00:06 Good morning,
00:07 everyone.
00:07 Um,
00:08 uh,
00:08 good afternoon,
00:09 good evening to those of you who are joining us online.
00:11 Thanks very much for coming to join this,
00:14 um,
00:15 deck Knowledge seminar today.
00:16 Um,
00:17 I'm Art Crey and I'm the World Bank Group
00:19 Deputy Chief Economist and Director of Development Policy in the
00:23 Development
00:24 Economics vice presidency
00:26 of the World Bank.
00:27 I think I said development many times in that sentence.
00:29 That was too many.
00:30 Uh,
00:30 I will be your,
00:31 um,
00:32 uh,
00:32 I'll be hosting and,
00:33 and,
00:33 and chairing this event.
00:35 So,
00:35 this event is organized by the Knowledge for Change
00:38 umbrella Trust Fund Program or the KCP program.
00:41 The KCP has been delivering high-impact policy-relevant research,
00:45 data and analytical products for evidence-based development
00:48 policy and practice for 20 years.
00:50 And to celebrate this milestone of a 20th anniversary,
00:54 we've organized a series of knowledge seminars to showcase
00:57 the evolution of research and knowledge and select,
01:00 uh,
01:00 thematic fields,
01:01 um,
01:02 over the past 20 years,
01:03 and particularly with an emphasis on research that has been
01:06 funded thanks to the generosity of our KCP donor partners.
01:11 In the first two events,
01:12 uh,
01:13 which we had,
01:13 um,
01:14 last fall and earlier this year,
01:15 we covered the topics of conflict and migration,
01:18 environment,
01:19 climate,
01:19 poverty,
01:20 inequality,
01:21 and human capital development.
01:23 Today's seminar is a doubleheader.
01:25 We will have a session on trade and then a session on private sector development.
01:29 And this will be the 3rd and final of our 20th anniversary celebrations,
01:34 um,
01:34 of,
01:34 uh,
01:35 of the KCP.
01:37 So just to give you a brief overview of how today's um uh event is organized.
01:41 We're gonna have a,
01:42 a two-part event.
01:43 So the first session will focus on trade and international integration.
01:46 The second one will be on private sector development.
01:49 Um,
01:50 you know,
01:50 we chose these topics not just because they're intrinsically important,
01:53 but because they're also really an excellent opportunity
01:56 to highlight a lot of the very interesting,
01:58 uh,
01:59 research work that KCP has funded,
02:01 um,
02:02 uh,
02:02 uh,
02:03 to,
02:03 you know,
02:03 help to build this body of knowledge
02:05 that's benefited not just the World Bank,
02:07 but the whole development community.
02:09 So through these discussions,
02:10 we'd like to be able to showcase the
02:12 evolution of research and knowledge in these fields
02:15 and have,
02:15 and have some forward-looking thinking about new solutions.
02:19 Um,
02:20 and with a particular emphasis on strengthening the links between original
02:24 research and then also the development policy questions that we face,
02:27 um,
02:28 at the World Bank and in the wider development community.
02:31 So for both sessions,
02:32 we're going to start with um headline presentations
02:35 that are led by um by deck researchers
02:38 followed by um a panel discussion,
02:40 and then we'll open the floor for interactive Q&A.
02:44 So,
02:45 the,
02:45 um,
02:45 the focus of each of the sessions is going to be,
02:48 uh,
02:49 to,
02:49 you know,
02:49 really think about how knowledge has evolved over the last,
02:53 um,
02:53 20 years.
02:54 What were some of the big questions over this twenty-year period?
02:57 What have been the major breakthroughs in our understanding,
03:00 um,
03:01 on these topics and how they influenced policy.
03:04 So,
03:05 And
03:06 we don't want this just to be sort of a self-congratulatory look
03:09 back and look at all these great things that we've done,
03:11 but we also really want this to be forward-looking and thinking about
03:14 how we set the agenda for a new set of questions that are coming,
03:18 uh,
03:18 that,
03:18 that are coming in the near future and in the longer term.
03:22 Um,
03:23 because,
03:23 you know,
03:23 20th anniversary is not a,
03:25 a,
03:25 a time to stop.
03:26 It's a time to start thinking about what the next
03:28 20 years of KCP are going to look like.
03:31 Um,
03:32 so,
03:33 um,
03:33 just as a couple of quick housekeeping items before we start,
03:36 um,
03:36 most of,
03:37 um,
03:37 our,
03:38 uh,
03:38 interested,
03:39 um,
03:39 uh,
03:40 participants are joining us online.
03:42 Um,
03:43 And if you have any questions,
03:45 please share them during the chat.
03:47 You can do so at any point during the presentation and
03:50 then we'll come back and collect the questions from the chat.
03:53 Also,
03:54 I just want you to note that this event is being recorded.
03:56 The recording and presentations will be
03:58 available on the event website afterwards.
04:00 So,
04:01 all your pithy thoughts and objections and,
04:04 uh,
04:04 and comments will be preserved,
04:06 uh,
04:06 for posterity in that way.
04:09 All right.
04:09 So,
04:10 without further ado,
04:11 let me turn to the first set of speakers.
04:12 Um,
04:13 I'll start just by introducing the speakers and
04:15 then when we return to the discussions I'll,
04:16 I'll introduce them.
04:18 Uh,
04:18 so it's,
04:19 uh,
04:19 really great to have,
04:20 um,
04:21 uh,
04:21 22 fantastic deck researchers highlighting this first session.
04:25 We have,
04:26 uh,
04:26 Daria Taglione,
04:27 who's the research manager of the trade and international integration,
04:31 trade and international integration
04:33 in the Development Research Group.
04:35 Um,
04:35 and then we have,
04:36 uh,
04:36 Florence Konbliss,
04:37 who is a research manager
04:39 focusing on issues related to economic transformation and growth research
04:43 in the,
04:44 in Development Impact Evaluation Group or DIME.
04:47 Um,
04:47 so,
04:48 I'll turn over the floor.
04:49 I think Daria is going first and then Florence.
04:51 Um,
04:52 You have an aggregate budget of 25 minutes,
04:55 uh,
04:55 which I will enforce rigidly.
04:56 Within that,
04:57 you can enforce it vis a vis each other or something like that.
05:00 Uh,
05:01 so,
05:01 the floor is yours,
05:02 Dario.
05:03 Um,
05:03 and,
05:04 uh,
05:04 you can,
05:05 uh,
05:05 start with 10 or 15 minutes and,
05:07 uh,
05:08 We'll go to Florence.
05:14 You see,
05:14 I never come to this.
05:19 OK.
05:19 Thanks very much.
05:20 Uh,
05:21 so,
05:22 um,
05:22 I will go over,
05:24 uh,
05:24 the evolution of knowledge in trade and international integration,
05:27 and then Florence will speak about how
05:31 trade data are actually useful to look at a range,
05:33 a wider range of issues.
05:36 Um,
05:37 So,
05:38 let's uh uh start with the reminder why it matters.
05:43 Uh,
05:43 we,
05:44 at this point have a large economic literature that
05:47 finds a sizable causal effect on trade and growth,
05:51 and this is a slide,
05:53 uh,
05:54 uh,
05:55 that shows the evolution of growth from 1945 to 2014.
06:00 Yet the public debate in recent years,
06:03 in the last several years have been,
06:05 has been focusing on
06:07 Some,
06:08 uh,
06:08 um,
06:09 of what are perceived the challenges that came with this growth.
06:13 And so the first challenge is about inequality,
06:16 which is,
06:17 uh,
06:17 distributed,
06:18 uh,
06:18 which,
06:19 which has been found across and within countries.
06:22 And so there is a large literature that
06:24 looks at various dimensions of this inequality,
06:27 but,
06:27 uh,
06:28 if we want to summarize the main points,
06:30 I would say that,
06:31 uh,
06:32 The,
06:32 the paper uh
06:34 by Nina Pasnik,
06:35 one of the discussants and the co-authors
06:38 that looks at the rising markups and profits of large multinationals is,
06:43 uh,
06:43 is uh,
06:44 one of the most important contributions.
06:47 We also note,
06:48 um,
06:48 from our world development report which was supported by the
06:52 KCP that supplier firms in developing countries are being squeezed.
06:57 Uh,
06:58 we,
06:58 uh,
06:59 we,
06:59 we know that there is evidence about a declining labor share within countries,
07:05 and this has been found both in developed and in developing countries.
07:09 Uh,
07:10 skilled workers get,
07:12 uh,
07:12 rewarded over and above unskilled workers.
07:16 Uh,
07:16 this is again,
07:17 uh,
07:17 work that,
07:18 uh,
07:19 indirectly benefit
07:20 benefitted from KCP funding
07:23 and uh women and youth are generally found in lower value-added segments of the,
07:29 of value chains of trade
07:31 and then there is the issue of raising tax revenues that has become more challenging
07:37 and in short,
07:38 it's harder to tax winners to compensate,
07:41 to compensate the losers.
07:43 In more In recent years,
07:45 uh,
07:45 there have been also growing worries about the trade externalities,
07:50 uh,
07:51 and in particular about the riskiness of the trade
07:55 with the,
07:56 the perception that there is an excessive dependence on
07:59 foreign suppliers and their ability to foreign shocks.
08:02 One of the most notable papers is the one mentioned here by Barrow and Sauvigna.
08:08 Uh,
08:08 there is,
08:09 uh,
08:09 the environment debate that has grown in importance
08:13 with the sense that trade might be contributing to
08:18 resource depletion in the form of unsustainable
08:21 production such as of tropical timber,
08:24 unsustainable shipping,
08:26 uh,
08:26 uh,
08:27 and,
08:28 uh,
08:28 more recently by undermining climate,
08:31 uh,
08:31 action at the national level.
08:33 And finally,
08:34 the,
08:34 the issue of rivalry,
08:36 uh,
08:37 where trade is increasingly seen as a zero-sum rather than a win-win.
08:41 So,
08:42 what we,
08:43 what happened in the past 20 years is that
08:48 These issues have increasingly been studied and in order to do that,
08:53 I would say that it has been a journey into opening up the box
08:58 of the one data point per country,
09:01 uh,
09:02 and,
09:03 and to look at the heterogeneity within that data point,
09:06 and that has happened at all dimensions of the trade equation,
09:10 which is the policies,
09:12 the firms,
09:13 and the incomes and the households.
09:15 Uh,
09:17 let me go shortly through these issues,
09:20 and I will highlight what I think it's important,
09:23 uh,
09:24 in particular,
09:25 uh,
09:25 going forward.
09:27 So,
09:28 let's start with policies.
09:30 So,
09:31 we tended to think in the past that the metrics of market access
09:35 was adequate to explain what was happening in trade policy and in fact,
09:39 for many years,
09:40 we haven't really been worrying so much about trade policy
09:43 because basically there was um
09:46 um a,
09:47 a,
09:48 a trend towards increasing liberalization which was largely unchallenged.
09:53 Uh,
09:54 but in,
09:54 in,
09:55 in,
09:55 uh,
09:56 the last decades,
09:57 we have seen,
09:59 uh,
09:59 we actually have seen,
10:00 um,
10:01 uh,
10:02 the inability of the multilateral trading system to broker certain
10:07 issues and hence the,
10:08 uh,
10:08 deep,
10:08 uh,
10:09 enhance the emergence of deep trade agreements.
10:12 So there have been policies that have become,
10:14 uh,
10:14 uh,
10:15 deeper,
10:16 um,
10:17 and more complex.
10:19 The deep trade agreements,
10:20 as I said,
10:21 is one dimension of that.
10:22 But that intersects with many other dimensions that
10:26 I will shortly mention in a moment.
10:28 But more recently,
10:29 we're also seeing that there are
10:31 uh policies that are not coming from the realm of trade but that impact trade.
10:37 And so this is the chart from um analysis we are conducting now
10:42 where we noticed that the trade-related Climate policies are on the rise,
10:47 and they are increasingly also targeting uh
10:50 uh trade objectives on top of the environmental objective.
10:54 And we see
10:56 a similar uh trend across other issues uh of the public concern such as security,
11:02 uh,
11:03 or industrial policy,
11:04 uh,
11:05 right now.
11:06 So,
11:07 the,
11:08 the way we are working,
11:10 I think this is a moment in which policies
11:12 really have to come back to the research agenda.
11:15 The way we tend to work on that is through a process where we,
11:19 uh,
11:20 we try to leverage the operational experience of the bank
11:23 and,
11:24 uh,
11:24 and,
11:25 uh,
11:25 mainly it's a process where
11:27 we take a rigorous,
11:29 uh,
11:29 approach to.
11:30 Research,
11:31 then we bring it to the operations and then we use the knowledge
11:34 from the operations to bring it back and refine the research questions.
11:38 The example of the work on the deep trade agreement of the bank,
11:42 it's,
11:42 I think,
11:42 uh,
11:43 uh,
11:44 uh,
11:44 a,
11:44 a,
11:44 a good example that we intend to follow in other areas going forward.
11:48 This gave rise to 23 working papers from the most notable uh policy.
11:54 Uh,
11:54 trade policy researchers,
11:57 um,
11:58 it created a database and a companion handbook which is widely cited in policy
12:05 and a,
12:05 a,
12:06 a range of,
12:07 of,
12:07 uh,
12:07 tools
12:08 that practitioners within the bank and in,
12:11 uh,
12:11 in,
12:11 uh,
12:12 in country administrations
12:14 can use to inform their policy.
12:17 Um,
12:19 how do,
12:20 what,
12:20 what do we need to do in this area?
12:22 I think that it's important to keep collecting,
12:25 uh,
12:26 data across all dimensions of policy that affect trade,
12:30 um,
12:31 and,
12:32 uh,
12:32 uh,
12:33 and to connect them with one another,
12:35 and these dimensions are many,
12:36 and we can discuss in the panel
12:38 which ones are more important and what really needs to be done.
12:42 Uh,
12:43 but this then can be used to actually re-ask old questions and,
12:48 uh,
12:48 to revisit old questions and ask new
12:51 questions,
12:51 and here there are some examples
12:53 which,
12:54 uh,
12:54 I'm not going to discuss in detail,
12:56 but basically,
12:57 uh,
12:58 the old question of whether policy,
13:00 uh,
13:01 Leads to more discriminatory practices
13:03 or helps navigating an uncertain environment
13:07 in light of new developments.
13:08 It's certainly one we need to re-ask.
13:11 And then new questions like
13:13 what will the global giants do
13:16 with this combination of tools they have in their hands.
13:20 Um,
13:21 we have a lot of research in firms.
13:23 The KCP supported the massive work on the exporter dynamic database.
13:28 This has been,
13:29 uh,
13:29 a,
13:30 a,
13:30 an,
13:30 uh,
13:30 an area that has been very prolific
13:33 across the world,
13:35 but basically 20 years ago,
13:36 we thought that all firms had the same production
13:39 function and input sourcing.
13:41 Patterns.
13:42 We now have a nuanced understanding of the
13:45 firm role in trade patterns and policy outcomes.
13:48 I think just looking at the difference of how
13:51 governments approach the COVID crisis compared to the global
13:55 crisis 10 years ago shows that we really learned
13:58 from firm heterogeneity.
14:00 Um.
14:02 And,
14:03 uh,
14:03 and as I said,
14:04 KCP has uh generously funded this work
14:08 which uh allowed us now
14:11 to know and to be able to quantify and to bring to policy the idea that exposed,
14:16 the firms exposed to trade perform better
14:19 in trade,
14:20 uh,
14:21 but also in,
14:21 uh,
14:22 in other,
14:23 um,
14:24 in other outcome variables.
14:26 Um.
14:29 The one example here that I want to mention
14:33 is how this type of work has also helped uh
14:36 um operationally in,
14:38 in,
14:39 in,
14:39 in,
14:39 in a range of areas.
14:41 So one notable paper is by uh my colleagues,
14:45 Bob Brickers and uh Ana Fernandez,
14:48 uh,
14:49 that looks at detecting collusion.
14:52 In Madagascar customs.
14:54 What they were able to do in collaboration with
14:57 uh operational staff of the World Bank was to
15:01 uh inform,
15:02 to use research to inform uh an experiment
15:06 um
15:07 er uh in,
15:08 uh,
15:09 in,
15:09 uh,
15:09 in uh the Madagascar custom,
15:12 an improvement in the way the custom uh
15:15 Uh,
15:16 declarations were handled which brought to an improvement in revenue comparable,
15:22 uh,
15:22 equal to 1% of GDP.
15:25 Uh,
15:25 this is,
15:26 um,
15:27 showing the,
15:28 the increase in revenue that is very steep clearly during the reform period
15:33 and what it's important to say is that it was really because KCP.
15:38 Uh,
15:39 was relatively,
15:41 uh,
15:41 liberal with what we could,
15:43 uh,
15:44 use the funds to do,
15:46 which we were basically able to take this high risk.
15:50 Experiment which actually uh pushed forward the,
15:54 the research.
15:55 It became uh
15:57 um uh
15:58 uh research published in one of the top journals but
16:01 also improved management practices in Madagascar and is being replicated
16:06 in many other high-risk environments,
16:08 Kenya.
16:09 ***,
16:10 Croatia.
16:11 So this active,
16:12 uh,
16:12 uh,
16:13 this relatively unbounded source of funding,
16:16 it's what allows these blue sky questions and then gives us the freedom to bring them
16:22 to the operations
16:23 and to actually
16:25 create innovative uh.
16:28 Um,
16:29 research supported,
16:31 uh,
16:32 operations.
16:33 And so,
16:34 here,
16:34 uh,
16:35 I would say that the main issue,
16:37 uh,
16:37 it's really to,
16:39 to understand how we need to,
16:41 uh,
16:42 yes,
16:43 how we need to,
16:44 uh,
16:44 uh,
16:45 to keep collecting data.
16:47 There is the country-specific examples and the point that I would
16:50 like to leave for the panel is to say that,
16:53 uh,
16:54 country-specific examples can only bring us,
16:56 uh,
16:57 To a certain point,
16:59 what we then need to do is collect the data with global
17:02 coverage and a lot of this data now are in private hands,
17:06 but Florence will speak a bit to that as well.
17:09 Um,
17:10 and,
17:10 uh,
17:11 and of course,
17:12 uh,
17:12 there are a number of issues we can do.
17:15 The last,
17:16 uh,
17:16 in my last minute,
17:18 what I want to do is to mention that we also have interesting work on inequality.
17:23 This is the household,
17:24 uh,
17:24 survey,
17:25 harmonized household survey project
17:28 which brought a lot of information about
17:31 how households at different income levels,
17:33 uh,
17:34 are.
17:34 Affected by trade,
17:35 positively and negatively,
17:37 there is a trade-off between expenditure
17:40 and income which determines that.
17:43 But what it's interesting is,
17:45 again,
17:45 uh,
17:46 a relatively flex flexible,
17:48 uh,
17:49 support by the KCP allowed us to do that
17:52 and it's,
17:52 uh,
17:53 allowing more recently to bring it to,
17:56 uh,
17:56 to new,
17:57 I don't know why it's,
17:58 uh,
17:58 OK.
18:00 OK.
18:01 2 new,
18:02 two new topics.
18:03 So,
18:04 uh,
18:04 we are,
18:05 uh,
18:06 we are,
18:06 uh,
18:06 able to use the basic modeling that was created for that
18:11 with modification to address the new shocks that we are seeing
18:16 such as the Russia-Ukraine war,
18:18 the COVID,
18:19 and more recent the climate shocks.
18:21 Thank you.
18:22 Uh,
18:22 let me stop it here and pass it to Florence.
18:29 Thank you so much,
18:29 Daria.
18:30 Um,
18:31 so I'm gonna jump into
18:33 a slightly,
18:34 sorry,
18:34 I'm gonna
18:35 skip through
18:36 this,
18:37 um,
18:37 into
18:38 an,
18:38 a really,
18:39 uh,
18:39 exciting area of the,
18:41 of the trade and,
18:42 and
18:43 tax agenda,
18:44 which works at this intersection of tax and trade.
18:46 And,
18:46 and so this is something that KCB has been really pioneering.
18:49 Um,
18:50 we'll see a lot of examples from
18:52 researchers who have been leveraging KCP financing,
18:54 uh,
18:55 to,
18:55 to Push,
18:56 uh,
18:57 research in this,
18:57 in this exciting areas.
18:59 So first I wanna start by saying,
19:00 and this is something that came through in Daria's presentation very clearly,
19:03 tax data is trade data.
19:05 Uh,
19:05 you know,
19:06 using data from customs has really helped,
19:08 uh,
19:08 trade economists understand trade flows.
19:10 So this is not
19:11 completely new,
19:12 right,
19:12 to use tax data.
19:13 It's just that in this presentation,
19:14 I'm gonna
19:15 showcase how using
19:17 subnational tax data,
19:19 um,
19:19 it can be very,
19:20 very prolific,
19:21 uh,
19:21 in the area of,
19:22 of trade.
19:23 And so,
19:24 KCP has
19:25 really,
19:26 you know,
19:26 one of the,
19:27 the examples from Daria's presentation is the ability to use KCP financing
19:31 to really
19:32 uh fuel this research partnership with
19:34 administrations such as the Madagascar Customs Administration
19:37 to really leverage
19:39 deep data on the administrative functions
19:42 to understand how far
19:43 Firms and the state interact.
19:45 Um,
19:46 this is really,
19:47 uh,
19:47 a promising avenue for policy impactful research because as I'll describe,
19:51 if we're not really in the depth of the state of the,
19:54 of the administration,
19:56 we can do all the research we want,
19:57 uh,
19:57 we may not get the best data and we may not have any policy impact.
20:01 So this is something that,
20:02 uh,
20:02 I'll showcase a bit.
20:03 So why is it exciting to work on tax data these days?
20:07 Uh,
20:07 well,
20:07 there's been an explosion of,
20:09 uh,
20:09 fiscal devices that,
20:11 uh,
20:11 sort of outline a lot of the transactions that happen in the formal economy.
20:15 So these transactions
20:17 through VAT,
20:18 uh,
20:18 type of arrangements with the tax administrations are documented,
20:22 document,
20:23 uh,
20:23 firm to firm interactions.
20:25 So that allows us to then
20:26 Map out a whole sector,
20:28 uh,
20:29 of interaction,
20:29 a whole sectoral network,
20:31 uh,
20:31 of trade interactions,
20:33 uh,
20:33 and,
20:34 and you can go down to the specific product line,
20:37 uh,
20:37 as we did with KCP financing,
20:39 studying the,
20:39 the production of essential goods such as masks during the COVID crisis.
20:43 You can really start looking at,
20:45 at very,
20:46 uh,
20:46 fine level data
20:48 on,
20:48 uh,
20:48 on what products are traded.
20:50 And then you can relate this back to the whole formal economy,
20:53 of course,
20:54 uh,
20:54 which is gonna be basically
20:55 the,
20:55 the crux of the presentation is to say,
20:57 you know,
20:57 these microdata are essential in understanding
20:59 partial equilibrium effect of policies,
21:02 but then being able to relate them back to the macro picture
21:05 to really say something a bit more general about,
21:07 you know,
21:07 are these tax policies that we want to study good or bad for the economy,
21:11 essentially.
21:12 And so I'm gonna
21:14 like Daria split this across three areas of work.
21:17 Uh,
21:17 these are not,
21:18 you know,
21:18 happening in a vacuum,
21:19 so they are sort of connected
21:21 across.
21:22 I'm gonna start with fiscal space.
21:23 So I think,
21:24 uh,
21:24 why are these data crucial,
21:26 crucial in studying,
21:27 uh,
21:27 the issue of fiscal space?
21:28 Of course,
21:29 they relate to tax,
21:30 uh,
21:30 the IMF,
21:31 the bank,
21:31 we have to think about fiscal space,
21:33 and,
21:33 and the tax administration is,
21:35 uh,
21:35 you know,
21:35 an administration we work with at the macro level.
21:37 Um,
21:38 but I think what we were
21:39 Able to do with this really granular data,
21:41 and again,
21:42 this is research financed by KCP
21:44 was to pull together
21:46 a database
21:47 of uh from various tax administrations that was fairly granular,
21:51 fairly real-time,
21:52 that really informed uh COVID-19 fiscal policy response.
21:56 And so,
21:57 uh,
21:57 in the case of this paper by uh some of our colleagues,
22:00 they were able to quantify the impact of the COVID-19 shock
22:04 on payroll losses.
22:07 Taxes are typically regressive and so in the term,
22:09 when there's a time of a shock,
22:11 uh,
22:11 this can really,
22:12 uh,
22:12 be a fiscal burden,
22:13 uh,
22:13 sorry,
22:14 a tax burden on the farms.
22:15 And then the question was,
22:17 how much of a wage subsidy do you need to put forward
22:20 to remedy these,
22:21 uh,
22:21 these payroll losses.
22:22 And so
22:23 with this data,
22:24 with this real
22:24 Time,
22:25 really rich data,
22:25 our colleagues were able to,
22:27 to inform sort of
22:28 how to maximize the impact of this type of wage subsidies.
22:32 Uh,
22:32 so,
22:32 you know,
22:33 of course,
22:33 that's costly fiscally,
22:34 but it's,
22:35 you know,
22:35 we were able to make it more effective,
22:37 more efficient by having very detailed,
22:39 uh,
22:39 data
22:40 on,
22:40 on this type of,
22:41 uh,
22:42 of losses.
22:43 Similarly,
22:43 in Rwanda,
22:44 we were able to,
22:45 again,
22:45 you know,
22:46 think about GDP,
22:47 uh,
22:47 figures,
22:48 they don't come in all the time.
22:49 So when there's a big crisis,
22:50 there's a moment of big decision making,
22:52 you may not have new data the day you need to make a call on a certain tax policy.
22:57 And this was very real during the COVID shock when,
23:00 you know,
23:00 certain industries were more affected by the shock than others.
23:03 Clearly compact industries were more affected,
23:05 and,
23:05 uh,
23:06 tax administrations had to make really fast decisions about,
23:09 you know,
23:10 what are the,
23:10 the tax breaks that they are giving to.
23:12 Boom
23:12 and how to manage the fiscal space.
23:13 So having this real-time data
23:15 that
23:16 really correlates very well with GDP figures in the aggregate
23:19 were really crucial in making this this decision.
23:22 Again,
23:22 this is something that KCP financed,
23:24 uh,
23:25 the,
23:25 the financing helped us put up dashboards for real-time policymaking,
23:29 so we didn't always have to be in Rwanda,
23:31 uh,
23:31 you know,
23:31 working with the data and being helpful.
23:33 We generated dashboards that the administration could really access and,
23:37 uh,
23:38 and,
23:38 you know,
23:38 have time series that helped them make better policies.
23:42 Then turning to state capacity,
23:43 which is of course connected to fiscal space,
23:45 you know,
23:45 one of the,
23:46 the things that uh the tax agenda really is about,
23:49 is about
23:50 documenting,
23:51 you know,
23:51 transactions that the firm,
23:53 that firms make to increase
23:54 sort of the,
23:55 the tax,
23:56 uh,
23:56 the fiscal,
23:57 um,
23:58 uh,
23:58 how do you say that,
23:59 asset fiscal,
24:00 the broaden the,
24:01 the tax base.
24:02 Um,
24:03 and,
24:03 and so,
24:04 You know,
24:05 this is,
24:05 this is important.
24:06 Uh,
24:07 if you can't document
24:08 how the revenues,
24:09 how firms' revenues are shaped,
24:11 you can't really tax it.
24:13 Uh,
24:13 I want to really show that
24:15 this is not just about tax administration,
24:17 right,
24:18 policies.
24:18 It's also about other policies.
24:20 So when we do policies that affect firms' performance,
24:23 such as,
24:23 you know,
24:24 in this case,
24:24 the speed of justice of commercial justice in Senegal,
24:27 we speed up,
24:28 uh,
24:28 something that should
24:29 should have an impact on firms
24:31 and
24:32 bringing state capacity up to the level where they can say,
24:35 when I reduce
24:36 uh pre-trial time by 30%,
24:38 what is the impact,
24:39 what is the what is the impact on firms is
24:41 really powerful because now you can say as a state,
24:44 you know,
24:44 I put in this reform.
24:46 I reduced,
24:47 uh,
24:47 the,
24:48 I increased farm revenues by 3 to 5% on average,
24:52 and this is gonna affect my fiscal space.
24:54 This is gonna,
24:54 this is a really,
24:55 this is a policy that's gonna pay for itself.
24:57 So this is the type of,
24:58 of tax capa of,
24:59 uh,
25:00 sorry,
25:00 state capacity that you can put,
25:02 uh,
25:02 that You could put in,
25:03 uh,
25:03 in motion and this is again something that KCP
25:06 as Daria said with being a very flexible instrument allowed us to work
25:10 with,
25:11 uh,
25:11 justice system
25:12 and then also collect data,
25:14 uh,
25:15 from tax administration to make that link between this reform and,
25:18 and farm revenues.
25:20 Now,
25:20 there's a lot of heterogeneity.
25:22 I think heterogeneity is the word of the presentation,
25:24 uh,
25:25 in firm's relationship to the state,
25:27 uh,
25:27 similarly,
25:28 that we have,
25:28 you know,
25:29 heterogene in the production function.
25:31 This means,
25:32 uh,
25:32 firms are gonna
25:33 interact with the state very differentially,
25:36 uh,
25:36 according to certain characteristics,
25:38 and
25:38 I think this is an agenda that KCP has really financed,
25:41 uh,
25:41 having this granular data,
25:43 uh,
25:43 from tax administration has been key
25:45 in showing that,
25:46 for example,
25:46 firm size predicts an effective tax rate.
25:49 That's really important when we design,
25:50 uh,
25:51 tax policies.
25:51 We don't want it to be too regressive,
25:53 uh,
25:53 and that's gonna be key
25:55 to,
25:55 to designing these tax policies.
25:56 Um,
25:58 some of our colleagues have shown that
26:00 political connections can really affect,
26:02 uh,
26:03 the,
26:03 the propensity to evade,
26:04 uh,
26:05 tax.
26:05 That's key again.
26:06 I mean,
26:06 this is something that tax administrations have to think about every day
26:09 and being able to document this and to say,
26:11 OK,
26:12 if political connections are coming in the way of my tax base,
26:16 what can I do,
26:17 right?
26:17 Um.
26:18 So that's,
26:19 that's really powerful findings.
26:20 And then similarly,
26:21 when we think about migration,
26:23 we can think about a tax rate
26:24 that makes skilled labor return.
26:26 That's again,
26:27 uh,
26:27 a KCP finance research.
26:29 Now,
26:30 this e-fiscal devices are really powerful
26:33 in terms of building capacity
26:34 in the sense that they can increase
26:36 just the tax base,
26:37 right?
26:37 So the question,
26:38 the big question in the room is,
26:39 OK,
26:40 you have e-filing,
26:41 what does it mean for the tax base?
26:42 And our colleagues in Tajikistan
26:44 were able to show,
26:45 and this is a really excellent paper,
26:47 that
26:48 by putting in place an e-filing system,
26:50 by increasing tax capacity uh state capacity that way,
26:53 they were able to close the evasion gap between firms that have.
26:57 propensity and low propensity to evade,
26:59 and this is a really uh,
27:01 important,
27:01 uh,
27:02 important finding in this,
27:03 in this literature,
27:04 um,
27:04 and it really,
27:06 you know,
27:06 showcased the fact that this type of work might
27:08 be even more important in low capacity environments.
27:11 So oftentimes we hear from donors,
27:12 oh,
27:13 but these are very low capacity environments and
27:15 you're going in with these really fancy things.
27:17 Well,
27:17 actually,
27:17 these fancy things could be really good substitutes
27:19 for a lack of capacity,
27:21 uh,
27:21 of the government
27:22 as shown in this uh particular research.
27:24 So again,
27:25 partnerships are really the cornerstone of this type of research.
27:28 We really need to have
27:29 deep collaborations,
27:31 uh,
27:31 building capacity,
27:32 uh,
27:32 having agreed work plan with the administration so that when the findings come,
27:36 they're not a surprise to the Ministry of Finance.
27:38 They're not a surprise to these organs,
27:39 uh,
27:40 that,
27:40 you know,
27:40 are pretty top down.
27:41 And so if you come in with,
27:43 oh,
27:43 we find that this tax is.
27:44 Really,
27:44 you know,
27:45 great for this and that,
27:46 uh,
27:46 and it wasn't on their work plan,
27:47 they're not gonna take it well.
27:49 Uh,
27:49 they're gonna be worried about tax secure data security and trust.
27:53 So this is really something that,
27:54 uh,
27:54 KCP has financed that,
27:56 uh,
27:56 we really encourage continuing
27:58 financing.
27:59 This is just a breakdown of how this relationship works,
28:01 but in the interest of time,
28:03 I'll leave it in the slides.
28:04 So how does that affect the firm's agenda and our
28:06 colleagues are gonna talk about this in the next session.
28:08 Uh,
28:09 so,
28:09 one of the,
28:10 the great,
28:10 uh,
28:11 work that KCP has financed is trying to understand formalization.
28:14 This,
28:14 of course,
28:15 relates to state capacity,
28:16 is how much,
28:17 uh,
28:17 can I tax firm?
28:19 Uh,
28:19 that's not gonna happen unless they're formalized.
28:21 Um,
28:22 now,
28:22 we know from previous research from,
28:24 uh,
28:24 our colleague here.
28:25 David,
28:25 that,
28:26 uh,
28:26 you know,
28:27 future taxation is basically the concern,
28:29 right?
28:29 I become formal,
28:30 suddenly you can tax me.
28:31 That's basically,
28:32 if I'm,
28:32 if I don't have this incentive
28:34 to,
28:34 to formalize,
28:35 I'm not gonna do it,
28:36 uh,
28:37 unless,
28:37 you know,
28:37 you do something really drastic.
28:39 And so,
28:40 in,
28:40 in some follow-up research,
28:41 what they were able to find is that
28:43 um when we give a strong incentive to formalize,
28:46 the firms that are gonna come forward are those that are formal like.
28:50 Those that are not behaving like formal firms are not necessarily gonna
28:53 come forward and,
28:54 and,
28:54 you know,
28:55 comply with the,
28:55 the formalization push.
28:57 So the bottom line from this research agenda is that formalization is really hard,
29:00 uh,
29:01 and,
29:01 uh,
29:02 tax registration status,
29:03 you know,
29:04 interacts with,
29:05 uh,
29:05 production networks in some ways,
29:07 uh,
29:07 but we don't know.
29:08 Exactly why,
29:09 how?
29:09 And so this data,
29:11 this tax data that really document these exchanges between
29:14 firms can really be crucial in understanding these dynamics,
29:16 right?
29:16 So this is work we're doing in Rwanda,
29:18 uh,
29:19 with some colleagues.
29:19 One of them is in the room,
29:20 Lucas,
29:21 where we're trying to understand
29:23 how tax,
29:24 uh,
29:24 sorry,
29:24 how trade networks are gonna
29:27 Shape those incentives to formalize and this is done through
29:30 the use of these e-billing machines uh in the case of Rwanda where 73%
29:36 of your receipts that you claim in a VAT declaration have to be,
29:40 have to come from a from an ebiing machine.
29:44 So that means that 73% of your inputs,
29:46 if you want them to be
29:48 uh tax deductible,
29:49 need to come
29:50 from a formalized business,
29:52 basically.
29:53 So what this means is if I'm a big firm and I'm,
29:56 you know,
29:56 having a lot of interactions with informal businesses,
29:59 I might not be able to claim all of my input expenditures.
30:02 And so I might actually have an incentive
30:05 to push that
30:06 uh formalization,
30:07 uh,
30:08 you know,
30:09 incentive to that small firm I'm,
30:11 I'm contracting with.
30:12 So we're using that,
30:12 what we're finding from this,
30:14 this exposure to,
30:15 to formal firms
30:16 is increasing.
30:17 Everything
30:18 on average,
30:19 uh,
30:20 formalization by 6% per year.
30:22 Uh,
30:22 so,
30:22 you know,
30:22 I'm not going to go into details,
30:23 but essentially,
30:24 is this good or bad,
30:25 right?
30:26 Is this good that 6% of firms start formalizing,
30:30 or is this bad for the economy?
30:31 The question is not obvious,
30:32 right?
30:32 The answer is not obvious.
30:33 And so for this,
30:34 we're going to use macro models
30:36 that are going to be able to pin down a trade-off between this formalization
30:40 and And this trade impact.
30:42 So if you know,
30:43 too much,
30:44 a target of 73% may be too high.
30:47 Maybe we want to go down to 50% to,
30:49 you know,
30:49 avoid shutting down businesses that are really crucial for the economy,
30:52 but at the same time encourage,
30:54 encourage formalization at a margin that's,
30:56 uh,
30:56 that's good for the economy.
30:57 So that's kind of,
30:58 uh,
30:58 the kind of work that I think is very exciting.
31:00 Uh,
31:01 and then,
31:01 you know,
31:01 moving forward,
31:02 there's a lot of exciting work that KCP has started.
31:04 To finance and can keep financing
31:06 uh on regional integration,
31:08 um,
31:09 particularly the geography of production networks.
31:11 I think
31:12 it's really nice to have RCT results,
31:14 for example,
31:15 working with traders,
31:16 working with truckers,
31:17 but then being able to relate it back to the big picture
31:20 and what does it mean when we,
31:21 you know,
31:22 reduce trade frictions,
31:23 what does it mean
31:24 at the local level,
31:25 and how does it scale,
31:26 uh,
31:27 at the,
31:27 at the economic level.
31:29 So this is it.
31:29 I think KCP is really uniquely placed,
31:31 uh,
31:31 to enable the,
31:32 the future of tax and trade research,
31:34 uh,
31:34 by creating this integrated approach,
31:36 uh,
31:37 to knowledge creation that combines this administrative data,
31:40 uh,
31:41 on micro responses to,
31:43 uh,
31:43 more aggregate,
31:44 uh,
31:44 measures and micro implications.
31:46 That's really,
31:46 uh,
31:47 where we wanna go.
31:48 Um,
31:48 the deep engagement with the government.
31:50 partners is gonna be key here,
31:51 so we need to finance that,
31:52 otherwise we're
31:53 not gonna make progress,
31:54 uh,
31:55 and,
31:55 uh,
31:56 and we can really think about this as,
31:58 you know,
31:58 public goods,
31:59 uh,
32:00 value that,
32:01 uh,
32:01 is gonna not be just used for one topic,
32:03 but really,
32:04 uh,
32:05 have,
32:05 uh,
32:05 have importance,
32:06 uh,
32:07 maybe for the global tax,
32:08 uh,
32:08 tax agenda.
32:09 So that's kind of exciting.
32:11 Is it?
32:13 Thank you.
32:14 Thanks very much,
32:15 Darian Fran,
32:16 uh,
32:16 for these great presentations.
32:17 I mean,
32:18 I really like the way that you sort of move
32:19 seamlessly from international trade to domestic trade and sort of from
32:22 firms to countries,
32:24 um,
32:24 which I think really shows the,
32:25 the scope of the research that,
32:27 um,
32:27 KCP has
32:29 Um,
32:29 has funded,
32:30 um,
32:31 uh,
32:31 in,
32:31 in these areas.
32:32 So we have 4 great,
32:34 um,
32:34 panelists lined up.
32:35 Uh,
32:36 what I'll do just in the interest of time is introduce
32:38 all 4 of our panelists who are joining us virtually,
32:41 um,
32:41 at,
32:42 at once,
32:42 and then we'll just move from one to the,
32:44 one to the next.
32:46 So,
32:46 um,
32:47 uh,
32:47 in order,
32:48 we'll,
32:48 uh,
32:48 start with Lionel Fontaine,
32:50 who is an advisor to the Directorate
32:52 for Economic Affairs and International Cooperation at the
32:55 Bank of France and also also a professor at the Paris School of Economics.
32:59 Um,
33:00 Lionel will be followed by Ralph Ossa,
33:02 who is the chief economist and director of Economic
33:04 Research and statistics at the World Trade Organization.
33:08 Uh,
33:08 then we'll go to Nina Putnik,
33:09 who is a,
33:10 uh,
33:11 professor,
33:11 who is the,
33:12 sorry,
33:12 I get the whole title right,
33:13 the Niehaus Family Professor in International Studies
33:16 at Dartmouth.
33:17 And then we'll wrap up with uh Yasuyuki Toto,
33:21 um,
33:21 who is professor of Economics at Waseda University in Japan.
33:25 Sorry,
33:25 Yasuyuki,
33:26 you're coming last even though the time difference is probably the hardest for you.
33:30 So,
33:30 stay with us.
33:31 Um,
33:32 I'd like to ask each of the panelists to try to keep your remarks to Sort of,
33:35 uh,
33:36 somewhere in the like 6 to 7 minute range.
33:38 Um,
33:39 maybe I can ask Karina to shoot a reminder,
33:41 um,
33:42 chat to each of the panelists when you're
33:44 kind of running out of time.
33:45 And if you go way past that,
33:46 then I'll have to very rudely interrupt you.
33:48 Um,
33:49 but that way,
33:49 if we keep these introductory,
33:51 um,
33:52 uh,
33:53 remarks from the panelists short,
33:54 we'll have a little bit more time for discussion afterwards.
33:57 So,
33:57 with that,
33:58 um,
33:58 over to you,
33:59 Lionel,
33:59 you're up first.
34:02 OK.
34:03 Thank you for having me.
34:05 Uh,
34:07 so this,
34:07 this is really a great pleasure to participate in this panel.
34:11 So,
34:11 uh,
34:12 Daria and Florence have presented a very,
34:15 uh,
34:16 impressive,
34:17 uh,
34:17 research,
34:18 uh,
34:18 agenda.
34:20 Uh,
34:20 so I have 7 to,
34:22 you said 8 initially,
34:23 but now,
34:24 it went to 7 minutes,
34:26 uh,
34:27 to,
34:28 uh,
34:28 give my
34:29 Views on how knowledge has evolved over the last two decades in the field,
34:34 what have been the breakthrough,
34:35 uh,
34:36 to this uh research agenda,
34:39 and,
34:39 uh,
34:40 just also I kind of look forward to looking at for sure.
34:43 This is very short,
34:44 and I will try to,
34:46 to give some,
34:46 uh,
34:47 very,
34:47 uh,
34:47 you know,
34:48 simple ideas
34:49 to,
34:49 to make my point.
34:50 So my take,
34:51 uh,
34:52 when I consider what has been done over the last two decades.
34:56 Uh,
34:56 is that we have basically learned,
34:59 uh,
34:59 three things.
35:00 One is that trade
35:02 is really first about new sourcing opportunities for firms,
35:06 for
35:07 households,
35:08 for,
35:08 you know,
35:08 countries in general.
35:10 So,
35:10 this is conducive to changes in relative prices.
35:13 So this is,
35:14 you know,
35:14 a source of uh additional purchasing power for,
35:17 for,
35:17 for,
35:18 for households.
35:19 And this is also uh
35:22 A way of increasing the variety of consumer goods,
35:25 of increasing the variety of intermediate goods that are,
35:28 you know,
35:28 sourced by,
35:29 by firms,
35:29 and this is leading to,
35:30 to productivity.
35:31 This has been documented extensively.
35:34 So now,
35:36 uh,
35:36 the,
35:37 the second thing that we have learned is that this is also
35:40 A way of diffusing the knowledge,
35:42 diffusing technologies worldwide.
35:45 And so this is something that has been very
35:46 important for the development path of many developing emerging economies
35:51 and so it has been conducive to uh technological catch-up for,
35:55 for certain economies.
35:57 So,
35:57 this is for the good side
35:59 of the story.
36:00 Now,
36:00 uh,
36:00 on the dark side of it,
36:02 uh,
36:02 uh,
36:02 and it has been mentioned briefly by Daria,
36:05 this is also conducive,
36:06 conducive to a polarization of our economies
36:09 and of developing economies.
36:11 Why so?
36:12 Uh,
36:13 what we have is
36:15 Rising inequalities of primary income,
36:18 which does not mean rising inequalities of
36:20 income because we have also a distribution,
36:22 but at least
36:23 rising inequalities of primary income.
36:25 rising inequalities in terms of individual opportunities.
36:30 And more importantly,
36:32 uh,
36:32 within countries,
36:33 all this uh accumulates with,
36:35 you know,
36:36 rising spatial inequalities,
36:38 rising urban concentration.
36:40 And so what we know from this literature over the last
36:42 two decades is that there are winners and there are losers,
36:45 and that we can spot them very easily.
36:48 are geographically concentrated.
36:50 And so this is really about,
36:52 you know,
36:52 where you are located,
36:54 which firm you are,
36:55 uh,
36:55 you know,
36:56 employed with,
36:57 where are you living,
36:58 and what are the,
36:59 the,
36:59 the,
36:59 the opportunities that you have given your education and the rest.
37:02 So all this has been perfectly documented.
37:04 And so,
37:05 on this,
37:05 I think that what has been presented by
37:08 Daria and Fran is really a fascinating research agenda.
37:12 So now
37:14 Uh,
37:16 Why it matters,
37:17 this agenda.
37:18 It matters because
37:21 He is shaping the,
37:22 the,
37:22 the private sector.
37:24 And so this is where it connects maybe with the next session.
37:26 So,
37:27 from the empiric uh side,
37:29 so what we have been learning from the,
37:31 learning from the uh empirical studies
37:33 is that,
37:34 you know,
37:34 businesses are heterogeneous,
37:36 to put it in a nutshell.
37:38 And so this has been facilitated,
37:40 uh,
37:40 by,
37:41 uh,
37:41 you know,
37:42 an increasing availability of microdata and it's good to,
37:46 to,
37:46 to support,
37:47 uh,
37:47 this point in the,
37:48 in the presentation.
37:49 Uh,
37:50 it has been said,
37:51 so we have the exporter dynamics database of the,
37:54 the,
37:54 the World Bank.
37:55 In France,
37:56 we,
37:56 we have launched something which is really amazing,
37:59 which is an open data room so you can access any,
38:03 uh,
38:03 you know,
38:03 administrative data.
38:05 You know,
38:05 comfortably from your,
38:06 uh,
38:07 office
38:08 when you are accredited.
38:09 So this is really uh something totally new.
38:12 In Europe,
38:12 we have had the Compett network that has,
38:15 you know,
38:15 produced some,
38:16 uh,
38:16 you know,
38:16 uh,
38:17 firm-level data that is uh comparable across countries.
38:21 So we have the surveys that are conducted by,
38:23 by the World Bank
38:24 and we have the,
38:25 the,
38:26 the LBD of the US Census Bureau,
38:28 and many more initiatives.
38:30 So all this has been really,
38:31 uh,
38:32 you know,
38:33 an important agreement into uh
38:35 understanding how,
38:37 you know,
38:37 the private sector is shaped
38:39 by,
38:39 uh,
38:40 by trade.
38:40 By international integration.
38:42 And so on the theory side,
38:44 so we basically have this
38:46 idea that uh we have an Epi few
38:50 uh series of businesses.
38:52 So the,
38:52 the,
38:53 this uh word has been uh coined by Thierry Meyer and G Marco Itavieno,
38:58 but
38:58 it's still there.
38:59 This is really about Epie.
39:01 And so,
39:02 we have this concentration of exports and exporters.
39:05 They are multi uh product and they invest also abroad.
39:08 And recently,
39:09 what we have had is this evidence of B2B networks.
39:13 And so,
39:14 networks are important because they are,
39:16 you know,
39:17 the way
39:18 productivity gains are diffused,
39:20 uh,
39:20 uh,
39:20 across firms and also whether uh how shocks
39:24 are diffused across firms,
39:25 and this is something that has been so important in the recent period.
39:29 So now,
39:31 What I take from uh all these,
39:33 uh,
39:34 so what,
39:34 what the frontier is now,
39:36 so there are many frontiers in the field,
39:38 but one which is important is the relationship
39:41 between the micro evidence and the macro,
39:43 uh,
39:44 evidence,
39:44 which is important for,
39:45 for policymakers as well.
39:47 So what we knew,
39:49 uh,
39:49 until recently is that we have to look from the micro to macro and know,
39:54 what we know is that we also have to look from the macro to micro.
39:57 So I will explain this in,
39:59 in a second.
40:00 Uh,
40:00 so,
40:01 let's start with this idea of granularity of the economy.
40:04 So,
40:05 what we call granularity in the macro literature,
40:07 which is more about the fact that,
40:08 you know,
40:09 firms are big,
40:10 certain,
40:11 uh,
40:11 handful of firms are,
40:12 are very big and so
40:14 these big firms are actually impacting the,
40:17 the,
40:17 the macro,
40:17 uh,
40:18 outcomes.
40:19 Uh,
40:19 so,
40:20 this is a literature that goes from the micro to macro.
40:23 So the idea is that individual
40:25 firm performance is shaping comparative advantages,
40:27 for instance,
40:28 when it comes to trade.
40:29 It's also that when there are shocks
40:32 to individual firms like idiosyncratic sharks,
40:35 they do not wash out in the aggregate because some firms are very big.
40:39 And so this is something that is driving the macro outcome.
40:42 And so,
40:43 this is also driving the international transmission of sharks through M&Es.
40:48 And last but not least,
40:49 this is something that we can use to explain.
40:52 would contribute to explaining the business cycles.
40:54 So this is one part of the story.
40:56 Now,
40:56 the other part of the story is that we have to go from the macro to micro.
41:00 What we have recently realized
41:02 during the GFC,
41:03 during the COVID crisis,
41:05 during the energy crisis in Europe.
41:07 Is that,
41:08 you know,
41:09 the big guys,
41:10 the big businesses
41:11 may also react differently to common shocks.
41:14 And so this is different from the micro to macro.
41:16 This is really that they are hit
41:18 by a common shock
41:19 and they're going to react differently to a common shock.
41:22 And so this adjustment of big players
41:24 may dampen or may worsen the consequences of the shock.
41:28 And so why so?
41:29 Because these big firms are involved in GVCs.
41:32 And also because they might react differently to a demand shock.
41:36 And so,
41:37 I think that this is something that is really
41:39 uh
41:40 brand new in the,
41:41 in this literature and that has to be considered seriously.
41:44 So what are the implications of all what I said
41:47 for the research agenda in the last minute that I have?
41:50 So,
41:51 first of all,
41:51 I think we are in a critical moment.
41:54 Critical moment,
41:55 why?
41:55 Just because we have this database,
41:57 this micro database that,
41:58 that,
41:58 that I was just mentioning,
42:00 we have also new analytical tools.
42:03 So just,
42:03 you know,
42:04 to,
42:04 to speak of some of them,
42:06 so,
42:06 about networks,
42:08 about granular and instrumental variables,
42:10 about machine learning,
42:11 etc.
42:11 etc.
42:11 etc.
42:13 So we have all these and we have a more uncertain business
42:16 environment to be considered and we are also a new policy agenda.
42:20 So the new policy agenda
42:22 is,
42:23 you know,
42:23 policies that
42:25 are
42:25 kind of safety belts,
42:27 for the economy
42:28 with more supervision,
42:29 more emergency funds,
42:31 a new
42:31 way of producing industrial policies.
42:34 So industrial policy is becoming more vertical,
42:37 so we have massive subsidies everywhere.
42:39 We have tax exemptions everywhere.
42:42 And so,
42:42 this is a critical moment and we have critical objects
42:45 that we want to shed light on as economists.
42:48 One is how we,
42:50 do we go from the micro evidence to the macro evidence,
42:53 and this is how
42:54 we can,
42:55 you know,
42:55 get to aggregate elasticities that we use in our models.
42:59 So this is one.
42:59 Question.
43:00 Another question is much more about
43:02 developing economies or about emerging economies,
43:05 businesses.
43:06 So if we have massive subsidies everywhere,
43:09 so it's not certain that these economies will be
43:11 in a position to subsidize their own firms,
43:14 and this is a competition issue that will arise very soon.
43:17 And last but not least,
43:20 uh,
43:21 DRP few that I was mentioning before are very
43:24 exposed.
43:24 So they are exposed to shock of the new type
43:27 which relate to corporate social responsibility,
43:30 to environmental shocks,
43:31 etc.
43:32 just because they are big.
43:33 And so I think that shedding light on this and shedding light on how firms
43:38 will adjust to this new environment is something that really uh is needed.
43:43 And with this,
43:43 I thank you.
43:47 Thanks very much,
43:48 Lionel.
43:48 Let's go over to Ralph.
43:57 Let me just share my screen.
44:08 I hope you can see that because I can't see you guys uh
44:11 anymore.
44:12 So please do complain if,
44:13 uh,
44:14 if you can't see me or hear me or uh or the presentation.
44:17 So first of all,
44:18 uh,
44:18 thank you very much to,
44:19 uh,
44:20 to the organizers for inviting me to this,
44:22 uh,
44:23 to the session and to provide
44:25 my perspective on the uh importance of research on international trade and also the
44:30 perspective of the,
44:31 um,
44:32 WTO.
44:33 So,
44:34 um,
44:34 in my
44:35 5 to
44:36 8 minutes or 5 to 7 minutes,
44:38 um,
44:38 you know,
44:39 I just have
44:40 kind of one slide with,
44:41 uh,
44:41 4
44:42 main messages,
44:43 uh,
44:44 to you,
44:45 uh,
44:45 and,
44:45 uh,
44:46 the first,
44:46 uh,
44:47 Ralph,
44:47 uh,
44:47 sorry,
44:48 I just want to let you know we haven't quite got your slides up yet.
44:50 I'm not sure if it's
44:53 something.
44:54 OK.
44:55 You know what?
44:55 Let me just,
44:56 uh,
44:58 Maybe it's,
44:59 maybe it's we've got it now.
45:01 Yeah.
45:01 Oh,
45:01 so,
45:01 but now I just click.
45:04 No,
45:04 you can make a full screen.
45:06 And,
45:08 uh,
45:09 if you can hear me,
45:10 then
45:11 I'm just going to stay cause it just said
45:13 the zoom quit unexpectedly.
45:16 We can hear you and see you still.
45:18 OK,
45:18 so you know what,
45:19 let me just uh go ahead without slides.
45:22 Thanks,
45:23 Ralph.
45:40 Ralph,
45:40 we
45:41 seem to have lost you.
45:45 OK,
45:45 it looks like,
45:46 uh,
45:46 it looks like I'm back.
45:48 Uh,
45:48 there seems to be some issue with,
45:49 uh,
45:50 with our Zoom.
45:51 So if we're speaking of,
45:52 uh,
45:52 research funding,
45:53 that seems like something that we could need,
45:55 uh,
45:55 for some
45:56 better Zoom connection.
45:57 But let me just not um.
46:00 You're good.
46:02 Perfect.
46:02 Let me just not,
46:03 uh,
46:03 mess with,
46:04 uh,
46:04 with the system and,
46:05 and just go ahead without,
46:07 uh,
46:07 without slides because really,
46:08 I just needed the slides for my own,
46:10 uh,
46:10 for my own orientation.
46:12 But,
46:12 you know,
46:12 basically,
46:13 I have 4 main messages for you today.
46:15 And the,
46:16 the first message really is that globalization is in a,
46:20 a deep crisis,
46:21 even though the situation is quite a bit
46:23 more nuanced than the deglobalization headlines suggest.
46:27 And this is exactly why we need to search.
46:28 So that's uh
46:29 kind of going to be the point.
46:31 And,
46:31 and given that I,
46:32 you know,
46:32 already used 2 minutes here on,
46:34 um,
46:35 on trying to get the Zoom working,
46:36 let me
46:37 be very quick on this because I think most of us know uh what I'm talking about.
46:42 The only
46:42 Kind of,
46:43 uh,
46:43 uh,
46:44 twist,
46:44 uh,
46:44 I would like to add is that really when I
46:46 think about the globalization crisis that we are in,
46:49 really I'm thinking about three different layers and,
46:51 and,
46:51 and the crisis,
46:52 if you will,
46:52 has progressed
46:54 to different degrees and in all these layers.
46:56 And,
46:56 and the first layer is just what has happened with the,
46:58 with the narrative.
46:59 I think that we see the
47:01 biggest change.
47:03 So economic interdependence is now seen as a problem,
47:06 uh,
47:06 even though it used to be kind of guiding principle
47:09 of economic integration for,
47:11 uh,
47:11 many decades.
47:12 Uh,
47:12 this changing narrative,
47:14 I think,
47:14 has had some,
47:15 uh,
47:15 impacts already on,
47:17 on trade policy,
47:18 uh,
47:19 making,
47:19 so the elephant in the room is,
47:21 of course,
47:21 the trade conflict between China and the United States.
47:24 Um,
47:24 but there are many other issues,
47:25 uh,
47:26 um,
47:26 uh,
47:27 proliferation of,
47:28 uh,
47:29 industrial policies,
47:30 uh,
47:30 uh,
47:30 export restrictions,
47:32 and so on.
47:33 And then the third layer is,
47:34 uh,
47:34 is,
47:35 is what it has,
47:35 where we see,
47:36 uh,
47:37 uh,
47:37 the,
47:37 the least impact so far,
47:39 which is that these kind of policy changes,
47:41 at least so far,
47:42 haven't really,
47:43 um,
47:44 had any major impact in terms of deglobalization.
47:47 So I'm not saying there's nothing in the data,
47:49 but it's not like,
47:50 uh,
47:50 you know,
47:50 we are,
47:51 you know,
47:51 globalization is,
47:52 is,
47:52 is collapsing.
47:54 And,
47:54 and what I just want to stress is that this kind of,
47:57 uh,
47:57 these,
47:58 these ingredients kind of combined to a
48:00 Uh,
48:01 you know,
48:01 I think a somewhat explosive combination,
48:04 maybe explosive is the wrong word,
48:05 but,
48:06 but,
48:06 but a dangerous situation where
48:08 I really think the
48:10 kind of future of globalization is being
48:12 debated now.
48:13 It's being decided or not,
48:14 and it's really important to
48:16 inform this,
48:17 this debate with,
48:18 with research.
48:20 Um,
48:20 so what kind of research is needed?
48:22 Um,
48:22 you know,
48:22 I think this,
48:23 this crisis is,
48:24 is not a crisis,
48:25 uh,
48:25 uh,
48:26 of,
48:26 uh,
48:27 uh,
48:27 uh,
48:28 of,
48:28 you,
48:28 you know,
48:29 that,
48:29 that,
48:29 that has so much to do with,
48:30 with economics directly in the sense that I don't think it's
48:33 about people not appreciating that the economic gains from trade,
48:36 but it's really about people,
48:38 um,
48:39 Thinking that trade is part of the problem,
48:41 uh,
48:41 when it comes to addressing the key challenges,
48:44 uh,
48:44 of our time.
48:45 I think the key challenges,
48:46 uh,
48:46 are to
48:47 maintain peace and security.
48:49 And with the security,
48:50 I also mean economic security,
48:52 so,
48:53 uh,
48:53 resilience and so on.
48:54 Uh,
48:55 second,
48:55 to,
48:55 um,
48:56 achieve a sustainable economy.
48:58 And third,
48:58 to reduce,
48:59 uh,
48:59 poverty and,
49:00 uh,
49:00 and inequality.
49:01 And,
49:02 and I think it's a dangerous misperception that,
49:04 you know,
49:04 trade is really
49:05 part of the problem because in fact,
49:07 after the right policies are in place,
49:09 trade is really,
49:09 uh,
49:10 part of the solution.
49:11 To
49:11 illustrate this,
49:12 let me pick one
49:13 that the,
49:14 uh,
49:14 pick the challenge of achieving a sustainable economy.
49:17 So,
49:17 so most people when they think of trade,
49:19 they think of transport emissions,
49:20 when they think of transport emissions,
49:22 they think of,
49:23 you know,
49:23 you know,
49:24 uh,
49:24 CO2 and climate change and,
49:26 and how this is all about.
49:28 But really when you think about some,
49:30 uh,
49:30 trade more holistically,
49:32 um,
49:32 you know,
49:32 there's not just transport emissions,
49:34 but there's also production emissions.
49:35 And there's actually a large variation of production emissions across countries.
49:39 Um,
49:39 and also trade,
49:40 uh,
49:41 sorry,
49:41 transport emissions are actually only a relatively small part of the overall.
49:45 So in general,
49:46 uh,
49:46 it's just not true that trade is,
49:48 uh,
49:48 necessarily bad for the,
49:49 uh,
49:50 environment because to the extent that you source from a greener location,
49:53 I call this green sourcing,
49:54 Um,
49:55 you actually save,
49:56 um,
49:56 uh,
49:56 overall emissions,
49:57 even though
49:58 you incur some transport emissions.
50:00 And,
50:00 and,
50:01 and some
50:02 research that I've done
50:03 on this issue
50:04 is,
50:05 uh,
50:05 what we've done is we've just taken a quantitative trade model,
50:08 um,
50:08 and we,
50:09 um,
50:09 uh,
50:09 hit the trade model with the worldwide carbon tax
50:12 to kind of internalize the externalities caused by,
50:15 um,
50:16 Uh,
50:17 you know,
50:17 caused by,
50:18 um,
50:18 by,
50:18 by,
50:19 by,
50:19 by promotion.
50:20 And,
50:21 and,
50:21 you know,
50:21 we,
50:22 we just ask,
50:22 you know,
50:23 to what extent,
50:23 you know,
50:24 traders,
50:24 uh,
50:25 a part of the solution.
50:26 And what we find,
50:27 we find is that the,
50:28 um,
50:29 environmental gains,
50:30 uh,
50:30 from trade that have something to do with countries
50:32 specializing in the sectors in which they're relatively green at
50:35 these environmental gains from trade.
50:37 Uh,
50:38 actually contribute one third
50:39 to the,
50:40 um,
50:40 overall emissions reduction that is achieved by this,
50:43 um,
50:43 uh,
50:44 carbon tax.
50:44 So just one example of
50:46 how I think you can conduct research,
50:47 advocacy research,
50:48 if you will,
50:49 that,
50:50 uh,
50:50 shows that trade is really an important part of the,
50:53 um,
50:53 of the solution.
50:55 And,
50:55 and this is just,
50:56 uh,
50:56 you know,
50:56 one example,
50:57 you can,
50:58 uh,
50:58 do the same when you think about maintaining peace and security.
51:01 You can think about the same when you,
51:03 um,
51:04 talk about reducing poverty and inequality.
51:06 And when I say advocacy research,
51:07 I don't mean that we should go in and kind of already know the conclusion,
51:10 but I think it's fine to go in with the hypothesis.
51:13 Uh,
51:13 and the hypothesis that I have is that trade,
51:16 uh,
51:16 is,
51:16 is extremely important
51:18 and deserves to be protected.
51:20 So,
51:20 um,
51:21 um,
51:22 so the system,
51:23 uh,
51:23 deserves to be protected.
51:24 So just,
51:25 just lastly,
51:25 in terms of,
51:26 you know,
51:26 the role of,
51:27 uh,
51:27 uh,
51:28 research,
51:28 so,
51:28 so one thing that I,
51:29 I do think is important to recognize is that the
51:33 crisis that,
51:33 that we are facing is really of a macroeconomic nature.
51:36 And I think,
51:37 therefore,
51:38 um,
51:38 uh,
51:39 it's also important to,
51:40 um,
51:40 conduct research,
51:41 um,
51:42 kind of at that level
51:43 and,
51:44 uh,
51:44 as important as,
51:45 um,
51:45 you know,
51:46 RCTs are and fer heterogeneity is,
51:48 uh,
51:49 and,
51:49 and so on.
51:50 And I really don't want to minimize the,
51:51 the value of that.
51:53 Um,
51:53 I do think if we want to do something about this current,
51:55 uh,
51:56 globalization crisis,
51:57 uh,
51:57 we should,
51:58 in addition
51:59 to,
51:59 uh,
51:59 doing these,
52:00 uh,
52:01 kind of very micro-level analysis,
52:03 also
52:03 not lose sight of the big picture,
52:05 uh,
52:06 because we really have a
52:07 big picture um problem here.
52:09 So
52:10 thank you very much.
52:13 Thanks very much,
52:14 Ralph.
52:14 Um,
52:15 Nina?
52:23 Let me share my screen.
52:33 Can you see my presentation?
52:35 Yes,
52:36 it looks good.
52:36 Yes,
52:37 we can.
52:37 Yes,
52:38 so thank you so much for,
52:39 uh,
52:39 inviting me to participate on this,
52:42 uh,
52:42 panel.
52:42 Uh,
52:43 it has been actually really exciting to kind of look through all the material,
52:46 material that,
52:47 uh,
52:47 Daria and Florence have shared and see,
52:50 you know,
52:50 how much,
52:50 uh,
52:51 you know,
52:51 the research in,
52:52 uh,
52:52 the World Bank has contributed to kind of our.
52:55 Knowledge in terms of how trade,
52:57 uh,
52:57 and international integration is shaping,
52:59 uh,
52:59 both foreign performance and kind of the lives of people in,
53:02 um,
53:03 you know,
53:03 in lots of,
53:04 uh,
53:04 lower income countries,
53:05 uh,
53:06 so just to kind of summarize kind of where I see the current state of,
53:09 uh,
53:10 research is,
53:11 uh,
53:11 you know,
53:11 first of all,
53:12 I think,
53:12 um,
53:13 the,
53:14 uh.
53:15 The research in uh this,
53:17 um,
53:18 uh,
53:18 program really
53:19 kind of highlights kind of that World Bank staff have a very unique vantage
53:23 points and expertise to address kind of with both with rigor and insight,
53:27 kind of the policy challenges that,
53:29 uh,
53:29 you know,
53:30 that,
53:30 uh,
53:30 uh,
53:31 different countries in the world,
53:32 uh,
53:33 face,
53:33 and that's because,
53:34 you know,
53:34 you through operations,
53:36 you know what,
53:36 uh,
53:36 you,
53:37 you're the first to kind of recognize what those challenges are,
53:40 and you can create,
53:41 uh,
53:41 partnerships with government to,
53:43 uh,
53:43 to,
53:43 uh.
53:44 Address them
53:45 while at the same time,
53:47 uh,
53:47 kinda use the tools of,
53:49 uh,
53:49 kinda aca you know,
53:50 kinda academic,
53:51 uh,
53:51 academic,
53:52 uh,
53:52 research.
53:53 Uh,
53:53 the other thing that is very apparent from this
53:56 research program is that over the past 20 years,
53:59 uh,
53:59 the World Bank has really,
54:01 uh,
54:02 increased investment in kinda
54:03 micro-level data sets needed for trade analysis,
54:06 and this goes
54:08 from,
54:08 uh,
54:08 you know,
54:09 investing a lot into,
54:10 uh,
54:11 trade policy,
54:11 uh,
54:12 databases,
54:12 for example,
54:13 like the deep trade agreements.
54:14 Uh,
54:15 export dynamics database,
54:17 uh,
54:17 you know,
54:17 uh,
54:18 and kind of the household impact of chairs database,
54:20 and what I wanna emphasize,
54:22 uh,
54:22 here is that like the key
54:24 aspect of this data set,
54:26 it's not that they're just micro,
54:27 they actually collect similar information across many countries,
54:31 uh,
54:31 and this is really,
54:32 really important because it doesn't,
54:34 uh,
54:34 just enable,
54:35 uh,
54:35 you know,
54:36 the research,
54:37 uh,
54:38 within a particular country,
54:39 but also to the extent that,
54:41 uh,
54:42 you know,
54:42 um,
54:43 a trade is,
54:44 uh.
54:45 The trade,
54:46 you know,
54:46 it propagates,
54:47 uh,
54:47 macroeconomic shocks across,
54:49 uh,
54:50 countries.
54:51 We are actually,
54:51 we're actually able to use these databases to
54:54 analyze this kind of macro implications of,
54:56 uh,
54:57 of international trade,
54:58 which both,
54:59 uh,
54:59 Lionel and,
55:00 uh,
55:00 uh Ralph kind of emphasized they're really,
55:02 really,
55:02 uh,
55:03 important.
55:03 And the other thing that,
55:05 uh,
55:05 where can I,
55:06 this increased investment really shows off is
55:08 collaboration and partnerships with governments
55:11 to uh learn uh more about how trade interacts with public finance,
55:16 um,
55:16 and,
55:17 uh,
55:17 kind of private,
55:18 uh,
55:18 sector development.
55:20 Uh,
55:20 the third thing that,
55:21 that,
55:21 uh,
55:22 really stands out,
55:23 uh,
55:23 in this research program is that,
55:25 uh,
55:26 the research priorities are very policy relevant.
55:29 Uh,
55:29 so,
55:29 you know,
55:30 currently,
55:30 as Ralph said,
55:31 like international trade is,
55:33 uh,
55:33 facing quite a bit of headwinds.
55:35 Uh,
55:35 you know,
55:36 people don't necessarily doubt the aggregate benefits of trade,
55:39 but,
55:40 you know,
55:40 there,
55:40 there are many more concerns about,
55:42 uh,
55:42 kind of distributional consequences of trade,
55:45 and this is where the World Bank,
55:46 uh,
55:47 has also contributed to our knowledge base in terms of.
55:49 Increasingly focusing on differential effects of trade,
55:53 either be it across firms,
55:55 uh,
55:55 regions,
55:55 or individuals,
55:57 uh,
55:57 and,
55:57 uh,
55:58 households,
55:59 and through that we have,
56:00 you know,
56:00 we haven't only learned how,
56:02 uh,
56:03 you know,
56:03 heterogeneous firms contribute to kind of aggregate productivity,
56:07 but also,
56:08 uh,
56:08 you know,
56:09 how trade shapes this,
56:10 uh,
56:10 distributional consequences,
56:12 and also kind of more recently in the research that Florence has highlighted,
56:16 kind of trade interactions with,
56:18 uh,
56:18 public finance.
56:19 And again,
56:20 I think that dimension is really important because,
56:22 you know,
56:22 as,
56:23 uh,
56:23 many countries in,
56:24 uh,
56:25 especially lower income countries have liberalized,
56:27 uh,
56:28 they've lost a pretty large share of revenue through elimination of,
56:32 uh,
56:33 uh,
56:33 you know,
56:33 tariff revenue
56:34 at the same time,
56:36 uh,
56:36 you know,
56:36 they,
56:37 they are,
56:37 they,
56:37 they need to be figuring out like how do we better,
56:40 uh,
56:40 um,
56:41 you know,
56:41 how do we better collect,
56:42 uh,
56:43 uh,
56:43 revenue from,
56:44 uh,
56:44 from other,
56:45 uh,
56:45 sours and also what's trade,
56:47 uh,
56:47 trade's role,
56:48 uh,
56:48 in that.
56:49 Uh,
56:49 I just wanna kind of highlight,
56:51 uh,
56:51 two areas where,
56:53 uh,
56:53 I think there's a lot of excite,
56:54 uh,
56:55 exciting research possibilities.
56:57 Uh,
56:58 that doesn't mean that like other areas do not matter.
57:00 I kind of picked the areas that are closer to,
57:02 uh,
57:03 my line of,
57:04 uh,
57:04 research.
57:05 Uh,
57:05 so one issue is this,
57:07 uh,
57:07 is,
57:07 you know,
57:08 kind of the role of global,
57:09 uh,
57:09 value change,
57:10 uh,
57:11 uh,
57:11 change.
57:11 So the research that both um uh Daria and Florence have highlighted
57:16 has
57:17 highlighted how much we have
57:19 uh learned about global value chains so far.
57:22 However,
57:22 I think
57:23 at the same time,
57:24 we want to learn more.
57:25 So I think we wanna dig deeper and deeper
57:27 into kind of the microeconomic determinants of like,
57:30 you know,
57:30 what's determining exporting and
57:32 importing within the supply chain.
57:34 And also what are the consequences of these supply chains for domestic firms,
57:37 uh,
57:38 and,
57:38 and households.
57:39 And here I kinda wanna highlight,
57:41 um,
57:42 uh,
57:43 uh,
57:43 two issues.
57:43 So on the one hand,
57:44 what we have learned so far is that exporting
57:48 and kind of just participation in these
57:49 global value chains is extremely concentrated,
57:52 kind of,
57:52 you know,
57:53 the,
57:53 uh,
57:54 the,
57:54 uh,
57:55 uh.
57:56 Exporter dynamics,
57:57 uh,
57:57 database and it really shows that large firms dominate trade across borders.
58:02 At the same time,
58:03 kind of the research that has been done within countries
58:06 suggests,
58:07 uh,
58:07 that,
58:08 you know,
58:08 many firms are informal,
58:10 uh,
58:10 uh,
58:11 uh,
58:11 and,
58:12 uh,
58:12 you know,
58:12 this,
58:13 uh,
58:13 you know,
58:14 this is the case for like trading firms,
58:16 uh,
58:16 you know,
58:17 producers,
58:18 and so the question becomes like.
58:19 You know,
58:20 how do we link kind of,
58:21 uh,
58:21 you know,
58:22 shocks and policies that,
58:24 uh,
58:24 uh,
58:24 uh,
58:25 that are related to trade
58:27 to informal,
58:28 informal traders and firms within companies and ultimately to kind of
58:32 the well-being of households within countries and I think here,
58:35 uh,
58:36 you know,
58:36 uh,
58:36 while we have learned quite a bit on these issues,
58:38 I think we need further,
58:40 uh,
58:40 connections and further investment in,
58:42 uh,
58:42 microdata.
58:43 That's,
58:43 uh,
58:44 to understand this,
58:45 and this would,
58:46 you know,
58:46 World Bank has,
58:47 has already connect,
58:48 uh,
58:48 invested a lot into kind of customs level,
58:50 uh,
58:51 databases,
58:52 uh,
58:52 through,
58:52 uh,
58:52 EDD across many countries.
58:55 It would be really good like to do that,
58:57 uh,
58:57 to,
58:58 uh,
58:58 in terms of administrative firm to firm data,
59:01 but at the same time,
59:02 given that those only,
59:03 uh,
59:04 cover formal,
59:05 uh,
59:05 in,
59:06 in,
59:06 um.
59:07 Formal transactions,
59:09 it's also important at the same time to also
59:10 invest into kind of industry-specific data sets and,
59:13 you know,
59:13 a good example of that is kind of the work that my colleague Meredith Stars did with,
59:18 you know,
59:19 um,
59:20 With,
59:20 uh,
59:20 documenting,
59:21 uh,
59:21 wholesale,
59:22 uh,
59:22 kind of wholesaler activities,
59:24 uh,
59:24 in Nigeria to better understand how,
59:26 for example,
59:27 informational and contractual frictions,
59:29 uh,
59:29 shape,
59:30 uh,
59:30 international trade,
59:31 uh,
59:31 you know,
59:32 many of those transactions would might not have actually,
59:35 uh,
59:35 appeared in kind of more commonly,
59:37 uh,
59:37 available administrative data sources.
59:39 Uh,
59:40 likewise,
59:40 you know,
59:41 with,
59:41 with those sort of industry-specific data sets,
59:43 we can learn more about relational contracted that
59:46 has been recently surveyed by Rocco Machiavello.
59:49 Which again provides like a link of like how do
59:51 these large firms interact with smaller firms and ultimately households,
59:55 uh,
59:55 within,
59:56 uh,
59:56 countries
59:57 and,
59:57 you know,
59:58 while,
59:58 uh,
59:59 uh,
59:59 you know,
1:00:00 previous,
1:00:00 uh,
1:00:01 uh,
1:00:02 speakers have,
1:00:02 have emphasized that it is really important to,
1:00:05 uh,
1:00:05 focus on macroeconomic implications of trade,
1:00:08 uh,
1:00:08 you know,
1:00:09 there is also value of like what we can learn
1:00:11 about specific chan uh channels to which trade is affecting,
1:00:14 especially kind of smaller players in the,
1:00:17 uh,
1:00:17 in.
1:00:17 Lower income countries
1:00:19 to randomize,
1:00:20 uh,
1:00:20 control trials and again,
1:00:22 you know,
1:00:22 work by people like Meredith Starts and,
1:00:25 uh,
1:00:25 Lucas Zavala and many others has actually shown how we can use those
1:00:29 RCTs,
1:00:30 uh,
1:00:30 combined with structural or quantitative analysis to kind
1:00:32 of really learn kind of the micro mechanisms,
1:00:35 uh,
1:00:35 through which trade is shaping the smaller
1:00:37 firms or linking them through a broader trading,
1:00:40 uh,
1:00:41 environment.
1:00:41 In part we can do that,
1:00:43 uh,
1:00:43 because,
1:00:44 uh,
1:00:44 these kind of specially collected data sets.
1:00:46 Improve our measurement of key outcomes,
1:00:48 uh,
1:00:48 both kind of firm to supplier or customer matches,
1:00:52 prices,
1:00:52 quality,
1:00:53 productivity,
1:00:54 uh,
1:00:55 frictions,
1:00:55 and so on.
1:00:56 Uh,
1:00:57 so that's the first area where I think there's
1:00:58 a lot of potential to continue to learn.
1:01:01 Uh,
1:01:01 the other area kind of goes back to kind of the old question of trade and,
1:01:05 uh,
1:01:05 development.
1:01:06 Uh,
1:01:06 I think,
1:01:07 uh,
1:01:07 you know,
1:01:07 traditional trade analysis,
1:01:09 very,
1:01:10 you know,
1:01:10 very,
1:01:10 uh,
1:01:11 you know,
1:01:11 in most cases relies on frameworks that are super frictionless economies.
1:01:15 Uh,
1:01:16 eco,
1:01:16 but recently we have really learned quite a bit that kinda,
1:01:20 uh,
1:01:20 country and market characteristics,
1:01:22 uh,
1:01:23 is,
1:01:23 you know,
1:01:23 such as like weaker institutions,
1:01:25 uh,
1:01:25 market failures such as,
1:01:26 uh,
1:01:26 you know,
1:01:27 uh,
1:01:27 market power,
1:01:28 uh,
1:01:28 size dependent distortions
1:01:30 can interact in important ways,
1:01:32 uh,
1:01:32 with trade,
1:01:33 uh,
1:01:34 and,
1:01:34 uh,
1:01:34 you know,
1:01:35 a good example that,
1:01:36 uh,
1:01:36 uh,
1:01:36 uh,
1:01:37 uh,
1:01:37 Daria provided is research by,
1:01:39 uh,
1:01:40 Ana Fernandez and,
1:01:41 uh,
1:01:41 Bob Brekers that actually showed like when we actually in,
1:01:44 uh.
1:01:45 Uh,
1:01:45 uh,
1:01:46 reform,
1:01:47 uh,
1:01:47 customs,
1:01:48 uh,
1:01:48 you know,
1:01:48 that actually has important implications for kind of aggregates,
1:01:52 uh,
1:01:52 uh,
1:01:52 gains,
1:01:53 uh,
1:01:53 gains from trade,
1:01:54 and I think kind of more research,
1:01:56 uh,
1:01:57 you know,
1:01:57 potentially with partnership with,
1:01:59 uh,
1:01:59 with,
1:02:00 uh,
1:02:00 with,
1:02:01 uh,
1:02:01 government partners,
1:02:02 uh,
1:02:03 uh,
1:02:03 you know,
1:02:03 to explore how can.
1:02:04 Trades,
1:02:05 uh,
1:02:05 reduce misallocation.
1:02:07 How can like changes in institutions reduce overall misallocation,
1:02:10 uh,
1:02:11 uh,
1:02:11 you know,
1:02:12 can play a potentially,
1:02:13 uh,
1:02:13 important,
1:02:14 uh,
1:02:14 role
1:02:15 both for better understanding of kind of,
1:02:17 uh,
1:02:17 gains from trade as well as,
1:02:18 uh,
1:02:19 you know,
1:02:19 kind of distributional consequences of trade and who
1:02:21 can and cannot participate in global markets.
1:02:24 So in terms of kind of big picture takeaways,
1:02:26 uh,
1:02:26 you know,
1:02:27 I think,
1:02:27 uh,
1:02:28 international trade is gonna continue to be a
1:02:29 really important component of World's Bank growth.
1:02:32 Uh,
1:02:32 you know,
1:02:33 we have,
1:02:33 uh,
1:02:34 we have been recently over the past 10 years through an
1:02:36 incredibly eventful period of trade with strong headwinds to globalization.
1:02:41 So,
1:02:41 uh,
1:02:42 I think because of that,
1:02:43 it's really important to be focusing both on kind of
1:02:46 micro and macro research to make progress on trade,
1:02:49 uh,
1:02:50 topics.
1:02:51 Uh,
1:02:51 I think.
1:02:52 Uh,
1:02:52 continued expertise of the World Bank both in,
1:02:55 um,
1:02:56 institutional features of trade policy as well
1:02:58 as political economy of trade policy.
1:03:00 It's gonna be really important here.
1:03:02 Uh,
1:03:02 and
1:03:03 the second thing that I would emphasize is,
1:03:05 you know,
1:03:05 it's,
1:03:06 it's really reassuring that international trade research is being
1:03:09 conducted in conjunction with research in public finance,
1:03:12 labor economics,
1:03:13 industrial organization,
1:03:14 and macro because that's the,
1:03:16 you know,
1:03:16 that's the only way we can kind of learn,
1:03:18 uh,
1:03:19 about,
1:03:19 uh.
1:03:20 Uh,
1:03:20 uh,
1:03:21 kind of the consequences of trade for both from macro and micro perspective,
1:03:24 uh,
1:03:24 but of course,
1:03:25 uh,
1:03:25 you know,
1:03:26 this sort of research kinda
1:03:28 requires continued investment in existing and new micro multi,
1:03:31 uh,
1:03:31 country databases because
1:03:33 it is this sort of databases that enable us to kind of dig deeper into,
1:03:37 you know,
1:03:37 how specific markets work and learn about the mechanisms as well as
1:03:42 better understand the linkages
1:03:44 across firms and households across,
1:03:46 um,
1:03:47 um,
1:03:47 across countries.
1:03:49 Thank you.
1:03:52 Thanks very much,
1:03:53 Nina.
1:03:53 And last,
1:03:54 we have Yasuyuki,
1:03:55 over to you.
1:03:59 OK.
1:04:00 Thank you very much.
1:04:02 Um,
1:04:03 can you see my slide?
1:04:07 Uh yes,
1:04:07 we do.
1:04:07 Thanks.
1:04:09 Uh,
1:04:09 is it a slideshow?
1:04:10 No.
1:04:12 Yeah,
1:04:14 yeah,
1:04:14 there we go.
1:04:14 It looks good.
1:04:15 OK,
1:04:15 good,
1:04:15 good.
1:04:16 Thank you.
1:04:16 So,
1:04:16 uh,
1:04:17 first of all,
1:04:17 I'd like to thank,
1:04:18 uh,
1:04:18 the organizers for inviting me to this,
1:04:20 uh,
1:04:20 great,
1:04:21 uh,
1:04:21 conference.
1:04:22 I'm,
1:04:22 uh,
1:04:23 pretty much impressed by the,
1:04:24 uh,
1:04:24 World Bank's,
1:04:25 uh,
1:04:25 uh,
1:04:25 works,
1:04:26 uh,
1:04:26 presented by,
1:04:27 um,
1:04:28 Daria in the Florence,
1:04:30 and,
1:04:30 uh,
1:04:30 I would like to,
1:04:31 uh,
1:04:31 follow up,
1:04:32 uh,
1:04:32 uh,
1:04:32 their great presentations
1:04:34 and also,
1:04:35 uh,
1:04:35 uh,
1:04:36 some of the,
1:04:36 uh,
1:04:37 discussions,
1:04:38 uh,
1:04:38 uh,
1:04:38 uh,
1:04:39 discussion.
1:04:40 Uh,
1:04:40 by focusing on benefits and risks of,
1:04:42 uh,
1:04:42 global value chains.
1:04:44 So benefits,
1:04:45 uh,
1:04:45 uh,
1:04:45 have already been,
1:04:46 uh,
1:04:46 uh,
1:04:47 discussed,
1:04:47 uh,
1:04:48 uh,
1:04:48 extensively,
1:04:49 but here I'd like to emphasize the,
1:04:51 uh,
1:04:51 effect of uh GVC participation
1:04:54 on productivity growth because,
1:04:55 uh,
1:04:56 evidence,
1:04:56 uh,
1:04:57 I think
1:04:58 on the,
1:04:59 uh,
1:04:59 learning by doing and also learning through supply chain,
1:05:02 uh,
1:05:02 supplier-customer relationships,
1:05:04 uh,
1:05:05 uh,
1:05:05 with the FDI firms.
1:05:07 And uh uh but uh one remaining policy question is that uh how can we,
1:05:12 how can policies upgrade the supply chains to knowledge networks?
1:05:17 Uh,
1:05:17 in Japan,
1:05:18 actually supply chain re generations are often
1:05:20 associated with uh uh technical assistance and research collaboration.
1:05:25 And also uh research collaboration,
1:05:27 uh,
1:05:27 in particular,
1:05:28 international research collaboration
1:05:30 is found to promote innovation as evidenced by this uh uh.
1:05:35 Uh,
1:05:35 figure,
1:05:36 but it is insufficient in emerging and developing countries.
1:05:40 So uh
1:05:41 it is quite important to promote,
1:05:42 uh,
1:05:43 uh,
1:05:43 to promote knowledge networks
1:05:45 in addition to,
1:05:46 uh,
1:05:47 supply chain networks in GVCs.
1:05:49 So that's one of my,
1:05:51 uh,
1:05:52 suggestion.
1:05:53 Uh,
1:05:53 but,
1:05:53 uh,
1:05:54 uh,
1:05:54 GVC participation incurs,
1:05:56 uh,
1:05:56 uh,
1:05:56 risks.
1:05:57 Uh,
1:05:57 recently,
1:05:58 GVCs have often been,
1:06:00 have often been disrupted by
1:06:02 natural disasters,
1:06:03 pandemics,
1:06:04 and military conflicts.
1:06:06 So these,
1:06:07 uh,
1:06:07 uh,
1:06:07 uh,
1:06:08 uh,
1:06:08 led to negative impacts on production
1:06:12 and welfare in developing countries.
1:06:14 So we need to minimize these,
1:06:16 uh,
1:06:16 risks.
1:06:17 But the risks are actually uh becoming larger and larger
1:06:21 because source countries of imports are more and more concentrated
1:06:25 for many developing countries as uh this figure shows.
1:06:29 So that means that when international trade is uh disrupted,
1:06:33 uh,
1:06:33 there will be a large economic loss in developing countries.
1:06:38 So this is a serious problem because uh uh several economic studies
1:06:42 have found that uh that uh uh economic shocks propagate through supply chains
1:06:47 uh using uh econometric analysis and using simulation uh uh framework.
1:06:53 So recently,
1:06:54 some simulation studies uh quantify.
1:06:57 The economic,
1:06:58 uh,
1:06:58 loss due to the COVID COVID pandemic
1:07:01 using country industry level
1:07:03 input output tables,
1:07:05 and they found a large indirect effect
1:07:09 of lockdowns in developed countries on developing countries,
1:07:13 uh,
1:07:13 as this figure shows.
1:07:17 And I myself did some uh firm level
1:07:20 simulation to incorporate the complexity of supply chains
1:07:25 into the analysis
1:07:26 using a unique data set for Japanese firms,
1:07:30 uh,
1:07:30 actually a large number,
1:07:33 like more than 1 million Japanese firms,
1:07:37 uh,
1:07:37 with a detailed supply chain data.
1:07:40 And this is important because
1:07:44 it is often the case that the number of suppliers and customers
1:07:48 exhibits a parallel distribution like this,
1:07:51 which means there are several
1:07:54 hub firms
1:07:55 with an extremely large number of suppliers and customers.
1:08:00 So with
1:08:01 incorporating this special network characteristics,
1:08:04 maybe we will,
1:08:05 we would undervalue the effect of propagation through supply chains.
1:08:10 So we need a,
1:08:11 a kind of this kind of uh uh firm level analysis.
1:08:15 And recently,
1:08:16 I examined the effect of disruption of imports
1:08:20 on the Japanese production.
1:08:22 Uh,
1:08:22 using this framework and found,
1:08:24 uh,
1:08:24 uh,
1:08:25 uh,
1:08:25 actually the effect is quite large.
1:08:27 For example,
1:08:28 uh,
1:08:28 uh,
1:08:29 the disruption of imports,
1:08:31 uh,
1:08:31 from China or other Asia
1:08:33 would
1:08:34 result in the reduction in value added
1:08:37 by
1:08:38 $100 billion.
1:08:40 And also the effect is heterogeneous
1:08:43 across industries.
1:08:44 For example,
1:08:45 the disruption of imports of.
1:08:47 The effect of uh disruption of imports
1:08:50 of uh more upstream products is larger than downstream products,
1:08:55 which means that uh uh when we think about the uh risks of GVCs,
1:09:00 we have to think about how domestic firms are linked
1:09:04 with uh GVCs.
1:09:06 So,
1:09:06 uh,
1:09:07 then,
1:09:07 uh,
1:09:07 the,
1:09:08 the uh effect uh through supply chains,
1:09:10 our GVCs
1:09:11 may vary.
1:09:14 And another thing is that uh to mitigate propagation uh through supply chains,
1:09:20 uh,
1:09:21 you know,
1:09:21 uh,
1:09:22 what we can do
1:09:23 uh to mitigate the propagation uh through supply chains.
1:09:26 Several studies have found that,
1:09:29 uh,
1:09:29 that the
1:09:31 substitutability
1:09:33 of uh inputs or suppliers by diversifying partners,
1:09:38 uh,
1:09:38 may help.
1:09:39 Uh,
1:09:39 these,
1:09:40 uh,
1:09:40 uh,
1:09:40 uh,
1:09:41 figures.
1:09:41 shows that uh in ASEAN countries and India
1:09:44 during the COVID pandemic,
1:09:46 uh,
1:09:46 firms were more likely to be resilient
1:09:50 when they
1:09:51 have uh uh customers and uh suppliers
1:09:54 in more than one country.
1:09:56 So that means a regional diversity of trade partners promotes can promote,
1:10:01 promote uh resilience,
1:10:03 because it leads to uh uh easiers suitability
1:10:07 of suppliers.
1:10:10 And,
1:10:11 uh,
1:10:11 another question,
1:10:12 uh,
1:10:12 which was,
1:10:13 uh,
1:10:13 uh,
1:10:13 uh,
1:10:14 raised by several panels
1:10:16 and the presenters is,
1:10:18 uh,
1:10:18 um,
1:10:19 uh,
1:10:19 uh,
1:10:20 you know,
1:10:20 the protectionism.
1:10:22 So maybe,
1:10:23 uh,
1:10:23 you may think that to mitigate the risks of uh GVCs,
1:10:28 you can utilize the protectionist policies
1:10:30 rather than supply chain diversification.
1:10:33 Uh,
1:10:33 in fact,
1:10:34 uh,
1:10:34 uh,
1:10:34 several developed countries are implementing,
1:10:37 uh,
1:10:37 implementing such,
1:10:38 uh,
1:10:38 uh.
1:10:39 Uh,
1:10:40 uh,
1:10:41 industrial policies to onshore production of,
1:10:44 uh,
1:10:44 critical
1:10:45 products,
1:10:46 uh,
1:10:46 to deal with,
1:10:47 uh,
1:10:47 and to deal with national security concerns.
1:10:49 Uh,
1:10:50 I have only one minute,
1:10:51 so,
1:10:51 uh,
1:10:52 let me,
1:10:53 uh,
1:10:53 wrap up.
1:10:54 Uh,
1:10:55 no,
1:10:55 no,
1:10:55 no,
1:10:55 so,
1:10:55 uh.
1:10:57 Yeah,
1:10:57 anyway,
1:10:58 so,
1:10:59 uh,
1:10:59 but,
1:10:59 uh,
1:10:59 uh,
1:11:00 as a previous presentation suggests,
1:11:02 uh,
1:11:03 uh,
1:11:03 openness is better
1:11:04 to economic growth generally.
1:11:07 So anyway,
1:11:08 uh,
1:11:08 let me wrap up my uh presentation by,
1:11:12 uh,
1:11:13 mentioning several remaining policy questions,
1:11:17 but uh I don't have time to read them through,
1:11:19 but,
1:11:19 uh,
1:11:20 I hope,
1:11:20 uh,
1:11:20 uh,
1:11:21 KCP
1:11:22 will also,
1:11:23 uh,
1:11:23 tackle these policy issues in the future.
1:11:26 Thank you very much.
1:11:31 Thanks very much,
1:11:31 Yuki,
1:11:32 for staying on,
1:11:33 uh,
1:11:33 on time.
1:11:33 So we have,
1:11:34 um,
1:11:35 uh,
1:11:36 we'll,
1:11:36 we'll postpone the start of our coffee break a little bit,
1:11:38 but we won't shorten the coffee break and
1:11:40 we'll just steal time from the next session.
1:11:41 So,
1:11:42 that'll give us until about 10,
1:11:44 uh,
1:11:44 10:25,
1:11:45 um.
1:11:46 Uh,
1:11:47 so,
1:11:47 um,
1:11:48 I'm happy to open up the floor for questions.
1:11:51 Uh,
1:11:51 those of you who are participating online,
1:11:53 please,
1:11:54 uh,
1:11:54 just put your questions in the chat,
1:11:56 which we're monitoring and happy to take,
1:11:58 uh,
1:11:59 questions the old fashioned way from people in the room.
1:12:02 Uh,
1:12:02 you know what to do,
1:12:03 you put your hand up,
1:12:04 I point to you,
1:12:04 that sort of thing.
1:12:06 It's right.
1:12:07 I think people are out of practice with how that works.
1:12:10 Um.
1:12:11 Maybe while,
1:12:12 while people are overcoming their reticence and thinking
1:12:15 about questions that they want to raise,
1:12:16 I wanted to
1:12:17 make sort of
1:12:18 two observations that came to me from thinking about sort of the,
1:12:21 the totality of the,
1:12:23 the presentations and,
1:12:23 and,
1:12:24 and the discussions.
1:12:26 The one,
1:12:26 and this really,
1:12:27 you know,
1:12:27 ran through things that,
1:12:29 uh,
1:12:29 that,
1:12:29 uh,
1:12:30 that Daria,
1:12:31 Florence,
1:12:32 Lionel,
1:12:33 in different ways,
1:12:34 Ralph and Nina all spoke about is the importance of granular data.
1:12:38 Um,
1:12:38 in particular,
1:12:39 our firm level data and administrative data,
1:12:42 and I think what we're seeing is this move in
1:12:45 the profession from sort of boutique boutique opportunistic access.
1:12:50 To granular data to
1:12:53 more sort of systematic smart access at scale.
1:12:57 And it would be great to hear particularly from Daria and Florence,
1:13:01 what,
1:13:02 you know,
1:13:02 what are the things that a place like the World Bank can do and,
1:13:05 uh,
1:13:06 in particular,
1:13:07 you know,
1:13:07 what are things that cost money,
1:13:08 right?
1:13:09 We need to invest in to do,
1:13:10 to,
1:13:11 to facilitate this sort of access.
1:13:13 So,
1:13:13 that,
1:13:13 that,
1:13:14 that's 111 theme that I see running through.
1:13:16 The second,
1:13:17 um,
1:13:18 theme,
1:13:18 which leads to a question as well,
1:13:19 and
1:13:20 this is a little bit more superficial,
1:13:21 but like,
1:13:21 you know,
1:13:22 I'm thinking back to like,
1:13:22 you know,
1:13:23 35 years ago when I took my first economics course,
1:13:25 right?
1:13:26 And in,
1:13:26 as an undergraduate,
1:13:28 you know,
1:13:28 35 years ago,
1:13:29 and I'm sure even longer ago,
1:13:31 professors were talking about the fact that,
1:13:34 you know,
1:13:35 Every,
1:13:36 you know,
1:13:36 um,
1:13:37 sorry,
1:13:38 how,
1:13:38 how do I put this the right way around?
1:13:40 Economists are very,
1:13:41 very good at articulating the case for trade to each other,
1:13:44 and they're terrible at articulating the case for trade to
1:13:48 everybody who's not an economist,
1:13:49 which unfortunately is almost everybody else,
1:13:52 right?
1:13:52 And,
1:13:53 you know,
1:13:53 somehow that's still sort of is,
1:13:55 is,
1:13:55 is coming through here,
1:13:56 right?
1:13:56 And,
1:13:57 and I wonder what we need to do to sort of sharpen the discussion.
1:14:00 So there's sort of very old flavors of this,
1:14:02 right?
1:14:02 So,
1:14:03 Yes,
1:14:03 we know that there are winners and losers,
1:14:05 but we know that under almost all circumstances,
1:14:07 the gains of the winners exceed the losses to the losers,
1:14:09 and there should,
1:14:10 so there should be compensatory mechanisms.
1:14:13 Yeah,
1:14:13 we've never been very clear at
1:14:15 persuading that,
1:14:15 or I was thinking about a variant on that point listening to
1:14:18 to Yasuyuki's presentation.
1:14:20 So you're focused very much on the propagation of negative shocks.
1:14:23 Through
1:14:24 global value chains,
1:14:25 right?
1:14:26 But,
1:14:26 but why is that asymmetric,
1:14:27 right?
1:14:27 So,
1:14:28 presumably also positive shocks
1:14:30 propagate,
1:14:31 and do we know whether there's asymmetries and positive versus negative shocks?
1:14:35 Um,
1:14:36 anyhow,
1:14:36 so,
1:14:37 those are two things that I wanted to put on the table,
1:14:39 but hopefully by now,
1:14:40 others have better questions to ask,
1:14:42 and,
1:14:42 uh,
1:14:42 go ahead,
1:14:43 David.
1:14:44 So I guess one question is,
1:14:46 is whether we're just still way too focused on manufacturing in all this
1:14:50 work because that's where the data is,
1:14:52 you know,
1:14:52 we talk about value chains,
1:14:53 we can measure
1:14:54 kind of manufacturing,
1:14:56 but,
1:14:57 you know,
1:14:57 services trade
1:14:59 is not.
1:15:00 You know,
1:15:00 capture,
1:15:01 you know,
1:15:01 I was looking at,
1:15:02 at the US and it's,
1:15:03 it's still relying on surveys occasionally to try and,
1:15:06 you know,
1:15:06 get some sense of
1:15:08 where
1:15:09 services trade is,
1:15:10 is taking place,
1:15:10 and we,
1:15:11 we,
1:15:11 you know,
1:15:12 trying to think through,
1:15:13 you know,
1:15:13 services value chains and,
1:15:15 uh,
1:15:16 you know,
1:15:16 this move away from a manufacturing-based,
1:15:19 um,
1:15:21 Sort of growth path to,
1:15:22 to,
1:15:23 you know,
1:15:24 services,
1:15:24 I just
1:15:25 sort of don't know,
1:15:26 you know,
1:15:26 what the barriers are to us doing that,
1:15:28 whether it's a data
1:15:30 question or whether some of the,
1:15:31 the sort of
1:15:32 trade theory is also different.
1:15:37 Thanks,
1:15:37 David.
1:15:38 Anybody else want to uh jump in?
1:15:45 we don't,
1:15:45 OK.
1:15:46 So
1:15:47 let's,
1:15:47 um,
1:15:48 uh,
1:15:49 give Daria and Florence a chance first,
1:15:51 um,
1:15:52 uh,
1:15:52 to respond to some of these points,
1:15:54 or if you'd like to respond to any of the
1:15:55 points that the discussants made in their presentations as well.
1:15:59 And then,
1:15:59 uh,
1:15:59 depending on how much time we have,
1:16:01 we can maybe do a very,
1:16:02 like,
1:16:02 you know,
1:16:02 30 seconds each parting shot from the,
1:16:05 from the panelists.
1:16:06 Uh,
1:16:06 so,
1:16:07 Florence,
1:16:08 do you want to go first?
1:16:10 Yeah,
1:16:11 I guess I'll,
1:16:11 um,
1:16:12 I'll start with the,
1:16:13 the question on the importance of granular data and,
1:16:15 and what I,
1:16:16 I see as a,
1:16:17 you know,
1:16:18 as a World Bank researcher,
1:16:19 uh,
1:16:20 how this can move forward towards,
1:16:22 you know,
1:16:22 less boutique and more,
1:16:23 um,
1:16:24 you know,
1:16:25 constant,
1:16:25 I mean,
1:16:26 more,
1:16:26 uh,
1:16:27 Database style like global efforts uh of bringing
1:16:31 together this granular data from tax administration particularly.
1:16:34 So I think from our experience,
1:16:35 I think
1:16:36 we're starting to see the public finance sort of lab uh approach that we're taking
1:16:41 sort of bear some fruits.
1:16:42 Uh,
1:16:43 I think,
1:16:43 you know,
1:16:43 Pierre Bachas and all Others and Brockmeyer were
1:16:46 able to really bring together some data,
1:16:48 uh,
1:16:48 from multiple tax administrations.
1:16:50 Um,
1:16:50 now there are some limitations in the sense that
1:16:53 the very granular data that we have in mind,
1:16:55 like the,
1:16:55 the network data,
1:16:56 uh,
1:16:57 is quite private.
1:16:58 Uh,
1:16:59 tax administrations are a little bit
1:17:00 reticent to share it widely.
1:17:02 Uh,
1:17:03 for obvious reason that,
1:17:04 you know,
1:17:04 it,
1:17:04 it might not be super hard to identify firms,
1:17:07 uh,
1:17:07 in,
1:17:07 uh,
1:17:08 you know,
1:17:08 when you don't have a lot of,
1:17:09 uh,
1:17:09 a lot of actors in a,
1:17:11 in a value chain.
1:17:11 So,
1:17:12 I think these are,
1:17:12 these are,
1:17:13 you know,
1:17:14 issues of data confidentiality that we can think about,
1:17:16 uh,
1:17:17 with,
1:17:17 you know,
1:17:17 the Census Bureau and other people like that who do data confidentiality.
1:17:21 I think more problematic perhaps is,
1:17:24 you know,
1:17:24 Building these incentives from the public administrations,
1:17:27 from the tax administration to share this data in the first place,
1:17:29 even this boutique kind of uh of interactions,
1:17:32 uh,
1:17:33 I think there'll be a time to consolidate,
1:17:35 but I think we really need to demonstrate the value of these partnerships
1:17:39 before we can sort of consolidate,
1:17:41 uh,
1:17:41 these databases together,
1:17:43 and I think there'll be a time for that.
1:17:44 I think that should be our
1:17:45 vision.
1:17:46 Right,
1:17:46 that,
1:17:46 that's where we wanna get,
1:17:47 uh,
1:17:48 and probably we need to articulate
1:17:50 what are the steps to that and have consultations with those tax administrations,
1:17:54 uh,
1:17:54 to understand what are their constraints,
1:17:56 but I think they really need to see some private good value,
1:17:58 uh,
1:17:59 to this work,
1:18:00 uh,
1:18:00 before they are willing to,
1:18:02 to share.
1:18:02 So that's,
1:18:03 that's my take on that,
1:18:04 and I,
1:18:04 but I think we can get there and I think that's an exciting
1:18:06 part of the agenda.
1:18:08 Um,
1:18:08 I'm gonna leave the other questions
1:18:11 to Daria and others.
1:18:15 Yes,
1:18:15 so,
1:18:16 uh,
1:18:17 on,
1:18:17 I think on the granular data,
1:18:19 my sense is that that's part of the work,
1:18:22 but then there is really this international dimension that has to come in.
1:18:27 So,
1:18:27 it has been a lot of the limit of that either
1:18:30 we observe the domestic linkages or we observe the international linkages,
1:18:35 and so we need to bring them together.
1:18:37 Where are these international linkages,
1:18:39 they are in this private large firm data sets.
1:18:43 And because the larger data provider are trying to monetize those data,
1:18:48 it becomes increasingly difficult for us in,
1:18:52 in,
1:18:52 in policy institutions and in research institutions
1:18:55 to use them over the long term and,
1:18:58 and to keep building on that.
1:19:00 So where,
1:19:00 where I think we all have to think,
1:19:02 it's really how to create partnerships with these data providers
1:19:07 to,
1:19:07 and to,
1:19:08 and with the national administrations to try to connect all this data and to,
1:19:12 and to buy the right to keep using and building on them.
1:19:16 Uh,
1:19:17 on,
1:19:17 um,
1:19:19 On,
1:19:19 uh,
1:19:20 how to sharpen the discussion on trade,
1:19:23 I,
1:19:24 I,
1:19:24 I totally agree.
1:19:25 I think for me,
1:19:26 one point is that some of the restrictions we are observing now
1:19:30 are actually bringing us further away from the objectives that we were
1:19:35 thinking that they would fix.
1:19:37 So that is for me one way to show that
1:19:40 in terms of shocks.
1:19:42 I agree that uh also positive shocks uh benefit,
1:19:46 uh,
1:19:47 uh,
1:19:47 I mean,
1:19:48 there is also positive shocks that we should study more,
1:19:51 but,
1:19:51 and also how much trade limits uh the
1:19:55 propagation of domestic idiosyncratic shocks.
1:19:58 So again,
1:19:59 we need to look at the full matrix of
1:20:02 cases and then study them all.
1:20:05 And finally,
1:20:06 are we too focused on manufacturing?
1:20:08 I think we are too focused on manufacturing maybe,
1:20:12 but even too focused on
1:20:14 trade
1:20:17 outcome data.
1:20:17 We,
1:20:17 we need to,
1:20:19 to look at,
1:20:20 you know,
1:20:21 again,
1:20:21 some of those data sets that I was
1:20:23 mentioning which talk about investment relationships between firms,
1:20:29 uh,
1:20:29 or other characteristics are also able to,
1:20:32 to bring us
1:20:34 Uh,
1:20:34 away from,
1:20:35 from this trade in manufacturing data.
1:20:37 The price data,
1:20:38 I think it's an incredible source
1:20:40 of data that would allow us to,
1:20:43 to look differently at manufacturing.
1:20:45 I think there is also a conceptual and statistical
1:20:48 problem that we are still separating manufacturing and services
1:20:51 when this is really an artifact,
1:20:53 right?
1:20:53 And so whatever we can do to use data that dispel that separation,
1:20:58 I think will actually uh help us because it's,
1:21:01 it's,
1:21:01 it's really like a continuum.
1:21:04 Thanks.
1:21:06 Uh,
1:21:06 thanks very much,
1:21:07 Lawrence and Daria.
1:21:08 Do we have questions online?
1:21:11 Oh,
1:21:11 sorry,
1:21:11 go ahead.
1:21:12 Uh,
1:21:12 so we have two questions from online participants.
1:21:14 The first one is about firms in,
1:21:16 uh,
1:21:16 non-special economic zones.
1:21:19 So,
1:21:19 um,
1:21:19 the person says the large share of trade,
1:21:21 um,
1:21:22 happens through special economic zones which allows
1:21:25 us to overcome distortions in the wider economy.
1:21:28 But there's still a lot of constraints and broadening trade to the wider economy,
1:21:32 uh,
1:21:33 which would usually involve more domestic and informal firms.
1:21:36 So,
1:21:36 how can all these new databases,
1:21:38 new tools being developed,
1:21:39 help expand policy advice to those that can cover non-SEZ firms?
1:21:44 That's the first question.
1:21:45 The second is,
1:21:46 um,
1:21:47 if there's any new research on the effects of
1:21:49 trade policies and household incomes and income distribution?
1:21:53 Thank you.
1:21:56 So,
1:21:57 in the interests of time and also giving the panelists a chance to come in,
1:22:00 maybe I can just do a lightning round through the,
1:22:02 the panelists and give you each sort of,
1:22:04 you know,
1:22:04 one minute with your parting observations,
1:22:07 either in response to these last two questions
1:22:10 or to things that other people have said.
1:22:12 And that way we can wrap up by,
1:22:14 uh,
1:22:14 by 10:30 or so.
1:22:16 Since you're joining us virtually,
1:22:17 you don't see that you're standing between us and coffee,
1:22:20 but,
1:22:20 but you are.
1:22:21 So,
1:22:22 anyhow,
1:22:22 let's go in reverse order.
1:22:23 So,
1:22:24 yes,
1:22:24 Yuki,
1:22:24 do you want to go,
1:22:25 uh,
1:22:26 uh,
1:22:26 first,
1:22:26 just,
1:22:26 you know,
1:22:27 one minute of observations?
1:22:32 I actually I'm not saying that you know,
1:22:35 GVC is only propagating a bad shots.
1:22:38 Of course,
1:22:39 GVC is a very important channel of technology diffusion,
1:22:43 but traditionally risks of GVCs are neglected.
1:22:48 So
1:22:49 I'd like to emphasize that.
1:22:50 And also services in my simulation of using a firmer.
1:22:56 Level data for Japan.
1:22:57 Uh,
1:22:58 so service firms are also included because,
1:23:00 uh,
1:23:00 uh,
1:23:01 you know,
1:23:02 it's kind of a,
1:23:02 a large dataset including 1 million firms.
1:23:05 So,
1:23:05 uh,
1:23:06 uh,
1:23:06 uh,
1:23:07 and I found,
1:23:08 uh,
1:23:08 uh,
1:23:09 you know,
1:23:09 uh,
1:23:10 shocks do not very much propagate to service firms.
1:23:14 So,
1:23:14 uh,
1:23:14 that's what I'm finding.
1:23:16 But,
1:23:16 uh,
1:23:17 still,
1:23:17 you know,
1:23:17 services are very important.
1:23:19 The sense that uh uh knowledge network
1:23:21 is kind of a part of uh uh service uh relationships.
1:23:25 So,
1:23:25 uh,
1:23:26 uh,
1:23:26 uh,
1:23:27 we would like to know,
1:23:28 we need to research uh further on uh what happens if a knowledge network
1:23:34 is disrupted,
1:23:36 uh,
1:23:37 so the effect on the,
1:23:38 uh,
1:23:38 on the innovation
1:23:40 or something.
1:23:41 OK,
1:23:41 thank you very much.
1:23:44 Thanks,
1:23:45 Yayuki,
1:23:45 and Nina?
1:23:48 Yeah,
1:23:49 uh,
1:23:49 I also like wrap it to like the questions about the data,
1:23:53 including from the,
1:23:54 uh,
1:23:54 audience,
1:23:54 I would say like more access to kind of more national
1:23:57 representative data sources that don't just cover special economic zones,
1:24:01 but kind of more broadly cover firms.
1:24:04 Uh,
1:24:04 as well as like people have been using,
1:24:06 uh,
1:24:06 kind of household service,
1:24:07 uh,
1:24:08 that sometimes have modules on informal businesses,
1:24:11 uh,
1:24:11 either through,
1:24:12 uh,
1:24:12 you know,
1:24:13 through a special module or through kind of
1:24:14 at least labor market linkages provides a way
1:24:17 with the existing data to,
1:24:19 uh,
1:24:20 to be looking at these parts of the economy that are,
1:24:22 um,
1:24:23 uh,
1:24:23 more difficult to capture in addition to kind of,
1:24:26 you know,
1:24:26 data such as I mentioned before by like Meredith starts that
1:24:29 actually went out and kind of collected their own data.
1:24:32 on kind of whole on wholesalers,
1:24:33 uh,
1:24:34 which,
1:24:34 you know,
1:24:34 do include services.
1:24:35 I think that I fully agree with Daria that dichotomy
1:24:39 between services and manufacturing is basically a product of,
1:24:42 uh,
1:24:42 data,
1:24:43 and it would be nice to,
1:24:44 uh,
1:24:45 consider both of them jointly if,
1:24:46 uh,
1:24:46 you know,
1:24:47 if,
1:24:47 uh,
1:24:48 kind of,
1:24:48 um,
1:24:49 if we,
1:24:49 if we,
1:24:49 if we could measure services,
1:24:51 uh,
1:24:52 we,
1:24:52 if we could measure services,
1:24:53 uh,
1:24:54 better,
1:24:54 but yeah,
1:24:54 but
1:24:55 more generally,
1:24:56 you know,
1:24:56 how do we,
1:24:57 uh,
1:24:57 you know,
1:24:57 how do we communicate kind of finding.
1:24:59 About,
1:25:00 uh,
1:25:00 consequences of trade more broadly to,
1:25:03 uh,
1:25:03 to,
1:25:03 uh,
1:25:04 the public.
1:25:05 What's interesting is from public perceptions actually people agree that
1:25:08 like trade generates benefits to the economy as a whole,
1:25:11 but there's much more disagreement about kinda how workers or kinda,
1:25:14 uh,
1:25:15 are affected and who benefits and gains,
1:25:17 uh,
1:25:17 there.
1:25:18 So
1:25:18 I think,
1:25:19 uh,
1:25:19 at the end of the day,
1:25:20 uh,
1:25:21 I,
1:25:21 I think,
1:25:21 I think governments needs to be,
1:25:23 you know,
1:25:24 we,
1:25:24 we need to work with kind of,
1:25:25 uh,
1:25:26 economists need to work with.
1:25:27 Governments to,
1:25:28 uh,
1:25:28 better figure out like how do we,
1:25:30 uh,
1:25:30 have programs in place that protect,
1:25:33 uh,
1:25:33 or kinda help people deal with kind of challenges of globalizations,
1:25:36 uh,
1:25:37 uh,
1:25:37 which are actually very similar to like kind of the challenges that we face with,
1:25:41 uh,
1:25:41 with,
1:25:41 uh,
1:25:42 technology,
1:25:42 and I think this is where
1:25:43 kind of the partnership between the
1:25:45 trade group and the public finance group,
1:25:47 uh,
1:25:47 and kind of labor group that focuses on,
1:25:49 uh,
1:25:49 you know,
1:25:50 uh,
1:25:50 active labor market policies is actually quite,
1:25:53 uh,
1:25:53 promising.
1:25:54 Thank you.
1:25:57 Thank you very much,
1:25:57 Nina.
1:25:58 Ralph.
1:25:59 Yeah,
1:26:00 thanks.
1:26:00 And I'll be quick,
1:26:01 uh,
1:26:01 not to be too much,
1:26:02 uh,
1:26:03 in the way between you and coffee.
1:26:05 So,
1:26:05 so,
1:26:06 so,
1:26:06 so two points.
1:26:07 The first one on the,
1:26:08 on the gains from trade,
1:26:09 I just want to,
1:26:09 on the articulation of the gains from trade.
1:26:11 I just want to
1:26:12 reiterate what I tried to say in the
1:26:14 presentation that I think the articulation problem that we
1:26:16 face now is a little bit different from the one that we faced in the past.
1:26:19 It's true,
1:26:20 uh,
1:26:21 that we are,
1:26:21 we have a hard time explaining the economic gains in trade.
1:26:24 And I think it's true that,
1:26:25 you know,
1:26:25 we still have that problem,
1:26:26 uh,
1:26:27 now and I have some ideas of how to overcome this,
1:26:29 but I don't think that's the problem at this point.
1:26:31 I think the problem at this point is that people think
1:26:34 that trade is part of the problem
1:26:35 when it comes to overcoming
1:26:37 other key challenges that they're facing today.
1:26:39 So,
1:26:40 for example,
1:26:40 For example,
1:26:40 uh,
1:26:41 achieving a sustainability,
1:26:42 a sustainable economy.
1:26:43 For example,
1:26:44 maintaining peace and security,
1:26:46 and for example,
1:26:47 uh,
1:26:47 achieving,
1:26:48 uh,
1:26:48 or reducing poverty and inequality.
1:26:50 So I think the task today
1:26:52 is to first ask ourselves,
1:26:54 but then also communicate
1:26:55 how trade can be part of the solution
1:26:57 to overcoming these,
1:26:58 uh,
1:26:59 these challenges.
1:27:00 And then second,
1:27:01 Um,
1:27:01 on,
1:27:02 um,
1:27:02 uh,
1:27:03 services.
1:27:03 Um,
1:27:04 I,
1:27:04 I think this is spot on.
1:27:06 So in,
1:27:06 in,
1:27:06 in my view,
1:27:07 the future of trades and services and particularly in digitally,
1:27:11 uh,
1:27:11 delivered services,
1:27:12 we see that,
1:27:12 uh,
1:27:12 in the data also.
1:27:14 And that,
1:27:15 uh,
1:27:15 brings it,
1:27:15 uh,
1:27:15 brings with it a whole,
1:27:16 a host of new questions that I think are also,
1:27:19 uh,
1:27:19 uh,
1:27:20 very important to the World Bank.
1:27:21 So for example,
1:27:22 you know,
1:27:22 trade and inclusiveness.
1:27:23 I think the future,
1:27:24 uh,
1:27:25 inclusiveness problem is that,
1:27:26 uh,
1:27:26 you know,
1:27:27 some developing countries are just having a hard time
1:27:29 to participate in Digital trade simply because there's this big
1:27:33 digital,
1:27:34 uh,
1:27:34 divide.
1:27:34 So I would encourage us to
1:27:36 focus attention on the
1:27:38 inequality problems of the future,
1:27:40 such as this one and not the inequality problems of the past,
1:27:43 such as the ones that have to do with,
1:27:44 uh,
1:27:44 China.
1:27:45 Frankly,
1:27:45 I think that uh shock is over.
1:27:50 Thank you,
1:27:51 Ralph and uh Lionel,
1:27:52 over to you for a very few last words.
1:27:55 OK,
1:27:55 thank you.
1:27:55 This is very embarrassing to have the last words and the more so that uh will
1:28:00 connect with the discussion on how to sharpen the discussion with non-economists.
1:28:04 So,
1:28:05 uh,
1:28:05 what I think is that as
1:28:07 trade economists,
1:28:08 we have our own,
1:28:09 you know,
1:28:09 responsibility.
1:28:11 Uh,
1:28:11 regarding this misunderstanding because,
1:28:14 uh,
1:28:14 most of the literature has been focusing,
1:28:17 so there are exceptions and Nina knows these exceptions,
1:28:20 very well when it comes to
1:28:22 the role of imports,
1:28:24 uh,
1:28:24 in India and other countries in,
1:28:25 in order,
1:28:26 you know,
1:28:26 to increase,
1:28:27 uh,
1:28:28 productivity.
1:28:29 But still,
1:28:29 uh,
1:28:30 if you look at the broad picture,
1:28:31 um,
1:28:31 um,
1:28:32 you know,
1:28:32 a large part of the literature,
1:28:34 uh,
1:28:34 is addressing,
1:28:35 you know,
1:28:36 exporters,
1:28:37 and so this is all about exporters,
1:28:39 uh,
1:28:39 the
1:28:40 The demography of exporters,
1:28:42 the benefit of exporting,
1:28:43 the learning by exporting,
1:28:45 etc.
1:28:46 So which at some point is misunderstood by governments as you know,
1:28:52 the fact that,
1:28:52 you know,
1:28:53 trade is about exporting,
1:28:54 so leading to kind of mercantilist view of trade.
1:28:57 And so I think that we,
1:28:59 we should,
1:29:00 uh,
1:29:00 you know,
1:29:01 uh,
1:29:02 communicate much more
1:29:04 about imports and all the benefits that imports have.
1:29:07 And so after the recent,
1:29:09 you know,
1:29:10 shocks and crises that we have had,
1:29:12 we have seen how imports are so important.
1:29:14 So this is not only about productivity of firms
1:29:17 for the good reasons that we can imagine.
1:29:19 Uh,
1:29:20 overall,
1:29:20 this is also important for households,
1:29:22 etc.
1:29:23 And so if we manage as economists to convince,
1:29:26 you know,
1:29:27 policymakers that imports are really
1:29:29 the way we gain a lot from trade,
1:29:32 we will change definitively demand.
1:29:38 Thank you very much,
1:29:39 Lionel.
1:29:40 Um,
1:29:40 so let's,
1:29:41 um,
1:29:41 uh,
1:29:42 wrap up this first session again with big thanks to our,
1:29:45 uh,
1:29:45 presenters,
1:29:46 Darian Florence,
1:29:47 and,
1:29:47 uh,
1:29:48 another round of,
1:29:49 uh,
1:29:49 thank you also to our,
1:29:50 our panelists,
1:29:51 Lionel,
1:29:52 Ralph,
1:29:52 Nina,
1:29:52 and Yasuyuki.
1:29:54 Uh,
1:29:54 really appreciate,
1:29:55 um,
1:29:56 your contributions to this discussion.
1:29:58 We'll stop now and reconvene at 10:40 for our,
1:30:02 uh,
1:30:02 for our second session.
1:30:04 Um,
1:30:04 so,
1:30:05 thanks very much,
1:30:06 everyone.
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