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Faust, Paul: Does Aid Contribute to Sustainable Development Goals? Empirical
Evidence from a Donor Comparison, Hamburg, Anchor Academic Publishing 2017
PDF-eBook-ISBN: 978-3-96067-716-1
Druck/Herstellung: Anchor Academic Publishing, Hamburg, 2017
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Contents
Contents
I
List of Abbreviations
II
List of Tables
III
List of Figures
IV
List of Appendices
V
1
Introduction
1
2
The Debate on Aid Effectiveness
6
2.1
The aid-growth literature . . . . . . . . . . . . . . . . . . . . . . . .
6
2.2
Looking beyond the effect of growth . . . . . . . . . . . . . . . . . .
10
2.3
Evidence from donor investigations . . . . . . . . . . . . . . . . . . .
12
2.3.1
The aid allocation literature: Deriving donor interests . . . . .
13
2.3.2
Determining donor differences . . . . . . . . . . . . . . . . .
16
3
Research objectives
19
4
Preliminary Empirical Analyses
21
4.1
Data sources and definitions
. . . . . . . . . . . . . . . . . . . . . .
21
4.2
Disaggregating aid descriptive statistics . . . . . . . . . . . . . . .
23
5
A first approximation: Cross-Country Evidence
29
5.1
The effect on growth . . . . . . . . . . . . . . . . . . . . . . . . . .
30
5.2
The effect on social indicators
. . . . . . . . . . . . . . . . . . . . .
35
5.3
Post-Cold War changes . . . . . . . . . . . . . . . . . . . . . . . . .
39
6
Insights from a Dynamic Panel Data Model
40
6.1
Reinvestigating the effect on growth . . . . . . . . . . . . . . . . . .
43
6.2
Reinvestigating the effect on social indicators . . . . . . . . . . . . .
49
6.3
Robustness tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
52
7
Policy Implications
55
8
Conclusion
58
Appendix
64
References
I
80
List of Abbreviations
BA . . . . . . . . . . . . Bilateral aid
DAC . . . . . . . . . . Development Assistance Committee
G1 . . . . . . . . . . . . Group 1 (Denmark, Finland, the Netherlands, Norway, Sweden)
G2 . . . . . . . . . . . . Group 2 (France, Germany, Japan, the UK, the US)
GDP . . . . . . . . . . Gross domestic product
GMM . . . . . . . . . Generalised method of moments
GNI . . . . . . . . . . . Gross national income
HDI . . . . . . . . . . . Human Development Indicator
IMF . . . . . . . . . . . International Monetary Fund
INSCR . . . . . . . . Integrated Network for Societal Conflict Research
MA . . . . . . . . . . . Multilateral aid
MDG . . . . . . . . . . Millennium Development Goals
MENA . . . . . . . . Middle East and North Africa (region)
NGO . . . . . . . . . . Non-governmental organisation
ODA . . . . . . . . . . Official Development Aid
OECD . . . . . . . . . Organisation for Economic Co-operation and Development
OLS . . . . . . . . . . . Ordinary least squares
SDG . . . . . . . . . . Sustainable Development Goal
SSA . . . . . . . . . . . Sub-Saharan Africa
UK . . . . . . . . . . . . United Kingdom
UN . . . . . . . . . . . . United Nations
UNDP . . . . . . . . . United Nations Development Programme
US . . . . . . . . . . . . United States of America
USD . . . . . . . . . . . US Dollar
WDI . . . . . . . . . . World Development Indicators
II
List of Tables
1
Group assignment of bilateral donors
. . . . . . . . . . . . . . . . .
23
2
Aid allocation of bilateral donor groups . . . . . . . . . . . . . . . .
27
3
OLS cross-sectional estimations: Aid and growth . . . . . . . . . . .
33
4
OLS cross-sectional estimations: Aid and infant mortality . . . . . . .
37
5
OLS cross-sectional estimations: Aid and primary completion
. . . .
38
6
First evidence of post-Cold War changes in aid effectiveness . . . . .
39
7
Aid and growth: GMM panel data evidence . . . . . . . . . . . . . .
44
8
Aid and social indicators: GMM panel data evidence . . . . . . . . .
50
9
Robustness of panel data estimations - the effect on growth . . . . . .
53
10
Robustness of panel data estimations - the effect on social indicators .
54
III
List of Figures
1
The development of aid payments by donor . . . . . . . . . . . . . . .
25
2
Conditional relationships between aid and growth . . . . . . . . . . .
34
2a)
G1 aid and growth . . . . . . . . . . . . . . . . . . . . . . . . . . .
34
2a)
G2 aid and growth . . . . . . . . . . . . . . . . . . . . . . . . . . .
34
IV
List of Appendices
Appendix A: The UN Development Goals . . . . . . . . . . . . . . . . . . . .
64
Appendix B: Data description and sources . . . . . . . . . . . . . . . . . . . .
66
Appendix C: Patterns of aid allocation . . . . . . . . . . . . . . . . . . . . . .
66
Appendix D: Cross-sectional estimation results . . . . . . . . . . . . . . . . .
69
Appendix E: GMM estimation results: Aid and growth . . . . . . . . . . . . .
71
Appendix F: GMM estimation results: Aid and social indicators . . . . . . . .
73
Appendix G: Robustness tests - main regression . . . . . . . . . . . . . . . . .
74
Appendix H: Additional tests for robustness . . . . . . . . . . . . . . . . . . .
76
Appendix I: Hausman specification tests . . . . . . . . . . . . . . . . . . . . .
78
V
1 Introduction
No Poverty, Zero Hunger, Good Health, Well-being and Quality Education - these are
the first priorities of the Sustainable Development Goals (SDGs) that were launched
jointly by all UN Member States on 1 January 2016. The agenda of this agreement
contains 17 main goals with a total of 169 targets and is dedicated to improving global
living conditions and to address issues of environmental and economical sustainability
with a planning horizon through to 2030. Development assistance from economically
advanced countries, also referred to as aid, is one of the major means to provide
financing for countries with less developed economies that face severe social problems
and which often cannot handle these problems alone.
Half a century ago, several major industrialised countries began to launch large aid
programmes after establishing the Development Assistance Committee (DAC) that
serves as a platform for dialogue and discussion about the way international donors can
contribute most effectively to the development of economically poorer countries. Since
1964, aid flows from DAC member countries are recorded as Official Development
Assistance (ODA) and corresponding data is made publicly available. The number of
donors, as well as the amount of funds, is consistently growing, reaching a maximum
of almost USD 95 billion spent by 30 member countries in 2014. Over certain periods
of time, aid payments accounted for a large share of the domestic economy of single
recipient countries. In the most extreme cases, aid flows from various donors added up
to more than 50% of the government budget often spanning several years.
Such extensive monetary flows that aim to improve economic and social conditions
in a broad range of developing countries were unknown until that time, leaving open
the question of the resulting effect. Because the topic also implies a moral importance
due to the donors' commitment to eliminate global poverty and inequality, the topic
immediately attracted world-wide interest among the research society. The first studies
dealing with the subject appeared almost simultaneously as the first aid flows were
disbursed. These studies assess the possible impact of aid, theoretically based on former
growth models. As soon as first data became available, researchers began to directly
estimate the effect of aid on economic parameters. By now, the topic of aid effectiveness
covers an immense amount of contributions with a variety of different research fields.
Estimation methods, as well as quality and availability of data on developing countries
have improved over the time. However, despite the emergence of more accurate
methodology and an increasing number of scientific contributions, the entire history
of research on this topic is accompanied by a lack of consensus. On the one hand,
several studies find that aid has a significant positive impact on growth, whereas an
equally large share of contributions cannot find an effect at all, or even demonstrate a
1
negative correlation between aid and growth. The disagreement among researchers is
not only consistent over time, but also across different estimation methods and even
between studies that apply the same approaches based on identical data. The perennial
debate that has emerged over the past twenty years particularly leaves the reader with
the impression that research in this area is going around in circles. Studies that take up
the finding of a preceding investigations, apply small changes to the original approach
and end up with a different result largely shape the image of the latest aid effectiveness
literature one can therefore conclude that the question whether aid as a positive impact
on growth or not still remains unanswered.
It is certain, however, that aid in general is falling short of the initial expectations
that donors and first researchers had. Therefore, a wide range of the literature aims
to find out why aid does not show to have the desired effect. Several studies find that
aid increases non-productive government expenditures instead of benefitting the poor.
Others argue that aid only shows to be effective when directed to recipient countries
with a high level of institutional quality and good policies, and conclude that funds have
largely been transferred to the wrong countries. A further avenue of research that has
developed over the past decades pursues a different objective than estimating the effect
of aid: By analysing the pattern of aid flows, the aid allocation literature determines the
main driving forces behind the donors' choice of recipient countries. Resulting insights
prove to be plausible explanations for the missing effectiveness of aid. The parameters
that presumably shape the allocation decisions are either related to the recipient, such
as humanitarian needs, institutional quality or the level of economic openness; or to the
donor, e.g. political and economic interests or ties with recipients that have formerly
been colonised by the donor.
One of the major conclusions of one strand of the aid allocation literature, most of
which published during the past 15 years, is that there are striking differences among
donors regarding their prioritisation of recipient needs or their own objectives. Several
studies find that major industrialised countries, such as the US, Japan or France, put
less emphasis on recipient needs and more on their own objectives. In contrast, aid
from multilateral donors or smaller bilateral donors, such as Scandinavian countries
or the Netherlands, is considered to be far less driven by economic or power-political
interests and proves to be distributed with a high regard for the different recipient-related
parameters.
Taking this observation into consideration, it appears evident that the effectiveness of aid,
equal to the pattern of allocation, differs among donors. Yet, nearly all investigations
focus on the effect of aggregated aid i.e. total aid funds from all donors. Only in
recent years, research begins to consider this issue, mostly distinguishing between the
impact of bilateral and multilateral aid. Empirical evidence on potential differences
2
in aid effectiveness between single bilateral donors, however, remains very limited.
Because bilateral aid accounts for most of the total supplied funds, further research on
this topic is indispensable.
Consequently, the main research objective of this thesis is to investigate whether the
insight of the aid allocation literature, i.e. bilateral donors differ significantly regarding
the motives behind allocating aid, can be applied to determine measurable differences
in aid effectiveness. In other words, are differences in the way distinct donor countries
allocate aid large enough to result in quantitative differences in the impact on develop-
ment of recipient countries? The answer to this question could offer an explanation for
why aid research often fails to find a positive effect of aid. And more importantly, it
could provide insight on the types of aid that appear to be unrelated with development
and those that show a positive impact on recipient countries.
In order to estimate differences between bilateral donors, this study forms two groups
that are assumed to allocate aid in a significantly different manner an approach that
is not applied up to the present. The first group comprises Denmark, Finland, the
Netherlands, Norway and Sweden; all of which seem to exclude personal interest and
to put great emphasis on recipient needs. France, Germany, Japan, the United States
of America (US) and the United Kingdom (UK) form the second group as bilateral
donors that are considered to allocate aid with high regard to their own objectives. To
determine the possible difference in aid effectiveness between these two donor groups,
the aim of this thesis is to follow the latest and established strategies of estimating the
effect of aid on growth in a first place.
As several recent studies argue that growth is not the only appropriate measure of
development, this thesis additionally investigates the impact of aid on the two most
often researched social indicators. These are infant mortality, as a key indicator for
heath standards, and primary education to measure the quality of the educational system.
Both of these indicators are explicitly included in the agenda of the eight Millennium
Development Goals (MDGs) of 2000 and are concrete targets of the current SDGs.
Thus, an analysis of the effect on the two indicators also covers a more concrete answer
to the question whether aid contributes to sustainable development goals.
Moreover, because the literature does not agree on whether or not multilateral aid is
more effective than bilateral aid, the analyses of this study are accompanied by a further
differentiation between these two types of aid. In addition to the separate analysis of
two bilateral donor groups, this kind of disaggregating aid offers a further opportunity to
decompose aid into potentially ineffective or beneficial types. As bilateral aid comprises
both donor groups of the main investigation, this additional analysis enables a direct
comparison of aggregated and disaggregated aid flows, which possibly achieves more
valuable results.
3
The investigations of this study consider two further insights of the previous literature.
The first one is that aid is assumed to affect development with a partially large time lag.
The rationale behind this assumption is that development assistance largely comprises
projects in areas such as infrastructure, energy, education or health, which require a
long implementation period until they may achieve benefits. Second, several studies
suggest that the aid allocation of major donors has significantly changed since the end
of the Cold War, implying changes in the underlying motives. As the latter finding
indicates that aid effectiveness increases after 1989, additional estimations shall reduce
the observation period to 1990-2014.
In order to gradually answer these research questions, the study first presents a detailed
investigation of the existing literature, beginning with a section that outlines the origin
and history of the research field. This section aims at identifying problems and solutions
associated with the estimation of aid effects and additionally addresses the current debate
on the impact of aid on growth. The closer inspection of the recent research covers
studies from the last 20 years; the aid effectiveness literature has seen a remarkable
upswing during this period, which has led to a persistent discussion. In a next step,
the literature review shifts the focus away from the aid-growth debate to the usage of
alternative development indicators for measuring the impact of aid.
A further section then discusses those investigations that determine the pattern of aid
allocation. Studies of this strand of literature provide an important theoretical foundation
for this thesis, i.e. the indication that aid effectiveness might differ between donors.
Investigations of this kind also demonstrate changes in motives for providing aid after
the end of the Cold War. The insights of the aid allocation literature lead to a final
section that discusses the approaches and results of previous studies that attempt to
measure differences in aid effectiveness among donors. Following the literature review,
a separate chapter utilises the obtained insights in order to draw implications for the
subsequent analysis and to precisely define the research objectives of this study.
A descriptive analysis initiates the empirical part of this study. After describing the
applied data and corresponding issues, the main section of this chapter attempts to
confirm the findings of the aid allocation literature in the case of the donors that are
analysed in this study. An investigation of the temporal development of each donor's aid
flows, followed by a more detailed analysis of the individual pattern of aid allocation
shall amplify the evidence achieved from the literature. Subsequent cross-sectional
estimations of the actual aid effects provide reader with a first approximation of the
results among different donors. The analysis of cross-country data based on ordinary
least squares (OLS) method is among the first approaches for estimating the effect
of aid, and is still applied by a number of recent studies. The initial assessment is
divided into three parts. The first section identifies donor-specific aid effects on growth
4
as the indicator that is most-often applied for estimating the impact on development
in recipient countries. The second part observes both infant mortality and primary
completion as social indicators. A final section approximates how aid effects vary in
the post-1989 period after the end of the Cold War.
The application of cross-sectional data, however, is for several reasons afflicted with a
certain inaccuracy, compared to more sophisticated estimation strategies based on panel
data that have emerged over the past decades. The main estimation method of choice,
therefore, is a generalised method of moments (GMM) based dynamic panel analysis.
Chapter 6, as the main of the empirical analysis, begins by discussing the benefits of
the GMM dynamic panel data approach in contrast to cross-sectional investigation.
Subsequently, the effect on growth and on both social indicators is reassessed. As
the application of GMM estimators is not free from bias either, a third section of
chapter 6 tests for robustness of the panel data approach. This is based on simple OLS
methodology and a fixed effects (FE) estimator, both of which are also applied in recent
research. A further step is to derive policy implications from the obtained results, and
chapter 8 concludes.
5
2 The Debate on Aid Eectiveness
Following the establishment of the Development Assistance Committee in 1960, nearly
all the major developed countries started extensive aid programmes with the objective of
alleviating global poverty (cf. Doucouliagos and Paldam 2006: 227). Shortly afterwards,
first researchers began to assess the effects of aid against the high expectations of the
donors. The first studies were published at the end of the 1960s and the early 1970s.
Since then, a great variety of researchers have been dealing with the question whether
and to which extent development assistance impacts economic growth of recipient
countries. Underlying theories and the methodical procedure to filter out the effect of
aid have been reconsidered and adapted to more sophisticated empirical approaches
several times up to the present.
More surprisingly, but very characteristic for the aid research, the numerous outcomes
for the effect of aid vary to a high extent and are inconsistent in sign and degree up until
now. For this reason, and for the great number of contributions in this area, multiple
studies attempt to categorise the research field by classifying contributions by their
findings or the methodical framework put to use. Scientific approaches from the first
decades of research have repeatedly been refined and further developed and hence are
less relevant for the empirical part of this thesis. Yet, their contributions are useful for
understanding the nature of the aid effectiveness debate and shall, thus, be summarised
briefly. Because the most influential and still discussed studies have been published
over the past 20 years, their procedure and findings shall be analysed in more detail.
1
At the beginning of the debate in this field, aid effectiveness was generally seen in
an economical context. After initial attempts to analyse the impact on more precise
macroeconomic determinants such as savings and investment, the approach of analysing
the direct impact on economic growth has prevailed so far in this strand of the literature.
A first section explains this development and the predominant strand of research, the
aid-growth literature. Recently, several contributions consider the impact of aid on
social indicators in addition to growth. A second section illustrates the reasons behind
this choice, as well as the approaches and outcomes of influential studies in this field.
2.1 The aid-growth literature
The first contributions from the early 1960s mostly focus on the estimated capital
required by developing countries. Theoretically based on the Harrod-Domar growth
model, these studies address the relationship between foreign assistance and total
savings with the underlying assumption that filling up the saving gap implies higher
1
Extensive investigations of the first decades of research can, for instance, be found in Hansen und Tarp
(2000) or the meta-analyses of Doucouliagos and Paldam (2006, 2009).
6
investments and therefore an increase in growth. With a positive expectation towards
the effect of aid on growth, they assume that aid payments contribute in an equal amount
to the developing countries' savings and thus investment, such as Rosenstein-Rodan
(1961: 136), to name one of the most influential studies of this period.
The arguments of a subsequent strand of the literature likewise draw on the effect
on savings. However, questioning the high expectations of the previous literature,
these studies find out a negative impact of foreign assistance on domestic savings of
developing countries. Since they attempt to determine the extent of aid for the first
time by applying cross-sectional or time series analyses, they are often regarded the
first contributions to the aid effectiveness literature (cf. Clemens et al. 2012: 591).
The earliest publication of this strand of the aid-savings literature, Griffin and Enos
(1970: 320), states that the former expected relationship between aid and savings would
be too simple and that a general negative tendency between foreign assistance and
domestic savings points towards a negative effect on growth. Weisskopf (1972: 37)
even concludes that the effect of aid on ex ante domestic savings would be significantly
negative.
Soon afterwards, Papanek (1972, 1973) marks an early turning point in the literature by
shifting away the focus from analysing the effect on savings towards directly measuring
the impact of aid on growth. He argues that savings had so far been determined by
subtracting inflows from investment, which would lead to a self-explanatory negative
correlation (cf. Papanek 1972: 945-947). Considering the issue of causality between
low savings in least developed countries (LDC) and high aid payments for the first time,
he questions the validity of previous results. Furthermore, he disputes the approaches
of his predecessors because of their aggregation of all foreign inflows. He attempts to
separate these, resulting in a regression for predicting the various effects of aid, savings,
investment and other components of foreign inflows on growth (Papanek 1973: 121)
and concludes that there is a strongly significant correlation between aid and growth
(ibid.: 129).
The approach of Papanek is taken up by a series of subsequent studies that investigate
the effect of aid on either investment. Amongst these is Mosley (1980: 81-84), who
introduces a further methodical advancement to the aid literature by instrumenting
for aid in a two stage least squares regression. He comes to the conclusion that the
overall relation between aid and growth is negative and insignificant, but positive when
only considering the poorest countries (ibid.: 89-90). Although several subsequent
publications take up this procedure, the actual impact of aid remains controversial: Levy
(1988: 1781-1787), for instance, finds a strongly significant positive impact on both
investment and growth in African countries. Snyder (1993: 484) even reports an overall
positive effect of aid after controlling for population growth of the recipient countries.
7
On the opposite side, various studies find that aid and growth prove are unrelated, such
as Mosley et al. (1987: 636).
The recent literature, considering the current status, is introduced by the work of Boone
(1996). With the help of more complete data, he performs panel data analyses with
five-year averages while controlling for country specific effects (ibid.: 305). Moreover,
he uses three new instruments for dealing with potential endogeneity in the regressors
and analyses aid effects on growth, infant mortality, life expectancy and primary school
attendance (ibid. 308-309). Boone (1996: 322-323) arrives at the conclusion that aid
does not show to have any significant effect on neither of the parameters. Instead, he
observes a connection between aid and higher total consumption. He states at the same
time, however, that there is no evidence that higher consumption would benefit the poor
(ibid.: 315). Boone's findings have been addressed by many studies up to the present.
The literature that has emerged since then can be classified into three strands of studies
in the following also termed studies of strand 1-3.
2
A first line of studies finds a positive
impact of aid under certain circumstances, such as the existence of specific policies or
relations between the donor country and the recipient. A second series of studies, strand
2, confirms the results of Boone, i.e. aid and growth are uncorrelated. On the contrary,
a third strand of the literature determines a positive effect of aid that holds regardless of
certain conditions.
The first strand, which Clemens et al. (2012) term the "conditional strand" (p. 592),
comprises several of the most influential studies of the aid-growth literature. These
studies reflect Boone's results of an absent effect of aid on growth in a total sample, but
determine a positive effect of aid only under certain circumstances and, thus, imply op-
portunities of (re)structuring aid flows in an effective manner. The arguably best-known
example is Burnside and Dollar (2000), which extend the instrumentation strategy by
including an interaction term of aid and economic policies. After determining a signifi-
cantly positive coefficient of this variable, Burnside and Dollar (2000: 857) conclude
that aid works better in countries that feature strong economic policies and institutions.
Many subsequent papers, for example Easterly (2003: 24) or Clemens et al. (2004:
8), highlight the great influence of Burnside and Dollar (2000) on both research and
the policies of major aid organisations, such as the World Bank and other multilateral
development banks. Furthermore, there are various papers that confirm the relationship
between good policies and the effectiveness of aid on growth, as for example Alvi et al.
(2008: 702). Other studies belonging to this strand of the literature identify a positive
effect of aid on growth in countries that are, for instance, geographically located outside
the tropics (cf. Dalgaard et al. 2004: 201) or in a longer period of peace (cf. Collier and
Doller 2002: 1135).
2
The following categorisation of the recent aid into three strands is inspired by Clemens et al. (2012:
592-593) and extended up to the present.
8
A further number of publications can be assigned to a second strand due to their common
conclusion that aid and growth are unrelated, regardless of certain circumstances. To this
category belongs Roodman (2007: 266), who tests the robustness of several influential
first strand studies - amongst them Burnside and Dollar (2000) and Dalgaard et al.
(2004). He concludes that all outcomes of the analysed studies are characterised by
fragility and that aid "is probably not a fundamentally decisive factor for development"
(ibid.: 275). One of the most prominent publications of the past decade, as many studies
highlight (cf. Clemens et al. 2012: 595), can also be found in this category: Rajan and
Subramanian (2008) analyse the causal relation between aid and growth based on both
cross-sectional and panel data analyses in a comprehensive way. They test for several
assumptions, such as the decisive role of good policies and the geographical location,
as well as the timing of the impact of aid; and conclude that aid over all their findings
has no significant positive effect on growth (ibid.: 660).
Opposed to the findings of the second cluster, the third strand of the recent literature
reveals an overall positive impact of aid on growth. An early influential work is Hansen
and Tarp (2001), who also address the insight of Burnside and Dollar (2000) that aid
would only work in good policy environments. They are the first within the aid literature
to apply a GMM estimator. This procedure has attracted particular attention within the
aid literature and is adopted by many subsequent studies, such as the aforementioned
Rajan and Subramanian (2008: 658-660).
3
Hansen and Tarp (2001: 552) retain the
strategy of instrumenting for policy, but modify the original set of instruments and
include lagged values of the aid regressors for modelling the assumption of non-linear
returns of aid. Accounting for both original least squares and GMM-estimations, Hansen
and Tarp (2001: 563) conclude that aid has a positive and significant effect on growth
via investment.
Gomanee et al. (2005A: 1068) arrive at the same result in a sample of 25 countries in
Sub-Saharan Africa (SSA). Several publications of the past years can also be classified
as studies of the third strand. Arndt et al. (2010: 19-21), as well as Clemens et al. (2012:
608) draw on the original specification of Rajan and Subramanian (2008) demonstrate
a modest but general positive effect of aid on growth. Both studies have in common
that they turn away from GMM-estimations, although this method has been recognised
as a sound practice in the aid literature since the work of Hansen and Tarp (2001).
The robustness check, carried out in section 6.3, revisits this recent doubt about the
applicability of GMM-estimators. Finally, Brückner (2013: 131-135) also achieves a
significantly positive effect of aid. Remarkable for his approach is that he tackles the
endogeneity problem by explicitly estimating the effect of an increase in gross domestic
product (GDP) per capita growth in recipient countries on the amount of foreign aid in
a first step.
3
Chapter 6 contains detailed information on the GMM approach and its benefits, as well as its limitations.
9
2.2 Looking beyond the eect of growth
The investigation of the impact of aid on economic growth in developing countries may
be considered the classical strand of the aid effectiveness literature. As indicated in the
introduction, however, there are several reasons why the growth effect should not be
the only criteria to use for measuring the effectiveness of aid. Several researches of the
past two decades shift their focus towards investigating the effect of aid on different
indicators of human development. These studies include key indicators in the areas of
health and education, as well as poverty indices. In the following, this section analyses
research in this rather novel field with a focus on the underlying theoretical assumptions
for turning towards a focus on social indicators.
A fundamental objective of investigating the effectiveness of aid regarding its impact
on social indicators is to evaluate whether it contributes to achieving the goals that
have jointly been defined by the United Nations (UN) member countries. At the UN
Millennium Summit in 2000, both developing and developed countries met for the first
time to establish a common target catalogue for promoting international development,
labelled Millennium Development Goals. These targets include improvements in the
fields of global health, education, poverty reduction, equality, as well as peace and
freedom promotion with an objective horizon of 15 years (cf. UNDP 2003: 31). After
the expiration of the 15 years planning horizon, the common goals were redefined in
2016 and laid down in the 17 Sustainable Development Goals of the UN (cf. DESA:
2016).
4
Because aid is expected to be an essential instrument for achieving these
goals, several studies devote to explicitly analysing the correlation between aid and the
achievement of MDGs, e.g. Dreher et al. (2008: 292) or Masud and Yontcheva (2005:
3).
Apart from the rather self-evident objective of assessing the ability of aid to contribute
to commonly defined goals, there are more reasons why indicators for social welfare are
suitable for measuring aid effectiveness. First, several studies point out that aid targeted
towards improvements in social areas may only have an impact on growth in the very
long run. Arndt et al. (2015: 9) demonstrate this time-lagged growth effect of aid based
on the example of the education field. They consider only those kinds of aid which are
directed at improving educational quality and show that higher school attendance rates,
caused by these aid flows, may only have an observable influence on growth after a
considerable share of beneficiaries has passed through the education system. Boone
(1996: 293) already stresses that infant mortality, as a key indicator for health, would
respond quickly to improved conditions. In line with this, Dreher et al. (2008) argue
that social indicators would be "more specific outcome variables than growth" (292).
A further line of arguments emphasises the high explanatory power of social indicators
4
Annex A shows provides an overview of the agendas of both MDGs and SDGs.
10
in measuring welfare gains of the poor. Gomanee et al. (2005B: 300) point out that
increases in aggregate economic growth do not necessarily reflect better conditions
of the poor; which is, however, a main target of aid. For this reason, they attempt to
capture a broader measure of total welfare benefits by focusing on improvements in
both infant mortality and the Human Development Indicator (HDI). Chong et al. (2009:
60), as well as Alvi and Senbeta (2012: 955) share the same position. In contrast to their
predecessors, however, they both rely on poverty headcount and poverty gap indices.
They argue that this procedure gives indication on income distribution and equality,
representing additional important factors of development besides a countries' average
economic growth (ibid.: 957).
Corresponding to the overall conclusion of the classical aid-growth literature, the
findings of this strand of the aid effectiveness research are also diverse. However, a
majority of the studies report positive effects of aid. Recent findings, furthermore,
show a clear trend towards more optimistic findings. Boone (1996: 312-313) is the
first to incorporate social indicators into his estimations with the purpose of measuring
improvements in the living conditions of the poor. For this purpose, he chooses infant
mortality, life expectancy, as well as primary schooling. He finds out that aid does not
significantly influence neither of the variables. As mentioned in the previous section,
Boone rather observes a higher consumption rate correlating with aid payments and
concludes that these results "are consistent with a model where politicians maximize
welfare of a wealthy elite" (ibid.: 322).
In line with this finding, Chong et al. (2009: 79) are not able to detect a significant
impact of aid on their measures for poverty. This negative overall picture of the relation
between aid and social indicators, however, is only supported in a small number of
studies. Gomanee et al. (2005B: 305), as well as Masud and Yontcheva (2005: 13)
find that aid reduces infant mortality. While Gomanee et al. (2005B, 302) use total
aggregated aid flows, Masud and Yontcheva (2005: 9) distinguish between bilateral aid
(BA) and aid from non-governmental organisations (NGOs) and demonstrate that only
the latter has a significant effect.
Particularly in recent years, a predominantly positive perception of aid towards im-
proving social welfare has become apparent. Dreher et al. (2008: 299), for instance,
show that aid specifically assigned to the education sector contributes significantly to
higher school enrolment rates. In a similar approach, Mishra and Newhouse (2009: 865)
consider aid in the health sector and find that this type of aid contributes to alleviating
infant mortality. The two latter mentioned investigations apply a separation of aid flows
by their purpose. Because their target is to investigate only the assistance for education
and health respectively, they separate these aid types from the total aid numbers. Section
3.2 discusses the approach of disaggregating aid according to assignment in more detail.
11
Even without separating aid, Alvi and Senbeta (2012: 965) determine a negative and
significant impact of total aid flows on both poverty gap and poverty rate. Finally,
Arndt et al. (2015: 10-13) apply a two-step analysis with intermediate outcomes of
aid, amongst them measures for health and education, that contribute accumulatively to
final outcomes, represented by GDP growth and poverty indices. They conclude that
aid has an average positive long-run effect on the final outcomes by stimulating the
intermediate outcomes, such as better health and education conditions (ibid.: 15).
2.3 Evidence from donor investigations
So far, one major conclusion can be drawn from the literature analysis: A larger share of
the research on aid effectiveness fails to find a significantly positive impact of aggregated
aid flows (cf. Rajan and Subramanian 2008 and 2011, Burnside and Dollar 2000 or
Easterly et al. 2004). For this reason, a major current research goal in this field is to
gain insight into the reasons for the apparent failure of total aggregated aid. Section 2.1
already describes one empirical procedure for this purpose; by instrumenting for certain
characteristics of the developing countries, such as their institutional quality or climatic
circumstances, scholars try to find out under which circumstances aid generates positive
effects and when it appears to not have any significant impact. Studies of this type have
already had a strong influence on policy, such as the shift of aid allocation of major
agencies towards countries with a better policy environment (cf. Easterly et al. 2004:
774).
A further possibility of understanding why overall aid apparently does not achieve its
goals is to look at the single development assistance flows separately, i.e. disaggregating
aid numbers. The underlying assumption behind this approach is that different aid, or
aid flows to different countries, can vary in their effectiveness. The disaggregation,
again, can be done in different ways. The two major differences of these approaches are
the following: One way is to consider the underlying objective behind the different aid
flows and, consequently, to distinguish between the different purposes of aid, which
are defined by the donor. Many studies apply such a procedure, amongst them Headey
(2008: 169) and Clemens et al. (2012: 594), who subtract the share of humanitarian aid
from total ODA with the purpose of only considering the types of aid that are targeted at
increasing economic growth, or Dreher et al. (2008: 300), who find a positive impact of
aid and education indicators while considering only those aid flows that were assigned
to the education sector. This thesis, however, does not apply such a procedure. Section
4.2 provides the argumentation behind this choice.
Beside this kind of disaggregation, there is a second established way of breaking down
aggregated aid: Various studies subdivide aid flows according to the way they are
12
allocated to recipient countries. This type of studies is often referred to as the aid
allocation literature (cf. Harrigan and Wang 2011: 1282). One objective of several
of these investigations is to determine a pattern of aid allocation that is most effective
regarding the aggregated increase of welfare in developing countries. Another major
target of this kind of research is to determine factors that prove to be decisive for the
choice of the individual donor's allocation. Such factors, on the one hand, can be
derived at the recipient country level - humanitarian needs or the degree of poverty are
examples for this. But they can also be investigated from the donor country perspective
and include factors such as political or commercial interests. Finally, these approaches
are expanded by several studies in order to compare the aid allocation of different
donors. These studies argue that the patterns of aid allocation vary significantly between
different donors. Some of them conclude that inadequate aid allocations, presumably
caused by personal donor motives, are a major cause for the ineffectiveness of total
aggregated aid. The following section depicts this strand of the literature and their
implications for this thesis in more detail, with a focus on those studies that devote to
determining differences between different donors.
The conclusions of the aid allocation literature, however, do not provide information on
the eventual effects of different patterns of aid flows. Or put differently: They provide
insights about differences in aid allocations of different donors (qualitatively), but do
not quantify these. Only a few studies so far attempt a quantification of aid impacts
separated by donors. Their measurements are mostly based on implications of the aid
allocation literature. A further section depicts these approaches and their results.
2.3.1 The aid allocation literature: Deriving donor interests
To begin with, this section outlines the main approaches and findings of the aid allocation
literature. Implications derived from this strand of research serve as the main theoretical
foundation of this thesis. Similar to the aid-growth literature depicted in section 2.1,
there are numerous studies contributing to this research field with a history that goes
back to the 1970s.
5
McKinlay and Little (1977) already elaborate on explaining the allocation of official
bilateral aid by the example of the US development assistance. They develop five models
for each possible type of donor interest and analyse, based on a cross-sectional analysis
of the period 1960-1970, which of the models correlates most with the allocation of US
aid over this period (ibid.: 68-72). The interests represented by the five models include
fostering development, political stability and democracy in developing countries, but
also (own) economical, security and power-political interests of the US. The authors find
5
For further reading: Harrigan and Wang (2011: 1282-1283) provide a detailed review on the aid
allocation literature, including early research.
13
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