include studies focusing on U.S. hearts and minds campaigns

in conflict zones, such as Iraq and Afghanistan, as well as studies focusing on disaster

relief aid after the 2004 Indian Ocean tsunami, the 2005 Pakistan earthquake, or the 2011

earthquake and tsunami in Japan (these are discussed in more detail in the following

paragraphs). One statistical paper by Goldsmith, Horiuchi, and Inoguchi (2005) takes a

comparative, cross-national perspective, using data from a variety of countries. It is,

however, not focused on estimating the effects of a specific foreign aid program. Rather,

foreign aid variables are included among a range of independent variables expected to

affect post-9/11 international opinion about U.S. foreign policy. Overall, these previous

studies on the impacts of foreign aid on public opinion about donors in recipient countries

provide mixed results.

A series of qualitative studies has been undertaken through the Feinstein Center at

Tufts University, looking at perceptions of aid donors in Kenya and Afghanistan

(Bradbury and Kleinman 2010; Fishstein 2010; Gompelman 2011; Gordon 2011). While

there is some variation across field sites, these studies generally find that aid is

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ineffective in positively influencing recipients’ perceptions of donors. Importantly,

although the Feinstein Center work is thorough and detailed, the external validity of their

findings is questionable because their qualitatively oriented studies are based on samples

that tend to be small. Furthermore, there is little basis for expecting that similar results to

be found in cases beyond the immediate context of Afghanistan and conflict

environments.

The generally pessimistic findings of the Feinstein Center studies are consistent

with the finding of a large-N quantitative study, also undertaken in Afghanistan,

associated with an evaluation of German aid (Böhnke, Koehler and Zürcher, 2010). This

study found a weak but statistically significant association between foreign aid and public

opinion about the foreign peace-building work. However, this positive relationship

disappeared when the survey, originally conducted in 2007, was repeated in 2009.

In a study of aid’s impact on attitudes in the wake of the 2005 Pakistan

earthquake, Andrabi and Das (2010) suggest that exposure to foreign assistance had a

long-lasting and statistically significant impact on affected villagers’ trust of foreigners.

At the same time, however, the authors found that positive perceptions tapered off as

distance from the fault line increased, suggesting that the impact was localized among

those who benefitted directly from the aid or who came from communities that benefitted.

Outside of academia, changes in surveyed public opinion over time have also

been claimed as evidence of aid’s ability to improve public opinion. Commonly cited

cases are high-profile U.S. disaster relief aid after the 2004 Indian Ocean tsunami, the

2005 earthquake in Pakistan, and the 2011 earthquake and tsunami in Japan. In all

instances, various polls (McCawley 2006; Terror Free Tomorrow 2005; Terror Free

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Tomorrow 2006; Wike 2012) show that opinions of the U.S. improved in assisted

countries. While such eye-ball studies of before and after comparisons lack the rigor of

careful statistical analysis and thus their findings might potentially be spurious, the

magnitude and timing of the change in opinion are suggestive. In the case of the Pakistan

earthquake, though, changes may have only been transient, with opinions of the U.S.

returning to pre-quake levels relatively rapidly (Kinder 2010).

Is PEPFAR Effective?

The mixed findings of these studies may in part stem from differing impacts associated

with different types of aid. Because foreign aid is given in different forms and in different

contexts, it is unlikely that all forms of aid will improve public opinion. PEPFAR differs

from those aid programs previously studied in that it is an ongoing aid program, as

opposed to a response to a natural disaster or aid extended during a military conflict, and

it is given across numerous countries and contexts. Accordingly, its impacts might quite

reasonably be different from those found in other studies.

PEPFAR comprises a substantial share of the U.S. development aid budget

(approximately 15% in 2009). Although the total amount of U.S. development aid itself is

small when contrasted with the total spending the U.S. devotes to the military and other

foreign policy activities,3 we argue that PEPFAR could nevertheless have positive

perceptual “externalities” (indirect effects in a separate policy realm) for the following

four reasons.

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!3 In 2008, total U.S. aid spending was 0.18% of the country’s Gross National Income

(GNI), compared to military spending of 4.32% of GNI. However, due to the size of its

economy, the U.S. also donates the largest amount of aid globally (Radelet 2006).

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First, it is targeted at a critical need. The proportion of direct and indirect

PEPFAR beneficiaries in the population of a recipient country is expected to be fairly

large, particularly in the countries worst affected by HIV and AIDS. This is due to the

scale of the HIV and AIDS epidemic. In those countries, the illness has had a major

adverse impact on the lives of a significant portion of the population. In Botswana, for

example, about a quarter of the population aged between 15 and 49 was HIV positive in

2009. This figure is high enough to ensure that the disease also impacts many of those not

living with HIV and AIDS themselves, as even non-sufferers are likely to have relatives

or friends suffering from HIV and AIDS. Moreover, many of the poorest countries

receiving PEPFAR funding had, prior to the arrival of large-scale aid, been almost

completely unable to provide anti-retroviral therapy (ART) to HIV and AIDS sufferers.

But the provision of PEPFAR (and other similar funding) has significantly changed this

situation.

Second, PEPFAR aid is sustained over a considerable period of time, which may

increase perceptions of genuine commitment by the donor among recipient populations. It

also allows for information about the effects of the aid and its source to become more

firmly embedded in public perceptions due to repeated exposure to information about

PEPFAR. This should operate through basic cognitive “priming” mechanisms (Kolb and

Whishaw 2008), and also through gradual social spread of awareness via word of mouth.

Third, PEPFAR appears to have been effective in reducing the adverse impacts of

HIV and AIDS. The U.S. has made considerable efforts to ensure that PEPFAR has been

a well-run aid program (El-Sadr et al. 2012; Sepulveda et al. 2007; Simonds, Carrino, and

Moloney-Kitts 2012). Its objectives are well specified and misuse of the funds by

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recipients is minimized, if not completely eliminated, through careful monitoring. Indeed,

the 2011 WHO/UNAIDS Global HIV/AIDS Response Progress Report argues that the

major reason for the decline in AIDS deaths in 2010 since the peak year in 2005 was

PEPFAR (Cumming 2012), and at least two academic studies provide evidence

suggesting that PEPFAR has had positive health impacts. Bendavid and Bhattacharya

(2009) found that PEPFAR funding has significantly reduced HIV and AIDS related

mortality. Nunnenkamp and Öhler (2011) found that U.S. bilateral HIV funding

(essentially PEPFAR) has a significant impact on HIV related deaths.

Finally, PEPFAR is well publicized and thus visible among publics. The U.S. has

made sure that the fund has a high profile in recipient countries as “the leading platform

for US health diplomacy and a symbol of American capacity to achieve constructive and

beneficial change” (Collins et al. 2012, 1578). The U.S. has carefully and deliberately

branded PEPFAR funded work to “ensure appropriate recognition for U.S. programs and

contributions” (PEPFAR 2012, 2). The stars and stripes of the U.S. flag are a prominent

feature of the PEPFAR logo, and the signing of PEPFAR country agreements is often

undertaken by high profile figures in the U.S. administration, increasing in-country media

exposure and public awareness (Ingram 2010).4 In countries with high HIV prevalence

rates, PEPFAR has a significant media profile with improvements in HIV outcomes

frequently being attributed to PEPFAR (for example, Botswana Gazette 2011; IOL 2012;

Sambira 2013; Times of Zambia 2012a; Times of Zambia 2012b; Vo 2008). PEPFAR is

also unlikely to be overshadowed, or even rivaled, by other donors’ HIV/AIDS-related

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!4 For examples of high profile figures’ visits and their news coverage, see Kanyesigye

(2011), Sunday Standard (2011), and Times of Zambia (2012a).

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aid. The U.S. was the source of 52% of such bilateral aid commitments globally, 2004-

2006, while the second largest donor, the U.K., contributed 18% (Henry J. Kaiser Family

Foundation 2013).5

These four characteristics of PEPFAR – targeted to address a critical and widely

understood need, sustained delivery of aid over time, effectiveness (or perceived

effectiveness), and being highly visible – condition the theoretical contribution of our

study. We expect that aid that meets these conditions will be more likely to actually affect

opinion among recipient populations about the donor state.

Data and Variables

To test whether PEPFAR has an impact on public opinion in recipient countries, we

conduct regression analysis. The treatment variable is the per capita amount of PEPFAR

funds provided to each recipient country (in natural log). We averaged official statistics

over the first three years (2004-2006) since the disbursement of funds began in 2004.6

The number of countries receiving PEPFAR funds during this period was 79. By taking

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!5 We only use PEPFAR data for 2004-2006, but in 2007-2010, the years for which we

measure public opinion, the U.S. share of global bilateral HIV/AIDS aid was 59%.

6 U.S. President George W. Bush announced PEPFAR in January 2003, but disbursement

did not start until 2004. The data sources are various PEPFAR Operational Plans for

PEPFAR funds (in millions of current U.S. dollars) obtained at

<http://www.pepfar.gov/about/c19388.htm>, and the World Bank’s World Development

Indicators (WDI) for the total population, obtained at <http://data.worldbank.org/data-

catalog/world-development-indicators?cid=GPD_WDI>.

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the natural log of the highly skewed per capita amount, we exclude countries not

receiving any funding during the first three years.7

The outcome variable is the difference between the percentages (in natural log) of

respondents answering “approve” and “disapprove” to the following question asked in

Gallup World Polls (GWP): “Do you approve or disapprove of the job performance of the

leadership of the United States?” The GWP is the only available multinational survey

with nearly universal coverage of the developing world, repeating the same questions

annually about perceptions of the U.S. This question is especially appropriate for our

study because it focuses on the evaluation of current or recent U.S. leaders and their

behavior. By taking the natural log for both treatment and outcome variables, the

estimated treatment effect measures elasticity.8

The sampling procedures of the GWP targeted the national population aged 15 or

older in each country. Random-Digit-Dial (RDD) phone surveys were conducted where

at least 80% of the population has a telephone (primarily in developed countries), while

face-to-face interviews were conducted in all other countries. When RDD telephone

surveys were conducted, Gallup applied a list-assisted sampling design (Casady and

Lepkowski 1993) with all telephone numbers as the sampling frame. For face-to-face

surveys, an area sampling frame was used based on the latest available census data, with

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!7 As a robustness test, we also run a set of regressions after imputing missing values so

that we are able to use a larger number of countries for estimation. See a subsection

(Robustness Tests) in the Results Section.

8 We also used a slightly different outcome variable for another robustness test, the

results of which are presented in a subsection (Robustness Tests) in the Results Section.

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a stratified multi-stage random sample based on population units ranging usually from

cities with 1 million or more people to villages with under 10,000. The sample size is

roughly 1,000 surveys per country per year.9

Gallup Inc. launched this annual global public opinion study in 2006, asking the

question about U.S. leadership in each year.10 For our analysis, we use three outcome

variables – the average during the last two years of the Bush administration (2007-2008),

the average during the first two years of the Obama administration (2009-2010), and the

average during all four years. The use of these variables allows us to examine whether the

PEPFAR funding affected public opinion in recipient countries only when George W.

Bush, the founder of the PEPFAR program, was in office, and to be sure that our results

are not driven by changing global public opinion about the U.S. resulting from the

election of Barack Obama.

Because it is likely to have taken time for PEPFAR’s positive health impacts to

become clearly apparent, any effects of providing PEPFAR funds over multiple years on

public opinion in recipient countries are expected to be gradual and cumulative. In other

words, we assume that any short-term change (for example, a change from the previous

year) in PEPFAR funds does not abruptly cause a short-term change in public opinion

about the donor among recipient countries. For this reason, we take the averaged values

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!9 For details, see Tortora, Srinivasan, and Esipova (2010).

10 The number of countries in which this specific question was asked was 119 in 2006, 93

in 2007, 114 in 2008, 112 in 2009, and 115 in 2010. The country-level aggregated data

were obtained at <https://worldview.gallup.com/>.

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for both treatment and outcome variables and run cross-sectional (i.e., cross-country)

regressions.11

To increase confidence in our causal inference, we use instrumental variables

(IVs) that are expected to influence public opinion about the U.S. only through the

treatment variable (the amount of per capita PEPFAR funding). The use of instrumental

variables is often an effective way to address the issue of endogeneity using observational

data. Specifically, we use the HIV prevalence rate (the average of 2000-2003, in natural

log) and the number of annual HIV related deaths divided by the total population (the

average of 2000-2003, in natural log).12 HIV prevalence and death-rate data were used

extensively in designing PEPFAR’s approach, including the selection of recipient

countries, and setting annual funding levels (Lyerla et al. 2012). As would be expected,

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!11 Previous studies have shown that general ODA’s effects on economic growth are better

modelled over periods of several (specifically, four) years (Burnside and Dollar 2000;

Headey 2008).

12 The data source for the HIV prevalence rate and the number of annual HIV related

deaths is UNAIDS Data obtained at

<http://unaids.org/globalreport/documents/HIV_Estimates_GR2010_1990_2009_en.xls>.

If the reported HIV prevalence rate is “<0.1” percentage, we assigned a random number

between 0 (exclusive) and 0.1 (exclusive). Similarly, if the reported number of deaths is

“<1000”, “<500”, “<200”, or “<100”, we assigned a random number within the possible

range for each observation. The total population (2000-2003 average), the denominator

for the second instrumental variable, is from the World Bank’s WDI (see Footnote 6).

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our instruments are therefore strongly correlated with the treatment variable – the per

capita amount of PEPFAR funding (the average in 2004-2006).

Assuming they are valid, our instruments estimate the “local average treatment

effect” (Imbens and Angrist 1994). Formally, we estimate the average cross-country

effects of the variation in PEPFAR funding, which is determined by the variation in these

health indicators, rather than by other motivations such as geo-strategic selection, on

foreign public opinion. In other words, we have considerable confidence that we estimate

the effect of foreign aid targeted to need on public opinion. The allocation of PEPFAR

funds may be politically determined to some degree, but our IV estimates are unrelated to

such political considerations.

An important assumption in this analysis is the exclusion restriction, an

assumption that instruments can be excluded from the second-stage regression because

they are uncorrelated with the error term, conditional on other covariates included in the

model. To make this assumption plausible, we need to add variables that are expected to

correlate with our instrumental and outcome variables.13

First, U.S. total Official Development Assistance (ODA) per capita (in natural log,

averaged over 2004-2006) is the total aid funding received in each recipient country from

the U.S. (gross disbursements, current million U.S. dollars) divided by the total

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!13 We considered using a wide range of variables. See a subsection (Robustness Tests) in

the Results Section for more details.

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population (in millions).14 Including this variable ensures that any impact on opinion is a

result of PEPFAR and not of other aid programs designed in part to address public health

problems in developing countries.

Second, the U.S. may provide more PEPFAR funds to poorer economies and/or

poorly governed countries, and these countries are also likely to have more severe public

health problems. To control for these possibilities, we add GDP per capita (2004-2006

average, in natural log).15 For similar reasons, we control for the level of civil liberties

and the quality of governance, using the Freedom House civil liberties score (2004-2006

average),16 as well as a compositional score based on six World Bank Governance

Indicators (2004-2006 average).17 We also include a dummy variable for sub-Saharan

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!14 The data source of ODA disbursements is OECD DAC CRS Aid Database, obtained at

<http://www.oecd.org/document/33/0,2340,en_2649_34447_36661793_1_1_1_1,00.html

#dac>. See Footnote 12 for the source of total population.

15 The data source is the World Bank’s WDI (see Footnote 6). Specifically, the variable

we use is GDP per capita, PPP (constant 2005 international dollars).

16 The data source is Freedom House, Freedom in the World Country Rankings, obtained

at <http://www.freedomhouse.org/template.cfm?page=439>. An alternative measure of

the level of political development is polity score from Polity IV data. We, however,

prefer to use the Freedom House’s score, as there are no missing values for countries

included in our analysis. The two variables are highly correlated (r=0.81).

17 The data source is Teorell, Samanni, Holmberg and Rothstein (2011). The original

source is Kaufmann et al. (2009) available at <http://www.govindicators.org>. Because

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African countries to control for unobserved region-specific covariates.18 Because the

global HIV and AIDS epidemic is most acute in Sub-Saharan Africa and because much

of PEPFAR funding has been directed to countries in this region, this variable is essential

to ensure that our results are not driven by other, unobserved, region specific

characteristics.

Third, the problems associated with HIV and AIDS in a given country may affect

that country’s economic and political relationships with the U.S. (and then, in turn, the

country’s public opinion about the U.S.) Specifically, the U.S. tends to have weaker trade

ties with countries with more severe public health problems. This may be because these

countries are economically closed and/or because they lack goods to export to the U.S.

These countries also tend to have weaker political ties with the U.S., perhaps because of

their small presence in political and economic negotiations at international arenas. To

account for these connections, we use three variables. The first two are imports to the U.S.

from a given country as a percentage of total U.S. imports (in natural log), and exports

from the U.S. to a given country as a percentage of total U.S. exports (in natural log).19

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!the six indicators are highly correlated, we measured a Cronbach’s alpha. The reliability

coefficient is 0.97.

18 We generate a dummy variable base on a variable indicating the region of the country

in Teorell, Samanni, Holmberg, and Rothstein (2011). The original source is Teorell and

Hadenius (2005).

19 Fleck and Kilby (2006) use these variables to capture the impact of trade with the U.S.

on U.S. aid allocation decisions. The data source is U.S. Department of Commerce,

Bureau of the Census, Foreign Trade, obtained at <http://www.census.gov/foreign-

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As a proxy for each recipient country’s political connection to the U.S., we add a variable

measuring accordance of each country’s United Nations General Assembly (UNGA)

voting pattern with that of the U.S.20

Conditional on these covariates, we argue, it is unlikely that our instrumental

variables (HIV/AIDS rates) would have any impact on the outcome variable (public

opinion about the U.S. leadership) through any mechanism other than their impact through

the treatment variable (PEPFAR). In other words, having accounted for these covariates,

we have confidence that our instrumental variables are not systematically correlated with

the error term in the second-stage regression. Ultimately, the validity of this exclusion

restriction assumption is an empirical matter, and thus we conduct a set of standard

specification tests.

Results

Figure 1 shows the results of our first-cut analysis – simple scatter plots using the

outcome variable and the treatment variable. Each panel in this figure corresponds to one

of three periods used for analysis (i.e., 2007-2010, 2007-2008, or 2009-2010). The !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!trade/balance/>. Another commonly used indicator for the trade ties with the U.S. is the

sum of exports to the U.S. and imports from the U.S. as the percentage of GDP. This

variable, however, is found to be very weakly correlated with our instrumental variables.

20 The data source is Dreher and Sturm (2012), obtained at <http://www.uni-

heidelberg.de/fakultaeten/wiso/awi/professuren/intwipol/datasets_en.html>. The measure

used is the proportion of UN votes in the year of interest in which the aid recipient

country voted in-line with the United States. For a detailed description of the calculation

involved see Dreher and Strum (2012, 371)

! 21!

straight lines are OLS regression lines. All these lines have a positive slope, and the

estimated slope coefficients from simple bivariate regressions (0.26 for 2007-2010, 0.27

for 2007-2008, and 0.32 for 2009-2010) are highly significant at the 99% level.

[Figure 1 about here]

The magnitude of the effect is substantial and similar across the last two years of

the Bush administration and the first two years of the Obama administration. Specifically,

regardless of who the U.S. president was at the time of the surveys, doubling the per

capita amount of PEPFAR funds increased the ratio of the percentages of Approve and

Disapprove by about 30%. For example, if the percentage of Approve was initially 40%,

the estimated coefficients suggest that it would increase to 52%.21

Estimated Treatment Effects

Table 1 shows the results of two-stage least square (2SLS) regressions. The effect of

PEPFAR funds per capita on the perception of U.S. leadership is positive and statistically

significant at the 99% level of confidence for the 2007-2010 period overall, as well as for

the final Bush years, 2007-2008. It is significant at the 95% level during the initial

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!21 This simple interpretation assumes that PEPFAR increases the percentage of Approve

while keeping the percentage of Disapprove constant. PEPFAR may also decrease the

percentage of Disapproval, but understanding the impacts of PEPFAR on the

composition of percentages is beyond the scope of this paper. The average percentages of

Approve and Disapprove for the period of 2007-2010 were 45.8% and 31.2%,

respectively. The remaining percentage includes respondents who either chose “Don’t

know” or refused to answer.

! 22!

Obama years, 2009-2010.22 The estimated marginal effects are slightly smaller than those

based on simple bivariate OLS (shown in Figure 1) but still substantial. Specifically, if

the per capita amount of PEPFAR funding doubles, the ratio of Approval to Disapproval

increases by 20-23%. Importantly, we re-emphasize, the effects of PEPFAR on public

opinion in recipient countries are independent of the U.S. president’s popularity,

partisanship and of any perceived policy differences between Bush and Obama.23

[Tables 1 and 2 about here]

As expected, a set of specification tests (shown in Table 2) suggests that our

instruments are highly valid empirically. The small values of test statistics for !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!22 We experimented with many different sets of control variables, but the results,

discussed shortly, are similar.

23 The negative – but statistically insignificant – association of total U.S. ODA per capita

with opinion about U.S. leadership might be related to the various strategic purposes for

which some U.S. aid is given (Dreher, Nunnenkamp, and Thiele 2008; Gates and

Hoeffler 2004). The mixed goals of promoting U.S. foreign policy may cause U.S. aid to

be less effective at promoting development (Headey 2008). Specifically, U.S. aid may be

extended to more corrupt (Alesina and Weder 2002) and/or less democratic regimes, and

to those that violate human rights, to a greater extent than is the case for most other major

bilateral donors (Hoeffler and Outram 2011). Thus, U.S. ODA might be perceived in

some recipient countries as ineffective, and complicit in propping up dysfunctional or

repressive regimes. It is worth further investigating such potentially negative effects of

more general U.S. aid on opinion about the U.S. in recipient countries, but we leave it for

future research.

! 23!

endogeneity – Wooldridge’s (1995) robust Chi-square score test and a robust regression-

based F test – imply that our treatment variable (PEPFAR funds per capita) does not need

to be considered as endogenous.24 The partial R-square statistics in the first-stage

regression range from 0.39 to 0.45. Thus, the instruments explain 39-45% of the first-

stage regression’s overall goodness of fit. The F statistics for the joint significance of the

instruments in the first stage range from 15.5 to 25.5 and are highly significant. They are

larger than 10, which Stock, Wright, and Yogo (2002) suggest as the benchmark to assess

the reliability of 2SLS estimates for causal inference (when there is one endogenous

variable).

We also conducted over-identification tests to examine whether the instruments

are uncorrelated with the error term. Sargan’s (1958) and Basmann’s (1960) Chi-square

test statistics are very small. The associated high p values indicate that the exclusion

restriction assumption is empirically supported.

Placebo Tests

To further ensure that no additional unobserved factors are driving our results, we also

conducted placebo tests – also called “control-outcome” tests (Rosenbaum 2010) – using

similar-but-different outcome variables. Given that we do not expect PEPFAR aid to

have an effect on opinions about other countries, besides the U.S., these tests “exploit the

anticipated absence of an effect to provide information about unmeasured biases”

(Rosenbaum 2010, 121). They are based on identical questions about the approval of

leadership of (“Do you approve or disapprove of the job performance of the leadership

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!24 For this reason, we also estimated our model based on OLS. See a subsection

(Robustness Tests) in the Results Section.

! 24!

of…?”) China, France, Germany, India, Japan, Russia, the United Kingdom, and the

respondent’s home country. As in the case of the U.S., each “non-equivalent dependent

variable” (Cook and Campbell 1979, Chap. 2) measures the 2007-2008, 2009-2010, or

2007-2010 average difference between the percentage of Approval (in natural log) and

the percentage of Disapproval (in natural log).

[Table 3 about here]

Table 3 shows the estimated marginal effects of the treatment variable on these

nine outcome variables. The only statistically significant effects (at the 99% or 95%

level) were obtained for the outcome variable measuring the Approval vis-à-vis

Disapproval of leadership of the U.S. These tests further support our expectation that

PEPFAR affects public opinion specifically about the U.S. in recipient countries, and the

relationship is not the result of confounding factors.

There is a theoretical rationale for these empirical results. While donor countries

tend to give aid to combat HIV/AIDS to those states that are most affected by the

epidemic, there is also a substitution or free-riding dynamic in which other donors give

less to a specific recipient state when one donor gives a larger amount (Gaibulloev and

Sandler 2012). This could also be due to explicit multilateral coordination among donors.

Given that the U.S. is the largest such donor, this implies that other donors give relatively

less HIV/AIDS-related aid to the states receiving more from the U.S., which would

support our expectation that public opinion about other countries would not be

significantly related to PEPFAR funding provided by the U.S.

Interestingly, however, the effects on the leadership Approval vis-à-vis

Disapproval ratio in a respondent’s own country are negative and significant at the 90%

! 25!

level (for 2007-2010 and 2007-2008). The publics in countries receiving large PEPFAR

funds may assess the relative performance of their country’s leaders in comparison to that

of the U.S. leaders who provide – or are perceived to provide – effective foreign aid.

These barely significant effects are, however, not robust. Among many model

specifications we tried, they are more often insignificant (even at the 90% level) than

significant.

Robustness Tests

We also ran a range of other regression models for further robustness tests. First, building

on the initial bivariate correlations reported with the scatter plots in Figure 1 at the

beginning of this section we estimated our model using multiple regression (i.e., without

instruments). The results are presented in Appendix A (Table A). The effects of PEPFAR

funds per capita are slightly smaller, ranging from 0.15 to 0.17, but are still highly

significant at the 95% level in all three periods of investigation. The similarity between

the 2SLS and OLS regression results is what we expect, given that the test results for

endogeneity suggest that we do not necessarily need to treat the per capita amount of

PEFAR funds as endogenous, conditional on the covariates included in our estimation.

Second, we tried an alternative outcome variable; specifically, the difference

between the Approval percentage and the Disapproval percentage without taking the

natural log. The results shown in Appendix B (Tables B1 and B2) are quite similar. The

effects of our treatment variable are positive and significant at the 99% or 95% level. The

results of specification tests are also similar.25

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!25 The Chi-square statistic for the test of over-identification restrictions is large (3.005)

enough to reject the null hypothesis at the 90% level but not at the 95% level.

! 26!

Third, we randomly imputed small numbers for countries not receiving PEPFAR

funds and/or other foreign aid programs.26 This is aimed at testing whether our results are

driven by non-random exclusion of countries not receiving aid by taking the natural log

of the highly skewed per capita amount of PEPFAR or total ODA. The results are

presented in Appendix C (Tables C1 and C2). By imputing the missing values, we

substantially increase the number of observations. All three coefficients of PEPFAR

funds per capita are positive and statistically significant at the 95% level for 2007-2010,

90% for 2007-2008, and 99% for 2009-2010. The magnitude of the effects is slightly

smaller for 2007-2010 and 2007-2008, but almost exactly the same for 2009-2010.

Finally, we considered using other pre-treatment covariates aimed to satisfy the

exclusion restriction assumption. They include the geographical distance from the U.S.,

variables measuring the amount of U.S. military aid, a dummy variable for United

Nations Security Council members, a dummy variable for former U.S. colonies, a dummy

variable for Latin American countries, a dummy variable for Egypt, and the percentage of

Muslims in each country’s population. Adding these variables individually or jointly does

not substantially change our main results, although doing so tends to increase the

standard errors of the coefficients for our treatment variable. To avoid this problem of

inefficiency, for our main results reported in Tables 1 and 2, we decided to keep a

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!26 Specifically, for each period of investigation (2007-2010, 2007-2008, or 2009-2010),

we calculated the minimum amount of PEPFAR funds per capita or U.S. total ODA per

capita. For each of countries not receiving PEPFAR or other aid programs, we imputed a

random number ranging from 0 (exclusive) to the observed minimum value. After

imputing these missing values, we took the natural log of each variable.

! 27!

variable not only when there was a theoretical reason to include it, but also when its

pairwise correlation with one of our instrumental variables was statistically significant at

the 95% level. None of these additional pre-treatment covariates satisfied our criteria, and

thus we did not include them in our main analysis.

Conclusion

These findings provide robust evidence that PEPFAR has had a strong positive effect on

how U.S. leadership has been perceived in recipient countries. The results of

specification tests, placebo tests, and robustness tests suggest that the observed effects are

not statistical artifacts, and thus we are strongly inclined to believe that they are causal.

Our theory is that these empirically robust results stem from the fact that PEPFAR is

targeted to address a widely understood need; has been sustained over some time; is –

and is perceived to be – effective; and is highly visible.

Whether, and the extent to which, these conditions apply individually and/or

jointly are important questions for future investigation. At present, such investigations

aimed to identify the mechanisms through which PEPFAR has had its impact are limited

by the absence of individual-level (or household-level) survey datasets. Once such data

become available, further work could examine, for example, whether positive perceptions

are higher among those impacted directly (i.e., suffering from HIV and AIDS or the

families of sufferers) and/or among those with better access to media and the publicity of

PEPFAR.

In addition to further work looking inwards, there is considerable scope for

further work looking outwards. Specifically, one important way our approach could be

extended is by testing whether other aid programs targeted to important needs, sustained

! 28!

over time, perceived as effective, and well-publicized or otherwise visible to the

population are also positively associated with opinion about the U.S. Another would be to

examine this relationship for other donor countries. Give the large absolute amounts of

aid the U.S. provides, it remains an open question whether other donors’ extant smaller

programs might affect perceptions within recipient countries about these donors.

Another promising area of further investigation stemming directly from this

article would be to study other humanitarian aid programs addressing global health issues

that have been successful in tackling other major illnesses, such as small pox, polio, river

blindness and malaria. While there are many examples of aid failing to provide benefits,

PEPFAR is not unique in its achievements. Indeed, there are other well-documented

examples of aid having significant positive impacts (for example, Demombynes and

Trommlerova 2012; Levine 2007). Thus, future work should seek to extend our analysis

across a range of programs.

Having acknowledged some limitations and future research directions, we

underscore that our analysis is the first of its kind to use cross-country data to make

systematic causal inference about the impacts of aid on public opinion in aid recipient

countries. Our findings suggest that policy debates about PEPFAR and similar programs

should consider not only their efficacy in achieving direct goals such as fighting HIV and

AIDS, but also their value in improving the donor country’s global or regional standing.

Beyond the literature on aid effectiveness, our research has broader implications

for understanding today’s international relations. If analysts are correct that national

image is increasingly a key resource for great powers’ international influence, our

findings may be good news. With militarized confrontation tempered by high economic

! 29!

interdependence (for example, between China and the U.S. today, but unlike the U.S. and

USSR during the Cold War), great powers might now start learning to place more

emphasis on improving their image through aid, because it enhances their power. Our

research shows that one possible means of doing well in the newly forming arena of

international competition for favorable perceptions is by actually doing good.

! 30!

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Figure 1: Scatter Plots

!

Note: The bivariate relationship between PEPFAR funding per capita (log) and the log-

ratio of the percentage of “approve” and the percentage of “disapprove” responses to the

following question asked in Gallup World Polls: “Do you approve or disapprove of the

job performance of the leadership of the United States?”

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log (PEPFAR funding per capita, 2004-2006 average)

! 43!

Table 1: Results of 2SLS Regressions

2007-2010 2007-2008 2009-2010

Average Average Average

PEPFAR funds per capita (log) 0.202 0.229 0.226

[0.068] [0.080] [0.091]

US total ODA per capita (log) -0.107 -0.101 -0.065

[0.067] [0.081] [0.057]

GDP per capita (log) -0.305 -0.405 0.039

[0.185] [0.205] [0.198]

World Bank governance indicator -0.528 -0.366 -0.472

[0.414] [0.502] [0.466]

Freedom House civil liberties score -0.250 -0.225 -0.282

[0.151] [0.166] [0.158]

Africa dummy 0.804 0.698 0.973

[0.318] [0.311] [0.428]

Imports to US (% of total US imports, log) 0.080 0.125 0.030

[0.089] [0.096] [0.091]

Exports from US (% to total US exports, log) -0.052 -0.118 -0.073

[0.130] [0.141] [0.152]

UN voting in accordance with US 0.970 0.476 0.531

[0.693] [0.697] [0.770]

Constant 4.089 4.710 1.439

[1.719] [1.909] [1.783]

Number of countries 57 55 46 Wald Chi-square 122.41 109.83 122.37 R-square 0.572 0.550 0.677 Root MSE 0.685 0.737 0.591 Note: The outcome variable is the log ratio of Approve (%) and Disapprove (%)

responses to the question, “Do you approve or disapprove of the job performance of the

leadership in the United States?” Numbers in brackets are robust standard errors.

! !

! 44!

Table 2: Results of Specification Tests

2007-2010 2007-2008 2009-2010


Tests of endogeneity: Robust score Chi-square 0.481 1.539 0.088

(0.488) (0.215) (0.766) Robust regression F 0.406 1.323 0.070

(0.527) (0.256) (0.792) Test of relevance of instruments: Partial R-square (first-stage regression) 0.452 0.449 0.387 F (first-stage regression) 25.509 23.877 15.505

(0.000) (0.000) (0.000) Test of over-identification restrictions: Chi-square 0.812 1.104 0.315

(0.368) (0.293) (0.574) Note: Numbers in parentheses are p values. Also see Note in Table 1.

! !

! 45!

Table 3: Results of Placebo Tests

2007-2010 2007-2008 2009-2010 Average Average Average

United States 0.202 0.229 0.226

[0.068] [0.080] [0.091] China -0.012 0.028 -0.042

[0.050] [0.055] [0.082] France -0.060 -0.064 0.032

[0.059] [0.059] [0.088] Germany -0.058 -0.069 -0.055

[0.052] [0.062] [0.079] India -0.021 -0.015 -0.086

[0.063] [0.076] [0.067] Japan -0.018 -0.018 -0.006

[0.052] [0.060] [0.079] Russia -0.043 -0.026 0.088

[0.101] [0.098] [0.191] United Kingdom 0.093 0.111 -0.021

[0.080] [0.087] [0.095] Own Country -0.128 -0.122 -0.123

[0.075] [0.074] [0.153] Note: The estimated effects of PEFPAR funding per capita (log, 2004-2006 average) on

the difference in the percentage of “approve” (in log) and “disapprove” (in log) responses

to the following question asked in Gallup World Polls (2007-2010 average, 2007-2008

average, or 2007-2010 average): “Do you approve or disapprove of the job performance

of the leadership of <China, France, Germany, India, Japan, Russia, the United Kingdom,

the United States, or Own Country>?” Numbers in brackets are robust standard errors.

! 1!

Doing Well by Doing Good:

The Impact of Foreign Aid on Foreign Public Opinion

Benjamin E. Goldsmith Yusaku Horiuchi Terence Wood

First Draft: February 20, 2012

Last Update: November 29, 2013

Appendices

A. The Results of OLS Regression

B. The Results of 2SLS Regression and Specification Tests, Alternative

Specification #1

C. The Results of 2SLS Regression and Specification Tests, Alternative

Specification #2

! 2!

Table A: Results of OLS Regressions

2007-2010 2007-2008 2009-2010



[0.061] [0.070] [0.068]


[0.069] [0.077] [0.063]


[0.212] [0.219] [0.228]


[0.425] [0.460] [0.500]


[0.162] [0.168] [0.159]

Africa dummy 0.857 0.773 1.142

[0.334] [0.344] [0.355]


[0.099] [0.108] [0.108]


[0.141] [0.152] [0.163]


[0.802] [0.766] [0.712]

Constant 2.053 4.994 -0.288

[2.136] [2.101] [2.180]

Number of countries 64 59 52 F statistics 11.53 11.69 11.28 R-square 0.538 0.601 0.623 Root MSE 0.821 0.807 0.708 Note: The outcome variable is the log ratio of Approve (%) and Disapprove (%)



!! !

! 3!

Table B1: Results of 2SLS Regressions, Alternative Specification #1

2007-2010 2007-2008 2009-2010



[0.021] [0.025] [0.025]


[0.021] [0.026] [0.017]

GDP per capita (log) -0.117 -0.145 -0.001

[0.061] [0.069] [0.054]


[0.131] [0.163] [0.122]


[0.046] [0.051] [0.042]

Africa dummy 0.340 0.313 0.389

[0.091] [0.094] [0.103]

Imports to US (% of total US imports, log) 0.011 0.024 -0.014

[0.025] [0.029] [0.020]

Exports from US (% to total US exports, log) 0.008 -0.009 0.010

[0.038] [0.042] [0.033]


[0.198] [0.208] [0.171]

Constant 1.460 1.658 0.505

[0.583] [0.650] [0.505]

Number of countries 57 55 46 Wald Chi-square 184.30 153.66 229.69 R-square 0.644 0.603 0.788 Root MSE 0.206 0.227 0.156 Note: The outcome variable is the difference between Approve (%) and Disapprove (%)



!! !

! 4!

Table B2: Results of Specification Tests, Alternative Specification #1

2007-2010 2007-2008 2009-2010






(0.746) (0.433) (0.083) Note: Numbers in parentheses are p values. Also see Note in Table B1.

!! !

! 5!

Table C1: Results of 2SLS Regressions, Alternative Specification #2

2007-2010 2007-2008 2009-2010



[0.081] [0.087] [0.087]


[0.065] [0.070] [0.056]


[0.159] [0.180] [0.191]

World Bank governance indicator -0.254 -0.154 0.084

[0.352] [0.428] [0.309]


[0.131] [0.161] [0.119]

Africa dummy 0.883 0.787 1.197

[0.261] [0.261] [0.288]


[0.065] [0.070] [0.084]


[0.095] [0.111] [0.106]


[0.562] [0.684] [0.572]

Constant 3.569 4.476 1.079

[1.429] [1.608] [1.646]

Number of countries 108 100 92 Wald Chi-square 139.58 183.68 78.46 R-square 0.479 0.554 0.417 Root MSE 0.795 0.856 0.779 Note: The outcome variable is the log ratio of Approve (%) and Disapprove (%)


leadership in the United States?” we randomly imputed small numbers for countries not

receiving PEPFAR funds and/or other foreign aid programs. Numbers in brackets are

robust standard errors.

! !

! 6!

Table C2: Results of Specification Tests, Alternative Specification #2

2007-2010 2007-2008 2009-2010






(0.093) (0.029) (0.511) Note: Numbers in parentheses are p values. Also see Note in Table C1.

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Doing Well by Doing Good: The Impact of Foreign Aid on Foreign Public Opinion