How Unpredictable Aid Influences Service Delivery:
Results from Country Case Studies
Methodology for Country Case Studies
May 2009
Geoff Handley and Edward Hedger
with Tony Killick
* This study has been supported by funding from the Knowledge for Change
Program, a multi-donor programmatic trust fund managed by the
Development Economics Vice Presidency of the World Bank.
Disclaimer: The views presented in this paper are those of the authors and
do not necessarily represent the views of the World Bank or of the
Knowledge for Change Program donors
Overseas Development Institute
111 Westminster Bridge Road
London SE1 7JD
UK
How Unpredictable Aid Influences Service Delivery
Tel: +44 (0)20 7922 0300 Fax: +44 (0)20 7922 0399
www.odi.org.uk
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How Unpredictable Aid Influences Service Delivery
Contents
Contents .............................................................................................................................. 3
1 Introduction ................................................................................................................... 4
2 Study objectives and approach ..................................................................................... 5
3 Content of the country case studies.............................................................................. 9
References ........................................................................................................................ 16
Annex 1: Glossary of terms................................................................................................ 17
Annex 2: Proposed data requirements for case studies..................................................... 22
Annex 3: Proposed background documentation for Uganda country case study ............... 23
How Unpredictable Aid Influences Service Delivery
1 Introduction
1. The Overseas Development Institute (ODI) has been contracted by the World Bank to
undertake a study on the effects of unpredictable aid on service delivery. This involves: i) a deskbased literature and data review (ODI, 2009); ii) the development of a methodology for in-depth
country case studies; iii) undertaking a first ‘Pilot’ country case study in Uganda; iv) helping to
quality assure a second country case study in Ghana; v) undertaking a third country case study,
and; vi) writing a synthesis report covering the findings of the desk-review and country case
studies. This methodology note covers stage ii) of this process, and sets out to:
 establish detailed guidelines for the country case studies;
 develop an analytical framework from the concept note and the literature and data review,
and;
 provide detailed questions for structured interviews with government officials and donors
(see Box 1).
2. The methodology should be regarded as a working document that may be subject to revision
once the Uganda ‘pilot’ country case study has been completed.
Box 1: ToR Requirements for the Case Study Methodology
“The case study methodology will establish detailed guidelines for the country case studies through a set of
common research questions and explanatory notes which suggest sources and sub-questions. The
methodology will be motivated by an analytical framework derived from the concept note and the literature
and data review and it will build upon the hypotheses advanced in the concept note and the issues identified
in the literature and data review.
The case study methodology will address the need for structured interviews with government officials and
donors. The aim will be to interview government officials involved in central strategic planning, budgeting,
budget implementing, and aid management. Donor-side information will be gathered through interviews with
local agencies of major official donors and global programs such as the Global Fund.
The output will be a paper detailing the design of the study methodology for the country case studies.”
Source: Terms of Reference (pp. 2 - 3).
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Methodology for Country Case Studies
2 Study objectives and approach
3. The concepts, definitions and study questions to be addressed in the case studies as set out
in the Terms of Reference (version dated January 22nd 2009 – see Error! Reference source not
found.) and the original Concept Note (dated November 2008 – see Error! Reference source not
found.) are taken as the starting point for the development of the methodology. These are
summarised in Box 2 below.
Box 2: Excerpts from ToR on Approach to Definitions and Study Questions
“While several recent studies and surveys have focused on measuring the predictability of aid and on
identifying donor-specific and recipient-side factors that influence predictability, less is known about the
sectoral implications of uncertain aid flows and how unpredictable aid has actually impacted budget
allocation and spending patterns in key sectors such as health, education, and infrastructure/roads.
Little is also known about whether the increasing importance of global programs/vertical funds (funds that
are typically earmarked) in the aid landscape, especially in health, is contributing to or mitigating the
predictability of aid flows.” (ToR, Page 1).
“The objective of this research is to examine in-depth the problem of aid predictability at the aggregate and
sector level, drawing on country-level evidence from highly aid-dependent countries. Particular focus will
be on addressing issues of aid expectations, reliability of aid, permanence of aid, type of aid, and
timing (short- and medium-term), as well as how fragmentation and donor coordination impact
predictability of aid resources. The country-level evidence will contribute to the dialogue on how aid can
be made more effective.”
“The proposed research will use the notion of expectations and reliability in examining aid predictability.
This approach is useful for understanding the different types of predictability problems and the implications
for policymaking. The analysis will also consider the long-term aspects of the predictability of aid
resources… The focus will be on better understanding the following key issues:
1. How unpredictable is aid?
2. Is the impact of aid shortfalls and windfalls on government spending asymmetric?
3. How donor arrangements and choice of aid instrument have influenced the predictability of aid.
4. How much of a concern is aid fragmentation?” (ToR, pp. 1 - 2).
“The country-level work will employ the country case methodology developed for this project… Particular
focus will be on:
1. Examining recent trends in the size and frequency of aid shortfalls and windfalls—both at the aggregate
and sector level.
2. Assessing the impact of contemporaneous aid shocks on current period spending.
3. Studying the effect of uncertainty of aid resources on the composition of public expenditure - sectoral
allocations and spending patterns by categories.
4. Understanding the rationale behind aid projections, both in the short term and the medium term, and how
aid information is incorporated in the Medium-Term Expenditure Framework, sector MTEFs, and the
budget. An important issue here is on assessing how donor coordination mechanisms and
arrangements such as multi-donor budget support (MDB), sector budget support, and sector-wide
approaches (SWAps) have influenced aid projections and helped to improve predictability on the
ground.” (p. 3)
Note: Emphasis added.
Source: ToR.
4. It is also worth emphasising some important points regarding the approach we propose to take
to the case studies, which in some areas will differ slightly from that set out in the ToR and KCP:
 Case study data collection: The country case studies will collect information through
i) collation of country-level data on aid, public finance and service delivery (see Annex 2); ii)
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How Unpredictable Aid Influences Service Delivery
collation of relevant background documentation; and, iii) Interviews with key stakeholders.
Background documentation will comprise government plans, budgets and reports and
secondary sources such as donor commissioned reports including PFM diagnostics: see
Annex 3 for a proposed list of background documentation for the Uganda case study.
Interviews will be undertaken with key officials from government, aid agencies and civil
society. Government interviews will focus on the ministry of finance and planning, central
bank, a selected sector ministry or ministries, and, where time and resources permit, subnational tiers of government (e.g. a district administration) and frontline service providers
(e.g. a health clinic). The questions listed in the methodology below will be divided up
across the different interviews as appropriate during the fieldwork phase.
 Sectoral focus: Beyond an analysis of the effects of aid unpredictability at the aggregate
level, the time and resources available permit an in-depth focus on the effects of aid
predictability on one sector only. Following the emphasis in the KCP and ToR on examining
the predictability of aid in sectors in which vertical funds operate, the Uganda country case
study will primarily focus on the health sector. Insofar as time and resources allow and in
line with the emphasis in the KCP and ToR on infrastructure, it is proposed that a
secondary sector for the Uganda case study should be the roads sector.
 Proposed definitions: Clear definitions of study terminology that can be easily understood,
calculated, differentiated from one another and explained to interviewees are essential.
Definitions for key terms can be found in the Glossary in Annex 1 below. A few definitions
merit particular emphasis however:
o Volatility refers to deviations between disbursed amounts from year to year. While
we will address this dimension, it is not a primary focus of the study.
o Unpredictability is the primary focus of the study. Following Andrews and Wilhelm
(2008) it has two constituent parts: reliability and expectation:
 Reliability refers to the extent to which aid commitments are a reliable
indicator of aid disbursements. Note for example that if disbursements are
consistently the same proportion below commitments then they could still be
regarded as reliable.
 Expectations, and particular the notion of unexpected aid, refer to the
understanding by recipients about how much aid they will receive, at which
times and over which periods. Such expectations may be based on the
credibility of commitment schedules or on other mechanisms for projecting
aid flows (e.g. systematic adjustments based on experience).
We can also distinguish between in-year, short-term and medium-term
(un)predictability:
 In-year predictability: typically measures how quarterly disbursements
correspond to quarterly commitments.
 Short-term predictability: how annual disbursements correspond to annual
commitments.
 Medium-term predictability: measures by how far ahead donors are able
to provide firm financing commitments.
 Treatment of ‘on-system’ aid: The concept of ‘on-system’ is used here to embrace all
elements of ‘on-budget’ covered by the recent SPA/CABRI study (Mokoro, 2008). It is
preferred to ‘on-budget’ since it avoids the ambiguity that arises from the use of ‘on-budget’
to refer to both to the capture of aid on the whole of the PFM system and to its capture on
only one of the elements (‘on budget documents’) – see Glossary. We propose to focus in
the case studies on three dimensions of this definition: ‘on-budget documents’, ‘onparliament’ and ‘on-treasury’. It is important to acknowledge the possible perverse effects
of improving the capture aid on-system. While off-budget aid complicates planning and
budgeting, on-budget aid does not automatically improve predictability and can create costs
as in Mozambique, where aid was included in the budget that was not under the
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Methodology for Country Case Studies
government’s management control (undermining its use as an accountability tool) and was
not disbursed (undermining its credibility).
 Estimating the extent of off ‘off-system’ aid: Where aid is not captured on these
dimensions, the extent of the problem will be almost by definition unknown. We will rely
primarily on existing estimates of the extent of off-system aid flows (such as those in
Williamson, 2007), complemented by estimates for very large programmes where data is
available (e.g. PEPFAR) as resources do not permit a full investigation of the extent of the
off-system problem.
 Time period: The case studies will attempt to cover the period from 1999 to 2009, insofar
as data and documentation are available and interviewees are able to cover authoritatively
that range. Where key donor personnel have moved on to new postings, efforts will be
made to follow-up with them.
 Attention to both aid windfalls/surges and aid shortfalls: The definition of
unpredictability used admits both an aid windfall/surge and an aid shortfall. Evidence from
Celasun and Walliser (2008) suggests that their effects can be asymmetric in terms of
increasing or reducing types and levels expenditure:
o Unexpected aid shortfalls force governments to disproportionately cut investments
in physical and human capital.
o Unexpected aid windfalls on the other hand disproportionately boost government
consumption or domestic debt reduction which, unlike investment spending, can be
adjusted without much delay and planning. They typically come too late in the
budget year to be spent on investment.
o Countries benefitting from consistent windfalls tend to use them to pay down
domestic debt rather than to finance additional expenditure, particularly where
monetary policy restrictions limit domestic borrowing (e.g. WAEMU countries).
o Short-term distortionary responses to unpredictable aid are more likely for budget
aid because recipients have full discretion on where to spend such aid.
 Focus on ‘episodes’ of unpredictability: Specific episodes where there were was a large
windfall/surge or shortfall in aid will be identified and examined to understand the particular
impact of those instances on the variables considered in this study (e.g. the institutional
arrangements for budget planning and management, the level and composition of planned
and executed expenditure, the reliability and predictability of resource flows to service
delivery units, and the measures of service delivery and performance).
 Strategic nature of the aid unpredictability problem: The aid unpredictability problem is
inherently strategic. The government has a ‘reaction function’ (or fiscal response function)
to respond to the provision of unpredictable aid and this will differ at national (ministry of
finance) and sector level. The Andrews and Wilhelm (2008) framework provides an entry
point here but could go further, for example by considering ‘unreliable but expected’ aid
rather than ‘expected but unreliable’ aid in Quadrant 2 of their framework. There is also a
useful distinction to be made between pre-emptive and retrospective responses. Over time
government officials will be familiar with the costs of unpredictability and will adopt preemptive strategies to mitigate its effects (e.g. by discounting their expectations of aid
disbursements, or [in countries which are not highly aid dependent] by ensuring that
domestic revenues are always sufficient to cover the recurrent portion of the budget, c.f.
Penrose, 2008).
 Attention to non-aid resources: Attention should be paid to the flow and predictability of
total resources (including non-aid). At the aggregate level this will provide an impression of
how unpredictable aid is in relation to non-aid resources following Bulir and Hamann
(2007). At the sector level the primary concern for government officials is likely to be
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How Unpredictable Aid Influences Service Delivery
resource unpredictability at a more general level that does not distinguish sources or types
of revenue or financing. It will then be necessary to investigate the extent to which aid is a
driving (or even mitigating) factor in such unpredictability. This distinction may not be
observable at sector level for on-system aid (e.g. if GBS is very unpredictable).
 An emphasis on how country budget systems work: Different styles of planning and
budgeting are likely to affect the way aid fluctuations work their way through the fiscal
system. The methodology pays close attention to planning and budgeting systems, and
budget execution in particular, in order to draw this out. This will also involve close attention
to informal institutions as well as formal ones. Helmke and Levitsky (2004) provide a
framework for analysing informal institutions which we draw upon for the methodology,
while Stevens (2004) discusses how informal arrangements emerge and are sustained
within budget processes.
 An attempt to trace effects lower down the service delivery chain: The KCP and ToR
focus strongly on first tier effects of aid unpredictability on government expenditure,
remaining very much at the ‘macro’ level. Our primary aim will be to fulfil the requirements
set out in these documents (reflected in Sections 1 to 5 of the methodology below).
However, insofar as time and available evidence allow, we will also attempt to trace the
cascaded effects of aid unpredictability through to spending ministries, sub-national
governments, and service delivery units and ultimately try to present any available evidence
regarding impacts on service delivery. This is primarily addressed in Section 6 of the
methodology below.
 Not proposing to investigate disaster/emergency aid: The macroeconomic, fiscal and
sectoral consequences of large swings in emergency aid (suggested in Andrews and
Wilhelm, 2008) are of course an important area for analysis. However, the issues are
substantially different from those arising from unpredictable/volatile development aid. We
propose therefore to exclude emergency aid from the country studies.
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Methodology for Country Case Studies
3 Content of the country case studies
[N.B. Overall page limit of max. 38 pages, not including annexes].
1. Summary of Conclusions and Lessons (max. 2 Pages)
A short note bringing out:
 Key findings from the case study.
 Conclusions from the case study.
 Lessons for international practice arising from the findings and conclusions, both in terms of
positive examples to follow and of potential mistakes to be avoided.
2. Background And Country Context (max. 4 Pages)
2.1. Background to the study (max. 1 page)
 Objectives
 Methodology (including definitions of key terms)
2.2. Country Context (max. 3 pages)

Macro Situation: a short description of the macro situation (economy, poverty, politics,
political economy)
o Briefly reference findings of IMF (2005) on absorption and spending of aid in the
country in question and articulation of monetary and fiscal policy.
o Trends in major macroeconomic indices: Real GDP, Real GDP growth, Real GDP
per capita, inflation, 1990 – present
o Note any structural constraints in national macroeconomic policy framework.1
o Trends in major fiscal aggregates: total revenue, total spending and fiscal deficit,
stock of debt (external and domestic), estimated payment arrears 1990 – present
o Headline findings of any studies of political economy (e.g. drivers of change)

National aid Environment: a description of the national aid environment
o aggregate aid volumes (1990 – present as % of GDP and % govt. expenditure
o number of donors,
o mix of instruments,
o nature of conditionality (especially IMF and GBS, explicit and implicit),
o donor harmonization and alignment, in particular donor coordination mechanisms
and arrangements such as multi-donor budget support (MDB).
o overview of country performance against Paris Declaration indicators.
o Overall, how volatile is aid at the aggregate level: how large are year on year
variations in aid volumes? (using data from literature and data review).

Sector aid environment:
o aid volumes in selected sector(s) (1999 – present as % of GDP and % govt.
expenditure
o number of donors,
o mix of instruments,
o nature of conditionality (especially SBS / Common Fund),
1
e.g. WAEMU countries do not have access to monetary policy instruments and have limited or no ability to
borrow from the central bank and are therefore more likely to cut investment spending more deeply than
other countries in response to aid shortfalls.
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How Unpredictable Aid Influences Service Delivery
o
o

donor harmonization and alignment, in particular donor coordination mechanisms
and arrangements such as sector budget support, and sector-wide approaches
(SWAps) in study sector(s).
overview of sector performance against Paris Declaration indicators, only if readily
available.
Trends in service delivery: Overall progress against:
o national priority targets (use MDGs if no equivalent set of summary indicators
exists),
o targets in selected study sector(s).
o Additional administrative and statistical data on trends in performance in selected
study sector(s).
3. Planning and budgeting (max. 7 pages)
3.1. Planning and budgeting at national level (max. 3 pages)
An overview of how the national planning and budgeting system operates, with an emphasis on aid
flows and on how the system ‘really’ works, as against formal written statements of the system (cf.
Stevens, 2004).
 How are national policy priorities articulated in theory and in practice? (E.g. national
development plan, annual plans, election manifesto, presidential decree, not written down
in one place).
 How does the MTEF process operate in theory and in reality? How are sector resource
ceilings set and are they credible?
 What factors are taken into account in forecasting the future resource envelope, especially
aid projections, in the short- and medium-term (i.e. the ‘rationale for projections’)? Do
projections involve different treatment of different aid instruments (e.g. programme and
project aid)?
 How does the national budget process operate, with particular reference to budget
execution (cash-based or other) and predictability of releases to MDAs, drawing on any
available PFM diagnostic tools (e.g. PEFA assessments)? To what extent does the
existence of ‘off-system’ aid affect this?
 How is aid information captured by government on-system? (Is there an external assistance
database(s) and are there formal procedures to guide donors in putting their funds on
budget and/or on-treasury?).
 How comprehensive is the capture of aid data on-system? (E.g. how much aid is not
captured, how has this changed over time and does coverage vary by aid instrument?).
 Brief outline of national M&E framework. How reliable and comprehensive are national
service delivery performance indicators and the underlying data (administrative, statistical
or both?).
3.2. Planning and budgeting at sector level (max. 3 pages)
A brief overview of how the planning and budgeting system operates in the sector of choice,
particularly where this deviates from/clashes with the national level process. This section will also
describe the nature of MoF – sector Ministry relations, examining how decisions are taken, by
whom and at what level.
 How are sector policy priorities articulated in theory and in practice (e.g. sector
development plan, annual plans, not written down in one place)?
 If there is a “sector MTEF” process, how does this operate in theory and in reality? Do
resource ceilings differ from those in national documents?
 If different from national level, what factors are taken into account in forecasting the future
sector resource envelope, especially aid projections, in the short- and medium-term? Do
projections involve different treatment of different aid instruments (e.g. programme and
project aid)?
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Methodology for Country Case Studies






If different from national level, how does the sector budget process operate, with particular
reference to budget execution (cash-based or other) and predictability of releases to lower
tiers of government, drawing on any available PFM diagnostic tools (e.g. PEFA
assessments)?
Indicate the channels by which on and off-system resources (both aid and non-aid) flow
through the sector to service delivery units (e.g. flow of funds diagram).
If different from national level, how is aid information captured by the sector on-system?
If different from national level, how comprehensive is the capture of aid data on-system?
(E.g. according to available estimates, how much aid is not captured, how has this changed
over time and does coverage vary by aid instrument?).2
What are the major differences between planning and budgeting at sector and national
level, are there any tensions between the two (particularly in aid management) and if so
what are the effects? How has this changed over time?
Brief outline of sector M&E framework. How reliable and comprehensive are sector service
delivery performance indicators and the underlying data (administrative, statistical or both?)
3.3. Planning and budgeting at sub-national level(s) (max. 1 page)
A brief overview of how the planning and budgeting system operates at the sub-national level, with
particular emphasis on the sector of choice, particularly where this deviates from/clashes with the
process for other sectors.
 Briefly summarise how planning and budgeting actually operates at different tiers of
government (e.g. provincial, district, service delivery unit)? How well is it articulated with
national planning and budget documents (plans, budgets, MTEFs)?
 How are resource ceilings set for different tiers of government?
 How are budget releases made to different tiers of government?
 Are allocated and executed resources sufficient to meet allocated responsibilities or is there
a mis-match?
 To what extent do aid flows impinge upon these allocative mechanism processes?
4. Aid predictability and its impacts at the aggregate level (max. 8 pages)
4.1. Predictability of aid flows at aggregate level (max. 3 pages)
How (un)predictable are non-aid resource flows at the aggregate level?
 Size and frequency of shortfalls and windfalls over time, comparing budgeted amounts to
outturns (1999 - present):
o short-term predictability (1999 - present)
o in-year predictability (1999 – present where data availble)
o reliability
How (un)predictable is aid at the aggregate level?
 Size and frequency of shortfalls and windfalls over time, comparing budgeted amounts to
outturns (1999 - present):
o short-term predictability (1999 - present)
o in-year predictability (1999 – present where data availble)
o reliability
 In summary, can we identify any specific episodes of dramatic aid unpredictability
(surge/windfall or shortfall)? (N.B. see Celasun and Walliser on asymmetric effects of
surges and windfalls).
 What are the major causes of these episodes? (i.e. donor administrative problems, failure
to meet donor conditionality, central bank delay in transferring funds etc.).
Time and resources do not permit a detailed effort to map the extent of ‘off-system’ aid during the country
case studies. We propose to rely on existing estimates, complemented by additional data for very large
programmes (e.g. PEPFAR) where available.
2
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How Unpredictable Aid Influences Service Delivery

Is aid more/less predictable compared with non-aid other revenue sources (c.f. Bulir and
Hamman, 2007)?
How do differences in aid delivery affect aid predictability?
 Permanence/persistence of aid (formal):
o Does aid predictability vary across different donors/creditors?
o How long can different donors make binding written commitments for and does this
match the time horizons of the activities they are funding (N.B. for major donors
only)?
o Medium-term predictability: How far ahead can donors make firm financing
commitments to government? How long are donor programming cycles and do they
align with the government cycle? If not are donors able to overcome this? [N.B. for
major donors only]
o Does aid predictability vary by type of instrument (GBS, SBS, Common Fund,
Project etc.)?
 Permanence/persistence of aid (informal).
o Are there important differences between formal donor/creditor time horizons and
government’s expected time horizons and do these vary by donor or aid instrument?
 How have changes in the capture of aid on-system affected budget predictability?
 Is the increasing proportion of aid channelled through (earmarked) global programs/vertical
funds contributing to/mitigating the predictability of aid flows?
4.2. Impacts of and government response to unpredictable aid (max. 3 pages)
What is the impact of (episodes of) unpredictable aid (surges/windfalls and shortfalls) on budget
allocation and spending patterns, in terms of:
 Inter-sectoral allocation of aid and total expenditure
 Functional composition
 Economic breakdown of expenditure
 Categorical allocation of spending
N.B. for possible measures see PEFA methodology PI-1 Aggregate expenditure outturn compared
to original approved budget, PI-2 Composition of expenditure outturn compared to original
approved budget.
Government response function: what mechanisms, both formal and informal, does government use
to help to mitigate the effects of aid surges/shortfalls at the aggregate level (both pre-emptive and
retrospective)?
 Institutions (not necessarily explicitly designed to address aid unpredictability but may have
useful benefits in this regard) e.g. sector or administrative ceilings
 Rules of thumb e.g. not using aid to finance recurrent budget, systematic discounting
 How is sustainability of large long-term recurrent costs (e.g. staff salaries, drug costs)
affected by medium-term unpredictability?
 Can more predictable and stable aid flows create sustainable fiscal space? What does aid
finance? Does it finance recurrent cost expenditure? (Cf. Penrose, 2008). Does it
compromise the content of the investment/development budget (i.e. by including items of
recurrent nature)?
 Does the fungibility of resources lead to a situation where certain expenditures (e.g. donor
priorities in social sectors) are disproportionately financed by aid flows? Does this leave
them, paradoxically, more vulnerable to aid unpredictability?
 How does the government response affect the management of budget execution (explicitly
identifying whether normal or cash budgeting operates)?
 In summary, does aid unpredictability create/contribute to temporary or permanent systemic
distortions?
4.3. Donors at national level and aid predictability (max. 2 pages)
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Methodology for Country Case Studies
Donor behaviour and mechanisms (e.g. GBS coordination), both formal and informal, and their
effects on: i) aid predictability and; ii) mitigating/exacerbating impacts of aid surges or shortfalls at
the aggregate level:
 How have donor coordination mechanisms influenced the predictability of aid projections?
 Is there a tension between aid predictability and conditionality frameworks and how have
donor coordination mechanisms affected this? (e.g. use of in-year triggers, donors lobbying
for collective punishment of transgressions).
 How have donor coordination mechanisms helped to mitigate/exacerbate the effects of aid
surges/windfalls and shortfalls?
Proliferation of aid delivery channels and fragmentation of aid financed activities (IDA, 2008).
 Proliferation: What is the total number of aid delivery channels and how has this changed
over the period (i.e. bilateral, multilateral, vertical funds, foundations, NGOs)? Express
individual donors’ shares of total aid (Cf. Knack and Rahman, 2004).
 Fragmentation: How has the total number of aid financed activities changed over time?
 How does average aid portfolio size affect predictability?
 Has there been any attempted Division of Labour exercise? If so, what has been the effect
on aid proliferation at sector and national level?
 To what extent do proliferation and fragmentation cause/reduce unpredictability and
exacerbate/mitigate its effects? How do these effects work and what might be done to
address them?
5. Aid predictability and its impacts at the sector level (max. 8 pages)
5.1. Predictability of resource flows at sector level (max. 3 pages)
How (un)predictable are total resource flows at the sector level?
 Size and frequency of shortfalls and windfalls over time, comparing budgeted amounts to
outturns (1999 - present):
o short-term predictability (1999 - present)
o in-year predictability (1999 – present where data availble)
o reliability
 In summary, can we identify any specific episodes of dramatic resource unpredictability?
How (un)predictable is aid at the sector level?
 Size and frequency of shortfalls and windfalls over time, comparing budgeted amounts to
outturns (1999 - present):
o short-term predictability (1999 - present)
o in-year predictability (1999 – present where data availble)
o reliability
 In summary, can we identify any specific episodes of dramatic aid unpredictability? Do
these help to explain episodes of resource unpredictability identified above?
 Comparison between predictability of aggregate and sector allocable aid flows – principally
on-budget, but also bring in off-budget (e.g. vertical fund) aid where information is available.
 Comparison between predictability of resources received from Ministry of Finance
(revenue, GBS, SBS) and aid flows direct to the sector.3 Does the unpredictability of
resource flows influence the sectors preferred mix of aid modalities (e.g. preference for offtreasury common funds)?
How do differences in aid delivery affect aid predictability at the sector level:
 Permanence/persistence of aid (formal):
o Does aid predictability vary across different sector donors/creditors?
3
For sector level data, it is important to be careful with comparisons. If we include of-budget aid in sector
data then this will undermine comparability with aggregate data.
13
How Unpredictable Aid Influences Service Delivery
o



Medium-term predictability: How long can different sector donors make binding
written commitments for and does this match the time horizons of the activities they
are funding? [N.B. for major donors only].
o How long are sector donor programming cycles and do they align with the
government cycle? [N.B. for major donors only]
o Does sector aid predictability vary by type of instrument (GBS, SBS, Common Fund,
Project etc.)?
Permanence/persistence of aid (informal):
o Are there important differences between formal sector donor/creditor time horizons
and government’s expected time horizons and do these vary by donor or aid
instrument?
How have changes in the capture of sector aid ‘on-system’ affected budget predictability?
Is the increasing proportion of sector aid channeled through (earmarked) global
programs/vertical funds contributing to/mitigating the predictability of aid flows?
5.2. Impacts of and sector response to unpredictable aid (max. 3 pages)
What is the impact of (episodes of) unpredictable sector aid (surges/windfalls and shortfalls) on
intra-sectoral budget allocation and spending patterns, in terms of:
 Intra-sectoral allocation of aid and total expenditure
 Functional composition
 Economic breakdown of expenditure
 Categorical allocation of spending at sector level
 How are decisions made, by whom and at what level?
 How does coexistence of on- and off-system aid affect outcomes?
Sector response function to (episodes of) aid shocks (surges/windfalls and shortfalls) at sector
level, in terms of:
 Impact on intra-sectoral allocation of aid and total expenditure
 Impact on categorical allocation of spending at sector level
N.B. for possible measures see PEFA PI-1 Aggregate expenditure outturn compared to original
approved budget, PI-2 Composition of expenditure outturn compared to original approved budget.
Sector response function: what mechanisms, both formal and informal, does the sector Ministry
use to help to mitigate the effects of aid surges/shortfalls at the aggregate level (both pre-emptive
and retrospective)?
 Institutions (not necessarily explicitly designed to address aid unpredictability but may have
useful benefits in this regard) e.g. sector or administrative ceilings
 Rules of thumb e.g. not using aid to finance recurrent budget, systematic discounting
 Mix of aid modalities (e.g. preference for off-treasury common funds over SBS)
5.3. Sector donors and aid predictability (max. 2 pages)
Donor behaviour and mechanisms, both formal and informal, and their effects on aid predictability
and in mitigating/exacerbating impacts of aid surges or shortfalls at the sector level
 How have donor coordination mechanisms (SBS coordination, SWAps) influenced the
predictability of sector aid projections?
 Is there a tension between aid predictability and sector conditionality frameworks and how
have donor coordination mechanisms affected this?
 How have donor coordination mechanisms at sector level helped to mitigate/exacerbate the
effects of aid surges/windfalls and shortfalls
 How has the total number of aid delivery channels changed at country level over the period
i.e. proliferation of bilateral, multilateral, vertical funds, foundations, NGOs?
 How has the total number of aid financed activities changed over time i.e. fragmentation?
 Has there been any attempted Division of Labour exercise? If so, what has been the effect
on aid proliferation at sector and national level?
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Methodology for Country Case Studies

To what extent do proliferation and fragmentation contribute to or cause unpredictability?
Are there instances where the opposite has occurred?
6. Impact on service delivery (max. 5 pages)
Impact of i) specific episodes of aid unpredictability (windfalls/surges and shortfalls) and; ii) preemptive strategies to insure against aid unpredictability.
 What has the experience been of the predictability of resource flows at sub-national tiers of
government (e.g. specific episodes or inherent unpredictability)?
o Are there any systemic distortions at sub-national level arising from the unreliability
of resource flows?
o How has any unreliability affected their capacity to deliver on their mandates?
o Can any unreliability be linked to aid unpredictability (e.g. specific episodes or
inherent unpredictability)?
 What has the experience been of the reliability of resource flows at selected frontline
service delivery unit(s) (e.g. specific episodes or inherent unpredictability)?
o Are there any systemic distortions at service delivery level arising from the
unreliability of resource flows?
o How has any unreliability affected the unit’s capacity to deliver services?
o Can any unreliability be linked to specific episodes of aid unpredictability (e.g.
specific episodes or inherent unpredictability)?
 Overall, can any specific episodes of aid unpredictability be linked to changes in service
delivery at the output level (e.g. on standard health sector indicators)?
 Can any systemic distorions (e.g. as a result of pre-emptive strategies to insure against aid
unpredictability) be linked to changes in service delivery at the output level (e.g. on
standard health sector indicators)?
7. Conclusions and recommendations (max. 3 pages)
A short note bringing out:
 Key conclusions from the case study
 To what extent do lessons emerge from the findings and conclusions for international
practice, both in terms of positive examples to follow and of potential mistakes to be
avoided. To what extent were the outcomes particular to the case chosen or the episodes
studied?
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How Unpredictable Aid Influences Service Delivery
References4
Andrews, M. and Wilhelm, V. (2008) ‘Thinking About Aid Predictability.’ The World Bank, Poverty
Reduction and Economic Management (PREM) Notes, 124.
Bulir, A. and Hamann, A. J. (2008) ‘Volatility of Development Aid: From the Frying Pan to the Fire?’
World Development, 36(10), 2048-2066.
Celasun, O. and Walliser, J. (2008) ‘Predictability of Aid:
Predictability of Aid?’ Economic Policy, 23(55), 545-86.
Do Fickle Donors Undermine the
Helmke, G. and Levitsky, S. (2004) ‘Informal Institutions and Comparative Politics: A research
Agenda.’ Perspectives on Politics, Vol. 2 No. 4, December 2004.
International Development Association (2007) ’Aid Architecture: An Overview of the Main Trends in
Official Development Assistance Flows.’ International Development Association Resource
Mobilisation (FRM), February 2007.
International Monetrary Fund (2005) IMF (2005) ‘The Macroeconomics of Managing Increased Aid
Inflows: Experiences of Low-Income Countries and Policy Implications.’
Killick, T. and Foster, M. (2007) ‘The Macroeconomics of Doubling Aid to Africa and the Centrality
of the Supply Side.’ Development Policy Review, 2007, 25 (2): 167-192.
Knack, S. and Rahman, A. (2005) ‘Donor Fragmentation and Bureaucratic Quality in Aid
Recipients.’
Mokoro (2008) ‘Good Practice Note: Using Country Budget Systems,’ June 2008.
Overseas Development Institute (2009) ‘How Unpredictable Aid Influences Service Delivery:
Literature and Data Review.’ Overseas Development Institute, London, Forthcoming.
PEFA Secretariat (2005) Public Financial Management Performance Measurement Framework,
PEFA Secretariat, World Bank, Washington D.C., June 2005.
Penrose, P. (2008) ‘European Commission Budget Support Programmes: Nature, Dialogue and
Design’, June 2008.
Stevens, M. (2004) ‘Institutional and Incentive Issues in Public Financial Management Reform in
Poor Countries.’ October 12th 2004, funded by the PEFA Programme.
Williamson, T. (2007) ‘Putting Aid on Budget: A Case Study of Uganda.’ A Study for the
Collaborative Africa Budget Reform Initiative (CABRI) and the Strategic partnership with
Africa (SPA), 2nd November 2007.
4
See literature and data review for a full list of readings on aid unpredictability and service delivery.
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Methodology for Country Case Studies
Annex 1: Glossary of terms
Aid modality or aid instrument: The way donor aid funds are channelled to the activities to be
funded. Source: Danida Glossary.
Aid: The words "aid" and "assistance" refer to flows which qualify as Official Development
Assistance (ODA) or Official Aid (OA). Source: OECD DAC Glossary.
Cash budgeting: To ensure effective budget implementation, the authority to spend must be given
to agencies on time. Funds should be released in conformity with budget authorizations… sound
cash management does not mean “cash budgeting” or “cash rationing”. In some countries, funds
are released to line ministries through day-to-day cash rationing because of fiscal problems or an
overestimated budget. Where a centralized Treasury system exists, this mechanism consists of an
ad hoc selection of agencies to which cash will be transferred or a selection of the invoices to be
paid. In some countries, this selection is made by a committee or a group composed of the
Treasury Head, the Minister of Finance, and the Prime Minister. The “effective cash budget”
formulated implicitly through this process is substituted for the authorized budget. Making budgets
on a daily basis through such mechanisms violates informal contracts in budgeting, between the
central agencies and the spending agencies, and the policy commitments stated in the budget.
Under cash rationing mechanism, funds are often released on emergency and political grounds,
discarding the priorities defined in the budget. The budget resulting from these day-to-day
decisions may be quite different from the budget approved by the Parliament. Moreover, cash
rationing can not solve the problems it is meant to solve, since spending agencies can continue to
make commitments according to the budget. They accumulate arrears, but comply with budget
procedures. Such situations are (or were) met in several transition economies. Source: SchiavoCampo and Tomassi (1999; pp. 149 - 150).
Channels of aid disbursement: There are three broad disbursement channels for aid: (i) Channel
1 is the normal channel for government’s own-funded expenditures. Aid is disbursed to
government’s finance ministry (or “treasury”). Funds may or may not be earmarked. These funds
are not necessarily “on budget” such as e.g. UN system projects that follow “national execution”
procedures and are typically off treasury and also off system in other important dimensions.
(ii) Channel 2 involves provision of funding direct to MDAs and managed through special accounts
outside of the regular government system. Funds are held by a government body but don’t follow
normal government procedures. (iii) Channel 3 expenditures are undertaken by a donor agency or
by an NGO on its behalf. Government receives assets or services in-kind but does not handle the
funds itself. Source: Mokoro (2008).
Commitment (aid): A firm obligation, expressed in writing and backed by the necessary funds,
undertaken by an official donor to provide specified assistance to a recipient country or a
multilateral organisation. Bilateral commitments are recorded in the full amount of expected
transfer, irrespective of the time required for the completion of disbursements. Commitments to
multilateral organisations are reported as the sum of (i) any disbursements in the year reported on
which have not previously been notified as commitments and (ii) expected disbursements in the
following year. Source: OECD DAC Glossary.
Comprehensiveness: is one of the characteristics of a robust PEM system. The budget should
capture all activities of government. Effective resource allocation through the budget process
requires current and capital expenditure decisions to be linked and assessed together. Source:
DFID (2001).
Conditionalities: Stipulations, or provisions, that needs to be satisfied to trigger aid disbursement.
Source: Danida Glossary.
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How Unpredictable Aid Influences Service Delivery
Contingent liability: Contingent liabilities are obligations triggered by a discrete but uncertain
event. They are therefore possible obligations whose existence will be confirmed only by the
occurrence of one or more uncertain future events not wholly within the government's control (this
should be contrasted with direct liabilities, which are predictable obligations that will arise in any
event). There is a second useful distinction to be made between explicit liabilities defined by law or
contract that the government is legally obliged to settle when due and implicit liabilities which the
government may be obliged to meet owing to public expectations and political pressures. Source:
Polackova (1998).
Development budget: public investments brought together in one plan intended to develop the
economic and social potential of the whole economy or a specific area. They often include both
capital and current spending on investment projects. In developing countries they are often mainly,
but not exclusively, financed externally. Source: DFID (2001).
Discretion: the power or right to decide or act according to one's own judgment; freedom of
judgment or choice. In the context of public expenditure, discretion is the ability of the government
or a government entity to allocate fund available to it according to its own priorities during planning
and budget formulation processes.
Donor Harmonization: refers to the efforts by both donors and partner countries to integrate all
aspects of their aid, including adopting common systems and procedures, adopting joint working
arrangements that include shared decision-making, and sharing information. Effective
harmonization requires greater ownership of the development agenda by partner governments and
the use of national systems as a starting point for all development efforts in a country.
Harmonization implies a shift over time toward more program-based approaches and direct budget
support and away from individual, isolated projects. It includes not only donor coordination, but
also bringing into alignment (without necessarily standardizing) donor operational policies,
practices, and procedures with those of developing country partners. In most developing countries,
harmonization will require significant capacity development efforts to improve government policies,
institutions, processes and human resources. Harmonization can also refer to efforts within
individual donor systems to integrate their development assistance actions (e.g. alignment of
various channels of assistance). Source: CIDA (2004).
Economic classification: The current IMF GFS Manual refers specifically to a “classification of
expenditure by the nature of transaction, that is, whether requited or unrequited, for current or
capital purposes, kind of goods or services obtained, and sector or sub-sector receiving
transactions” (p. 325). It is generally used to identify the nature and economic effects of
government operations. Though not formally described as “economic” in the GFS, the classification
of revenue into current (tax and non-tax), capital, and grants serves a similar purpose. Source: IMF
(2007).
Economy (of public expenditure): Absence of waste for a given output. Note: An activity is
economical when the costs of the scarce resources used approximate the minimum needed to
achieve planned objectives. Source: OECD-DAC (2002).
Efficiency (of public expenditure): A measure of how economically resources/inputs (funds,
expertise, time, etc.) are converted to results. An efficient activity maximises output for a given
input, or minimises the unit cost of output. Sources: OECD-DAC (2002) and Schiavo-Campo and
Tommasi (1999).
Fiscal space: Room in a government’s budget that allows it to provide resources for a desired
purpose without jeopardising the sustainability of its financial position or the stability of the
economy. Source: Heller (2005).
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Methodology for Country Case Studies
Fiscal sustainability: A set of policies is sustainable if a borrower is expected to be able to
continue servicing its debt without an unrealistically large future correction to the balance of income
and expenditure. Source: IMF (2007).
Fragmentation: The growth in the number of donor aid activities. Source: IDA (2007).
Functional classification: The current GFS Manual refers specifically to the Classification of the
Functions of Government (COFOG), which is the international standard for classifying
expenditures of government according to broad purposes for which transactions are undertaken. It
is generally used to measure the allocation of resources by government for the promotion of
various activities and objectives (such as health, education, and transportation and
communication). Source: IMF (2007).
Fungibility: Fungibility of aid comprises three elements. General fungibility arises where aid
intended for a general purpose, investment spending, is actually used for a different purpose,
consumption spending. If donors believe that aid must finance investment if it is to impact on
growth, they will believe that aid redirected to recurrent spending undermines the (growth)
effectiveness of aid. A more specific case is categorical fungibility, where aid intended for a
particular spending heading, such as health, is used for a different heading, in particular one that
the donor does not intend to support, such as security or wages. Again, donors will believe that this
undermines the development effectiveness of their aid. The third issue is additionality (see
definition). It is important to note that fungibility per se is not concerned with the misuse of aid
(such as corruption), but simply with misallocation, or specifically non-additionality. Source:
Morrisey (2005).
Medium Term Expenditure Framework (MTEF): There is no single, concise definition of the term
‘MTEF’. It represents a set of broad principles for sound budgeting that are implemented in
different ways in different institutional settings. At its heart, the MTEF approach seeks to link
expenditure allocations to government policy priorities using a medium-term (i.e. three to five year)
perspective for budget planning and preparation. This typically involves some combination of: (i) a
unified ‘whole-of-government’ approach that encompasses all sectors; (ii) a ‘top-down’ hard budget
constraint consistent with macroeconomic sustainability; (iii) a ‘top-down’ set of strategic policy
priorities; (iv) ‘bottom-up’ forward estimates of the costs of existing policies, programmes and
activities over the medium-term; (v) a single nationally owned political process at the centre of
government that reconciles the bottom-up and top-down components; (vi) a strong and clear link
between MTEF projections and the annual budget process, so that multi-annual targets (duly
updated for changes in the macroeconomic situation) set in the previous years should form the
basis upon which the budget is prepared; (vii) a focus on results (i.e. outputs and outcomes).
Source: Bird et al. (2008).
On-system is used here to embrace all elements of ‘on-budget’ covered by the recent SPA/CABRI
study (Mokoro, 2008). It is preferred to ‘on-budget’ since it avoids the ambiguity that arises from
the use of ‘on-budget’ to refer to both to the capture of aid on the whole of the PFM system and to
its capture on only one of the elements (‘on budget documents’). Following the Accra High Level
Forum in September 2008 there has also been a stronger emphasis on use of national M&E
systems as well as PFM systems. The dimensions of ‘on-system’ are summarised in Table 1. As
discussed above, we are primarily interested in the ‘on-budget documents’, ‘on-parliament’ and ontreasury’ dimensions of ‘off-system’.
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How Unpredictable Aid Influences Service Delivery
Table 1: Different Dimensions of “On System”/Capturing Aid
Term
Definition
On plan
Programme and project aid spending is integrated into spending
agencies' strategic planning and supporting documentation for policy
intentions behind the budget submissions.
On budget
documents
External financing, including programme and project financing, and its
intended use are reported in the budget documentation.
On parliament
External financing is included in the revenue and appropriations
approved by parliament.
On procurement
External financing follows government’s standard procurement
procedures.
On treasury
External financing is disbursed into the main revenue funds of
government and managed through government’s systems.
On accounting
External financing is recorded and accounted for in the government’s
accounting system, in line with the government’s classification system.
On audit
External financing is audited by the government’s auditing system.
On report
External financing is included in ex post reports by government.
On M&E
Conditionality associated with aid delivery uses government M&E
indicators.
Note: This list is not exhaustive and there are other dimensions of government systems that may also be
relevant.
Source: Good Practice Note: Using Country Budget Systems (Mokoro Ltd, 2008).
Permanence/persistence: able to exist for an indefinite duration.
Predictability of aid refers to whether the aid received equates to the aid anticipated. Both the
amount and the timing of any differences are relevant factors in assessing predictability. The
difference between aid commitments and disbursements, as recorded in the OECD-DAC statistics,
is often used as a proxy for predictability (e.g. Celasun and Walliser, 2008). There are three
commonly used measures:
 In-year predictability: typically measures how quarterly disbursements correspond to
quarterly commitments.
 Short-term predictability: how annual disbursements correspond to annual commitments.
 Medium-term predictability: measures by how far ahead donors are able to provide firm
financing commitments.
Predictability, following Andrews and Wilhelm (2008), also relates to whether aid is
reliable/unreliable and expected/unexpected:
 Reliability refers to the extent to which aid commitments are a reliable indicator of aid
disbursements. Note for example that if disbursements are consistently the same
proportion below commitments then they could still be regarded as reliable.
 Expectations, and in particular the notion of unexpected aid, refer to the understanding by
recipients about how much aid they will receive, at which times and over which periods.
Such expectations may be based on the credibility of commitment schedules or on other
mechanisms for projecting aid flows (e.g. systematic adjustments based on experience).
Proliferation: The growth in the number of channels of donor aid flows. Source: IDA (2007).
Recurrent budget: expenditures on wages and salaries, operations and maintenance that is not of
an investment nature. Source: DFID (2001).
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Methodology for Country Case Studies
Sector-Wide Approach (SWAp): The defining characteristics of a SWAp are that all significant
funding for the sector supports a single sector policy and expenditure programme, under
Government leadership, adopting common approaches across the sector, and progressing towards
relying on Government procedures to disburse and account for all funds. This working definition
deliberately focuses on the intended direction of change rather than just the current attainment.
Most programmes, even quite well established ones, are in the midst of a process for moving
overtime towards broadening support to all sources of funding, making the coverage of the sector
more comprehensive, bringing ongoing projects into line with the SWAp, and developing common
procedures and increased reliance on Government. A SWAp is not a distinct financing modality
and should therefore not be confused with pooled funds. Further, the existence of a SWAp does
not imply the need for a pooled fund. Sources: Foster (2000) and IDD and Associates (2006).
Transactions costs: The direct and indirect costs incurred by aid providers and recipients, which
are specifically associated with the management of aid and the aid partnership generally. Costs
may be in terms of funds, time, use of resources, efficiency losses, etc. Often, the term is used
particularly about the transaction costs on the recipient side. Source: Danida Glossary.
Value for money: the achievement of economy, efficiency and effectiveness in the use of
resources, in order to achieve desired outcomes at the lowest cost. Source: DFID (2001).
Volatility of aid refers to periodic (e.g. year-on-year) variation in aid disbursements (for example,
measured by the coefficient of variation).
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How Unpredictable Aid Influences Service Delivery
Annex 2: Proposed data requirements for case studies
Country Context
 Poverty trends (headcount) from HH Surveys
 Headline economic indicators (real GDP, real GDP per capita, inflation) [IMF-AFREO] 1999
– 2009
 Headline fiscal indicators (total revenue, total spending, fiscal deficit before grants, fiscal
deficit after grants, interest payments) [IMF-AFREO] 1999 – 2009
 Stock of debt (external) [Bank of Uganda] 1999 – 2009
 Stock of debt (domestic) [Bank of Uganda] 1999 – 2009
 Estimated payment arrears
 Aggregate aid flows (absolute terms, % of expenditure, % GDP) 1999 – 2008
 Aid flows disaggregated by individual donor 1999 – 2008
 Aid volumes in selected sectors (absolute terms, % of expenditure, % GDP) 1999 – 2008
 Total number of donors over time
 Mix of aid instruments over time (as a % of total aid)
 Performance against national targets such as PEAP
 Performance against sector targets
 Routinely collected health sector administrative data
 Statistical data providing evidence on health indicators (e.g. DHS, HH Survey, census) for
triangulation with administrative data
Aid predictability and its impact at the aggregate level
 Past MTEF projections as available
 Budget allocations as appropriated by parliament (aggregate, sector totals, transfers to
districts, by administrative, economic and functional classification and by aid instrument)
1999 - 2008
 Specific discount rates applied by MoF to donor commitments (either by donor or by aid
modality) and how these have changed over time
 Budget outturns (against above appropriations) 1999 – 2008
 In-year budget execution data if available (e.g. quarterly timing of disbursments against
commitments, with particular emphasis on aid flows) 1999 – 2008
 Donor commitment time horizons / donor programming cycles
 Estimate of total number of aid delivery channels (use total donors?)
 Estimate of total number of aid financed activities
 Estimate of proportion of off-system aid against the different dimensions (budget
documents, parliament, treasury etc.)
Aid predictability and its impact at the sector level
 Health sector MTEF projections as available (if different from national)
 Budget allocations as appropriated by parliament (intra sectoral information, by
administrative, economic and functional classification) 1999 - 2008
 Health sector own revenues (budgeted and outturn) 1999 – 2008
 Commitments and disbursements of vertical funds (all available data)
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Methodology for Country Case Studies
Annex 3: Proposed background documentation for Uganda
country case study
Macroeconomy and Political Economy
Barkan, J. D., Simba Kayunga, S., Ng’ethe, N. and Titsworth, J. (2004) ‘The Political Economy of
Uganda: The Art of Managing a Donor-Financed Neo-Patrimonial State.’ Final Draft, July 6th
2004.
Celasun and Walliser (2005) ‘Predictability of Budget Aid: Experience from Eight African
Countries.’
IMF (2009) 2008 Article IV Report.
IMF (2007) Aid Inflows—The Role of the Fund and Operational Issues for Program Design
Background Paper (Including Ghana and Uganda case studies).
IMF (2005) Macroeconomics of Managing Increased Aid Inflows.
Moncrieffe J. (2004) ‘Uganda’s Political Economy: A Synthesis of Major Thought.’
OPM (2008) PEAP Evaluation Synthesis.
OPM (2008) PEAP Evaluation: Institutional Arrangements Theme Paper
OPM (2008) PEAP Evaluation: Partnerships Theme Paper
OPM (2008) PEAP Evaluation: Political Economy Theme Paper
OPM (2008) PEAP Evaluation: Partnerships Theme Paper
Aid Environment
Afrodad (2007) ‘A Critical Assessment of Aid Management and Donor Harmonisation. The Case of
Uganda.’
de Renzio, P. (2006) ‘The primacy of domestic politics and the dilemmas of aid: What can donors
do in Ethiopia and Uganda?’ Opinion, Overseas Development Institute, February 2006.
Government of Uganda (2008) Evaluation of the Implementation of the Parise Declaration.’
ODI (2007) Division of Labour Exercise for Uganda. Interim Report
OECD (2008) ‘2008 Survey on Monitoring the Paris Declaration: Uganda Country Chapter.’
Schneider, B. (2006) ‘An Analysis of Donor Flows: Case Study of Uganda.’ UNU WIDER
conference, 2006.
Vargas Hill (2005) Assessing the Rhetoric and Reality in the Predictability of Aid.’ HDR 2005
Background Paper.
Williamson (2007) Minding the Gaps: Uganda Case Study
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How Unpredictable Aid Influences Service Delivery
PFM
Hubbard (2007) Putting the Power of Transparency in Context: Information's Role in Reducing
Corruption in Uganda's Education Sector - Working Paper 136:
http://www.cgdev.org/content/publications/detail/15050
Office of the Auditor General, 2008, PEFA “LITE” Public Expenditure and Financial Accountability
Appraisal of the Financial Management Performance, Kampala-Uganda
Regional Forecasts Limited, 2007, Northern Uganda Public Expenditure Review (NUPER), Final
report for Uganda Multi-Donor Group
Reinikka, R and Svensson, J, 2003, The power of information: Evidence from a newspaper
campaign to reduce capture, Working Paper, IIES, Stockholm University:
http://www.iies.su.se/~svenssoj/Information.pdf
Williamson, T, 2008, “Putting Aid on Budget: A Case Study of Uganda.” A study prepared for the
Collaborative Africa Budget Reform Initiative and for the Strategic Partnership with Africa.
Mokoro Ltd., Oxford, UK
Wynne, Andy. 2005. “Public Financial Management Reforms in Developing Countries: Lessons of
Experience from Ghana, Tanzania and Uganda.” African Capacity Building Foundation
Working Paper No 7.
Health
Anon (2007) ‘Identified areas for possible efficiency gains in the public health sector in Uganda.’
HealthNet Consult (2007) Assessment of Public Expenditures for the Health Sector in Uganda
2003/04 – 2005/06, May 2007.
MoH (2005) Health Sector Strategic Plan 2005/06 – 2009/10 Volume I.
Ortendahl (2007) ‘The Uganda Health SWAp: New Approaches for a More Balanced Aid
Architecture.’
World Bank (2008) DRAFT UGANDA Focus on Health in the Budget PUBLIC EXPENDITURE
REVIEW 2008 CHAPTER 3: GETTING MORE HEALTH FROM THE BUDGET.
Yates, R. Et Al (Undated) Health care outputs have doubled in Uganda: What has been the role of
health financing reforms?
24