Pablo Bandeira

1. Pablo Bandeira pbandeira@ceu.es The Quality of Foreign Aid: Review and New Evidence on Selectivity, Transparency and Results-Based Management 13th EADI General Conference 19-22 September 2011, University of York

2. Introduction • Foreign aid can help or damage growth and poverty reduction depending on recipient’s capacity, and form of aid. • Towards enhancing positive impacts, two global agreements, new aid data and empirical studies have been recently produced This paper reviews aid quality concepts, data and studies, and constructs new indicators on selectivity, transparency and results-based management

3. 1. Defining Aid quality and the unit of analysis

4. Defining aid quality… • From the two international references on aid effectiveness (PD and AAA) we can define quality dimensions and concepts referred to donor practices: • Alignment: support participative national development strategies, use recipients’ systems when they provide assurance, and provide reliable multi-year commitments. • Harmonization: coordination between donors at the country level for planning, funding and evaluating • Results-based management: link resources to human development results • Good conditionality: conditions must be few, transparent and based upon development results • Transparency: publicly disclose detailed and timely information on allocations, results and conditions associated with disbursements. Before (selectivity) or after?

5. Defining unit of analysis • Most studies take donor and recipient countries as the unit of analysis, but aid is given and received by agents, not by countries. • We cannot really state that aid from country A to country B is of any quality, because there are many agents on each side, with varying qualities. • We need to differentiate agents as much as possible: national government, subnational governments, multilateral organizations (MO), and civil society organizations (CSO).

6. 2. The available aid data and its characteristics

7. Aid data sources • Three important worldwide data sources: • DAC-OECD • AidData Project • PD 2008 and 2005 monitoring surveys • Besides, researchers have commonly used information on agencies’ web pages or send them questionnaires

8. Aid databases • DAC-OECD has two databases: • DAC annual aggregates: by country • Creditor reporting System (CRS): by donor agency and project, including information on channelling organization. • AidData Project: based on the CRS, adding more donors and more information on projects.

9. Aid databases • PD 2008 and 2005 monitoring surveys: 16 progress indicators, 10 of them referred to donors. Best indicators a priori, since we base aid quality on the PD, but 3 important problems: • Data measured by country • Specification/data gathering problems on 3 indicators. • Representativity: average of 16/26 recipients per donor measured, not randomly, when 151 recipients.

10. 3. Choosing aid quality indicators

11. Choosing indicators • Many empirical studies trying to understand how agencies allocate their aid flows. Self-interest, recipient needs, or recipient merits. • Several recent empirical studies on donors’ aid quality: Roodman (2003-2010), Easterly and Pfutze (2008), Birdsall and Kharas (2010), Knack et al (2010). • 4 important problems in their indicators: • None of them differentiate between agency and country at the recipient level. • Most use unrepresentative PD data • Most produce rankings based on an overall abstract notion of aid quality: highly sensitive to weightings and little policy meaning. • Some use arguable indicators

12. Choosing indicators • Therefore, there is an important need of more studies based on indicators that: • Differentiate between both donor and recipient agencies • Have representative or comprehensive data • Identify meaningful quality strengths and weaknesses for each donor • Have sufficient universal consensus

13. 4. New indicators on selectivity, transparency and results-based management

14. ∑j (GovAidij x WGIj/10) S1i = ∑ j GovAidij Selectivity indicators • Goal: see if donors reward/punish recipient governments’ merits/weaknesses on good governance. • Data: AidData Project for aid flows and Kaufman, Kray and Mastruzzi (2009) for recipient governments’ governance indicators • Donors = central governments • Differentiate between two type of agents per recipient country: governments and MO/CSO.

15. ∑j (GovAidij x WGIj/10) ∑j (100 - |%GovAidij – (WGIj x 10)|) x TotAidij) S1i = S2i= ∑ j GovAidij ∑ j TotAidij Selectivity indicators Proxy of % of aid channelled through governments that is likely to be effective due to adequate governance capacity of the recipient government. Eg: Only 14% of govaid is likely to be effective when given to a country with a WGI score of 1.4 Proxy of % of total aid given to countries with bad governance indicators that is likely to be correctly channelled. Eg: Total aid is well channelled to a country with score 1.4, if 14% is given to its gov, and 86% to MO and CSO.

16. Selectivity indicators

17. Selectivity indicators • S1 average (37%): most aid given directly to governments goes to the worst governments • S2 average (66%): : however, donors tend to give a higher proportion of aid MO or CSO if governments perform badly It seems that donors first choose recipient countries based on poverty levels, commercial interests, historic linkages and the like, and then do some agent selection based on governance capacities, but still not enough (bad governments are probably receiving too much aid)

18. Transparency and results-based management indicators • Data source: central government and MO web pages • Do they publish: • Project appraisal documents? • Results matrix within project appraisal documents? • Project evaluation documents? • Results analysis within project evaluation documents?

19. Transparency and results-based management indicators

20. 5. Conclusions

21. Conclusions • Enhancing the quality of foreign aid is becoming one of the cornerstones of international relations. • Empirical studies can help detect areas in which donors need to improve, but need to go beyond countries as the unit of analysis, and use meaningful indicators on which there is consensus and representative data. • Applying these ideas, I have constructed indicators on selectivity, transparency and results-based management, which show that: • It seems that donors first choose recipient countries based on poverty levels, interests and the like, and then do some agent selection based on governance capacities, but still not enough (bad governments are probably still receiving too much aid) • Only the governments of Australia and Japan, and 3 MO (African, Asian and World Banks) measure and publish information on results at the project level.

22. Pablo Bandeira ¡Thank you for you attention! pbandeira@ceu.es