Default and recovery statistics : sovereign and sovereign-guaranteed lending 1984-2023.
Date: 2024-10-28
Institutions: European Investment Bank
Subjects: credit, database, financial risk, financial stability, financial statistics, investment, sovereign wealth fund, technical cooperation

Multilateral development banks and development finance institutions

DEFAULT 
 AND RECOVERY  
STATISTICS

SOVEREIGN AND  
SOVEREIGN-GUARANTEED 
LENDING
1984-2023

DEFAULT 

 AND RECOVERY  

STATISTICS

Multilateral development banks and development finance institutions

DEFAULT 
 AND RECOVERY  
STATISTICS

SOVEREIGN AND 
SOVEREIGN-GUARANTEED 
LENDING 1984-2023

DEFAULT AND RECOVERY STATISTICS 

Sovereign and sovereign-guaranteed lending 1984-2023 

© European Investment Bank (the “Administrator”), as host and administrator for, and on behalf of, Global 
Emerging  Markets  Risk  Database  (GEMs)  Consortium,  2024.  GEMs  is  a  consortium  of  multilateral 
development  banks  and  development  finance  institutions,  including  the  Asian  Development  Bank  (ADB), 
Agence  Française  de  Développement  (AFD),  African  Development  Bank  (AfDB),  Asian  Infrastructure 
Investment  Bank  (AIIB),  British  International  Investment  (BII),  Banque  Ouest  Africaine  de  Développement 
(BOAD), Black Sea Trade and Development Bank (BSTDB), Central American Bank for Economic Integration 
(CABEI), Cassa Depositi e Prestiti (CDP), Council of Europe Development Bank (CEB), Development Bank of 
South  Africa  (DBSA),  U.S.  International  Development  Finance  Corporation  (DFC),  European  Bank  for 
Reconstruction and Development (EBRD), European Investment Bank Group (EIB), Netherlands Development 
Finance Company (FMO), GuarantCo, International Bank for Reconstruction and Development (IBRD), Inter-
American Development Bank (IDB), Inter-American Investment Corporation (IDB Invest), International Fund 
for  Agricultural  Development  (IFAD),  International  Finance  Corporation  (IFC),  Islamic  Development  Bank 
(MIGA),  
(KfW),  Multilateral 
für  Wiederaufbau 
(IsDB),  Kreditanstalt 
New Development Bank (NDB), Proparco. 

Investment  Guarantee  Agency 

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Neither GEMs nor any of its members represents or warrants as to the accuracy, reliability or completeness of 
the content, conclusions or judgments of this work. Neither GEMs nor any of its members makes any express 
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statistics,  information  and  results  presented  in  this  document  are  based  on  reasonable  assumptions  and 
methodologies, the use of other assumptions and methodologies might lead to different conclusions. 

The information, contents, results and statistics in this document differ significantly from published historical 
data regarding default rates to other creditors and should not be regarded as indicative of results that other 
creditors  may  experience.  They  also  reflect  GEMs  members’  historical  experience,  which  is  not  necessarily 
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The contents of this work are intended for general informational purposes only, and should not be relied upon 
for any specific purpose. All relevant parties should make lending and investment decisions based on their 
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pdf: 

QH-01-24-011-EN-N 

ISBN: 

978-92-861-5823-0 

doi: 

10.2867/3426827 

Printed on FSC® Paper. 

 
 
 
 
 
 
Table of contents 

Preface ......................................................................................................................... vii 

1 

2 

Highlights....................................................................................................................... 1 

Characteristics of sovereign  and sovereign-guaranteed lending ............................................ 6 

2.1  Definition ................................................................................................................... 6 

2.2 

Preferred creditor status ............................................................................................... 7 

2.3  GEMs rating for countries ............................................................................................ 8 

2.4  Countries in the dataset ............................................................................................. 10 

3 

Default rate statistics ...................................................................................................... 13 

3.1  Annual default rate methodology ............................................................................... 13 

3.1.1  Annual default rates by year ....................................................................................... 14 

3.1.2  Annual default rates by region ................................................................................... 15 

3.1.3  Annual default rates by historic income group ............................................................. 17 

3.2  Default rates by credit rating ...................................................................................... 19 

3.2.1  Marginal default rates by credit rating category ........................................................... 20 

3.2.2  Cumulative default rates by credit rating category ........................................................ 21 

3.2.3  Marginal default rates by credit rating ......................................................................... 22 

3.2.4  Cumulative default rates by credit rating ..................................................................... 23 

4 

Recovery rate statistics .................................................................................................... 24 

4.1 

4.2 

Recovery rates by region ............................................................................................ 25 

Recovery rates by historic income group...................................................................... 26 

5 

Rating migrations .......................................................................................................... 27 

5.1  Annual upgrade vs. downgrade ratio .......................................................................... 27 

5.2 

Rating migration rates ............................................................................................... 28 

 
 
 
 
 
Preface 

The Global Emerging Markets Risk Database (GEMs) Consortium was established in 2009 as a joint initiative 
between the European Investment Bank and the International Finance Corporation to pool credit risk data. 
The GEMs database is a unique example of a tangible common good designed to catalyse investments in 
emerging markets and support technical cooperation between international institutions. At the time of writing, 
GEMs comprises 26 member institutions, all of which are multilateral development banks and development 
finance institutions, with business activities in emerging markets and developing economies.  

GEMs collects de-identified data from multilateral development banks and development finance institutions 
on their performing and non-performing exposures in emerging markets and developing economies. In return, 
output  statistics  are  produced  encompassing  default  rates  and  recovery  rates  categorised  by  various 
dimensions,  such  as  geography,  sector,  income  group  and  others.  GEMs  is  also  a  discussion  and 
collaboration forum for building technical alignment and sharing best practices among member institutions, 
including  through  working-level  meetings.  Compiling  GEMs  risk  statistics  relies  on  a  robust,  shared 
methodological framework. Bringing together data and expertise from leading public institutions, GEMs offers:  

  a  risk  data  hub  of  contract-level  information  for  private  and  public  lending  and  sovereign  and 
sovereign-guaranteed  lending  –  one  of  the  largest  such  datasets  for  emerging  markets  and 
developing economies; 

  a trusted data collection and processing platform  hosting a scalable data  model, which could be 

expanded to cover other contract-level data related to investment projects; 

  a  statistical  platform  for  member  multilateral  development  banks  and  development  finance 
institutions,  with  the  ability  to  calculate  GEMs  outputs,  default  rates,  recovery  rates  and  rating 
migrations  facilitating  better-informed  investment  decisions  in  emerging  markets  and  developing 
economies; 

  a public good data source for aggregated statistics, with the reported default and recovery rates for 
private and public lending and sovereign and sovereign-guaranteed lending providing an anchor for 
risk perceptions; 

  a  framework  for  collaboration  among  member  multilateral  development  banks  and  development 

finance institutions to improve risk management practices across the industry. 

More  private  investment  is  needed  to  combat  climate  change  and  achieve  the  Sustainable  Development 
Goals. This requires institutions to work together on addressing some of the current barriers to investment. Key 
priorities include supporting the preparation of well-designed projects; facilitating the use of public resources 
to mitigate risks; promoting and enabling an appropriate legal and contractual environment; and improving 
standardisation,  transparency  and  data  availability.  The  scarcity  of  data  around  emerging  markets  and 
developing  economies  and  the  tightening  of  regulatory  requirements  call  for  more  sophisticated  risk 
management practices and more reliable metrics. 

Through GEMs, member multilateral development banks and development finance institutions are addressing 
the investment gap by sharing their experience and market knowledge among themselves and with investors 
and the broader public. These banks and institutions pool their data using a harmonised template, generating 
more  valuable  statistics  than  those  available  to  any  individual  lending  institution.  GEMs  is  thus  a  unique, 
comprehensive data source for current and potential investors in emerging markets – one that helps refine risk 
perceptions and inform better decision-making. The Group of 20 (G20) Eminent Persons Group on Global 
Financial Governance highlights the benefits of a joined-up system built by members, which delivers more 
than the sum of its parts. The need for a collaborative approach applies to member multilateral development 
banks and development finance institutions, to private investors and to other stakeholders constrained by the 
same persistent data gap. 

The scarcity of accessible, standardised, transparent and high-quality information on investment projects in 
emerging markets can skew risk perceptions, leading to suboptimal investment decisions. Institutions with little 
or  no  experience  in  such  markets  have  to  rely  on  risk  assumptions  based  on  limited  public  information.  

 
By  anchoring  risk  perceptions  with  actual  statistics,  GEMs  aims  to  help  unlock  capital  that  can  fill  such 
investment gaps. 

The  statistics  produced  by  GEMs  enable  the  calibration  and  benchmarking  of  internal  models,  leading  to 
efficient  provisioning,  greater  accuracy  in  setting  capital  requirements,  and  better-informed  investment 
decisions.  GEMs  statistics  provide  an  objective,  reliable  and  statistically  significant  basis  for  discussing 
regulatory compliance, capital adequacy and risk management practices with auditors, rating agencies and 
supervisors. Furthermore, GEMs statistics can be a powerful tool for transparent assessment of portfolio risks 
when third parties engage in risk transfer or co-financing operations with multilateral development banks or 
development finance institutions, or in any other balance sheet optimisation initiative – thereby supporting the 
crowding-in of additional funding for emerging markets. 

Since 2021, GEMs has shared its aggregated statistics publicly, recognising the potential value for various 
stakeholders, from academics to regulators and commercial entities. This report builds on the well-received 
previous publications, combining and offering default and recovery statistics in greater detail and reflecting 
the  contributing  institutions’  lending  profiles  in  emerging  markets  and  developing  economies.  The  report 
discloses statistics derived from pooled GEMs data from 1984 to 2023, supplied by 11 member institutions. 
Furthermore, niche features and unique insights of this database are described in the report, along with the 
methodological framework for generating GEMs statistics. 

Specific applications of GEMs statistics may vary across institutions. GEMs therefore welcomes feedback from 
readers  of  this  report,  and  looks  forward  to  working  with  financial  stakeholders  to  improve  the  focus  and 
content of future publications, aiming to support new and sustainable investment where it is most needed. 

GEMs member institutions participating in this publication: 

 
 
  
 
1 Highlights 

Compared  with  previous  GEMs  publications  on  sovereign  and  sovereign-guaranteed  lending,  this  report 
provides  statistics  with  a  much-widened  scope.  The  underlying  dataset  now  covers  a  40-year  period  from 
1984 to 2023, adding 15 years of data to the previous publication (which ranged from 1998 to 2022). In 
addition, for the first time, the report includes statistics on recovery rates for default events and further analysis 
of the results along various dimensions that are available in the dataset and may be of interest to the public. 

Statical  metrics  are  provided  on  the  underlying  distributions  of  results,  allowing  readers  to  gauge  the 
significance of the averages presented for default and recovery rates. As default rate distributions mainly follow 
a normal distribution, 90% confidence intervals are supplied for all averages. In contrast, for recovery rates, 
where the distributions are heavily skewed, distribution percentiles are provided. 

Figure 1 illustrates the default events in the GEMs dataset. A total of 38 countries defaulted over the 40-year 
observation period, some of them multiple times, and 13 countries have ongoing default events at the end of 
2023. 

Figure 1: Countries with default events by year 

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Afghanistan
Angola
Bosnia and Herzegovina
Belarus
Democratic Republic of the Congo
Congo
Côte d'Ivoire
Cuba
Gabon
Ghana
Guatemala
Guyana
Honduras
Iraq
Iran
Lebanon
Liberia
Marshall Islands
Macedonia
Mali
Myanmar
Niger
Nigeria
Nicaragua
Nauru
Panama
Peru
Serbia
Russia
Seychelles
Sudan
Sierra Leone
Suriname
Syria
Venezuela
Yemen
Zambia
Zimbabwe

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Figure 2 shows the number of countries in default for each of the 40 years of observation. The number of 
countries in default in the late 1980s and 1990s declined strongly in the 2000s and 2010s. However, an 
upward trend has been evident since 2022.  

Highlights     1 

 
Figure 2: Number of countries in default by year 

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Displaying the number of countries in default as a percentage of total countries in the GEMs dataset (Figure 3) 
produces a similarly shaped graph to that in Figure 2, but with a lower peak for the later years, as the dataset 
includes more countries in those years. 

Figure 3: Percentage of countries in default by year 

15%

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Based on 50 defaults and 4 726 observations for countries over the period 1984-2023, Table 1 shows an 
average annual default rate of 1.06% overall. The increase compared with the previous publication – which 
showed an average annual default rate of 0.64% – is mainly driven by extending the underlying data back to 
1984 and adding the 2023 data. In addition, the table shows the range of the 40 annual observations and 
the 90% confidence interval for the average. 

Note that duplicate observations have been eliminated when calculating default rates. When a country has 
lending from multiple multilateral development banks for a given year, only one observation is counted. If a 
country defaults in respect of any multilateral development bank, then a default is counted. The removal of 
duplicates results in an average default rate for the combined data that is substantially higher than the default 
rates for individual institutions, which range from 0.00% to 0.95% and average at 0.60%. 

2     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
Table 1: Overall annual default rate 

Unique 
countries

Signed 
amount  in 
€ million

Observed 
years

Observations Defaults

Minimum 
annual 
default rate

Maximum 
annual 
default rate

Average 
annual 
default rate

Lower of 90% 
confidence 
interval

Upper of 90% 
confidence 
interval

166

1 715 388

40

4 726

50

0.00%

6.02%

1.06%

0.67%

1.45%

The 40 individual annual results for the default rates are displayed in Figure 4, and in more detail in Table 9. 
Some of the 40 individual annual default rates are 0.00% because the 50 observed defaults are not distributed 
evenly over the 40 years. The range and 90% confidence interval for these data – 0.00% to 6.02% and 0.67% 
to  1.45%,  respectively  (Table 1)  –  are  relatively  large  because  of  the  overall  scarcity  of  observations.  In 
addition, Figure 4 provides the averages for the four ten-year periods making up the total observation time. 
Relatively high annual default rates are seen in the late 1980s and, to a lesser extent, in the 1990s, followed 
by  even  lower  rates  until  2021.  Then,  an  increase  in  default  rates  during  2022  and  2023  reverses  the 
downward trend in the ten-year averages.  

Figure 4: Annual default rates and averages, by ten-year period 

6.5%

6.0%

5.5%

5.0%

4.5%

4.0%

3.5%

3.0%

2.5%

2.0%

1.5%

1.0%

0.5%

0.0%

2.53%

1.23%

1.06%

0.30%

0.81%

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1
2
0
2

2
2
0
2

3
2
0
2

Annual default rate

Average 1994-2003

Overall average

Average 2004-2013

Average 1984-1993

Average 2014-2023

The  overall  statistics  for  recovery  rates  are  shown  in  Table 2.  Based  on  44  default  events  in  28  unique 
countries, an average recovery rate of 94.9% is observed. Unresolved default events are not included in the 
recovery rate statistics. The table also shows the range of results (from 47.1% to 100.0%) and the levels of 
recovery for different percentiles of the individual results. 

Table 2: Overall recovery rates 

Unique  
countries

Default 
events

Average 
recovery 
rate

Minimum 
observation

10th 
percentile

25th 
percentile

Median

75th 
percentile

90th 
percentile

Maximum 
observation

28

44

94.9%

47.1%

87.8%

95.5%

98.0%

99.8%

100.0%

100.0%

Table 3 and Figure 5 provide further information about the distribution of results by showing how many of the 
individual recovery rates are within each 10% range. Most of the results (88.6%) are within the range of 90% 
to 100%. 

Highlights     3 

 
 
 
 
Table 3: Distribution of recovery rates 

Recovery 
rate

From 0%

To

10%

Defaults

% of total

0

10%

20%

0

20%

30%

0

30%

40%

0

40%

50%

1

50%

60%

0

60%

70%

0

70%

80%

3

80%

90%

1

90%

100%

39

Total

44

0.0%

0.0%

0.0%

0.0%

2.3%

0.0%

0.0%

6.8%

2.3%

88.6% 100.0%

Figure 5: Distribution of recovery rates (percentage of all defaults) 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Below 10% 10%-20% 20%-30% 30%-40% 40%-50% 50%-60% 60%-70% 70%-80% 80%-90% 90%-100%

Further insight into the distribution of recovery rates between 90% and 100% is provided by dividing this range 
into 1% intervals (Table 4 and Figure 6). This analysis shows that 59.0% of default events have recovery rates 
above 98% and 43.6% of events have recovery rates greater than 99%. 

Table 4: Distribution of recovery rates – detail for 90% to 100% 

Recovery 
rate

From 90%

To

91%

Defaults

% of total

1

91%

92%

1

92%

93%

0

93%

94%

2

94%

95%

1

95%

96%

3

96%

97%

3

97%

98%

5

98%

99%

6

99%

100%

17

Total

39

2.6%

2.6%

0.0%

5.1%

2.6%

7.7%

7.7%

12.8% 15.4% 43.6% 100.0%

4     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
 
Figure 6: Distribution of recovery rates – detail for 90% to 100% (percentage of all defaults) 

50%

45%

40%

35%

30%

25%

20%

15%

10%

5%

0%

90%-91%

91%-92%

92%-93%

93%-94%

94%-95%

95%-96%

96%-97%

97%-98%

98%-99% 99%-100%

The observed length of default events is shown in Table 5 and Figure 7. Although about one-third of default 
events only last a year or less, and two-thirds of them are concluded within five years, there are a few very 
long events, with the longest duration being over 20 years. The median time to resolution is slightly more than 
three years.  

Table 5: Time to resolution 

1

14

2

3

3

4

4

7

5

2

6

3

Resolution of default during year
7
14

10

11

12

13

8

9

15

16

17

18

19

>=20

Total

3

2

1

1

0

0

0

1

1

1

0

0

0

1

44

32% 39% 48% 64% 68% 75% 82% 86% 89% 91% 91% 91% 91% 93% 95% 98% 98% 98% 98% 100%

Annual 
resolutions

Cumulative % 
resolved

Figure 7: Time to resolution 

s
n
o
i
t
u
o
s
e
r

l

l

a
u
n
n
A

16

14

12

10

8

6

4

2

0

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

d
e
v
l
o
s
e
r
e
g
a
t
n
e
c
r
e
p
e
v
i
t
a
u
m
u
C

l

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19 >=20

Years

Annual resolutions

Cumulative % resolved

Highlights     5 

 
 
 
 
 
 
 
2  Characteristics of sovereign  

and sovereign-guaranteed lending 

2.1  Definition 
Sovereign and sovereign-guaranteed lending is provided by GEMs institutions, all of which are multilateral 
development banks. This is direct lending to sovereign countries, and lending to a sovereign country’s states, 
institutions  and  agencies  with  an  explicit  guarantee  by  the  country  to  pay  overdue  amounts  if  individual 
borrowers  fail  to  pay  on  time.  All  lending  operations  in  a  country  that  are  considered  in  this  report  are 
connected  via  contractual  cross-default  clauses  within  each  multilateral  development  bank.  In  addition, 
multilateral  development  banks  apply  arrears  sanctions  to  all  operations  of  a  government  simultaneously, 
even if only one operation is in arrears. To reflect the specific format of this lending, the following methodology 
is used in this report:  

•  Default event  has only one  definition: a payment delay  on any operation beyond the most severe 

sanction trigger applicable to each respective multilateral development bank. 

•  Default events are only considered resolved when all overdue amounts (principal, interest and any 

applicable charges) on all loans pertaining to the government in default are fully paid.  

• 

To avoid duplicates, only one observation is counted when multiple multilateral development banks 
have exposure to the same country and the amounts of exposure are combined. A default event is 
counted if it happened in respect of at least one multilateral development bank, even if others do not 
experience a default. 

This approach for eliminating duplicates results in worst case default rates and observed average default rates 
calculated individually for each of the multilateral development banks that are lower than the combined result. 
As  shown  in  Table 6,  individual  annual  default  rates  for  the  contributing  institutions  range  from  0.00%  to 
0.95% and have an observation-weighted average of 0.60%.  

Table 6: Average annual default rates of contributing institutions 

Contributing 
institutions

Defaults

Observations

Average default 
rate

Minimum annual 
default rate

Maximum annual 
default rate

11

63

10 554

0.60%

0.00%

0.95%

6     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
Preferred creditor status 

2.2 
The statistics in this report show substantially lower default and recovery rates than those in other publications 
on  sovereign  lending,  such  as  the  output  from  databases  maintained  by  credit  rating  agencies  for  non-
multilateral development bank lending. 

This  superior  performance  largely  results  from  the  specific  features  of  multilateral  development  banks. 
Multilateral  lending  institutions  benefit  from  stringent  arrears  policies,  solid  shareholding  structures  and  a 
preferred creditor status for their sovereign and sovereign-guaranteed loans. 

Preferred  creditor  status  is  a  widely  accepted  principle  under  which  multilateral  development  banks  have 
historically  been  given  priority  for  debt  repayment  if  a  country  experiences  financial  stress.  It  has  been  a 
cornerstone for multilateral development banks, allowing them to operate with low losses. Although it is not 
legally enforceable, preferred creditor status entails the following expectations: 

•  Countries commit to timely payment of their obligations to multilateral development banks. 

•  Countries commit to exempt multilateral development banks from generalised payment moratoriums 

and exchange rate controls. 

• 

The International Monetary Fund (IMF) typically requests that the preferred creditor status be granted 
for itself and for multilateral development banks with global membership as a condition for providing 
funding to a country in crisis. 

•  Multilateral development banks are exempt from participating in sovereign debt rescheduling. This 
benefit is granted by official creditors organised under the Paris Club and officially recognised in the 
Paris  Club  Agreed  Minutes.  This  practice  exempts  multilateral  development  banks  from  the 
“comparability  of  treatment”  clause,  which  requires  all  creditors  to  seek  rescheduling  terms 
comparable to those agreed by the Paris Club. 

Characteristics of sovereign and sovereign-guaranteed lending     7 

 
2.3  GEMs rating for countries 
The  GEMs  rating  for  countries  (as  shown  in  Table 7)  is  not  collected  from  the  member  institutions,  but  is 
derived as the average of country ratings by the main rating agencies (S&P, Moody’s and Fitch). This approach 
ensures that a consistent rating scale is used among the multilateral development banks contributing data to 
GEMs. In cases where no such rating is available, Organisation for Economic Co-operation and Development 
(OECD) ratings are used. If those are also unavailable, then World Risk Review (WRR) ratings are applied. 
Countries are categorised as not rated (NR) if none of these ratings are available. During periods of default 
with any multilateral development bank, GEMs assigns a rating of “non-accrual” to the country. 

Table 7: Mapping of external ratings to the GEMs scale 

Numeric

GEMs scale

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

AAA
AA+
AA
AA-
A+
A
A-
BBB+
BBB
BBB-
BB+
BB
BB-
B+
B
B-
CCC+
CCC
CCC-
CC
C
SD
Non-accrual
NR

S&P

AAA
AA+
AA
AA-
A+
A
A-
BBB+
BBB
BBB-
BB+
BB
BB-
B+
B
B-
CCC+
CCC
CCC-
CC
C
SD

NR

Moody's

Aaa
Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
Ba2
Ba3
B1
B2
B3
Caa1
Caa2
Caa3

Ca/C

NR

Fitch

AAA
AA+
AA
AA-
A+
A
A-
BBB+
BBB
BBB-
BB+
BB
BB-
B+
B
B-
CCC+
CCC
CCC-
CC
C
SD

NR

OECD

WRR

0.1

1

2

3

4

5

6

7

NR

1

2

3

4

5

6

7

8

9
10

NR

Figure 8 and Figure 9 illustrate the rating history of the GEMs dataset. Each year shows the composition of 
the dataset based on the GEMs rating as of 1 January of that year. Substantial reductions in the number of 
unrated  countries  occurred  in  2000  when  OECD  ratings  became  available  as  fallbacks  to  rating  agency 
ratings, and in 2010 when WRR ratings were first published. Since 2010, less than 5% of the countries have 
gone unrated. 

8     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
Figure 8: Historic dataset composition by rating category – country count 

170
160
150
140
130
120
110
100
90
80
70
60
50
40
30
20
10
0

4
8
9
1

5
8
9
1

6
8
9
1

7
8
9
1

8
8
9
1

9
8
9
1

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

8
0
0
2

9
0
0
2

0
1
0
2

1
1
0
2

2
1
0
2

3
1
0
2

4
1
0
2

5
1
0
2

6
1
0
2

7
1
0
2

8
1
0
2

9
1
0
2

0
2
0
2

1
2
0
2

2
2
0
2

3
2
0
2

AA

A

BBB

BB

B

CCC

CC/C

SD

NR

Figure 9: Historic dataset composition by rating category – percentage of total number of countries 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

4
8
9
1

5
8
9
1

6
8
9
1

7
8
9
1

8
8
9
1

9
8
9
1

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

8
0
0
2

9
0
0
2

0
1
0
2

1
1
0
2

2
1
0
2

3
1
0
2

4
1
0
2

5
1
0
2

6
1
0
2

7
1
0
2

8
1
0
2

9
1
0
2

0
2
0
2

1
2
0
2

2
2
0
2

3
2
0
2

AA

A

BBB

BB

B

CCC

CC/C

SD

NR

Characteristics of sovereign and sovereign-guaranteed lending     9 

 
 
 
 
Countries in the dataset 

2.4 
As detailed in Table 8, there are 166 countries in the dataset. Not all of them have necessarily been active 
throughout the entire 40-year period covered by this publication. In addition to data on the years that a country 
has been in the GEMs dataset, the table includes information on how many GEMs members provide lending 
to the country, the cumulative signed amount with multilateral development banks, and the first year that the 
country was given a GEMs rating. 

Table 8: Dataset information for included countries 

ISO 
country 
code

Country

Region

Number of 
MDBs with 
lending

Cumulative 
signed amount
(in € million)

Outstanding
 31 Dec. 2023
(in € million)

First year 
in dataset

Last year 
in dataset

First year 
of GEMs 
rating

Angola
Argentina
Azerbaijan
Bosnia and Herzegovina
Barbados
Bangladesh
Burkina Faso
Bulgaria
Bahrain
Burundi
Benin
Brunei
Bolivia
Brazil
Bahamas
Bhutan

Afghanistan
AF
Antigua and Barbuda
AG
AL
Albania
AM Armenia
AO
AR
AZ
BA
BB
BD
BF
BG
BH
BI
BJ
BN
BO
BR
BS
BT
BW Botswana
Belarus
BY
Belize
BZ
Democratic Republic of the Congo
CD
Central African Republic
CF
Congo
CG
Côte d'Ivoire
CI
Cook Islands
CK
CL
Chile
CM Cameroon
CN
CO
CR
CU
CV
CY
CZ
DJ
DM Dominica
Dominican Republic
DO
Algeria
DZ
Ecuador
EC
Estonia
EE
Egypt
EG
Eritrea
ER
Ethiopia
ET
FJ
Fiji
FM Micronesia
GA
GD

China
Colombia
Costa Rica
Cuba
Cabo Verde
Cyprus
Czechia
Djibouti

Gabon
Grenada

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

2
1
5
4
4
5
5
4
3
6
3
2
1
2
3
1
4
5
3
2
4
1
5
3
1
4
6
2
2
5
6
4
4
1
4
3
2
2
3
5
3
4
2
6
2
3
5
1
5
3

949.0
11.7
3 050.0
2 383.8
8 177.4
80 310.2
7 209.9
4 395.5
1 750.2
43 150.6
1 173.7
3 359.1
1 049.4
135.2
1 093.1
4.6
9 125.0
107 977.6
1 571.3
688.2
3 080.9
1 987.7
558.0
540.2
35.1
1 512.5
7 457.3
172.6
13 071.2
5 761.1
99 538.6
57 654.8
10 110.1
47.9
533.8
1 291.2
866.3
182.1
15.7
14 812.5
9 082.3
22 672.9
365.3
33 388.5
43.5
877.9
1 648.2
69.6
3 598.4
52.8

515.6
3.6
1 538.5
1 837
4 263.5
24 482.2
3 790.3
1 941.0
947.4
16 748.8
643.6
556.3
419.4
95.9
542.2
-
4 780.7
29 300.7
898.2
471.1
1 153.6
908.7
181.6
78.0
16.6
589.6
1 995.3
113.1
2 538.2
2 222.3
37 936.5
25 513.5
4 175.6
16.6
344.2
299.1
300.0
97.1
1.1
5 777.0
750.0
12 376.0
200.0
16 690.8
17.6
554.5
836.7
32.7
1 629.5
17.3

2005
2013
1994
1993
1984
1984
1994
1984
1984
1984
1984
1991
1997
1984
1984
2005
1984
1984
1984
1984
1984
1993
1984
1984
1984
1984
1984
2009
1984
1984
1984
1984
1984
2013
1984
1984
1991
1984
1984
1984
1984
1984
1992
1984
1994
1984
1984
2005
1984
1995

2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2011
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023

1999
1999
1999
1999
1997
1986
1999
1997
1994
1999
1999
1996
1996
2007
1999
1999
1998
1986
1997
1999
1999
1999
1999
1997
1999
1997
1999
1998
1992
1999
1988
1993
1997
2023
1999
1994
1993
2009
2009
1997
1999
1997
1997
1996
2007
1999
1999
2009
1999
2014

10     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
                    
                      
                      
                          
                      
                      
                      
                      
                    
                        
                      
                         
                          
                      
                    
                      
                      
                    
                      
                    
                        
                      
                        
                      
                    
                      
                      
                        
                    
                      
                      
                    
                      
                    
                        
                      
                          
                      
                    
                      
                      
                        
                    
                      
                      
                      
                        
                      
                        
Table 8 (continued): Dataset information for included countries  

ISO 
country 
code

Country

Region

Number of 
MDBs with 
lending

Cumulative 
signed amount
(in € million)

Outstanding
 31 Dec. 2023
(in € million)

First year 
in dataset

Last year 
in dataset

First year 
of GEMs 
rating

Georgia
Ghana

GE
GH
GM Gambia
Guinea
GN
Equatorial Guinea
GQ
GT
Guatemala
GW Guinea-Bissau
Guyana
GY
Honduras
HN
Croatia
HR
Haiti
HT
Hungary
HU
Indonesia
ID
Israel
IL
India
IN
Iraq
IQ
IR
Iran
JM Jamaica
Jordan
JO
Kenya
KE
Kyrgyzstan
KG
Cambodia
KH
KI
Kiribati
KM Comoros
KN
KR
KZ
LA
LB
LC
LK
LR
LS
LT
LV
MA Morocco
MD Moldova
ME Montenegro
MG Madagascar
MH Marshall Islands
MK
ML Mali
MM Myanmar
MN Mongolia
MR Mauritania
MU Mauritius
MV Maldives
MW Malawi
MX Mexico
MY Malaysia
MZ Mozambique
NA
NC
NE
NG
NI
NP
NR

Namibia
New Caledonia
Niger
Nigeria
Nicaragua
Nepal
Nauru

Saint Kitts and Nevis
Korea
Kazakhstan
Laos
Lebanon
Saint Lucia
Sri Lanka
Liberia
Lesotho
Lithuania
Latvia

North Macedonia

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

6
3
3
4
2
4
2
5
5
3
1
3
6
1
6
2
2
3
5
4
6
4
2
2
2
2
4
4
4
2
5
3
3
2
2
5
4
4
3
1
4
3
2
5
4
4
5
3
4
3
4
3
1
3
5
5
4
1

6 685.4
642.7
357.0
1 274.1
128.8
12 185.8
76.3
1 714.0
9 109.0
6 195.8
72.8
13 707.6
123 248.9
257.3
147 680.1
4 721.2
5 303.5
6 410.7
10 507.0
5 350.0
1 686.4
5 729.9
40.3
41.0
26.9
21 931.0
14 620.3
1 853.9
5 106.3
76.3
15 971.6
265.0
373.5
1 323.1
931.7
42 182.8
1 440.2
1 952.0
547.9
108.8
3 406.7
1 055.4
4 268.7
3 282.4
809.6
2 261.1
561.4
557.8
92 885.4
6 694.8
815.4
1 862.4
20.0
838.9
12 884.9
7 890.2
9 329.8
4.4

4 708.7
204.8
248.3
627.5
27.9
4 025.7
31.2
771.9
4 496.6
1 951.9
33.4
905.5
34 924.1
-
50 879.8
2 774.0
1 089.8
2 349.5
4 480.3
2 724.6
906.1
2 347.9
17.8
16.8
-
-
5 573.9
928.4
1 142.9
7.1
7 167.5
84.7
84.4
658.4
2.5
16 129.6
737.7
693.3
333.6
27.5
1 076.9
585.8
719.6
2 168.2
345.9
770.2
222.3
265.0
26 608.4
17.5
422.1
988.2
11.7
373.8
2 481.3
4 330.3
2 847.0
-

1997
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1984
1996
1999
1984
1991
1984
1993
1984
1984
1986
1984
1984
1984
1992
1992
1984
1993
2001
1984
2001
1984
1984
1984
1996
1984
1984
1984
1984
1984
1984
1984
1994
2014
1984
1984
1984
1984
1999

2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
1997
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2020
2013
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2013

1999
1999
1999
1999
2000
1990
1999
1999
1989
1997
2000
1989
1992
1988
1988
1997
2008
1998
1995
1999
1999
2023
2009
2009
2000
1986
1996
2000
1997
2018
1999
1997
1999
1996
1997
1998
2009
2004
1999
2006
1992
1999
1998
1999
1999
1996
1999
1999
1990
1986
1999
2005
unrated
1999
1999
1984
1999
2000

Characteristics of sovereign and sovereign-guaranteed lending     11 

 
                    
                      
                    
                      
                      
                    
                        
                      
                        
                      
                      
                        
                      
                    
                          
                      
                      
                        
                      
                        
                      
                          
                          
                      
                      
                          
                    
                        
                    
                        
                      
                    
                          
                      
                      
                    
                      
                    
                        
                      
                      
                    
                      
                      
                    
                      
                    
                      
                        
                    
                      
                      
                      
                        
                    
                      
                         
                          
Table 8 (continued): Dataset information for included countries  

ISO 
country 
code

Country

Region

Number of 
MDBs with 
lending

Cumulative 
signed amount
(in € million)

Outstanding
 31 Dec. 2023
(in € million)

First year 
in dataset

Last year 
in dataset

First year 
of GEMs 
rating

Panama
Peru
French Polynesia
Papua New Guinea
Philippines
Pakistan
Poland
Palestinian territories

Saudi Arabia
Solomon Islands
Seychelles
Sudan
Slovenia
Slovakia
Sierra Leone
Senegal
Suriname
South Sudan
Sao Tome and Principe
El Salvador
Sint Maarten
Syria
Swaziland
Chad
Togo
Thailand
Tajikistan
Timor-Leste

OM Oman
PA
PE
PF
PG
PH
PK
PL
PS
PW Palau
Paraguay
PY
Qatar
QA
Romania
RO
Serbia
RS
RU
Russia 
RW Rwanda
SA
SB
SC
SD
SI
SK
SL
SN
SR
SS
ST
SV
SX
SY
SZ
TD
TG
TH
TJ
TL
TM Turkmenistan
Tunisia
TN
Tonga
TO
Türkiye
TR
Trinidad and Tobago
TT
Tuvalu
TV
Tanzania
TZ
Ukraine
UA
Uganda
UG
Uruguay
UY
Uzbekistan
UZ
Saint Vincent and the Grenadines
VC
Venezuela
VE
British Virgin Islands
VG
Vietnam
VN
Vanuatu
VU
Samoa
WS
Kosovo (temporary code)
XK
Yemen
YE
ZA
South Africa
ZM Zambia
ZW Zimbabwe

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

2
4
4
1
4
5
6
2
2
2
4
1
3
3
3
3
2
2
4
3
2
2
4
5
4
1
2
5
1
4
4
4
4
3
5
2
3
5
3
6
3
2
4
2
4
3
6
2
3
1
4
2
2
4
1
4
4
4

1 498.9
13 025.0
29 552.0
7.5
6 470.0
70 290.9
66 496.5
16 304.1
183.1
148.0
8 840.2
0.3
16 664.8
11 847.1
15 087.3
352.8
242.7
267.7
399.9
975.2
477.3
1 485.2
391.5
5 298.1
1 362.2
1.6
30.7
13 326.4
44.2
2 091.4
1 164.8
866.4
379.3
17 426.5
924.5
482.4
1 474.5
30 730.8
96.1
72 870.9
2 306.9
7.6
2 376.1
25 197.3
1 565.2
13 599.5
18 489.0
30.5
10 084.6
5.5
24 189.4
125.5
208.1
503.1
242.7
13 073.5
2 046.1
1 898.2

917.2
5 942.7
7 972
5.8
2 356.9
26 292.2
18 833.8
6 187.4
18.7
132.8
4 067.7
-
4 811.7
4 564.3
1 187.1
233.5
131.5
75.2
242.6
576.9
109.8
875.6
221.2
2 842.1
793.1
0.5
21.1
4 820.8
46.2
891.5
404.2
395.8
127.2
1 720.2
555.8
166.5
1 267.1
8 587.8
23.6
19 789.3
645.8
1.5
843.9
14 201.6
836.8
4 707.5
10 689.9
-
1 821
-
9 191.7
52.3
56.2
213.7
158.8
6 630.6
643.5
736.7

1984
1984
1984
2012
1984
1984
1984
1990
1995
2006
1984
2005
1984
1984
1992
1984
1999
1984
1984
1984
1984
1991
1984
1984
1985
2021
1984
1984
2019
1984
1984
1984
1984
1984
1997
2012
1994
1984
1984
1984
1984
2004
1984
1993
1984
1984
1993
1989
1984
1994
1984
1999
1984
2001
1990
1984
1984
1984

2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2013
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2023
2022
2023
2013
2023
2023
2023
2023
2023
2023
2023
2023

1996
1988
1987
unrated
1998
1993
1994
1995
2009
unrated
1995
1996
1996
1997
2022
1999
1996
2000
1999
1997
1996
1994
2000
1999
1993
2013
2000
1996
2020
1997
2007
1999
1999
1989
1999
2013
2010
1995
2009
1992
1993
2009
1999
1998
1999
1993
1999
1999
1983
unrated
1997
2009
2009
2011
1999
1994
1999
1999

Total

1 715 388.9

589 129.7

12     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

                      
                         
                          
                    
                        
                    
                      
                         
                          
                    
                      
                    
                      
                    
                        
                    
                      
                    
                      
                    
                      
                      
                    
                      
                      
                         
                          
                      
                        
                      
                        
                      
                      
                    
                      
                    
                      
                    
                      
                    
                      
                      
                        
                      
                         
                          
                      
                      
                      
                          
                         
                          
                    
                        
                    
                        
                    
                      
                    
                      
                      
                      
3  Default rate statistics 

3.1 Annual default rate methodology 
The annual default rates and their averages and confidence intervals presented in this publication are derived 
for the respective dimensions and categories using the equations below. 

Annual default rates are calculated as: 

Equation 1: Annual default rate for year i 

Where: 

𝑥𝑥𝑖𝑖 =  

𝑑𝑑𝑖𝑖
𝑤𝑤𝑖𝑖

  = Number of new defaults of countries during year i 
 = Number of performing countries as of 1 January of year i 

𝑑𝑑𝑖𝑖
𝑤𝑤𝑖𝑖

Annual default rates are averaged using the number of performing countries as of 1 January of each year as 
weights: 

Equation 2: Average annual default rate 

∗

Where: 

𝑥𝑥̅

=  

𝑁𝑁
∑ 𝑤𝑤𝑖𝑖𝑥𝑥𝑖𝑖
𝑖𝑖=1
𝑁𝑁
 ∑ 𝑤𝑤𝑖𝑖
𝑖𝑖=1

  = Number of years 

Standard deviations of annual default rates are calculated using the number of performing countries as of 
1 January of each year as weights: 

𝑁𝑁

Equation 3: Standard deviation of annual default rates 

 𝜎𝜎 = �

∗

2

)

𝑁𝑁
𝑖𝑖=1

∑ 𝑤𝑤𝑖𝑖(𝑥𝑥𝑖𝑖 −   𝑥𝑥̅
(N − 1)
𝑁𝑁

𝑁𝑁
 ∑ 𝑤𝑤𝑖𝑖
𝑖𝑖=1

Assuming default rates are normally distributed, the confidence intervals around the averages are determined 
as: 

Equation 4: Confidence intervals for annual default rates 

𝐶𝐶𝐶𝐶𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 =   𝑥𝑥̅

∗

+  z ∗

Where: 

𝐶𝐶𝐶𝐶𝑙𝑙𝑙𝑙𝑤𝑤𝑢𝑢𝑢𝑢 =   𝑥𝑥̅

∗

−  z ∗

σ

√N
σ

√N

  = 

- value from the standard normal distribution for the chosen confidence interval 

∗

𝑧𝑧

∗

𝑧𝑧

Default rate statistics     13 

  
  
 
 
 
3.1.1  Annual default rates by year 
Some of the 40 individual annual default rates are 0.00% since the observed 50 defaults are not distributed 
evenly over the 40 years. The range and 90% confidence interval (0.00% to 6.02% and 0.67% to 1.45%, 
respectively) for the dataset are relatively large because of the overall scarcity of observations. 

Table 9: Annual default rates 

Defaults

Active countries

Annual default rate

Year

1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023

1
0
2
5
1
1
2
1
5
3
1
0
0
1
2
1
5
1
0
2
0
0
1
0
0
0
0
0
1
2
1
0
0
0
2
0
0
0
6
3

83
83
84
83
82
80
78
79
84
93
97
102
105
105
104
105
108
104
111
114
115
116
120
139
140
141
146
146
146
146
143
142
140
150
152
152
153
153
154
148

Total

50

4 726

1.20%
0.00%
2.38%
6.02%
1.22%
1.25%
2.56%
1.27%
5.95%
3.23%
1.03%
0.00%
0.00%
0.95%
1.92%
0.95%
4.63%
0.96%
0.00%
1.75%
0.00%
0.00%
0.83%
0.00%
0.00%
0.00%
0.00%
0.00%
0.68%
1.37%
0.70%
0.00%
0.00%
0.00%
1.32%
0.00%
0.00%
0.00%
3.90%
2.03%

1.06%

14     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

3.1.2  Annual default rates by region 
The World Bank Group classification of countries to regions is used for the statistics shown in this section. The 
allocation of individual countries to regions can be found in Table 8. 

Table 10: Annual default rates by region  

Region

Unique 
countries

Observed
years

Number of
defaults

Number of
observations

Signed 
amount
in € million

Lower of 90% 
confidence 
interval

Average 
annual 
default rate

Upper of 90% 
confidence 
interval

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

Overall

28
31
35
17
8
47

166

40
40
40
40
40
40

40

3
5
12
6
1
23

50

638
880
1 168
445
247
1 348

4 726

388 337
258 183
542 290
146 770
284 827
94 981

1 715 388

0.00%
0.00%
0.58%
0.44%
0.00%
0.99%

0.67%

0.47%
0.57%
1.03%
1.35%
0.40%
1.71%

1.06%

0.95%
1.46%
1.48%
2.25%
0.99%
2.42%

1.45%

Figure 10: Dataset composition by region 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Unique countries

Number of
defaults

Number of
observations

Signed amount
in € million

East Asia & Pacific
Middle East & North Africa

Europe & Central Asia
South Asia

Latin America & Caribbean
Sub-Saharan Africa

Default rate statistics     15 

 
 
 
 
 
 
Figure 11: Annual default rates by region 

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

0.00%

East Asia &
Pacific

Europe &
Central Asia

Latin America &
Caribbean

Middle East &
North Africa

South Asia

Sub-Saharan Africa

90% confidence interval

Average annual default rate

16     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
 
3.1.3  Annual default rates by historic income group 
The World Bank Group database on historic income groups is used for assigning countries to groups for each 
year of the observation period. For this statistic, the number of observed years is reduced to 37 as historic 
income groups are only available from 1987. Two countries in the dataset are currently not categorised by 
the World Bank Group. The signed amounts and count of unique countries shown in this section reflect income 
groups at the date of reporting. 

Table 11: Annual default rates by historic income group 

Income Group

Unique 
countries

Observed
years

Number of
defaults

Number of
observations

Signed 
amount
in € million

Lower of 90% 
confidence 
interval

Average 
annual default 
rate

Upper of 90% 
confidence 
interval

High income
Upper-middle income
Lower-middle income
Low income
Not available

Overall

33
53
54
24
2

166

37
37
37
37
38

40

0
11
18
16
5

50

433
1 301
1 657
1 022
313

4 726

132 155
889 544
668 298
15 135
10 257

1 715 388

0.00%
0.38%
0.65%
0.81%
0.00%

0.67%

0.00%
0.85%
1.09%
1.57%
1.60%

1.06%

0.00%
1.31%
1.52%
2.32%
3.46%

1.45%

Note: The historic income group is defined as of default date. Signed amounts, however, reflect current income 
groups.  

Figure 12: Dataset composition over time by historic income group – percentage of active countries 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

4
8
9
1

5
8
9
1

6
8
9
1

7
8
9
1

8
8
9
1

9
8
9
1

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

8
0
0
2

9
0
0
2

0
1
0
2

1
1
0
2

2
1
0
2

3
1
0
2

4
1
0
2

5
1
0
2

6
1
0
2

7
1
0
2

8
1
0
2

9
1
0
2

0
2
0
2

1
2
0
2

2
2
0
2

3
2
0
2

High income

Upper-middle income

Lower-middle income

Low income

Not available

Default rate statistics     17 

 
 
 
 
Figure 13: Dataset composition by historic income group 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Unique countries

Number of
defaults

Number of
observations

Signed amount
in € million

High income

Upper-middle income

Lower-middle income

Low income

Not available

Figure 14: Annual default rates by historic income group 

4.00%

3.50%

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

0.00%

High income

Upper-middle income Lower-middle income

Low income

Not available

90% confidence interval

Average annual default rate

18     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
 
3.2 Default rates by credit rating  
The GEMs default rate calculation by credit rating for sovereign and sovereign-guaranteed lending follows a 
static cohort approach in which cohorts of countries with the same rating are established on 1 January of each 
year. Then, the default behaviour of the countries in each cohort is recorded until the end of the observation 
period. 

A static cohort approach was selected because it reflects the form of lending that multilateral development 
banks typically provide to developing countries. At any given time,  multiple loans are outstanding to each 
country, and new loans are added as existing loans mature and are paid down. This results in an ongoing 
exposure to the countries without a final maturity. 

Following the static cohort approach for each credit rating, the marginal default rate in 
formed in 

 is calculated as: 

Equation 5: Marginal default rate for a static cohort 

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑗𝑗

 for a cohort 

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑖𝑖

Where: 

𝑖𝑖
𝑀𝑀𝑀𝑀𝑀𝑀𝑗𝑗
=  
 for the cohort formed in 
 = Number of defaulted countries in 
𝑗𝑗
 = Number of performing countries on 1 January of 
𝑑𝑑𝑖𝑖
𝑛𝑛𝑗𝑗
Combining all cohorts for each credit rating, the weighted marginal default rate in 
formed in 

 is calculated as: 

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑗𝑗

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑗𝑗

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑖𝑖

𝑖𝑖
𝑑𝑑𝑗𝑗
𝑛𝑛𝑗𝑗

Equation 6: Marginal default rate for all static cohorts 

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑗𝑗

 for all cohorts 

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑖𝑖

Where: 

∑

𝐾𝐾
𝑗𝑗=1
𝐾𝐾
𝑗𝑗=1

𝑖𝑖
𝑑𝑑𝑗𝑗
𝑛𝑛𝑗𝑗

𝑤𝑤𝑀𝑀𝑀𝑀𝑀𝑀𝑖𝑖 =
 = Total number of cohorts for a credit rating, meaning the number of years for which a cohort has been 
∑
established for a given credit rating 
𝐾𝐾

Default rate statistics     19 

 
 
 
 
 
 
 
3.2.1  Marginal default rates by credit rating category 
The observed marginal default rates in Table 12 do not show the same pattern as those in similar tables for 
sovereign or corporate exposures provided by credit rating agencies. Only 50 defaults over a 40-year history 
leaves many cells empty or with values of 0.00%. Therefore, unlike tables from credit rating agencies, Table 12 
includes not rated (NR) as a rating category, as this state represents a large part of the historical observations. 
The results for NR illustrate that unrated countries are not necessarily more likely to default on loans  from 
multilateral development banks than rated ones. 

Table 12: Marginal default rates by credit rating category and year 

During 
year
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

28

29

30

31

32

33

34

35

36

37

38

39

40

AAA

AA

A

BBB

BB

B

CCC

CC/C

SD

NR

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.20%

0.21%

0.22%

0.23%

0.00%

0.00%

0.00%

0.27%

0.29%

0.31%

0.34%

0.37%

0.81%

0.44%

0.48%

0.52%

0.57%

0.62%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.19%

0.20%

0.21%

0.22%

0.23%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.46%

0.51%

0.56%

0.00%

1.42%

1.63%

2.88%

2.44%

1.64%

0.00%

0.00%

3.85%

5.56%

7.14%

0.44%

0.47%

0.79%

0.84%

0.91%

0.99%

0.67%

0.58%

0.63%

0.85%

1.10%

1.19%

1.31%

1.46%

1.37%

1.23%

1.06%

1.20%

1.36%

1.56%

1.22%

2.16%

0.87%

1.15%

0.00%

0.00%

0.00%

4.17%

5.00%

0.00%

0.00%

0.00%

10.00% 0.00%

12.50% 0.00%

12.50% 0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

2.68%

1.83%

0.94%

0.96%

0.97%

1.00%

1.04%

2.25%

2.38%

1.25%

1.39%

1.79%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

1.41%

1.16%

0.71%

0.75%

0.78%

0.82%

1.07%

0.91%

0.72%

1.04%

0.84%

0.60%

0.64%

1.01%

1.08%

1.19%

1.34%

0.52%

0.61%

0.73%

1.87%

2.63%

4.26%

4.17%

0.00%

13.79% 2.02%

4.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

1.96%

2.03%

1.82%

1.53%

1.24%

1.03%

0.81%

0.74%

0.67%

0.52%

0.45%

0.45%

0.46%

0.53%

0.54%

0.39%

0.16%

0.08%

0.08%

0.08%

0.08%

0.08%

0.17%

0.26%

0.35%

0.47%

0.50%

0.54%

0.47%

0.26%

0.29%

0.33%

0.37%

0.42%

0.50%

0.62%

0.81%

1.22%

1.22%

20     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
3.2.2  Cumulative default rates by credit rating category 
Table 13: Cumulative default rates by credit rating category and year 

AAA

AA

A

BBB

BB

B

CCC

CC/C

SD

NR

During 
year
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

28

29

30

31

32

33

34

35

36

37

38

39

40

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.20%

0.41%

0.63%

0.85%

0.85%

0.85%

0.85%

1.12%

1.41%

1.71%

2.05%

2.41%

3.20%

3.62%

4.09%

4.59%

5.13%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

5.72%

0.00%

0.00%

0.00%

0.00%

0.19%

0.40%

0.61%

0.83%

1.06%

1.06%

1.06%

1.06%

1.06%

1.06%

1.06%

1.06%

1.06%

1.06%

1.52%

2.01%

2.56%

2.56%

3.94%

5.50%

8.23%

0.44%

0.91%

1.69%

2.52%

3.40%

4.35%

4.99%

5.55%

6.14%

6.94%

7.97%

9.07%

1.41%

2.56%

3.25%

3.97%

4.73%

5.50%

6.52%

7.37%

8.04%

9.00%

9.77%

2.68%

4.46%

5.37%

6.28%

7.19%

8.11%

9.07%

13.79% 2.02%

17.24% 3.94%

17.24% 5.90%

17.24% 7.61%

17.24% 9.03%

17.24% 10.16%

17.24% 11.09%

11.11% 17.24% 11.81%

13.23% 17.24% 12.46%

14.32% 17.24% 13.05%

15.51% 17.24% 13.50%

10.31% 17.01% 17.24% 13.89%

10.26% 10.88% 17.01% 17.24% 14.29%

11.57% 11.78% 17.01% 17.24% 14.68%

12.78% 12.73% 17.01% 17.24% 15.13%

13.85% 13.77% 17.01% 17.24% 15.59%

14.76% 14.92% 17.01% 17.24% 15.92%

15.79% 15.36% 17.01% 17.24% 16.05%

16.94% 15.88% 17.01% 17.24% 16.12%

18.24% 16.49% 17.01% 17.24% 16.19%

19.23% 18.05%

20.98% 20.21%

21.66% 23.60%

22.56% 26.79%

22.56% 26.79%

10.47% 22.56%

11.94% 22.56%

11.94% 25.79%

11.94% 29.50%

15.32% 29.50%

20.03% 29.50%

25.74% 29.50%

33.17% 29.50%

41.52% 29.50%

48.83% 29.50%

48.83% 29.50%

48.83%

48.83%

48.83%

48.83%

17.24% 16.26%

17.24% 16.33%

16.39%

16.54%

16.75%

17.04%

17.43%

17.84%

18.29%

18.67%

18.88%

19.12%

19.38%

19.68%

20.02%

20.42%

20.91%

21.55%

22.50%

23.45%

Default rate statistics     21 

 
 
 
3.2.3  Marginal default rates by credit rating 
Breaking down the rating categories into individual ratings as illustrated in Figure 14 increases the impact of the scarcity of default observations. 

Table 14: Marginal default rates by credit rating and year 

During 
year

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
28
29
30
31
32
33
34
35
36
37
38
39
40

AAA

AA+

AA

AA-

A+

A

A-

BBB+

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC+

CCC

CCC-

CC

C

SD

NR

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
1.56%
1.64%
1.75%
1.92%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.46%
0.47%
0.49%
0.51%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
1.35%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.88%
0.92%
1.00%
1.10%
1.23%
1.41%
0.00%
0.00%
0.00%
2.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.65%
0.68%
0.71%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
1.37%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.62%
0.65%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
2.22%
0.00%
6.06%
6.90%
3.85%
0.00%
0.00%
0.00%
0.00%
25.00% 0.00%
33.33% 0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.25%
0.00%
0.26%
0.00%
0.28%
0.32%
0.61%
0.34%
0.67%
0.35%
0.38%
0.74%
0.42%
0.78%
0.46%
0.41%
0.99%
0.45%
1.06%
0.95%
0.58%
1.52%
1.91%
1.08%
2.11%
1.19%
1.59%
1.32%
0.00%
1.41%
0.00%
0.76%
0.00%
1.75%
0.00%
1.96%
1.64%
1.05%
2.00%
1.14%
2.38%
1.30%
2.78%
2.94%
0.00%
0.00%
0.00%
2.27%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
7.14%
0.00%
10.00% 0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
1.23%
0.00%
0.00%
0.00%
0.00%
5.00%
5.88%
3.57%
0.00%
0.00%
0.00%
0.00%
12.50% 0.00%
20.00% 0.00%
25.00% 0.00%
25.00% 0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

14.29% 1.90%
1.94%
0.00%
1.00%
0.00%
1.02%
0.00%
1.03%
0.00%
1.06%
0.00%
1.11%
0.00%
2.38%
0.00%
2.50%
0.00%
1.30%
0.00%
1.45%
0.00%
1.89%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.80%
1.79%
0.50%
1.69%
1.23%
0.68%
2.31%
1.69%
1.85%
2.13%
0.00%
0.00%
1.67%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

1.73%
2.50%
0.29%
5.13%
0.30%
6.06%
0.00%
3.70%
0.31%
4.17%
0.62%
4.55%
0.63%
0.00%
0.66%
0.00%
0.34%
0.00%
0.73%
0.00%
1.15%
0.00%
0.80%
0.00%
0.41%
0.00%
1.26%
0.00%
1.30%
0.00%
1.44%
0.00%
1.63%
0.00%
0.63%
0.00%
0.71%
0.00%
0.83%
0.00%
2.11%
0.00%
3.03%
0.00%
0.00%
4.88%
50.00% 0.00%
0.00%
0.00%

1.04%
1.10%
1.74%
1.54%
1.67%
1.81%
0.80%
0.88%
0.48%
0.53%
1.16%
0.62%
0.68%
1.52%
2.61%
3.06%
1.18%
1.35%
1.56%
1.85%
0.00%
0.00%
3.45%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

13.79% 2.02%
1.96%
4.00%
2.03%
0.00%
1.82%
0.00%
1.53%
0.00%
1.24%
0.00%
1.03%
0.00%
0.81%
0.00%
0.74%
0.00%
0.67%
0.00%
0.52%
0.00%
0.45%
0.00%
0.45%
0.00%
0.46%
0.00%
0.53%
0.00%
0.54%
0.00%
0.39%
0.00%
0.16%
0.00%
0.08%
0.00%
0.08%
0.00%
0.08%
0.00%
0.08%
0.00%
0.08%
0.17%
0.26%
0.35%
0.47%
0.50%
0.54%
0.47%
0.26%
0.29%
0.33%
0.37%
0.42%
0.50%
0.62%
0.81%
1.22%
1.22%

22     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
3.2.4  Cumulative default rates by credit rating 
Table 15: Cumulative default rates by credit rating and year 

During 
year

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
28
29
30
31
32
33
34
35
36
37
38
39
40

AAA

AA+

AA

AA-

A+

A

A-

BBB+

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC+

CCC

CCC-

CC

C

SD

NR

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
1.56%
3.18%
4.87%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%
6.70%

0.46%
0.93%
1.42%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
1.92%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%
3.24%

0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.88%
1.79%
2.77%
3.84%
5.02%
6.36%
6.36%
6.36%
6.36%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%
8.23%

0.00%
0.00%
0.00%
0.00%
0.65%
1.32%
2.02%
2.02%
2.02%
2.02%
2.02%
2.02%
2.02%
2.02%
2.02%
2.02%
2.02%
2.02%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%
3.36%

0.80%
2.57%
3.06%
4.69%
5.86%
6.50%
8.66%

1.73%
2.50%
1.04%
0.25%
7.50%
2.02%
2.13%
0.51%
13.11% 2.31%
3.83%
0.79%
16.32% 2.31%
5.32%
1.39%
19.81% 2.62%
6.90%
2.06%
23.46% 3.22%
8.58%
2.42%
9.31%
23.46% 3.83%
2.83%
10.11% 10.21% 23.46% 4.46%
3.28%
10.54% 11.87% 23.46% 4.79%
4.23%
11.02% 13.74% 23.46% 5.49%
5.25%
12.04% 13.74% 23.46% 6.58%
5.80%
12.59% 13.74% 23.46% 7.32%
7.60%
9.55%
13.18% 15.18% 23.46% 7.71%
10.99% 14.49% 15.18% 23.46% 8.87%

13.79% 2.02%
14.29% 1.90%
0.00%
0.00%
0.00%
17.24% 3.94%
14.29% 3.81%
0.00%
0.00%
0.00%
17.24% 5.90%
14.29% 4.77%
0.32%
0.00%
0.00%
17.24% 7.61%
14.29% 5.74%
0.66%
0.00%
0.00%
17.24% 9.03%
14.29% 6.71%
1.00%
0.00%
0.00%
17.24% 10.16%
14.29% 7.71%
1.74%
0.00%
0.00%
14.29% 8.73%
17.24% 11.09%
2.51%
0.00%
0.00%
14.29% 10.91% 17.24% 11.81%
2.91%
0.62%
0.00%
14.29% 13.13% 17.24% 12.46%
3.34%
1.27%
0.00%
14.29% 14.26% 17.24% 13.05%
4.26%
1.27%
0.00%
14.29% 15.50% 17.24% 13.50%
5.71%
1.27%
0.00%
14.29% 17.10% 17.24% 13.89%
6.73%
1.27%
0.00%
14.29% 17.10% 17.24% 14.29%
7.84%
1.27%
0.00%
9.06%
14.29% 17.10% 17.24% 14.68%
1.27%
0.00%
10.34% 10.99% 16.72% 15.18% 23.46% 10.06% 14.29% 17.10% 17.24% 15.13%
1.27%
0.00%
11.02% 10.99% 19.27% 15.18% 23.46% 11.36% 14.29% 17.10% 17.24% 15.59%
1.27%
0.00%
12.58% 10.99% 20.22% 15.18% 23.46% 12.80% 14.29% 17.10% 17.24% 15.92%
1.27%
0.00%
17.24% 16.05%
14.30% 10.99% 21.30% 15.18% 23.46% 13.35% 14.29%
1.27%
0.00%
17.24% 16.12%
15.20% 12.45% 22.53% 15.18% 23.46% 13.97% 14.29%
1.27%
0.00%
17.24% 16.19%
16.16% 14.20% 23.96% 15.18% 23.46% 14.68% 14.29%
1.27%
1.23%
17.24% 16.26%
17.25% 16.24% 23.96% 15.18% 23.46% 16.48%
3.46%
1.23%
17.24% 16.33%
19.69% 18.57% 23.96% 15.18% 23.46% 19.01%
3.46%
1.23%
16.39%
9.31%
19.69% 18.57% 26.59% 15.18% 23.46% 22.96%
1.23%
16.54%
15.57% 21.51% 18.57% 26.59% 15.18% 61.73% 22.96%
1.23%
16.75%
6.17%
61.73% 22.96%
18.81% 21.51% 18.57% 26.59%
17.04%
11.69% 18.81% 21.51% 18.57% 26.59%
17.43%
14.85% 18.81% 21.51% 18.57% 26.59%
17.84%
14.85% 18.81% 27.12% 18.57% 26.59%
18.29%
14.85% 18.81% 34.41% 18.57% 26.59%
18.67%
14.85% 39.11% 34.41% 18.57% 26.59%
18.88%
14.85% 59.41% 34.41% 18.57% 26.59%
19.12%
25.49% 59.41% 34.41% 18.57% 26.59%
19.38%
40.39% 59.41% 34.41% 18.57% 26.59%
19.68%
55.29% 59.41% 34.41% 18.57% 26.59%
20.02%
66.47% 59.41% 34.41% 18.57%
20.42%
66.47% 59.41% 34.41% 18.57%
20.91%
66.47% 59.41%
21.55%
66.47%
22.50%
66.47%
23.45%
66.47%

Default rate statistics     23 

 
4  Recovery rate statistics 

Recovery rates are determined for each default event of a country separately. As per the definition of sovereign 
and sovereign-guaranteed lending, all such loans by multilateral development banks to a country default on 
the same date and all return to a performing state on the same date. So far, all defaults covered by the GEMs 
dataset  have  ended  with  the  multilateral  development  bank  recovering  all  overdue  principal  and  interest 
amounts on a nominal basis, resulting only in losses from the cost of funding overdue interest amounts, as 
these are not capitalised or charged to borrowers. 

As detailed in Equation 7, recovery rates are calculated as the ratio of: 

A. 
B. 

the discounted payments received between the start and resolution of a default event, plus  
the discounted remaining outstanding principal amount immediately after resolution of the default 
event, divided by  

C.  the nominal outstanding principal and interest amounts at the start of the default event.  

Discounting is performed at the applicable lending rates back to the time of default. 

Equation 7: Calculation of recovery rates 

𝑀𝑀𝑀𝑀 =
Where: 

𝐴𝐴 + 𝐵𝐵
𝐶𝐶

=  

𝑅𝑅
𝑖𝑖=𝐷𝐷

∑

𝑃𝑃𝑃𝑃𝑃𝑃𝑖𝑖
(1 + 𝑑𝑑𝑦𝑦𝑖𝑖)

𝑖𝑖 +  

𝑃𝑃𝑦𝑦𝑛𝑛𝑅𝑅
𝑅𝑅
(1 + 𝑑𝑑𝑦𝑦𝑅𝑅)

𝑃𝑃𝑦𝑦𝑛𝑛𝐷𝐷 +   𝐶𝐶𝑛𝑛𝑃𝑃𝐷𝐷

= Start of default event 
= Resolution of default event 
= Numbered period for periods starting after D and ending with R 

  = Payment of principal or interest received during 
  = Remaining outstanding principal amount immediately after R 

  = Discount rate applicable to payments received during 
  = Outstanding principal amount at time of default (D) 
  = Outstanding interest amount at time of default (D) 

period 𝑖𝑖

period 𝑖𝑖

𝑀𝑀
𝑀𝑀
𝑖𝑖
𝑃𝑃𝑃𝑃𝑃𝑃𝑖𝑖
𝑃𝑃𝑦𝑦𝑛𝑛𝑅𝑅
𝑑𝑑𝑦𝑦𝑖𝑖
𝑃𝑃𝑦𝑦𝑛𝑛𝐷𝐷
𝐶𝐶𝑛𝑛𝑃𝑃𝐷𝐷

The average recovery rates in this publication are the simple average of the observations in the respective 
dimensions  and  categories.  Confidence  intervals  around  those  averages  are  not  provided  because  the 
recovery  rates  are  not  normally  distributed.  Instead,  the  ranges  and  various  percentiles  describing  the 
distributions  of  the  recovery  rates  are  presented.  Recovery  rates  for  unresolved  default  events  are  not 
calculated. 

24     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
4.1 Recovery rates by region 
The World Bank Group classification of countries to regions is used for the statistics shown in this section. The 
GEMs dataset does not currently contain any observations for recovery rates of countries in South Asia. The 
allocation of individual countries to regions can be found in Table 8. 

Table 16: Recovery rates by region  

Region

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

Overall

Unique 
defaulted 
countries
3
3
8
3

11

28

Number of 
defaults

3
3
14
3

21

44

Average 
recovery 
rate
95.4%
88.4%
97.4%
84.4%

95.5%

94.9%

Minimum 
observation

10th 
percentile

25th 
percentile

Median

75th 
percentile

90th 
percentile

Maximum 
observation

93.1%
73.3%
86.7%
74.1%

47.1%

47.1%

93.1%
77.7%
94.7%
75.1%

91.8%

87.8%

93.1%
84.3%
96.2%
76.6%

97.1%

95.5%

93.1%
95.3%
98.5%
79.1%

98.3%

98.0%

96.6%
96.0%
99.8%
89.5%

99.8%

99.8%

98.6%
96.4%
100.0%
95.8%

100.0%

100.0%

100.0%
96.7%
100.0%
100.0%

100.0%

100.0%

Figure 15: Recovery rates by region  

100%

95%

90%

85%

80%

75%

70%

East Asia &
Pacific

Europe &
Central Asia

Latin America &
Caribbean

Middle East &
North Africa

South Asia

Sub-Saharan Africa

25th percentile to 75th percentile

Median

Average recovery rate

Recovery rate statistics     25 

 
 
 
 
 
 
4.2 Recovery rates by historic income group 
The World Bank Group database on historic income groups is used for assigning countries to groups for the 
year of each default. Five countries in the dataset had not been categorised by the World Bank Group at the 
time of their defaults. The GEMs dataset does not currently contain any observations for recovery rates of high-
income countries. 

Table 17: Recovery rates by historic income group 

Region

High income
Upper-middle income
Lower-middle income
Low income
Not available

   Overall

Unique 
Defaulted 
Countries

Number of 
Defaults

Average 
recovery 
rate

Minimum 
observation

10th 
percentile

25th 
percentile

Median

75th 
percentile

90th 
percentile

Maximum 
observation

6
12
9
5

28

8
17
14
5

44

96.0%
96.4%
93.9%
90.2%

94.9%

74.1%
79.1%
47.1%
73.3%

47.1%

90.2%
93.3%
91.2%
78.7%

87.8%

98.0%
95.6%
96.9%
86.7%

95.5%

99.2%
97.6%
98.1%
93.1%

98.0%

100.0%
99.7%
99.7%
97.9%

99.8%

100.0%
100.0%
99.9%
99.2%

100.0%

100.0%
100.0%
100.0%
100.0%

100.0%

Note: The historic income group is defined as of default date.  

Figure 16: Recovery rates by historic income group 

100%

95%

90%

85%

80%

75%

70%

High income

Upper-middle income

Lower-middle income

Low income

Not available

25th percentile to 75th percentile

Median

Average recovery rate

26     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
 
 
5  Rating migrations 

The  rating  migrations  in  this  publication  are  based  on  the  GEMs  rating  determined  for  the  countries,  as 
described  in  Section 3.3.  Only  years  in  which  countries  have  exposure  to  at  least  one  of  the  multilateral 
development banks are considered. Migrations are taken as snapshots of ratings on 1 January of each year 
over the 40-year observation period. For example, for the one-year migration rates, the rating of each country 
on 1 January of 
. Intra-year rating changes are not 
considered. 

 is compared to the ratings on 1 January of 

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑖𝑖

𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑖𝑖+1

In addition to the ratings shown in migration tables by credit rating agencies, the tables in this report, following 
the GEMs rating scale, include “non-accrual” as a rating. As mentioned in Section 3.3, this rating category 
represents instances when countries are in default with multilateral development banks. “Non-accrual” is not 
considered an absorbing state, as the migration tables show the  movement of countries from non-accrual 
back to performing ratings. The SD (selective default) category signifies countries’ defaults to other lenders, 
such  as  commercial  banks  or  investors  in  bond  issuances,  that  occur  while  they  are  performing  on  their 
obligations to multilateral development banks. 

5.1 Annual upgrade vs. downgrade ratio 
Figure 17  shows  the  yearly  credit  rating  upgrades  and  downgrades  of  countries  in  the  GEMs  dataset. 
Migrations to and from not rated (NR) are excluded from the calculation, as they do not reflect changes in 
creditworthiness.  This  explains  the  limited  rating  changes  in  the  earlier  years  when  many  countries  in  the 
dataset were still unrated. 

The ratio of the yearly rating changes has been calculated as the difference of upgrades and downgrades over 
the total number of rating changes. 

Figure 17: Annual upgrade vs. downgrade ratio 

s
e
d
a
r
g
n
w
o
d
/
p
u
f
o
r
e
b
m
u
N

50
45
40
35
30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
-35
-40
-45
-50

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
-10%
-20%
-30%
-40%
-50%
-60%
-70%
-80%
-90%
-100%

o
i
t
a
R

4
8
9
1

5
8
9
1

6
8
9
1

7
8
9
1

8
8
9
1

9
8
9
1

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

8
0
0
2

9
0
0
2

0
1
0
2

1
1
0
2

2
1
0
2

3
1
0
2

4
1
0
2

5
1
0
2

6
1
0
2

7
1
0
2

8
1
0
2

9
1
0
2

0
2
0
2

1
2
0
2

2
2
0
2

Upgrades

Downgrades

Average ratio

Ratio: Difference of rating changes over total rating changes

Rating migrations     27 

 
 
 
 
 
5.2 Rating migration rates 

Table 18: One-year rating migration rates  

From/To Observations AAA

AA+

AA

AA-

A+

A

A-

BBB+

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC+

CCC

CCC-

CC

C

SD

Non-
accrual

NR

AAA

AA+

AA

AA-

A+

A

A-

BBB+

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC+

CCC

CCC-

CC

C

SD

Non-accrual

0

0

7

33

48

93

141

113

152

211

172

184

227

328

377

363

223

39

340

6

102

25

220

85.7% 14.3%

6.1% 78.8% 9.1%

3.0%

18.8% 70.8% 10.4%

3.0%

10.8% 79.6% 5.4%

2.2% 1.1% 1.1%

12.8% 79.4% 5.0% 2.8%

15.0% 72.6% 11.5%

0.9%

0.7% 15.1% 71.1% 9.2% 2.6% 0.7%

0.7%

0.5% 12.8% 74.9% 8.5% 1.4%

0.5% 0.5% 0.5%

0.5%

1.7% 18.6% 67.4% 7.0% 3.5% 1.2%

0.6%

1.1% 15.2% 69.6% 9.8% 2.2% 1.1%

0.5%

0.5%

0.4% 0.9% 9.3% 69.6% 14.1% 3.1% 1.8%

0.9%

0.3% 1.5% 9.5% 72.3% 11.3% 4.6% 0.6%

1.9% 10.3% 72.1% 7.4% 5.6% 0.8% 0.8% 0.3% 0.3% 0.3% 0.3%

0.8% 3.6% 8.5% 73.8% 5.5% 1.9% 4.1% 0.6% 0.3% 0.3% 0.6%

9.9% 9.9% 68.6% 4.0% 5.4%

0.9% 0.9% 0.4%

2.6% 7.7% 28.2% 38.5% 7.7% 2.6% 5.1% 7.7%

0.3%

0.3% 0.6% 0.9% 2.6% 5.3% 9.1% 0.3% 72.9%

5.0% 0.6% 1.5%

0.6%

16.7% 16.7% 16.7%

33.3% 16.7%

1.0%

2.0% 3.9% 2.0% 1.0% 15.7%

70.6% 2.0% 2.0%

4.0% 8.0% 4.0%

4.0% 12.0% 60.0% 8.0%

0.5%

0.5% 0.9%

3.6%

1.7%

0.5%

88.2% 5.9%

0.1% 0.1% 1.8% 90.0%

NR

1 371

0.1%

0.1% 0.4% 0.1% 0.3% 0.6% 0.4% 1.1% 0.8% 0.7% 0.7% 0.8% 0.3%

28     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
Table 19: Two-year rating migration rates  

From/To Observations AAA

AA+

AA

AA-

A+

A

A-

BBB+

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC+

CCC

CCC-

CC

C

SD

Non-
accrual

NR

AAA

AA+

AA

AA-

A+

A

A-

BBB+

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC+

CCC

CCC-

CC

C

SD

0

0

6

30

45

86

138

110

143

204

167

179

219

312

352

344

198

33

330

6

98

21

66.7% 16.7%

16.7%

13.3% 60.0% 20.0%

3.3%

28.9% 46.7% 20.0%

3.3%

2.2%

2.2%

1.2% 20.9% 59.3% 8.1%

7.0% 1.2% 1.2% 1.2%

0.7% 20.3% 65.9% 8.0% 3.6% 0.7% 0.7%

3.6% 20.9% 55.5% 15.5% 3.6%

0.9%

5.6% 18.9% 54.5% 11.9% 6.3% 2.1%

0.7%

0.5% 4.4% 18.6% 56.4% 12.3% 2.0% 2.0% 0.5% 1.0% 1.5%

0.5%

0.5%

0.6% 4.8% 27.5% 47.3% 10.8% 4.8% 2.4% 0.6% 1.2%

6.1% 21.8% 49.2% 14.5% 6.1%

1.1%

0.6% 0.6%

1.4% 1.8% 12.8% 50.7% 19.2% 7.8% 4.1% 0.5% 0.5%

1.4%

0.3%

1.0% 3.5% 12.5% 55.1% 17.0% 6.7% 1.3% 1.0% 1.3% 0.3%

0.3%

0.6% 3.4% 13.9% 55.4% 13.6% 7.7% 1.7% 1.4% 0.3% 1.1% 0.3% 0.3%

2.0% 8.7% 12.2% 56.4% 10.2% 2.6% 4.9% 0.3% 0.6% 1.7% 0.3%

0.5% 16.7% 13.6% 53.5% 4.5% 6.1% 0.5% 2.0% 1.0% 1.5%

12.1% 12.1% 30.3% 18.2% 9.1% 3.0% 3.0% 9.1% 3.0%

0.3%

0.3% 1.2% 1.8% 5.2% 10.9% 11.5%

56.1%

10.0% 0.3% 1.2%

1.2%

16.7% 16.7% 33.3% 16.7%

16.7%

2.0% 1.0% 3.1% 4.1% 6.1% 2.0% 26.5%

49.0% 2.0% 4.1%

9.5% 14.3%

9.5% 14.3% 42.9% 9.5%

Non-accrual

NR

213

1 359

0.1%

0.3% 0.7% 0.4% 0.5% 1.2% 0.9% 2.1% 1.5% 1.6% 1.4% 1.4% 0.7%

0.9%

0.9% 1.4%

6.6%

3.0%

0.9%

78.4% 10.8%

0.1% 0.1% 3.4% 80.6%

Rating migrations     29 

 
 
 
 
Table 20: Ten-year rating migration rates 

From/To Observations AAA

AA+

AA

AA-

A+

A

A-

BBB+

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC+

CCC

CCC-

CC

C

SD

Non-
accrual

NR

AAA

AA+

AA

AA-

A+

A

A-

BBB+

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC+

CCC

CCC-

CC

C

SD

0

0

5

16

25

64

90

67

91

134

127

138

126

198

171

173

83

13

259

3

69

12

Non-accrual

NR

169

1 267

40.0% 40.0% 20.0%

18.8% 62.5%

6.3% 6.3%

6.3%

8.0% 28.0% 24.0% 24.0% 4.0% 8.0%

4.0%

3.1% 12.5% 17.2% 1.6% 20.3% 6.3% 3.1% 1.6% 10.9% 4.7% 6.3% 7.8% 3.1%

1.6%

3.3% 8.9% 6.7% 8.9% 36.7% 7.8% 7.8% 11.1% 7.8% 1.1%

4.5% 4.5% 10.4% 14.9% 23.9% 7.5% 11.9% 11.9%

7.5% 1.5%

1.5%

1.1% 8.8% 9.9% 18.7% 23.1% 12.1% 4.4% 1.1% 6.6% 4.4% 3.3% 2.2% 1.1% 1.1%

1.1%

1.1%

0.7% 6.0% 6.7% 11.2% 13.4% 21.6% 12.7% 9.7% 6.0% 6.7% 1.5% 0.7% 3.0%

2.4% 6.3% 6.3% 7.9% 18.1% 12.6% 10.2% 7.9% 7.9% 3.1% 8.7% 6.3% 2.4%

0.7%

5.1% 13.8% 17.4% 12.3% 16.7% 3.6% 18.1% 3.6% 5.1% 1.4% 0.7%

1.4%

0.8% 0.8% 12.7% 6.3% 4.8% 14.3% 12.7% 16.7% 10.3% 7.1% 7.9% 2.4% 0.8%

0.8% 1.6%

0.5%

2.5% 5.6% 2.5% 4.0% 7.6% 26.3% 21.7% 14.6% 3.5% 2.5% 0.5% 1.5% 1.5% 2.0% 2.5%

0.5%

2.3% 3.5% 0.6% 2.9% 9.4% 18.7% 29.8% 17.0% 5.8% 2.3% 4.1% 0.6% 1.2% 1.2% 0.6%

0.6% 2.9% 2.9% 2.3% 15.6% 15.0% 15.6% 20.8% 11.0% 2.3% 1.7%

2.3% 1.7% 4.6%

0.6%

1.2% 3.6% 3.6% 2.4% 25.3% 37.3% 16.9% 3.6% 3.6%

2.4%

7.7%

0.4%

15.4% 7.7% 7.7% 7.7% 7.7% 38.5% 7.7%

6.6% 9.3% 20.8% 20.5% 18.1% 1.2% 10.8%

6.9% 0.4% 3.9%

1.2%

33.3%

33.3%

33.3%

1.4% 2.9% 4.3% 7.2% 24.6% 40.6% 1.4% 8.7%

8.7%

8.3%

8.3% 16.7% 16.7%

8.3% 33.3% 8.3%

2.4% 1.8% 9.5% 5.3% 8.3% 4.7%

24.9%

11.2%

21.3% 10.7%

0.3% 0.6% 1.9% 2.4% 1.3% 1.6% 4.9% 4.6% 5.4% 4.9% 8.1% 7.1% 7.1% 2.9% 0.6% 9.9% 0.1% 0.9% 0.7% 6.9% 27.8%

30     Default and recovery statistics: Sovereign and sovereign-guaranteed lending 1984-2023 

 
 
 
 
Multilateral development banks and development finance institutions

DEFAULT 
AND 
RECOVERY 
STATISTICS

SOVEREIGN AND  
SOVEREIGN-GUARANTEED 
LENDING 1984-2023

European Investment Bank
98 -100, boulevard Konrad Adenauer
L-2950 Luxembourg
+352 4379-1
www.eib.org – info@eib.org

pdf:

ISBN 978-92-861-5823-0  

EN   10/2024

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