COMMISSION STAFF WORKING PAPER Criteria for determining the Use of Loans and Grants in EU Macro-Financial Assistance
Date: 2011-07-07
Institutions: European Commission
Subjects: Community loan, International Monetary Fund, administrative transparency, aid for restructuring, balance-of-payments deficit, economic indicator, financial aid, gift, third country

EUROPEAN COMMISSION 

Brussels, 7.7.2011 
SEC(2011) 874 final 

COMMISSION STAFF WORKING PAPER 

Criteria for determining the Use of Loans and Grants in EU Macro-Financial Assistance

Accompanying the document 

Report from the Commission to the Council and to the European Parliament on the 
implementation of macro-financial assistance to third  

{COM(2011) 408 final} 
{SEC(2011) 873 final} 

 
 
 
 
  
 
 
TABLE OF CONTENTS 

1. 

INTRODUCTION.............................................................................................................. 2 

2.  HISTORICAL OVERVIEW.............................................................................................. 2 

3.  PRACTICES OF OTHER INTERNATIONAL ORGANISATIONS ............................... 3 

4.  CRITERIA ......................................................................................................................... 6 

4.1.  Level of economic and social development ............................................................. 7 

4.2.  Debt sustainability and repayment capacity............................................................. 9 

5.  THE COMMISSION’S APPROACH.............................................................................. 11 

6.  CONCLUSION ................................................................................................................ 14 

ANNEX 1: WORLD BANK COUNTRY CLASSIFICATION BY INCOME GROUP ........ 15 

ANNEX 2: COUNTRIES ELIGIBLE FOR THE IMF’S PRGT ............................................. 18 

ANNEX 3: DAC LIST OF ODA RECIPIENTS...................................................................... 19 

ANNEX 4: SELECTED DEBT INDICATORS OF MFA-ELIGIBLE 

COUNTRIES/TERRITORIES......................................................................................... 20 

 
 
 
1. 

INTRODUCTION 

Macro-financial  Assistance  (MFA)  from  the  EU  can  take  the  form  of  loans  or  grants,  or  a 
combination  of  both.  While  eligibility  for  MFA  has  been  informally  based  on  the  “Genval 
criteria” (last stated in the conclusions of the ECOFIN Council of 8 October 2002), these do 
not precisely define the criteria on which to base the decision whether to provide MFA in the 
form  of  a  loan,  a  grant  or  a  combination  of  the  two.  An  accompanying  letter  from  the 
President  of  the  Council  to  the  President  of  the  Commission1  simply  notes  that  “the 
concessionary element shall be reserved to low income countries established according to the 
country’s  per  capita  income  and  creditworthiness  and  be  adapted  to  the  debt  repayment 
capacity of the beneficiary country concerned.” 

The  present  note  explains  the  methodology  that  the  European  Commission  has  developed 
over  time  to  guide  the  decisions  on  the  use  of  loans  or  grants  in  MFA  operations.  This 
methodology  was  further  formalised  and  updated  in  a  note  that  was  endorsed  by  the 
Economic  and  Financial  Committee  (EFC)  in  January  2011.  Its  main  principles  are  also 
expected  to  be  reflected  in  the  proposal  of  a  Framework  Regulation  on  MFA  under 
preparation.  

The  note  sets  out  with  a  brief  historical  overview  of  the  use  of  loans  and  grants  in  MFA, 
followed  by a review  of  practices employed by other international donors, notably the IFIs. 
Starting from the premise that MFA – as an instrument of support in short-term and transitory 
balance-of-payments difficulties – should by default take the form of a loan, the methodology 
uses various criteria in order to determine possible eligibility for MFA grants. A selection of 
indicators  deemed  best-suited  to  guide  decisions  on  whether  to  opt  for  a  loan,  a  grant  or  a 
blend  is  used.  The  results  are  then  cross-checked  against  the  treatment  granted  by  the  IMF 
and  the  World  Bank  to  the  country  in  question,  notably  with  regard  to  its  access  to  the 
concessional facilities of these institutions. 

For  simplicity  and  completeness,  the  tables  and  charts  in  this  note  include  analysis  on  all 
candidate and potential candidate countries and all ENP countries. In addition, Tajikistan and 
the Kyrgyz Republic appear as memorandum items, having either received or requested MFA 
from the EU in the past. 

2. 

HISTORICAL OVERVIEW 

Since  1990,  55  MFA  decisions  have  been  approved,  with  total  commitments  amounting  to 
EUR7.4bn and effective disbursements of EUR5.3bn. Twenty-three countries have benefited 
from  this  assistance.  The  size  of  individual  MFA  operations  has  ranged  from  EUR15m 
(Moldova in 1996, 2000 and 2002) to EUR870m (Hungary in 1990). 

1 Regarding geographical eligibility, this letter specifies the following. Two groups of countries are in principle 
eligible: i) the candidate countries and potential candidate countries; and ii) the European countries of the CIS 
and the Mediterranean countries concerned by the Barcelona process. The letter further states that “certain other 
countries  which  are  not  covered  by  the  second  group  above  may  in  very  exceptional  and  duly  justified 
circumstances also become eligible.” Indeed, a number of operations have been approved in favour of countries 
in the Southern Caucasus (which are now part of the European Neighbourhood Policy, ENP) and Central Asia.  

2 

 
 
                                                 
The  experience  with  MFA  operations  over  the past  20  years  shows  that  most  MFA  support 
(86% in terms of financial volume) has taken the form of loans. However, while during the 
1990s, nearly 95% of MFA funding was lent to beneficiary countries, the first five years of 
the 2000s saw a significant increase in grants: nearly half of all MFA funding took this form 
(see left-hand side of Chart 1). This shift reflected in part the increased number of operations 
in the Balkans during this period, combined with the fact that many of them were in a post-
conflict situation and had weak repayment capacity. Meanwhile, during the recent resurgence 
in MFA operations in the wake of the global economic crisis, loan financing has risen again, 
to roughly three-quarters of total financial volume committed. This includes substantial loans 
to  Balkan  countries  (Serbia  and  Bosnia-Herzegovina),  whose  debt  servicing  capacity  has 
strengthened significantly since the initial MFA operations in the region, and to Ukraine. 

Chart 1:   Percentage of loans and grants (on a commitment basis), 1990-2010 

Financial volume 

Number of operations 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

1990-1994

1995-1999

2000-2004

2005-2010

1990-1994

1995-1999

2000-2004

2005-2010

Grants

Loans

Grants

Blend

Loans

Source: European Commission, Annual Reports on Macro-Financial Assistance 

The  share  of  grants  is  generally  higher  if  measured  by  the  number  of  operations  (see  right-
hand side of Chart 1) than if measured by financial volume committed. This reflects the fact 
that  grant  operations  have  tended  to  be  of  relatively  small  amounts,  not  least  in  light  of 
budgetary constraints. Over the entire lifespan of the MFA instrument, 54% of operations (in 
number) took the form of loans, 27% were grants and blend operations made up the remainder.  

3. 

PRACTICES OF OTHER INTERNATIONAL ORGANISATIONS 

Different international organisations have developed methodologies for classifying countries 
and,  on  that  basis,  for  determining  the  eligibility  for  certain  types  or  terms  of  assistance. 
Notably,  the  World  Bank  first  divides  recipient  countries  into  those  eligible  for  IDA  (the 
concessional arm of the Bank), IBRD (the arm responsible for non-concessional lending) or 
“blend”  financing.2  Within  the  IDA-only  group,  there  is  then  a  “traffic  light”  system  to 
determine  whether  a  recipient  country  will  receive  all  of  its  aid  either  in  grants  or 
concessional loans or whether an (equal) split between the two will be applied. Furthermore, 
the  terms  of  IDA  loans,  while  always  concessional,  are  also  differentiated  depending  on 
beneficiary countries’ income levels. 

2  World  Bank:  “How  we  Classify  Countries”,  available  on  http://data.worldbank.org/about/country-
classifications, accessed on 29 November 2010. 

3 

 
 
 
 
                                                 
The  World  Bank’s  official  criteria  for  IDA  eligibility  are  per  capita  income3  and 
creditworthiness for IBRD lending as assessed by the IBRD’s credit risk department.4 While 
the  two  criteria  are  often  related,  the  creditworthiness  criterion  is  in  practice  the  more 
important one, as a World Bank beneficiary country can remain IDA-eligible even if it has an 
average  income  level  above  the  IDA  income  cut-off,  until  it  is  sufficiently  creditworthy  to 
access IBRD loans; this is to avoid a situation in which a country is cut off from World Bank 
financing altogether.5 By contrast, if a country is sufficiently creditworthy for IBRD lending, 
it will not remain an IDA-only country, even if its per capita income is below the threshold. 
Instead,  it  will  be  a  “blended”  country,  with  access  to  both  IBRD  and  IDA  (e.g.  India, 
Pakistan and Vietnam).  

That said, the category of “blend” countries is not only composed of creditworthy countries 
with low average income levels. It also comprises countries whose per capita income exceeds 
the  IDA  threshold  (e.g.  Armenia,  Bolivia  and  Georgia).  This  reflects  a  phased  approach  to 
graduation from IDA, which seeks to ensure that a change in a country’s status is permanent 
and  to  avoid  sudden  breaks  in  funding.  Nonetheless,  this  qualification  should  not  mask  the 
fact  that  the  World  Bank  also  applies  a  degree  of  judgement,  in  addition  to  looking  at 
objective  criteria,  in  its  classification  of  countries,  not  least  in  the  assessment  of 
creditworthiness by the IBRD’s credit risk department. 

The  IMF  uses  a  system  modelled  on  that  of  the  World  Bank  to  determine  eligibility  for 
funding  from  the  Poverty  Reduction  and  Growth  Trust  (PRGT),  its  own  concessional  arm.6 
The  proximity  in  the  methodology  is  intentional,  aiming  at  ensuring  broad  consistency 
between  the  eligibility  for  the  concessional  arms  of  both  institutions  (see  Table  1  for  a 
comparison  of  categorisation  of  MFA-eligible  countries/territories  across  institutions).  In 
other  words,  IDA-eligible  countries  should  normally  also  be  PRGT-eligible.  Specifically,  a 
country is PRGT-eligible if its per capita income is below the IDA cut-off level and if it is 
unable to access international capital markets on a durable and substantial basis.  

Conversely,  this  means  that  a  country  graduates  from  PRGT  if  it  meets  one  of  the  two 
preceding criteria. In order to ensure that graduation is permanent, the IMF, akin to the World 
Bank, stipulates a number of safeguards: 

3 The World Bank uses gross national income (GNI), converted into US dollar on the basis of market or official 
exchange rate through the Atlas method, which seeks to limit the influence of short-term currency volatility inter 
alia by averaging conversion rates over a period of three years. While recognising that income measures based 
on  purchasing  power  parity  (PPP)  are  conceptually  more  suitable  for  comparing  standards  of  living  across 
countries, the Bank uses the Atlas method because PPP-based income estimates tend to be less reliable and less 
timely. The current operational cut-off for IDA eligibility is a per capita GNI of USD1,165. 

4 The IBRD’s creditworthiness assessment includes a combination of quantitative and qualitative indicators in 
eight broad categories: political risk; external debt and liquidity; fiscal policy and public debt burden; balance of 
payments  risk;  economic  structure  and  growth  prospects;  monetary  and  exchange  rate  policy;  financial  sector 
risks; and corporate sector debt and vulnerabilities. 

5  Countries  that  remain  IDA-eligible  because  they  would  otherwise  lose  access  to  World  Bank  funding 
altogether  are  sometimes  referred  to  as  “gap  countries”;  examples  are  Angola,  Honduras  and  Moldova.  See 
Annex 1 for the World Bank’s latest full country classification. 

6 The IMF upgraded its concessional financial facilities in 2009 in response to the global financial crisis. The 
PRGT  was  established  as  part  of  this  reform,  replacing  and  expanding  the  previous  Poverty  Reduction  and 
Growth  Facility /  Exogenous  Shocks  Facility  (PRGF-ESF)  Trust.  PRGT  eligibility  rules  are  described  in 
“Eligibility to Use the Fund’s Facilities for Concessional Financing”, IMF working paper 11 January 2010. For 
the latest PRGT eligibility list, see Annex 2. 

4 

 
 
                                                 
•  Per capita income must exceed the required threshold for five consecutive years, must not 
have been on a declining trend over this period and, at the time of presumed graduation, 
must be at least twice as high as the IDA cut-off level.  

•  The  market  access  criterion  is  operationally  defined  as  a  sovereign  having  borrowed  on 
international private capital markets in at least three of the last five years for which data 
are available, through bonds or commercial loans, cumulatively at least 100% of its IMF 
quota.7 As an additional safeguard, a country with market access will only graduate out of 
PRGT  if  its  per  capita  income  is  at  least  80%  of  the  IDA  cut-off  and  has  not  been  on  a 
declining trend in the last five years.  

•  A country must also be free from serious short-term vulnerabilities in order to graduate. 

Finally, the list of official development assistance (ODA) recipients compiled by the OECD’s 
Development Assistance Committee (DAC) separates countries into four categories.8 First, all 
countries  classified  as  least  developed  by  the  United  Nations  are  listed  as  such.9  The 
remaining  ODA  recipients  are  categorised  as  low  income,  lower  middle  income  and  upper 
middle income.10 The differentiation between these three categories occurs solely on the basis 
of World Bank per capita GNI data (Atlas method).  

The  DAC  list  is  normally  updated  every  three  years,  with  the  next  revision  scheduled  for 
2011.  The  most  recent  revision,  of  September  2009  (see  Annex 3),  only  added  Kosovo11  to 
the  list,  but  otherwise  reproduced  the  previous list,  published  in August 2008, based on the 
same data (for 2007) and GNI per capita thresholds, in keeping with the three-year rhythm. 

As  the  OECD  itself  does  not  provide  financial  support  to  third  countries  (other  than  in  the 
form of specific technical assistance, on a small scale), the DAC list is conceived as a tool for 
statistical and reporting purposes, rather than for an ex-ante decision on aid eligibility. That 
said,  it  is  being  used  by  the  EU  to  define  developing  countries  in  the  Development 
Cooperation Instrument. 

7 Sovereign guarantees of bonds or commercial loans are also taken into account for this calculation. If a country 
falls  short  of  the  stipulated  thresholds  of  amount  or  duration,  but  is  judged  to  have  had  the  capacity  to  reach 
them, it is also deemed to have met the market access criterion. 

8  OECD:  “DAC  List  of  ODA  Recipients  used  for  2008,  2009  and  2010  flows”,  available  on 
http://www.oecd.org/dac/stats/daclist, accessed on 29 November 2010. 

9  The  criteria  used  by  the  UN  to  classify  countries  as  least  developed  are:  GNI  per  capita;  the  Human  Asset 
Index  (itself  based  on  indicators  of:  nutrition;  health;  education;  and  adult  literacy);  and  the  Economic 
Vulnerability  Index  (itself  based  on the following indicators: population size; remoteness; merchandise export 
concentration; share of agriculture, forestry and fisheries in gross domestic product; the share of the population 
displaced  by  natural  disasters;  stability  of  agricultural  production;  and  stability  of  exports  of  goods  and 
services).  

10 High income countries are not ODA recipients and therefore not included in the DAC list. 

11 Under UNSCR 1244/1999. 

5 

 
 
                                                 
Table 1:   Categorisation of MFA-eligible countries/territories by other international 

organisations 

Country

Albania
Algeria
Armenia
Azerbaijan
Belarus
Bosnia and Herzegovina
Croatia
Egypt
Georgia
Iceland
Israel
Jordan
Kosovo (UNSCR 1244)
Lebanon
Libya
Macedonia (FYR)
Moldova
Montenegro
Morocco
Palestinian Territories†
Serbia
Syria
Tunisia
Turkey
Ukraine
Memorandum items:
   Kyrgyz Republic
   Tajikistan

IMF PRGT list
(March 2011)
Not eligible
Not eligible
Eligible*

World Bank IDA list
(January 2011)
IBRD
IBRD
Blend
Blend
IBRD
Blend
IBRD
IBRD
Blend
Not eligible
Not eligible
IBRD
IDA
IBRD
IBRD
IBRD
IDA
IBRD
IBRD

OECD DAC list
(September 2009)
Lower Middle Income
Lower Middle Income
Lower Middle Income
Recently graduated Lower Middle Income
Upper Middle Income
Lower Middle Income
Upper Middle Income
Lower Middle Income
Lower Middle Income
High Income OECD
High Income OECD
Lower Middle Income
Lower Middle Income
Upper Middle Income
Upper Middle Income
Lower Middle Income
Lower Middle Income
Upper Middle Income
Lower Middle Income
Not a World Bank member Not an IMF member Lower Middle Income
Upper Middle Income
Lower Middle Income
Lower Middle Income
Upper Middle Income
Lower Middle Income

Not eligible
Not eligible
Not eligible
Not eligible
Eligible*
Not eligible
Not eligible
Not eligible
Not eligible
Not eligible
Not eligible
Not eligible
Eligible
Not eligible
Not eligible

Not eligible
Not eligible
Not eligible
Not eligible
Not eligible

IBRD
IBRD
IBRD
IBRD
IBRD

IDA
IDA

Eligible
Eligible

Low Income
Low Income

* Continued eligibility only due to short-term vulnerabilities; otherwise graduated. 

† World Bank funding to the Palestinian Territories is provided primarily by the special-purpose Trust 
Fund  for  Gaza  and  West  Bank.  IMF  activity  in  the  Palestinian  Territories  is  limited  to  technical 
assistance. 

Sources: World Bank, IMF, OECD 

4. 

CRITERIA 

This section introduces various indicators that can be used to decide between loans and grants 
(or  a  combination  thereof)  in  MFA  operations  and  discusses  their  strengths  and  limitations. 
Akin to the practice of the IMF and the World Bank, and in line with the general orientations 
given  in  the  letter  from  the  President  of  the  Council  to  the  President  of  the  Commission 
accompanying  the  Genval  criteria,  they  are  subdivided  into  two  main  areas:  the  level  of 
development of the recipient country; and its debt sustainability and/or creditworthiness.  

6 

 
 
 
4.1. 

Level of economic and social development 

Per capita income 

Gross  national  income  (GNI)  per  capita  is  the  indicator  most  commonly  used  to  gauge  the 
level of development of a country. An income measure, such as GNI, is more relevant than an 
output  measure,  such  as  GDP,  for  a  comparison  of  the  level  of  economic  development  of 
countries  and  of  their  residents’  average  economic  well-being,  as  it  takes  into  account  net 
income transfers to other countries, such as dividend payments to foreign owners of domestic 
companies  and  interest  payments  to  foreign  bondholders,  thus  leaving  only  that  part  of 
economic output that is available to domestic residents for spending or saving. 

For  cross-border  comparisons,  each  country’s  GNI  per  capita  has  to  be  converted  into  one 
currency.  The  two  principal  methods  of  doing  so  are  purchasing  power  parity  (PPP)  and 
market (or official) exchange rates. Taking differences in price levels between countries into 
account,  PPP  is  more  suitable  for  comparing  standards  of  living  across  countries.  A  PPP-
based  measure  is  also  less  prone  to  currency  fluctuations  than  an  exchange-rate-based 
measure. However, as real and cross-border transactions (export, import, remittances, interest 
payments,  debt  repayments  etc)  are  conducted  using  (market)  exchange  rates,  an  exchange-
rate-based GNI per capita measure gives a better picture of the average level of development 
of  an  economy  as  regards  its  exchanges  with  the  rest  of  the  world.  The  international 
benchmark for exchange-rate-based measures is the World Bank’s Atlas method, which seeks 
to  limit  the  influence  of  short-term  currency  volatility  inter  alia  by  averaging  market 
exchange rates over a period of three years. Another advantage of the Atlas method relative to 
PPP  is  that  data  is  consistently  available  for  all  countries  from  a  central  source  (the  World 
Bank),  whereas  data  for  per  capita  GNI  on  a  PPP  basis  is  less  timely,  more  prone  to 
measurement errors and unavailable for some countries/territories. The international standard 
for country classifications is therefore GNI per capita converted through the Atlas method. 

Based  on  the  latest  available  GNI  data  and  classification  thresholds  from  the  World  Bank, 
three  countries  from  the  MFA  universe  (Croatia,  Iceland  and  Israel)  are  in  the  high  income 
category,  while  the  other  22  are  middle  income  countries  (11 lower  and  11  upper  middle 
income). The two Central Asian republics included in this note as memorandum items are low 
income countries. 

Poverty ratios 

MFA  is  not  an  instrument  of  poverty  reduction,  but  of  response  to  short-term  balance-of-
payments emergencies. Poverty ratios should therefore in principle not feature as a criterion 
for MFA eligibility as such. However, they can be relevant for decisions on the grant element 
of  individual  MFA  operations  –  as  important  indicators  for  the  social  and  developmental 
challenges of a country and as a gauge of the income distribution, specifically at the low end 
of the  spectrum.  In particular,  while  poverty is generally  correlated  with  per capita income, 
the use of poverty indicators alongside income measures ensures that countries for which this 
correlation does not hold are identified. 

7 

 
 
Table 2:  

Income per capita and poverty figures of MFA-eligible countries/territories* 

Country

Albania
Algeria
Armenia
Azerbaijan
Belarus
Bosnia and Herzegovina
Croatia
Egypt
Georgia
Iceland
Israel
Jordan
Kosovo (UNSCR 1244)
Lebanon
Libya
Macedonia (FYR)
Moldova
Montenegro
Morocco
Palestinian Territories
Serbia
Syria
Tunisia
Turkey
Ukraine
Memorandum items:
   Kyrgyz Republic
   Tajikistan

GNI per capita, Atlas 
method
current USD
3 950
4 420
3 100
4 840
5 540
4 700
13 810
2 070
2 530
43 220
25 740
3 740
3 240
7 970
12 020
4 400
1 590
6 550
2 790
1 250
5 990
2 410
3 720
8 730
2 800

870
700

Extreme poverty

Poverty

% of population

% of population

2.0

3.7
2.0
2.0
2.0
2.0
2.0
13.4

2.0

2.0
2.4
2.0
2.5

2.0

2.6
2.0

3.4
21.5

7.8

21.0
2.0
2.0
2.0
2.0
18.5
30.4

3.5

5.3
11.5
2.0
14.0

2.0

8.2
2.0

27.5
50.8

* Data for GNI per capita refer to 2009, while the columns on poverty show the latest available World 
Bank data, which refer to 2005, 2006, 2007 or 2008, depending on the country. 

Source: World Bank, World Development Indicators 

Measures  of  absolute  poverty  set  a  certain  threshold  (measured  in  PPP),  which  is  uniform 
across  countries,  while  poverty  can  also  be  defined  in  relation  to  the  country’s  average 
income. As relative poverty is not comparable across borders, the absolute measure is more 
relevant  as  a  criterion  for  determining  eligibility  across  a  number  of  countries.  Data  on 
absolute poverty12 are available from the World Bank, albeit with gaps. 

For the MFA universe, the inclusion, alongside per capita GNI, of (absolute) poverty data in 
the overall tally of countries’ levels of development does not change the picture substantially. 
This reflects the significant degree of correlation between the two indicators. However, two 
observations  can  be  made.  First,  many  European  transition  economies  boast  relatively  low 
poverty  ratios  compared  with  countries  with  similar  per  capita  income  levels  but  different 
socio-economic legacies, reducing the case for using grants. Second, in Armenia and Georgia, 
the  incidence  of  poverty  is  high  by  regional  and  per  capita  income standards (see  Table 2), 

12  In  the  Bank’s  definition,  anyone  living  on  USD2  per  day  (PPP)  or  less  counts  as  poor  (in  absolute  terms), 
while those living on USD1.25 per day (PPP) or less count as extremely poor. These benchmarks are therefore 
used to calculate the often-cited poverty and extreme poverty (headcount) ratios. 

8 

 
 
 
                                                 
which, ceteris paribus, should lend support to the consideration of a grant element in potential 
MFA  operations  with  these  countries.  As  these  examples  illustrate  and  notwithstanding  the 
general  correlation  between  the  two,  poverty  ratios  can  play  a  useful  role  as  secondary 
indicators alongside GNI per capita to give a fuller picture of a country’s level of economic 
and social development. 

4.2. 

Debt sustainability and repayment capacity 

As  noted,  a  country’s  debt  sustainability  and  repayment  capacity  is  a  key  concern  in  a 
decision on whether to provide MFA as a loan or a grant. Firstly, to extend more credit to a 
country than it can sustainably service would be counterproductive in terms of the country’s 
long-term external solvency and economic development; thus, the short-term help that MFA 
is designed to provide would go to the detriment of key long-term goals. Secondly, it would 
be against the  direct self-interest of the EU, as the lender, to extend a loan that runs a high 
risk of not being repaid. 

While no doubt important, debt sustainability is also a complex concept. To analyse it, a solid 
basis of data on debt stocks and future repayment flows is required, along with medium- to 
long-term  projections  of  corresponding  revenue  figures  (exports  for  external  debt 
sustainability; public revenue for public debt sustainability) and a variety of other variables, 
such as real GDP growth, interest rates, the current account and the primary fiscal balance.  

The  Bretton  Woods  institutions  have  developed  a  methodology  for  Debt  Sustainability 
Analysis  (DSA)  that  classifies  countries  into  low,  moderate  or  high  risk  of  debt  distress,  or 
identifies them as currently “in debt distress”. However, DSA are currently available for only 
a limited number of MFA-eligible countries/territories. 

The  IMF  also  addresses  the  issue  of  debt  sustainability  beyond  the  group  of  low  income 
countries,  notably  in  reviews  of  its  Stand-by  Arrangements  and  in  reports  summarising  its 
Article IV consultations with its members. In its analyses that concern countries with access 
to capital markets, the Fund follows a slightly different methodological framework than in its 
DSA for low income countries. Crucially, DSA conducted for market-access countries omit a 
clear categorisation into risk levels by country, partly for fear of market movements resulting 
from  the  publication  of  these  ‘ratings’.  Overall,  owing  to  their  limited  availability, 
IMF/World Bank DSA scores are of little use for determining the grant eligibility within the 
MFA universe as a whole. 

Still, it is clear that debt sustainability (both public and external) is a key consideration when 
deciding  whether  it  is  responsible  to  extend  new  credit  to  a  borrower,  as  is  the  case  when 
MFA  takes  the  form  of  a  loan.  It  is  therefore  essential  to  include  it  among  the  decision-
making criteria. Despite the importance of projections for determining whether a debt burden 
is sustainable, a combination of several objective, backward-looking indicators can serve as a 
useful approximation of a country’s debt situation, while still limiting discretion. 

Table 3 lists several indicators and discusses their significance and limitations, including data 
availability  problems.  The  indicators  essentially  consist  of  ratios  between  a  country’s  debt 
and debt service and corresponding variables of a country’s economic size and revenues so as 
to show the burden that the debt in question (external or public) imposes on the country. 

9 

 
 
Table 3:   Debt burden indicators 

External debt 
over 
GDP/GNI 

Significance 
Key variable for external 
debt sustainability, which 
sets the external debt 
stock in relation to the size 
of the economy 

External debt 
over exports 

Key variable for external 
debt sustainability, which 
sets the external debt 
stock in relation to the key 
external revenue 
generator (exports) 

Net present 
value of 
external debt 
over GNI 

External debt 
service ratio 
(debt service 
over exports) 

Public debt 
over GDP 

Key variable for external 
debt sustainability, which 
eliminates the shortcoming 
of looking at the external 
debt stock in nominal 
terms by calculating the 
payment stream in today’s 
prices 

Key variable for external 
debt sustainability, which 
sets the payments related 
to debt incurred in relation 
to the main corresponding 
revenue generator 
(exports) 
Key variable for public 
debt sustainability, which 
sets the public debt stock 
in relation to the size of the 
economy 

Limitations 
No clear threshold above 
which external 
indebtedness should be 
deemed problematic or 
unsustainable, as 
countries with a strong 
export base, a track record 
of economic growth and 
monetary credibility have 
significantly more leeway 
to accumulate external 
debt without facing 
refinancing problems 
No clear threshold above 
which external debt over 
exports should be deemed 
problematic or 
unsustainable, as debt 
stock figures give no 
indication about the 
financial terms of the debt 
(interest rates and 
maturities) 
The net present value can 
vary significantly 
depending on the interest 
rate used to discount the 
payment stream 

Past debt service 
payments are not 
necessarily comparable to 
future payments 

No clear threshold above 
which public indebtedness 
should be deemed 
problematic or 
unsustainable; high 
income countries with a 
developed domestic 
capital market have 
significantly more leeway 
to accumulate public debt 
without facing refinancing 
problems 

Data availability 
Available from the World 
Bank for 20 out of 25 MFA-
eligible countries/ 
territories; most high 
income countries do not 
systematically collect 
external debt data 

Available from the World 
Bank for 18 out of 25 MFA-
eligible countries/ 
territories; most high 
income countries do not 
systematically collect 
external debt data 

For the calculation of the 
net present value of 
outstanding debt, data on 
all future debt service 
payments (principal and 
interest) is required; such 
detailed data is 
unavailable on a broad 
basis 
Available from the World 
Bank for 18 out of 25 MFA-
eligible countries/ 
territories; most high 
income countries do not 
systematically collect 
external debt data 
Not available on a 
comparable basis across 
countries from a standard 
international source; EBRD 
Transition Report contains 
public debt figures for 11 
out of 25 MFA-eligible 
countries/ territories; IMF 
country reports contain 
data for most MFA-eligible 
countries/territories, albeit 
without necessarily 
applying a consistent 
methodology, but taking 
country idiosyncrasies into 
account 

10 

 
 
 
Public 
external debt 
over GNI 

Public debt 
service to tax 
revenue 

Significance 
Secondary variable for 
public and external debt 
sustainability; indicative 
where total public debt 
figures are unavailable, in 
particular for countries with 
poorly developed domestic 
capital markets 
Key variable for public 
debt sustainability, which 
sets the payments related 
to debt incurred in relation 
to the main corresponding 
source of revenue 
(collected taxes) 

Limitations 
Public external 
indebtedness can be low, 
even if either total external 
or total public 
indebtedness is 
problematically high 

Past debt service 
payments are not 
necessarily comparable to 
future payments 

Data availability 
Available from the World 
Bank for 17 out of 25 MFA-
eligible countries/ 
territories; IMF country 
reports contain figures for 
public external 
indebtedness for some 
countries 
Data on public debt 
service, as well as on 
revenues, is patchy and of 
poor cross-border 
comparability 

In addition to the indicators discussed in Table 3, a country’s export potential is a key factor 
determining debt sustainability in the long term. It could be approximated by country export 
forecasts. However, Commission forecasts for third countries’ exports normally span only 2-3 
years,  whereas  debt  sustainability  would  require  a  longer  time  horizon.  Moreover,  as  a 
forward-looking indicator, it leaves room for discretion in the same way as noted above for 
DSA in general, thus in part defeating the purpose for the exercise of defining criteria, which 
is to reduce discretion. 

There are also several widely used external liquidity indicators, including the ratio of official 
reserves to external debt, the so-called reserve cover ratio (official reserves over external debt 
falling due within one year) and the share of short-term debt in total external debt. However, 
as noted, all of these are liquidity, rather than solvency, indicators and, as such, less relevant 
for  an  analysis  of  medium-  to  long-term  external  debt  sustainability.  Indeed,  countries  are 
only  considered  for  MFA  if  they  are  in  an  acute  balance-of-payments  crisis.  Liquidity 
indicators  should  therefore,  by  definition,  be  problematically  low  for  any  MFA  recipient. 
Thus, these indicators are central for a decision on making MFA available, but are not used 
for deciding whether MFA should take the form of a loan or a grant. 

5. 

THE COMMISSION’S APPROACH 

As  discussed  in  the  previous  section,  various  indicators  can  add  value  in  deciding  on  the 
appropriate form of MFA (loan, grant or blend). However, no individual indicator suffices, on 
its  own,  to  decide  on  the  form  of  the  assistance.  Rather,  each  indicator  has  to  be  read  in 
conjunction  with  others  in  order  to  be  meaningful.  The  Commission’s  approach  uses  a 
selection of the indicators discussed above and synthesises the information that they contain 
on  the  country’s  level  of  economic  and  social  development  and  its  debt  sustainability.  The 
aim is to guide decisions on the form of MFA, while maintaining the necessary flexibility.  

Regarding economic and social development criteria, GNI per capita (Atlas method), the 
most widely used indicator, is used as a basis for a country’s positioning. As a general rule, in 
order  to  be  eligible  for  MFA  grants,  countries  would  in  principle  have  to  be  in  the  lower 
middle  income  category  or  below  according  to  the  latest  available  data  and  classification 
thresholds  from  the  World  Bank.  Poverty  ratios  are  also  taken  into  consideration, 
complementing GNI per capita, to the extent that they give a different picture of a country’s 
level of development. 

11 

 
 
 
The  information  provided  by  the  economic  and  social  development  indicators  is  then 
complemented  with  that  on  the  recipient  country’s  debt  sustainability.  This  second 
criterion looks in particular at the following five debt burden indicators: external debt over 
GNI; external debt over exports; public external debt over GNI; total public debt over 
GDP; and the external debt service ratio (debt service over exports). This choice represents 
a compromise between the significance and limitations of possible indicators, as well as data 
availability considerations, as discussed in the previous section. In addition, where available, 
the  results  of  the  DSA  conducted  by  the  IMF  and  the  World  Bank,  as  well  as  other 
relevant analysis on the long-term debt dynamics of the beneficiary countries, are taken 
into account. 

The  information  on  development  and  debt  sustainability  is  then  cross-checked  against  the 
status  that  the  country  in  question  has  in  its  cooperation  with  other  international  donors.  In 
particular, full or partial IDA eligibility and access to PRGT financing can be considered as 
arguments to consider a grant element. In the case of countries with access to IDA financing, 
IDA terms and, for “blended” countries, the share of IDA financing in the total assistance 
provided by the World Bank to the country is taken into account, wherever this information is 
available.  Finally,  budgetary  constraints, 
to  observe  annual 
appropriations,  within  the  framework  provided  by  the  EU’s  medium-term  Financial 
Perspectives, also needs to be taken into consideration, reflecting the fact that MFA grants are 
fully financed through the EU budget, whereas loans have only limited and indirect budgetary 
implications.13  For  example,  in  a  situation  of  limited  availability  of  funds  under  the 
macroeconomic assistance line of the EU budget, it may be appropriate to opt for a blend of 
MFA  loans  and  grants,  or  even  to  consider  a  loan-only  operation,  even  if  the  beneficiary’s 
development and debt indicators would in principle argue for a full grant. 

the  requirement 

i.e. 

For  illustrative  purposes,  Chart  2  plots  MFA-eligible  countries/territories  (plus  the  Kyrgyz 
Republic  and  Tajikistan,  as  memorandum  items)  according  to  their  per  capita  income 
(horizontal  axis)  and  a  combined  score  of  the  five  debt  burden  indicators  identified  above 
(vertical  axis).  This  “combined  debt  score”,  which  has  been  developed  to  enable  the 
presentation of the data in a chart, is the simple average of a score assigned to each individual 
debt  burden  indicator  (external  debt  over  GNI;  external  debt  over  exports;  public  external 
debt over GNI; total public debt over GDP; and the external debt service ratio), depending on 
the  extent  to  which  its  level  falls  into  a  range  that  can  be  presumed  to  be  “safe”  (score: 2), 
“problematic” (score: 0) or “intermediate” (score: 1). The indicative thresholds are defined in 
Table 4, while Annex 4 contains the underlying data, as well as the resulting individual and 
combined debt scores, for all MFA-eligible countries/territories. 

13 When MFA takes the form of a loan, the implications for the EU budget are limited to the need to provision 
the  Guarantee  Fund  the  year  after  the  loan  has  been  disbursed  at  a  level  of  9%  of  the  amount  disbursed.  The 
Guarantee  Fund was established in 1994 to cover the risks of default on external loans guaranteed by the EU 
budget (including MFA loans but also EIB and Euratom loans). In the current Financial Perspective, which runs 
from 2007 to 2013, an annual amount of up to EUR200m has been foreseen for the provisioning of the Fund, i.e. 
permitting net growth of the corresponding loan portfolio by around EUR2.2bn each year. 

12 

 
 
                                                 
Table 4:  

Indicative thresholds for five debt burden indicators (for charting purposes) 

External debt over GNI 
External debt over exports 
Public external debt over GNI 
Total public debt over GDP 
External debt service ratio 

Safe (2) 
≤15% 
≤25% 
≤10% 
≤15% 
≤15% 

Intermediate (1)  Problematic (0) 
>15% and ≤50% 
>25% and ≤80% 
>10% and ≤25% 
>15% and ≤40% 
>15% and ≤30% 

>50% 
>80% 
>25% 
>40% 
>30% 

While the thresholds are to some extent arbitrary, they have been chosen with due regard to 
past  experience  of  debt  dynamics  in  countries  at  comparable  stages  of  development  and, 
where  applicable,  to  thresholds  applied  in  the  HIPC  exercise  of  the  Bretton  Woods 
institutions. 

Chart 2 illustrates in a simplified manner the interplay of the two main criteria proposed here 
for  a  case-by-case  decision  on  the  form  of  MFA.  It  thus  gives  a  rough  indication  of  which 
countries  would  currently  be  candidates  for  receiving MFA only in the form  of a  pure loan 
(countries in the top right-hand shaded area of the chart) and of those countries for which a 
presumption  of  a  grant  should  exist  (bottom  left  shaded  area  of  the  chart).  Countries  in  the 
intermediate range may, on a case-by-case basis, be deemed eligible for a grant element. 

Chart 2:  

Illustrative scatter plot of MFA-eligible countries/territories* 

e
r
o
c
s

t
b
e
d
d
e
n
b
m
o
C

i

2

1

0

Algeria

Azerbaijan

Syria

Jordan

Belarus

Kosovo
(UNSCR 1244)

Egypt

Georgia

FYRoM

Albania

BiH

Moldova

Morocco

Ukraine

Kyrgyz Republic

Armenia

Tunesia

Tajikistan

Palestinian Territories

Serbia

Montenegro

Turkey

Lebanon

0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000

GNI per capita (current USD, Atlas method)

*  For  legibility  reasons,  countries  with  a  per  capita  income  of  more  than  USD9,000  (Croatia,  Iceland, 
Israel and Libya) have been excluded from this chart. For the Palestinian Territories, a combined debt 
score of zero has been assumed for charting purposes, reflecting a lack of comparable debt burden data. 

Sources: ECFIN calculation based on the World Bank’s World Development Indicators, supplemented 
by IMF data 

13 

 
 
 
 
 
 
6. 

CONCLUSION 

This  document  has  explained  the  methodological  approach  used  for  deciding  whether  a 
proposed  MFA  operation  should  take  the  form  of  a  loan,  a  grant  or  a  blend  of  the  two. 
Defining  verifiable  eligibility  criteria  ex-ante  increases  the  transparency  of  the  MFA 
instrument  and  reduces  discretion  and  arbitrariness.  The  approach  developed  by  the 
Commission is consistent with those applied by the World Bank and the IMF. It is based on 
objective indicators concerning countries’ level of development and debt sustainability, cross-
checked  against  the  judgment  of  other  multilateral  donors,  notably  the  Bretton  Woods 
institutions. It provides guidance on which countries could be considered for a grant element 
in MFA, starting from the premise that MFA should, by default, take the form of loans – in 
line  with  the  nature  of  the  instrument,  namely  to  help  alleviate  short-term  and  transitory 
balance-of-payments difficulties. 

While it is generally good practice to use verifiable criteria to determine eligibility for MFA 
grants,  it  is  equally  necessary  to  retain  a  degree  of  flexibility.  Notably,  some  room  for 
political  discretion  in  the  grant-versus-loan  decision  may  in  some  cases  be  desirable, 
strengthening the EU’s capacity to act in line with its wider strategic interests. Last but not 
least,  discretion  is  also  required  in  the  interest  of  overall  financial  discipline,  notably  to 
ensure that budgetary ceilings for providing MFA grants are respected. 

14 

 
 
ANNEX 1: WORLD BANK COUNTRY CLASSIFICATION BY INCOME GROUP 

World Bank list of economies (January 2011)

(Bold indicates a change of classification)

Economy

Afghanistan
Bangladesh
Benin
Burkina Faso
Burundi
Cambodia
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Eritrea
Ethiopia
Gambia, The
Ghana
Guinea
Guinea-Bissau
Haiti
Kenya
Korea, Dem. Rep.
Kyrgyz Republic
Lao PDR
Liberia
Madagascar
Malawi
Mali
Mauritania
Mozambique
Myanmar
Nepal
Niger
Rwanda
Sierra Leone
Solomon Islands
Somalia
Tajikistan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Angola
Armenia
Belize
Bhutan
Bolivia
Cameroon
Cape Verde
China
Congo, Rep.
Côte d'Ivoire
Djibouti
Ecuador
Egypt, Arab Rep.
El Salvador
Georgia
Guatemala
Guyana
Honduras
India
Indonesia
Iraq
Jordan
Kiribati
Kosovo
Lesotho
Maldives
Marshall Islands
Micronesia, Fed. Sts.
Moldova
Mongolia
Morocco
Nicaragua
Nigeria
Pakistan
Papua New Guinea

1
16
21
30
31
32
37
38
43
44
60
62
69
72
79
80
82
99
101
105
106
110
117
118
121
124
134
135
137
143
161
169
173
174
187
188
191
199
212
213
6
9
20
23
24
33
35
41
45
47
53
56
57
58
70
78
81
83
87
88
90
97
100
103
109
120
123
128
129
131
133
142
144
148
151

Other

HIPC

HIPC
HIPC
HIPC

HIPC
HIPC
HIPC
HIPC
HIPC
HIPC
HIPC
HIPC
HIPC
HIPC
HIPC

HIPC

HIPC
HIPC
HIPC
HIPC
HIPC
HIPC

HIPC
HIPC
HIPC

HIPC

HIPC
HIPC
HIPC
HIPC

HIPC
HIPC

HIPC
HIPC

HIPC
HIPC

HIPC

Code

AFG
BGD
BEN
BFA
BDI
KHM
CAF
TCD
COM
ZAR
ERI
ETH
GMB
GHA
GIN
GNB
HTI
KEN
PRK
KGZ
LAO
LBR
MDG
MWI
MLI
MRT
MOZ
MMR
NPL
NER
RWA
SLE
SLB
SOM
TJK
TZA
TGO
UGA
ZMB
ZWE
AGO
ARM
BLZ
BTN
BOL
CMR
CPV
CHN
COG
CIV
DJI
ECU
EGY
SLV
GEO
GTM
GUY
HND
IND
IDN
IRQ
JOR
KIR
KSV
LSO
MDV
MHL
FSM
MDA
MNG
MAR
NIC
NGA
PAK
PNG

Region

Income group

Lending category

IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
..
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
IDA
Blend
IDA
Blend
IBRD
IDA
Blend
IDA
Blend
IBRD
IDA
IDA
IDA
IBRD
IBRD
IBRD
Blend
IBRD
IDA
IDA
Blend
IBRD
IBRD
IBRD
IDA
IDA
IDA
IDA
IBRD
IBRD
IDA
IDA
IBRD
IDA
IDA
Blend
Blend

Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Low income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income

South Asia
South Asia
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
East Asia & Pacific
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Latin America & Caribbean
Sub-Saharan Africa
East Asia & Pacific
Europe & Central Asia
East Asia & Pacific
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
East Asia & Pacific
South Asia
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
East Asia & Pacific
Sub-Saharan Africa
Europe & Central Asia
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Europe & Central Asia
Latin America & Caribbean
South Asia
Latin America & Caribbean
Sub-Saharan Africa
Sub-Saharan Africa
East Asia & Pacific
Sub-Saharan Africa
Sub-Saharan Africa
Middle East & North Africa
Latin America & Caribbean
Middle East & North Africa
Latin America & Caribbean
Europe & Central Asia
Latin America & Caribbean
Latin America & Caribbean
Latin America & Caribbean
South Asia
East Asia & Pacific
Middle East & North Africa
Middle East & North Africa
East Asia & Pacific
Europe & Central Asia
Sub-Saharan Africa
South Asia
East Asia & Pacific
East Asia & Pacific
Europe & Central Asia
East Asia & Pacific
Middle East & North Africa
Latin America & Caribbean
Sub-Saharan Africa
South Asia
East Asia & Pacific

15 

 
 
 
 
152
154
162
164
166
177
181
183
186
189
190
192
194
196
198
200
205
206
208
210
211
2
3
4
7
8
13
18
25
26
27
29
40
42
46
49
54
55
64
68
76
89
95
98
108
111
113
116
119
125
126
127
132
136
149
150
153
159
160
167
168
175
178
179
180
182
195
204
207
5
10
14
15
17
22
28
36
39
48
50
59
63
67
73
75

Paraguay
Philippines
Samoa
São Tomé and Principe
Senegal
Sri Lanka
Sudan
Swaziland
Syrian Arab Republic
Thailand
Timor-Leste
Tonga
Tunisia
Turkmenistan
Tuvalu
Ukraine
Uzbekistan
Vanuatu
Vietnam
West Bank and Gaza
Yemen, Rep.
Albania
Algeria
American Samoa
Antigua and Barbuda
Argentina
Azerbaijan
Belarus
Bosnia and Herzegovina
Botswana
Brazil
Bulgaria
Chile
Colombia
Costa Rica
Cuba
Dominica
Dominican Republic
Fiji
Gabon
Grenada
Iran, Islamic Rep.
Jamaica
Kazakhstan
Lebanon
Libya
Lithuania
Macedonia, FYR
Malaysia
Mauritius
Mayotte
Mexico
Montenegro
Namibia
Palau
Panama
Peru
Romania
Russian Federation
Serbia
Seychelles
South Africa
St. Kitts and Nevis
St. Lucia
St. Vincent and the Grenadines
Suriname
Turkey
Uruguay
Venezuela, RB
Andorra
Aruba
Bahamas, The
Bahrain
Barbados
Bermuda
Brunei Darussalam
Cayman Islands
Channel Islands
Croatia
Cyprus
Equatorial Guinea
Faeroe Islands
French Polynesia
Gibraltar
Greenland

Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Lower middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
Upper middle income
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD

IBRD
IBRD
IDA
IDA
IDA
IDA
IDA
IBRD
IBRD
IBRD
IDA
IDA
IBRD
IBRD
..
IBRD
Blend
IDA
Blend
..
IDA
IBRD
IBRD
..
IBRD
IBRD
Blend
IBRD
Blend
IBRD
IBRD
IBRD
IBRD
IBRD
IBRD
..
Blend
IBRD
IBRD
IBRD
Blend
IBRD
IBRD
IBRD
IBRD
IBRD
..
IBRD
IBRD
IBRD
..
IBRD
IBRD
IBRD
IBRD
IBRD
IBRD
IBRD
IBRD
IBRD
IBRD
IBRD
IBRD
Blend
Blend
IBRD
IBRD
IBRD
IBRD
..
..
..
..
..
..
..
..
..
IBRD
..
IBRD
..
..
..
..

PRY
PHL
WSM
STP
SEN
LKA
SDN
SWZ
SYR
THA
TMP
TON
TUN
TKM
TUV
UKR
UZB
VUT
VNM
WBG
YEM
ALB
DZA
ASM
ATG
ARG
AZE
BLR
BIH
BWA
BRA
BGR
CHL
COL
CRI
CUB
DMA
DOM
FJI
GAB
GRD
IRN
JAM
KAZ
LBN
LBY
LTU
MKD
MYS
MUS
MYT
MEX
MNE
NAM
PLW
PAN
PER
ROM
RUS
SRB
SYC
ZAF
KNA
LCA
VCT
SUR
TUR
URY
VEN
ADO
ABW
BHS
BHR
BRB
BMU
BRN
CYM
CHI
HRV
CYP
GNQ
FRO
PYF
GIB
GRL

Latin America & Caribbean
East Asia & Pacific
East Asia & Pacific
Sub-Saharan Africa
Sub-Saharan Africa
South Asia
Sub-Saharan Africa
Sub-Saharan Africa
Middle East & North Africa
East Asia & Pacific
East Asia & Pacific
East Asia & Pacific
Middle East & North Africa
Europe & Central Asia
East Asia & Pacific
Europe & Central Asia
Europe & Central Asia
East Asia & Pacific
East Asia & Pacific
Middle East & North Africa
Middle East & North Africa
Europe & Central Asia
Middle East & North Africa
East Asia & Pacific
Latin America & Caribbean
Latin America & Caribbean
Europe & Central Asia
Europe & Central Asia
Europe & Central Asia
Sub-Saharan Africa
Latin America & Caribbean
Europe & Central Asia
Latin America & Caribbean
Latin America & Caribbean
Latin America & Caribbean
Latin America & Caribbean
Latin America & Caribbean
Latin America & Caribbean
East Asia & Pacific
Sub-Saharan Africa
Latin America & Caribbean
Middle East & North Africa
Latin America & Caribbean
Europe & Central Asia
Middle East & North Africa
Middle East & North Africa
Europe & Central Asia
Europe & Central Asia
East Asia & Pacific
Sub-Saharan Africa
Sub-Saharan Africa
Latin America & Caribbean
Europe & Central Asia
Sub-Saharan Africa
East Asia & Pacific
Latin America & Caribbean
Latin America & Caribbean
Europe & Central Asia
Europe & Central Asia
Europe & Central Asia
Sub-Saharan Africa
Sub-Saharan Africa
Latin America & Caribbean
Latin America & Caribbean
Latin America & Caribbean
Latin America & Caribbean
Europe & Central Asia
Latin America & Caribbean
Latin America & Caribbean
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..

16 

HIPC
HIPC

HIPC

EMU

 
 
 
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: nonOECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD
High income: OECD

..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
IBRD
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
IBRD
..
..
..
..
IBRD
..
..
..
..
..
..
..
..

EMU

EMU
EMU

EMU
EMU
EMU
EMU
EMU

EMU

EMU

EMU
EMU

EMU
EMU
EMU
EMU

77
84
92
104
107
112
115
122
130
139
140
145
147
157
158
163
165
170
193
197
201
209
11
12
19
34
51
52
61
65
66
71
74
85
86
91
93
94
96
102
114
138
141
146
155
156
171
172
176
184
185
202
203

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27

Guam
Hong Kong SAR, China
Isle of Man
Kuwait
Latvia
Liechtenstein
Macao SAR, China
Malta
Monaco
Netherlands Antilles
New Caledonia
Northern Mariana Islands
Oman
Puerto Rico
Qatar
San Marino
Saudi Arabia
Singapore
Trinidad and Tobago
Turks and Caicos Islands
United Arab Emirates
Virgin Islands (U.S.)
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea, Rep.
Luxembourg
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
United Kingdom
United States

GUM
HKG
IMY
KWT
LVA
LIE
MAC
MLT
MCO
ANT
NCL
MNP
OMN
PRI
QAT
SMR
SAU
SGP
TTO
TCA
ARE
VIR
AUS
AUT
BEL
CAN
CZE
DNK
EST
FIN
FRA
DEU
GRC
HUN
ISL
IRL
ISR
ITA
JPN
KOR
LUX
NLD
NZL
NOR
POL
PRT
SVK
SVN
ESP
SWE
CHE
GBR
USA

..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..

World
WLD
Low income
LIC
Middle income
MIC
  Lower middle income
LMC
  Upper middle income
UMC
Low & middle income
LMY
  East Asia & Pacific
EAP
  Europe & Central Asia
ECA
  Latin America & Caribbean
LAC
  Middle East & North Africa
MNA
  South Asia
SAS
  Sub-Saharan Africa
SSA
High income
HIC
  Euro area
EMU
  High income: OECD
OEC
  High income: nonOECD
NOC
Arab World
ARB
East Asia & Pacific (all income levels)
EAS
Europe & Central Asia (all income levels)
ECS
European Union
EUU
HPC
Heavily indebted poor countries (HIPC)
Latin America & the Caribbean (all income levels) LCN
LDC
Least developed countries: UN classification
Middle East & North Africa (all income levels)
MEA
NAC
North America
OED
OECD members
Sub-Saharan Africa (all income levels)
SSF

This table classifies all World Bank member economies, and all other economies with populations of more than 30,000. For operational and analytical purposes, economies are
divided among income groups according to 2009 gross national income (GNI) per capita, calculated using the World Bank Atlas method. The groups are: low income, $995 or less;
lower middle income, $996–3,945; upper middle income, $3,946–12,195; and high income, $12,196 or more. Other analytical groups based on geographic regions are also used.

Geographic classifications and data reported for geographic regions are for low-income and middle-income economies only. Low-income and middle-income economies are
sometimes referred to as developing economies. The use of the term is convenient; it is not intended to imply that all economies in the group are experiencing similar development
or that other economies have reached a preferred or final stage of development. Classification by income does not necessarily reflect development status.

Lending category: IDA countries are those that had a per capita income in 2009 of less than $1,165 and lack the financial ability to borrow from IBRD. IDA loans are deeply
concessional—interest-free loans and grants for programs aimed at boosting economic growth and improving living conditions. IBRD loans are noncessional. Blend countries are
eligible for IDA loans because of their low per capita incomes but are also eligible for IBRD loans because they are financially creditworthy.

Note: Income classifications are in effect until 1 July 2011. August 2010 revision: Slovenia added to high income OECD; September 2010 revision: Israel added to high income OEC
January 2011 revision: Estonia added to high income OECD and Euro area.

17 

 
 
 
ANNEX 2: COUNTRIES ELIGIBLE FOR THE IMF’S PRGT 

18 

 
 
 
ANNEX 3: DAC LIST OF ODA RECIPIENTS 

19 

 
 
 
ANNEX 4: SELECTED DEBT INDICATORS OF MFA-ELIGIBLE COUNTRIES/TERRITORIES 

Country

External debt over 
GNI

External debt over 
exports

Public external debt 
over GNI

Total public debt 
over GDP

External debt 
service ratio

Albania
Algeria
Armenia
Azerbaijan
Belarus
Bosnia and Herzegovina
Croatia
Egypt
Georgia
Iceland
Israel
Jordan
Kosovo (UNSCR 1244)
Lebanon
Libya
Macedonia (FYR)
Moldova
Montenegro
Morocco
Palestinian Territories
Serbia
Syria
Tunisia
Turkey
Ukraine
Memorandum items:
   Kyrgyz Republic
   Tajikistan

% of GNI

40.3
3.8
55.3
12.1
35.6
54.6
97.7
17.6
40.0
300.7
42.6
28.3
22.6
70.7

62.2
59.7
56.4
26.4

79.7
10.3
58.2
41.2
83.8

65.8
51.2

Score
1
2
0
2
1
0
0
1
1
0
1
1
1
0

0
0
0
1

0
2
0
1
0

0
0

% of 
exports
123.0
6.7
240.0
20.8
68.4
156.5
176.6
72.9
116.8

54.7
144.8
105.3

150.0
133.2

86.9

266.1
26.7
104.4
169.8
158.2

112.3
205.2

Score % of GNI

Score % of GDP

0
2
0
2
1
0
0
1
0

1
0
0

0
0

0

0
1
0
0
0

0
0

23.8
2.1
26.6
8.5
9.9
20.5

16.2
24.5
38.9
16.1
21.2
17.8
59.3

20.8
13.7
26.3
21.5

20.6
8.8
25.0
14.0
9.4

52.6
32.6

1
2
0
2
2
1

1
1
0
1
1
1
0

1
1
0
1

1
2
0
1
2

0
0

55.9
7.4
20.0
12.1
13.0
19.6
33.6
76.2
22.9
99.9
76.8
9.7
17.8
157.0

21.3
21.4
29.0
47.3

33.4
21.8
42.8
40.7
19.9

48.6
30.1

Score
0
2
1
2
2
1
1
0
1
0
0
2
1
0

1
1
1
0

1
1
0
0
1

0
1

% of 
exports
6.9
1.4
20.9
1.7
5.0
10.5
33.0
6.5
7.3

Score
2
2
1
2
2
2
0
2
2

4.8
3.3
18.0

14.8
14.9

12.5

37.1
3.5
10.1
41.6
36.2

14.0
38.4

2
2
1

2
2

2

0
2
2
0
0

2
0

Combined 
debt score
(for charting 
purposes)
0.80
2.00
0.40
2.00
1.60
0.80
0.25
1.00
1.00
0.00
0.67
1.40
1.00
0.20

0.80
0.80
0.33
0.80

0.40
1.60
0.40
0.40
0.60

0.40
0.20  

Sources: Where available, data from the World Bank’s World Development Indicators have been used. Most of these data refer to 2009. Any gaps in the 
World Bank data have been filled, where possible, with latest available data from IMF country reports. The scores are based on ECFIN calculations. 

20