00:06 Welcome back everyone
00:08 to the afternoon session.
00:10 Uh,
00:10 for those joining online,
00:11 please join using the discussion
00:13 hashtag ABCDE 2024.
00:17 Uh,
00:17 I'm
00:18 very excited to welcome you to the second session
00:20 which will focus on sovereign debt and
00:23 default.
00:24 Our moderator is Manuela Francisco,
00:26 and I,
00:27 she,
00:28 it's,
00:28 it's now July,
00:29 so she has a new title.
00:30 So Manuela is the Global Director for Economic
00:33 policies,
00:34 um,
00:34 in the prosperity vertical.
00:36 Um,
00:36 I'll hand over to you,
00:37 Manuela.
00:43 Thank you,
00:43 thank you very much
00:45 and good afternoon everyone here in Washington and
00:48 good evening to everyone that is connected online.
00:51 Um,
00:52 I'm very pleased to see the inclusion of
00:54 a session on sovereign debt at this distinguished
00:58 conference because as we all know it's a very relevant topic.
01:03 Uh,
01:03 to motivate this discussion,
01:06 I would like to make 3 points that I will be very,
01:09 and I will be very brief.
01:11 First,
01:12 Is the following,
01:13 debt levels have stabilized,
01:16 these are the good news,
01:17 but they have stabilized at very high levels,
01:20 and many countries are facing liquidity challenge.
01:24 Just to give you a few numbers,
01:26 8 years ago in 2015.
01:29 25% of the low income countries that prepared DSF
01:34 were at high risk of that distress or
01:37 in distress.
01:38 By 2019,
01:41 this number reached 50%.
01:45 And this was because
01:47 between 2010 and 2019,
01:50 countries borrowed significantly,
01:53 which was facilitated by widely available capital at a very low cost.
01:59 Between 2010 and 2019,
02:01 during this period,
02:03 Public debt.
02:06 In low-income countries,
02:07 and middle-income countries grew by 131% in nominal terms.
02:14 Then,
02:15 as we know,
02:15 came COVID.
02:17 And then in 2022,
02:19 it started the tightening of monetary policy
02:22 and many countries were pushed over a cliff.
02:26 But there are encouraging news.
02:29 Uh,
02:29 some countries have started to tighten fiscal policy.
02:34 Uh,
02:34 some countries have gained access to the capital markets,
02:38 uh,
02:39 but we know that gross financing needs remain still very,
02:42 very high.
02:44 And while credit spreads have declined,
02:47 we know that the underlying interest rates are still very high.
02:52 My second message is that the that landscape
02:56 has changed.
02:58 And the debt structuring process are still adapting to this new world.
03:04 So as public debt levels increase,
03:06 the composition of the creditors also changed.
03:09 There has been a shift
03:11 towards non-traditional creditors
03:13 and bondholders.
03:16 There is also more domestic debt.
03:18 So now over 50 low-income countries have
03:22 domestic debt and total debt is about 25% of GDP.
03:28 There are good news with that.
03:30 Countries will be shielded from exchange rate volatility and currency mismatch.
03:36 But
03:37 when it comes the time of that restructuring,
03:40 this can become very complicated because of
03:43 the wider implications for the economy.
03:47 My last comment is that
03:49 our point is that countries are struggling
03:53 to roll over their debt.
03:56 We are living
03:57 a period
03:58 of very expensive funding costs.
04:02 There is uncertainty regarding the pace of monetary policy easing.
04:08 But I think there is certainty about the fact
04:11 that
04:12 the era
04:13 of very low interest rates will not come back.
04:19 So while major central banks around the world
04:22 are in a path
04:23 of monetary policy easing
04:26 and the Fed has already cut policy rates,
04:30 The,
04:31 the ECB I mean has cut policy rates.
04:34 The Fed is still waiting to see what's happened in the job market and the,
04:37 and prices.
04:39 But even
04:41 When the Fed cuts policy rates,
04:43 the low income countries will still face
04:46 very expensive
04:48 financing costs.
04:50 So that's why this is also relevant today.
04:54 So,
04:54 um,
04:55 it is my honor to moderate this distinguished
04:58 panel and let me introduce the panelists,
05:01 and I will start by the order of their presentation.
05:05 So
05:05 on my left I have Christoph Tribes from Keo University,
05:10 Enrico Mallucci from the Federal Reserve Board,
05:14 Ron Kang
05:16 from the World Bank.
05:17 And following their presentations of these three speakers,
05:21 Marcos Chasmos from the Fund
05:23 and Luca Bandiera from the World Bank will provide discuss and remarks.
05:28 So
05:29 let me pass the floor to
05:31 um
05:32 Christo.
05:40 Thank you so much,
05:40 uh,
05:42 for the moderation.
05:43 Thank you so much for inviting me,
05:44 uh,
05:45 and allowing me to,
05:46 uh,
05:47 present to you our most recent
05:49 paper,
05:50 uh,
05:50 we just joined with,
05:51 uh,
05:51 Lukas Franz uh from the Keen Institute,
05:53 Sebastian Horn from the Bank,
05:55 Bradley Parks from William and Mary,
05:57 and Carmen Reinhardt from Harvard University.
05:59 And this is part of a
06:00 broader research agenda on official lending,
06:04 so state-driven
06:05 lending on official creditors.
06:07 In general,
06:08 and uh
06:09 in particular on China's
06:11 overseas lending.
06:12 So despite the
06:13 growing literature on China's overseas lending,
06:15 we still have very little
06:17 insights on the financial terms,
06:19 especially in,
06:19 in particular,
06:20 the
06:21 returns,
06:22 the financial returns
06:23 of this 1 trillion
06:26 lending program that China has rolled out over the last 15 years,
06:29 and this is the focus.
06:30 Of today.
06:32 Um,
06:33 we see this paper speaking to a bigger phenomenon a long history
06:37 in which great powers have shown
06:39 a,
06:40 uh,
06:40 tendency to invest or to,
06:42 to launch these large scale infrastructure
06:45 investment
06:46 programs,
06:47 uh,
06:47 this just two historical examples.
06:50 Germany in the late 19th century launched the Berlin-Baghdad
06:52 railway or the US with this famous Marshall Plan.
06:55 Both of them investing heavily in infrastructure and faraway lands and facing
07:00 substantial
07:01 risks on this kind of large scale
07:03 uh investments.
07:04 Um,
07:04 so the benefit of looking at China today is that,
07:07 uh,
07:07 thanks to uh consider research by a data and,
07:10 and Uh,
07:10 and this other scholarly work,
07:12 we actually have a pretty
07:13 good idea,
07:14 more granular insight into these,
07:16 into one of the most prominent
07:18 lending programs of this type,
07:20 uh,
07:20 and we can assess
07:21 the dissociated default risk
07:23 and the returns
07:24 to the creditors,
07:25 to the,
07:26 to the great power,
07:27 uh,
07:27 lender,
07:28 uh,
07:28 in a more systematic way than we could do before.
07:31 Um,
07:32 so the key question I'm gonna focus on is,
07:35 is China's project of the century
07:37 a financial success?
07:41 There's two main contributions of the paper.
07:44 Uh the first,
07:45 and that's an essential ingredient to understanding
07:48 the financial returns,
07:49 is to understand defaults and credit losses.
07:52 So,
07:53 uh,
07:53 events of great events and the associated restructurings or,
07:56 um,
07:57 credit loss,
07:58 so haircuts,
07:59 uh it's often called
08:01 on
08:02 uh either the Chinese banks,
08:03 and we put together this comprehensive data set with
08:06 really the details of the sovereign debt restructuring.
08:09 Um,
08:09 deals,
08:10 uh,
08:10 with Chinese creditors
08:12 and then,
08:13 uh,
08:13 compute haircuts,
08:14 um,
08:15 and compare it to the Paris Club and other
08:17 and private external creditors.
08:19 And the second
08:20 contribution is we use the haircuts and the default information.
08:23 Um,
08:24 to compute exposed returns,
08:27 uh,
08:27 on,
08:28 uh,
08:28 on China's,
08:29 uh,
08:30 lending portfolio.
08:31 Uh,
08:31 so for every
08:32 one of these 3500 Chinese loans with the total volume of volume of 1 trillion,
08:39 we compute,
08:39 you know,
08:40 the exact cash flows,
08:41 we consider the,
08:42 uh,
08:43 credit events,
08:44 uh,
08:45 towards each of those loans
08:46 and come to the,
08:48 uh,
08:48 the keys inside is that realized rate of return is about 1.7.
08:53 Uh,
08:53 percent per year,
08:55 uh,
08:55 in real terms,
08:56 inflation adjusted,
08:57 which is neither particularly high
08:59 and not particularly low,
09:00 I'm gonna benchmark that to other,
09:02 uh,
09:02 creditor types.
09:04 So let me turn to the first part,
09:07 haircuts.
09:08 So the losses of Chinese banks on their
09:11 Belt and Road portfolio abroad.
09:14 The central contribution is that uh we we uh we
09:18 compile this granular data set,
09:20 um,
09:21 and importantly,
09:22 uh,
09:23 most of these deals
09:25 are rescheduling
09:26 agreements.
09:26 So they push out the payment
09:28 by a couple of years,
09:29 often not even cutting the interest rate.
09:31 So it's basically just a five year
09:33 kicking down
09:36 uh the can operation with very few instances of face value reduction.
09:39 So nominal debt reduction is rare in these deals.
09:42 Uh,
09:42 which is why you really need to,
09:43 to look at the present value or the,
09:45 the,
09:45 the,
09:46 uh,
09:46 payment streams of these loans
09:48 in detail.
09:49 Um,
09:51 So we use a standard uh to get Fettelmeyer haircuts uh
09:55 to compute uh haircuts.
09:56 So comparing
09:58 like a hypothetical scenario in which you say
10:00 99% of the credit is agreed and 1% does not agree,
10:04 uh,
10:04 and is repaid as if the default would never have occurred.
10:08 Uh,
10:08 what is the loss of the 99% participating vis a vis that 1% holdout is being paid,
10:14 right?
10:14 So,
10:15 so that's kind of at the point of the restructuring.
10:17 How much do creditors lose?
10:18 That's the way haircuts are computed here.
10:21 Um,
10:21 and,
10:22 uh,
10:22 as of course discount rate is crucial,
10:24 we use kind of uh an upper bound here,
10:26 the market yield,
10:27 an exit yield,
10:28 uh,
10:28 based on bond,
10:29 uh,
10:30 uh,
10:30 bond yields at the exit from the restructure but we also
10:33 use a official creditor uh
10:35 uh discount rates of CIRR as a,
10:38 a robustness check.
10:40 This is one of the key graphs of the paper,
10:43 so this is the size of the haircuts on Chinese
10:46 loans and various
10:48 um restructuring operations.
10:50 Um,
10:51 I guess I can't,
10:52 you can't see the,
10:53 uh,
10:53 no here.
10:54 So what you can see,
10:55 the big takeaway is that That
10:58 in the large number of cases,
10:59 haircuts are surprisingly low.
11:00 Uh,
11:01 so from
11:02 0 to 0 to
11:05 20%,
11:05 so the average
11:06 is just 12%,
11:08 and that's in historical comparison,
11:10 low.
11:11 Uh,
11:12 this is just one comparison,
11:13 we also do the comparison with Paris Club haircuts from our other uh work.
11:17 Um,
11:18 and what you can see is that
11:20 if we
11:22 Compare the haircuts on the Chinese restructuring events,
11:25 which are the red dots,
11:27 uh,
11:27 with haircuts,
11:28 uh,
11:29 on private external credits from the Cruz's Trevich data set,
11:32 uh,
11:32 we get a,
11:33 we get substantial differences,
11:35 so the mean
11:36 Chinese haircut is
11:37 10% or close to 0 if you want,
11:40 and the mean,
11:41 uh,
11:41 on private external credit is the mean haircut is 36%,
11:45 uh,
11:45 so considerably higher.
11:47 And if you consider the Paris Club haircuts,
11:50 those are above 50% on average,
11:52 so significantly higher than that even.
11:56 Let's move to the second part,
11:58 creditor returns.
11:59 Um,
12:00 we,
12:01 since these are not market instruments,
12:03 these are not traded instruments,
12:04 these are loans by Chinese banks,
12:06 um,
12:07 we compute internal rates of return.
12:10 Um,
12:10 and therefore,
12:11 for every single of those loans,
12:13 we,
12:13 we,
12:14 you know,
12:14 map the information we have on commitments,
12:17 uh,
12:18 the financial characteristics of the,
12:19 of the term of the terms,
12:21 the grace periods,
12:21 etc.
12:22 uh,
12:22 and then incorporate
12:24 the information on default and missed payments,
12:26 OK,
12:26 and the haircuts,
12:27 uh,
12:27 which gives us
12:29 this,
12:29 uh,
12:29 realized rate of return measure.
12:32 Uh,
12:32 just,
12:33 this is just an example,
12:34 what,
12:34 what kind of a
12:36 Just an illustration of the repayment terms,
12:38 once we do bond by bond and we,
12:40 uh sorry,
12:41 loan by loan and then aggregated
12:43 at a yearly level,
12:44 right?
12:44 What,
12:45 what are the repayments towards Chinese creditors from
12:48 the global south or from the debt Belt and Road countries,
12:51 you can see
12:52 that there is no,
12:53 it's no surprise that we're currently talking a lot about
12:56 uh debt sustainability and about repayment problems
12:59 towards China because this since 2020,
13:01 we really see a peak in repayment.
13:03 And we see that,
13:04 you know,
13:05 there's two big elephants in the room in terms of creditors,
13:07 and that's China Development Bank
13:09 and uh Export Import Bank,
13:12 so Exim Bank of China.
13:15 This graph shows you
13:17 the difference in realized payments.
13:20 Um,
13:21 so what,
13:21 what part of these repayments,
13:23 uh,
13:24 did not occur,
13:25 right?
13:25 So the red
13:26 parts of these bars are the missed payments.
13:28 And what you can see is that,
13:29 of course,
13:30 the Blue bars are much larger.
13:31 Missed payments account for a relatively small share
13:35 of total debt due to China.
13:37 Uh,
13:38 so overall,
13:40 China has not suffered massive arrears,
13:42 massive missed payments,
13:43 defaults on its portfolio.
13:47 We can also look at this by comparing ex ante returns or the promised returns at,
13:52 at,
13:52 at the landing point.
13:54 And exposed returns accounting for
13:56 uh losses and haircuts.
13:58 Um,
13:59 this is
14:00 the nominal return now,
14:02 uh,
14:02 and so the every country is colored according to the average return.
14:07 Um,
14:08 and when we compare these ex ante returns and compare that
14:12 to the exposed ones,
14:13 we see very little change in the coloring.
14:15 Only a few African countries see a substantial shift in the aggregate return.
14:20 Uh,
14:20 on,
14:21 uh,
14:21 Chinese,
14:22 uh,
14:22 loans from a,
14:23 from a Chinese perspective.
14:24 Uh,
14:25 so the
14:26 difference
14:27 in short between ex ante and exposed returns
14:29 is not particularly large
14:31 except for a few outlier countries.
14:33 OK?
14:35 So how does the return on China's
14:38 lending portfolio compare in the bigger picture,
14:41 right?
14:41 So
14:42 would it have
14:44 been a better alternative uh to put this money,
14:47 say,
14:47 in a sovereign wealth fund,
14:49 safe,
14:49 China's uh sovereign wealth fund
14:51 and invest in a portfolio of emerging market bonds instead
14:55 or maybe in a treasury
14:57 account with treasury.
14:58 bonds.
14:58 Uh,
14:59 to,
14:59 to understand that,
15:01 we compare the average real
15:03 uh return uh on a yearly basis of the BRI loans
15:07 with other
15:08 asset types,
15:09 asset classes,
15:10 and we can see that
15:11 the returns are higher
15:12 than the alternative of investing in US treasuries
15:16 and even higher than the alternative investing in Chinese government bonds.
15:20 But they are significantly lower.
15:23 Uh,
15:23 towards the benchmark of investing that same money
15:26 into Chinese equities
15:28 or into the standard,
15:29 you know,
15:30 JP Morgan MB,
15:31 uh,
15:31 portfolio,
15:32 uh,
15:32 or even MSCI
15:34 World Global Equity portfolio.
15:36 So
15:37 in that sense,
15:37 the markets,
15:38 uh,
15:39 returns in standard,
15:40 uh,
15:40 asset classes in emerging markets are considerably higher,
15:43 uh,
15:44 but it is,
15:45 uh,
15:45 more profitable than,
15:47 than investing,
15:48 uh,
15:48 holding more treasury bonds.
15:50 It's uh in the,
15:51 in the mid-range.
15:53 So why are creditor returns so low compared to that kind of market
15:57 benchmark?
15:59 To answer this question,
16:00 we're now gonna
16:01 make use of the large
16:03 loan by loan variation in returns.
16:05 We know the ex ante returns of every single loan.
16:08 And here it's just plotted the variation for every year
16:12 uh in the,
16:12 in the uh contracted return,
16:15 right,
16:16 ranging between 0
16:17 and uh even up to 10% or more,
16:19 right?
16:19 And what you can see that there's considerable variation
16:22 in the lending terms that China gives out.
16:25 So what drives this variation?
16:27 What,
16:27 what explains why some of these loans are really
16:30 low,
16:31 below market rates?
16:32 Um,
16:34 and to make sense of that,
16:35 we,
16:36 uh,
16:36 exploit the fact that China's overseas lending is state-driven.
16:40 So likely to have a,
16:42 uh,
16:43 or at least there is a possibility
16:44 of direct political
16:46 control and strategic lending because this is the state lending,
16:49 right?
16:50 Or state entities lending.
16:51 Um,
16:53 with that perspective,
16:54 we,
16:55 uh,
16:55 look at,
16:56 uh,
16:57 projects that might be in the interest
16:59 of China's,
17:00 you know,
17:01 overall,
17:02 uh,
17:02 um,
17:03 uh,
17:03 so
17:04 overall activities abroad.
17:06 First of all,
17:07 uh,
17:08 projects that might foster
17:10 market access or exports,
17:12 um,
17:12 like
17:13 infrastructure projects,
17:15 uh,
17:15 projects that are implemented by the Chinese entities or construction.
17:19 In Africa,
17:20 for example,
17:21 or loans denominated in renminbi.
17:23 So it's,
17:24 it's China trying to push
17:25 uh the internationalization of its currency
17:28 by subsidizing
17:29 loans that are renminbi dominominated,
17:32 right?
17:32 So
17:33 the question of uh non-financial externalities is what we're after and proxies for
17:38 project with such
17:39 non-financial externalities.
17:41 And the second is
17:42 uh looking at political potential uh project with political um uh
17:47 Uh,
17:48 implications of prestige projects.
17:50 It could be stadiums or a parliamentary buildings,
17:53 uh,
17:53 military security projects in the recipient countries,
17:56 uh,
17:57 loans to public recipients or loans to the region
18:00 from which the leader of the country,
18:03 uh,
18:03 originally comes from.
18:04 OK?
18:04 So this is classic leader favoritism,
18:06 uh,
18:07 literature.
18:08 And what you can See
18:09 in this graph,
18:10 and that's my penultimate slide here,
18:12 is that uh
18:14 projects that are associated or likely to have higher non-financial returns
18:19 beyond the mere
18:20 financial relationship
18:22 uh like prestige projects,
18:24 those denominated in RMB,
18:26 uh,
18:26 military security projects or projects for trade infrastructure,
18:30 um,
18:31 uh,
18:32 see a higher,
18:33 uh,
18:33 see,
18:33 see a significantly lower return,
18:35 so they're subsidized.
18:37 Uh,
18:37 whereas,
18:38 uh,
18:39 other projects that are,
18:40 uh,
18:40 you know,
18:40 for private recipients or for emerging market recipients
18:43 see higher,
18:44 uh,
18:45 uh,
18:45 returns and are not subsidized.
18:47 And we confirmed this in a regression framework,
18:49 but since I promised to be short,
18:51 let me wrap up.
18:52 Uh,
18:53 overall,
18:54 uh,
18:54 the financial returns of the BRI so far,
18:57 uh,
18:58 show that this is a no gain,
18:59 no loss project,
18:59 so the,
19:00 the returns are needed.
19:01 Catastrophic as sometimes
19:03 assumed.
19:04 Um,
19:04 and looking ahead,
19:05 of course,
19:05 the big question is
19:07 whether the haircuts of the China will have to accept higher losses,
19:13 uh,
19:13 and whether,
19:14 uh,
19:14 which would imply lower returns,
19:15 uh,
19:16 and what the current shifts in the way China lends that do,
19:19 especially the focus to,
19:21 uh,
19:21 towards more state-owned commercial bank lending with higher returns ex ante.
19:25 Thank you so much.
19:30 Thank you so much.
19:32 And let's now hear from Eric.
19:36 Enrico Mallucci.
19:38 OK
19:40 All right.
19:41 So thank you very much for including the paper,
19:43 uh,
19:44 in the program.
19:45 So this is joint work uh with AOEE,
19:48 uh,
19:49 University of Navarra and Mattia Piccarelli,
19:51 uh,
19:52 from the European Stability Mechanism,
19:54 uh,
19:54 and,
19:54 uh,
19:55 of course,
19:55 uh,
19:56 the usual disclaimer applies.
19:59 So it's a well-known fact that,
20:01 uh,
20:02 sovereign debt markets have evolved quite a bit in the last 30,
20:05 40 years.
20:06 So
20:07 if you think about it,
20:08 I mean,
20:08 uh,
20:09 bank loans were replaced by bonded debt,
20:12 uh,
20:12 and the size of emerging markets government debt
20:16 has increased,
20:17 uh,
20:17 uh,
20:18 substantially,
20:19 but perhaps,
20:19 uh,
20:20 at least it's our taking the biggest change of all.
20:23 has been the growing role of domestic markets.
20:27 So we have seen,
20:28 uh,
20:28 just to give you an example,
20:30 uh,
20:31 think about Mexico.
20:32 So in Mexico,
20:33 uh,
20:34 domestic,
20:35 uh,
20:35 the domestic share of government debt was about 25% in 1995.
20:41 If you take the same number in 2010,
20:44 you find an 80%.
20:46 So this huge increase in the size of,
20:48 uh,
20:48 of domestic markets.
20:49 And of course,
20:50 the growing role of domestic markets for government debt
20:54 has also translated uh into a greater involvement uh in uh
20:59 Domestic,
20:59 uh,
21:00 uh,
21:00 of domestic debt in defaults and restructuring events.
21:03 So,
21:04 Greece,
21:04 for instance,
21:05 uh,
21:05 is a poster child example.
21:07 So if you think about the,
21:08 the Greek restructuring of 2012,
21:11 well,
21:11 92% of the debt that was restructured uh was actually domestic debt.
21:16 So it was really
21:17 a domestic restructuring.
21:19 And as we speak,
21:20 of course,
21:20 countries,
21:21 uh,
21:22 Both under and and outside the cover of
21:24 the common framework are conducting sovereign debt restructuring involving
21:29 uh bonds issued domestically,
21:32 so it's very much uh in today's topic.
21:35 Um,
21:37 so the problem is,
21:38 uh,
21:38 that we have seen this,
21:39 uh,
21:40 increasing the importance of domestic debt,
21:43 but there is limited systematic understanding
21:46 of how,
21:47 of the differences,
21:48 uh,
21:49 between,
21:49 uh,
21:50 uh,
21:50 defaults,
21:51 uh,
21:52 between sovereign defaults that involve,
21:53 uh,
21:54 domestic debt and external debt.
21:56 And so this is exactly what we do in this paper.
21:59 So we systematically compare sovereign defaults.
22:03 of government debt issued in domestic and
22:06 international debt markets and we compare them.
22:09 And of course,
22:09 then we use the insights to inform the academic literature
22:13 as well uh as uh policymakers.
22:18 Now,
22:19 to,
22:19 to,
22:20 to,
22:20 to really compare what,
22:22 uh,
22:22 what is happening when you default on domestic
22:24 and when you default on external debt,
22:26 of course,
22:27 you need the
22:28 data,
22:29 OK?
22:29 So you need
22:31 uh to have a comprehensive view,
22:33 you need to look at the universe of uh the domestic and external debt restructuring.
22:39 So this is why in this,
22:40 in our paper,
22:41 we leverage on uh two state of the art databases.
22:45 So we take information uh about uh domestic
22:49 defaults and restructuring uh from uh the paper
22:52 by Chris Treves here and uh and Tamon which I also saw in the audience.
22:57 And then we complement this information about external
23:00 restructuring with information about the domestic data restructuring,
23:04 which we take from a paper that I or I,
23:07 and,
23:07 uh,
23:07 and Matthia
23:09 we constructed,
23:10 we constructed over the last 10 years,
23:12 OK?
23:13 And then we harmonize the two databases
23:16 and uh we just uh again analyze how the two
23:21 phenomenon differ.
23:24 So the resulting database has uh about 100 and 116
23:30 uh domestic default restructurings and 177 external default uh uh
23:36 events.
23:36 We span from 1980 until 2018,
23:40 and we have information of really a bunch of things.
23:43 So we have information about the timing of this restructuring,
23:46 so when they start and when they end.
23:49 We have information about the instruments involved,
23:50 so we see if,
23:51 uh,
23:51 if we are talking about bond,
23:53 if we are talking about loans,
23:55 we see the volumes involved.
23:56 So we see how big these defaults actually are.
23:59 And then we also look at the,
24:01 uh,
24:01 we also have information about the restructuring terms and the restructuring,
24:05 uh,
24:05 approach that are taken in,
24:07 uh,
24:07 in,
24:08 uh,
24:08 in this restructuring events.
24:10 And we also have information about the
24:12 NPV losses,
24:13 but this is only a few,
24:14 for a,
24:15 for a,
24:15 for a subset of,
24:16 uh,
24:17 Of the restructuring event.
24:18 And then a key feature of the database is that it also has a global coverage.
24:23 So we,
24:24 uh,
24:24 we have information coming from 84 countries that span,
24:28 uh,
24:28 uh,
24:28 all continents and all income group.
24:32 So this being said,
24:34 uh,
24:35 how the two differ,
24:36 how the,
24:37 uh,
24:37 how these two phenomena,
24:39 uh,
24:39 differ.
24:40 So the first thing we find is that domestic defaults
24:44 have become more frequent than external ones.
24:46 So if you look at the red line,
24:48 that is like uh,
24:50 uh,
24:50 the three-year sum of uh external default episodes,
24:54 and you see that essentially they peaked in the 80s,
24:57 but now they are,
24:59 uh,
24:59 if not rare,
25:00 they are rarer than they used to be.
25:02 The black line instead plots the same,
25:05 uh,
25:05 the same uh information for uh domestic uh restructurings.
25:10 And you see that from uh about like
25:13 the end of the 90s,
25:14 the black line has crossed the,
25:16 the,
25:16 the,
25:16 the red line,
25:17 meaning that nowadays,
25:19 uh
25:20 domestic
25:21 uh restructuring are actually uh more frequent than,
25:24 uh,
25:25 than,
25:25 uh,
25:25 than external ones.
25:28 The second thing that we find that selective defaults are the norm.
25:31 So we define selective defaults as the restructuring episode that only involved
25:35 either domestic or external,
25:37 uh,
25:38 or external debt.
25:39 And,
25:40 uh,
25:41 essentially,
25:41 uh,
25:42 what we find is that 70% of the default episodes are selective.
25:47 So when we think about,
25:48 uh,
25:49 uh,
25:50 sovereign defaults,
25:51 we are really
25:52 normally facing,
25:54 uh,
25:54 uh,
25:54 selective defaults.
25:56 And we find that about 60% of the domestic
25:58 defaults and 77% of the external defaults are selective.
26:02 Now,
26:03 the additional
26:04 piece of information is that
26:06 not only
26:08 Selective defaults are the norm,
26:10 but non-selective defaults,
26:12 so if we look at the last,
26:13 the,
26:13 the remaining 30% of,
26:15 uh,
26:15 of the episode,
26:17 they are also somehow selective in the
26:19 sense that they discriminate between lenders.
26:21 So in this
26:23 Uh,
26:23 scattered plot,
26:24 uh,
26:24 essentially you have on the horizontal axis,
26:27 the domestic,
26:27 uh,
26:28 restructured debt as a percentage of total
26:31 restructure debt and on the vertical axis,
26:33 uh,
26:33 the,
26:33 the,
26:34 the domestic versus external composition of government debt.
26:37 So this is
26:38 what this graph is telling you is that
26:40 even when governments do
26:43 default on both external and domestic debt,
26:46 they tend to discriminate
26:49 against the type of debt
26:51 which has the largest share in the overall composition of,
26:55 uh,
26:55 of total debt.
26:56 So if you have a very high
26:58 external debt,
26:59 you tend to default more
27:02 on,
27:02 uh,
27:02 on,
27:03 uh,
27:03 on the external portion of,
27:05 uh,
27:05 of,
27:05 of the debt.
27:08 Next,
27:10 we look at the size of uh domestic versus external default.
27:14 We find that the domestic defaults are smaller,
27:17 so here in the table,
27:18 we report
27:19 Uh,
27:20 the,
27:20 the,
27:21 the,
27:21 the,
27:21 the,
27:22 the percentage as a fraction of the GDP of the debt in default and you see that,
27:26 uh,
27:27 on average,
27:28 uh,
27:28 domestic,
27:29 uh,
27:29 defaults are,
27:30 uh,
27:30 they,
27:31 they involve uh
27:32 debt which is about 5% points lower as a fraction of GDP of,
27:36 uh,
27:36 of,
27:36 uh,
27:37 external debt restructurings.
27:40 Uh,
27:41 we also find that the domestic restructurings are faster.
27:45 So in the table here,
27:45 you have,
27:46 uh,
27:46 the,
27:46 the duration in months
27:49 of external and domestic,
27:50 uh,
27:50 debt restructurings,
27:51 and what we find is that,
27:53 uh,
27:54 uh,
27:54 domestic restructuring takes on average
27:57 about 9 months less,
27:58 uh,
27:58 to be resolved than,
28:00 uh,
28:00 than,
28:01 uh,
28:01 than,
28:01 uh,
28:01 external one.
28:03 And then interesting thing here is perhaps like,
28:05 uh,
28:06 the evolution of these,
28:07 uh,
28:07 of these numbers.
28:08 So,
28:09 Uh,
28:10 we interpret the fact that,
28:11 uh,
28:12 domestic restructuring are faster to resolve
28:15 as a reflection of the fact,
28:17 uh,
28:17 that when you have domestic debt,
28:19 it's actually easier to restructure it because typically
28:22 domestic debt is governed by the domestic law.
28:24 And so changing the domestic law is much easier than,
28:27 uh,
28:28 than changing the international law.
28:30 But then the interesting aspect is that uh
28:32 there,
28:32 there is a,
28:33 we have seen a convergence uh
28:35 in the speed of uh uh the restructuring of domestic and external restructuring,
28:41 and we
28:42 attribute this to the fact that external restructurings
28:46 are getting faster thanks to to the introduction of cuts in,
28:50 uh,
28:50 in,
28:50 uh,
28:51 in,
28:51 in the contracts.
28:54 Um,
28:55 I'm gonna skip this,
28:57 uh,
28:57 because,
28:58 uh,
28:58 we need to be quicker.
28:59 Uh,
29:00 the next thing I want to say about domestic and external default is that,
29:03 uh,
29:03 what we are seeing is that domestic defaults are smaller,
29:06 quicker,
29:07 but yet,
29:08 uh,
29:08 for the subset
29:10 of,
29:11 uh,
29:11 uh,
29:12 of episodes for which we have the information about NPD losses,
29:16 NPV losses,
29:16 we see that domestic defaults are actually more punitive.
29:19 So here,
29:20 we report NPV losses for domestic and external debt,
29:24 and you see that,
29:25 uh,
29:26 uh,
29:27 that,
29:27 that the NPV losses are actually higher for,
29:30 uh,
29:30 for domestic,
29:31 uh,
29:31 for domestic restructuring.
29:33 And this is for us a bit surprising because there is often
29:37 this belief,
29:38 uh,
29:38 that governments tend to be nicer,
29:40 let's say,
29:41 uh,
29:42 towards,
29:43 uh,
29:43 their,
29:43 uh,
29:44 towards domestic creditors,
29:45 but here we don't,
29:46 we don't see this.
29:50 I'm gonna also jump,
29:51 uh,
29:52 uh,
29:52 this slide,
29:53 and I'm gonna concentrate to the last bit,
29:55 uh,
29:55 of,
29:55 uh,
29:56 the paper.
29:56 So in the last bit of the paper,
29:58 we change a bit the focus and,
30:01 uh,
30:01 we compare essentially the economic and political context,
30:06 uh,
30:07 in which domestic and external debt restructuring happens.
30:10 So in particular,
30:12 we are interested in,
30:13 uh,
30:14 how,
30:14 uh,
30:15 macrofinancial and political variable differ,
30:18 uh,
30:18 when,
30:18 uh,
30:19 when,
30:19 uh,
30:20 Uh,
30:20 governments take the decision to,
30:22 to restructure their debt.
30:24 Um,
30:25 so the first thing that we look at,
30:27 of course,
30:28 uh,
30:28 is,
30:28 uh,
30:29 at,
30:29 uh,
30:31 how GDP evolves around domestic and external,
30:34 uh,
30:34 external debt restructurings,
30:36 uh,
30:36 and,
30:37 uh,
30:37 this is what we show in the first,
30:38 uh,
30:39 in the first column.
30:40 And what you see here is that the coefficients are
30:42 very similar and they are both negative and significant.
30:45 So,
30:45 what we find is that both domestic and external
30:48 defaults tend to happen in periods of low growth,
30:51 OK?
30:51 And so this is actually
30:53 a very standard result.
30:54 And the,
30:55 the second,
30:55 uh,
30:56 the second column tells you that,
30:57 uh,
30:58 both also happen in periods of very high debt.
31:01 So this is nothing surprising.
31:02 So we see defaults when the economy is doing very badly and when,
31:05 uh,
31:06 Uh,
31:07 that is very high.
31:08 But then in the next table,
31:10 we actually
31:11 look into
31:12 essentially what are the different channels that might explain,
31:15 uh,
31:16 this,
31:16 uh,
31:16 uh,
31:17 uh,
31:18 this decline in GDP.
31:19 And we see that domestic and external,
31:21 uh,
31:22 restructuring,
31:23 uh,
31:23 happening very different,
31:24 uh,
31:25 in very different environments.
31:26 So we see
31:28 that the external default happen in periods of substantial
31:31 external adjustment and you can see it in the first
31:34 corner.
31:34 So you can see that
31:35 when you have an external default,
31:38 then you have like
31:39 uh
31:40 uh like an improvement of the current account
31:44 and,
31:44 and,
31:44 and also like a drop in the,
31:46 in the foreign inflow.
31:47 So this is an external adjustment and we don't see
31:50 this happening this as much when you,
31:53 when you,
31:53 when you have like a domestic restructuring.
31:56 Instead,
31:56 when we look at
31:58 Private credit,
31:59 so when we look at one of the variables that
32:02 is telling us what is happening on the credit side,
32:05 we see a negative significant coefficient only for domestic,
32:09 uh,
32:10 for domestic restructuring.
32:11 So this is telling us that domestic default
32:13 happens in period or are associated with the,
32:16 uh,
32:17 credit crunches.
32:19 Um,
32:20 so
32:21 the conclusion here is that even though like perhaps the,
32:24 the,
32:24 the,
32:24 the overall
32:26 economic environment is not to be similar because we see,
32:30 uh,
32:30 we see this contraction of GDP,
32:32 the channel that explains this contraction of GDP can be very different,
32:36 uh,
32:36 in the two,
32:37 in two different,
32:38 uh,
32:39 Episodes
32:41 I'm gonna jump the,
32:42 the,
32:42 the slides and gonna like talk about the last two
32:46 things that we look in the paper which is uh
32:49 the political context in which domestic and external uh uh restructuring happens.
32:55 And then I'm gonna talk about the role of the IMF.
32:57 Um,
32:58 so,
33:00 What we see in the first,
33:02 sorry,
33:02 uh,
33:03 in the first column
33:05 is,
33:05 uh,
33:05 a variable that measures political,
33:07 uh,
33:08 stability.
33:08 So what we find,
33:09 and this is a commonality between domestic and external default,
33:12 is that both of them,
33:14 they are associated with political instability,
33:16 OK?
33:18 But then,
33:18 uh,
33:19 we see that the elections uh are twice as
33:21 likely during domestic defaults than during external default,
33:26 OK?
33:27 So,
33:28 Possibly,
33:28 voters are very displeased when you default on,
33:31 uh,
33:31 on domestic debt.
33:33 And then instead,
33:34 what we see is that the radical governments
33:37 are more often in power
33:39 when,
33:39 uh,
33:40 when you have uh external,
33:41 uh,
33:42 external,
33:42 uh,
33:43 external defaults because perhaps you need a reckless government
33:47 to challenge,
33:47 uh,
33:48 you know,
33:48 the,
33:49 the,
33:49 the international,
33:50 uh,
33:50 rule of law.
33:54 And finally,
33:54 as I anticipated before,
33:56 I,
33:56 I,
33:56 we also look a bit at the role of uh bilateral lenders.
34:00 And so we see,
34:01 we look at what uh
34:02 IMF programs and official debt relief,
34:05 so what is their impact on,
34:06 uh,
34:07 on external and domestic uh restructurings,
34:09 uh,
34:10 and we see that,
34:11 uh,
34:12 In the,
34:13 uh,
34:13 and you can see this in the first column,
34:15 countries that receive support from the IMF,
34:18 uh,
34:18 they tend to prioritize uh repayment
34:22 of external debt
34:24 at the cost of actually increasing,
34:27 uh,
34:27 their,
34:27 uh,
34:28 their domestic,
34:28 uh,
34:29 domestic restructuring.
34:30 And here for,
34:31 for the IMF people in the,
34:33 in the,
34:33 in the room,
34:34 uh,
34:34 I mean,
34:34 we interpret this a reflection of the uh of the lending into arrears policies.
34:38 So the lending into arrears policies adds
34:41 An additional layer
34:43 of uh uh requirements uh to,
34:45 to,
34:45 to actually
34:47 Uh,
34:48 to actually,
34:48 for the IMF to borrow money to,
34:50 to,
34:50 to lend money to countries in troubles.
34:53 And so,
34:54 the,
34:55 and the lending into a real policy
34:57 only covers external debt.
34:59 So,
35:00 our
35:01 intuition is that perhaps uh
35:03 Countries want to avoid this additional layer of
35:07 like requirements and so they prefer to,
35:09 to,
35:09 to default on domestic debt to avoid entering uh into
35:13 the uh lending into arrears programs uh with the IMF.
35:17 And finally,
35:18 when we look at the official uh
35:21 debt relief,
35:22 uh,
35:22 we see that countries that uh receive official
35:24 debt relief are more likely to default,
35:26 uh,
35:27 externally,
35:27 and we,
35:28 we think this,
35:29 uh,
35:29 as a reflection of the comparability of
35:31 treatment policies that are often associated with,
35:33 uh,
35:34 uh,
35:35 with,
35:35 uh,
35:36 with this official debt relief.
35:38 In conclusion,
35:40 uh,
35:40 compared to the faults abroad,
35:42 the faults at home are smaller,
35:43 quicker,
35:44 and deliver larger,
35:46 uh,
35:47 Uh,
35:47 larger losses and the environment surrounding domestic and external defaults,
35:52 uh,
35:52 is very different.
35:54 Domestic defaults are associated with credit crunches.
35:56 External defaults happen at times of fiscal and external adjustments,
36:01 and also what we see
36:03 is that external defaults are less likely with moderate governments,
36:07 while domestic defaults are more likely to trigger elections.
36:17 Many thanks a week.
36:19 Now let's hear from Rong Cheng.
36:21 The floor is yours.
36:29 Thank you for inviting me to present this paper
36:31 which is joint work with Francisco from the IMF.
36:34 Um,
36:34 so,
36:35 the previous two presenters show a little bit of the
36:38 historical,
36:40 uh,
36:40 default history.
36:41 What I'm gonna present
36:42 is uh
36:43 more or less a theoretical model to
36:45 explain why some countries deform more than others
36:49 and the role of institutions.
36:51 So,
36:51 I will go very quickly on the motivation is to
36:56 try to understand
36:57 what explains the difference behavior between high-income
37:01 countries and middle and low-income countries.
37:03 In principle,
37:05 the,
37:05 the level of income doesn't matter for default risk,
37:08 but we do observe from the history.
37:11 And when we look at it among the middle and low-income country,
37:14 we also see that Latin American countries
37:17 tend to devolve more often historically.
37:20 And I'm from Argentina,
37:21 uh,
37:22 so that's my motivation.
37:24 Um
37:25 and then
37:26 I,
37:27 well,
37:27 I have two anecdotal evidence,
37:29 but I will only present the case of Argentina
37:31 in the 80s that had two sovereign default crises.
37:34 So,
37:35 in the 80s,
37:35 the,
37:36 the consolidated fiscal deficits reached to 15% of GDP
37:40 from the federal government,
37:42 local government,
37:43 and uh SOEs.
37:45 And at that time,
37:46 there was a,
37:47 a revenue sharing scheme.
37:49 Uh,
37:49 basically,
37:49 the federal government raised revenue and then transfer
37:53 to the,
37:54 uh,
37:54 local government,
37:55 and they do have an extraordinary uh treasury transfer system
37:59 for um
38:01 unusual events.
38:02 But during the three years.
38:04 In 1985 and 1987,
38:07 this revenue sharing scheme was suspended because the law that governed
38:11 it expired and took them three years to put back.
38:14 So during these three years,
38:16 basically the transfer between the federal government to the local government,
38:20 local government,
38:21 it was a
38:22 bilateral negotiation.
38:24 Uh,
38:25 and that created the uncooperative behavior by the local government,
38:30 tried to get maximum,
38:32 uh,
38:32 they can from the,
38:33 uh,
38:33 central government,
38:35 uh,
38:35 and the federal government couldn't,
38:38 uh,
38:38 push back because there was no legal framework in it.
38:41 So that's just keeping in mind this,
38:43 the,
38:44 the influence of the local government
38:46 on the federal government borrowing decision.
38:50 I will skip,
38:50 uh,
38:51 Brazil.
38:52 So,
38:52 just very quickly,
38:53 the
38:54 related literature,
38:55 look at the sovereign default,
38:57 um,
38:58 and usually in one country like Argentina,
39:01 try to explain what explained it,
39:03 and more recently,
39:05 there's a series of papers that incorporate political.
39:08 Economic consideration
39:09 in to explain that,
39:11 such as
39:12 the degree of impatience from the incumbent government
39:16 or
39:17 there's a left-wing government and
39:19 right-wing government that has different preference
39:22 that can lead to overborrowing.
39:25 And that is um
39:26 something that uh our paper as well as show.
39:29 So let me show you
39:30 quickly,
39:31 uh,
39:32 two-period model
39:33 with a closed form solution so you can see the intuition of the model.
39:38 So this is the government structure.
39:40 Um,
39:40 the government is
39:42 composed by a group of powerful groups
39:45 that want to influence in policy decisions.
39:49 In countries with good institutions,
39:52 there's rules set up
39:54 that limit the influence of these powerful groups in
39:58 central government decisions on spending and on borrowing.
40:02 Uh,
40:03 in weak institutions,
40:04 the central government cannot
40:06 limit the influence,
40:08 so something,
40:09 uh,
40:10 will happen,
40:10 as you will see,
40:12 and these,
40:12 um,
40:13 groups,
40:14 they also have different
40:16 ideas about what to spend,
40:18 how to spend,
40:19 so there's existence of a polarized,
40:22 uh,
40:22 polarization in ideology.
40:25 That,
40:26 that means that they cannot actually coordinate in
40:28 the optimal solutions because they have different ideas about
40:32 how to govern and how to spend.
40:35 And the distribution of power is captured by the,
40:38 the their power in the Congress,
40:40 for example,
40:41 or in terms of the share they get from the central government.
40:46 And these powerful groups,
40:48 they consume,
40:49 um,
40:50 they derive utility from the consumption goods.
40:53 They receive revenue or external borrowing from the central government.
40:58 They cannot do it directly.
40:59 They have to go through the central government.
41:01 And the good institutions,
41:03 because the central government
41:06 uh
41:07 solution is the optimal solution,
41:10 they borrow,
41:11 they make the optimal decision and transfer
41:14 to the local government.
41:16 In a weak institutions set up,
41:18 these groups.
41:20 Kind of uh maximize their own utility function,
41:23 make
41:24 decisions,
41:25 and as a result of that,
41:26 there's a negative externality that will arise because they do not internalize
41:31 the action of their
41:32 maximization function
41:34 into other groups.
41:36 So that's the,
41:37 the,
41:38 how the powerful groups try to influence policy.
41:40 And then we have the foreign investor that this is very typical in the literature,
41:44 that they are risk neutral
41:46 and they,
41:47 they are competitive,
41:48 uh,
41:48 they try to maximize,
41:50 um,
41:50 um,
41:51 the,
41:52 the interest rate that to match the risk-free interest rate.
41:55 They know
41:56 the institutional quality of the government.
41:59 Uh,
41:59 and the degree of polarization in the economy,
42:02 they lend
42:03 to the government,
42:04 uh,
42:05 as a whole,
42:06 not to individual groups.
42:10 And for the foreign investor,
42:11 as long as they don't get the full repayment,
42:14 they constitute a sovereign default.
42:17 So these are the,
42:18 they are all extreme,
42:19 but it's uh the setup for the modeling purpose.
42:23 So in the two-group and two-perio model,
42:26 we have two groups.
42:28 They have,
42:28 uh,
42:28 they are trying to uh uh consume goods through the transfer,
42:34 and in the model,
42:36 I just separate
42:38 countries with good institutions,
42:40 what I call unified government
42:42 or
42:43 countries with weak institutions,
42:45 what I call polarized government.
42:47 And remember that in the polarized government,
42:50 The powerful group tried to influence the central government policy,
42:54 and they succeeded.
42:56 Uh,
42:56 so there's a,
42:57 a negative externality because they cannot coordinate.
43:02 So I won't go into detail.
43:04 The unified government is the typical uh central planner solution.
43:08 They maximize utility of the two periods subject
43:11 to a budget constraint which derived from the endowment
43:15 and the borrowing.
43:17 And in the second period,
43:18 the revenue is the only shock in the economy,
43:22 so they either default or repay depending on the
43:25 realization of the revenue shock in the second period.
43:29 In a paralyzed government,
43:31 each group makes this same maximization problem.
43:34 Uh,
43:35 as you say,
43:36 uh,
43:36 see,
43:36 there's,
43:36 uh,
43:37 the maximization problem is for group one and two.
43:40 And the foreign investor
43:43 know that uh in a weak institution,
43:46 which means in this case,
43:47 the paralyzed government,
43:49 the default risk is the default risk,
43:51 the maximum default risk among the two groups.
43:54 As long as one group defaults,
43:56 it's optimal for the other group to default as well.
44:00 So that's the equilibrium interest rate.
44:02 And,
44:03 OK,
44:03 uh let me skip this.
44:04 Uh,
44:04 so,
44:04 uh,
44:05 the,
44:05 the,
44:06 the theoretical model can derive that
44:09 for all,
44:10 uh,
44:11 degree of polarization
44:12 in a,
44:14 a weak institution,
44:15 which means it's the polarized government,
44:17 the default
44:19 rate is higher,
44:20 the interest rate is higher,
44:21 and the debt level is higher.
44:24 And this is the intensive margin.
44:25 On the extensive margin,
44:27 the more polarized is the government,
44:30 the higher the default and the debt and interest rate.
44:33 And
44:34 let me just quickly
44:36 tell about the intuition.
44:38 It's the marginal cost
44:40 of borrowing
44:41 for one group
44:43 in a weak institution set up
44:46 is lower than the aggregate cost
44:48 of borrowing because they,
44:50 they do not internal.
44:52 The cost of borrowing that affects the whole country as a group while they only
44:57 receive a portion of that debt.
45:00 That's the source of a negative externality,
45:03 not internalized in a paralyzed government,
45:06 which means it's a weak institution set up.
45:10 So let me
45:11 quickly show you,
45:12 uh,
45:13 we try to incorporate this uh in an empirical study
45:17 and use two variables to capture the institution.
45:21 One is the standard CIRG and one is the
45:25 regulation of influence by the different interest groups in the,
45:30 in the economy.
45:31 So,
45:32 and the number 5 is the regulator's
45:35 case,
45:35 the country.
45:35 Has
45:36 set up the clear rule of how these different powerful group can
45:40 influence in the central government decision
45:43 and which policy cannot be influenced.
45:45 In an unregulated situation is,
45:49 remember the case of Argentina during those three years,
45:51 there's no legal framework how this negotiation happened.
45:55 And then we tested,
45:56 uh,
45:57 let me just show this one.
45:59 so we separate the countries,
46:01 uh,
46:01 in
46:03 good institution
46:04 versus,
46:05 uh,
46:06 weak institution.
46:07 So the variable para is the high,
46:10 the higher is the better.
46:12 So for countries below the medium,
46:15 uh,
46:15 the first column,
46:16 and above the medium,
46:18 and the 3 and 4 is the countries with para
46:22 above a medium,
46:23 uh,
46:24 below medium plus 1 standard deviation and above.
46:27 What I see,
46:28 what I try to show here is that the degree of polarization
46:32 only matters
46:34 in the setting of weak institutions.
46:37 So you can have,
46:38 you know,
46:39 the ideological difference among the government as
46:42 long as the institution is strong enough
46:44 to limit the influence of these groups,
46:47 the default risk is still,
46:48 uh,
46:49 manageable or the,
46:50 the variable doesn't even matter for default risk.
46:53 So let me conclude,
46:55 uh,
46:56 how this is,
46:58 um,
46:58 research is relevant today as Mueller already said,
47:02 many countries have higher debt to GDP ratio even before the pandemic.
47:06 It's even higher now,
47:08 and we also know there's a rising inequality
47:11 which could translate into ideological polarizations.
47:15 So what do we do to
47:18 limit these two factors that are already there,
47:22 is to set up institutions
47:24 to limit the spending pressure that will arise from the different groups.
47:29 And now,
47:29 currently I'm,
47:30 I'm,
47:30 I'm in Indonesia,
47:32 the only country in Asia that had a
47:35 a default crisis
47:37 after the Asian financial crisis,
47:38 and they do have a fiscal rule since then.
47:41 So I see that this political influence still exists in the context of Indonesia,
47:46 not maybe from the local government,
47:48 but from SOEs,
47:50 but they have the 3% of GDP as a fiscal rule
47:54 that is hard since 2003 and still remain very relevant.
47:58 As a result,
47:59 their debt to GDP ratios.
48:01 Remain the lowest in among the lowest in Asia Pacific,
48:04 but at the same time,
48:06 um,
48:06 this budgetary
48:08 process,
48:09 the PFM that the bank also uh uh advised a lot,
48:13 is also very important to make it transparent
48:15 so
48:16 this political negotiation doesn't happen.
48:18 And finally,
48:19 the debt transparency and.
48:21 Part of the other speakers um
48:24 show,
48:24 it's very important to know actually how much is the total debt
48:28 that we are talking about
48:29 and try to
48:31 conduct fiscal consolidation to lower the risk
48:34 because all defaults happen for only 3
48:37 reasons
48:38 either
48:39 capital flow reversal.
48:42 Interest increased by the um developed country or commodity shock.
48:47 And to lower the
48:48 risk for default is only to limit the debt level
48:51 for many of the developing countries.
48:53 Thank you.
48:58 Many times um
49:00 wrong and with this we concluded the presentations
49:03 and now we will hear from the discussions.
49:06 Let's start with Mark Chamon from the fund.
49:14 Thank you.
49:14 Uh,
49:14 it's a pleasure to be here to discuss the 3 papers.
49:17 Uh,
49:17 we have 3 papers to cover,
49:19 and I think,
49:19 uh,
49:19 we are behind schedule,
49:20 so let me just jump right in.
49:23 So,
49:24 uh,
49:24 first paper,
49:25 uh,
49:25 the one on the returns to China's Belt and Road Initiative,
49:29 um,
49:30 I wanna focus the comments on the issue of the haircuts
49:33 because I think they're also tied very closely to the,
49:36 uh,
49:37 financial returns on those loans.
49:39 Um,
49:39 the paper goes through,
49:40 uh,
49:40 systematically estimating the haircuts.
49:42 I just want to highlight a few,
49:44 uh,
49:44 points on this issue of haircuts.
49:47 First,
49:47 that
49:48 it,
49:48 it is somewhat constrained the choice of haircuts.
49:50 There are many reasons why,
49:52 uh,
49:53 even a large creditor may not have that much wiggle room to decide on its own haircuts
49:58 because we tend to have fairly robust,
50:01 uh,
50:02 creditor coordinating mechanisms when it
50:04 comes to official sector restructuring.
50:05 So notably the price club process.
50:08 And even if a,
50:09 uh,
50:09 uh,
50:09 a creditor is not a member of the Paris Club,
50:11 it will still end up being bound by the process because of the,
50:15 uh,
50:15 need to respect comparability of treatment.
50:17 So that could,
50:18 uh,
50:18 constrain the choices.
50:20 Uh,
50:20 it can also be constrained by
50:22 some hard restructuring targets.
50:23 For example,
50:24 if the country has an IMF supported program,
50:26 uh,
50:27 there might be a requirement to restore that sustainability,
50:30 which
50:30 will also,
50:31 uh,
50:31 in a sense constrain the,
50:32 the choice of haircuts of the different creditors,
50:34 uh,
50:35 could propose.
50:36 And
50:37 last but not least,
50:38 in the particular case of HPE,
50:40 there were like very clear rules for how each,
50:44 like,
50:44 you could go low one by low one and apply those rules that would then determine
50:48 what type of treatment would be expected on those low ones.
50:50 Um.
50:51 So if,
50:52 maybe if one wants to focus on this sort of bargaining dimension,
50:55 it might be useful to just focus on,
50:57 on episodes where there was only a restructuring,
50:59 a bilateral restructuring between the debtor and China,
51:03 which was not part of,
51:04 say,
51:04 a broader uh debt restructuring.
51:07 On,
51:08 on the issue of haircuts,
51:09 I also want to mention the discount rates.
51:11 Uh,
51:12 they,
51:12 they consider a range of discount rates.
51:14 I would suggest focusing
51:16 on the sample on the HIPIC discount rates and maybe on the more recent ones,
51:19 on the LDSF 5% discount rates,
51:22 which
51:22 is the,
51:23 uh,
51:24 yardstick that the other official creditors would use,
51:26 uh,
51:27 when looking at comparability of treatment.
51:29 Um,
51:30 on this,
51:31 uh,
51:32 and also encourage maybe a bit more comparison between the compare the haircuts,
51:35 but also looking at the rate of returns,
51:38 how it would compare to the other official creditors to also get a sense of how
51:42 usual or unusual the,
51:43 the lending behavior is.
51:46 But on,
51:46 on this issue of HP,
51:47 going back to this issue of HPI,
51:48 this is one of the charts that was used in the presentation.
51:52 And,
51:52 and just visually,
51:53 the point I want to highlight is that
51:55 A lot of the very episodes with very high haircuts tend to occur
51:59 early in the sample where the circle where the circles are quite small.
52:02 Remember,
52:03 the circles show the size of China's exposure to the country.
52:07 So in,
52:07 in a sense,
52:08 since China is a relatively new,
52:10 uh,
52:11 bilateral creditor,
52:12 it sort of sit out hit peak.
52:13 So when HI was taking place and all these very large haircuts were
52:18 Taking place,
52:18 China had very small exposures,
52:21 and to the extent they had small exposure,
52:22 it still
52:23 did participate in the HIPIC initiative,
52:25 uh,
52:26 but the exposures were small,
52:27 and I think that's
52:29 maybe that factor alone
52:30 may be driving the low average haircut and
52:34 taking account HIPIC maybe would bring it closer to the average of,
52:37 uh,
52:37 the other official creditors.
52:41 Turning to the second paper looking at domestic defaults,
52:44 this is actually something quite topical.
52:45 I mean,
52:46 as the paper highlights,
52:47 uh,
52:48 domestic debt is playing,
52:49 um,
52:50 a relatively more important role,
52:52 uh,
52:52 in recent episodes.
52:53 Uh,
52:54 I think
52:54 they may have too broad a definition of a domestic default.
52:58 Uh,
52:58 I think the,
53:00 the,
53:00 it may be including a lot of episodes that may be 1 may not necessarily,
53:04 uh,
53:04 considered a default,
53:05 but I think
53:06 Either way,
53:07 11 will cut it,
53:07 the,
53:08 the pattern will remain the same,
53:09 that this has become uh more important uh in recent years.
53:13 And I think this time dimension is something that maybe
53:15 the paper could go uh in a bit more detail.
53:17 They do have different breakdowns by time,
53:20 but I think this is quite an important dimension to explore.
53:23 On this issue of domestic restructuring,
53:25 there is this perception that maybe restructuring domestic debt is,
53:29 is easier because you're operating in your own jurisdiction,
53:31 but I think that's quite a
53:33 simplistic reading of the situation because any domestic restructuring would
53:37 bring a lot of financial stability considerations into play.
53:41 Uh,
53:41 and however bad the debt crisis is,
53:43 the financial crisis can be,
53:45 uh,
53:45 a lot worse.
53:46 So
53:47 you really need to be careful,
53:49 uh,
53:49 and,
53:50 and I think countries do tend to be quite conservative when approaching this issue.
53:53 Uh,
53:54 and
53:55 there was a reference to the IMF and we also tend to be quite,
53:57 quite cautious about it as well.
53:59 There's a recent,
54:00 uh,
54:00 board paper on domestic debt restructuring about 2 years ago where
54:04 this financial stability,
54:05 uh,
54:06 considerations to the future quite importantly.
54:09 Uh,
54:10 the paper finds larger losses for domestic debt,
54:12 uh,
54:13 which is,
54:13 uh,
54:14 uh,
54:14 a bit of a surprising result,
54:15 uh,
54:16 again,
54:16 because this financial stability considerations are,
54:18 are,
54:19 are so prominent and you have to be very careful about pushing losses
54:22 beyond
54:23 what the domestic bank can take.
54:26 Uh,
54:27 and,
54:27 uh,
54:27 it's also surprising because in the,
54:29 some recent cases,
54:30 there is indeed the,
54:32 the view that the domestic debt was restructured more likely,
54:35 and there's no expectation of,
54:37 uh,
54:37 comparability of treatment,
54:38 uh,
54:39 between domestic and external debts,
54:41 including the limiting case,
54:42 which are many cases where
54:44 external debt is restructured and domestic debt is not touched at all.
54:48 Uh,
54:49 so I,
54:49 I would,
54:50 uh,
54:50 I think part of the challenge here would be finding
54:53 the right discount rate for the domestic debt restructuring.
54:56 I think this is something that's
54:57 hard to do even for external debt restructurings.
55:00 For domestic debt,
55:01 it would be even more complicated because chances are,
55:04 you are in a very volatile situation,
55:06 high inflationary environment,
55:07 so what discount rate should one plug in?
55:10 Uh,
55:10 maybe one way around it could be to,
55:13 to complement the final analysis of the
55:16 comparing the expost and the ex ante market prices of the restructured claims.
55:19 I think
55:20 maybe that should be
55:22 doable,
55:22 at least for a few recent cases where this data may not be so hard to get.
55:26 And,
55:26 and from there,
55:27 you can compute different measures of either market or MPV haircuts
55:31 and use it as a cross-check.
55:34 And last but not least,
55:36 uh,
55:36 I'll turn to the,
55:38 to the third paper on the role of institutions.
55:40 Uh,
55:41 it presents a
55:43 very interesting model where you have two
55:44 different groups in the economy making separate,
55:47 uh,
55:47 borrowing and spending decisions,
55:49 and they're default decisions,
55:51 uh,
55:51 will affect the other groups.
55:52 So it's a very,
55:53 uh,
55:54 Easy way to get this overborrowing problem,
55:57 which is an alternative way to get over borrowing problem,
56:00 like
56:00 more traditional political economy channels in the literature like related to uh
56:05 short horizons or,
56:06 or high discounting.
56:08 And they,
56:08 they motivate the paper by the role of the subnationals,
56:11 uh,
56:12 giving examples of,
56:12 of states in Brazil and provinces in Argentina.
56:16 And the channel highlighted is quite strong as,
56:18 as the model calibration shows.
56:20 I mean,
56:21 it,
56:21 it is so strong that there has been a lot of effort,
56:23 uh,
56:24 to,
56:24 to try to address this institutional shortcomings.
56:27 So,
56:28 I,
56:28 I,
56:28 in the case of Brazil,
56:29 I know there was a,
56:30 a,
56:30 a fiscal responsibility law that was passed
56:32 in 2000 that really constrained how much,
56:35 uh,
56:35 The,
56:35 the fiscal policy of the states and local governments,
56:38 and I think uh probably something similar may have taken place in Argentina.
56:42 But
56:43 so this initial uh size and indeed the
56:46 anecdotal evidence all dates back from the 1980s.
56:49 So when I first read the paper,
56:51 my first reaction was that,
56:52 OK,
56:53 maybe this was a,
56:53 a big problem back then,
56:55 but we have seen uh graduated and the problem has been solved.
56:58 But then on second thought,
56:59 I,
57:00 I think this problem is still quite relevant because there are many,
57:03 many cases where we have state-owned enterprises
57:06 which do make a lot of borrowing decisions and they
57:09 are outside the direct control of the Ministry of Finance.
57:12 They may not necessarily be reporting what they're doing to the debt offices.
57:15 So I think this
57:17 Sort of channel of the centralized borrowings,
57:19 make borrowers making these decisions and then having spillovers of the country,
57:23 uh,
57:24 can,
57:24 is still quite relevant,
57:25 maybe not in the initial in the in the way that they,
57:29 uh,
57:30 related to the states or provinces,
57:32 but I think through the role of SOEs,
57:34 it's still,
57:35 it can be quite relevant.
57:36 So I think it's quite,
57:37 quite an important paper
57:39 in that regard.
57:40 And that's it.
57:41 I hope I,
57:41 I'm OK on time.
57:43 It's very well.
57:44 Thanks.
57:47 And now the last speaker
57:49 of this session,
57:49 Luca Bandera.
57:55 Thank you very much.
57:56 So I'll try to be brief.
57:57 I took,
57:58 I,
57:58 I kept time for everybody now,
57:59 I keep time for myself.
58:01 OK.
58:02 All right.
58:03 So,
58:04 uh,
58:05 yeah,
58:05 uh,
58:05 so comments on these three papers,
58:07 I will focus my comment on,
58:08 on what's,
58:09 uh,
58:09 basically
58:10 the,
58:11 the,
58:11 the policy implications since we are the World Bank and I work in the World Bank.
58:15 Uh,
58:15 then,
58:15 uh,
58:16 the date and definitions,
58:17 uh,
58:17 the regression and the theoretical model.
58:20 So let me go very fast.
58:22 So the key contribution,
58:23 I would say,
58:24 You know,
58:25 I,
58:25 I'm working with a lot of data on defaults and,
58:28 and these papers,
58:29 these two papers,
58:30 no,
58:30 the,
58:30 the,
58:31 the papers that,
58:31 that,
58:31 uh Christoph presented and,
58:33 and,
58:33 uh,
58:33 and uh Enrico presented,
58:35 um,
58:36 were,
58:36 were really,
58:37 uh,
58:37 really,
58:38 uh,
58:39 you know,
58:39 uh,
58:40 gave key contributions,
58:41 right?
58:41 Because the granularity of this information is extremely important,
58:44 uh,
58:44 knowing when a country defaults,
58:46 how long the default lasts,
58:47 it's,
58:48 it's extremely important,
58:49 and
58:49 there is,
58:50 uh,
58:50 uh,
58:51 say paity of data.
58:53 On the domestic debt default episodes and,
58:56 uh,
58:56 and,
58:57 you know,
58:57 this,
58:57 this analysis that was presented today really feels,
59:00 feels,
59:00 uh,
59:00 uh,
59:01 part of the gap,
59:02 um,
59:03 um,
59:03 with,
59:04 with some,
59:05 some,
59:05 uh,
59:06 empirical uh statistics that it's,
59:08 uh,
59:08 it's important to notice,
59:09 uh,
59:10 so far,
59:10 no,
59:10 the,
59:11 the,
59:12 uh,
59:13 you know,
59:13 conventional wisdom is that the default episode basically overlap,
59:16 but they said no,
59:16 they don't,
59:17 right?
59:17 And it will be important to understand exactly in which countries in,
59:20 in,
59:21 in what circumstances.
59:22 Also,
59:23 the importance of political-related variables
59:25 and um
59:27 the fact that,
59:27 that uh different defaults have different outcomes in terms of uh
59:31 haircuts,
59:32 uh uh they are preventive uh which creators have lost,
59:35 so it's really rich,
59:37 uh,
59:37 the,
59:37 the contribution of this paper is really rich.
59:40 Uh,
59:40 and there are policy implications,
59:41 no,
59:42 the,
59:42 if I can really summarize,
59:43 the defaults are very expensive,
59:45 so better to avoid them,
59:46 even though
59:46 the contribution that,
59:47 for example,
59:47 an institution like the World Bank could give to this default is very different.
59:50 Uh,
59:50 external defaults
59:52 are linked to,
59:52 you know,
59:53 balance of payment problems,
59:54 uh,
59:54 domestic default connected with,
59:56 you know,
59:57 uh,
59:57 financial,
59:58 uh,
59:58 stress,
59:59 domestic financial stress.
1:00:00 Uh,
1:00:01 debt relief is often not deep that we knew,
1:00:03 and,
1:00:03 uh,
1:00:04 the fact that many countries today require deep debt restructure implies
1:00:08 That,
1:00:08 that debt restructuring are really prolonged and very
1:00:10 costly for the countries and the creditors likewise,
1:00:13 and loans from Chinese banks uh seems not to follow,
1:00:16 you know,
1:00:17 uh,
1:00:17 economic and financial risk assessment,
1:00:19 but they are motivated in a different way.
1:00:21 That implies that maybe one of the largest creditors do not really follow
1:00:25 what we try to preach,
1:00:26 right?
1:00:27 That
1:00:28 the terms of the loans is to be
1:00:30 uh adequated to the,
1:00:31 to the,
1:00:32 to the capacity repayment of the country.
1:00:34 Other,
1:00:35 other implications are less clear,
1:00:36 uh,
1:00:37 like,
1:00:37 for example,
1:00:38 we have very little uh leverage on the political system of the country.
1:00:42 So I wonder if
1:00:43 the analysis,
1:00:44 especially the analysis on the,
1:00:46 uh,
1:00:46 defaulted institutions can look at
1:00:48 You know,
1:00:49 we can use in the regression and the empirical analysis,
1:00:51 the variables that are more
1:00:53 closer to what we can impact upon like countries that have fiscal rules,
1:00:57 countries that have a good understanding of how to,
1:01:00 you know,
1:01:00 regulate SOEs,
1:01:02 uh,
1:01:03 or institutional variables like
1:01:05 federal governments,
1:01:06 right,
1:01:07 uh,
1:01:07 compared to centralized governments.
1:01:10 Um,
1:01:11 also,
1:01:12 another point is,
1:01:14 uh,
1:01:14 Chinese debt restructuring seems
1:01:17 Uh,
1:01:18 you know,
1:01:18 have different
1:01:19 haircuts and maybe a temporal dimension of it,
1:01:22 as also Marco,
1:01:23 uh,
1:01:23 noticed,
1:01:24 uh,
1:01:24 may be important.
1:01:25 Uh,
1:01:25 during HEPIC time,
1:01:26 it seems to us,
1:01:27 uh,
1:01:27 we,
1:01:28 we draft,
1:01:28 uh,
1:01:29 together with the IMF progress report on the HEPIC initiative.
1:01:33 Chinese creditors provided debt relief that was in line
1:01:36 with the debt relief required in the HEPIC initiative.
1:01:38 Uh,
1:01:39 therefore,
1:01:39 maybe it's worth,
1:01:40 uh,
1:01:41 uh,
1:01:41 stressing the fact that maybe there is
1:01:43 The Chi and Chinese banks or,
1:01:45 or different Chinese policy banks may have followed
1:01:49 uh other creditors,
1:01:50 comparability of treatment uh implications apply.
1:01:53 Um,
1:01:54 also,
1:01:54 uh,
1:01:55 in the paper on the domestic around default at the home and away.
1:01:59 Um,
1:02:01 There is a,
1:02:01 a bit of a contradiction.
1:02:03 On one hand,
1:02:03 it seems that
1:02:05 Uh
1:02:07 IMF lending.
1:02:09 Implies that there is not,
1:02:11 there are not external defaults,
1:02:12 but on the other hand,
1:02:14 external defaults are associated with the
1:02:16 debt relief from official creditors which in turn are also
1:02:19 take place always in the context of an IMF program or very,
1:02:23 very often,
1:02:24 I would say.
1:02:25 So there is a kind of internal contradiction
1:02:28 in this,
1:02:28 in these results.
1:02:31 Uh,
1:02:31 moving to data and definitions,
1:02:33 um,
1:02:34 I think that,
1:02:35 that both papers on the Belt and Road and the,
1:02:37 uh,
1:02:38 default,
1:02:38 uh,
1:02:39 home and,
1:02:39 uh,
1:02:39 and abroad,
1:02:40 uh,
1:02:42 could be more precise on the definition of defaults and restructuring periods.
1:02:46 This is really,
1:02:46 really,
1:02:47 uh,
1:02:47 relevant for the empirical analysis
1:02:49 to know exactly when a default happened,
1:02:51 right?
1:02:51 Default is different from restructuring,
1:02:53 so it's very important to be very clear on
1:02:57 what,
1:02:58 what is the,
1:02:59 what they measure.
1:03:00 Um,
1:03:01 also,
1:03:02 surprisingly,
1:03:03 the paper on the Belt and Road implies that many loans,
1:03:05 this is what is in slide 5,
1:03:08 are,
1:03:08 are not from China Exim Bank or China Development Bank.
1:03:11 And maybe,
1:03:13 you know,
1:03:13 it's worth
1:03:14 digging through,
1:03:15 right?
1:03:15 Provide more detail.
1:03:16 Would these
1:03:17 banks somehow or these creditors behave differently
1:03:20 and provide more or,
1:03:22 or less
1:03:23 uh PV reduction compared to the
1:03:26 two big banks,
1:03:27 not the China Exim Bank and the China Development Bank.
1:03:30 Uh,
1:03:31 finally,
1:03:32 the,
1:03:32 the,
1:03:32 the,
1:03:32 the default and institution paper uses probabilities that are from,
1:03:36 you know,
1:03:37 the,
1:03:37 the initial papers on the default like the
1:03:39 Reiner Rogoff paper in 2009 and other papers,
1:03:42 but there are,
1:03:43 you know,
1:03:43 sources of,
1:03:44 uh,
1:03:45 of,
1:03:45 uh,
1:03:45 of,
1:03:46 um,
1:03:47 you know,
1:03:47 of distress,
1:03:48 including these two papers now presented that could
1:03:50 be used to update and use much longer time period compared to the,
1:03:55 to the data presented.
1:03:57 Uh,
1:03:57 so let me skip the last one because I already made the point that,
1:04:00 that maybe we need,
1:04:01 we need,
1:04:01 uh,
1:04:02 it,
1:04:02 it could
1:04:03 be helpful to use indicators that are
1:04:06 closer to
1:04:07 Uh,
1:04:07 you know,
1:04:08 causes that,
1:04:09 that the World Bank or IFIs in general can act upon,
1:04:12 uh,
1:04:13 to,
1:04:13 to,
1:04:14 to help countries.
1:04:16 Finally,
1:04:17 moving to regressions,
1:04:18 um,
1:04:20 The Belt and Road paper focuses on the regressions basically on
1:04:23 the financial returns and put emphasis on loan purposes and characteristics.
1:04:27 But what about the characteristic of the country?
1:04:29 Would
1:04:29 the,
1:04:30 would
1:04:31 PV reduction be higher in low in low-income
1:04:34 countries or um compared to middle-income countries,
1:04:37 uh,
1:04:38 would,
1:04:39 you know,
1:04:39 Chinese
1:04:40 lenders
1:04:42 provide more concessional terms to,
1:04:44 uh,
1:04:45 countries that are also recipient of concessional financing from IFI.
1:04:49 So is there a
1:04:50 You know,
1:04:50 similar behavior,
1:04:51 uh,
1:04:52 that could be considered since you have all the terms,
1:04:54 um,
1:04:55 and
1:04:56 also
1:04:57 there is,
1:04:58 there was not similar analysis for the PB reduction,
1:05:01 right?
1:05:01 There are countries where China provide more or less debt reduction,
1:05:05 the original loan terms matter for the amount of PB reduction,
1:05:08 or,
1:05:09 you know,
1:05:09 different banks provide different debt relief.
1:05:12 Um,
1:05:13 the same,
1:05:14 same thing on the,
1:05:15 on the,
1:05:15 uh,
1:05:16 paper,
1:05:16 uh,
1:05:17 on the
1:05:19 default at home and,
1:05:20 uh,
1:05:20 and abroad,
1:05:21 where
1:05:22 basically regressions measure the association of certain
1:05:25 characteristics in the case of default,
1:05:27 however,
1:05:27 if the focus would be on more on a profit model,
1:05:30 Uh,
1:05:31 then,
1:05:32 you know,
1:05:32 probability of
1:05:34 default could have been
1:05:36 estimated,
1:05:37 uh,
1:05:37 that would have been very helpful to researchers and,
1:05:40 uh,
1:05:40 you know,
1:05:41 users like ourselves,
1:05:43 uh,
1:05:43 to understand the causes of,
1:05:44 of,
1:05:45 of defaults.
1:05:46 Finally,
1:05:46 the default and institutions paper uses
1:05:49 regressors that are are highly correlated,
1:05:52 uh,
1:05:52 richer countries have better institutions,
1:05:54 uh,
1:05:55 and therefore some robustness checks and uh
1:05:58 Uh,
1:05:58 for example,
1:05:59 use of instrumental variable would have been,
1:06:01 uh,
1:06:01 possible,
1:06:02 then theoretical model are a few,
1:06:04 um,
1:06:05 so just to the bare minimum,
1:06:07 is that in the theoretical model of the,
1:06:10 uh,
1:06:10 defaulted institutions,
1:06:11 basically,
1:06:13 the,
1:06:14 it is important to understand that,
1:06:15 that,
1:06:16 so a country with high
1:06:17 level of institutions basically does not suffer polarization.
1:06:21 This is what comes out from the empirical analysis.
1:06:24 But the model
1:06:25 in a sense implies that there is always impact on polarization,
1:06:28 and I wonder if
1:06:29 this,
1:06:29 uh,
1:06:30 this,
1:06:30 uh,
1:06:31 you know,
1:06:31 an additional variable could be introduced
1:06:33 in order to maintain the same
1:06:35 regularity that we see in the,
1:06:37 uh,
1:06:38 in the empirical data.
1:06:40 I'll stop here.
1:06:41 Thank you very much.
1:06:44 Yeah,
1:06:44 thank you.
1:06:47 And I believe we still have some time according to the revised agenda.
1:06:52 So,
1:06:52 um,
1:06:53 we'll now take questions from the floor,
1:06:56 5 minutes and so I think there are mics in the room.
1:07:00 So if you could go to a mic
1:07:02 and uh if you could briefly introduce yourself.
1:07:08 Thank you.
1:07:16 Hi,
1:07:17 thank you very much.
1:07:18 My name is Mohindra Gulati,
1:07:19 and my question is on the presentation on the BRI.
1:07:24 Where he showed that the rate of return,
1:07:26 financial rate of return was
1:07:28 Less than 2%.
1:07:30 I assume that this is on the basis of the
1:07:33 project cost,
1:07:34 structuring,
1:07:35 and the financing plan
1:07:37 as presented.
1:07:39 Did you take into account
1:07:41 the fact
1:07:43 that the goods and services
1:07:46 in the BRI projects
1:07:47 are generally supplied by the Chinese firms?
1:07:51 The clawback that you can get
1:07:54 from the inflated prices of those contracts,
1:07:58 which can be 1415,
1:07:59 16%,
1:08:00 and believe me,
1:08:01 that's a conservative estimate.
1:08:03 So if you have a clawback of 15% from inflated prices of those contracts,
1:08:09 Your rate of return would be
1:08:11 14 to 16%,
1:08:12 even if you deflate it
1:08:14 over a period of 3 or 4 years of implementation.
1:08:17 So the financial rate of return
1:08:19 is not 2%,
1:08:20 it could be
1:08:21 14 to 16%.
1:08:24 And one more variable,
1:08:25 if you add to it,
1:08:26 if these goods and services
1:08:29 are being supplied by firms
1:08:31 which have overcapacity,
1:08:34 then just imagine
1:08:36 the multiplier effect
1:08:38 of the utilization of that idle capacity,
1:08:41 uh,
1:08:42 which,
1:08:42 which would otherwise be a,
1:08:43 be a very expensive
1:08:45 financial and economic cost to the,
1:08:47 to the,
1:08:47 to the Chinese economy.
1:08:49 So the haircut that you see of 2%,
1:08:52 compare that with the
1:08:54 cost of ideal capacity
1:08:56 of the goods and services which are being supplied
1:08:58 in the BRI projects.
1:09:00 So,
1:09:00 were you able to take any of these things into account
1:09:03 in your calculations?
1:09:06 Let's take 2 more questions.
1:09:14 Hello,
1:09:17 I'm sorry.
1:09:17 Hello,
1:09:17 my name is Benny Lara,
1:09:19 um,
1:09:19 previously a member of parliament from Nigeria.
1:09:23 I'm here with the members of the Foundation and our heads,
1:09:27 Solomon and Mary La Foundation,
1:09:28 my mother,
1:09:29 former ambassador,
1:09:30 and Doctor Lara.
1:09:31 So the question
1:09:32 I have is,
1:09:34 you did say that
1:09:36 um there's
1:09:40 Domestic borrowing,
1:09:41 there's usually higher returns of,
1:09:43 um,
1:09:44 you know,
1:09:44 repayment on domestic loans than external loans.
1:09:48 What are you doing to ensure that because my country,
1:09:51 usually Nigeria,
1:09:52 we have,
1:09:52 you know,
1:09:53 huge volumes,
1:09:53 we borrow so much money and it becomes a political issue.
1:09:57 And it is going to be an issue in the next election.
1:09:59 What are you doing to try to ensure that some countries such as ours,
1:10:03 um,
1:10:04 we do more of
1:10:06 domestic borrowing rather than external loans,
1:10:09 um,
1:10:10 because that is always a,
1:10:11 a big political issue when it comes to elections.
1:10:15 Um,
1:10:15 and then also,
1:10:16 are we,
1:10:17 is Nigeria considered a low income,
1:10:19 medium,
1:10:19 middle income,
1:10:20 or
1:10:21 What,
1:10:22 you know,
1:10:22 because I hear in different parlance,
1:10:24 some say we're lower income,
1:10:25 some say we're middle income.
1:10:26 What exactly are we,
1:10:27 is our income level,
1:10:29 according to the World Bank.
1:10:30 Thank you.
1:10:32 Thank you.
1:10:34 Do we have uh another question?
1:10:38 OK.
1:10:39 If not,
1:10:39 let's start with this.
1:10:44 Yes,
1:10:45 mhm,
1:10:46 yeah,
1:10:46 it was,
1:10:46 I guess a question for,
1:10:47 uh,
1:10:48 for me.
1:10:48 I'm not quite sure honestly how this is classified,
1:10:50 uh,
1:10:51 by the World Bank.
1:10:52 Uh,
1:10:53 the,
1:10:53 the,
1:10:53 the income level for,
1:10:54 uh,
1:10:55 for your country,
1:10:55 I think it's a low-income country,
1:10:57 but honestly,
1:10:57 I would need to,
1:10:58 low middle income country.
1:11:00 OK,
1:11:00 thanks for,
1:11:01 uh,
1:11:01 for the,
1:11:02 I don't work for the World Bank,
1:11:03 so I'm not
1:11:04 supposed to know this.
1:11:05 So,
1:11:06 um.
1:11:07 In terms of domestic versus external,
1:11:10 uh,
1:11:10 uh,
1:11:10 we,
1:11:11 I mean,
1:11:11 uh,
1:11:12 we are not so sure that it's so straightforward to say that,
1:11:16 uh,
1:11:17 domestic debt is better than external one when it comes to default.
1:11:20 I mean,
1:11:21 we have a more nuanced,
1:11:22 uh,
1:11:23 actually take,
1:11:23 uh,
1:11:24 on,
1:11:24 uh,
1:11:24 on our result.
1:11:25 Uh,
1:11:26 for sure,
1:11:27 uh,
1:11:28 We see,
1:11:29 uh,
1:11:30 that,
1:11:30 uh,
1:11:31 widening,
1:11:32 uh,
1:11:33 the investor base,
1:11:34 uh,
1:11:35 is helpful for countries and is also
1:11:37 helpful for government because government can,
1:11:39 can actually default selectively
1:11:42 and therefore,
1:11:43 uh,
1:11:44 uh,
1:11:45 essentially,
1:11:46 uh,
1:11:46 you,
1:11:47 you go from a very discrete choice of either default or I don't default to a more like,
1:11:51 uh,
1:11:52 Uh,
1:11:53 continuous choice of uh a default on
1:11:56 a fraction of the debt.
1:11:58 So you,
1:11:58 you essentially,
1:11:59 you increase,
1:12:00 uh,
1:12:00 your,
1:12:00 uh,
1:12:01 your,
1:12:01 uh,
1:12:01 your,
1:12:02 your,
1:12:02 your possibilities as a government when you have,
1:12:05 uh,
1:12:05 uh,
1:12:06 domestic and external debt market.
1:12:07 I think a key issue
1:12:09 to develop domestic,
1:12:10 uh,
1:12:10 debt market is,
1:12:11 uh,
1:12:11 the debt uh of financial,
1:12:13 of domestic financial markets.
1:12:14 You need,
1:12:14 uh,
1:12:15 to have the ability to absorb the
1:12:17 debt domestically.
1:12:19 Thank you.
1:12:20 Do you want to take the question,
1:12:21 right?
1:12:21 Yes,
1:12:22 sure.
1:12:22 Uh,
1:12:22 thank you very much for the question.
1:12:24 These are very good points.
1:12:25 Uh,
1:12:25 so
1:12:26 the way we see the paper is that it's a first step towards moving away from anecdotes
1:12:31 and having a more systematic overview on the returns.
1:12:34 Now,
1:12:34 this said,
1:12:35 this is the first step in the sense that we look at
1:12:37 the perspective of Chinese creditor banks,
1:12:40 right?
1:12:40 So these are just the loans,
1:12:42 the pure financial returns or the
1:12:43 loans accounting for defaults and restructurings.
1:12:46 Um.
1:12:47 We do not
1:12:48 compute that this would be another project,
1:12:50 uh,
1:12:51 very ambitious one,
1:12:52 the returns for Chinese firms at large,
1:12:54 for the construction firms,
1:12:56 for the railway companies engaged there,
1:12:57 etc.
1:12:58 etc.
1:12:58 So that's,
1:12:59 you know,
1:12:59 the equity returns or the construction returns,
1:13:01 they are not in our paper,
1:13:03 but it would be fascinating to move that step and,
1:13:06 uh,
1:13:06 the,
1:13:07 the,
1:13:07 the points you raised,
1:13:08 uh,
1:13:09 you know,
1:13:09 raise further my interest in going in that direction,
1:13:11 but it's hard to get systematic.
1:13:13 Data
1:13:14 on these projects and to compute uh return on equity or return on investments,
1:13:20 both in the construction and the management of
1:13:21 these projects and what it all involves.
1:13:23 So I think
1:13:25 in a way,
1:13:26 this is a bigger agenda.
1:13:27 We are doing an,
1:13:28 I,
1:13:29 I think an important first step to understand the lending dimension,
1:13:32 the financial uh returns,
1:13:34 uh,
1:13:34 but there's much more of course to understand uh the,
1:13:37 the,
1:13:38 uh,
1:13:38 additional returns involved.
1:13:40 First,
1:13:41 the equity,
1:13:41 but also the non-financial returns,
1:13:42 the geopolitical returns that I was also uh mentioning in,
1:13:46 in my,
1:13:46 in my talk.
1:13:47 Thank you.
1:13:48 I believe we have time for one
1:13:51 or two more questions.
1:13:58 Please
1:14:04 I just wanted a clarification,
1:14:06 uh,
1:14:07 when you were presenting,
1:14:08 I think,
1:14:08 uh,
1:14:09 wrong.
1:14:09 I think it was your presentation about inequality,
1:14:12 increasing polarization.
1:14:15 Can you please clarify that?
1:14:17 Because
1:14:17 in terms of Gini coefficient,
1:14:19 which is what came to mind as you were talking about inequality.
1:14:23 I was wondering why you would say it increases.
1:14:26 Doesn't polarization
1:14:28 also worsen
1:14:29 inequality?
1:14:30 Because you have sort of people who
1:14:33 control the system in terms of governance.
1:14:36 And so when they control the system,
1:14:38 they manipulate
1:14:39 whatever resources comes in.
1:14:41 To me,
1:14:42 that seems to actually increase
1:14:44 inequality in terms of the Gini coefficient as opposed to the reverse.
1:14:48 Or maybe it's just a
1:14:50 You know,
1:14:51 maybe I got it wrong,
1:14:52 so please clarify that.
1:14:53 Thanks.
1:14:54 Yeah,
1:14:54 very good question.
1:14:55 Uh,
1:14:56 I was just waiting to see if there is,
1:14:58 uh,
1:14:59 one more question from the audience,
1:15:00 and will that,
1:15:01 with that will conclude the questions.
1:15:04 OK.
1:15:05 I think uh we are good from the audience,
1:15:07 so over to you.
1:15:09 Yeah,
1:15:09 uh,
1:15:09 this,
1:15:10 uh,
1:15:10 from,
1:15:10 so,
1:15:11 uh let me separate the,
1:15:13 the,
1:15:13 uh,
1:15:13 policy implication versus in the model.
1:15:15 In the model,
1:15:16 uh,
1:15:16 in the empirics,
1:15:17 the polarization is measured as ideological difference.
1:15:22 So in a country,
1:15:23 the largest 3 groups
1:15:26 was their ideology,
1:15:27 was their seat in the government to capture this ideological or political
1:15:32 polarization.
1:15:34 What I mean by increasing income inequality,
1:15:37 there's actually a recent
1:15:40 growing literature to try to understand
1:15:42 whether the increasing income.
1:15:44 Equality
1:15:45 also lead to ideological polarization.
1:15:48 And I think I see this in working in the countries
1:15:51 is
1:15:52 since
1:15:52 income inequality is so wide,
1:15:55 only the,
1:15:56 uh,
1:15:57 the elites are in the government
1:15:59 and they have a very different preference in spending decision
1:16:02 than other groups.
1:16:04 So,
1:16:05 if they are more.
1:16:06 Likely to be in making decision,
1:16:10 they might prefer different spending or borrowing decision
1:16:13 than if the inequality is less.
1:16:15 So,
1:16:16 so that's
1:16:17 where the policy implication come from.
1:16:19 But this,
1:16:19 this is not in the paper per se.
1:16:22 It's more on the reflection of how this paper,
1:16:25 the theoretical model can be applied in the current context.
1:16:29 Thank you.
1:16:29 And with this,
1:16:30 let's conclude.
1:16:31 Thank you so much for your participation
1:16:35 and many thanks to.
1:16:41 Thank you so much,
1:16:42 Manuela.
1:16:43 Uh,
1:16:43 we're taking a 5-minute break,
1:16:46 right.
1:16:47 Greater than the incoherence is the challenge of keeping us on time.
1:16:49 So please be back in 5 minutes.
1:16:50 There is coffee outside.
1:16:55 That
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- lp-body-content
A video recording of the second session—Day 1—of The Annual Bank Conference on Development Economics 2024 "The Great Incoherence: Growth and Human Development in An Era of Stagnation." This session discusses "Sovereign Debt and Default."
Papers discussed in this session are:
- Paper 1: The Financial Returns on China’s Belt and Road (Christoph Trebesch, Kiel University)
➜ Presentation - Paper 2: Sovereign Defaults at Home and Abroad (Enrico Mallucci, Federal Reserve Board)
➜ Presentation - Paper 3: Why do Some Countries Default More Often Than Others? The Role of Institutions (Rong Qian, World Bank)
➜ Presentation