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Contents

List of Tables, Figures and Boxes vi

List of Abbreviations viii

Acknowledgements x

Notes on the Contributors xi

Foreword xiv

1 Development Aid: Expectations, Effectiveness and Allocation 1

George Mavrotas and Mark McGillivray

2 Decentralizing Aid with Interested Parties 15

Gil S. Epstein and Ira N. Gang

3 Blind Spots on the Map of Aid Allocations: Concentration

and Complementarity of International NGO Aid 26

Dirk-Jan Koch

4 On the Volatility and Unpredictability of Aid 58

David Fielding and George Mavrotas

5 Aid Project Proliferation and Absorptive Capacity 79David Roodman

6 Aid Allocation and Aid Effectiveness: An Empirical Analysis 114

Alessia Isopi and George Mavrotas

7 The Fiscal Effects of Aid in Developing Countries:

A Comparative Dynamic Analysis 158

Tim Lloyd, Mark McGillivray, Oliver Morrissey andMaxwell Opoku-Afari

8 Development Effectiveness: An Evaluation Perspective 180

Robert Picciotto

9 Evaluating Aid Impact 211

Howard White

Index 233

v

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1Development Aid: Expectations,Effectiveness and AllocationGeorge Mavrotas and Mark McGillivray

Introduction

The international community has come to expect much of foreign

development aid in recent years, especially since the adoption of the

Millennium Development Goals (MDGs) at the UN Millennium Summit

in September 2000. The MDGs aim inter alia by 2015, to halve the 1990figures for numbers of people living in extreme income poverty, achieve

universal primary schooling, and reduce by two-thirds the 1990 mortal-

ity rate among children worldwide. A key component of the strategy to

achieve, or at least work towards, the MDGs is a substantial scaling-up of

aid flows by OECD donor nations (United Nations Millennium Project,

2005). This strategy is clearly evident in aid statistics on global Official

Development Assistance (ODA) from members the Development Assis-tance Committee of the OECD (see Figure 1.1). The level of DAC ODA

rose from US$69 billion in 2003 to US$107 billion in 2005, the highest

annual level of ODA on record. While the level of ODA fell slightly to

US$104 billion in 2006, it is expected to rise to US$130 billion in 2010,

and to somewhere between US$160 and US$170 billion by 2015 (OECD,

2007a, 2007b).

This chapter serves as an introduction to Development Aid: A Fresh

Look and the chapters that follow. It consists of two further sections.

The first provides brief surveys of the two kinds of literature to which

the book principally attempts to contribute: those on aid effectiveness

at country level; and on those on the inter-country allocation of aid

by recipient. The second provides details of the remaining chapters in

this book.

1

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2 Expectations, Effectiveness and Allocation

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Netdisbursements

($USmillions,

2005prices)

Actual Predicted

Figure 1.1 Total ODA from DAC member countries, 19902010Source: OECD (2007a, 2007b).

Aid effectiveness and allocation: brief surveys

Aid effectiveness

An obvious premise of strategy to accelerate progress towards the MDGs is

that aid is, or can reasonably be made, effective in promoting outcomes

such as reduced poverty, increased schooling and improved health. Isthis premise valid? There are a number of ways in which this question

can be examined. One is to look at the research literature on aid effective-

ness and allocation. A question that has dominated the aid effectiveness

literature is the relationship between aid and per capita national income

growth in recipient countries. The key questions are whether growth

would be lower in the absence of aid, and if so, by how much? This is

of clear relevance to the MDGs. While growth alone is clearly not suffi-cient to achieve the MDGs, it is agreed reasonably widely that increased

growth is necessary for this achievement. Therefore, it is instructive to

examine initially the aid-growth literature, before turning to other areas

of aid effectiveness research.

For many decades, the research literature on the country-level impacts

of aid sent mixed messages as to whether aid was effective in promoting

economic growth. Some empirical studies found evidence of a positive

association between aid and recipient country growth; other empirical

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George Mavrotas and Mark McGillivray 3

studies either failed to find any association, or if they did, found that

it was negative. The second group of studies had support from non-

empirical research, with many influential writers providing damning

critiques of aid, from both left- and right-wing perspectives. The lack

of a consensus regarding the country-level impact of aid combined with

strong evidence that aid projects were in general effective in attaining

their intended outcomes, was described as the micromacro paradox of

aid (Mosley, 1986). This paradox was widely accepted in the aid policy

and research circles.

The late 1990s saw a fundamental change in the literature on aid and

growth, however. Beginning with the publication of the seminal andextremely influential study by Burnside and Dollar (1997), a new stream

of empirical studies emerged. They use better cross-country empirical

methods (in particular, those that involve pooling of time series and

cross-section data), are based on more informative theories about the

determinants of growth, and use better data. These studies provide a rea-

sonably clear and consistent message that growth would on average be

lower in the absence of aid. This has proved to be a quite robust research

finding drawn by the clear majority of an increasingly large number of

empirical studies of aid and growth conducted since Burnside and Dollar

(1997). The consistency of this finding across studies is evident from an

objective reading of a number of aid-growth literature surveys (Hansen

and Tarp, 2000; Morrissey, 2001; Beynon, 2002; McGillivray, 2003a;

Clemens et al., 2004, Addison et al., 2005; McGillivray et al., 2006). This

is not to imply that there are some who still claim that aid does not

contribute to growth (see, for example, Easterly, 2007; Rajan and Sub-ramanian, 2008); simply that any objective reading of the aid-growth

literature from the late 1990s onwards tells us that, in the absence of

aid, growth in recipient countries would have been lower over recent

decades. The macromicro paradox of aid would therefore appear to be

dead and buried.

The next question to ask is: if growth would have been lower in the

absence of aid, how much lower would it have been? This question, sur-prisingly, has not been addressed explicitly in much of the literature,

which has confined itself simply to the detection of causal relationships,

rather then the extent or numerical size of their impact. But it is possible

to derive this information mathematically; using the results of some of

the most econometrically and theoretically robust post-late-1990s stud-

ies (Hansen and Tarp 2000, 2001; Dalgaard and Hansen, 2001; Dalgaard

et al., 2004; Clemens et al., 2004). This suggests that real per capita

economic growth would be around 1 per cent lower in the absence of

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aid. There are results reported in the literature that suggest growth gains

that are a little lower than this, and some suggest one or slightly more

percentage points higher than this, but we consider that one percentage

point is a reasonable, representative approximation.

What does an approximately one percentage point contribution of aid

to growth mean with regard to the role of aid in achieving or promoting

progress towards the MDGs, in particular the goal of halving by 2015 the

proportion of the worlds population living in extreme income poverty?

Achieving the MDG income poverty goal involves reducing the number

of people living in absolute poverty by a little over 60 billion per year

between 2004 and 2015 (United Nations, 2007). Given these numbers,the answer to the above question is that, while aid will certainly play a

role in promoting progress towards the MDGs, it will be only partial if

assessed solely on the basis of its contribution to growth. Even the most

favourable estimates of the impact of growth on income poverty will see

aid having a comparatively small impact on growth-induced progress

towards the MDGs.1

Aid can, of course, contribute towards poverty reduction or, more gen-

erally, wellbeing enhancement more directly, via channels other than

growth. Gomanee et al. (2005) look at aid and pro-poor expenditure,

finding that aid is associated with increases in such expenditure, and, in

turn, improvements in the achievement of overall wellbeing. Kosack

(2003) found that, contingent on the extent of democracy in recipi-

ent countries, aid was associated positively with the achievement of a

level of wellbeing across countries, as measured by the Human Develop-

ment Index. A related literature, one that has grown rapidly in recentyears, looks at the impact of aid on various categories of public expen-

diture and revenue. This is an important area of research. Most aid is

allocated by donors to the public sector of recipient countries. How

this sector uses aid will almost certainly mediate its broader impacts on

growth, poverty reduction and other developmental outcomes. More-

over, included in expenditure categories examined by this research are

those that support the provision of health and education services impor-tant to MDG achievement. These studies are surveyed in McGillivray and

Morrissey (2004). More recent studies include Mavrotas (2002, 2005),

McGillivray and Ouattara (2005) and Mavrotas and Ouattara (2006,

2007). The evidence emerging from these studies is not as unambigu-

ous as that emerging from the aid-growth literature, but it is often the

case that aid results in higher public expenditure than would otherwise

have prevailed, although it can also result in decreases in tax revenue

and increases in public sector debt.

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The demise of the macromicro paradox and some agreement in

other areas of aid research does not imply that there are no remaining

controversies or gaps in knowledge regarding aid effectiveness within

research circles that aid works in all countries and at all levels. A repeated

finding of the recent aid-growth literature is that there is an inverted

U-shaped relationship between aid and growth. It is not beyond the

bounds of imagination to infer that the levels of inflows to some coun-

tries are such that aid might have in fact reduced growth within them.

This is obviously a huge issue in the context of substantially larger

global aid budgets and progress towards the MDGs. There are also

widespread concerns about the impact of aid in what the donor com-munity has termed fragile states those judged to have especially bad

policies and poorly performing institutions (McGillivray, 2005). A dis-

puted finding in the literature, which to date remains unsettled, is

that the impact of aid on growth is contingent on the policy regimes

of recipient countries. Some studies conclude that policies do matter

for aid effectiveness, including those of Burnside and Dollar (1997,

2000, 2004), but more conclude otherwise. Some studies point to the

importance of alternative contingencies (Hansen and Tarp 2000, 2001;

Dalgaard and Hansen, 2001; Guillaumont and Chauvet, 2001; Chauvet

and Guillaumont, 2002; Dalgaard et al., 2004). These include political

stability and structural vulnerability (Guillaumont and Chauvet, 2001;

Chauvet and Guillaumont, 2002). More generally, a great failing of the

aid-growth literature, which has relied almost entirely on the estimates

of cross-country growth modelling, is that it has yet to reach a con-

sensus on this issue, which is clearly of great relevance to policy. Normight it ever be able to reach this consensus if the Roodman method-

ological warnings regarding the limits of cross-country econometrics are

taken into account (Roodman, 2007). If donors are to make aid more

effective, they need to know what its effectiveness is contingent upon.

Indeed, there is a case for turning away from the literature as currently

defined unless there are signs that this controversy cannot be settled

reasonably quickly. This involves two acceptances. The first is that aiddoes result in higher per capita national income growth than would oth-

erwise be the case. As Riddell (2007) argues convincingly, this renders

further cross-country aid-growth as it is currently conducted unneces-

sary, as it simply reaffirms what we already know.2 The second is that

cross-country growth modelling is inappropriate for providing robust

information on what makes aid effective, be it in terms of growth or other

growth-driven outcomes against which the effectiveness of aid can be

judged.

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Aid allocation

An additional premise of the strategy to achieve the MDGs is that donors

are in fact motived by developmental considerations, such as povertyreduction. Put differently, it is assumed that donors strive consciously to

achieve development outcomes in their aid programmes. An empirical

literature that dates back to the 1960s has sought to address this issue by

seeking to analyse the determinants of allocation of aid among recipient

countries. Put differently, this literature attempt to explain the observed

inter-recipient allocation of aid. Most explanatory aid allocation studies

posit that donors pursue humanitarian, commercial and political objec-

tives in their aid programmes. The humanitarian or altruistic motiveinvolves the promotion of development and alleviation of need. The

aid allocation literature hypothesizes that, if donors are genuinely moti-

vated by humanitarian concerns, they will allocate aid among recipients

on the basis of relative need, allocating most aid to countries with low

levels of development, high levels of poverty, and so on. The commercial

and political motives relate to donor self-interest. Pursing commercial

motives involves such behaviour as allocating funding in such a waythat it promotes trade and investment opportunities. More aid than

would otherwise be the case is allocated to countries that buy, or are

likely to buy, relatively large amounts of exports from the donor in ques-

tion, should that donor be motivated by commercial interests. The same

would apply to countries in which the donor has investment interests.

Allocating aid according to political motives involves such actions as

giving more aid to countries with which the donor has close political

ties or interests, be it a result of geographical proximity, historical rela-

tions or other reasons. It might also involve penalizing a country for a

particular course of action to which the donor objects, or vice versa.

Traditional aid allocation research tended to reject humanitarianism as

a motive for official aid. This was based on the finding, reported by some

highly influential studies, that the inter-recipient allocation of aid, espe-

cially that from bilateral agencies, was consistent with relative recipient

need. McKinley and Little (1979: 243), for example, concluded that thereare no grounds for asserting that humanitarian criteria have any signif-

icant direct influence on aid allocation. Similarly, Maizels and Nissanke

(1984: 891) concluded that bilateral aid allocations are made solely

in support of donors perceived foreign economic, political and security

interests and not, therefore, on the basis of relative need. While these

studies have been questioned on methodological grounds (McGillivray,

2003a, 2003b), simple descriptive statistics bear this out. In 1995, Israels

income per capita was twenty-seven times that of Sierra Leone, and

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the life expectancy of its citizens was forty-three years longer. During

the period 196995, Sierra Leone received an annual average of US$74

million in net disbursements of ODA from all sources, while over the

same period Israel received an annual average of US$937 million

roughly thirteen times the amount allocated to Sierra Leone, or twelve

times if these amounts are measured using the respective population sizes

of each country (UNDP, 1998; OECD, 2002).

More recent research has generally found that recipient needs do influ-

ence inter-country aid allocation (Alesina and Dollar, 2000; Alesina and

Weder, 2002; Berthlemy and Tichit, 2004; Berthlemy, 2006). This is

potentially good news from an MDG perspective, although these studiesalso find that self-interest remains a significant determinant. A theme of

recent aid allocation studies has been whether governance is important

to aid allocation. The question under consideration is whether donors

reward recipients that have good governance records, and penalize those

with bad records. Good governance is defined using various criteria, such

as official respect for political and civil rights, the absence of official cor-

ruption, the promotion of democratic principles, or the performance of

public institutions. It can also be defined in terms of the quality of poli-

cies. This brings us back to the research by Burnside and Dollar, cited

above. As mentioned earlier, this research finds that the impact of aid on

growth is contingent on the policy regimes of recipient countries. More

precisely, the finding is that, the better are these policies, the larger is the

impact. It follows logically that, if donors want to maximize the global

effectiveness of aid, in terms not only of its impact on growth but also

in terms of growth-driven reductions in income poverty, they shouldallocate it among countries on the basis of the quality of policy regimes.

Collier and Dollar (2001, 2002) originally described such an allocation

strategy as aid selectivity.

Aid allocation research has provided mixed results regarding the extent

to which good governance, variously defined, has been relevant to

inter-country aid allocation. This generally reflects the large diversity

among donors. Svensson (2000) found that political and civil rightslead to higher total aid flows from Canada, Denmark, Norway and

Sweden the so-called like-minded countries that traditionally put

an emphasis on democracy and human rights in their development

assistance and the UK. Alesina and Dollar (2000) came to a similar

conclusion for the amount of aid allocated by Australia, Canada, Ger-

many, Japan, the Netherlands, the Nordic countries, the UK and the

US, but not for Austria, Belgium, France and Italy. Burnside and Dollar

(2000) found that allocation decisions by all bilateral donors were not

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consistent with a selectivity strategy, but that multilateral aid allocation

decisions were.

Volume contents

Development Aid: A Fresh Look consists of nine chapters. Chapters 2

and 3 look at aid allocation issues; Chapters 46 look at the interface

between aid allocation and aid effectiveness; and Chapters 79 look

purely at recipient country-level aid effectiveness issues. Details of each

follow.

Chapter 2, a theoretical piece by Gil Epstein and Ira Gang, is enti-tled Decentralizing Aid with Interested Parties. The chapter responds to

the observation that donors have moved towards allocating aid among

recipient countries on the basis of good governance. This is broadly

consistent with the donor communitys espousal of the findings of the

influential work of Burnside and Dollar, discussed above. Epstein and

Gang define decentralizing aid as allocating these flows only to countries

with good governance. Chapter 2 analyses the decentralization of aid

decision-making in a theoretical rent-seeking framework. It models the

aid allocation decision where the donor government has announced that

good governance is the criterion for receiving aid. Potential recipients

must therefore compete for aid funds. The chapter shows that the struc-

ture of the competition is important to the donor in terms of achieving

good governance, and to the recipients in terms of what they will receive.

It also investigates whether, under certain reasonable conditions, aid

procedures will lead to the development of a poverty trap.The literature on aid effectiveness, in particular that having an empir-

ical orientation, focuses overwhelmingly on aid from official agencies.

Aid from non-government organizations (NGOs) is examined relatively

rarely. Chapter 3, entitled Blind Spots on the Map of Aid Allocations:

Concentration and Complementarity of International NGO Aid, by

Dirk-Jan Koch, addresses this imbalance. Using a new dataset and Lorenz

curves, this chapter shows that NGOs are very active in some countriesbut not in others. Clustering of NGO activity takes place in UN-labelled

high priority countries, but ample room for improved targeting exists.

Aid concentration curves provide insights as to whether NGOs tar-

get the same countries as bilateral donors. The chapter concludes that

they do, and are thus acting as complements. The drawback of this

complementary approach is that it reinforces the donor darling/donor

orphan divide. The chapter ends with some research suggestions and

preliminary policy implications.

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There have in recent years been growing concerns over year-on-year

volatility in the amount of aid allocated to recipient countries. Such

volatility makes the management of aid inflows more difficult and can

offset the potentially positive impact of these inflows, especially if year-

on-year changes are not anticipated by recipients. Chapter 4, by David

Fielding and George Mavrotas and entitled On the Volatility and Unpre-

dictability of Aid, explores this issue. The chapter examines aid volatility,

using data for sixty-six aid recipients over the period 19732002. It

improves upon earlier work in this important area by disaggregating

total aid inflows into sector and programme aid, and in this way it

avoids focusing on a single aggregate, unlike most previous studies onaid volatility. Chapter 4 finds that recipient country institutional quality

affects the stability of sector aid but not that of programme assistance.

Macroeconomic stability affects the stability of both kinds of aid, as does

the extent to which a country relies on a small number of individual

donors.

Much public discussion about foreign aid has focused on whether (and

how) to increase its quantity. But recently, aid quality the efficiency of

the aid allocation or delivery process has come to the fore. Chapter 5,

by David Roodman, entitled Aid Project Proliferation and Absorptive

Capacity, focuses on one process problem, namely the proliferation of

aid projects and the associated administrative burden for recipients. It

models aid delivery as a set of production activities (projects) with two

inputs the donors aid and a recipient-side resource; and two outputs

development and throughput, which represents the private benefits

of implementing projects, from kickbacks to career rewards for disburs-ment. The donors allocation of aid across projects is for the purposes

of the chapter taken as exogenous, while the recipients allocation of

its resource is modelled and subject to a budget constraint. Unless the

recipient cares purely about development, an aid increase can reduce

development in some circumstances. Sunk costs, representing for the

recipient the administrative burden of donor meetings and reports, are

introduced. Using data on the distribution of projects by size and coun-try, Chapter 5 reports results of simulations of aid increases run in

order to examine how the project distribution evolves, how the recip-

ients resource allocation responds, and how this affects development

if the recipient is not a pure development optimizer. A threshold is

revealed beyond which marginal aid effectiveness drops sharply. It occurs

when development maximization calls for the recipient to withdraw

from some donor-backed projects, but the recipient does not, for the

sake of throughput. Roodman argues that donors can push back this

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threshold by moving to larger projects if there are scale economies in aid

projects.

Chapter 6, by Alessia Isopi and George Mavrotas and entitled Aid

Allocation and Aid Effectiveness, looks at the selectivity issue discussed

above. It does so by augmenting an explanatory model of aid alloca-

tion with a variable measuring past developmental outcomes from aid.

Past developmental outcomes, in turn, serve as the measure of how

effectively the recipient in question has been able to use aid inflows.

Chapter 6 therefore seeks to establish the extent to which this effective-

ness determines the allocation of aid among recipients after controlling

for donor self-interest and other altruistic or developmental concerns.The chapter analyses data covering twenty aid donor countries and 176

recipients over the period 19802003. It finds that while both altruis-

tic and selfish donor motives seem to motivate aid allocation for most

donors over the two periods under examination, a small group of donors

do seem to have adopted a selectivity approach to aid allocation since

the late 1990s.

Chapter 7, entitled The Fiscal Effects of Aid in Developing Countries:

A Comparative Dynamic Analysis and authored by Tim Lloyd,

Mark McGillivray, Oliver Morrissey and Maxwell Opoku-Afari, looks

at the impact of aid on fiscal aggregates in recipient countries, thus

attempting to contribute to the literature discussed above. The principal

innovation in this chapter is to conduct a comparative study of twenty-

one countries, applying the same econometric method to each. Vector

autoregressive (VAR) methods are used to estimate the effect of aid on

fiscal aggregates, especially whether aid is endogenous (in the long run)or exogenous (short run only) to the fiscal relationship. Results suggest

that, for low-income countries, aid is generally significant in the fiscal

relationship and tends to be associated with lower tax effort. In middle-

income countries, while aid is part of the long-run fiscal relationship in

most cases, often it only has a short-run effect and there is no consis-

tent association with tax effort. In general, the results suggest that aid

has causal fiscal effects; that is, is part of the long run, although preciseeffects are country-specific.

Much analysis of aid impact has been at the macro level and has

relied heavily on cross-country regressions focusing on linkages between

aid and growth. The principal limitation of these studies, as noted

above, is that they do not to inform more intricate aspects of aid pol-

icy and management. What is required to do that is more detailed

analysis of aids impact on the ground, at the level of individual coun-

tries. This is the focus of Chapter 8, by Robert Picciotto, and entitled

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Development Effectiveness at the Country Level. The chapter argues

that the mix of qualitative and quantitative methods fashioned by inde-

pendent evaluators constitutes a serviceable approach to the assessment

of aid effectiveness, at both project and country level. The chapter sug-

gests that, despite the risks involved, aid does the most good when it

privileges the weakest and poorest economies, and those most vulnera-

ble to shocks. It further argues that development operations should be (i)

selected to fit within coherent country assistance strategies; (ii) aligned

with the priorities of the country; and (iii) co-ordinated with other

policies and the actions of partners. The final proposition offered by

Chapter 8 is that professionally administered aid works, but that it wouldwork even better in concert with reforms of rich countries policies geared

to levelling the playing field of the global market and to peace-building

and human security in the zones of turmoil of the developing world.

The focus on country-level analyses of aid impact is continued in

Chapter 9, entitled Evaluating Aid Impact and written by Howard

White, the chapter outlines developments in field analyses of the

impact of aid on outcomes such as infant mortality, gender dispar-

ity in schooling, and income-poverty. It argues that, while technical

rigour is important, it is at least as important not to lose sight of policy

relevance, which is achieved by avoiding black box approaches. The

chapter then discusses basic concepts and principles in impact evalua-

tion, and approaches to measuring impact. This discussion draws on the

experiences of a number of official agencies in evaluating the impact of

aid. It concludes by arguing that, properly done, impact evaluation not

only provides evidence as to whether aid works, but also how to make itwork better.

The topics covered in this book address important issues relating to

development aid research, policy and practice. They are useful in their

own right, but beyond that it is hoped that they will stimulate further

discussion aimed at better and more effective aid that contributes more

substantially to the fight against poverty, and results in a fairer, more

equitable and more stable world. This is, of course, fully consistent withthe very essence of the MDGs.

Notes

1. Collier and Dollar (2001, 2002) look at the inter-country allocation of aidthat maximizes global poverty reduction, using a growthpoverty reduction

elasticity of minus two.

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2. It should, however, be emphasized that Riddells insights apply to research ongrowth and aggregate aid flows as there remain substantial gaps in knowledgeon the impact of different aid modalities. Mavrotas and Nunnenkamp (2007)

provide a recent review of this issue.

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Mavrotas, G. and B. Ouattara (2006) Aid Disaggregation and the Public Sectorin Aid-recipient Economies: Some Evidence from Cte dIvoire, Review of

Development Economics, 10: 43451.

Mavrotas, G. and B. Ouattara (2007) Aid Modalities and Budgetary Response:Panel Data Evidence, Review of World Economics, 143 (4): 72041.

McGillivray, M. (2003a) Aid Effectiveness and Selectivity: Integrating MultipleObjectives in Aid Allocations, DAC Journal, 4 (3): 2336.

McGillivray, M. (2003b) Modelling Foreign Aid Allocation: Issues, Approachesand Results, Journal of Economic Development, 28 (1): 17188.

McGillivray, M. (2005) Aid Allocation and Fragile States, Background paper pre-pared for the Senior Level Forum on Development Effectiveness in Fragile States,1314 January, Lancaster House, London.

McGillivray, M. and O. Morrissey, (2004) Fiscal Effects of Aid, in T. Addison andA. Roe (eds), Fiscal Policy for Development: Poverty, Reconstruction and Growth,Basingtoke: Palgrave Macmillan for UNU-WIDER.

McGillivray, M. and B. Ouattara (2005) Aid, Debt Burden and Government FiscalBehaviour in Cte dIvoire, Journal of African Economies, 14: 24769.

McGillivray, M., S. Feeny, N. Hermes and R. Lensink (2006) Controversies overthe Impact of Development Aid: It Works, It Doesnt, It Might, but thatDepends , Journal of International Development, 18 (7): 103150.

McKinley, R. D. and R. Little (1979) The US Aid Relationship: A Test of the

Recipient Need and Donor Interest Models, Political Studies, 27 (2): 23650.Morrissey, O. (2001) Does Aid Increase Growth?, Progress in Development Studies,

1 (1): 3750.Mosley, P. (1986) Aid-Effectiveness: The MicroMacro Paradox, IDS Bulletin, 17:

21425.OECD (2002) International Development Statistics Online, Paris: OECD.OECD (2007a) OECD Journal on Development: OECD DAC Development Co-operation

Report 2006, Paris: OECD.OECD (2007b) Press Release: Development Aid from OECD Countries Fell 5.1%

in 2006, Paris: OECD.

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Rajan, R. and A. Subramanian (2008) Aid and Growth: What Does the Cross-Country Evidence Really Show?,Review of Economics and Statistics, forthcoming.

Riddell, R. (2007) Does Foreign Aid Really Work?, Oxford: Oxford University Press.

Roodman, D. (2007) Through the Looking-Glass, and What OLS Found There:On Growth, Foreign Aid and Reverse Causality, Centre for Global DevelopmentWorking Paper 137, Centre for Global Development, Washington DC.

Svensson, J. (2000) Why Conditional Aid Does Not Work and What Can Be DoneAbout It?, Journal of Development Economics, 70 (2): 381402.

United Nations (2007) The Millennium Development Goals Report 2007, New York:United Nations.

United Nations Millennium Project (2005) Investing in Development: A PracticalPlan for Achieving the Millennium Development Goals, New York: United Nations

Development Programme.UNDP (United Nations Development Programme) (1998) Human Development

Report 1998, New York: Oxford University Press.White, H. (1992) The Macroeconomic Impact of Development Aid: A Critical

Survey, Journal of Development Studies, 28 (2): 163240.

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Index

Key: bold=extended discussion; b=box; f= figure; n=note; t= table.

absorptive capacity 9, 58, 79113,189

accountability 40, 53(n11), 106,181, 185, 190b, 193, 208(n30)

accounting identity 1623,177(n4)

Acharya, A., et al. (2006) 83, 112

Lima, A. de 112

Moore, M. 112

ActionAid International xi, 190b

Addison, T. 76n

Addison, T., et al. (2005) 3, 12

Mavrotas, G. 12McGillivray, M. 12

Addison, T., et al. (2005a, 2005b)76(n2), 77

Mavrotas, G. 77

McGillivray, M. 77

administrative burden 9

administrative capacity 199

administrative costs 82, 190b

Africa 356, 37t, 61t, 713, 82, 106,158, 182, 197, 202

African Development Bank 69t,207(n22)

African Development Fund 69t

agency theory 30

agents: types (Isopi and Mavrotas)116

agglomeration economies (Bielefeld

and Murdoch) 29aggregation bias 63

agriculture 80, 201, 206(n10), 217,224, 225

Ahmed, A. 160, 179

aid

and arms transfers 124t

benefit derived 116

bilateral 312, 3840, 42, 43f, 47,

54(n14), 11416, 186

bilateral (2004) 4851t

bilateral (country-wisedisbursement) 44f, 44

per capita 367, 424, 44f, 115,119, 122, 1267, 1303

centrality of side effects(Hirschman) 184

commitments versusdisbursements 83, 112(n2),119, 154(n89), 159

conditional 119

cross-country competition 1623

decentralization 1525different measures 15960

diminishing returns 58, 189

doctrinal positions 204

doctrinal shifts 191

dual role 164

endogeneity issue 15960

expenditure per capita (bilateraldonors versus NGOs) 44

fiscal effects in developing countries15879

as fraction of GNI 612t, 62

government-to-government 27,3841

humanitarian 53(n3), 114, 132,184, 200

impact on development 191

initial 68, 723t

legitimacy problem 1801long-run-forcing 169

macroeconomic consequences 188

macroeconomic effectiveness 158

making a difference 1825

marginal effectiveness 105

marginal productivity 84, 105

misdirected 190b

money dimension 202

multilateral 3940, 116

233

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234 Index

aid continued

versus national income growth percapita in recipient countries 24

NGO 2657NGO (country-wise disbursement)

44f, 44

not spent in recipient country 170

not spent throughrecipient-country budget 170

past developmental outcomes 10

perspectives (left- and right-wing)3

price 39probability of receiving 17, 115

professionally administered 11

proportionate to governancequality 20, 212

quantity versus quality 79

recipient performance 117

results-based, not a panacea 205

securitization 200single aggregates 59, 76(n5)

social and economic components135

targeted 43f

treated as endogenous/exogenous1778(n6)

true value 190b

weak exogeneity 173t, 175

see also development aidaid: volatility and unpredictability 8,

9, 5878

aid shocks (measuring) 647,77(n13)

assumptions 63

correlation matrix for governanceindicators 70t

cross-country correlations 645,

71, 77(n12)cross-country variation (modelling)

6774, 77(n1416)

cross-section regressions forconditional aid volatility 73t

data deficiencies 60, 70,77(n1516)

empiricism 58, 59, 6474,77(n1316)

literature 59, 76(n8)

methodology and data issues604, 767(n1012)

policy implications 746, 77(n17)

aid activities 812, 112(n2)aid administration 181, 191

economics 105aid agencies 389, 45, 125, 181, 186,

188, 204, 21719, 229cannot be voted out of power 40evaluation departments 212, 228governmental 31, 39, 58multilateral 203

official 8, 11regional desks 33universalistic 31

aid agency performance versusdevelopment outcomes 1989

aid allocation xiv, 1617, 31, 38,425, 107, 176, 200, 204

average per capita (2004) 35, 37tfactors 114

inter-country 11(n1)inter-recipient determinants 68interface with aid effectiveness 8,910

literature survey 1, 68

by NGOs (2004) 4851toptimal 116regional 17small-country bias 37

stylized cases 18aid allocation (research blind spots):

concentration andcomplementarity of internationalNGO aid 8, 2657

aid allocations by Germany,Netherlands, Norway, USA (2004)4851t

assumptions 41, 42, 45, 47

caveats 456complement view 401concentration 26, 2830, 32, 334,

468country allocation processes

(background) 323, 53(n2)data 348, 53(n36)data deficiencies 26, 46, 512,

53(n11)

dispersion 302, 48

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Index 235

empiricism 414, 54(n1014), 57equality of opportunity approach

31

further research required 45, 46,47

literature 27, 289, 31, 32NGO aid (complementarity versus

substitution) 38NGO-selection criteria 53(n2)non-profit location theory 278,

53(n1)policy recommendations 47

priority countries 26, 346, 37t, 47response rate 53(n3)reverse causality 46substitute view 3840, 53(n9)substitutes versus complements

414, 47theory 42, 48utilitarian approach 31

aid allocation and aid effectiveness:

empirical analysis 8, 10, 11457assumptions 122, 126, 128, 131,

154(n6), 155(n18)bilateral aid and arms transfers 124tbilateral per capita aid and per

capita income 121tcross-country variations 11415,

125data deficiencies 127, 154(n14),

155(n212)definitions of variables and data

issues 11925, 1545(n815)estimation methodology 1256,

155(n1618)estimation results 12634, 1407t,

155(n1921)estimation results for selected

donors (19902003) 14853t

estimation results for twenty donorcountries 1407t

literature 114, 125, 126, 127, 134,136, 139, 1537

model 11618, 154(n37)sensitivity analysis (testing for

experience of 19902003)1349, 14853t, 155(n22)

usual factors 123

variables 120t, 155(n18)

aid allocation rules 208(n33)aid budget/s 17, 68, 69, 77(n14)aid in budget

dynamic considerations 1667,1778(n6)

aid changemarginal impact 108

aid commitments (indicator) 120t,123, 125, 155(n17), 177, 177(n3),178(n8), 190b

per capita 119definition 154(n8)

aid concentration 8, 26, 2830, 32,334, 42, 468, 54(n13), 68,154(n13)

aid conditionality 59, 205aid coordination 189, 191aid crises 211aid deflator 68aid delivery 79, 189, 190baid dependency 183, 184, 188, 204,

208(n31), 209aid disbursements 132, 177,

177(n3), 178(n8)definition 154(n9)donor measures versus

recipient-country statistics 170,178(n8)

aid dispersion 28, 302, 48aid doctrines 193

aid donors xiv, 5, 9, 1617, 31, 35,39, 43, 48, 6971, 745, 77(n14),7991, 93t, 93, 94, 96, 1057,11619, 1223, 1267, 12930,132, 1347, 154(n15), 159, 1667,169, 171(n3), 1756, 178(n8),181, 1845, 1879, 190b, 1934,199, 2035, 207(n17, n21), 224

bilateral 78, 15, 27, 32, 412,

457, 197characteristics 68

coalitions 204coordination 79, 81foreign policy goals 114missions 81motives 154(n4)multilateral 15, 27, 812, 204multiplicity 207(n19)

national and multinational 69t

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236 Index

aid donors continued

NGOs 46official versus voluntary 201

official 53(n10)political allies 115preferences 118, 139, 188proliferation 84, 192self-interest 67, 10see also donor countries

aid effectiveness xiv, 5, 7, 15, 17, 27,80, 1324, 158, 194

evaluation hierarchy 192

instrument selectivity critical 186interface with aid allocation 8,910

literature survey 1, 25,1112(n12)

obstacles 1889

qualitative and quantitativemethods 11

recipient country-level 8, 1011

unit of account 186, 206(n12)see also development effectiveness

aid evaluation systems 189aid fatigue 211aid flows 1, 12(n2), 62, 6971, 75,

12730, 154(n15), 189, 2002,205, 206(n10), 207(n1516)

disaggregation 60pro-cyclical 59, 76(n4)

size 68uncertainty 678

aid fragmentation (number of donors)834, 189, 204, 207(n19)

aid funds (fungibility) 188aid given to one country only

1920, 212, 24(n56)aid grants 162, 177(n4)aid heterogeneity 76(n6)

aid impact: evaluation 8, 11,21131

approaches 21316, 229(n14)assumptions 2201balance 228baseline (absence) 2246baseline versus endline surveys

218before versus after 21315,

229(n14)

causal chain 225concepts and principles 21218,

229(n14)

contamination problem 21718cross-country regressions 211, 228data deficiencies 215, 217, 221,

222, 230(n6)dummy variables 21516, 223evaluation design: summary

2268experimental approaches 21820further research required 228

impact evaluation design 21828,22930(n56)

literature 211, 229(n2)modelling of determinants

approach 216modelling the theory 2234natural experiments 220observable versus unobservable

characteristics 216

pipeline approach 2201, 226,227f, 22930(n56)

quasi-experimental approaches2213, 224, 227f

regressions 211, 223, 226, 228selection bias 21617theory-based approach 218, 223,

228, 229aid increases

modelling 8491, 10612aid industry

direction 199202, 208(n301)doctrinal debates 200fragmented and competitive

2001new kid on block 180reform 189revised strategy needed 2025,

208(n326)aid inflows 177(n5)

disaggregation (sector versusprogramme aid) 9

aid inputsversus development outcomes 185

aid levels 115, 11719aid loans 162, 177(n4)aid management 189

aid markets 84

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Index 237

aid measures 171(n3), 177aid modalities 59aid obligation 180

aid officials 80aid optimists 183aid outcomes

good policy 187aid pessimism 183, 184, 200, 211Aid, Policies, and Growth (Burnside

& Dollar, 2000) 135, 155aid policy 117, 189, 191, 193aid portfolios 83, 85

aid predictability 76(n5)aid programmes

harmonization and co-ordination185

implementation 194outcomes 193relevance 194

aid project outcomes 117, 204, 216ratings 197

aid project proliferation andabsorptive capacity 8, 910,79113

assumptions 80, 82, 88, 90, 967,99, 1048, 110

background and motivation 804,112(n13)

causality direction 96continuous setting 97104,

112(n4)data deficiencies 80, 81, 83definitions 813empirical distribution of aid

projects 916empiricism 84, 99, 102, 104, 105further research required 105key ideas 845literature 834, 11213

maximum likelihood estimates ofmodel parameters (2003) 93t

modelling effects of aid increases8491, 10612

proposition (with proof) 11011sensitivity tests 102, 1034fsimulations with sunk costs

96104, 112(n4)theory 105

aid project size 105

aid projects 11, 87, 90, 99, 116, 125,1545(n15), 1857, 195

budget constraints 219

commitments (19952003) 82t, 83coordinated 180costs and benefits 217de-funding 101, 102, 1056design 204distribution 92fdonor-controlled 170duration 112(n3)empirical distribution 916

inputs 84marginal total productivity 90multiplicity 189, 207(n1920)outputs 85performance 116programmes 15results 1945results-aggregation 192selectivity 1923

side-benefits 85water 214t

aid proliferation (dispersion) 83aid quality 9, 189, 2045

dimensions 1845

aid quantity 9, 106, 117, 1301, 139optimal 117

aid selectivity (Collier & Dollar)78, 10

see also selectivityaid shocks (measuring) 647,

77(n13)aid target 178(n8)aid targeting 8, 36, 122aid-for-trade schemes 201aid transfers 126

equilibrium level 117aid tying 85, 189, 190b, 204,

207(n17)aid untying 79aid volatility

conditional 667tsee also aid: volatility and

unpredictabilityaid volume 1834, 1878aid works 187aidgrowth literature 25

aidgrowth relationship 211

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238 Index

Akaike information criterion (AIC)71, 723t, 734, 170

Albania 48t

Alesina, A. 7, 59, 11415, 155Algeria 48t, 61t, 67t

all-pay auctions 1920

altruism 6, 10, 116, 122, 1289,1334, 139

Andhra Pradesh 229(n5)

Angola 48t, 183Annual Review of Development

Effectiveness (World Bank) 120t,

124Argentina 48t, 61t, 67t, 196b, 220

Armenia 48t

arms 203

arms transfers (indicator) 120t, 123,124t, 12734, 1368, 14053t,155(n212)

Asia 61t, 201, 202

Asian Development Bank 69t

Asian Development Fund 69tAssessing Aid(World Bank) 39

Augmented DickeyFuller (ADF) test170, 171, 172t, 178(n10, n12)

DickeyFuller test 63

Australia 7, 69t, 115, 121t, 140t,142t, 144t, 146t, 207(n22)

aid allocation process 131

Australian Agency for InternationalDevelopment (AusAID) xiii,214, 230

Austria 7, 69t, 115, 121t, 141t, 143t,145t


autocorrelation 171, 172n

automatic stabilizers 76(n7)

average costs 29

Azerbaijan 48t, 183

back donors 27, 33, 37t, 447,53(n1)

versus NGOs (country-wisedisbursements) 45, 46f, 46

Bahamas 1723t, 174

Bangladesh 48t, 61t, 66t, 1723t,1745, 177(n1), 178(n10,

n1213), 205, 226, 230

Bangladesh Integration NutritionProject (BINP) 223, 224, 225

bank deposits

ratio to GDP 183banking sector 183Baum, J. A. C. 30Baye, M. R., et al. (1993) 19, 24

Kovenock, D. 24Vries, C. G. de 24

Belarus 48tBelgium 7, 69t, 115, 121t, 122, 134,

141t, 143t

Belize 48t, 62t, 67tbeneficiaries 215, 219beneficiary impact assessment 213Beni Suef (Egypt) 214tBenin 49t, 62t, 66tBerthlemy, J. C. 114, 115, 119, 125,

155Beynon, J. 3, 153(n2), 155Bhavnani, R. 12, 77, 209

Bhutan 49tBiekart, K. 39Bielefeld, W. 29, 30Blndal, N. 229nblack box approaches 11, 212, 215,

2223, 2289Blair, H. 39blame-sharing effects 28t, 28, 30, 31,

48

Bolivia 49t, 623t, 66t, 196bcountry assistance strategy 197,

208(n29)borrowing 162, 177(n4), 198

domestic 1706, 178(n13)government borrowing 160, 163,

177(n5)Bosnia-Herzegovina 49tBotswana 49t, 61t, 66t

bottom-up approach 202, 228boundary conditions 109boundary solution 111Brandt Report (1980) 211, 230Brazil 49t, 61t, 66t, 1823, 195, 196bBrown, G. 79budget constraint/s 89, 109, 15961,

166, 167, 171, 176, 177(n6), 192see also fiscal effects

budget discipline 188

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Index 239

budget planning 166, 167, 170budget support 202, 204, 206(n10)budgetary disequilibrium 175

budgetary equilibrium 167, 169, 176questions 1634role of aid 1745

budgetary process 176budgetary targets 160Buenos Aires 220Bulr, A. 59, 63, 76(n3, n5, n89),

77(n17)Bulgaria 196b, 199

bureaucracies 30, 54bureaucratic planning 16Burkina Faso 49t, 62t, 66t, 196b, 197Burnside, C. 3, 5, 78, 114, 135, 155Burton, J. 76nBurundi 49t, 623t, 66tbusiness: ease of starting 183business analysis 29business practices 207(n18)

calculus of variations problem 109Cambodia 49t, 196b, 218Cameroon 45, 49t, 61t, 66t, 196b,

197Canada 7, 69t, 115, 121t, 122, 124t,

140t, 142t, 144t, 146t, 148t, 150taid allocation and aid effectiveness

(19902003): sensitivity analysis

136aid allocation process 129

Canavire, G., et al. (2005) 114,11516, 125, 155

Nunnenkamp, P. 155Thiele, R. 155Triveno, L. 155

capacity building 1934, 202,207(n18)

Cape Verde 49tcapital revenue 58CARE 26CARE Norway 52CARE USA 52cash transfers 219Cassen, R. 76(n6), 114, 155censored regression model 1256Central African Republic 26, 34, 45,

47, 49t, 62t, 66t

Centre for Global Development:Evaluation Gap Working GroupReport (2006) 212, 230

centrifugal/centripetal forces 28t,2832, 37, 48

Chad 49t, 623t, 66tchain rule 86, 107Chauvet, L. 5, 76ncharities

see non-governmentalorganizations as well asindividual citations

children 200, 209, 214, 215, 224mortality rate (MDG) xivwelfare indicators 33see also education

Chile 43, 49t, 61t, 67t, 1723t,1745, 196b, 205, 2223

China 42, 44, 49t, 83t, 91, 92f, 183,195, 199, 201, 203

economic growth 1812,

206(n34)has received little aid 182

Christian Childrens Fund 52civil liberties 118, 1223, 1279,

133, 154(n12)civil rights 7, 115civil society 40, 41, 2035, 207(n21)Civil Society Unit 47Clarke, M. xii

class size 220Clemens, M. 84, 112Clemens, M., et al. (2004) 3, 12,

76(n6), 77, 184, 206(n10), 209Radelet, S. 12, 77, 209Bhavnani, R. 12, 77, 209

Clements, B. 78clustering 289, 37, 56co-financing systems 32

Coady, D. 218, 230CobbDouglas production function

856, 96, 97, 98, 102Cogneau, D. 31cointegrating relation 165, 166, 168,

169, 173tcointegrating relationship 1725cointegrating vectors 178(n13)cointegration 161, 164, 1724,

178(n1112)

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240 Index

cointegration (long-run)relationships 168

cointegration relationships 171

Cold War 135, 202Collier, P. 7, 11(n1), 31, 208(n334),

209Colombia 49t, 61t, 67t, 1723t, 174colonial ties 45, 115, 118, 130, 139,

154(n7), 197Commission for Africa 158, 178Commitment to Development Index

xiii, 122

common pool good 31communism 208(n32)community-driven projects 21617community-level organizations 204Comoros 49tcomparative dynamic analysis

fiscal effects of aid 15879comparison groups 21419, 2212,

224, 229(n23)

data on interventions 218single and double difference project

impact estimates 21516,229(n4)

competition 24(n3), 28aid donors versus recipient

governments 84between aid donors 834

competition effects 28t, 30

competitive bidding 181computable general equilibrium

(CGE) models 229(n2)conditionality policies 175conflict (violent) 2023conflict analysis 204conflict prevention 204, 208(n33)Congo Democratic Republic

[Congo-Kinshasa] 49t, 61t, 63t,

67tCongo Republic [Congo-Brazzaville]

49t, 61t, 67tconstant-elasticity-of-substitution

functions 105consultants 29, 201consumer price index (CPI) 723t,

734consumer price inflation 70, 71

consumer search costs 29

consumption 123, 158fluctuations 76(n4)private 118

contamination/contagion problem21718

contest success function (CSF) ix,1920

continuous setting 97104

control groups 2203, 229(n1),230(n6)

see also comparison groupsCordaid 51

Cordella, T. 76(n6)coreperiphery 29corner solution equilibrium 117,

154(n5)corporatism 32corruption 24(n3), 53(n11), 70, 71,

72t, 80, 85, 115, 118, 1667, 197,200, 218, 224

bribery 17

misappropriation of funds206(n11)

Costa Rica 49t, 61t, 66t, 1723t, 175,196b

micromacro disconnect 198Cte dIvoire 49t, 61t, 66t, 179counterfactual analysis 192, 21215,

21718country allocation system formalized

33country assistance evaluations (CAEs)

192, 208(n268)country assistance programmes 204

evaluation 1945, 208(n26)country assistance strategies (CASs)

1867, 203evaluation 1914, 2078(n225)joint evaluation 192

outcome ratings 196bratings 1945, 196b

country policy and institutionalassessment (CPIA) index 191, 205

country programmes 1857country size 47, 83, 119, 1314, 139,

154(n10)country studies 162covariance matrix

non-diagonal 168

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Index 241

credit access 220

critical values 171, 172n

Croatia 49t

Cuba 49tculture 200

cumulative causation processes 29

Dalgaard, C. 3, 5

Dalgaard, C., et al. (2004) 3, 12

Hansen, H. 12

Tarp, F. 12

Danida (Danish InternationalDevelopment Agency) 225, 226,230

data

censored 125

cross-section 3

ex post 217

stationary versus non-stationary

168see also time-series econometrics

data pooling 3

databases 59, 60, 81, 112(n3), 126

datasets 8, 267, 60, 64, 101, 2256,228

dbrent routine 100

de Renzio, P. 76(n2)

debt crisis (1980s) 187

debt relief 82, 190bdebt sustainability 163

decentralizing aid with interestedparties 8, 1525

aid given to one country only1920, 24(n56)

aid proportionate to governancequality of each country 20

appropriate channelling of

resources 21assumptions 1620, 23, 24(n4)

comparing aid to one country andproportional aid 212

empiricism 24(n2)

endogenous poverty 223

incentives often work innon-obvious ways 16, 23

literature 17, 19, 24(n2)

model 1622, 24(n46)

theoretical rent-seeking framework16

decision-makers 48, 161, 185

decision-making 33, 161budgetary process 159decentralization 8

default 208(n34)DellAriccia, G. 76(n6)demand 28, 29, 38demand dispersion 28t, 30, 48democracy 4, 115, 12733, 1356,

138, 184, 197, 200, 202, 207(n16)

demonstration effects 195Denmark 7, 69t, 115, 121t, 122,

124t, 139, 141t, 143t, 145t, 147t,149t, 1512t

aid allocation and aid effectiveness(19902003): sensitivity analysis136

aid allocation and aid effectiveness(19992003): sensitivity analysis

138aid allocation process 132

Denmark: Royal Ministry of ForeignAffairs xi

design 207(n18)deterministic behaviour 171developed countries 202

aid target (0.7 per cent of GDP) 79economic growth 181

income per capita (PPP) 206(n4)industrial countries 211industrial democracies 205industrialized countries 192northsouth (global divide) 200rich countries 11, 79, 1801, 185,

201, 203, 206(n4)see also OECD

developing countries 10, 11, 42,

58, 128, 1801, 189, 2002,206(n6)

economic growth 1812fiscal effects of aid 15879

higher-income 171income per capita (PPP) 206(n4)least-developed countries 47low-income countries 10, 158,

164, 170, 172t, 1756, 183, 203,

209

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242 Index

developing countries continued

low-income countries: definition177(n1)

lower-income countries 130middle-income countries 10,

1301, 158, 170, 172t, 1756,183, 203

poor countries 24(n3), 175,1845, 2013, 206(n13),208(n30), 209

poorer countries 53(n12), 177poorest countries 122, 171, 189,

191, 201, 2034, 207(n17),208(n31)

very poor countries 136weakest and poorest economies

11development 6, 9, 10, 53(n2), 7980,

82, 8690, 96105, 1078, 112,114, 116, 1334, 164

aid project output 85

conceptions 186diseconomies of scale 102f, 102,

1034f, 104economic 15, 42optimization 101f, 101potential versus actual 101sound policy framework 1867

development agencies 15, 207(n25)development aid 24(n3)

see also ODAdevelopment aid: expectations,

effectiveness, allocation 114,211

assumptions 6cross-country modelling 5, 10empiricism 23, 6key questions 2knowledge gaps 5, 12(n2)

literature 10literature survey: aid allocation 1,

68literature survey: aid effectiveness

1, 25, 1112(n12)methodology 6theory 3, 8

development challenge 199development cooperation 192, 203

changing nature 201

development economics 187development education

high priority 205

development effectiveness: evaluationperspective 8, 1011, 180210

agency performance versusdevelopment outcomes 1989

aid: making a difference (or not)1825, 206(n710)

aid: true value 190baid industry: direction 199202,

208(n301)

assumptions 185, 190bcountry assistance strategies:

evaluation 1914, 2078(n225)country assistance strategy 196bcountry-level evaluation 1945,

207(n26)cross-country

differences/correlations 180,183, 186, 187, 199200

development: achievement 1812from projects to country

programmes 1857,206(n1112)

literature 183, 187, 20810micromacro disconnect 198micromacro paradox 18791,

2067(n1321)misconceptions 2045

project portfolio outcome ratings196b

project-level and country levelresults: congruence 1958,208(n279)

questions 180, 181regional [continental] differences

182what is to be done? 2025,

208(n326)Development Gateway 207(n20)

Accessible Information onDevelopment Activities (AiDA)databases 112(n3)

development impact assessment1934

development indicators 15development ministries 201

development NGOs 53(n3)

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Index 243

development optimization 108

development outcomes 4

versus aid agency performance

1989development path (optimal) 102

development planning 59

development policy 16, 206(n8)

development profession 185

development projects 130

development technologies 106

dictatorship 39

Dietz, T. 37

difficult partnership countries (DPCs)58

digital divide 201

diplomatic leverage 186

diplomatic representation 45

distance 217

district primary education programme(DPEP) 222

division of labour

country-wise 44geographical (absent) 45

Djibouti 49t

Doha Round 201

Dollar, D. 3, 5, 78, 11(n1), 12, 31,39, 589, 11415, 134, 135, 155

Dollar and Kraay openness index(2003) 70, 77

Dominican Republic 49t, 61t, 66t,1723t, 196b, 218, 2301

donor countries 1, 16, 18, 203, 36,88, 1845

priorities 44

see also aid donors

donor darlings 47, 105

donor governments 8, 15

donor orphans 47

double counting 53(n10)double difference 21516, 221, 225

Doucouliagos, H. 187, 206(n13), 209

drugs [medicines] 201

drugs [narcotics] 203

Dutch disease 84, 2067(n14)

dynamic structural models 168

East Asia 182

East Asia and Pacific 36, 37t

East Asian financial crisis (1997) 197Easterly, W. 3, 30, 54Eastern Europe and Central Asia 202

econometric analysis 1701econometrics 3, 10, 1256, 15961,

169, 179, 183, 205fiscal effects of aid 1645

large-scale models 207(n23)notions of long- and short-run

1647see also time-series econometrics

economic crises 59

economic diversification 195economic equity 203economic factors 137, 138, 139economic growth 15, 24(n2), 58, 75,

85, 126, 158, 1834, 187, 197,202, 206(n8), 211

aid impact 10per capita 1812long-term models 207(n23)

real per capita 34economic growth theory 206(n12)economic liberalization 24(n2)Economic and Sector Work 207(n18)economic stabilization 197economic theory 169

static 165economics 164

classical 180

neo-classical 187, 202economies of scale 10, 869, 100f,

101, 1034f, 1046diseconomies of scale 868, 91,

102f, 102external 29, 38internal 289

economists 289, 180Ecuador 49t, 196b

education 24(n3), 40, 154(n11), 158gender disparity 11, 212primary 1, 219, 222, 231universal (MDG) xv, 1, 4, 219see also schools

educational delivery projects 218,219

educational institutions 222Edwards, M. 39

Eeckhout, M. 76n

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244 Index

efficiency 31, 118, 1934Egypt 49t, 61t, 66t, 196b, 214tEl Nio 199

El Salvador 34, 49t, 61t, 63t, 66t,196b

eligibility stage (Neumayer) 33elites 206(n11)

private benefit 118type I agents 11618, 154(n3)

emergency aid 59, 60, 63, 82, 202as fraction of GNI 63tunconditional volatility 63t

see also humanitarianismenergy sector reform 195Envelope Theorem 87, 108environment 201, 202, 203

social and institutional 183environmental impact analysis 212environmental protection 195environmental sustainability 203Epstein, G. S. xi, 8, 20, 24(n1), 245

Epstein, H. 207(n18), 209equality of opportunity 31equilibrium/disequilibrium 164equilibrium fiscal relation 174equity [fairness] 31equity flows 201equity investment 82Eritrea 49t, 183, 196b, 200error correction coefficient 166, 168

error correction mechanism 166Ethiopia 49t, 183, 196b, 198,

206(n7)Euler equation 109Europe and Central Asia 36, 37tEuropean Bank for Reconstruction

and Development 207(n22)European Commission 69t, 69,

723t

European Union 205, 2078(n25)evaluation design 2268

Evangelischer Entwicklungsdienst 52exchange rate

real 188, 206(n14)exchange-rate dollars 99100exogeneity test (Johansen) 169export competitiveness 188,

2067(n14)

exports 119, 120t

F-statistic 64Faaland, J. 76nfactor endowments 207(n23)

Fagerman, B. xfamily planning 31, 224farmers 215, 229(n5)Feeny, S. 13, 25fiduciary assurance gaps 197fiduciary controls 181fiduciary rules 204field surveying 225Fielding, D. xi, 9, 76n

Fiji 49t, 61t, 66tfinance 80financial flows, geographical

distribution 120tfinancial sector 197financing from abroad 170, 1723t,

175, 178(n13)Finland 69t, 121t, 122, 141t, 143t,

145t, 147t, 149t, 151t, 152t




Finland: Ministry for ForeignAffairs x

FINNIDA 214n, 229(n2), 230firms 28, 220first-order conditions 86, 88, 107first-order serial correlation 178(n11)fiscal aggregates 10fiscal balance (long-run) 171fiscal effects of aid in developing

countries: comparative dynamicanalysis 8, 10, 15879

assumptions/presumptions 1603,165, 168, 16970, 177(n3)

causality 174, 175, 176caveats 162, 178(n12)conceptualizing aid in the budget:

dynamic considerations 1667,1778(n6)

data and model specification16970, 178(n89)

econometric method 1645

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Index 245

impact of aid: representation andhypotheses 1604, 177(n25)

fundamental issue 158

further research required 162,1767

key concepts 165literature 15860, 163, 174,

177(n6), 178(n8), 1789policy implications 176questions 1634results and discussion 1715,

178(n1013)

statistical preliminaries 1656theory 159, 1601, 1645unit root tests 1723tVAR approach 1689, 1701,

178(n7)see also government budgets

fiscal imbalance 169fiscal reform 195fiscal response models (FRMs) 159,

1602, 167, 16970, 1746,177(n2), 1778(n6), 178(n8)

questions 1634Flanagan, A. 229nFlannery, B. P. 113focus groups 226food aid 76(n7)foreign direct investment (FDI) 201,

203

foreign exchange reserves 75foreign policy 119Foster, M. 76(n2), 77(n17)Fowler, A. 39France 7, 45, 69t, 69, 715, 115,

121t, 124t, 125, 139, 140t, 142t,144t, 146t, 148t, 150t, 152t


135aid allocation and aid effectiveness

(19992003): sensitivity analysis137

aid allocation processes 128Franco-Rodriguez, S., et al. (1998)

159, 160, 178(n6), 178McGillivray, M., 178Morrissey, O. 178

freedom from fear/want 200

Freedom House democracy index120t

Freedom House Evaluation website

120tFreedom House index of civil liberty

122Friedrich Ebert Stiftung 52fruit of disappointment 206(n11)Fruttero, A. 301funding 28, 30, 53(n2), 154(n8)

competitive pressure 47private and public 34

fungibility 1589, 2045

G7 aid money 207(n17)Gabon 49t, 61t, 67tGambia 49t, 63t, 66t, 76(n10)Gang, I. N. 8, 24(n1), 24Gates, S. 11415, 135, 155Gauri, V. 301Gemmell, N. 58, 78

gender 11, 212geo-economics 191

geographical economics 28, 38, 55geography 6, 30, 32, 185, 193, 217

geo-politics 71, 189, 191, 200,208(n32)

Georgia 49t, 182Germany 7, 69t, 69, 72t, 745, 115,

121t, 122, 124t, 140t, 142t, 144t,

146t, 148t, 150t, 152taid allocation and aid effectiveness

(19902003): sensitivity analysis135


aid allocation processes 1289

aid allocations 4851t

NGOs 32, 34, 36f, 36, 37t, 46f, 47,4851t, 52

Germany: Ministry of EconomicCooperation and Development(NGO Division) 52

Ghana 49t, 62t, 66t, 177(n5), 179,183, 196b, 198, 205, 2245

Gini coefficient 334, 54(n13)Gini index 118, 120t, 123, 1269,

1313, 1368, 14053t

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246 Index

girls 215, 222Girma, S. 78Glinskaya, E. 222, 231

global market 11, 200global warming 201globalization 202, 203Gomanee, K., et al. (2003) 76(n2), 78

Girma, S. 78Morrissey, O. 78

Gomanee, K., et al. (2005) 4, 13Morrissey, O. 13Mosley, P. 13

Verschoor, A. 13goods and services 79, 154(n9), 189Gounder, R. 114, 155governance

democratic 3940, 42rules-based 183

governance indicators 70tgovernance quality 78, 1516, 27,

3944, 53(n11), 54(n14), 56, 75,

84, 115, 131, 186, 1978, 202,2045, 209

aid proportionate to 20, 212investment in 1722, 24(n46)

governance targeting 423government (indicator) 120t,

1223, 127, 1328, 14053t,154(n12)

government budgets 40, 81, 97, 101,

1067, 108accounting framework 162aid component (dynamic

considerations) 1667,1778(n6)

deficits 162, 169, 177, 177(n4)primary surplus 162, 163share allocated to aid 205,

208(n35)

surplus 169see also budget constraint/s

government effectiveness 70t, 70,72t

governments 16, 28, 40, 45, 47, 84,104, 11617, 154(n3, n8), 1979,2034, 229n

core functions 189donor versus recipients 53(n9)

targeting criteria 31

Grangers Representation Theorem1656

grants 24(n3), 32, 33, 82, 177, 201,

206(n8), 222Greece 69t

Groot, D. de 52n

gross domestic product (GDP) 60,84, 100, 119, 183

GDP per capita 202

GDP per capita (real) 119, 120t,122, 12734, 136, 138, 14053t

GDP deflator 170

GDP growth (indicator) 119, 120t,122, 126, 1278, 1302, 14053t

GDP growth rate 118

gross national income (GNI) 60,645, 68, 76(n10), 172t, 177(n1),183

aid as fraction of 612t, 62

national income 201

national income growth 23, 5,

12(n2)gross national product (GNP) 183,

186

growth/poverty-reduction elasticity11(n1)

Guatemala 49t, 61t, 67t, 196b, 197

Guillaumont, P. 5, 12

Guinea 49t

Guinea-Bissau 47, 49t

Gupta, S. 76(n2)

Gupta, S., et al. (2004) 76(n7), 78

Clements, B. 78

Tiongson, E. 78

Guyana 49t, 623t, 67t

Haiti 49t, 62t, 66t, 196b, 199, 221

Hamann, J. 59, 63, 76(n3, n5, n89)

Hamilton, J. D. 168, 178(n7), 178Hansen, H. 3, 5, 12

harmonization 79, 207(n21)

health 2, 4, 154(n11), 158, 215, 224

health care 24(n3), 214

contracting out 218

health clinics 217

Heckelman, J. 24(n2)

Heckman sample selection model

125

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Index 247

Heller, P. 76(n2)

Herfindahl index 723t, 74

Hermes, N. 13, 25

heteroscedasticity 171, 172nLagrange multiplier (LM) test

723t

Hirschman, A. O. 184, 185, 209

HIV/AIDS 182, 197, 201, 203, 209,214, 230

Hivos 51

Hodrick, R. 59, 67

Hoeffler, A. 11415, 135, 155

Honduras 49t, 623t, 66t, 183Hook, S. 156

horizontal inequalities 204

households 120t, 123, 220

housing quality 222

Hulme, D. 39

human capital 38, 59

human development 133

Human Development Index 4, 33

Human Development Report(UNDP)34, 120t

human fertility 224

human resources 122, 1278, 195

personnel quality 38

human rights 115

human security 11, 204

human trafficking 203

human welfare 182

humanitarianism 6, 34, 53(n3), 114,132, 184, 200

Hungary 205

Hunt, J. xii

ICCO 51

ideas 191, 203

Im, K., et al. (2003) 63, 78

Pesaran, H. 78Shin, Y. 78

immobility of inputs (Krugman) 30

immunization 199200, 224, 226

impact evaluation

definitions 21213

import tariffs 201

imports 119

income per capita 130, 183,

206(n7)

income distribution 120t,123, 1278, 1301, 134,1368

income inequality 34income poverty 11, 212

MDG 1, 4, 7independent and identically

distributed (i.i.d.)random variables 126residuals 64

India 34, 42, 44, 47, 49t, 61t, 66t,83t, 1723t, 177(n1), 183, 196b,

199, 201, 203, 206(n7), 218, 222,229(n5)

aid received 206(n5)economic growth 181, 206(n34)reforms (1991) 206(n5)

indirect demand function 107indirect supply functions 107indirect utility function 107individuals 27, 120t

Indonesia 49t, 61t, 66t, 83t, 196b,197

inequality, international andsub-national 199200

infant mortality 11, 120t, 123,12633, 135, 1378, 14053t,182, 199, 21213

inflation 75, 188, 197information 29, 60, 207(n20)

information asymmetry 206(n2,n11)

see also knowledgeinfrastructure 29, 80, 158, 202, 204,

206(n10), 219inputs 29, 85, 105, 223

cheaper 29price 48

Institute of Social Studies, the Hague

52ninstitutional development 194institutional frameworks 207(n23)institutional mapping 226institutional quality 9, 68, 701, 72t,

745institutions 15, 52, 84, 135, 166,

186, 191, 197, 200, 202democratic 138

economic 188, 207(n15)

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248 Index

institutions continued

political 75, 135, 188, 207(n16)

public 7

quality 183sound 135, 1867

intellectual property 201, 203

Inter-American Development Bank(IDB) 69t, 207(n22), 2213, 230

IDB Special Fund 69t

International Cooperation Academyon Civil Society 52n

International Development

Association (IDA) 69t, 69, 723tInternational Finance Corporation

204, 208(n34)

International Finance Facility (IFF)58, 76(n1), 78, 79

international financial institutions191, 207(n25)

International Fund for AgriculturalDevelopment (IFAD) 69t, 225,231

International Monetary Fund (IMF)120t, 188

international relations 180,208(n32)

internet 81, 112(n1), 207(n20)

interviews 267, 323, 38, 41, 45,512, 53(n2)

qualitative 226 Investing in Development(UNDP, 2005)79, 113

investment 6, 1589, 183, 187, 195,207(n15), 208(n34), 224

private 202

public 185, 186

public (big push) 206(n12)

investment guarantee institutions

201Iran 50t

Iraq 54(n14), 200

Ireland (ROI) 69t, 121t, 122, 141t,143t, 145t, 147t


irrigation 224, 229(n5)

Islamic Development Bank 207(n22)

Islei, O. 179

isomorphic transformation 45

Isopi, A. xi, 10, 116, 139, 154(n5,n14), 156

Israel 67, 220

Italy 7, 69t, 115, 121t, 131, 139,141t, 143t, 145t, 147t, 152t,207(n17)

Jalan, J. 222, 231

Jamaica 50t, 66t, 196b

Japan 7, 69t, 69, 723t, 745, 80,115, 121t, 122, 124t, 125, 139,140t, 142t, 144t, 146t, 148t, 150t,152t, 180

aid allocation and aid effectiveness(19902003): sensitivity analysis135, 155(n22)


aid allocation process 129,155(n19)

JarqueBera tests 723t

Joassart-Marcelli, P. 32

Johansen, S. 164, 168, 169, 179

Johansen trace statistic 172, 173t

Johnston, T. A. 81, 113

Jordan 50t, 61t, 66t, 196b, 207(n22)

Juselius, K. 168, 179

Kandy (Sri Lanka) 214tKaufmann, D., et al. (2003) 70,

77(n15), 78

Kraay, A. 78

Mastruzzi, M. 78

Kaufmann indicators 53(n11)

Kazakhstan 50t, 196b, 207(n22)

Keeble, D., et al. (1999) 29, 55

Lawson, C. 55

Moore, B. 55Wilkinson, F. 55

Keen, M. 175, 179

Kenya 50t, 62t, 66t, 81, 170, 1723t,177, 177(n1), 178(n12), 179, 215,218, 221, 225, 230

Keynes, J. M. 206(n1)

Killick, T. 52n, 59Kinder Nothilfe Deutschland 52

Kingsbury, D. xii

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Index 249

Knack, S. 24(n2), 834, 113

knowledge 29, 202

local 31

see also spillover effectsKoch, D.-J. xi, 8, 27, 32, 39, 47,

523n, 55, D-J., 37n, 53(n3)

Kohama, H. 210

Koizumi, J. 180

Kono, H. 210Konrad Adenauer Stiftung 52

Korea: North 39

Korea: South 50t, 183

Kosack, S. 4Kosovo 30

Kovenock, D. 24

Kraay, A. 70, 78

Krugman, P. 28, 30, 55

Kyrgyz Republic 50t, 183, 196b

labour 29, 30, 217

labour market thickness 38, 48labour mobility 28t, 28, 2930

labour productivity 183

Lagrange multiplier (LM) test 723t

Lagrangian 86, 106

land 197, 220

Landes, D. S. 206(n1), 210

landlocked countries 26

Lane, T. 77(n17), 77

Laos 50tLatin America 347, 62t, 715, 202

Latin America and Caribbean 35, 37t

Latvia 183

Lawson, C. 55

leaders 16, 24(n5)

pay-offs 1822

utility 1718

leadership 204

Lebanon 50tlegal framework 15

legislation 208(n30)

legislatures 80

lending agencies (multilateral)154(n15)

Lennon, J. O. 182

Lensink, R. 13, 25, 58, 76(n3)

Lesotho 50t, 196b, 207(n22)

level playing field 11

level stage 33

Levin, V. 39, 58, 11415, 134,155

liberalism 32Liberia 42, 50t

Libya 50t

life expectancy 7, 182

Lima, A. de 112

Lin, T. 76(n1)

Lindi (Tanzania) 214t

linkages (forward and backward) 29

literacy 182, 222

Lithuania 196bLittle, R. 6, 114, 156

living standards 182, 206(n13)

Llavador, H. G. 31

Lloyd, T. xixii, 10, 178(n9), 179

loans 82, 201, 206(n8)

concessional 177

infrastructure 206(n10)

policy-based, speedy disbursement

202

local government 204

Lockard, A. A. 20

log frame analysis 30

Loman, B. 53(n3)

long run forcing 169

Lorenz curve 8, 34, 356f

Lundborg, P. 114, 156

Luxembourg 69t

MAmanja, D. 179

Macedonia 50t

macro level 229(n2)

macroeconomic conditions 161

macroeconomic policy 68, 701,1834, 202

conditionality 206(n12)

macroeconomic stability 9, 75macroeconomic stabilization: halo

effect 197

macroeconomic variables 60, 75

macroeconomics 58, 76(n7), 164,188

empirical 168

macroeconomists 185

Madagascar 50t, 62t, 66t

Maizels, A. 6, 114, 156

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250 Index

make poverty history 200Malawi 26, 34, 50t, 623t, 66t, 183,

207(n22), 221

Malaysia 50t, 61t, 67tMaldives 50t, 196bMali 50t, 623t, 66t, 199malnutrition 130, 182, 199Malthus, T. R. 180marginal productivity 90marginal utility 107market access 216market size 48

Marshall Plan 208(n36)Martens, B., et al. (2002) 206(n2),

210Mummert, U. 210Murrell, P. 210Ostrom, E. 210Seabright, P. 210

Mastruzzi, M. 78mathematics 90, 100, 105, 108

Mattesini, F. 116, 139, 154(n5), 156Mauritania 50t, 623t, 66tMauritius 50t, 1723tMavrotas, G. x, xii, 4, 9, 10, 12(n2),

12, 13, 24(n3), 76n, 76(n1, n6),77, 78, 153(n1), 154(n14), 156,160

maximum likelihood 93t, 93, 94f,125, 168

McGillivray, M. x, xii, 3, 4, 6, 10, 12,13, 52n, 58, 76n, 77, 78, 114,119, 153n, 153(n2), 156, 158,160, 178(n9), 178, 179

McGillivray, M., et al. (2005) 24(n2),25

Feeny, S. 25Hermes, N. 25Lensink, R. 25

McGillivray, M., et al. (2006) 3, 13Feeny, S. 13Hermes, N. 13Lensink, R. 13

McKay, J. xiiiMcKinley, R. D. 6, 13, 114, 156Mdecins Sans Frontires 34Mercy Corps 52Mexico 34, 50t, 61t, 67t, 171,

1723t, 196b, 205, 218, 230

micro-credit 216micro-economics 185, 197micro-finance 221

micromacro disconnect 198micromacro gap 41, 42micromacro paradox (Mosley) 3, 5,

18791, 192, 199, 202,2067(n1321), 228

project results versus country results187

micro-states 60Middle East 202

Middle East and North Africa 358,47, 182

migrants/migration 60, 201, 203Millennium Challenge Account 16Millennium Challenge Corporation

16, 24(n3)Millennium Development Goals

(MDGs) 1, 2, 47, 11, 356,589, 75, 1945, 200, 212

minority groups 222MISEREOR 52model selection criteria 172nmodelling of determinants approach

216Moldova 34, 47, 50t, 183Molenaar, H. 52nmonetary policy 188Mongolia 50t, 196b

monitoring 40, 81, 106, 131,206(n2), 207(n18), 223

monitoring and evaluation (M&E)systems 222

monopolies 53(n9)Moore, B. 55Moore, M. 112moral hazard 116, 117Morocco 50t, 61t, 66t, 196b, 198

Morosino, P. 29Morrissey, O. xii, 3, 4, 10, 13, 58,

76(n3), 78, 158, 178(n9), 178, 179

Morrissey, O., et al. (2006) 163, 175, 179Islei, O. 179MAmanja, D. 179

Morrissey, O., et al. (2007) 170, 177,179

Lloyd, T. 179

MAmanja, D. 179

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Index 251

Morss, E. R. 801, 113

programme aid 82

Mosley, P. 3, 13, 76(n1), 114, 156,

212, 228Mozambique 47, 50t, 83t, 183, 226,

230

Mtwara (Tanzania) 214t

Mummert, U. 210

Munro, L. 153(n2), 156

Murdoch, J. C. 29, 30

Murrell, P. 210

Myanmar 39, 50t

NAFTA (North American Free TradeAgreement) 205

Namibia 50t

naming-and-shaming 81

Nash equilibria 1920

nation-building 186

national security 186

natural experiments 220natural resources 185, 197, 200, 202,

206(n14)

Naudet, J. D. 31

neo-institutionalists 45

Nepal 50t, 62t, 66t, 196b

Netherlands 7, 69t, 69, 121t, 122,139, 140t, 142t, 144t, 146t, 152t,2067(n14)

aid allocation processes 1301aid allocations 4851t

NGOs 32, 36f, 36, 37t, 46f,4751

Netherlands: Ministry of ForeignAffairs 40, 523n

Netherlands: Ministry of ForeignAffairs (Division of Effectivenessand Quality) 52

Neumayer, E. 33, 56, 11415, 156New Zealand 69t, 121t, 139, 141t,

143t, 145t, 147t, 152t,207(n22)


Nicaragua 34, 47, 50t

Niger 50t, 623t, 66t, 183

Nigeria 34, 42, 47, 50t, 221

Nijmegen: Radboud University

523n

Nissanke, M. 6, 114, 156Nitzan, S. 20, 245Noakhali Rural Development Project

(Bangladesh) 225, 230non-governmental organizations

(NGOs) 8, 15, 24(n1), 37,54(n14), 82, 188, 1912, 200

choice of location 278

clustering 8comparative advantage 26concentration and

complementarity of aid 2657

country allocation processes(background) 323, 53(n2)

country-wise disbursement pattern45

financial dependence on backdonors 45, 46f

German, Norwegian, American,Dutch 32, 346, 37t, 46f, 4752

humanitarian 34

international 52interviews 512local 40versus back donors (country-wise

disbursements) 45, 46f, 46non-governmental organizations: aid

41, 53(n10)complement view versus substitute

view 3841, 53(n69)

per donor country 36fsub-national level 27

non-profit location theory 278, 29,53(n1), 54

non-profit organizations 45ignore equity, particularistic

312Nordic countries/Scandinavia 7,

115, 136, 155(n16)

normality (vector tests) 171Norway 7, 69t, 121t, 122, 141t, 143t,

145t, 147t, 149t, 151t, 152t,207(n22)



138

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252 Index

Norway continued


aid allocations 4851t

NGOs 32, 34, 36f, 36, 37t, 46f,4752

Norway: Ministry of Developmentcooperation (NORAD) 47, 52

Norway: Royal Ministry of ForeignAffairs x

Norwegian Church Aid 52

Norwegian Peoples Aid 52

Novib (now OxfamNovib) 51

Nunnenkamp, P. 12(n2), 13, 155

nutrition 213, 215, 223, 224

observables/unobservables 227f

official aid (OA) 42, 120t

official development assistance (ODA)xiv, 1, 24(n1)

see also aid

Ohlin, G. 211, 231

Okonjo-Iweala, N. 208(n334), 209

Oliver, C. 30

Oman 50t, 171, 1723t, 175

open economies 24(n3)

Opoku-Afari, M. v, xii, 10, 158,178(n9)

opportunity cost 117

ordinary least squares (OLS) 64,155(n18)

two-stage/three-stage 160

Organisation for EconomicCo-operation and Development

aid budget (public perception)205, 208(n36)

data source 60

OECD countries 1, 38, 185, 205,

208(n36)Organisation for Economic

Co-operation and Development:Development AssistanceCommittee 115, 119, 190b,20810

aid statistics (major problem) 170

member countries 2f

conference (March 2005) 190b

countries aided by 34, 53(n11)

data source/statistics 42, 51n,53(n10), 64, 68, 823n, 92n, 113,116, 120t, 125, 139, 170

donors 133IEGDAC initiative 229n

ODA 2f, 24(n1)

OECD DAC: Creditor ReportingSystem (CRS) database 60, 813,91, 112(n23)

OECD DAC: DevelopmentCooperation Report (2003) 192

OECD DAC: Network on

Development Evaluation 192organizational design 27

organizational growth 30

Osei, R., et al. (2003) 161, 179

Lloyd, T. 179

Morrissey, O. 179

Osei

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