00:00 Great.
00:00 Ernesto,
00:00 I think we can go ahead and get started.
00:01 It sounds like we have uh
00:03 a few more people connected,
00:04 so over to you.
00:05 Uh,
00:06 thank you,
00:06 Joyce,
00:07 and,
00:07 uh,
00:07 let me start by thanking,
00:09 uh,
00:10 SOIC,
00:11 uh,
00:11 you,
00:11 Joyce,
00:12 and of course,
00:13 the old uh WDR
00:15 24 team
00:17 for inviting me to chair this uh seminar.
00:20 Um,
00:21 as you all know,
00:22 the next WDR will be dealing with economic growth in middle-income countries,
00:28 and
00:29 they have,
00:30 the,
00:30 the team have prepared
00:32 a,
00:32 a series of seminars
00:34 and this one,
00:35 the one that we will have today,
00:37 it's quite important.
00:39 It's distortions and
00:41 uh firm dynamics in middle-income countries.
00:44 As you are aware,
00:46 the economic growth is a very important topic in the economic literature
00:51 and it can be traced back
00:53 many,
00:54 many decades ago,
00:55 but,
00:56 uh,
00:56 some of the most uh seminal works were dated in,
01:00 in 1956 with uh the solo growth model
01:05 and of course,
01:06 after that,
01:06 there had been many important elements
01:09 in trying to explain uh economic growth.
01:13 And I would say that uh there's a,
01:15 a,
01:16 a very nice evolution
01:18 of the economic thought
01:20 and
01:21 uh
01:21 of course,
01:22 most of those uh theoretical explanations
01:26 are dealing with uh economic growth in developed economies
01:31 and
01:31 Uh,
01:32 a little bit less in,
01:34 uh,
01:34 middle-income countries.
01:36 So I think it's,
01:37 it's very,
01:38 very relevant to frame
01:40 this,
01:41 uh,
01:41 uh,
01:41 seminar
01:42 in this,
01:43 uh,
01:44 setting
01:45 so that we can have a better
01:46 explanation of economic growth in middle-income countries.
01:49 Uh,
01:50 I would like uh to thank and welcome
01:53 Uh,
01:53 Roberto Fatal.
01:55 He's a senior economist in the Department of
01:58 Economic Research here at the World Bank,
02:01 and he has a special interest,
02:04 uh among different topics
02:06 in his,
02:07 uh,
02:08 research
02:08 in the role of market extortions on Of course,
02:12 um,
02:13 the firm behavior,
02:15 entrepreneurships,
02:16 and some other elements,
02:18 and of course,
02:19 also in micro and macro
02:22 uh patterns of transition growth,
02:25 uh,
02:25 paths
02:26 and of course,
02:27 the role of credit uh for business cycle.
02:30 So I think uh today
02:32 uh he will present us with this uh very important elements
02:37 about the,
02:38 the distortions that we can see in middle-income countries.
02:41 Probably some of them are
02:43 very relevant as well in developed countries
02:46 but I think distortions might be amplified
02:50 in middle-income countries
02:52 uh without further
02:53 Do,
02:54 I would let the,
02:54 the,
02:55 the floor to Roberto
02:58 and after his presentation,
03:00 we will have an uh questions
03:02 and answer session that will be
03:04 uh
03:05 uh managed by Joyce.
03:07 So if you have questions,
03:09 please uh do it properly
03:11 so we uh can uh handle them
03:14 to Roberto
03:15 to address them.
03:17 Without further ado,
03:18 uh,
03:19 thank you,
03:19 Roberto.
03:20 The floor is yours.
03:22 Thank you,
03:23 Ernesto.
03:23 Uh,
03:23 welcome everyone.
03:25 Bear with me,
03:26 bear with me for a second as I share my screen.
03:40 Hopefully,
03:41 everything is well visible and you can hear me well.
03:44 Otherwise,
03:44 please let me know
03:46 at any point.
03:50 Yeah,
03:50 it's good Roberto,
03:51 we can see it in here.
03:53 OK,
03:53 I'm just trying to get rid of a window here that's popping up.
03:57 Announcing me something.
04:03 OK,
04:03 here we go.
04:04 OK.
04:05 Yeah,
04:05 thank you.
04:05 Thank you,
04:06 everyone,
04:06 uh,
04:07 for connecting.
04:08 Um,
04:09 so,
04:09 the presentation today will be based on
04:11 a couple of research papers I've been working
04:14 over the years and that,
04:16 um,
04:17 as Ernesto was anticipating,
04:18 will inform
04:20 some of the chapters in the forthcoming World Development Report,
04:24 and the topic of interest today is how
04:27 Distortions in low and middle-income countries might be shaping
04:32 firm dynamics in this eco in these economies and ultimately
04:36 uh try to understand how this can help us rationalize
04:40 the vast differences in,
04:42 in economic performance uh
04:44 that we see.
04:45 So,
04:45 let me uh go straight to the main,
04:48 the framing of the presentation.
04:49 I would like to
04:51 Uh,
04:52 contextualize it with what I believe were
04:54 the two most actively researched questions in,
04:57 in the area of micro microeconomics and growth,
05:00 and these are exemplified with these two figures.
05:03 So the figure to the left
05:05 uh motivates the question of what explains
05:09 the large differences in productivity and income across countries.
05:13 So,
05:13 mm,
05:13 uh,
05:14 uh,
05:16 what I'm plotting here is the relative,
05:18 uh,
05:18 total factor productivity of each country
05:21 with respect to the United States,
05:22 both for
05:24 back in the 1970s on the horizontal axis and more recently in 2014,
05:29 and as you can see this,
05:30 there's huge dispersion in,
05:32 in the levels of productivity and
05:33 It has been shown that these
05:36 productivity differences are the most important driver
05:39 um of income differences,
05:41 so that's why I just went straight to,
05:43 to productivity and also it comes out very easily from the picture that this uh
05:48 differences have not gotten
05:50 better over time.
05:52 Uh,
05:52 there are some salient cases of convergence,
05:54 but
05:54 many countries have either stayed where they were 30 years ago or even some have,
05:59 uh,
05:59 receded.
06:01 So that,
06:01 that belongs to the camp of research
06:04 trying to address what explains level differences around the world.
06:08 Now,
06:08 the,
06:08 the figure to the right,
06:09 I,
06:10 I,
06:10 I,
06:10 I hope it can motivate,
06:11 uh,
06:12 or,
06:12 or,
06:12 or um illustrate or make honor to this other area of active research,
06:17 which uh I believe it has been more active in,
06:19 in,
06:19 in academic circles than perhaps has,
06:22 uh,
06:22 as it has been taken up in more policy environment is the idea of
06:26 what explains periods of accelerated growth.
06:30 So in,
06:30 in the field to the right,
06:32 I am plotting,
06:33 um,
06:33 salient cases of um
06:36 Uh,
06:36 fast,
06:37 uh,
06:37 accelerations,
06:38 uh,
06:38 the,
06:38 the solid black line is actually an average
06:42 of all growth accelerations that you can identify from the data
06:46 defined as countries that have managed to
06:49 sustain
06:50 aggregate growth at above 5% for over a decade,
06:54 and I'm accompanying this average with some salient cases that
06:58 are,
06:59 we will be dig uh analyzing in,
07:01 uh,
07:01 with more detail later,
07:02 which is the case of China,
07:04 India,
07:04 and Chile.
07:05 And this is not just GDP,
07:06 this is productivity.
07:07 So these are the things that we want to understand,
07:10 uh,
07:10 and we are usually taking them as exogenous,
07:12 but we want to think about
07:14 what are the channels that explain these accelerations in,
07:17 in,
07:18 in aggregate,
07:18 uh,
07:19 productivity.
07:20 So,
07:21 in,
07:21 in today's talk,
07:22 I,
07:22 I,
07:22 I would like to propose a unifying theme.
07:25 That can connect or speak to these broad areas.
07:28 And the unifying theme are distortions.
07:30 So I,
07:31 I would try to persuade you that
07:33 countries that remain stuck at low or middle income
07:36 levels are so because of persistence
07:40 in,
07:40 in,
07:41 in barriers to the efficient allocation of resources
07:44 in those economies,
07:45 and,
07:46 and
07:47 I think that,
07:47 that idea has sunk uh quite uh broadly within the World Bank.
07:52 That's my perception.
07:53 Uh,
07:54 by,
07:54 by talking to many of you in,
07:55 in,
07:56 in,
07:56 in operational collaboration,
07:58 but
07:59 I would also want to point out something that perhaps is less known,
08:03 which is that
08:04 even in these periods of fast growth,
08:07 they were accompanied and I would argue fueled
08:10 by steep declines in,
08:12 in these distortions.
08:13 So,
08:14 The fate of an economy is to a large extent,
08:17 and that's what I would try to convince you,
08:18 driven by how countries handle
08:21 the perverse incentives that emerge
08:24 that translate into,
08:25 barriers to,
08:26 to resource allocation.
08:28 So the,
08:29 the rest of the talk will be to articulate this,
08:31 this idea.
08:32 First,
08:32 I'm gonna do some conceptual
08:34 uh detour to,
08:35 to,
08:36 to explain the,
08:37 the,
08:37 the,
08:37 the,
08:37 the theoretical framework in very simple
08:40 fashion
08:41 uh that makes
08:43 distortions a plausible theory of TFP,
08:46 uh,
08:46 an endogenous explanation for,
08:48 for total factor productivity,
08:50 and then I will go into quantitatively measuring
08:53 distortions around the world and,
08:55 and over time.
08:56 And just to give you two of the style uh of the salient findings right off the bat,
09:01 so the figure to the left,
09:03 which I think speaks to
09:05 the figure that used to be on the left in the previous slide,
09:07 namely,
09:08 the one that uh thinks about level differences in income.
09:12 What I'm plotting here is one particular measure of
09:15 distortion on the vertical axis,
09:17 and,
09:17 and I will develop what this measure is and how it's constructed.
09:21 Against,
09:21 uh,
09:22 development
09:23 just to
09:24 provide support to the view that indeed the countries that are
09:28 struggling with,
09:28 with overcoming,
09:30 uh,
09:30 um,
09:31 the,
09:31 the,
09:31 the,
09:32 if there is a trap or,
09:33 or,
09:33 or,
09:33 or the,
09:33 the,
09:33 the region of development where they've been
09:36 standing for quite some time,
09:37 it has a lot to do
09:39 with,
09:39 with distortions.
09:40 In their business environments and
09:42 we are,
09:42 uh,
09:43 interestingly,
09:43 so uh as you go
09:45 to the right on the development spectrum,
09:47 you see a strong decline in distortions,
09:49 reassuringly getting to a point where if you are uh an advanced economy,
09:54 there is almost no sign of this particular measure of,
09:57 of,
09:58 uh,
09:58 of misallocation.
10:00 And I believe that
10:01 Uh,
10:01 as I was saying earlier,
10:02 this,
10:02 this fact is somewhat already well received,
10:05 uh,
10:05 uh,
10:05 broadly both in academia and in,
10:08 and policy,
10:08 uh,
10:09 in,
10:09 uh,
10:10 organizations.
10:11 Now,
10:11 to the right,
10:12 uh,
10:13 uh,
10:13 what I think it's less known is that
10:15 this is the same countries that have managed to ignite,
10:18 uh,
10:19 a convergence path
10:20 have done so while having dealt with the
10:23 distortions in their business environments and having partially
10:26 or to a large extent improved them.
10:29 And this is most notably the case in China and Chile,
10:32 which are the solid black and gray lines,
10:35 uh,
10:35 uh,
10:35 a bit less,
10:36 uh,
10:36 convincingly so in India,
10:38 but if,
10:39 if you think,
10:39 if you see carefully,
10:41 despite some cyclical fluctuations that can be rationalized by some shocks,
10:45 there is some trend,
10:46 uh,
10:47 albeit not,
10:48 of course,
10:48 uh,
10:49 a more modest decline,
10:50 uh,
10:51 in distortions.
10:52 So
10:52 this is just
10:53 Anticipating that indeed this unifying view that we want to propose has some bite
10:58 in rationalizing both of these
11:01 big areas of um
11:02 of research.
11:04 So,
11:04 uh,
11:05 let me take a second then to
11:09 To provide you,
11:10 uh,
11:10 a flavor of,
11:11 of the,
11:11 of the theoretical framework that guides the thinking,
11:15 I want to make you,
11:16 uh,
11:17 clear that,
11:18 uh,
11:18 distortions
11:20 through,
11:20 through which channels do distortions become a theory of TFP
11:24 and then I want to uh spell out
11:27 the particular measurement strategy that will be pursued
11:30 to gauge distortions from the data.
11:33 OK.
11:33 So conceptually,
11:34 I,
11:34 uh,
11:35 I think about,
11:36 uh,
11:36 the standard models of endogenous growth.
11:38 So
11:39 for the WDR we've chosen our guiding principle,
11:43 uh,
11:43 or the guiding framework to be the,
11:45 the Schumpeterian model of creative distraction.
11:48 There are,
11:48 what you have is a,
11:49 a frontier,
11:50 uh,
11:50 a production possibility frontier which is pushed
11:53 over time by the innovations of entrants.
11:57 That's how the,
11:57 uh,
11:58 traditionalchumpeterian models viewed growth as
12:01 newcomers displacing old technologies with better knowledge.
12:05 In more modern reincarnations of,
12:08 of,
12:08 of these theories,
12:09 of course,
12:10 entrants as well can respond by joining
12:13 uh the right of innovation and trying to preserve their market shares and,
12:17 and gain.
12:18 Uh,
12:18 markets from competitors,
12:19 so both entrants and incumbents are
12:22 pushing the frontier outwards.
12:24 But what I want to stress is that
12:26 every time we are thinking of firms
12:29 as being,
12:30 uh,
12:31 confronting no kind of headwind from the policy environment.
12:35 We don't think that an entrepreneur that developed a new product
12:38 is going to be distorted by a lack of access to credit
12:43 to leverage that technology and bring capital and hire workers,
12:48 nor we are allowing firms
12:50 to be excessively taxed because of the lack of tax.
12:55 Capacity in less developed countries and therefore the
12:57 concentration of tax enforcement on the large firms,
13:01 none of those possibilities which are realistic and I will show
13:05 actually a fair representation of less developed economies
13:08 are accounted for.
13:09 So,
13:10 we are used to thinking of creative destruction in a purely undistorted context
13:14 and despite this aggregate feature of being on the frontier
13:18 at the micro level,
13:19 uh,
13:20 What we are expected to see in this undistorted uh environment is that,
13:24 you know,
13:25 Firms will not be all alike.
13:27 Some of them would have climbed the,
13:29 the quality ladder further than others,
13:31 and certain industries may be more prone
13:34 to exposing firms to steeper ladders than others.
13:38 So
13:38 at the end of the day,
13:39 there will be some particularly shaped
13:42 size distribution.
13:43 And importantly,
13:44 the,
13:44 the,
13:44 the competitive pressures of the entrance plus the incentives of incumbents to
13:49 uh displace incumbents in other industries,
13:52 what will create is that if you take a snapshot or if you take a movie of,
13:56 of,
13:56 if you were to,
13:57 you know,
13:57 yeah,
13:57 keep track of
13:59 Of a cohort of firms over time in this efficient economy,
14:02 this will be
14:03 a cohort that either through selection or through organic growth,
14:07 they will be growing very steeply over time.
14:09 This is a pattern that
14:10 um has been
14:12 for a shorthand characterization being.
14:14 Labeled it up or out.
14:16 So that's,
14:16 that's what happens
14:17 in an economy like the US,
14:18 whereas
14:19 if you think about the,
14:20 the,
14:20 the,
14:21 the likely situations of countries,
14:23 middle-income countries like India and I could
14:25 have put there in the figure Argentina,
14:27 Mexico,
14:28 Brazil,
14:28 Peru,
14:29 and
14:30 there.
14:31 That's the reason why the report is focused on middle-income countries.
14:34 There's too many of them.
14:35 Is that the most likely the environment for,
14:38 for firms that are already producing is not as
14:41 rosy as it is in the standard model of
14:44 creative destruction.
14:45 There could be,
14:46 you know,
14:47 indeed financial frictions
14:49 that might be uh
14:51 disproportionately more binding for
14:53 young firms that have good and radical ideas but don't have assets to pledge for,
14:58 to the financial system,
15:00 or there could be all these kinds of size-dependent taxes that I.
15:03 was alluding to earlier,
15:05 but
15:05 the outcome will be that
15:07 those capable entrepreneurs will most likely be
15:10 confronting frictions in their ability to achieve efficient scales
15:14 and implicitly that is kind of a subsidy
15:17 to those
15:17 less able entrepreneurs that confront less competition and
15:21 cheaper factor prices so that they can attain
15:24 scales that are beyond what
15:26 uh they would have otherwise in,
15:27 in a competitive in,
15:28 in,
15:28 in a,
15:29 in a scenario without distortions and,
15:31 and,
15:31 and more competition.
15:34 Now,
15:34 that,
15:34 that channel,
15:35 the fact that the economy will,
15:37 will
15:38 waste its potential by producing within the,
15:41 the production possibilities frontier
15:44 is the,
15:44 the,
15:44 the typical misallocation mechanism that we are all somewhat convinced that
15:49 uh that it is important.
15:51 But what I want to stress is this dynamic compounding force that
15:55 distortions also generate and I would,
15:57 as I've been saying,
15:58 I would argue has been less absorbed
16:01 in,
16:01 in,
16:02 in,
16:02 in,
16:02 in policy organizations,
16:03 which is the idea that
16:05 if you think about those innovators or entrepreneurs deciding whether to enter
16:10 or those incumbents deciding on whether to keep investing in their technologies.
16:15 If they are anticipating confronting
16:17 uh
16:18 um
16:19 hurdles
16:20 that are increasing in size and productivity,
16:22 then they will be dissuaded
16:24 to do so.
16:24 So it's
16:25 The,
16:26 the whole production possibility frontier will also be shifted inwards in,
16:30 in economies with distortions and,
16:32 and that's a dynamic channel that
16:34 I will provide evidence of being also very importantly
16:37 at play both in the cross-section when we look at level differences in development
16:42 and more importantly
16:43 uh today with data
16:45 uh along those development paths that I've shown you earlier.
16:50 And to conclude the,
16:51 the,
16:51 this conceptual introduction,
16:52 what you expect at the micro level
16:55 uh uh in a distorted economy
16:58 will be very contrasting with what we discussed uh before for an efficient economy.
17:03 So whatever is the efficient shape of the size distribution,
17:06 what will happen in a distorted economy is that
17:09 capable firms,
17:10 those that would have been large,
17:12 will be less so because of the size-dependent nature of the business environment.
17:16 And over time,
17:18 the steep
17:19 runway of growth that uh
17:22 uh entrants and incumbents confront and,
17:25 and uh as,
17:26 as an outcome of their innovations
17:28 that will be more muted when,
17:30 when distortions are at place uh uh at work.
17:32 So these are some
17:34 simple diagnostic statistics that you can take to the data
17:37 uh as preliminary evidence of the economies being distorted
17:42 that don't require the sophistication of the.
17:45 Inference strategy that I will uh uh
17:48 uh present in a,
17:49 in a few slides.
17:51 So let me then go ahead and
17:57 Uh,
17:57 evaluate whether this,
17:59 let me use the language of an X-ray as,
18:02 a,
18:02 a simple diagnostic tool of what might be going on with the anatomy of an economy
18:07 are already suggestive of distortions.
18:09 OK.
18:10 So let's,
18:11 let's begin with what I've been using as the baseline
18:14 of efficiency.
18:15 Uh,
18:16 I'm not saying that,
18:17 that there are no distortions in the US and,
18:19 and that has been
18:21 A whole area of active research more recently,
18:23 how,
18:24 why has the US
18:25 uh lost some dynamism compared to previous years,
18:28 but I would argue and,
18:29 and I,
18:30 I'm sure that you will agree
18:32 that still in relative terms,
18:33 the United States remains to be,
18:35 uh,
18:36 well open to,
18:37 to the forces of creative destruction.
18:39 So if you look at the life cycle dynamics of firms,
18:42 uh,
18:42 in the US which is not here by the employment.
18:45 Uh,
18:46 of firms of various
18:48 ages
18:49 relative to the employment they had when they entered or in the first,
18:54 uh,
18:54 five years of operation,
18:56 there is very steep increase
18:58 in the average,
18:59 uh,
18:59 size of,
18:59 of cohorts over time,
19:01 achieving like a 7-fold increase over the course of,
19:04 uh,
19:05 4 decades.
19:07 Now,
19:08 if you go to middle-income countries and for today
19:11 uh the data at our disposal allows us to,
19:15 to reproduce this exercise for India,
19:18 for Mexico,
19:19 and for Peru,
19:20 what you see is a very startlingly different picture.
19:23 In all of these economies and again in reflection of
19:27 Distortions that might be at,
19:29 uh,
19:30 at,
19:30 at work.
19:31 The dynamism of the economy is much more muted.
19:34 Firms barely grow in India,
19:35 it's almost a flat,
19:36 uh,
19:37 dynamics,
19:37 and this is with recent data
19:40 reflecting some of the improvements that India has
19:42 done in the last couple of decades.
19:44 If you have done it
19:45 with earlier data,
19:46 the,
19:47 the,
19:47 the,
19:47 the flatness would even be more pronounced.
19:50 Even if it's
19:51 hard to imagine that,
19:52 that can be possible
19:54 and similarly for Mexico and Peru,
19:56 the,
19:56 the,
19:56 the,
19:56 the performance
19:58 of,
19:58 uh,
19:58 of firms,
19:59 at least on this dimension has been
20:01 quite grim.
20:02 Again,
20:03 this is just an X-ray,
20:04 so this doesn't prove anything,
20:05 but it's a,
20:06 it's quite convincing.
20:07 I would argue that,
20:08 that it's,
20:09 that it's a fertile area to look at like uh what are the distortions that might be,
20:13 be generating this,
20:15 OK.
20:15 So,
20:15 that's
20:16 That's just to give you a,
20:17 a,
20:17 a,
20:17 a first diagnostic tool.
20:19 Now,
20:20 I talked about size distributions also
20:23 the shape of them
20:24 being a potential diagnostic tool to assess distortion.
20:27 So let's look at size distributions
20:29 as before.
20:30 Uh,
20:31 let me start with the US.
20:32 So this is the fraction of establishments
20:35 in the US manufacturing sector,
20:37 uh,
20:38 across firms of different sizes and you see that.
20:42 Still,
20:42 small firms are the modal form of production even in an economy like the US,
20:48 but you see how the size distribution sort of reflects this runway towards
20:52 large scale.
20:53 So you have a more uh rather uniform,
20:56 um,
20:57 distribution of firms across various sizes.
21:00 Uh,
21:01 uh,
21:01 expectedly,
21:02 however,
21:02 if you,
21:03 uh,
21:04 overlay
21:05 the size distributions of India,
21:07 Mexico,
21:07 and Peru,
21:08 uh,
21:09 the lack of a runway at the,
21:10 at,
21:11 uh,
21:12 the life cycle,
21:13 uh,
21:13 level translates in a cross-section of sizes
21:16 in this,
21:17 uh,
21:17 microenterprise dominance.
21:20 So essentially,
21:21 firms less than 10 workers account for almost all of the producers in,
21:25 in,
21:26 in Mexico,
21:27 Peru.
21:28 Uh,
21:28 and India.
21:29 So,
21:29 I,
21:29 I,
21:29 I,
21:30 I would say that's quite convincing,
21:31 uh,
21:32 this preliminary view,
21:33 if I were to show you this data and you have none,
21:37 uh,
21:37 expertise in distortion,
21:38 that this will be something you would look,
21:40 uh,
21:40 uh,
21:41 with,
21:41 with,
21:41 you may wanna,
21:42 uh,
21:43 research further.
21:46 So then,
21:47 let,
21:47 let me take on the challenge.
21:49 So let's,
21:49 let's see if we can measure actually
21:52 that there are distortions hindering the
21:54 possibilities of these three and many other
21:57 economies in the low and middle income range.
22:01 So now,
22:01 that begs the question of how,
22:03 how do we do this measurement exercise,
22:05 OK?
22:06 The,
22:07 the most
22:08 traditional approach before uh certain uh developments both on
22:13 the data front and on the structural front.
22:16 The only approach was to say,
22:17 well,
22:18 let's look at the legislation of each country.
22:20 Let's see if we can,
22:21 uh,
22:22 study the labor codes,
22:24 the regulatory,
22:25 the,
22:25 the entry policies for different industries,
22:28 the red tape that firms have to confront to register businesses,
22:32 and,
22:32 uh,
22:33 there are many indicators that are very useful
22:35 because they can be deployed,
22:37 uh,
22:38 at larger scales and,
22:40 and they have some history now in,
22:42 in,
22:42 in the profession.
22:43 The,
22:43 the,
22:43 the PMR stands from
22:45 For the product market regulation of the OECD and
22:49 they're doing business indicators,
22:50 uh,
22:51 soon to be superseded by the business rate indicators by the World Bank.
22:54 So that's one route
22:56 that can give us a flavor.
22:58 An alternative approach is to say,
23:00 well,
23:00 why don't we go ask the firms what they think the problems are,
23:03 how they,
23:04 how they feel about the,
23:06 the financial environment,
23:08 the,
23:09 the functioning,
23:10 the governance,
23:11 and the functioning of institutions,
23:13 and
23:13 that has uh progress that been made also at the World Bank by the Enterprise survey.
23:19 That's progress,
23:19 although,
23:20 uh,
23:20 some scholars uh at the World Bank and uh partnered with,
23:23 with,
23:24 with academics have shown that in,
23:25 if you think about
23:27 How these two approaches correlate,
23:30 there's very little correlation between what you would think
23:33 about the business environment if you ask the firm,
23:35 as if,
23:36 if you look
23:37 at the,
23:37 at the red tapes and the legislation.
23:39 So that keeps you thinking whether we are
23:41 learning anything from either of the two.
23:44 So,
23:45 what,
23:45 what we're gonna pursue today by building on,
23:47 on,
23:48 on,
23:48 uh,
23:49 this is not entirely an innovation of my own,
23:51 but it's building on,
23:52 on a body of,
23:53 of,
23:53 of research
23:54 is to focus instead not on what firms think or say they,
23:58 uh they are facing
24:00 or what the papers say they are facing,
24:01 but just look at the firms' outcomes,
24:03 what they are actually doing.
24:05 And of course,
24:06 for that to be a useful strategy,
24:08 we will have to have a sense of what the firms should be doing,
24:12 so that when,
24:13 if we see firms doing something different than what they should be doing,
24:17 then we can say
24:18 actually that there was a distortion or a policy
24:21 creating that,
24:22 that uh
24:23 differential behavior.
24:26 Of course,
24:27 If we are able to do this successfully,
24:29 I think we would have made a lot of progress relative to the other two approaches,
24:33 but in order to be able to do so,
24:35 we have to rely a lot on
24:37 Economic and mathematical structure.
24:39 So we have to tell in the first place,
24:42 how can we measure the fundamentals of firms.
24:45 We need to say,
24:46 we need to be able to gauge from the data whether the firm is better than the other,
24:50 and that's a non-trivial task,
24:52 although we are gonna rely on some advancements on
24:54 that front to measure productivity from firm-level data.
24:58 But even if you have captured
25:00 those uh fundamental attributes of a firm,
25:03 we still need a theory of efficiency,
25:05 right?
25:05 Uh,
25:06 and that's
25:07 To a large extent,
25:08 gonna depend on what we assume about markets.
25:10 Are they competitive?
25:11 Are they monopolistic
25:13 about production functions,
25:14 how substitutable are uh
25:16 different forms of labor and capital.
25:19 So,
25:19 um,
25:20 all of those challenges will have to be confronted,
25:22 but the payoff potential is very large,
25:23 which is kind of to resolve this,
25:26 this,
25:26 uh,
25:26 crossroads at which the survey-based and the,
25:29 the jury-based analysis of distortions have led us to.
25:32 OK?
25:33 So,
25:33 uh,
25:34 let me give you an example of how would you go about.
25:37 Uh,
25:37 gauging distortions based on firm's outcomes,
25:41 um,
25:41 OK.
25:43 So let's think about a particular industry.
25:45 So uh I've chosen
25:47 uh the manufacturing industry of dairy products,
25:50 which is the four-digit ICIC code 1050
25:54 and let's assume that there are two firms in that industry,
25:56 the firm A and the firm B.
25:58 Then let's assume that I deploy all
26:01 the productivity estimation techniques and we learn
26:04 that the firm A is more productive than the firm B.
26:09 OK,
26:09 so what our the,
26:10 what the theory of efficient that I propose is that,
26:13 well,
26:14 for resources to be allocated such that the output is maximized,
26:18 I would like to equalize the marginal products across these firms.
26:22 So if firm A is more productive than firm B,
26:25 we would like to allocate more resources to such firm.
26:29 Away from firm B so that until,
26:31 and you stop once the marginal products are equalized.
26:34 That's the point where
26:35 there's no other reallocation of resources that
26:37 would keep increasing the aggregate output.
26:40 OK,
26:40 so that's the theory of efficiency
26:42 I would like you to,
26:43 to think about.
26:44 And let's say that that leads to the firm A having to
26:48 hire 300 workers.
26:51 By virtue of being more productive,
26:53 and let's say that firm B
26:55 should have hired 100 workers,
26:57 OK?
26:58 So,
26:58 that's,
26:58 that's the normative implication from the particular
27:01 theory of efficiency under measured fundamentals.
27:06 Now,
27:06 let's suppose on the content that you go to the data and say,
27:09 well,
27:09 how,
27:09 how well are the firms doing
27:11 given this prescription?
27:13 And let's assume,
27:14 uh,
27:15 and this is actually in the direction of what we find,
27:17 that firm A,
27:18 the productive one is smaller than what it would be,
27:21 it's 250 workers,
27:23 and let's assume that firm B is more,
27:25 uh,
27:25 uh,
27:26 it's bigger than what it should be,
27:27 say 150 workers.
27:30 So these gaps between the actual behavior and the,
27:34 and the,
27:34 and the
27:35 optimal behavior
27:37 is what has been revealing.
27:39 The distortions in,
27:41 in,
27:41 in the,
27:41 in the environments or in the industries in which these firms are operating.
27:45 OK.
27:45 So in particular,
27:46 the firm A would be
27:48 as if it was being taxed by some
27:50 distortion that
27:52 uh
27:52 motivates the firm in equilibrium
27:55 to want,
27:55 to want to be
27:56 50 workers smaller than what it would like to be in,
28:00 in a free world,
28:01 in,
28:01 in a,
28:02 in a free of distortions world,
28:04 and conversely,
28:05 firm B
28:06 must be enjoying some sort of policy.
28:10 That uh is allowing her or inducing her to want to attract 50 more workers
28:15 than what she would
28:17 had there been no implicit substance,
28:19 OK?
28:20 So this is kind of the logic in very,
28:21 in very simple works,
28:22 of course,
28:23 there's some formal uh assumptions that we can discuss later,
28:26 but
28:27 at the end of the day,
28:28 if you deploy this methodology,
28:30 uh,
28:31 Across all firms and industries,
28:33 and then if you repeat
28:34 the analysis across countries,
28:35 then
28:36 for each country,
28:37 what this methodology gives you
28:39 is a particular distribution of these implicit taxes and subsidies.
28:44 And then once you have distribution,
28:46 you can
28:47 start computing summary statistics
28:49 and project them on measures of economic performance of the country.
28:53 And that's what I've done in the previous field
28:54 and I'm gonna I've done in the next field,
28:56 which is
28:57 Let me compute,
28:58 for example,
28:59 uh,
28:59 uh,
29:00 how true is it that the large firms
29:03 or the,
29:04 the more productive firms are
29:05 facing more headwinds
29:07 from the environment than the,
29:08 than the least productive firms,
29:10 OK?
29:10 So,
29:11 in other words,
29:11 how true is it that the,
29:13 the,
29:13 the more productive firms are implicitly taxed
29:16 and the less productive firms are implicitly subsidized?
29:19 That will be my
29:20 preferred statistics for today,
29:22 but you can choose many others and,
29:23 and,
29:24 and the patterns will,
29:25 will,
29:25 will go through.
29:33 So,
29:34 this is what the,
29:35 the outcome of this analysis is and,
29:36 and this is the picture I,
29:38 I
29:39 presented to you at,
29:40 uh
29:41 at,
29:41 at,
29:41 at,
29:42 in the introduction.
29:43 So,
29:44 This particular measure of what I call productivity dependent distortions.
29:49 Again,
29:50 distortions that
29:52 translate into the firms that are fundamentally
29:55 more capable of being inefficiently too small
29:58 compared to firms that are less fundamentally able and end up being too big.
30:03 And the,
30:04 the,
30:04 the pattern in the figure is,
30:05 is showing indeed that the most distorted
30:07 economies are the least developed economies.
30:10 We still have some fair degree of distortions in the middle income range,
30:15 uh,
30:15 suggesting that
30:16 on the one hand,
30:17 they are a little bit better.
30:19 To some extent,
30:20 presumably because of the slightly better business environment,
30:23 but
30:24 if you go to advanced economies,
30:25 you see reassuringly,
30:26 as I was saying earlier,
30:27 that,
30:28 that the evidence of these productivity distortions is almo almost not.
30:32 OK?
30:32 So,
30:33 uh,
30:34 this is my piece of evidence to persuade you
30:38 that thinking about distortion has
30:40 an important explanatory power on understanding these,
30:44 these productivity differences.
30:46 Something I,
30:47 I,
30:47 I haven't prepared to show you,
30:48 but I've done in the research papers that informed this presentation is that you can
30:53 think in counterfactual terms.
30:55 Given that this is a model-driven
30:57 uh strategy to read distortions,
31:00 then you can always use the model to say,
31:02 well,
31:02 what would the productivity of these countries be
31:05 had the distortions not been there and how much of the
31:08 TFP gaps I've shown
31:10 in the introduction will be closed,
31:12 and the answer will be that there will be substantial
31:16 Gains to be reaped by alleviating these distortions,
31:19 of course,
31:20 there will be some uh non-trivial amount of the actual gap
31:24 uh pending for an explanation,
31:26 so I'm not saying that distortions are the full story,
31:29 but,
31:29 uh,
31:30 they provide fertile starting points to,
31:33 uh,
31:34 to,
31:34 to dig deeper.
31:37 Now,
31:37 at,
31:37 at this stage,
31:41 I felt you might be wondering,
31:42 well,
31:42 you've said distortions
31:44 about 30 times now or even more,
31:46 but what do you actually mean by them?
31:48 So,
31:49 uh,
31:49 let me take a brief detour by,
31:51 by giving you some examples of specific policies
31:54 that
31:55 behave as this implicit taxes that I read from the firm level data
32:00 that the literature has studied as actually explaining
32:04 non-trivial amounts of these,
32:06 of these metrics of misallocation.
32:08 One example,
32:09 uh,
32:09 studied carefully by uh Manuel Garcia Santana and co-authors.
32:14 Refer to the small scale reservation laws in India.
32:18 So India,
32:19 for a few decades between the 60s and the early or the late 80s,
32:24 they've
32:24 had industrial policies that were geared towards
32:28 uh subsidizing uh uh small scale operations
32:31 and that subsidization schemes to various forms from direct
32:35 credit subsidies to
32:37 specific restrictions
32:39 in certain industries for firms not to exceed a particular scale.
32:44 So you can see immediately that this policy
32:47 directly misallocates resources away from
32:50 potentially large firms into being small
32:52 and dynamically into discouraging firms to want to become uh
32:57 uh you know,
32:58 productive and,
32:59 and,
32:59 and,
33:00 and,
33:00 and,
33:00 and more capable.
33:02 So that's one prominent example of a size or productivity-dependent policy.
33:06 Uh,
33:07 Peru's labor legislation also,
33:09 also has a very clear,
33:11 uh,
33:11 size-dependent feature in it
33:13 that are a host of fixed and marginal costs
33:18 that become binding once firms reach
33:21 the 21,
33:22 uh,
33:22 employee mark,
33:23 and that's been studied by
33:26 Era Do Norris at the IMF and coauthors,
33:28 and they've shown that indeed this policy
33:31 accounts for a lot of the misallocation in Peru and for the lack of firm growth.
33:35 In Peru and then uh Pierre Vachia,
33:37 myself and,
33:38 and,
33:39 and Anders Jensen have looked at
33:41 uh tax enforcement around the world and documented
33:44 indeed that the less developed economies
33:47 have a higher gradient of tax enforcement,
33:50 namely
33:51 increasingly,
33:52 are increasingly more reliant on large firms to collect taxes than
33:57 advanced economies and how,
33:58 of course,
33:59 that
34:00 becomes a disincentive for innovation in the first place.
34:03 And add additional incentive for large firms to,
34:05 to achieve economies of scale in the second place.
34:09 There are many other policies that don't have a by design
34:13 a productivity dependent or idiosyncratic flavor but end up having so
34:19 because of
34:21 firms being heterogeneously capable to circumvent those frictions.
34:25 So,
34:25 uh,
34:26 11 case is financial frictions,
34:27 you know,
34:28 uh,
34:29 credit constraints,
34:30 uh,
34:31 potentially could affect every firm in the economy,
34:33 but
34:34 by virtue of the,
34:35 of the wealth of entrepreneurs and so on,
34:37 some firms might
34:39 Uh,
34:39 avoid being financially constrained at the expense of others.
34:42 That's the,
34:43 the channel in,
34:44 in the Bura Kaboski and the Midrigans.
34:46 And of papers,
34:47 then state-owned enterprises
34:49 are another example that industries where firms are
34:53 uh in more stringent uh competition with uh SOEs and SOEs are shown to be
34:58 uh subsidized in the,
35:00 in the costs that they perceive for their
35:02 financing as shown in Cusolito and Gothers lately
35:06 and,
35:07 and,
35:07 and,
35:07 and in the real resources as shown by
35:10 Uh,
35:10 uh,
35:11 you know,
35:11 a bunch of other uh scholars as
35:14 again becoming a,
35:15 a,
35:15 a,
35:16 a,
35:16 a type of,
35:16 uh,
35:17 distortion that has idiosyncratic uh effects on firms.
35:19 So just
35:20 And just to give you a flavor of,
35:22 of what distortions mean and let me go back
35:24 to treating them in this sort of black boxy word
35:27 that I've been using uh
35:29 until now.
35:30 So now,
35:31 let me turn to what is,
35:32 I believe,
35:32 less known about how distortions shape economic performance
35:36 and that they have an important role
35:38 in helping us understand growth accelerations.
35:42 So this is the figure I showed at the beginning.
35:44 On the left-hand side,
35:45 I'm
35:46 again reproducing the,
35:48 the TFP accelerations of Chile,
35:51 China,
35:51 and India,
35:52 and on the right-hand side,
35:54 I'm
35:55 uh retelling you how
35:57 these growth accelerations have been underpinned
36:01 by notable declines
36:03 in this productivity-dependent distortions that I
36:06 have shown before being very prevalent
36:09 in the cross-section.
36:10 So,
36:11 uh,
36:12 Uh,
36:13 the,
36:13 the,
36:13 the,
36:14 so you see in the figure here,
36:15 I'm just looking at changes in the degrees of distortions and these are
36:19 abstract numbers.
36:20 So,
36:21 uh,
36:21 for Chile,
36:22 the,
36:22 the,
36:23 the period of analysis is,
36:24 is
36:25 Um
36:27 intersects with a period of active reforming in the economy.
36:31 So this is the
36:32 end of the 70s and the beginning of the 80s,
36:35 period where
36:37 political institutions were not in a great place,
36:40 but economic institutions were uh being redirected
36:44 away from state control more into market forces
36:47 and what the data is telling us is that those
36:50 um
36:52 New institutions were prone to a better allocation of resources
36:56 and uh I,
36:57 I would argue that explains
37:00 quite a bit of the outstanding performance the economy had in terms of productivity
37:05 over that decade immediately after uh the reforms
37:09 for China also they have
37:11 continuously been
37:13 uh
37:13 dismantling an economic regime and progressively.
37:18 Uh,
37:19 adopting more liberal policies,
37:20 so the,
37:21 the data reflects that,
37:23 and India perhaps has been the most,
37:25 uh,
37:26 uh,
37:26 disappointing in terms of what
37:28 on paper they've done and what the data shows that
37:32 what they've done translates into actual,
37:34 um,
37:36 uh,
37:37 improvements.
37:38 Uh,
37:38 but still,
37:39 uh,
37:39 I would argue that if you,
37:41 if,
37:42 leaving aside some cyclical aspects,
37:44 India is still making,
37:45 making progress in the direction of,
37:48 uh,
37:48 better incentives for resource allocation.
37:52 Now,
37:53 uh,
37:53 as I was saying in the,
37:54 in the introduction,
37:55 one channel through which these distortions affect the aggregate
37:59 is by putting the economy within the possibilities frontier.
38:02 So if these distortions go down,
38:04 I should be able to tell you that then
38:06 these
38:07 countries are approaching their frontiers.
38:10 It's true that their frontiers might be moving,
38:12 but
38:13 To what extent are,
38:14 uh,
38:15 uh,
38:16 uh,
38:17 the,
38:18 the,
38:18 the economies approaching the frontier,
38:21 uh,
38:21 uh,
38:21 it's something that we can trace,
38:23 uh,
38:23 in,
38:23 in,
38:23 in,
38:24 in,
38:24 in the methodology,
38:25 and that's actually that we can,
38:26 we can see.
38:27 So
38:27 how has the actual TFP fared
38:31 relative to the potential,
38:32 so this ratio is,
38:33 is sort of telling you.
38:35 How much has the economy uh uh approached the frontier and these,
38:39 all these three countries have
38:41 between 10 and 20% closed
38:43 the gap with their own frontiers.
38:45 But I would like to
38:47 show you,
38:48 uh,
38:49 uh,
38:49 uh,
38:50 something that perhaps is less well known,
38:52 which is this dynamic element
38:54 of,
38:55 uh,
38:56 the actual TFP of the firms improving as a result of,
39:00 of,
39:01 a better,
39:02 uh,
39:02 uh,
39:02 business environments.
39:04 And one way to convey you that insight is by
39:07 plotting what was it,
39:09 the TFPQ,
39:10 so these are actual firm capabilities.
39:12 This is the fundamentals.
39:13 I was telling you the example when I said
39:16 firm A was more productive than firm B.
39:18 This is
39:19 the whole distribution of those
39:21 productivities.
39:22 In the case of Chile,
39:23 which is the leftmost,
39:25 uh,
39:26 quadrant,
39:27 the black line captures that distribution at the beginning of the reform period
39:31 and the blue line is towards the end
39:34 of the growth acceleration and,
39:35 and you can see how that,
39:37 uh,
39:38 Uh,
39:39 distribution shifted to the right,
39:41 uh,
39:42 uh,
39:42 uh,
39:43 and,
39:43 uh,
39:44 uh,
39:45 very,
39:45 very notably that's also the case
39:48 in China if you compare these outcomes of this productivities that
39:52 in the early,
39:52 in the late 1990s,
39:54 so like the beginning of the 2000s and towards 2013,
39:57 you see a,
39:57 a,
39:58 a,
39:58 a sharp improvement in,
39:59 in the Chinese economy on the,
40:01 on this front
40:02 and of course consistently with the more muted.
40:05 Uh,
40:06 decline of distortions in India,
40:07 we also see a more muted,
40:09 uh,
40:10 improvement in,
40:11 in,
40:11 in its productivity distribution to the point that it
40:13 makes you question whether there was any improvement whatsoever,
40:17 but,
40:17 uh,
40:18 I would argue that as,
40:19 as we keep,
40:20 or if we would look more granularly
40:22 across different regions and sectors,
40:24 and,
40:24 and this is something we've been looking with.
40:27 With then uh Kartik Narayan,
40:29 a co-author,
40:30 um,
40:30 uh,
40:31 his student from Oxford that,
40:32 uh,
40:33 indeed you find more evidence of this,
40:35 uh,
40:35 improvements in the regions in India where distortions have declined the most,
40:39 but that's,
40:39 that's still,
40:40 uh,
40:41 work,
40:41 uh,
40:41 in progress.
40:43 And the last piece of evidence again in the favor or in,
40:45 in the direction of convincing you that this dynamic response
40:50 of the economy to,
40:51 uh,
40:52 improve the incentives is at work is by looking at patenting activity.
40:57 So,
40:57 what,
40:58 what,
40:58 what I'm going to construct here is I'm gonna go to Google's patenting database.
41:02 Of course,
41:02 patenting is just one
41:04 measure of innovativeness.
41:06 There are many others like uh that,
41:09 and many others that
41:10 would be even more important
41:12 in the initial stages of a growth acceleration
41:15 such as licensing and technology diffusion contracts,
41:19 but this is the one measure that we,
41:20 that we can actually see in the data.
41:22 So what I,
41:23 what I'm computing here is
41:25 how much has the frontier countries in the world,
41:28 the US,
41:29 the Japan's,
41:30 the Canada's,
41:30 and the Germany's
41:32 started citing
41:34 patents developed
41:36 in the fast-growing economies of China,
41:38 Chile,
41:39 India,
41:39 and,
41:39 and brought in Korea as well,
41:41 uh,
41:41 to the analysis,
41:42 OK.
41:43 And I want to compare that to how much these countries have been citing the frontier
41:48 so as to get a sense of whether
41:50 there was more
41:52 incoming knowledge at the beginning of these accelerations
41:56 and a subsequent reversal whereby
41:58 as countries developed and as their own innovation started to pay off,
42:03 they become
42:04 Uh,
42:05 net or
42:06 to some extent contributors
42:08 to the world knowledge frontier.
42:10 OK,
42:10 so this is the ratio that,
42:11 that's been measured on this figure is
42:14 how much is the world
42:15 or the frontier world citing China,
42:18 India,
42:19 and Chile
42:19 relative to
42:21 uh the,
42:21 the,
42:22 the entire uh knowledge flows.
42:25 And what you see is in the US always as the benchmark,
42:28 this ratio is always close to 1.
42:30 So basically,
42:31 the US is always
42:32 uh a net provider of knowledge or uh uh than,
42:35 than it's receiving knowledge from the frontier.
42:38 Uh,
42:39 but in,
42:39 in,
42:40 in,
42:40 in,
42:40 in the,
42:41 in the fast-growing economies under study here,
42:43 we see that they start
42:45 very low value,
42:46 so
42:47 B is the most
42:49 dominant force,
42:50 B being
42:51 the countries citing the frontier to bring in knowledge.
42:54 But eventually over time,
42:56 over the course of their growth accelerations,
42:58 we
42:59 see
42:59 the the share of the,
43:01 the uh uh of the,
43:02 the,
43:02 the rest of the world rely relying on
43:05 domestic patents in these economies starts to rise
43:08 and particularly in the case of China and,
43:10 and,
43:10 and Korea,
43:11 we see that they are
43:12 very close to converging to,
43:14 to the levels um um
43:16 in,
43:16 in,
43:16 in the US.
43:18 So I could conclude here.
43:20 I don't know if I have time to make a few more remarks,
43:22 uh,
43:23 Joyce,
43:23 uh,
43:23 but I wanna give enough time for the discussion,
43:25 so maybe,
43:27 uh,
43:27 I can stop it here and,
43:28 and,
43:29 and open up the floor for Q&A and then maybe
43:31 I can use the questions as an opportunity to show
43:34 uh more results.
43:36 Thank you.
43:48 Please
43:51 Can we move to the question and answer
43:54 uh section?
43:59 Yes,
43:59 but would you like to ask a couple of questions,
44:01 Ernesto?
44:02 should I open it up?
44:05 OK.
44:05 uh,
44:06 first of all,
44:06 thank you,
44:07 Roberto.
44:07 It was very good,
44:09 the,
44:09 the presentation and very
44:12 insightful.
44:13 I think your,
44:14 uh,
44:15 presentation,
44:16 particularly in those distortions that play
44:18 a bigger role in,
44:19 in growth in middle-income countries,
44:22 uh,
44:22 shed good light
44:23 in explaining
44:25 why the uh growth in middle-income countries may be slower
44:30 than normally what you would see in developed countries.
44:33 I would like to uh put uh two questions,
44:36 Roberto.
44:37 The first one is if
44:39 do you think that productivity
44:41 and growth
44:43 are driven largely by incumbents
44:46 or do incumbents and entrants
44:49 have
44:50 in a,
44:51 a symbiotic manner?
44:53 I think uh this is very important
44:56 because as mentioned in the presentation,
44:59 uh,
45:00 You can say that larger distortions
45:03 are observed in less developed countries
45:06 and I would say that probably large firms may benefit
45:11 for those distortions as well.
45:14 Uh,
45:14 the second question would be that if you think
45:19 about,
45:19 uh,
45:19 a country like Mexico,
45:21 if there are some reasons behind why large firms
45:27 end up acting
45:28 like predators.
45:30 As opposed to
45:33 driving change.
45:34 Uh,
45:35 so that would be my two questions and,
45:37 and then
45:38 I,
45:38 I invite all of the
45:40 participants to share
45:42 your questions as well.
45:43 Thank you.
45:48 So Joyce,
45:49 should I give it a shot at these two,
45:50 or you want to collect a couple more?
45:53 Up to you.
45:53 Should I collect a few more,
45:55 or do you prefer to answer?
45:56 Well,
45:56 I,
45:56 I,
45:56 I,
45:56 I,
45:57 I can,
45:57 I can proceed because actually,
45:59 uh,
46:00 Ernesto leads me nicely to what I was gonna present if I had more time,
46:04 which is essentially
46:06 to,
46:07 to venture.
46:08 I mean this is
46:09 all,
46:09 uh,
46:10 uh.
46:11 Not purely conjectural,
46:12 it's,
46:12 it's motivated by,
46:13 by the analysis,
46:15 but,
46:15 uh,
46:15 but I want to,
46:16 uh,
46:17 make a few remarks with regards to
46:19 the relative role that entrants and incumbents might play,
46:23 um,
46:24 in,
46:24 in,
46:24 in shaping productivity growth,
46:26 and I think that
46:27 as I was alluding to initially,
46:29 the aspiration of an efficient economy would be
46:33 to all actors of the economy contribute in a symbiotic way to innovation,
46:37 you know,
46:37 so.
46:38 To combine the standard Jumpeterian view of the
46:40 entrants being the ones that displace incumbents,
46:43 but then the more modern
46:45 view where incumbents are endowed also with the same labs and incentives
46:50 to,
46:50 I mean,
46:50 the,
46:51 the incentives to build the labs of their own to actually compete
46:54 or deter entrants or join them
46:57 uh in the directions that entrants are doing.
46:59 Now,
46:59 I think that's,
47:00 that's an aspiration and that's definitely
47:03 uh the way uh the US economy works and that's why so many
47:08 Um,
47:08 you know,
47:09 in the,
47:09 in the press,
47:09 in policymakers,
47:10 they're so worried that
47:12 dynamism through entry in the US is so,
47:15 so slow,
47:16 but I think that in the,
47:17 in,
47:17 in,
47:17 in the economies that are stuck in the middle income
47:20 range and that are thinking about how to ignite growth,
47:24 my
47:25 prediction based on,
47:26 on what I see in the data and through models that interpret the data is that
47:31 Initially,
47:32 most of the entrants that already,
47:34 you know,
47:34 most of the entrepreneurial activity in this economies of the low,
47:37 is kind of a low quality.
47:39 So,
47:40 um,
47:40 they have little dynamism to begin with.
47:43 Most of the entrants don't grow as I showed you,
47:45 so that suggests,
47:47 uh,
47:48 little incentives to,
47:50 uh,
47:50 keep building on the entrepreneurial spirits and,
47:53 and capabilities,
47:54 and there may be exogenous reasons as well,
47:56 but
47:58 Definitely the environment is not favoring that.
48:01 However,
48:02 I I've also shown you that those
48:06 Capable firms that have high technologies,
48:08 better technologies
48:09 are the ones that are suffering the headwinds
48:12 from the policy environment and they sort of leaving
48:15 uh uh um unused potential on the table.
48:19 So what I,
48:20 what I,
48:21 what I've seen in,
48:21 in India,
48:22 in,
48:22 in,
48:23 in Chile uh and,
48:24 and,
48:25 and uh more,
48:26 more prominently
48:27 is that when distortions were dismantled,
48:29 it were those incumbents that had some
48:32 advantage of having somehow managed to thrive
48:35 in those webs.
48:36 of distortions
48:37 that will continue to,
48:38 you know,
48:39 to take off even further
48:41 once those constraints were unleashed.
48:43 So I have some
48:44 data here looking at the famous,
48:47 famous because of precisely how dynamic it's become.
48:50 This is
48:52 the business services industry in India
48:55 and this is an industry that didn't exist up until the 70s.
49:00 And in,
49:00 in that time,
49:01 India wasn't very welcome to,
49:03 to large firm or to,
49:04 to productive firms to,
49:06 to,
49:06 to invest in innovations.
49:08 It took an incumbent which is the,
49:10 the Tata
49:11 uh business conglomerate,
49:13 which is the,
49:13 the,
49:14 the,
49:14 the,
49:15 the um
49:16 The purple line here
49:18 that had the resources to circumvent the financial frictions,
49:21 to circumvent the foreign exchange restrictions at the time,
49:25 but had the
49:26 vision to say,
49:27 well,
49:27 I have a bunch of good engineers in India,
49:30 and I have all the world
49:32 becoming more demanding of computers.
49:35 Why don't we
49:36 sell the world these services?
49:38 And they basically built an industry out of the ground,
49:42 uh,
49:42 circumventing all the frictions and
49:44 A few years later,
49:46 when,
49:46 when
49:47 India started
49:48 becoming more
49:49 open to,
49:50 to,
49:51 to capital flows,
49:52 to credit,
49:53 and so on,
49:55 the industry became very competitive.
49:56 So,
49:57 uh,
49:57 then you have here,
49:59 this is the dynamics of employment of a newcomer to
50:01 the industry that came 20 years later with this Infosys,
50:05 and you see how Infosys has sort of become a neck to neck
50:08 fighter to,
50:09 to the incumbent.
50:10 So
50:10 just to
50:12 conclude this very long answer,
50:13 I think that
50:15 it's quite likely that incumbents gaining
50:18 More traction as soon as they
50:21 face
50:22 a better environment is,
50:23 is a likely outcome
50:24 and eventually we would expect the entrants to catch up and,
50:28 and start putting pressure.
50:29 So the,
50:30 the policy challenge,
50:31 I would argue for policymakers is,
50:33 is how to manage that incumbency advantage
50:36 and keep it like it happened in,
50:38 in India's business.
50:39 The sector
50:40 in the direction of innovation
50:42 as opposed to what is happening in many industries in Mexico where it's become
50:47 more,
50:47 less costly to just
50:49 connect with the policymaker in town and,
50:52 and instead of innovate your way up,
50:54 that you just
50:55 uh block the competition to,
50:57 to keep preserving your profits.
50:58 That,
50:59 that's kind of my,
51:00 my answer to,
51:01 to your two questions.
51:05 Thank you,
51:06 Roberto.
51:07 Joyce,
51:08 do,
51:08 do we have questions from our,
51:10 uh,
51:10 participants?
51:13 Uh,
51:13 I don't see any,
51:14 but I think we have a few more minutes.
51:15 So if you'd like to ask a question,
51:17 please feel free to,
51:18 to raise your hand.
51:20 And I'll call you,
51:21 or if you'd like to put it in the chat,
51:23 uh,
51:23 that works too.
51:25 You see Jaafar.
51:27 It's asking
51:30 So far,
51:30 go ahead.
51:32 Hi,
51:32 Roberto.
51:33 Thanks,
51:33 thanks for a very interesting presentation.
51:35 I,
51:35 I want to uh ask you a question that links um two aspects of your presentation.
51:40 You,
51:41 you gave us a sort of a,
51:42 a framework for,
51:44 for
51:44 how you define,
51:45 um,
51:46 and,
51:46 and,
51:47 and measure um distortions and then you gave us
51:51 a sort of a slide that brought that down to earth.
51:54 And,
51:54 and basically said these are examples of actual,
51:57 uh,
51:58 actual distortions.
51:59 And,
51:59 so my,
52:00 my,
52:00 my follow-up question to that is
52:03 whether in the WDR or,
52:05 you know,
52:05 previous supporting work,
52:07 uh,
52:07 are you doing any causal work that looks at,
52:10 uh,
52:11 policy reforms,
52:13 um,
52:13 uh,
52:14 uh,
52:14 you know,
52:14 in specific countries where some of the distortions you described
52:17 are reformed
52:19 and then see what is the impact on your measure of
52:23 Uh,
52:23 you know,
52:24 distortions and productivity.
52:25 Do you,
52:26 can you track that
52:27 when I reform,
52:29 say,
52:29 size-dependent taxation,
52:31 the result is
52:33 lower distortions according to my measure and higher productivity.
52:44 Roberto,
52:44 should we take a few
52:45 questions?
52:46 Yeah,
52:46 I see Artie is raising her hand.
52:48 Uh,
52:49 I can take Artis and then.
52:51 Reply and then if there are more.
52:53 And sorry,
52:54 just RT before you come in,
52:55 Rhi also just had a,
52:57 a clarification in the chat.
52:58 Are the firms you selected for analysis in developing countries like India,
53:02 Chile,
53:03 and China registered firms,
53:05 the informal sector in these countries,
53:07 particularly India's,
53:08 is quite large,
53:09 and with this aspect,
53:10 um,
53:11 the informality of enterprises affect the results in,
53:13 in any way.
53:14 Um,
53:15 so if you could just also address that,
53:16 um,
53:16 and RT,
53:17 go ahead and,
53:18 and come in as well.
53:19 Thanks.
53:21 So thanks,
53:22 Roberto.
53:22 This is really an interesting presentation.
53:25 I had one quick question.
53:27 So as you showed us these uh numbers or
53:30 uh
53:32 Uh,
53:32 ways to measure misallocation,
53:34 I guess it's mostly on the output market.
53:37 Do you also have some way to measure misallocation on the input market?
53:42 So,
53:43 and especially when I look at the graph
53:45 that you showed for services and how innovators.
53:48 could basically
53:49 supersede um incumbents in a very short span of time.
53:54 The example of VPro and Tata.
53:56 It seems to me like
53:58 the sources of distortion in manufacturing
54:01 could have been very different than the sources of
54:04 misallocation in the services industry.
54:07 In particular,
54:08 in India,
54:08 land markets are very mis uh misallocated.
54:12 Uh,
54:13 but labor market or labor
54:15 was generally less so,
54:17 and then over a period of time,
54:19 land markets
54:21 continued to remain misallocated or distorted.
54:25 But labor regulations had changed over time.
54:28 And since
54:29 land is much more important and manufacturing is
54:33 more intensive in land and the services,
54:36 so maybe input market distortions or the differences in
54:40 what is used as an input in the two
54:41 industries could be an important explanatory variable as well.
54:45 Thanks.
54:52 I see there's one more question from Omar.
54:54 Should we,
54:55 do you want to answer Roberto,
54:56 or other ones?
54:58 Let me answer the three,
54:59 otherwise,
55:00 yeah,
55:01 so I think it's easier,
55:02 uh,
55:03 so thank you,
55:04 Jaffar.
55:04 Um,
55:06 yes,
55:06 indeed,
55:06 um,
55:08 in the report,
55:09 we,
55:09 so the literature has grown in this direction of trying to
55:13 leverage some policy reform.
55:16 That in some
55:18 econometrically useful way so that you can tease out some causal interpretation.
55:23 There is a paper by Natalie Bao and Adrian Matrai,
55:27 uh,
55:28 recently published in Econometrica looking in at India
55:32 specifically,
55:33 and India has
55:35 protractedly and
55:37 arguably randomly or unpredictably
55:40 uh opened certain industries to
55:43 To foreign capital
55:45 and they've shown that as a,
55:47 as a way to see whether the industries where that happened
55:51 showed uh a disproportionate decline in capital misallocation
55:56 and they do find that causal evidence to be very prominently uh um
56:01 at work uh there.
56:02 Um,
56:03 I believe,
56:04 I don't know from the top of my mind,
56:05 but,
56:06 um,
56:07 so.
56:09 Some,
56:09 some work.
56:11 Against the lack of uh an econometrically useful scenario,
56:15 do some counterfactuals
56:17 within the concept of a model,
56:19 and that's not the best way to go,
56:21 but in a counterfactual sense,
56:22 you can see.
56:23 Whether
56:24 uh the mechanisms through which
56:27 a policy change would uh
56:30 affect,
56:30 affect outcomes
56:32 indeed uh happened that way in the data and,
56:35 and that's something that uh the,
56:36 the,
56:36 the papers I've cited before,
56:38 uh,
56:39 looking at reservation laws in India and uh size-dependent policies in
56:43 Uh,
56:44 more broadly and more globally do with that,
56:46 with that flavor and there is evidence that,
56:48 that,
56:48 those,
56:49 those policies were affecting economic outcomes
56:52 through these,
56:53 these channels.
56:54 Um,
56:55 but yeah,
56:55 so that's,
56:56 that's exactly where
56:58 many of the subsequent papers have made contributions trying to
57:02 Uh,
57:03 look at episodes of reforms that allow for that,
57:06 uh,
57:06 nice causal,
57:07 uh,
57:07 identification.
57:10 The,
57:10 the question about informality,
57:11 uh,
57:12 I,
57:12 I appreciate it,
57:12 it,
57:13 it allows me to clarify.
57:14 Definitely,
57:15 uh,
57:16 the size distributions in particular
57:18 are very heavily influenced by the capturing of those informal sectors.
57:23 Uh,
57:23 in the WDR and,
57:25 and in the papers that I've,
57:26 uh,
57:26 based this presentation
57:28 on,
57:28 I've
57:29 also shown that there are
57:31 notable differences in,
57:32 in firm sizes even when you
57:35 constrain on 10 more workers,
57:37 which
57:38 More confidently,
57:39 you can say that
57:40 those are the formal firms
57:42 and,
57:42 and,
57:43 and they are,
57:44 uh,
57:45 it's still true that,
57:46 that less developed economies have more stagnant and smaller firms.
57:50 Now,
57:50 the,
57:50 the distortion inference exercise is purely based on formal firms.
57:55 So,
57:55 if that helps in any way,
57:57 uh,
57:57 to feel more reassured then that,
57:59 that's a,
57:59 a clarification I wanted to make.
58:01 And Arti,
58:02 uh,
58:02 yeah,
58:03 definitely.
58:05 So in a way,
58:06 once you are on board with,
58:07 with the approach,
58:08 then you might wonder,
58:09 well,
58:09 I like this idea,
58:10 distortions are important,
58:12 maybe uh
58:14 a sec,
58:15 certain sectors
58:17 would show up in the data as distorted in different markets.
58:21 Let me just point out that
58:23 the measure of distortions I've shown you is like a
58:26 Like an aggregate of factor distortions,
58:29 those that alter the capital labor ratio
58:32 and output distortions,
58:34 those that affect the,
58:35 the entire sort of um
58:38 scale of a firm,
58:39 if we have had a more richer decomposition of production factors in,
58:44 in the data,
58:46 then you could have contrasted
58:48 the data with a richer structure,
58:49 you know,
58:50 with the production function that doesn't just have one type of label,
58:53 you can have heterogeneous labels.
58:55 And then you can go the extra step of seeing if the,
58:58 the misallocation is
59:00 disproportionately affecting certain factors
59:03 more than others.
59:04 Um,
59:04 I agree with you that uh land markets,
59:07 if,
59:07 if land was a production factor,
59:09 uh,
59:09 a factor,
59:09 uh,
59:10 uh,
59:10 would pop up as being more relevant,
59:12 uh,
59:13 uh,
59:13 than in services.
59:14 Uh,
59:14 but
59:15 I take your question as to saying,
59:17 well,
59:17 As we gather more data,
59:19 let's keep thinking in these lines because that's where
59:22 hopefully we can make progress to pinpoint where the actual
59:25 policy friction lies.
59:27 That's,
59:27 that's how I,
59:28 I interpret your question,
59:29 Arti.
59:31 Thank you,
59:31 Joyce.
59:32 Great,
59:33 thanks,
59:33 Roberto.
59:33 Um,
59:34 I'm sorry,
59:34 we are out of time,
59:35 so I do want to just make a couple of
59:36 announcements for those that need to go and then Omar,
59:39 I,
59:39 I'll let you come in after if Roberto's willing to stay,
59:42 um,
59:43 a few,
59:43 a few extra minutes.
59:44 So,
59:45 um,
59:45 so tomorrow,
59:46 uh,
59:46 Indra McGill,
59:47 our,
59:47 our chief economist,
59:48 will be giving a talk,
59:50 um,
59:50 at a very large academic conference in India.
59:53 It will be actually chaired by The chief economic advisor
59:56 of the government of India and um it will be streamed on Zoom.
1:00:00 So we do have the registration link on our website
1:00:04 under the events page,
1:00:05 um,
1:00:06 so,
1:00:06 you know,
1:00:06 please feel free to,
1:00:07 uh,
1:00:08 to go in and,
1:00:09 and it will be in the morning,
1:00:10 uh DC time.
1:00:10 It's actually in the evening India time.
1:00:12 So for those that are interested,
1:00:13 uh,
1:00:13 please feel free to register through that,
1:00:15 um,
1:00:15 through that link.
1:00:17 Um,
1:00:17 and then just a couple of,
1:00:19 uh,
1:00:19 previews for our next seminars next week.
1:00:21 It's,
1:00:21 um,
1:00:21 going to be on higher education for social mobility
1:00:25 and talent development with a focus on Chile,
1:00:27 and that will be,
1:00:28 um,
1:00:28 chaired by,
1:00:29 um,
1:00:30 Ms.
1:00:30 Najon,
1:00:30 the,
1:00:31 um,
1:00:31 the ED for,
1:00:32 for Argentina.
1:00:33 So same time next Wednesday at 12:30,
1:00:35 also on our Website and the announcement will go out soon and
1:00:37 then the seminar the week after is on trade firms and,
1:00:40 and economic development um
1:00:43 by Yng Hongh from the um from the IMF
1:00:45 um so hope you can join and um
1:00:48 with that again for those that need to log off,
1:00:49 uh,
1:00:50 we understand,
1:00:50 but Omar,
1:00:51 I do want to give you a chance to uh to ask your question for,
1:00:53 for those that,
1:00:54 uh,
1:00:55 can stay on.
1:00:56 So please go ahead.
1:00:59 Thank you,
1:00:59 uh,
1:01:00 Joyce and,
1:01:01 uh,
1:01:02 thank you,
1:01:02 uh,
1:01:02 Roberto,
1:01:03 uh,
1:01:04 for this very interesting presentation.
1:01:05 It's good to see some results,
1:01:07 uh,
1:01:07 we,
1:01:08 we,
1:01:09 uh,
1:01:09 had the chance to touch base.
1:01:11 Um,
1:01:11 now my question actually is,
1:01:13 um,
1:01:13 if you remember when we were chatting,
1:01:15 uh,
1:01:16 one of the,
1:01:16 the questions I have,
1:01:19 uh,
1:01:19 was,
1:01:20 you know,
1:01:20 related to the trade-off between,
1:01:23 uh,
1:01:23 improvements in productivity and
1:01:26 employment.
1:01:27 Uh,
1:01:27 and so what I'm wondering is if in the analysis you've
1:01:30 done so far in the simulations of what happens when,
1:01:34 uh,
1:01:35 you know,
1:01:35 distortions improve or in these,
1:01:37 uh,
1:01:37 growth acceleration
1:01:39 episodes,
1:01:40 uh,
1:01:40 what,
1:01:40 what actually happens with employment because part of the reason why you see these,
1:01:44 um,
1:01:45 Sort of lopsided,
1:01:47 um,
1:01:48 you know,
1:01:48 size distribution of firms is because
1:01:51 those small firms tend to create,
1:01:52 uh,
1:01:53 more employment.
1:01:54 It's low productivity employment,
1:01:56 yet,
1:01:56 you know,
1:01:57 um,
1:01:57 you know,
1:01:58 there's a value to having those jobs,
1:02:00 and,
1:02:00 uh,
1:02:00 oftentimes the political economy of
1:02:03 doing the reforms that one would need to do,
1:02:06 including actually enforcement,
1:02:08 uh,
1:02:09 you know,
1:02:09 of,
1:02:09 um,
1:02:10 uh,
1:02:10 uh,
1:02:11 informal firms that escape,
1:02:13 uh,
1:02:13 taxation and regulation.
1:02:14 are very politically difficult
1:02:17 because there will be a,
1:02:18 a price in terms of employment destruction which uh
1:02:21 may create uh uh uh issues with,
1:02:24 you know,
1:02:24 political stability.
1:02:26 So what is happening with employment at the same
1:02:28 time that productivity is improving when distortions are removed?
1:02:32 Thanks.
1:02:33 Excellent,
1:02:34 Omar,
1:02:34 thank you.
1:02:34 And uh you just reminded me that uh I should have added that figure.
1:02:39 So the,
1:02:39 the,
1:02:40 what actually happens and,
1:02:41 and that's exactly the mechanism that um
1:02:45 That that's exactly consistent with the mechanism is that
1:02:48 as distortions are improving,
1:02:50 the,
1:02:51 the firms that
1:02:52 actually benefit from that improvement immediately higher.
1:02:55 So you see
1:02:56 the average firm,
1:02:57 so you see the employment
1:02:59 being reallocated progressively towards larger firms
1:03:02 and you can document this by just looking
1:03:05 at the average firm size in the industry
1:03:08 um or the employment concentration at the top end of the distribution.
1:03:13 So,
1:03:14 indeed,
1:03:15 The,
1:03:15 the flourishing in the firms
1:03:18 start to absorb some of the
1:03:20 either labor force that was
1:03:23 sunk into less able firms
1:03:26 or even the entrepreneurs themselves that I cannot
1:03:28 tease out,
1:03:29 so we do see a reduction in the overall number of firms,
1:03:32 particularly in India and,
1:03:34 and Chile.
1:03:35 The case of China is very different in this regard.
1:03:38 Uh,
1:03:38 uh,
1:03:39 because India is coming from a different equilibrium,
1:03:41 right?
1:03:41 Indeed,
1:03:41 they have a lot of
1:03:43 allocative distortions,
1:03:44 but they have a very strong entry barrier,
1:03:46 which is,
1:03:47 you have to be a government firm to produce
1:03:50 and that was
1:03:51 protractedly reversed,
1:03:53 so
1:03:53 you might still see
1:03:55 a lot of the small firms coming into India,
1:03:57 uh,
1:03:57 sorry,
1:03:57 to China,
1:03:58 um.
1:04:00 But in the other countries,
1:04:01 it's indeed the case that
1:04:03 the,
1:04:03 the,
1:04:03 the,
1:04:03 the flourishing firms absorb
1:04:06 the labor force that,
1:04:07 and,
1:04:07 and that's actually the reason why allocative efficiency was,
1:04:10 was getting better.
1:04:11 So I would say that
1:04:13 the firms
1:04:14 that get their constraints relaxed immediately converge to the new efficient
1:04:18 level consistent with whatever is the new degree of the constraint.
1:04:22 The constraint doesn't go all the way to zero as we saw,
1:04:25 they decline,
1:04:26 but they don't go all the way to zero.
1:04:28 So the firm immediately goes there
1:04:30 and then subsequently starts investing in these dynamic forces that
1:04:35 uh improve the fundamentals and eventually lead to even more hiring.
1:04:39 So,
1:04:39 definitely,
1:04:40 the employment channel is,
1:04:41 is very
1:04:42 uh important for,
1:04:43 for accounting for the gains of
1:04:46 uh reducing distortions.
1:04:54 Well,
1:04:54 uh,
1:04:54 thank you,
1:04:55 thank you very much all of you for attending this,
1:04:58 uh,
1:04:58 seminar.
1:04:59 I would like to thank you,
1:05:00 Roberto,
1:05:01 for
1:05:02 giving a lot of light in,
1:05:03 in the issues of,
1:05:04 uh,
1:05:05 trying to understand better
1:05:07 the growth in middle-income countries.
1:05:09 You touch upon endogenous growth,
1:05:11 uh,
1:05:12 behavioral economics,
1:05:13 and how distortions
1:05:15 are affecting the allocation of resources.
1:05:18 Of course,
1:05:19 The allocation of
1:05:21 uh technology
1:05:23 adaptations and uh promotions.
1:05:25 So I think uh all of the elements that you have uh mentioned
1:05:29 will help us here at the World Bank
1:05:32 to try to design better public policies
1:05:35 to help
1:05:36 middle-income countries
1:05:37 to have a higher
1:05:39 uh rates of economic growth,
1:05:41 more persistent
1:05:43 and more sustainable as well.
1:05:45 Thank you all for attending.
1:05:47 Thank you very much.
1:05:48 Thank you,
1:05:49 Ernesto.
1:05:49 Thank you,
1:05:50 everyone.
1:05:53 Thank you,
1:05:54 Joyce.
1:05:54 Bye-bye.
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