metadata: authors: 0: author: Ishihara,Yoichiro
count: World
docna: 0: docna: Identifying aid effectiveness challenges in
            fragile and conflict-affected states
docty: Policy Research Working Paper
subtopic: Economic Conditions and Volatility,Public Sector Economics,Public Financial Management,Public Finance Decentralization and
            Poverty Reduction
teratopic: Private Sector Development,Macroeconomics and Economic Growth,Social Protections and Labor,Finance and Financial Sector Development
abstracts: cdata!: Fragile and conflict-affected states
            face daunting challenges for development. Aid has a greater
            importance on development in these states than in others,
            and therefore aid effectiveness management and delivery of
            aid  bears serious consideration. Despite its significance,
            aid effectiveness is appreciably lower in fragile and
            conflict-affected states than in others. What are the key
            aid effectiveness challenges in these states and how can
            these issues be better addressed? As important initial
            steps, this paper aims to identify (i) aid effectiveness
            challenges facing fragile and conflict-affected states and
            (ii) good aid effectiveness examples using the results of
            the Survey on Monitoring the Paris Declaration on aid
            effectiveness, which was designed as a mechanism to support
            global and country level accountability. Both fragile and
            conflict-affected states (recipients) and development
            partners (providers) are mutually accountable for aid
            effectiveness; therefore, this paper focuses on both sides.
            While the analysis confirms the significantly lower aid
            effectiveness performance in fragile and conflict-affected
            states -- especially on aid on budget, aid predictability,
            and use of country systems -- good performance examples in
            several of these states are identified. The aid
            effectiveness performance of development partners in fragile
            and conflict-affected states differs significantly across
            different groups. Multilateral development banks and other
            multilateral organizations perform better on average than
            bilateral organizations and vertical funds. Disaggregation
            of development partner performance at the institutional
            level and the partner country level enables the analysis
            successfully to identify good performance examples. In using
            the results of this paper to improve aid effectiveness, key
            additional steps should include (i) considering whether the
            identified challenges are essential; (ii) analyzing the
            factors/reasons behind good performance examples; and (iii)
            discussing whether good performance examples can provide
            lessons that can be adapted and applied.
repnme: repnme: Identifying aid effectiveness challenges in
            fragile and conflict-affected states
display_title: Identifying aid effectiveness
            challenges in fragile and conflict-affected states
listing_relative_url: /research/2012/04/16223318/identifying-aid-effectiveness-challenges-fragile-conflict-affected-states
topicv3: Macroeconomic Vulnerability and Debt
            m1326057 1104,Public Finance Management m1326316 716
publishtoextweb_dt: 2012-04-01T00:00:00Z
historic_topic: Private Sector Development,Macroeconomics and Economic Growth,Social Protections and Labor,Finance and Financial Sector Development
no_of_pages: 29
author_keys: 0: author_key: 605091
model_extractions: WPS6037 Policy Research Working Paper 6037 Identifying Aid Effectiveness Challenges in Fragile and Conflict-Affected States _Yoichiro Ishihara_ The World Bank Operations Policy and Country Services Corporate Reform and Strategy Unit April 2012
Policy Research Working Paper 6037

# **Abstract**

Fragile and conflict-affected states face daunting challenges for development. Aid has a greater importance on development in these states than in others, and therefore aid effectiveness—management and delivery of aid—bears serious consideration. Despite its significance, aid effectiveness is appreciably lower in fragile and conflict-affected states than in others. What are the key aid effectiveness challenges in these states and how can these issues be better addressed?

As important initial steps, this paper aims to identify (i) aid effectiveness challenges facing fragile and conflictaffected states and (ii) good aid effectiveness examples using the results of the Survey on Monitoring the Paris Declaration on aid effectiveness, which was designed as a mechanism to support global and country level accountability.

Both fragile and conflict-affected states (recipients) and development partners (providers) are mutually accountable for aid effectiveness; therefore, this paper focuses on both sides. While the analysis confirms the significantly lower aid effectiveness performance in fragile and conflict-affected states—especially on aid on budget, aid predictability, and use of country systems—good performance examples in several of these states are identified. The aid effectiveness performance of development partners in fragile and conflict-affected states differs significantly across different groups. Multilateral development banks and other multilateral organizations perform better on average than bilateral organizations and vertical funds. Disaggregation of development partner performance at the institutional level and the partner country level enables the analysis successfully to identify good performance examples. In using the results of this paper to improve aid effectiveness, key additional steps should include (i) considering whether the identified challenges are essential; (ii) analyzing the factors/reasons behind good performance examples; and (iii) discussing whether good performance examples can provide lessons that can be adapted and applied.

This paper is a product of the Corporate Reform and Strategy Unit, Operations Policy and Country Services. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at yishihara@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Identifying Aid Effectiveness Challenges in Fragile and Conflict-Affected States**

# Yoichiro ISHIHARA<sup>1</sup>

World Bank Email: yishihara@worldbank.org

**JEL:** F35, O10, O19

**Key Words** : Aid Effectiveness, the Paris Declaration Survey, Fragile and Conflict-Affected States **Sector Board** : Economic Policy (EPOL)

> 1 Yoichiro Ishihara (Sr. Economist, OPCS) is the author of this paper.  The author is grateful for comments from Steve Knack (Lead Economist, DECHD), Gary Milante (Sr. Economist, OPCFC) and Matthew Eldridge (JPA, OPCS).  The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent.  This paper is still work in progress and therefore not for quotation.  Comments on this paper should be addressed to Yoichiro Ishihara (yishihara@worldbank.org)
# **1. Introduction**

Fragile and conflict-affected states (FCS)<sup>2</sup> face daunting challenges for development. The international community has been increasing its focus on FCS and has provided them with significant amounts of aid. Recently, FCS are receiving 30 percent of total Official Development Assistance (ODA)<sup>3</sup> . However, the increasing attention and resources have not yet translated into significantly improved development results. One and a half billion people live in FCS and they remain the group furthest away from achieving the Millennium Development Goals (MDGs)<sup>4</sup> . The contrast between the increasing focus/aid and development results leads to a critical question: Is aid effective enough to address the development challenges in FCS?

The importance of aid effectiveness in FCS is emphasized in ̳A New Deal for engagement in fragile states‘, endorsed by more than 40 partner countries and development partners since it was officially introduced at the 4<sup>th</sup> High Level Forum (HLF-4) on Aid Effectiveness in Busan, Korea in November 2011. While the relationship between aid and development is not straightforward, the improvement of aid effectiveness – defined as the management and delivery of aid – is rationally linked to improved development results<sup>5</sup> .

Identifying key aid effectiveness challenges is the critical first step for both FCS (recipients of aid) and development partners (providers of aid). This is the first of two main purposes of this paper. The second is an attempt to identify good performance examples in this area, as learning from each other‘s experiences is an important and practical step to improve aid effectiveness.

In order to serve for these purposes, this paper relies on quantitative results generated through the Survey on Monitoring the Paris Declaration (the PD survey) given the survey‘s three key advantages. First, it has comprehensive country coverage with 78 countries participating in the latest survey round in 2011. Second, as it was conducted three times – in 2006, 2008 and 2011 – it allows us to conduct some degree of time series analysis over the past half-decade. Third, it has a comprehensive coverage of aid effectiveness issues, consisting of 15 indicators (including subindicators). Among the 15 indicators, this paper selects 10 which directly relate to the delivery and management of aid. However, as the indicators have different definitions and methodology, they cannot be directly compared to each other. Therefore, this paper translates indicator values into standardized scores so that indicators can be more easily compared.

As both recipients of aid (FCS) and providers of aid (development partners) are mutually accountable for aid effectiveness, analyses are conducted by focusing on both sides of the equation. First, performance in 2010 is compared across partner countries and indicators, which enables us to

> 2 This paper uses the World Bank classification of FCS in FY2012.

> 3 <u>A New Deal for engagement in fragile states</u>

> 4 <u>World Development Report 2011: Conflict, Security and Development (World Bank)</u>

> 5 <u>The World Bank defines aid effectiveness as</u> ― a cross-cutting mandate for partner countries, donors, and other aid providers- including the Bank; embodying a reform agenda to better deliver and manage aid‖

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identify not only performance by country but also by regions, country groups (IDA vs. IBRD, FCS vs. non-FCS), and indicators. The comparison between FCS and non-FCS confirm that performance in FCS significantly lags behind that of non-FCS in all regions. Second, to identify the areas of FCS challenges, FCS performance is compared across 10 indicators. Among the indicators, FCS challenges emerge in ̳aid flows are aligned with national priorities (aid on budget)‘, ̳aid predictability‘ and ̳use of country procurement systems‘. Third, the results in FCS are disaggregated by country and indicator so that FCS will be able to find good performance examples among themselves (albeit with the need for significant contextualization). Fourth, the performance between 2005 and 2010 is compared for countries participated in both the 2006 and 2011 surveys. Although only three FCS (Afghanistan, Burundi and Democratic Republic of Congo) participated in both surveys, their progress between the periods was below average, suggesting that fragility and conflict negatively acts as a drag on improvements of aid effectiveness.

Turning to development partner performance in FCS, they are first categorized into 4 groups (bilaterals, MDBs, other multilateral organizations (MOs), and vertical funds). MDBs and other MOs perform better collectively than the overall average, while bilaterals and vertical funds perform below the average. Second, further disaggregation by development partner, indicator and partner country enables us to identify strengths and challenges among the development partners, and also distinguish there are good performance examples. In aggregate, the World Bank performs best among the 32 selected development partners. In addition, the Inter-American Development Bank (IADB) performs especially well on indicators 7 (aid is more predictable); 9 (use of common arrangements or procedures) and 10b (joint country analytics work). At the partner country level, specific examples of good performance can be found. For instance, the indicator 7 (aid is more predictable) performances of Japan in the Democratic Republic of Congo, the African Development Bank in Guinea-Bissau, the World Bank in Sierra Leone, the United Nations in Sudan and TimorLeste, and Australia in Timor- Leste are especially strong.

After the introduction, the second section examines the importance of aid effectiveness in FCS. Section three explains the methodology and data sources used in this paper. Section four provides analyses of aid effectiveness performance for both partner countries and development partners. This is followed by a presentation of conclusions in section five.

# **2. Importance of Aid Effectiveness in FCS**

The importance of aid effectiveness in FCS is articulated in the New Deal which has been endorsed by more than 40 FCS and development partners (including the World Bank) since HLF-4 in November 2011. The New Deal states that ―We commit to build mutual TRUST by providing aid and managing resources more effectively and aligning these resources for results‖. In the New Deal, 3
TRUST stands for Transparency, Risk management, Use of country systems, Strengthening capacities and Timely and predictable aid.

The focus on aid effectiveness at the political level articulated in the New Deal is supported by two indicators: the share of net ODA in Gross National Income (GNI) and net ODA per capita. The comparison between FCS and non-FCS below shows that both indicators are significantly higher for FCS.

**Figure 1: The Importance of Aid in FCS**

<!-- Start of picture text --> Net ODA per capita ($)<br>1000<br>: FCSs<br>: Non-FCSs<br>FCS Ave $197<br>(Median $77)<br>100 Non-FCS Ave<br>$101<br>(Median $50)<br>10<br>1<br>0.01 0.1 1 Non-FCS Ave 10 FCS Ave 100<br>5.3% 19.7%<br>(Median (Median<br>2.6%) 14.2%)<br>Net ODA % GNI<br>0.1<br><!-- End of picture text --> _Source: Author’s Calculation based on the World Bank database_ In Figure 1, the horizontal axis shows net ODA in GNI in log, and the vertical axis shows the net ODA per capita in US$. In order to avoid fluctuations across years, data in these indicators uses annual average between 2005 and 2009. Twenty-nine countries marked in red are FCS and 106 countries marked in blue are non-FCS.

The unweighted average net ODA as a share in GNI reaches almost 20 percent in FCS, which is more than three times as high as in non-FCS (5.5 percent). The unweighted net ODA per capita in FCS (US$197) is almost twice compared with that in non-FCS (US$101). Medians of these indicators show that while the gap between FCS and non-FCS is narrower on net ODA per capita, the gap is wider on net ODA as a share of GNI. These indicators show that aid effectiveness plays a relatively more significant role in FCS than in non-FCS.

4
# **3. Data and Methodology**

# **(1) Data**

In light of the significant relevancy of aid effectiveness issues in FCS relative to non-FCS, a critical question is whether aid is more effective in FCS than non-FCS. In order to measure _relative_ aid effectiveness performance in FCS vis-à-vis non-FCS, this paper uses the results of the PD survey due to its three advantages.

First, it is the most comprehensive survey on aid effectiveness, with 15 indicators (including subindicators) covering the five aid effectiveness principles agreed in the Paris Declaration<sup>6</sup> , namely ownership, alignment, harmonization, managing for results, and mutual accountability<sup>7</sup> . Second, it has had a significant and increasing participation from both partner countries and development partners. The number of participating countries increased from 33 in the 2006 baseline survey to 55 in the 2008 survey and 78 in the 2011 survey<sup>8</sup> . More than 50 development partner participated in the 2011 survey. The 2011 survey captured US$70 billion of aid which was about three quarters of the core aid provided to developing countries worldwide (OECD, 2011, p.18). Third, it was conducted three times, in 2006 (for 2005 baseline data); 2008 (for 2007 data); and 2011 (for 2010 data). Three surveys allow us to conduct a comparison between 2005 and 2010 (although each round of the survey had different country coverage).

Among the 15 indicators, 10 indicators are relevant for the analysis of this paper, as they measure the management and delivery of aid while the remaining 5 measure quality of country systems etc. (Table 1).

**Table 1: Ten PD Survey Indicators**

|**Principle**|**Indicators**|**How Measured**|
|---|---|---|
|Alignment|**Ind 3:**Aid flows are aligned with national<br>priorities (aid on budget)|Aid flows reported in the annual budget by<br>government/aid<br>flows<br>actually<br>disbursed<br>by<br>development partners (%)|
|Alignment|**Ind 4:**Strengthen capacity by coordinated<br>support (technicalassistance)|Amount of coordinated technical cooperation /<br>totaltechnicalcooperation(%)|
|Alignment|**Ind 5a: **Use ofcountryPFMsystems|Use of PFM/totalassistance (%)|
|Alignment|**Ind 5b:**Use of country procurement<br>systems|Use of procurement / total assistance (%)|
|Alignment|**Ind 6:**Strengthen capacity by avoiding<br>parallel<br>project<br>implementation<br>units<br>(PIUs)|Number of parallel PIUs|
|Alignment|**Ind 7:**Aid is more predictable|Actual<br>aid<br>flows<br>recorded<br>by<br>the<br>government/scheduled aid flows by development<br>partners (%)|
|Alignment|**Ind8:**Aid is untied|OECD-DAC data|
|Harmonization|**Ind 9:**Use of common arrangements or<br>procedures (program-based approaches—<br>PBAs)|Program-based approaches (budget support + non-<br>budget support PBAs)/total assistance (%)|

> 6 <u>The Paris Declaration on Aid Effectiveness</u>

> 7 Appendix 1 has list and brief explanations of 15 indicators.

> 8 Seventy-eight countries include both Sudan and South-Sudan.  As Sudan data includes South-Sudan, this paper used data of 77 countries excluding South Sudan in the 2011 survey.

5
|**Principle**|**Indicators**|**How Measured**|
|---|---|---|
|Harmonization|**Ind 10a:**Joint missions to the field|Number of joint missions/total number of missions<br>(%)|
|Harmonization|**Ind 10b:**Joint country analytic work|Number of joint analytic work /total number of<br>analytic work(%)|

_Source: World Bank (2011, p.4), see Appendix 1_ While the results of the PD survey provide useful data sources to track progress against the commitments in the Paris Declaration, there are some limitations (World Bank, 2011b). The limitations include (i) the fact that the PD survey tracks only selected PD commitments and does not cover many commitments identified as important for aid effectiveness by the subsequent Accra Agenda for Action (AAA) in 2008; and (ii) methodological concerns regarding some indicators. For example, indicator 3 on ̳aid flows aligned to national priorities‘ is actually more of a measure of aid on budget then alignment per se. Moreover, not only does this not measure what was originally intended, but it even oversimplifies the concept on aid on budget. Therefore, while the advantages of the results of the PD survey still hold, the results of the analysis using the results of the PD survey – including the ones in this paper - need to be carefully interpreted.

The results of the 2011 survey are available for 77 partner countries and 33 selected development partners<sup>9</sup> . Table 2 and 3 summarize the profiles of partner countries and development partners.

**Table 2: Profile** **<u>of Partner Countries which Participated in the 2011 PD survey</u>**

||T|otal|o/w IDA<br>(incl.|eligible<br>blend)|F|CS|
|---|---|---|---|---|---|---|
||No.|%|No.|%|No.|%|
|Africa (AFR)|37|48%|32|42%|10|13%|
|EastAsia andPacific|13|17%|10|13%|2|3%|
|Europe and Central Asia|8|10%|6|8%|2|3%|
|Latin America and Caribbean|11|14%|4|5%|1|1%|
|Middle East and North Africa|4|5%|0|0%|1|1%|
|South Asia|4|5%|4|5%|1|1%|
|**Total**|**77**|**100%**|**56**|**73%**|**17**|**22%**|

_Source: OECD (2011), World Bank classification_

**Table** **<u>3: Profile of Selected Development Partners which Participated in the 2011 PD survey</u>**

|**Group**|**Number **|**Country / Organization **|
|---|---|---|
|Bilateral|22|Australia, Austria, Belgium, Canada, Denmark, Finland, France,<br>Germany, Ireland, Italy, Japan, Korea, Luxembourg, Netherlands,<br>New Zealand, Norway<br>Portugal, Spain, Sweden, Switzerland, United Kingdom, United<br>States|
|Multilateral Development Banks<br>(MDBs)|4|African Dev. Bank, Asian Dev. Bank, Inter-American Dev. Bank,<br>WorldBank|
|Other Multilateral Organizations<br>(Other MOs)|4|EU, IFAD, IMF, United Nations|
|Vertical funds|2|GAVI Alliance, Global Fund|
|**Total**|**32 **||

_Islamic Development Bank is not included in the list, as there is no data of the bank in FCS Source: Author_

> 9 The selection of key development partners is based on an ODA threshold of more than US$100 million and/or their intention to publish data (OECD (2011, p.141))

6
It is important to note that the PD survey does not cover all countries in any region. Therefore, regional performance as overviewed in section four is simply based on countries where data is available.

# **(2) Methodology**

The results of the PD survey cannot be directly used to compare across indicators. The indicators are measured using different methodology and their targets are arbitrarily decided. For example, indicator 5a on ̳use of country public financial management (PFM) systems is measured as the share of assistance using country PFM systems out of total assistance (%), while indicator 6 on ̳strengthen capacity by avoiding parallel project implementation unit (PIUs)‘ is measured by the number of parallel PIUs. Indicator targets are set up in different ways without clear rationales. In other words, measuring performance against targets is not a sensible way to conduct comparison across indicators.

Therefore, in order to enable us to conduct such a comparison across indicators, standardized scores of the PD survey results are calculated using the following formula.

Standardized scores follow a normal distribution with a mean of _zero_ and a standard deviation of _one_ . Standardized scores show how many standard deviations the value is away from the mean. For example, when a standardized score of an indicator is 1.0, this means that the indicator is away from the mean by 1.0 standard deviation and the probability of exceeding 1.0 is 15.9 percent.

The analysis using the standard deviation has two advantages. One is that it enables us to calculate a composite global aid effectiveness score for both partner countries and development partners. The other is that the change between 2005 and 2010 can be also standardized to compare the improvement in performance between these periods.

While the standardization of partner country data is simple as data is available for all indicators in all partner countries, that of development partners needs some adjustments as not all development partners are active in all partner countries. For example, the Asian Development Bank is not operating in Africa and the African Development Bank is not operating in Asia. Assuming that development partner performance is influenced by partner country performance, the different partner country coverage in operation cannot be ignored and some adjustments are required. Therefore, standardized scores of development partners are calculated separately in all partner countries by indicators.

In this paper, the calculation of the standardized scores is unweighted. In other words, all partner countries and development partners are equally treated regardless of their size and other characteristics. This is consistent with the main purposes of this paper – which identifies key aid effectiveness constraints of FCS in comparison with non-FCS.

7
# **4. Results**

Standardized scores based on the results of the PD survey are used for the following analyses: (1) overall partner country performance in 2010; (2) characteristics of FCS performance in 2010; (3) FCS partner country progress between 2005 and 2010; (4) overall development partner performance in 2010; and (5) development partner performance in FCS in 2010. The first three analyses focus on partner countries, while the remaining two analyses focus on development partners. The results of the analyses identify key aid effectiveness challenges in FCS and also provide good performance examples drawing from both FCS and development partners.

# **(1) Partner Country Performance in 2010**

The sum of standardized scores across indicators provides a comprehensive picture of a partner country‘s performance relative to that of other countries. By definition, if the sum is zero, the country‘s aid effectiveness performance is an average. If it is positive (negative), performance of the country is above (below) average. It is important to note that all indicators are treated equally. In other words, there are no different weights among indicators and correlations among indicators have not taken into account. Table 4 and figure 2 show the results of the sum of the standardized scores in all countries<sup>10</sup> .

**Table** **<u>4: Results by Regions and Country Groups</u>**

||**Total **|**IDA**|**IBRD**|**FCS**|**Non-FCS**|
|---|---|---|---|---|---|
|Africa|0.4|0.3|0.1|-1.0|1.4|
|EastAsia andPacific|1.0|0.1|0.9|-0.3|1.2|
|Europe and Central Asia|-3.4|-1.5|-1.9|-1.9|-1.5|
|Latin America and Caribbean|-1.6|-1.2|-0.4|-0.1|-1.5|
|Middle East and North Africa|3.3|0.0|3.0|0.4|3.0|
|South Asia|0.9|0.9|0.0|-1.9|2.8|
|**Total**|**0.0**|**-0.2**|**0.4**|**-3.6**|**1.0**|

_Note 1: Based on World Bank’s Classifications; sum of IDA and IBRD is not zero due to West Bank and Gaza that is not classified as IDA nor IBRD._ _Note 2: This is average sum of indicators by the number of countries in regions and country groups. Note 3: shadowed areas show negative scores Source: Author’s Calculation_

> 10 Standardized scores of all indicators by regions, country groups and countries are available in Appendix 2.

8
**Figure 2: Sum of Standardized Scores by Countries**

<!-- Start of picture text --> 15 Sum of standardized values<br>:FCSs<br>10<br>:Non-FCSs<br>5<br>0<br>-5<br>-10<br>-15<br>RwandaDominican RepublicTanzaniaPhilippinesMoroccoUgandaMalawiMoldovaEthiopiaSamoaIndonesiaGhanaSouth AfricaViet Nam PeruBangladeshSenegalPakistanBurkina Faso KenyaZambiaMozambiqueTogoLesotho Vanuatu EgyptBotswana LaosArmeniaJordanNepalWest Bank & Gaza StripSolomon IslandsBeninEcuadorHondurasTajikistanSierra LeoneNigeriaGabon TongaCape VerdeSwazilandSao Tome & PrincipeHaiti CameroonBoliviaLiberiaCambodiaMaliGuatemalaFijiNigerChadMauritaniaNamibiaColombiaPapua New GuineaBurundiGuinea-BissauAlbaniaTimor-LesteBosnia-HerzegovinaComorosJamaicaCongo Dem.Rep. (Zaire)Kyrgyz RepublicMadagascarMongoliaCentral African Rep.GambiaAfghanistanEl SalvadorSudanUkraine KosovoSt.Vincent&Grenadines<br><!-- End of picture text --> _Source: Author_ Among all countries and across the six regions, MNA performs best (3.3) followed by EAP (1.0), SAR (0.9) and AFR (0.4). On the other hand, performance in ECA (-3.4) and LAC (-1.6) are both below average. AFR‘s above the average performance is noteworthy, and a breakdown of performance by country (Figure 2) shows that two AFR countries (Rwanda and Tanzania) are among the top three countries. Among country groups, while the difference between IDA and IBRD is insignificant and there are no patterns (i.e., some IDA countries perform better than IBRD and vice versa), in all regions except for MNA, FCS performance is worse than that of non-FCS countries (and this also holds true across regions)<sup>11</sup> . In Figure 2, 13 countries out of 17 FCS (bars marked in red) are below average.

# **(2) Characteristics of FCS Performance in 2010**

A disaggregation of FCS performance by indicators helps identify on which indicators FCS performance lags behind that of non-FCS. Figure 3 shows the sum of standardized scores for FCS across indicators.

> 11 In MNA, West Bank and Gaza is the only FCS.

9
**Figure 3: FCS Performance by Indicators**

<!-- Start of picture text --> Indicator 3. Aid flows are aligned with national priorities (aid on budget)<br>Indicator 7. Aid is more predictable<br>Indicator 5b. Use of country procurement systems<br>Indicator 10a. Joint missions to the field<br>Indicator 5a. Use of country PFM systems<br>Indicator 9. Use of common arrangements or procedures (program based<br>approach)<br>Indicator 4. Strengthen capacity by coordinated support (technical<br>assistance)<br>Indicator 10b. Joint country analytic work<br>Indicator 6. Strengthen capacity by avoiding parallel project<br>implementation units<br>Indicator 8. Aid is untied<br>-12 -10 -8 -6 -4 -2 0 2 4 6<br>sum of standardized scores<br>Worse Better<br><!-- End of picture text --> _Source: Author’s Calculation_ Among the 10 indicators, FCS performance is worse than non-FCS performance on all except indicator 8 (aid is untied). The poor performance is especially outstanding on indicator 3 (aid flows are aligned with national priorities (aid on budget)), indicator 7 (aid is more predictable) and indicator 5b (use of country procurement systems). This finding is consistent with the New Deal which highlights transparency, aid predictability and use of country systems as the key aid effectiveness challenges in FCS.

While the disaggregation of FCS performance by indicators helps us to better understand the comprehensive picture of FCS performance, key aid effectiveness constraints need to be identified on a country by country basis so that each FCS can identify areas for improvement. Table 5 shows standardized scores of all indicators across FCS.

**Table** **<u>5: Standardized Scores by Indicator and FCS</u>**

||Ind<br>3|Ind<br>4|Ind<br>5a|Ind<br>5b|Ind<br>6|Ind<br>7|Ind<br>8|Ind<br>9|Ind<br>10a|Ind<br>10b|Total|+|-|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Afghanistan|-1.1|-1.9|-0.6|-1.3|0.1|-0.9|0.0|0.1|-1.3|-0.4|-7.4|3|7|
|Bosnia-Herzegovina|-2.1|0.6|0.6|0.4|-0.9|-1.7|0.3|0.0|-0.8|-0.9|-4.4|5|5|
|Burundi|-0.3|-0.5|-0.7|-0.3|-1.9|-0.1|0.5|0.8|-0.5|-0.6|-3.8|2|8|
|Central African Rep.|-2.1|-1.5|-0.4|-0.4|0.8|-1.7|0.5|-1.8|0.9|-1.1|-6.7|3|7|
|Chad|-0.6|0.9|-1.4|-1.5|0.9|**1.0**|-0.2|-1.3|-0.6|0.0|-2.8|4|6|
|Comoros|**1.2**|-1.0|-1.0|-0.3|0.2|-1.3|**1.1**|-0.8|-1.0|-1.4|-4.4|3|7|
|Congo Dem.Rep.|-0.3|-1.5|-1.2|-1.4|-1.7|0.2|0.7|0.1|0.4|-0.4|-4.9|4|6|

10
|Guinea-Bissau|-0.7|-0.8|-1.1|-1.4|0.8|-1.0|0.2|-0.2|-0.1|0.2|-4.1|3|7|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Haiti|-1.3|0.8|0.7|0.0|-2.2|-0.3|0.3|0.0|0.0|0.4|-1.6|7|3|
|Kosovo|-0.9|-2.8|-0.8|-0.8|0.1|-1.1|-1.5|-1.2|-1.3|-0.7|-11.0|1|9|
|Liberia|-1.9|**1.5**|0.2|-0.2|**1.0**|-1.6|0.6|-1.2|-0.6|0.2|-2.1|5|5|
|SierraLeone|-0.3|0.4|-0.1|-0.8|**1.0**|0.2|0.7|0.0|-0.5|-0.5|0.2|4|6|
|Solomon Islands|-1.4|**1.0**|-0.2|0.0|0.5|-0.8|1.0|0.2|-0.1|1.0|1.3|5|5|
|Sudan|-0.9|-0.3|-1.1|-1.4|-2.9|-0.5|0.4|-1.8|-0.6|-0.3|-9.5|1|9|
|Timor-Leste|0.7|-0.7|-0.9|-1.1|0.3|-1.6|-0.8|-0.6|-0.3|0.4|-4.5|3|7|
|Togo|0.9|-0.2|0.7|0.5|0.8|-0.2|1.0|0.0|-0.7|0.2|3.0|7|3|
|WestBank& Gaza|0.0|0.7|-0.1|0.7|0.1|**1.3**|-0.3|**1.2**|-1.4|-0.9|1.4|5|4|
|**Total**|**-11**|**-5.2**|**-7.4**|**-9.2**|**-3.1**|**-10**|**4.3**|**-6.4**|**-8.5**|**-4.9**|**-61.4**|||
|#ofpositive (+)|3|7|4|4|12|4|13|8|3|7||65||
|#of negative (-)|13|10|13|13|5|13|4|9|14|10|||104|

**_Ind 3:_** _Aid flows are aligned with national priorities (aid on budget)_ **_Ind 4:_** _Strengthen capacity by coordinated support (technical assistance)_ **_Ind 5a:_** _Use of country PFM systems_ **_Ind 5b_** _: Use of country procurement systems_ **_Ind 6:_** _Strengthen capacity by avoiding parallel project implementation units (PIUs)_ **_Ind 7:_** _Aid is more predictable_ **_Ind 8:_** _Aid is untied_ **_Ind 9:_** _Use of common arrangements or procedures (program-based approaches—PBAs)_ **_Ind 10a:_** _Joint missions to the field_ **_Ind 10b:_** _Joint country analytic work Note: Shadowed areas show negative scores Source: Author’s Calculation_

Among 17o scores (10 indicators in 17 FCS), 65 are positive, 104 are negative and 1 is zero. While more than one third of scores are positive, the degree is small. However, there are 8 scores exceeding 1.0 which shows relatively good performance. These are:

# **Indicator 3 (Aid on budget):** Comoros (1.2)

**Indicator 4 (Strengthen capacity by coordinated support):** Liberia (1.5) and Solomon Islands (1.0)

**Indicator 6: (Strengthen capacity by avoiding parallel project implementation units):** Sierra Leone (1.0)

**Indicator 7:** (Aid is more predictable): Chad (1.0) and West Bank and Gaza (1.3) **Indicator 8 (Aid is untied):** Comoros (1.0)

**Indicator 9 (Use of common arrangements or procedures):** West Bank and Gaza (1.2)

While the threshold (1.0) is arbitrarily decided, if FCS prefer to learn from each other‘s experience, these are the potential list of candidates. However, there are four indicators without any examples of good performance including indicators 5a (use of country PFM systems); 5b (use of country procurement systems); 10a (joint missions); and 10b (joint country analytic work). For these indicators, FCS may have to seek lessons from non-FCS, with significant efforts to adapt good examples to FCS realities.

Lessons can be learned not only from good performance examples, but also from poor performance examples; using these cases as lessons on avoiding similar mistakes. With the threshold at -1.8, nine relatively poor performance examples can be identified. These are:

**Indicator 3 (Aid on budget):** Bosnia-Herzegovina (-2.1), Central African Republic (-2.1) and Liberia (-1.9)

11
**Indicator 4 (Strengthen capacity by coordinated support):** Afghanistan (-1.9) and Kosovo (- 2.8)

# **Indicator 6 (Strengthen capacity by avoiding parallel project implementation units):** Burundi (-1.9), Haiti (-2.2) and Sudan (-2.9) **Indicator 9 (Use of common arrangements or procedures):** Central African Republic (-1.9).

# **(3) FCS Partner Country Progress between 2005 and 2010**

Poor FCS aid effectiveness performance in 2010 identified in the previous analyses may not be surprising due to well recognized challenges. However, the question on whether FCS performance improved between 2005 and 2010 is unanswered. There are two hypotheses. One is that as FCS started from a weak base, progress would be better than for non-FCS. The other is that the challenges faced by FCS would prevent these countries from improving their performance.

The same methodology as used previously is employed to compare progress between 2005 and 2010. Changes in indicator values are standardized to enable comparison across indicators and countries. Thirty-two countries participated in the PD survey in both 2006 and 2011. Among these, three countries (Afghanistan, Burundi and Democratic Republic of Congo) are FCS and one country (Cambodia) graduated from FCS between the periods<sup>12</sup> . Figure 4 shows performance in 2010 (the horizontal axis) and progress between 2005 and 2010 (the vertical axis)<sup>13</sup> .

**Figure 4: 2010 Performance and Progress between 2005 and 2010**

<!-- Start of picture text --> 20<br>3rd Quadrant: Progress since<br>1st Quadrant: Both2010<br>2005 is better than average, but<br>performance in 2010 is worse Dominican Rep performance and progress<br>since 2005 are better than<br>than average 15<br>average<br>10<br>: FCSs<br>Peru<br>: Non-FCSs<br>Mongolia 5 Rwanda<br>Cambodia<br>Burkina Faso<br>Albania Brundi Benin<br>0<br>-20 -15 -10 -5 0 5 10 15 20<br>DRC<br>Bolivia -5 Bangladesh<br>Afghanistan<br>Cape Verde<br>-10<br>4th Quadrant: Both2010 2nd Quadnrat: 2010 performance<br>performance and progress -15 is better than average, but the<br>since 2005 are worse than progress is worse than average<br>better than average<br>-20<br><!-- End of picture text -->

> 12 Based on FY05 Low-Income Countries under Stress (LICUS) 13 Appendix 3 includes data used for Figure 4.

12
## _Source: Author’s Calculation_

The first quadrant shows countries that are better than the average on both 2010 performance and in terms of progress between 2005 and 2010. The fourth quadrant, on the other, shows countries which are worse than both averages. The second quadrant shows that while countries are better than the average 2010 performance, their progress between 2005 and 2010 is below average. Finally, the third quadrant shows countries that are better than the average in terms of their progress between 2005 and 2010, but their 2010 performance is below average.

All three FCS marked in red and Cambodia (marked blue) fall into the fourth quadrant which means that not only performance in 2010, but also progress between 2005 and 2010 is worse than the average. While the sample size of FCS prevents us from generating a concrete answer to the question, the second hypothesis (i.e., challenges in FCS prevent them from improving aid effectiveness performance between 2005 and 2010) seems to apply for these countries.

# **(4) Development Partner Performance in 2010**

The ten aid effectiveness indicators measure not only partner country performance but also development partner performance by country. As aid effectiveness is a measure of the delivery and management of aid, it is logical to analyze the performance from both the recipient side (partner country) and the provider side (development partner).

Using the methodology introduced in section 3, standardized scores for 32 development partners are calculated by indicator and by country. Table 6 shows the average sum of standardized scores by development partner groups and country groups (i.e., averaged by the number of institution/countries in a group).

**Table** **<u>6: Performance by Development Partner Groups and Country Groups</u>**

|**Group**|**No**|**FCS (Rank)**|**Non-FCS (Rank)**|**FCS + Non-FCS**<br>**(Rank)**|
|---|---|---|---|---|
|Bilateral|22|-15.9 (3)|-40.8(3)|-56.7 (3)|
|MDBs|4|54.0 (1)|150.9 (1)|204.9 (1)|
|Other MOs|4|51.7 (2)|128.2(2)|180.0 (2)|
|Vertical funds|2|-36.2(4)|-113.2(4)|-149.3 (4)|

_Source: Author_ There are two findings. First, there are no differences in ranking among the groups between FCS and non-FCS (e.g. bilaterals are on average the lowest performers in both FCS and non-FCS countries). Second, among the four groups, MDBs perform best followed by other MOs, vertical funds and bilaterals. Table 5 provides us with a general sense that relative development partner performance is quite similar between FCS and non-FCS. However, development partner performance may still differ between FCS and non-FCS on particular indicators.

Table 7-A and B includes the average standardized scores by indicator.

13
# **Table 7: Performance by Development Partner Groups by Indicators A. All Partner Countries** **<u>(including FCS and non-FCS)</u>**

||**Bilateral**|**MDBs**|**Other**<br>**MOs**|**Other**|
|---|---|---|---|---|
|**Ind 3:**Aid flows are aligned with national priorities (aid on<br>budget)|-9.4|26.8|23.4|-9.8|
|**Ind 4:**Strengthen capacity by coordinated support (technical<br>assistance)|-6.4|22.0|28.2|-40.8|
|**Ind 5a: **Use ofcountryPFMsystems|-10.9|25.7|31.8|-8.6|
|**Ind5b: **Use of country procurement systems|-6.4|12.9|19.0|0.3|
|**Ind 6:**Strengthen capacity by avoiding parallel project<br>implementationunits (PIUs)|6.6|-6.4|-38.7|20.7|
|**Ind7: **Aid is morepredictable|-8.1|24.5|19.0|-10.1|
|**Ind 8:**Aidis untied|8.4|14.8|-3.2|-122.5|
|**Ind 9:**Use of common arrangements or procedures (program-<br>based approaches—PBAs)|-9.2|13.2|15.7|37.2|
|**Ind 10a: **Jointmissions to thefield|-10.0|12.9|39.6|-1.9|
|**Ind 10b: **Joint country analytic work|-11.3|19.0|45.2|-13.9|
|**Total **|**-56.7**|**165.4**|**180.0**|**-149.3**|

# **B. FCS**

||**Bilateral**|**MDBs**|**Other**<br>**MOs **|**Other**|
|---|---|---|---|---|
|**Ind 3:**Aid flows are aligned with national priorities (aid on<br>budget)|-2.8|9.0|7.1|-1.2|
|**Ind 4:**Strengthen capacity by coordinated support (technical<br>assistance)|-2.2|6.7|9.3|-7.7|
|**Ind5a:**Use of countryPFM systems|-2.9|9.2|7.4|-1.7|
|**Ind 5b: **Use ofcountry procurement systems|-1.9|5.0|5.8|-0.5|
|**Ind 6:**Strengthen capacity by avoiding parallel project<br>implementation units(PIUs)|1.6|-2.2|-9.1|4.7|
|**Ind 7: **Aidismore predictable|-2.1|6.5|4.7|0.5|
|**Ind 8:**Aidis untied|2.1|3.5|-0.6|-29.3|
|**Ind 9:**Use of common arrangements or procedures (program-<br>based approaches—PBAs)|-2.0|5.6|3.6|3.2|
|**Ind 10a: **Jointmissions to thefield|-2.7|3.1|11.5|0.9|
|**Ind 10b: **Joint countryanalytic work|-3.1|7.6|12.1|-5.2|
|**Total **|**-15.9**|**54.0**|**51.7**|**-36.2 **|

_Note: Islamic Development Bank does not have operations in FCS, and therefore average MDB performance is divided by 5 for table 6-A and by 4 for table 6-B_ The comparison between table 7-A and B shows almost the same. This confirms that even disaggregated by indicators, relative development partner performance is similar between FCS and non-FCS.

In FCS (Table 6-B), the average performance of MDBs is the strongest, followed by other MOs, bilaterals and vertical funds. Bilaterals exceed the average on two indicators: indicator 6 (strengthen capacity by avoiding parallel PIUs) and indicator 8 (aid is untied). On indicator 8, the better than average performance of bilaterals is a reflection of particularly weak performance of vertical funds. As vertical fund assistance is almost all tied, relative performance of other groups becomes positive almost by default.

14
While performance of vertical funds is the worst in aggregation (i.e., -36.2), this group performs best of any on indicator 6 (strengthen capacity by avoiding parallel PIUs) and has good performance on indicator 9 (use of common arrangements or procedures (program-based approached- PBAs)). Their assistance is 100 percent program-based in several FCS (e.g., GAVI alliance in Afghanistan and Sierra Leone). MDBs and other MOs perform above average in all but one or two indicators. MDBs are the top performers on indicators 3 (aid flows are aligned with national priorities (aid on budget)); 5a (use of country PFM systems); 7 (aid is more predictable); 8 (aid is untied); and 9 (Use of common arrangements or procedures (program-based approaches—PBAs). Other MOs have the top performance on indicators 4 (strengthen capacity by coordinated support (technical assistance)); 5b (use of country procurement systems); 10a (joint missions to the field); and 10b (joint country analytic work).

# **(5) Development Partner Performance in FCS in 2010**

The previous sub-section provides a comparative analysis based on development partner groups on areas of strength as well as those needing further improvement, disaggregated by indicator. However, the improvement of aid effectiveness for each development partner requires the same analysis done at the country/institution level. Figure 5 shows the sum of standardized scores by development partners in FCS.

## **Figure 5: Standardized Scores by Development Partners in FCS**

<!-- Start of picture text --> 150<br> Bilateral<br> MDBs<br> Other MOs<br>100  Vertical funds<br>50<br>0<br>-50<br>-100<br>World Bank EU Institutions United Nations African Dev. Bank Germany IFAD Asian Dev. Bank Japan IMF Netherlands France IDB Australia Sweden Portugal Ireland New Zealand Korea Denmark Finland United Kingdom Global Fund Switzerland Canada Belgium Austria Norway Spain Luxembourg GAVI Alliance United States Italy<br><!-- End of picture text --> _Source: Author’s Calculation_ 15
MDBs and other MOs including the World Bank, EU Institutions and United Nations are among the top performers on the figure. On the other hand, bilaterals and vertical funds‘ performance are below average.

While Figure 5 provides a comprehensive picture of relative strengths and challenges among the development partners, yet it does not provide specify relative strengths and weaknesses in each indicator. This is because the more partner countries a development partner operates in, the greater the extent that strength/weakness is exaggerated. For example, the World Bank operates in 17 FCS, while the African Development Bank operates in 9 FCS countries. With such differences in the number of partner countries per each development partner, the comparison of aggregated standardized scores may not make sense.

In order to enable us to compare across development partners, average standardized scores by development partners and indicators is calculated (Figure 6)<sup>14</sup> .

**Figure 6: Development Partner Performance by Indicators in FCS**

<!-- Start of picture text --> 10<br>Ind 10b<br>8 Ind 10a<br>Ind 9<br>Ind 8<br>6 Ind 7<br>Ind 6<br>Ind 5b<br>4 Ind 5a<br>Ind 4<br>Ind 3<br>2 total<br>0<br>-2<br>-4<br>-6<br><!-- End of picture text -->

# _Source: Author_

In Figure 6, even after taking the number of FCS in operation into consideration, the World Bank is at the top of the table with all indicators above the average followed by the Asian Development Bank and the IMF. More interestingly, the average standardized scores help us to identify where

> 14 Average by the number of FCS in operation

16
there are strengths and challenges by indicators. Table 8 shows the most prominent strengths/challenges identified by standardized scores being above/below 1.5.

# **Table** **<u>8: Strengths and Challenges by Development Partners</u>**

|Strengths|**Name of Development Partner (Indicator)**<br>IADB(Ind7, 9,10b);IFAD(Ind5a,10b);IMF(Ind5a, 5b)|
|---|---|
|Challenges|GAVI(Ind 8); Global Fund (Ind 8);IFAD(Ind 8); UN (Ind 6)|
|_Source: Appe_|_ndix 4_|

IADB performs well on indicators 7, 9 and 10b; IFAD performs well on indicators 5a and 10b and the IMF performs well on indicators 5a and 5b. While IADB and IMF operated in limited numbers of FCS<sup>15</sup> , it is nonetheless worth exploring efforts and implementation at their institutional levels.

This analysis helps development partners to identify areas of relative strengths and challenges, and encourages peer learning, and therefore FCS may in turn wish to learn from specific indicator examples by development partners from other FCS. If we pick up the top 5 percent of standardized scores for each indicator, we can obtain 5 examples of superior performance for each indicator (Table 9).

# **Table** **<u>9: Good Examples</u>**

|**Country**|**Ind 3**|**Ind 4**|**Ind 5a**|**Ind 5b**|**Ind 7**|**Ind 9**|**Ind 10a**|**Ind 10b**|
|---|---|---|---|---|---|---|---|---|
|Afghanistan||||||||Canada,<br>Germany|
|Bosnia-<br>Herzegovina|||WB|||GAVI|EU|WB|
|Burundi|||||||||
|Central<br>African Rep.||UN|IMF|IMF|||||
|Chad|||IFAD|IFAD||Switzerla<br>nd||EU|
|Comoros|||||||||
|Congo<br>Dem.Rep.||Belgium,<br>Netherlan<br>ds|IFAD|IFAD|Japan||IFAD||
|Guinea-<br>Bissau|AfDB|||WB|AfDB||AfDB||
|Haiti|||||||||
|Kosovo|WB|WB|||||||
|Liberia|EU|||||AfDB|||
|Sierra Leone|||||WB|GAVI|EU|WB|
|Solomon<br>Islands|||||||||
|Sudan|UN||WB|UN|UN|Sweden|||
|Timor-Leste|||||Australia||||
|Togo|EU|AfDB,<br>WB|||UN||Germany||
|West Bank &<br>Gaza|||||||||

_Source: Author_ For example, if FCS would like to learn how to improve performance on indicator 7 (aid is more predictable), the operations of Japan in Democratic Republic of Congo, AfDB in Guinea-Bissau;

> 15 IaDB operates in Haiti, and the IMF operates in Central African Republic and Haiti.

17
World Bank in Sierra Leone; UN in Sudan; Australia in Timor Leste; and UN in Togo may be able to provide good examples.

# **5. Conclusion**

The two main purposes of this paper are to identify (i) the key aid effectiveness challenges in FCS and (ii) good performance examples which can provide useful lessons to help address aid effectiveness challenges. The identification of challenges is the critical first step to improve aid effectiveness, and exploring strong performance by peers in critical areas is a practical way to find adaptable approaches. As both recipients and providers are key stakeholders for aid effectiveness – recognized as the delivery and management of aid – this paper provides analyses from both angles.

This paper relies on the results of the PD survey due to its country coverage, issue coverage and availability of historical data. In order to enable us to use the results for comparison, the results are standardized. While the data sources and methodology are useful, they have limitations. Therefore, the results of this paper need to be carefully interpreted and strong performance on a particular indicator by a given country/development partner many be the result of factors other than good and replicable practices.

Bearing that in mind, the results show that:

- In all regions except MNA, the performance of FCS significantly lags behind that of non-FCS, especially on indicator 3 (aid flows are aligned with national priorities (aid on budget)); indicator 7 (aid is more predictable) and indicator 5b (use of country procurement systems).

- Despite the poor FCS performance in general, several countries can provide good examples which other FCS can learn from (e.g. indicator 7 (aid is more predictable) in West Bank and Gaza).

- The comparison between 2005 and 2010 shows that FCS‘ below average performance in 2010 is matched by below average improvements over this period.

- On average, among development partners, MDBs and other MOs such as the World Bank, EU institutions and United Nations perform better than bilaterals and vertical funds in both FCS and non-FCS contexts, although performance differs across countries, indicators,  and institutions.

- In FCS, good institutional-level examples abound, and include IADB‘s performance on indicators 7 (aid is more predictable), 9 (use of common arrangements and procedures) and 10b (joint country analytic work).

- At the partner country level, good development partner examples also exist and include the indicator 7 performances of Japan in Democratic Republic of Congo, of the African Development Bank in Guinea-Bissau and of the World Bank in Sierra Leone.

- The identification of key aid effectiveness challenges and good performance examples are the

- initial steps for both partner countries and development partners to improve their aid effectiveness.

18
Going forward, it is critical to take the following factors into account. First, it is important to consider whether the identified challenges are important. While this paper equally treats all indicators, in practice, the importance of indicators differs across partner countries and development partners, dependent upon preferences and contexts and there may be correlations between indicators. Second, in learning from good examples, it is important to analyze the reasons and factors behind them. Third, applicability of good examples needs to be carefully considered as lessons from strong performance in one indicator in a given country may not be directly applied to another country.

19
# **Reference**

OECD (2011) ―Aid Effectiveness 2005-2011: Progress in Implementing the Paris Declaration‖ World Bank (2011a) ―World Development Report 2011: Conflict, Security and Development" World Bank (2011b) ―The World Bank and Aid Effectiveness: Performance to Date and Agenda Ahead‖ 20
**Appendix 1: 15 Indicators of the Survey on Monitoring the Paris Declaration**

||**_Indicators_**|**_Partner_**<br>**_country_**<br>**_performanc_**<br>**_e_**|**_Developme_**<br>**_nt partner_**<br>**_performanc_**<br>**_e_**|**_How measured (including_**<br>**_source of information)_**|**_2010 target_**|
|---|---|---|---|---|---|
|1|Operational national<br>development<br>strategies<br>|<br>||Bank‘s assessment based on<br>information from partner<br>countries|**75%**of partner countries<br>have operational national<br>development strategies|
|2a|Reliable public<br>financial<br>management (PFM)<br>systems|||Country Policy and<br>Institutional Assessment<br>(CPIA) Indicator 13|Half of partner countries<br>move up at least one<br>measure|
|2b|Reliable<br>procurement<br>systems|||Self-assessment using<br>Methodology for Assessing<br>Procurement Systems (MAPS)<br>|No target (due to the small<br>number of countries<br>conductingMAPSin 2010)|
|3|Aid flows are aligned<br>with national<br>priorities (aid on<br>budget)|||Aid flows reported in the<br>annual budget by<br>government/aid flows actually<br>disbursed by development<br>partners(%)|Halve the gap (at least<br>**85%**reported on budget)|
|4|Strengthen capacity<br>by coordinated<br>support (technical<br>assistance)|||Amount of coordinated<br>technical cooperation / total<br>technical cooperation (%)|**50%**of technical<br>cooperation is coordinated|
|5a|Use of country PFM<br>systems|||Use of PFM/total assistance<br>(%)|A one-third (two-thirds)<br>reduction in the % of aid<br>for partner countries with<br>a score of 3.5-4.5 (5 or<br>above) on indicator 2a|
|5b|Use of country<br>procurement<br>systems|||Use of procurement / total<br>assistance (%)|No target (as no target is<br>set for indicator 2b)|
|6|Strengthen capacity<br>by avoiding parallel<br>project<br>implementation<br>units(PIUs)|||Number of parallel PIUs|Reduce by two-thirds the<br>stock of parallel PIUs (**-**<br>**67%**)|
|7|<br>Aid is more<br>predictable|||Actual aid flows recorded by<br>the government/scheduled aid<br>flows by development partners<br>(%)|Halve the proportion of<br>aid not disbursed within<br>FY for which it was<br>scheduled|
|8|Aid is untied|||OECD-DAC data|Continue progress over<br>time|
|9|Use of common<br>arrangements or<br>procedures<br>(program-based<br>approaches—PBAs)|||Program-based approaches<br>(budget support + non-budget<br>support PBAs)/total<br>assistance (%)|**66%**of aid flows are<br>through PBAs|
|10<br>a|Joint missions to the<br>field|||Number of joint<br>missions/total number of<br>missions (%)|**40%**|
|10<br>b|Joint country<br>analytic work|||Number of joint analytic work<br>/total number of analytic work<br>(%)|**66%**|
|11|Results-oriented<br>frameworks|||Bank‘s assessment based on<br>information from partner<br>countries|**38%**of partner countries<br>have sound results-<br>oriented frameworks|
|12|Mutual<br>accountability|||Partner countries have mutual<br>assessment reviews based on<br>their response|**All**partner countries have<br>mutual assessment<br>reviews|

_Source: World Bank (2011, p.4)_ 21
||Country|IDA vs.<br>IBRD|Region|FCS vs.<br>Non-FCS|Ind 3|Ind 4|Ind 5a|Ind 5b|Ind 6|Ind 7|Ind 8|Ind 9|Ind<br>10a|Ind<br>10b|Total|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Guinea|||||||||||||||
|55|Peru|IBRD|LCR|Non-FCS|0.6|0.5|1.6|1.6|-0.3|0.9|0.2|-0.1|0.1|0.1|5.2|
|56|Philippines|IBRD|EAP|Non-FCS|-1.2|1.6|1.6|1.3|0.8|-0.8|0.1|1.0|1.1|2.4|7.9|
|57|Rwanda|IDA|AFR|Non-FCS|0.3|1.3|0.5|1.3|0.2|0.7|0.9|1.7|2.8|2.9|12.7|
|58|Samoa|IDA|EAP|Non-FCS|0.8|0.6|0.5|0.7|0.8|1.0|0.2|1.3|-0.3|0.3|6.0|
|59|Sao Tome &<br>Principe|IDA|AFR|Non-FCS|1.0|-0.5|-1.4|0.3|0.9|0.6|-0.2|-0.9|-0.6|-0.7|-1.5|
|60|Senegal|IDA|AFR|Non-FCS|0.2|0.7|-0.4|0.1|0.7|0.3|0.8|0.4|0.7|0.9|4.4|
|61|Sierra Leone|IDA|AFR|FCS|-0.3|0.4|-0.1|-0.8|1.0|0.2|0.7|0.0|-0.5|-0.5|0.2|
|62|Solomon Islands|IDA|EAP|FCS|-1.4|1.0|-0.2|0.0|0.5|-0.8|1.0|0.2|-0.1|1.0|1.3|
|63|South Africa|IBRD|AFR|Non-FCS|-2.1|1.1|-0.6|-0.3|0.3|1.3|1.0|1.4|3.7|-0.2|5.7|
|64|St.Vincent&Gre<br>nadines|IDA|LCR|Non-FCS|0.9|1.6|-1.6|-1.8|1.1|-1.7|-2.5|-1.8|-1.5|-2.9|-10.2|
|65|Sudan|IDA|AFR|FCS|-0.9|-0.3|-1.1|-1.4|-2.9|-0.5|0.4|-1.8|-0.6|-0.3|-9.5|
|66|Swaziland|IBRD|AFR|Non-FCS|0.0|0.7|-1.6|-1.2|1.0|1.3|0.6|-0.5|0.0|-1.2|-0.8|
|67|Tajikistan|IDA|ECA|Non-FCS|-0.4|0.9|-0.3|-0.3|0.6|1.2|-1.1|-1.4|0.4|0.7|0.3|
|68|Tanzania|IDA|AFR|Non-FCS|1.0|-1.8|1.9|1.7|0.5|1.4|0.9|1.3|0.9|0.5|8.3|
|69|Timor-Leste|IDA|EAP|FCS|0.7|-0.7|-0.9|-1.1|0.3|-1.6|-0.8|-0.6|-0.3|0.4|-4.5|
|70|Togo|IDA|AFR|FCS|0.9|-0.2|0.7|0.5|0.8|-0.2|1.0|0.0|-0.7|0.2|3.0|
|71|Tonga|IDA|EAP|Non-FCS|0.9|-1.3|-0.1|0.0|1.0|0.8|0.0|0.3|-0.2|-1.8|-0.3|
|72|Uganda|IDA|AFR|Non-FCS|1.2|0.6|1.3|0.3|0.6|0.7|0.8|0.7|0.6|1.1|7.8|
|73|Ukraine|IBRD|ECA|Non-FCS|-0.5|-1.8|-0.5|-0.8|-1.9|-0.3|-1.5|-1.3|-1.1|-1.0|-10.8|
|74|Vanuatu|IDA|EAP|Non-FCS|-0.3|-0.2|-0.3|-0.4|0.8|1.2|0.7|-0.4|0.6|1.2|2.9|
|75|Viet Nam|IDA|EAP|Non-FCS|0.9|-0.3|1.1|1.4|0.5|1.0|0.2|1.4|-0.8|-0.1|5.4|
|76|West Bank &<br>Gaza Strip|N/A|MNA|FCS|0.0|0.7|-0.1|0.7|0.1|1.3|-0.3|1.2|-1.4|-0.9|1.4|
|77|Zambia|IDA|AFR|Non-FCS|-0.3|0.7|0.6|0.9|0.0|-1.7|1.0|0.5|0.9|0.6|3.3|

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