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Coping with Disasters:
Two Centuries of International Official Lending
Sebastian Horn
(Kiel Institute)
Carmen Reinhart
(World Bank, Harvard)
Christoph Trebesch
(Kiel Institute)
World Bank
November 19, 2020
All views are personal
1
The Covid-19 disaster: private capital flows
“Sudden stop“ in
private capital flows
 limited risk sharing
2
The Covid-19 disaster: the official response
“Sudden spike“
in official flows
 risk sharing
(Horn 2020)
3
The (unexplored) world of official capital flows
– Extensive literature on private cross-border flows (see paper), but little
work/data on official flows; narrower focus/time spans
Our contribution: encompassing new database and analysis
of official international lending, 1790-2015
– Definition: includes loans, grants and guarantees by governments,
multilateral institutions and central banks across borders
– Sources: International treaty series (archives), creditor and debtor
budget accounts, annual reports, post-1970: World Bank, OECD
– 230,000 grants & loans by 134 governments, 50 intl. institutions,
in total 15 trillion real USD (committments in 2015 terms)
4
Who lends? The universe of official creditors
Bilateral
creditors
1800 1918
Multilateral
creditors
Regional Safety Nets
Regional Development Banks
League of Nations United Nations System
Bank for International Settlements
International Monetary Fund
World Bank
Foreign and Colonial Offices Ministries of Development
Export Credit Banks
Central Banks & Treasuries
1945 1973 2015
5
Examples of sources
Historical budget accounts CIA reports on Sino-Soviet loans
6
Disasters 1800-2015: A new database
We collect data on severe disasters from many sources:
 Financial crises: Banking, currency and sovereign debt crises
from Reinhart & Rogoff (2009) and Meyer et al. (2019)
 Wars and military conflict: Inter- and intra-state wars from
the Correlates of War project (Sarkees and Wayman 2010)
 Natural catastrophes: Earthquakes, storms, floods, volcano
eruptions, famines, epidemics from EM-DAT since 1900.
Dozens of historical and country studies for 1800-1900
7
Research questions and key take aways
1. Scale of official lending: It is large, often larger than private flows
– Rescue lending common long before IMF/World Bank
– Much more institutionalized today (“globalization of assistance“)
2. Interaction of private and official flows: When private flows
retrench, official lending often steps in
– Private capital tends to be pro-cyclical, while official flows tend to
be counter-cyclical (Covid crisis is a recent example)
3. Patterns of official lending: trade and financial integration matters
 What drives country rescues and official lending? (Tirole 2015,
Gourinchas et al. 2019)
 Bailouts increase with economic exposure (selfish motive vs.
altruism an intepretation issue) 8
A panorama of
international official lending
9
Official international lending: 1790 - 2015
10
Official lending is much bigger than IMF & World Bank
Regional
& others
Bilateral
(government to government)
IMF and World Bank
11
Central bank lending: credits then, swap lines now
Great Depression:
Short-term credits to
CBs of Germany,
Austria, Britain etc
2008 crisis:
US Fed emergency
dollar liquidity
12
Adding central bank lending across borders
13
When private investors retrench,
official lending often steps in
(private capital tends to be pro-cyclical,
while official flows tend to be counter-cyclical)
14
Official vs private capital flows: 200 year view
Official international
lending
Private international
capital flows Correlation: -0.36
15
Case study: Interwar and Great Depression
16
Case study: Asian crisis (1997)
17
Case study: Eurozone crisis (2010-2012)
18
Why do countries extend rescue loans?
(Who gets what and why?
Altruism or self-interest?)
19
Natural disasters: increasing odds of rescue lending
Probability of receiving official loans/grants
in major natural disasters, by era, in %
20
Why do countries extend rescue loans?
Main hypothesis: economic integration matters. Sovereigns
extend bilateral rescue loans to those countries with largest trade
and finance exposure (Tirole 2015, Gourinchas et al. 2019)
Interpretation: helping your friends vs. self-interest of preventing
negative spillovers
Empirical approach: gravity model of bilateral rescue lending:
𝒍𝒏 𝑹𝒆𝒔𝒄𝑳𝒐𝒂𝒏𝒔𝒊,𝒋,𝒕 = 𝛽 𝑙𝑛 𝐸𝑐𝑜𝑛 𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒𝑖,𝑗,𝑡 + 𝛾 𝑃𝑜𝑙𝑖𝑡𝑖𝑐𝑎𝑙 𝑇𝑖𝑒𝑠𝑖,𝑗,𝑡 +
𝛿 𝑙𝑛 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒𝑖,𝑗 + ∆ 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠𝑖,𝑗,𝑡 + 𝜗𝑡 + 𝜎𝑖 + 𝜃𝑗 + 𝜖𝑖,𝑗,𝑡
… loans by creditor country j, to crisis country i, in disaster episode t
in constant 2015 US;
… 𝐸𝑐𝑜𝑛 𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒: pre-disaster shares of bilateral trade and bank loans
21
Trade and bank exposure predicts rescue loans
The more exposed you are, the more you lend
Full Sample Pre-WWII Bretton Woods Modern Era Modern Era
1830 - 2015 1830 - 1945 1946 - 1973 1973 - 2015 1984 - 2015
(trade linkages) (banking linkages)
(1) (2) (3) (4) (5)
Trade exposure 0.34*** 0.99* 0.32** 0.50***
(0.10) (0.54) (0.15) (0.12)
Financial exposure 0.26***
(0.06)
Distance -0.35** -0.95** -0.63** -0.30* -0.55***
(0.15) (0.48) (0.28) (0.18) (0.17)
UN voting 6.60*** 2.54** 5.44**
(1.45) (1.25) (2.41)
(Former) colony 1.12*** 1.37*** 1.53*** 0.69*** 1.18***
(0.29) (0.46) (0.34) (0.26) (0.22)
Constant 9.67*** 7.10 8.25*** 0.67 -0.43
(1.26) (4.63) (2.65) (1.53) (1.92)
Observations 15429 449 1736 12042 1283
R-squared 0.825 0.997 0.921 0.730 0.961
Creditor FE     
Debtor FE     
Episode FE     
Controls     
Dep. variable: Bilateral rescue lending
1% higher
trade exposure
0.34% more
official loans
23
Conclusion
• Official lending is much larger than previously known and
existed long before the foundation of IMF and World Bank
• Official lending rises in times of disaster, when private
capital flows retrench
• Rescue loans and bailouts much more prevalent today
(from exception to norm); economic integration matters
24
Appendix
25
Purposes of official cross-border lending
26
Financial crises, wars, and natural disasters
27
Rescue lending has become much more systematic
28
Bilateral loans 1790-2015
29

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Christoph-Trebesch-Slides Debt crisis on.

  • 1. Coping with Disasters: Two Centuries of International Official Lending Sebastian Horn (Kiel Institute) Carmen Reinhart (World Bank, Harvard) Christoph Trebesch (Kiel Institute) World Bank November 19, 2020 All views are personal 1
  • 2. The Covid-19 disaster: private capital flows “Sudden stop“ in private capital flows  limited risk sharing 2
  • 3. The Covid-19 disaster: the official response “Sudden spike“ in official flows  risk sharing (Horn 2020) 3
  • 4. The (unexplored) world of official capital flows – Extensive literature on private cross-border flows (see paper), but little work/data on official flows; narrower focus/time spans Our contribution: encompassing new database and analysis of official international lending, 1790-2015 – Definition: includes loans, grants and guarantees by governments, multilateral institutions and central banks across borders – Sources: International treaty series (archives), creditor and debtor budget accounts, annual reports, post-1970: World Bank, OECD – 230,000 grants & loans by 134 governments, 50 intl. institutions, in total 15 trillion real USD (committments in 2015 terms) 4
  • 5. Who lends? The universe of official creditors Bilateral creditors 1800 1918 Multilateral creditors Regional Safety Nets Regional Development Banks League of Nations United Nations System Bank for International Settlements International Monetary Fund World Bank Foreign and Colonial Offices Ministries of Development Export Credit Banks Central Banks & Treasuries 1945 1973 2015 5
  • 6. Examples of sources Historical budget accounts CIA reports on Sino-Soviet loans 6
  • 7. Disasters 1800-2015: A new database We collect data on severe disasters from many sources:  Financial crises: Banking, currency and sovereign debt crises from Reinhart & Rogoff (2009) and Meyer et al. (2019)  Wars and military conflict: Inter- and intra-state wars from the Correlates of War project (Sarkees and Wayman 2010)  Natural catastrophes: Earthquakes, storms, floods, volcano eruptions, famines, epidemics from EM-DAT since 1900. Dozens of historical and country studies for 1800-1900 7
  • 8. Research questions and key take aways 1. Scale of official lending: It is large, often larger than private flows – Rescue lending common long before IMF/World Bank – Much more institutionalized today (“globalization of assistance“) 2. Interaction of private and official flows: When private flows retrench, official lending often steps in – Private capital tends to be pro-cyclical, while official flows tend to be counter-cyclical (Covid crisis is a recent example) 3. Patterns of official lending: trade and financial integration matters  What drives country rescues and official lending? (Tirole 2015, Gourinchas et al. 2019)  Bailouts increase with economic exposure (selfish motive vs. altruism an intepretation issue) 8
  • 9. A panorama of international official lending 9
  • 11. Official lending is much bigger than IMF & World Bank Regional & others Bilateral (government to government) IMF and World Bank 11
  • 12. Central bank lending: credits then, swap lines now Great Depression: Short-term credits to CBs of Germany, Austria, Britain etc 2008 crisis: US Fed emergency dollar liquidity 12
  • 13. Adding central bank lending across borders 13
  • 14. When private investors retrench, official lending often steps in (private capital tends to be pro-cyclical, while official flows tend to be counter-cyclical) 14
  • 15. Official vs private capital flows: 200 year view Official international lending Private international capital flows Correlation: -0.36 15
  • 16. Case study: Interwar and Great Depression 16
  • 17. Case study: Asian crisis (1997) 17
  • 18. Case study: Eurozone crisis (2010-2012) 18
  • 19. Why do countries extend rescue loans? (Who gets what and why? Altruism or self-interest?) 19
  • 20. Natural disasters: increasing odds of rescue lending Probability of receiving official loans/grants in major natural disasters, by era, in % 20
  • 21. Why do countries extend rescue loans? Main hypothesis: economic integration matters. Sovereigns extend bilateral rescue loans to those countries with largest trade and finance exposure (Tirole 2015, Gourinchas et al. 2019) Interpretation: helping your friends vs. self-interest of preventing negative spillovers Empirical approach: gravity model of bilateral rescue lending: 𝒍𝒏 𝑹𝒆𝒔𝒄𝑳𝒐𝒂𝒏𝒔𝒊,𝒋,𝒕 = 𝛽 𝑙𝑛 𝐸𝑐𝑜𝑛 𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒𝑖,𝑗,𝑡 + 𝛾 𝑃𝑜𝑙𝑖𝑡𝑖𝑐𝑎𝑙 𝑇𝑖𝑒𝑠𝑖,𝑗,𝑡 + 𝛿 𝑙𝑛 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒𝑖,𝑗 + ∆ 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠𝑖,𝑗,𝑡 + 𝜗𝑡 + 𝜎𝑖 + 𝜃𝑗 + 𝜖𝑖,𝑗,𝑡 … loans by creditor country j, to crisis country i, in disaster episode t in constant 2015 US; … 𝐸𝑐𝑜𝑛 𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒: pre-disaster shares of bilateral trade and bank loans 21
  • 22. Trade and bank exposure predicts rescue loans
  • 23. The more exposed you are, the more you lend Full Sample Pre-WWII Bretton Woods Modern Era Modern Era 1830 - 2015 1830 - 1945 1946 - 1973 1973 - 2015 1984 - 2015 (trade linkages) (banking linkages) (1) (2) (3) (4) (5) Trade exposure 0.34*** 0.99* 0.32** 0.50*** (0.10) (0.54) (0.15) (0.12) Financial exposure 0.26*** (0.06) Distance -0.35** -0.95** -0.63** -0.30* -0.55*** (0.15) (0.48) (0.28) (0.18) (0.17) UN voting 6.60*** 2.54** 5.44** (1.45) (1.25) (2.41) (Former) colony 1.12*** 1.37*** 1.53*** 0.69*** 1.18*** (0.29) (0.46) (0.34) (0.26) (0.22) Constant 9.67*** 7.10 8.25*** 0.67 -0.43 (1.26) (4.63) (2.65) (1.53) (1.92) Observations 15429 449 1736 12042 1283 R-squared 0.825 0.997 0.921 0.730 0.961 Creditor FE      Debtor FE      Episode FE      Controls      Dep. variable: Bilateral rescue lending 1% higher trade exposure 0.34% more official loans 23
  • 24. Conclusion • Official lending is much larger than previously known and existed long before the foundation of IMF and World Bank • Official lending rises in times of disaster, when private capital flows retrench • Rescue loans and bailouts much more prevalent today (from exception to norm); economic integration matters 24
  • 26. Purposes of official cross-border lending 26
  • 27. Financial crises, wars, and natural disasters 27
  • 28. Rescue lending has become much more systematic 28

Editor's Notes

  1. Multilateral!!!
  2. Variable definition: Net non-resident purchases of EM stocks ("portfolio equity flows") and bonds ("portfolio debt flows") in USD billion. Proxy for portfolio flows as measured in the balance of payments
  3. Our data comes from both standard sources (IMF programs, World Bank) but also from more obscure or idiosyncratic sources (historcial treaties, CIA reports etc etc(
  4.   Motivation disasters Official – private connection --- going back in opposite direction Motivate with Covid Rating   What does history tell us about international help in disasters? Has the world become more altruistic? Amounts increased a lot, more systematic Would debt standstill have occurred in the 1930sor 19th century  Probably not: Hoover moratorium 1934 NOT voluntary The world has certainly become more interconnected, both economically and official flows  good dosage of self-interest
  5. Bretton woods
  6. Country sample includes Austria, Bulgaria, Czechoslovakia, Estonia, Finland, Germany, Greece, Hungary, Italy, Latvia, Lithuania, Poland, Roumania, Yugoslavia, Denmark, Norway, Portugal, Spain US and Western European Creditor countries are excluded: US, France, Britain, Switzerland and the Netherlands
  7. Country sample includes Thailand, Korea, Malaysia, Indonesia
  8. Sample includes Greece, Ireland, Spain, Portugal
  9. Size of the pie (who gets what?)
  10. Despite first major era of globalization very little rescue lending. Globalization in trade and finance, but no globalization in assistance. That suggests that globalization has taken a humanitarian dimension that it didn‘t have today. Put differently, the world has become more altrustic Irish potato famine vs Haiti earthquakes
  11. Econ exposure captures the relative weight of the crisis country in total trade or international bank lending of the potential creditor country. So how econoically important is the disaster economy for the creditor country
  12. Poisson Pseudo Maximum Likelihood (PPML) estimator that has the desirable properties of being consistent under heteroskedastic error terms and that naturally incorporates zero observations (Head and Meyer, 2014).
  13. Size of the pie (who gets what?)