1 00:00:05,860 --> 00:00:09,568 Speaker 1: Hello, this is Kobe Time, a podcast series on Markets 2 00:00:09,579 --> 00:00:12,239 Speaker 1: and Economies from D BS Group Research. I'm Tamur Big 3 00:00:12,289 --> 00:00:17,270 Speaker 1: chief economist, welcoming you to our 130th episode. Today we 4 00:00:17,280 --> 00:00:20,799 Speaker 1: have a first for copy time. After over four years 5 00:00:20,809 --> 00:00:23,790 Speaker 1: of running the show, we have the first instance of 6 00:00:23,799 --> 00:00:26,780 Speaker 1: two people from the same household grace. This show on 7 00:00:26,790 --> 00:00:30,170 Speaker 1: separate occasions. Back in 2023 we had World Bank South 8 00:00:30,180 --> 00:00:34,000 Speaker 1: Asia chief economist Francisco Zorg on episode 113. 9 00:00:34,360 --> 00:00:38,740 Speaker 1: And for this episode, we have her husband Shekher is 10 00:00:38,750 --> 00:00:42,330 Speaker 1: a non-resident fellow at rural, a visiting scholar at the 11 00:00:42,340 --> 00:00:45,528 Speaker 1: Johns Hopkins School of Advanced International Studies and a visiting 12 00:00:45,540 --> 00:00:48,000 Speaker 1: professor at the National Council of 13 00:00:49,909 --> 00:00:54,369 Speaker 1: Applied Economic Research and C er until 2023 shaker held 14 00:00:54,380 --> 00:00:56,750 Speaker 1: a number of senior physicians in the International Monetary Fund. 15 00:00:56,759 --> 00:01:00,029 Speaker 1: More recently as division chief in the research department where 16 00:01:00,040 --> 00:01:02,889 Speaker 1: he helped coordinate the fund's monitoring of the global economy 17 00:01:02,970 --> 00:01:05,489 Speaker 1: and liaise with the international groups such as the G 18 00:01:05,500 --> 00:01:08,919 Speaker 1: 20 G7 shaker. A warm welcome to Kobe time. 19 00:01:10,010 --> 00:01:11,839 Speaker 2: Thank you. Demo. Very nice to be 20 00:01:11,849 --> 00:01:12,190 Speaker 2: here. 21 00:01:12,639 --> 00:01:16,550 Speaker 1: It's great to have you and Shekhar. I am really 22 00:01:16,559 --> 00:01:20,369 Speaker 1: keen to talk about two of your recent research output. 23 00:01:20,510 --> 00:01:23,589 Speaker 1: Uh early last year, you and your colleagues at the 24 00:01:23,599 --> 00:01:27,399 Speaker 1: IMF released a note on geo economic fragmentation, which subsequently 25 00:01:27,410 --> 00:01:31,709 Speaker 1: became several notes and papers. So let's begin with you 26 00:01:31,720 --> 00:01:34,750 Speaker 1: explaining what geo economic fragmentation means. 27 00:01:35,629 --> 00:01:39,669 Speaker 2: Sure. Um So if you look at global flows of 28 00:01:39,680 --> 00:01:43,010 Speaker 2: goods and capital, you'll find that they've plateaued since the 29 00:01:43,019 --> 00:01:46,879 Speaker 2: global financial crisis services continue to rise from a small 30 00:01:46,889 --> 00:01:51,480 Speaker 2: base but goods uh and FD I have plateaued at 31 00:01:51,489 --> 00:01:54,730 Speaker 2: the same time when you look at trade restrictions, they've 32 00:01:54,739 --> 00:01:58,250 Speaker 2: been rising very steeply. And since well before the pandemic, 33 00:01:59,029 --> 00:02:01,309 Speaker 2: if you look at the number of new trade restrictions 34 00:02:01,319 --> 00:02:04,290 Speaker 2: that are being imposed in 2022 35 00:02:04,629 --> 00:02:08,320 Speaker 2: there were almost 10 times as many trade restrictions imposed 36 00:02:08,490 --> 00:02:11,979 Speaker 2: as the flow of trade restrictions about one decade ago 37 00:02:11,990 --> 00:02:16,399 Speaker 2: in 2012. Um This is happening at a time when 38 00:02:16,410 --> 00:02:19,960 Speaker 2: geopolitical concerns are rising to the forefront all over the 39 00:02:19,970 --> 00:02:24,089 Speaker 2: world on a number of different issues, whether it's Russia, Ukraine, 40 00:02:24,100 --> 00:02:27,600 Speaker 2: whether it's the Middle East. Um And this is, this 41 00:02:27,610 --> 00:02:29,729 Speaker 2: can again be be seen tangibly in 42 00:02:29,809 --> 00:02:33,209 Speaker 2: the economic sphere. For example, the IMF releases every year, 43 00:02:33,220 --> 00:02:38,228 Speaker 2: a report on every single country's exchange rate restrictions. If 44 00:02:38,240 --> 00:02:42,149 Speaker 2: you look at recent reports and see how many times 45 00:02:42,160 --> 00:02:45,788 Speaker 2: the the the there is mention of the word national security, 46 00:02:45,970 --> 00:02:48,940 Speaker 2: this has been rising very steeply. So you can see 47 00:02:48,949 --> 00:02:51,750 Speaker 2: that this is coming to the forefront of policy discussions. 48 00:02:52,089 --> 00:02:55,888 Speaker 2: Um If you look at earnings calls from the corporate sector, 49 00:02:55,899 --> 00:03:00,070 Speaker 2: we've done text mining on corporate sector earnings calls and 50 00:03:00,080 --> 00:03:02,470 Speaker 2: you find that the number of times they, they use 51 00:03:02,479 --> 00:03:07,429 Speaker 2: words like friend shoring, reshoring has been rising exponentially in 52 00:03:07,440 --> 00:03:10,589 Speaker 2: recent years. So all of this suggested to us 53 00:03:11,258 --> 00:03:15,800 Speaker 2: a working definition of geo economic fragmentation, which we propose 54 00:03:15,809 --> 00:03:18,500 Speaker 2: in the note that you refer to and which I 55 00:03:18,508 --> 00:03:22,279 Speaker 2: think has now become or gained some measure of common acceptance. 56 00:03:22,479 --> 00:03:27,880 Speaker 2: We define geo economic fragmentation as a policy driven reversal 57 00:03:27,889 --> 00:03:33,429 Speaker 2: of global economic integration. It's a deliberately broad definition but 58 00:03:33,460 --> 00:03:37,830 Speaker 2: not the policy driven part that's important. So obviously, 59 00:03:38,460 --> 00:03:41,639 Speaker 2: le let's say that there's a slowdown in trade because 60 00:03:41,649 --> 00:03:45,320 Speaker 2: consumer preferences shift from goods which tend to be tradable 61 00:03:45,330 --> 00:03:47,360 Speaker 2: to services, which tend to be nontradable. 62 00:03:47,800 --> 00:03:50,729 Speaker 2: Um As a result, you find some kind of shrinking 63 00:03:50,740 --> 00:03:54,779 Speaker 2: of trade that's not geo economic fragmentation, that's simply consumer 64 00:03:54,789 --> 00:03:59,009 Speaker 2: preference is changing. Similarly, if technological shifts occur or if 65 00:03:59,020 --> 00:04:02,460 Speaker 2: there are changes in transportation or communication costs and these 66 00:04:02,470 --> 00:04:05,520 Speaker 2: affect trade, that's not geo economic fragmentation, it has to 67 00:04:05,529 --> 00:04:08,419 Speaker 2: be policy driven. So, so that's a crucial part of 68 00:04:08,429 --> 00:04:10,089 Speaker 2: the definition. And 69 00:04:11,029 --> 00:04:12,809 Speaker 2: so obviously, when we do this, 70 00:04:13,740 --> 00:04:17,230 Speaker 2: there are some prudential policies such as macro prudential controls 71 00:04:17,238 --> 00:04:20,859 Speaker 2: on certain capital account transactions, which we think are valid 72 00:04:20,869 --> 00:04:24,779 Speaker 2: and legitimate. And you know, there's good economic reasoning. You 73 00:04:24,790 --> 00:04:28,880 Speaker 2: don't want that to be defined as geo economic fragmentation. 74 00:04:29,079 --> 00:04:30,359 Speaker 2: So we want to exclude 75 00:04:30,434 --> 00:04:33,875 Speaker 2: prudential policies. But of course, when we do so, we 76 00:04:33,885 --> 00:04:38,045 Speaker 2: recognize that there is no bright line between prudential policies 77 00:04:38,053 --> 00:04:41,445 Speaker 2: and protectionist policies and often, you know, the latter can 78 00:04:41,454 --> 00:04:44,954 Speaker 2: masquerade as the former. So, but this is the working 79 00:04:44,964 --> 00:04:47,054 Speaker 2: definition and this is what we mean by the term 80 00:04:47,839 --> 00:04:48,178 Speaker 2: good. 81 00:04:48,589 --> 00:04:51,178 Speaker 1: Um I want to sort of, you know, build the 82 00:04:51,190 --> 00:04:53,149 Speaker 1: key messages of the paper, but I want to add 83 00:04:53,160 --> 00:04:56,179 Speaker 1: a couple of more concepts to this this area. So 84 00:04:56,190 --> 00:05:00,980 Speaker 1: I suppose the opposite of geo economic fragmentation shaker is globalization, 85 00:05:01,209 --> 00:05:04,100 Speaker 1: which is a much maligned word these days in certain 86 00:05:04,109 --> 00:05:09,500 Speaker 1: political circles. So how would you assess the impact of globalization? 87 00:05:09,649 --> 00:05:14,000 Speaker 1: Say from the nineties to the mid 20 tens after 88 00:05:14,010 --> 00:05:17,339 Speaker 1: which we began to see strong evidence of geo economic fragmentation. 89 00:05:19,019 --> 00:05:21,040 Speaker 2: Yeah, it's a, it's a very good question and a 90 00:05:21,049 --> 00:05:23,079 Speaker 2: very good way of putting it and a very good 91 00:05:23,089 --> 00:05:27,239 Speaker 2: way of thinking through it. So, you know, we've amassed 92 00:05:27,250 --> 00:05:31,250 Speaker 2: immense amounts of evidence in the economics literature over the 93 00:05:31,260 --> 00:05:36,178 Speaker 2: last half century about the great benefits that globalization brings 94 00:05:36,190 --> 00:05:37,109 Speaker 2: through multiple channels. 95 00:05:37,178 --> 00:05:41,040 Speaker 2: So that's an excellent starting point. Let's start with trade. 96 00:05:41,049 --> 00:05:44,440 Speaker 2: That's the most obvious. There is a lot of evidence, 97 00:05:44,450 --> 00:05:49,320 Speaker 2: for example, that international trade is strongly linked to economic growth. 98 00:05:49,410 --> 00:05:52,459 Speaker 2: Um And this is this is an important bridge especially 99 00:05:52,470 --> 00:05:55,230 Speaker 2: for developing countries to use as a ladder of development. 100 00:05:55,570 --> 00:05:57,579 Speaker 2: You know, if you if you look at, let's say 101 00:05:57,589 --> 00:06:00,459 Speaker 2: the last 30 or 40 years of data and you 102 00:06:00,470 --> 00:06:04,809 Speaker 2: divide developing countries into globalizer, those which opened up their 103 00:06:04,820 --> 00:06:07,809 Speaker 2: trade regimes and integrated more with the world where the 104 00:06:07,820 --> 00:06:12,510 Speaker 2: trade to GDP ratio went up and non globalizer which 105 00:06:12,519 --> 00:06:15,850 Speaker 2: remained relatively OIC did not open up to the world, 106 00:06:15,859 --> 00:06:16,480 Speaker 2: et cetera. 107 00:06:16,988 --> 00:06:19,359 Speaker 2: You find that over a long period of time, I'm 108 00:06:19,369 --> 00:06:22,730 Speaker 2: talking about 30 or 40 years, there is an enormous 109 00:06:22,738 --> 00:06:26,988 Speaker 2: difference between the growth rate of the globalizer and the 110 00:06:27,000 --> 00:06:28,059 Speaker 2: non globalizer. 111 00:06:28,500 --> 00:06:32,409 Speaker 2: Also, the globalizer have grown much faster than rich countries, 112 00:06:32,600 --> 00:06:36,730 Speaker 2: thereby achieving convergence and catching up with Western living standards. 113 00:06:36,799 --> 00:06:39,529 Speaker 2: This is what you and I studied when we looked 114 00:06:39,540 --> 00:06:43,390 Speaker 2: at neoclassical growth models or solo models in graduate school. 115 00:06:43,510 --> 00:06:46,558 Speaker 2: Uh Yes, it's happening but it's only happening for those 116 00:06:46,570 --> 00:06:49,750 Speaker 2: developing countries which are globalizer, which are integrating with the 117 00:06:49,760 --> 00:06:53,359 Speaker 2: global economy. It's not happening with the rest. So tremendous 118 00:06:53,369 --> 00:06:53,959 Speaker 2: association 119 00:06:54,072 --> 00:06:58,493 Speaker 2: between between trade and growth now intimately linked to that 120 00:06:58,733 --> 00:07:01,613 Speaker 2: of course, is the success that the world has had 121 00:07:01,622 --> 00:07:04,972 Speaker 2: with poverty reduction because we know that poverty reduction is 122 00:07:04,983 --> 00:07:08,692 Speaker 2: intimately related to growth. So trade has had an enormous 123 00:07:08,702 --> 00:07:12,143 Speaker 2: impact in kind of lifting up the developing world via 124 00:07:12,153 --> 00:07:16,722 Speaker 2: convergence and reducing poverty. Um Another thing I would mention 125 00:07:16,733 --> 00:07:19,532 Speaker 2: about trade and this is more to do with advanced economies. 126 00:07:19,726 --> 00:07:24,385 Speaker 2: There's a lot of evidence that trade reduces consumer prices 127 00:07:24,496 --> 00:07:29,256 Speaker 2: uh for the poorest consumers in advanced economies. So we're 128 00:07:29,265 --> 00:07:33,476 Speaker 2: talking about, we're not talking about sort of richer college 129 00:07:33,485 --> 00:07:36,865 Speaker 2: educated people who anyway tend to consume larger shares of 130 00:07:36,876 --> 00:07:40,145 Speaker 2: services than goods. But when you look at low income 131 00:07:40,156 --> 00:07:45,126 Speaker 2: consumers in advanced economies, they have benefited tremendously from trade. 132 00:07:45,536 --> 00:07:49,325 Speaker 2: Um So that's, that's just trade. Then of course, 133 00:07:49,609 --> 00:07:52,609 Speaker 2: let me, let me touch on technology diffusion, which is 134 00:07:52,619 --> 00:07:57,309 Speaker 2: another enormous source for convergence and for kind of the, 135 00:07:57,320 --> 00:08:00,649 Speaker 2: the uplift of the entire globe. Um We have very 136 00:08:00,660 --> 00:08:03,549 Speaker 2: good evidence that FD I for example, and we'll get 137 00:08:03,559 --> 00:08:05,739 Speaker 2: into this later when we discuss the second paper you 138 00:08:05,750 --> 00:08:10,160 Speaker 2: had in mind, um can diffuse technology across borders. So, 139 00:08:10,170 --> 00:08:11,869 Speaker 2: you know, every country in the world doesn't have to 140 00:08:11,880 --> 00:08:12,510 Speaker 2: re invent the 141 00:08:13,225 --> 00:08:16,703 Speaker 2: uh developing countries can take advantage of progress that's been 142 00:08:16,714 --> 00:08:20,005 Speaker 2: made at the technological frontier and it can catch up 143 00:08:20,015 --> 00:08:22,494 Speaker 2: and during the catch up phase, it can enjoy faster 144 00:08:22,505 --> 00:08:25,355 Speaker 2: rates of growth. But of course, this can only happen 145 00:08:25,364 --> 00:08:28,065 Speaker 2: if there's some channel for technology diffusion and the channels 146 00:08:28,075 --> 00:08:31,274 Speaker 2: for technology diffusion tend to be things like trade, foreign 147 00:08:31,285 --> 00:08:35,544 Speaker 2: direct investment participation in global value chains. Um 148 00:08:36,190 --> 00:08:38,289 Speaker 2: Let me come to one more which is kind of 149 00:08:38,299 --> 00:08:42,340 Speaker 2: close to my heart, which is migration. Uh I know 150 00:08:42,349 --> 00:08:45,630 Speaker 2: that migration can be very controversial. Certainly it's a big 151 00:08:45,640 --> 00:08:49,159 Speaker 2: political football in a lot of Western countries. But again, 152 00:08:49,169 --> 00:08:50,369 Speaker 2: it is one of those 153 00:08:50,729 --> 00:08:53,830 Speaker 2: things which and this is true actually for millennia, it's 154 00:08:53,840 --> 00:08:56,929 Speaker 2: not just true of the last five decades. Migration is 155 00:08:56,940 --> 00:09:02,460 Speaker 2: a primary uh mover of the diffusion of ideas and 156 00:09:02,469 --> 00:09:05,949 Speaker 2: technologies and knowledge throughout the world, right? It's, it's happened 157 00:09:05,960 --> 00:09:09,150 Speaker 2: throughout history. It's, it's not a recent phenomenon. Um 158 00:09:09,500 --> 00:09:11,700 Speaker 2: And you know, just to look at recent history, there's 159 00:09:11,710 --> 00:09:14,599 Speaker 2: ample evidence if you look at Silicon Valley, for example, 160 00:09:14,750 --> 00:09:17,179 Speaker 2: and if you look at the number of immigrants and 161 00:09:17,190 --> 00:09:21,468 Speaker 2: the amount of dynamism that immigrants have brought uh to and, 162 00:09:21,479 --> 00:09:24,349 Speaker 2: and that's, that's the leading edge of world technology, right? 163 00:09:24,809 --> 00:09:28,179 Speaker 2: In the US, there's ample evidence that immigrants are more 164 00:09:28,190 --> 00:09:31,099 Speaker 2: likely to have college degrees. They are more likely to 165 00:09:31,109 --> 00:09:34,739 Speaker 2: have stem certifications. They are more likely to start a 166 00:09:34,750 --> 00:09:38,710 Speaker 2: new business, they are more likely to patent. Um There's 167 00:09:38,719 --> 00:09:41,929 Speaker 2: this amazing statistic which might appeal to you Temur, 168 00:09:42,539 --> 00:09:46,358 Speaker 2: if you just look at ethnic Chinese and ethnic Indians 169 00:09:46,369 --> 00:09:49,940 Speaker 2: living in Silicon Valley, just that small group of ethnic 170 00:09:49,950 --> 00:09:54,609 Speaker 2: Indians and Chinese, the amount they account for 11% of 171 00:09:54,619 --> 00:09:56,950 Speaker 2: all patents in America, 172 00:09:57,320 --> 00:10:01,460 Speaker 2: their patent output is greater than the combined patent output 173 00:10:01,469 --> 00:10:04,409 Speaker 2: of the bottom 28 states in the US. We're just 174 00:10:04,419 --> 00:10:08,099 Speaker 2: talking about Chinese and Indian ethnic investors living in the 175 00:10:08,109 --> 00:10:11,380 Speaker 2: San Francisco Bay area. So yes, I mean, you know, 176 00:10:11,390 --> 00:10:14,619 Speaker 2: they're a tremendous source of dynamism and it works both ways. 177 00:10:14,640 --> 00:10:15,609 Speaker 2: So when you have immigrants 178 00:10:15,674 --> 00:10:19,255 Speaker 2: abroad, they send back remittances, we all know that Remittance, 179 00:10:19,265 --> 00:10:23,304 Speaker 2: remittances tend to be countercyclical, remittances were much more stable 180 00:10:23,315 --> 00:10:27,294 Speaker 2: during the COVID-19 pandemic than other types of capital flows. So, 181 00:10:27,455 --> 00:10:32,414 Speaker 2: so they're countercyclical, they help with macroeconomic stabilization um and 182 00:10:32,424 --> 00:10:33,875 Speaker 2: they help with poverty reduction. 183 00:10:34,219 --> 00:10:37,710 Speaker 2: Um And then you have diaspora effect. So I think 184 00:10:37,719 --> 00:10:42,150 Speaker 2: the success of, let's say the Taiwanese semiconductor industry can 185 00:10:42,159 --> 00:10:45,189 Speaker 2: be traced to earlier waves of skilled immigrants who went 186 00:10:45,200 --> 00:10:47,929 Speaker 2: to Silicon Valley and Wall Street and then brought this 187 00:10:47,940 --> 00:10:52,669 Speaker 2: technological expertise back with them to this small, backward, agriculturally 188 00:10:52,679 --> 00:10:56,559 Speaker 2: dominant island, which today is a global leader of high tech. 189 00:10:56,690 --> 00:10:57,299 Speaker 2: So 190 00:10:57,809 --> 00:11:01,159 Speaker 2: migration, I think is another channel which is a threat 191 00:11:01,349 --> 00:11:05,069 Speaker 2: uh given geo economic fragmentation. Let, let me stop there. 192 00:11:05,080 --> 00:11:07,228 Speaker 2: I could go on on this forever. But that's, that's, 193 00:11:07,239 --> 00:11:13,070 Speaker 2: that's three things, trade, um FD I migration, tremendous benefits 194 00:11:13,080 --> 00:11:15,419 Speaker 2: of globalization. And of course, all of this could go 195 00:11:15,429 --> 00:11:17,669 Speaker 2: into reverse with geo economic fragmentation. 196 00:11:18,150 --> 00:11:21,239 Speaker 1: OK. Very compelling Shekhar. You may or may not have 197 00:11:21,250 --> 00:11:23,960 Speaker 1: noticed that I smiled when you talked about convergence and 198 00:11:23,969 --> 00:11:25,609 Speaker 1: I'll take a personal detail to tell you why I 199 00:11:25,619 --> 00:11:30,309 Speaker 1: smiled over two decades ago. I was at a party 200 00:11:30,320 --> 00:11:34,659 Speaker 1: in Van Nest in Washington DC. And I heard a 201 00:11:34,669 --> 00:11:38,718 Speaker 1: new economist in the IMF who just joined talk adly 202 00:11:38,729 --> 00:11:40,090 Speaker 1: about conditional convergence. 203 00:11:40,219 --> 00:11:43,400 Speaker 1: It was you. And so so when you mentioned that 204 00:11:43,719 --> 00:11:45,709 Speaker 1: you really took me back to the very first days 205 00:11:45,719 --> 00:11:48,049 Speaker 1: when I got to know you. All right, back to 206 00:11:48,059 --> 00:11:51,000 Speaker 1: the uh podcast. All right. So you made very compelling 207 00:11:51,010 --> 00:11:55,960 Speaker 1: arguments in terms of the benefits from globalization and the 208 00:11:55,969 --> 00:11:59,830 Speaker 1: fact that there is volumes of, there are volumes of 209 00:11:59,840 --> 00:12:02,200 Speaker 1: empirical evidence to, to establish that point. 210 00:12:02,549 --> 00:12:07,049 Speaker 1: Um We don't have a very large data set for 211 00:12:07,330 --> 00:12:10,760 Speaker 1: geo economic fragmentation, maybe a decade, maybe 12 years. So 212 00:12:10,770 --> 00:12:14,090 Speaker 1: how does one measure robustly the cost of geo economic fragmentation? 213 00:12:15,719 --> 00:12:19,900 Speaker 2: Uh Very good question. Um Although I should say that this, 214 00:12:19,909 --> 00:12:23,108 Speaker 2: you know, your previous remarks demonstrate the perils of doing 215 00:12:23,119 --> 00:12:25,789 Speaker 2: podcasts with people who remember going to parties with you 216 00:12:25,799 --> 00:12:30,319 Speaker 2: 20 years ago. Um Look, this is a new literature. 217 00:12:30,330 --> 00:12:32,949 Speaker 2: It's a field which is in its infancy, it's just 218 00:12:32,960 --> 00:12:36,369 Speaker 2: developing uh in the and because we don't have so 219 00:12:36,380 --> 00:12:40,150 Speaker 2: many years of geo economic fragmentation compared to the many 220 00:12:40,159 --> 00:12:43,159 Speaker 2: decades of globalization, it will be a while before we 221 00:12:43,169 --> 00:12:43,890 Speaker 2: can do 222 00:12:44,179 --> 00:12:47,710 Speaker 2: you know, very good analytically rigorous work on this that 223 00:12:47,719 --> 00:12:52,080 Speaker 2: said in the Sdn we review four recent papers which 224 00:12:52,090 --> 00:12:54,569 Speaker 2: try to estimate the cost of fragmentation 225 00:12:54,960 --> 00:12:58,718 Speaker 2: the way it's done these days is through modeling exercises. 226 00:12:58,729 --> 00:13:02,770 Speaker 2: So essentially all the four papers we review model geo 227 00:13:02,780 --> 00:13:07,059 Speaker 2: economic fragmentation in some way. They set up blocks of countries, 228 00:13:07,109 --> 00:13:11,520 Speaker 2: they introduce trade barriers or investment barriers between the blocks. 229 00:13:11,789 --> 00:13:15,460 Speaker 2: They have very different assumptions about the severity of the 230 00:13:15,565 --> 00:13:20,473 Speaker 2: barriers between blocks. They have different definitions of the blocks themselves. 231 00:13:20,484 --> 00:13:23,343 Speaker 2: In some of the papers, non aligned countries are allowed 232 00:13:23,354 --> 00:13:26,005 Speaker 2: which don't belong to either block. This is just a 233 00:13:26,155 --> 00:13:28,945 Speaker 2: long way of saying that the four papers are extremely 234 00:13:28,955 --> 00:13:33,184 Speaker 2: disparate from each other. Nonetheless, all of them show significant costs, 235 00:13:33,195 --> 00:13:36,064 Speaker 2: global costs of geo economic fragmentation. 236 00:13:36,309 --> 00:13:39,729 Speaker 2: And depending on the severity of the assumptions, uh you 237 00:13:39,739 --> 00:13:43,929 Speaker 2: can get very large results up to 8% global losses 238 00:13:44,099 --> 00:13:48,500 Speaker 2: and much higher losses for individual countries up to 12% 15%. 239 00:13:48,710 --> 00:13:51,039 Speaker 2: Uh depending on the scenario that you have in mind. 240 00:13:51,450 --> 00:13:54,619 Speaker 2: Um There are some common lessons however, that seem to 241 00:13:54,630 --> 00:13:56,869 Speaker 2: emerge from these studies. Let me just go through some 242 00:13:56,880 --> 00:14:01,049 Speaker 2: of them. First, the deeper the fragmentation, the larger the 243 00:14:01,059 --> 00:14:03,299 Speaker 2: estimated losses. What do we, what do I mean by 244 00:14:03,309 --> 00:14:04,520 Speaker 2: deeper the fragmentation, 245 00:14:04,979 --> 00:14:09,119 Speaker 2: there's many parameters in these models which could act to 246 00:14:09,130 --> 00:14:13,630 Speaker 2: deepen the fragmentation uh for one thing, greater barriers between 247 00:14:13,640 --> 00:14:16,530 Speaker 2: the blocks, right? So typically in these models, you put 248 00:14:16,539 --> 00:14:18,650 Speaker 2: some kind of tariff barriers or some kind of non 249 00:14:18,679 --> 00:14:22,510 Speaker 2: tariff barriers between the two blocks, depending on how, how 250 00:14:22,520 --> 00:14:24,460 Speaker 2: restrictive you make those uh 251 00:14:25,284 --> 00:14:29,465 Speaker 2: you get larger output losses for the globe. Um Second, 252 00:14:29,474 --> 00:14:32,815 Speaker 2: do you allow non-aligned countries? So, you know, if you 253 00:14:32,825 --> 00:14:36,505 Speaker 2: allow non-aligned countries, then it's a less fragmented world. If 254 00:14:36,515 --> 00:14:39,135 Speaker 2: you force every country to choose one block, then that's 255 00:14:39,145 --> 00:14:41,135 Speaker 2: a deeper level of fragmentation. So 256 00:14:42,020 --> 00:14:45,020 Speaker 2: the deeper the fragmentation, the higher the loss is second, 257 00:14:45,969 --> 00:14:50,630 Speaker 2: if you put technological diffusion on top of trade barriers, 258 00:14:50,640 --> 00:14:53,109 Speaker 2: then the losses are much greater. You know, we talked 259 00:14:53,119 --> 00:14:55,729 Speaker 2: about this a bit earlier. There are modeling techniques which 260 00:14:55,739 --> 00:14:57,919 Speaker 2: allow you to do this. And when you do this, 261 00:14:57,929 --> 00:15:00,530 Speaker 2: you find that the losses are higher. Third, 262 00:15:01,229 --> 00:15:06,020 Speaker 2: the losses vary widely among countries. They're not heterogenous. And 263 00:15:06,030 --> 00:15:06,929 Speaker 2: in particular, 264 00:15:07,679 --> 00:15:10,929 Speaker 2: the losses tend to be higher for emerging markets and 265 00:15:10,940 --> 00:15:14,739 Speaker 2: developing economies. And this is not surprising because as we discussed, 266 00:15:14,750 --> 00:15:17,909 Speaker 2: they tend to be further back from the technological frontier 267 00:15:18,090 --> 00:15:20,409 Speaker 2: and they can benefit a lot from trade and FD 268 00:15:20,419 --> 00:15:23,710 Speaker 2: I in terms of technological diffusion, if you remove that, 269 00:15:23,719 --> 00:15:25,840 Speaker 2: you remove an important source of growth, so they are 270 00:15:25,849 --> 00:15:30,710 Speaker 2: very badly hurt. And then finally, um short term elastic 271 00:15:30,719 --> 00:15:33,880 Speaker 2: cities of substitution are likely to be smaller than long 272 00:15:33,890 --> 00:15:35,849 Speaker 2: run elastic cities of substitution. 273 00:15:36,469 --> 00:15:38,840 Speaker 2: And that means that even the cost that you see 274 00:15:39,000 --> 00:15:41,669 Speaker 2: in the papers that we survey are likely to be 275 00:15:41,679 --> 00:15:44,140 Speaker 2: an underestimate for the short run because these are all 276 00:15:44,150 --> 00:15:47,840 Speaker 2: long run equilibrium numbers in the short run, you could 277 00:15:47,849 --> 00:15:52,039 Speaker 2: have uh disruptions to output, which are many multiples of 278 00:15:52,049 --> 00:15:53,429 Speaker 2: what we find in the long run. 279 00:15:54,190 --> 00:15:57,789 Speaker 2: Um So that's, that's just, you know, some flavor of, 280 00:15:57,799 --> 00:16:00,510 Speaker 2: of where the literature has been going. I should also 281 00:16:00,520 --> 00:16:04,150 Speaker 2: mention that, that I did some work with IMF co 282 00:16:04,289 --> 00:16:08,830 Speaker 2: authors specifically on FD I fragmentation and FD I fragmentation 283 00:16:08,840 --> 00:16:12,000 Speaker 2: is quite interesting because it's taking the literature in a 284 00:16:12,010 --> 00:16:15,250 Speaker 2: new direction I think. And the basic idea is simple, 285 00:16:15,260 --> 00:16:16,599 Speaker 2: what we do is we take 286 00:16:17,099 --> 00:16:20,479 Speaker 2: voting patterns from the United Nations and there's a few 287 00:16:20,489 --> 00:16:23,539 Speaker 2: academics at Harvard who have built up a database which, 288 00:16:23,549 --> 00:16:27,849 Speaker 2: which show for any pair of countries how far apart 289 00:16:27,859 --> 00:16:32,159 Speaker 2: they are geopolitically based on un voting patterns. And the 290 00:16:32,169 --> 00:16:34,280 Speaker 2: nice thing about this database is that it gives you 291 00:16:34,289 --> 00:16:35,830 Speaker 2: a geopolitical distance 292 00:16:36,260 --> 00:16:40,320 Speaker 2: of bilateral geopolitical distance which is time varying. So then 293 00:16:40,330 --> 00:16:44,429 Speaker 2: this is like extremely nice for all kinds of econometric work. 294 00:16:44,590 --> 00:16:46,719 Speaker 2: And the way we do it is we try to 295 00:16:46,729 --> 00:16:51,359 Speaker 2: establish relationships, you know, we divide the world into quintiles. 296 00:16:51,380 --> 00:16:53,609 Speaker 2: And in the first quintiles are countries which are quite 297 00:16:53,619 --> 00:16:57,239 Speaker 2: close together geopolitically according to this measure that I've talked about. 298 00:16:57,539 --> 00:16:59,919 Speaker 2: And then the final quintile is countries which are quite 299 00:16:59,929 --> 00:17:01,479 Speaker 2: far apart from each other. 300 00:17:01,809 --> 00:17:05,359 Speaker 2: And when you follow these quintiles over time, you find 301 00:17:05,369 --> 00:17:08,540 Speaker 2: that they are becoming very important in determining trade patterns. 302 00:17:08,550 --> 00:17:12,030 Speaker 2: In particular, the share of world trade that is taking 303 00:17:12,040 --> 00:17:14,639 Speaker 2: place among countries which are similar to each other in 304 00:17:14,650 --> 00:17:17,909 Speaker 2: terms of geopolitical alignment is going up steeply. 305 00:17:18,640 --> 00:17:22,979 Speaker 2: So it's already more important than geographical distance. And over time, 306 00:17:23,260 --> 00:17:26,560 Speaker 2: its importance seems to be increasing further. Then you can 307 00:17:26,569 --> 00:17:28,530 Speaker 2: be more rigorous about it and put it into a 308 00:17:28,540 --> 00:17:31,979 Speaker 2: gravity model, which we do. And indeed, we find that 309 00:17:31,989 --> 00:17:37,280 Speaker 2: there's a strong correlation between FD patterns and geopolitical distance. 310 00:17:38,099 --> 00:17:40,300 Speaker 2: So let me, let me give you, let me try 311 00:17:40,310 --> 00:17:44,919 Speaker 2: to distill so you know, consider the geopolitical distance between 312 00:17:45,050 --> 00:17:49,130 Speaker 2: France and the UK. They, they're quite close together, obviously, 313 00:17:49,369 --> 00:17:53,359 Speaker 2: um if you move from that geopolitical distance to the 314 00:17:53,369 --> 00:17:58,150 Speaker 2: distance between France and India, which are much further apart geopolitically, 315 00:17:58,439 --> 00:18:02,410 Speaker 2: you would, you can, you can relate that to a 17% 316 00:18:02,420 --> 00:18:03,589 Speaker 2: decline in FD I. 317 00:18:04,180 --> 00:18:06,790 Speaker 2: So that just gives you an idea of how economically 318 00:18:06,800 --> 00:18:10,160 Speaker 2: powerful geopolitical distance can be. Um 319 00:18:10,979 --> 00:18:14,449 Speaker 2: And then, yeah, then so once you have those parameters about, 320 00:18:14,459 --> 00:18:17,810 Speaker 2: you know how important geo economic fragmentation can be for 321 00:18:17,819 --> 00:18:20,458 Speaker 2: FD I, then you can feed that into a model. 322 00:18:20,650 --> 00:18:24,260 Speaker 2: So we use the IMF SGM model to divide the 323 00:18:24,270 --> 00:18:27,439 Speaker 2: world into different blocks and then to put barriers between 324 00:18:27,449 --> 00:18:28,449 Speaker 2: blocks and then 325 00:18:28,560 --> 00:18:32,810 Speaker 2: use these gravity estimates to parameterize the model and calculate 326 00:18:32,819 --> 00:18:35,439 Speaker 2: global losses. And we find that you can get global 327 00:18:35,449 --> 00:18:39,209 Speaker 2: losses from FD I fragmentation of 2% but the losses 328 00:18:39,219 --> 00:18:42,040 Speaker 2: are much higher for some countries than for others. In particular, 329 00:18:42,050 --> 00:18:46,130 Speaker 2: they are much higher for developing countries than for advanced economies. 330 00:18:47,359 --> 00:18:49,859 Speaker 1: Um Shekar two follow up questions. One is if I 331 00:18:49,869 --> 00:18:53,129 Speaker 1: were to rank all the economies in the world by 332 00:18:53,140 --> 00:18:56,380 Speaker 1: say trade GDP ratio, so you know, a proxy for 333 00:18:56,390 --> 00:19:00,170 Speaker 1: openness or trade intensity, uh would it be fair to 334 00:19:00,180 --> 00:19:04,280 Speaker 1: say that that ranking would be congruent with the vulnerability 335 00:19:04,290 --> 00:19:07,699 Speaker 1: of those economies that the most integrated are the most 336 00:19:07,709 --> 00:19:09,739 Speaker 1: vulnerable to economic fragmentation? 337 00:19:12,130 --> 00:19:17,030 Speaker 2: Yes, although I think there are some subtleties. So, so yes, 338 00:19:17,040 --> 00:19:19,569 Speaker 2: I mean, what what you can do and what we 339 00:19:19,579 --> 00:19:22,819 Speaker 2: do in the in the Rio chapter. Uh for example, 340 00:19:22,880 --> 00:19:25,989 Speaker 2: is to develop an index of geo economic vulnerability 341 00:19:26,219 --> 00:19:28,819 Speaker 2: and it's quite easy to do that because you have 342 00:19:28,829 --> 00:19:32,810 Speaker 2: this index of um geopolitical distance. So what you can 343 00:19:32,819 --> 00:19:36,290 Speaker 2: do is you can wait geopolitical distance by trade shares. 344 00:19:36,520 --> 00:19:39,609 Speaker 2: And if you're trading a lot with countries that are 345 00:19:39,619 --> 00:19:42,708 Speaker 2: very far away from you geopolitically, then mechanically you are 346 00:19:42,719 --> 00:19:44,040 Speaker 2: more vulnerable, right? 347 00:19:44,900 --> 00:19:45,439 Speaker 2: Um 348 00:19:46,089 --> 00:19:48,569 Speaker 2: Now, the reason I'm saying is this is a little 349 00:19:48,579 --> 00:19:51,739 Speaker 2: more subtle is that more recently, people are talking about 350 00:19:51,750 --> 00:19:56,000 Speaker 2: connector countries. And the idea here is that if you 351 00:19:56,010 --> 00:20:00,949 Speaker 2: have a diversified trading base, then in some sense that 352 00:20:00,959 --> 00:20:05,390 Speaker 2: builds resilience because if there's a geopolitical spat with one 353 00:20:05,400 --> 00:20:07,149 Speaker 2: particular set of, of global 354 00:20:07,319 --> 00:20:10,859 Speaker 2: factors because of your diversification and the fact that you're 355 00:20:10,869 --> 00:20:14,069 Speaker 2: trading with a lot of people, there's some insulation from 356 00:20:14,079 --> 00:20:17,770 Speaker 2: that shock. Uh People are also talking about connectors in 357 00:20:17,780 --> 00:20:20,910 Speaker 2: terms of linking hostile blocks to each other. So people 358 00:20:20,920 --> 00:20:24,319 Speaker 2: like Laura Pau at Harvard have been looking at countries 359 00:20:24,329 --> 00:20:27,599 Speaker 2: like Mexico, which is getting a lot of FT I 360 00:20:27,609 --> 00:20:28,410 Speaker 2: from China 361 00:20:28,910 --> 00:20:31,198 Speaker 2: at the same time that it's increasing its exports to 362 00:20:31,209 --> 00:20:33,669 Speaker 2: the US. So in some sense, you could think of 363 00:20:33,680 --> 00:20:37,510 Speaker 2: Mexico as being a connected country between China and the US. So, 364 00:20:37,520 --> 00:20:40,550 Speaker 2: so lots of work going on in this area. Um Yes, 365 00:20:40,560 --> 00:20:43,810 Speaker 2: if you trade a lot with a lot of diverse countries, 366 00:20:43,849 --> 00:20:44,579 Speaker 2: uh you may be 367 00:20:44,655 --> 00:20:48,275 Speaker 2: vulnerable to the extent that you're trading with with people 368 00:20:48,285 --> 00:20:50,994 Speaker 2: who are geopolitically distant from you. On the other hand, 369 00:20:51,005 --> 00:20:53,895 Speaker 2: if you're doing this very diversely and you're doing it 370 00:20:53,905 --> 00:20:55,954 Speaker 2: with a lot of people, then you can be a 371 00:20:55,964 --> 00:20:59,555 Speaker 2: connector as well. Uh So, so there's some pluses and 372 00:20:59,564 --> 00:21:00,494 Speaker 2: some minuses, 373 00:21:01,084 --> 00:21:05,074 Speaker 1: right? I'm compelled by the Mexico example because I think 374 00:21:05,244 --> 00:21:09,113 Speaker 1: Mexico has been a big beneficiary of some of these 375 00:21:09,125 --> 00:21:11,555 Speaker 1: restriction measures that the US has been putting in and 376 00:21:11,564 --> 00:21:12,555 Speaker 1: countries like China 377 00:21:12,930 --> 00:21:16,839 Speaker 1: uh have thousands of companies if not more uh in 378 00:21:16,849 --> 00:21:20,410 Speaker 1: Mexico trading with the US under US MC A. But 379 00:21:20,420 --> 00:21:24,050 Speaker 1: I think this has been noticed by the proponent of 380 00:21:24,060 --> 00:21:27,050 Speaker 1: socio-economic fragmentation and therefore, we could see an undermining of 381 00:21:27,060 --> 00:21:29,839 Speaker 1: us MC A uh if say Trump were to come 382 00:21:29,849 --> 00:21:32,149 Speaker 1: to power because I think there's also 383 00:21:32,390 --> 00:21:36,119 Speaker 1: been some sort of promise made that if Chinese made 384 00:21:36,130 --> 00:21:39,280 Speaker 1: EVs from Mexico or have their way to the US, 385 00:21:39,290 --> 00:21:41,650 Speaker 1: there will be like 100% tired from them US MC 386 00:21:41,660 --> 00:21:45,290 Speaker 1: A be damned. Um So uh so yeah, uh Mexico 387 00:21:45,300 --> 00:21:47,680 Speaker 1: is indeed an interesting example of how at least in 388 00:21:47,689 --> 00:21:50,270 Speaker 1: the short term it can be a buffer, but uh 389 00:21:50,280 --> 00:21:51,400 Speaker 1: it's a dynamic game, 390 00:21:51,410 --> 00:21:51,729 Speaker 2: right? 391 00:21:52,390 --> 00:21:54,250 Speaker 2: Let me, let me jump in. I think that's an 392 00:21:54,260 --> 00:21:56,869 Speaker 2: excellent observation and I think this kind of brings us 393 00:21:56,880 --> 00:22:00,079 Speaker 2: to the cutting edge of the literature. So uh so yes, 394 00:22:00,089 --> 00:22:02,579 Speaker 2: so there are these papers talking about Mexico as a 395 00:22:02,589 --> 00:22:05,209 Speaker 2: great connector. I share your skepticism 396 00:22:05,560 --> 00:22:09,339 Speaker 2: if you saw Donald Trump's speech at the Republican National Convention, 397 00:22:09,349 --> 00:22:13,520 Speaker 2: he explicitly mentioned we're not going to allow the Chinese 398 00:22:13,530 --> 00:22:17,420 Speaker 2: to build automobile factories in Mexico and then export them 399 00:22:17,430 --> 00:22:20,760 Speaker 2: to the US. Uh That's on the Republican side. But 400 00:22:20,770 --> 00:22:24,129 Speaker 2: if you look at the trade representative Catherine Sai under 401 00:22:24,140 --> 00:22:28,260 Speaker 2: the Biden administration, she has made similar pronouncements in more 402 00:22:28,270 --> 00:22:31,448 Speaker 2: guarded language. So, so clearly, this is something that's been 403 00:22:31,459 --> 00:22:33,890 Speaker 2: noticed and it's something that may come to a stop 404 00:22:33,900 --> 00:22:34,609 Speaker 2: at some point. 405 00:22:35,040 --> 00:22:38,619 Speaker 2: So there's that concept of connector which is kind of 406 00:22:38,630 --> 00:22:41,760 Speaker 2: a supply chain type of definition, right? You get investment 407 00:22:41,770 --> 00:22:44,750 Speaker 2: from one block and then you do exports to another block. 408 00:22:45,239 --> 00:22:49,969 Speaker 2: And like you, I'm skeptical that that kind of connector 409 00:22:49,979 --> 00:22:52,819 Speaker 2: can survive the hostile geopolitical environment. 410 00:22:53,079 --> 00:22:56,420 Speaker 2: So I'm actually more attracted to a definition of connected 411 00:22:56,430 --> 00:23:01,139 Speaker 2: countries that emphasizes the diversity of the links that you have. 412 00:23:01,349 --> 00:23:04,579 Speaker 2: And there the paradigm is actually not so much Mexico 413 00:23:04,729 --> 00:23:08,050 Speaker 2: but a country like Vietnam or Cambodia. When you look 414 00:23:08,060 --> 00:23:11,879 Speaker 2: at the diversification of their exports, at the amount of 415 00:23:11,890 --> 00:23:15,229 Speaker 2: balance they have in their exports both to countries to 416 00:23:15,239 --> 00:23:18,489 Speaker 2: which they are geopolitically closed and to countries which are 417 00:23:18,500 --> 00:23:20,969 Speaker 2: geopolitically distant from them, it's very balanced. 418 00:23:21,280 --> 00:23:24,469 Speaker 2: So actually, you know, Francisca and I have a new 419 00:23:24,479 --> 00:23:27,010 Speaker 2: paper which is not yet issued where we try to 420 00:23:27,020 --> 00:23:32,819 Speaker 2: define connectedness in terms of the standard deviation of the 421 00:23:32,829 --> 00:23:36,329 Speaker 2: geopolitical distance that you have from all your trade partners. 422 00:23:36,339 --> 00:23:38,859 Speaker 2: The idea being that the more balanced you are the 423 00:23:38,869 --> 00:23:42,119 Speaker 2: better connector you would make. So, so there are currently 424 00:23:42,130 --> 00:23:44,660 Speaker 2: these debates about how should we define a connector? 425 00:23:45,640 --> 00:23:47,250 Speaker 1: Oh Brilliant. I look forward to the paper and I'm 426 00:23:47,260 --> 00:23:51,938 Speaker 1: hoping my country Singapore scores high in that that balanced aspect. 427 00:23:52,310 --> 00:23:56,449 Speaker 1: Um Shekhar, you are a staff of the IMF you're 428 00:23:56,459 --> 00:23:59,209 Speaker 1: on leave writing a book that I'm also looking forward to. 429 00:23:59,260 --> 00:24:02,510 Speaker 1: But let's talk about the International Monetary System a little 430 00:24:02,520 --> 00:24:05,170 Speaker 1: bit that related to this issue of geo economic recognition. 431 00:24:05,180 --> 00:24:09,319 Speaker 1: What are the consequences if we have persistent geo economic recommendation? 432 00:24:09,329 --> 00:24:12,198 Speaker 1: What does it mean for the international monetary system and 433 00:24:12,209 --> 00:24:15,770 Speaker 1: the global financial safety net, which this international monetary system offers? 434 00:24:17,020 --> 00:24:20,800 Speaker 2: So I guess the first obvious consequence is that 435 00:24:21,489 --> 00:24:27,448 Speaker 2: we will probably move towards regionalization of financial arrangements. So 436 00:24:27,829 --> 00:24:31,260 Speaker 2: to the extent that there's currently a global safety net 437 00:24:31,400 --> 00:24:35,550 Speaker 2: that may become a series of sort of block 438 00:24:36,530 --> 00:24:40,699 Speaker 2: safety nets or regional safety nets depending on the configuration 439 00:24:40,709 --> 00:24:43,859 Speaker 2: of those blocks. And of course, given that the blocks 440 00:24:43,869 --> 00:24:48,849 Speaker 2: are smaller and uh you know, often may have oo 441 00:24:48,859 --> 00:24:54,438 Speaker 2: often may be economically correlated more closely than outside the block. 442 00:24:54,449 --> 00:24:57,270 Speaker 2: It means that the amount of insurance that it can 443 00:24:57,280 --> 00:25:01,589 Speaker 2: give you is suboptimal compared to a truly global safety net. 444 00:25:01,599 --> 00:25:02,780 Speaker 2: So that's one concern. 445 00:25:03,229 --> 00:25:05,969 Speaker 2: I I think one way to to sort of highlight 446 00:25:05,979 --> 00:25:09,290 Speaker 2: the the the issue may actually be to look at 447 00:25:09,300 --> 00:25:12,449 Speaker 2: debt restructuring, you know, that's a big topic right now 448 00:25:12,459 --> 00:25:15,500 Speaker 2: because a lot of countries have elevated levels of debt 449 00:25:15,569 --> 00:25:19,150 Speaker 2: and need some kind of debt restructuring as you and 450 00:25:19,160 --> 00:25:21,209 Speaker 2: I both know because both of us worked at the 451 00:25:21,219 --> 00:25:24,729 Speaker 2: IMF in the early two thousands. Um The last time 452 00:25:24,739 --> 00:25:27,439 Speaker 2: that this was tackled in the in the hippic debt 453 00:25:27,449 --> 00:25:31,109 Speaker 2: relief initiatives, uh a very leading role was taken by 454 00:25:31,119 --> 00:25:31,929 Speaker 2: the Paris Club. 455 00:25:32,520 --> 00:25:35,780 Speaker 2: So the Paris Club is a group of of mainly 456 00:25:35,790 --> 00:25:43,099 Speaker 2: rich country creditors who traditionally have been responsible for delivering 457 00:25:43,109 --> 00:25:45,140 Speaker 2: most of the bilateral credit in the world. 458 00:25:45,369 --> 00:25:47,800 Speaker 2: So when you had a debt restructuring, it was relatively 459 00:25:47,810 --> 00:25:51,069 Speaker 2: easy to get all the Paris Club creditors in one room, 460 00:25:51,079 --> 00:25:53,489 Speaker 2: get them to agree a deal and then you would 461 00:25:53,500 --> 00:25:56,708 Speaker 2: have the debt restructuring. Now if you look at how 462 00:25:56,719 --> 00:26:00,459 Speaker 2: the debt structure in em Ds has been evolving. Non 463 00:26:00,510 --> 00:26:04,319 Speaker 2: Paris Club, creditors are accounting for a larger and larger 464 00:26:04,329 --> 00:26:06,909 Speaker 2: share of total debt. So when you look at countries 465 00:26:07,005 --> 00:26:11,344 Speaker 2: like India, well, China, especially China and India, who were 466 00:26:11,354 --> 00:26:15,304 Speaker 2: not important players in in in as as global creditors 467 00:26:15,385 --> 00:26:19,665 Speaker 2: earlier now they are. So if if you have hostile 468 00:26:19,675 --> 00:26:21,875 Speaker 2: blocks and China is in one block and the Paris 469 00:26:21,885 --> 00:26:24,264 Speaker 2: clubs in another block, it's going to be much more 470 00:26:24,275 --> 00:26:28,545 Speaker 2: difficult to for creditors to agree on things like debt restructuring. 471 00:26:28,780 --> 00:26:32,160 Speaker 2: So that's just one example to highlight ways in which 472 00:26:32,390 --> 00:26:36,419 Speaker 2: the International Monetary system could start fragmenting and could suffer 473 00:26:36,430 --> 00:26:39,239 Speaker 2: consequences as a result of geo economic fragmentation. 474 00:26:40,339 --> 00:26:44,550 Speaker 1: Sure. Um Again, uh really interesting research and I'm sure 475 00:26:44,560 --> 00:26:47,160 Speaker 1: you'll be following up with this with uh more work 476 00:26:47,170 --> 00:26:49,689 Speaker 1: including with Francisca. So look forward to that. Uh She, 477 00:26:49,849 --> 00:26:51,750 Speaker 1: I want to talk about the other research that you've 478 00:26:51,760 --> 00:26:55,209 Speaker 1: been doing uh earlier this month. Uh Bruegel published a 479 00:26:55,219 --> 00:26:58,510 Speaker 1: paper co-authored by you. The title was a productivity spillovers 480 00:26:58,520 --> 00:27:02,438 Speaker 1: from f dia firm level cross country analysis. We've touched 481 00:27:02,449 --> 00:27:04,420 Speaker 1: upon this a little bit, but I'm really interested in 482 00:27:04,430 --> 00:27:07,000 Speaker 1: this subject sitting here in Singapore. So let's start with, 483 00:27:07,750 --> 00:27:10,670 Speaker 1: you know, walk us through how you find this robust 484 00:27:10,680 --> 00:27:12,890 Speaker 1: evidence of productivity spillovers from FD I. 485 00:27:14,119 --> 00:27:15,609 Speaker 2: OK. Um So, 486 00:27:16,520 --> 00:27:18,329 Speaker 2: you know, a lot of work has been done in 487 00:27:18,339 --> 00:27:20,419 Speaker 2: this area as you know, but a lot of it 488 00:27:20,430 --> 00:27:24,540 Speaker 2: tends to be kind of country specific studies. What we 489 00:27:24,550 --> 00:27:28,909 Speaker 2: do here is we collect a really large database with 490 00:27:28,920 --> 00:27:32,079 Speaker 2: three sources of data. So we've got data on Greenfield 491 00:27:32,089 --> 00:27:37,699 Speaker 2: investment on uh on a firm sector country level from 492 00:27:37,709 --> 00:27:41,619 Speaker 2: FD I markets, which is a private database, um which, 493 00:27:41,630 --> 00:27:44,000 Speaker 2: which uh which licenses its data out. 494 00:27:44,300 --> 00:27:47,420 Speaker 2: And then from definitive icon, we've got data on mergers 495 00:27:47,430 --> 00:27:50,939 Speaker 2: and acquisitions, which are an alternative way of doing FT I. 496 00:27:51,189 --> 00:27:54,228 Speaker 2: And then finally, from the World Bank Enterprise Survey, we've 497 00:27:54,239 --> 00:27:57,849 Speaker 2: got some data on the labor productivity of individual firms. 498 00:27:58,040 --> 00:28:00,680 Speaker 2: So we put this together in a, in a big 499 00:28:00,689 --> 00:28:06,010 Speaker 2: uh cross country cross firm panel study and what we 500 00:28:06,020 --> 00:28:10,390 Speaker 2: are looking for specifically are spillovers. So our left hand 501 00:28:10,400 --> 00:28:13,160 Speaker 2: side variable is labor productivity in a firm. 502 00:28:13,390 --> 00:28:18,409 Speaker 2: And we're asking, you know, what are the sources of 503 00:28:18,890 --> 00:28:22,619 Speaker 2: that labor productivity? And there are three possible sources of 504 00:28:22,630 --> 00:28:25,670 Speaker 2: labor productivity. On the right hand side, the first is 505 00:28:25,680 --> 00:28:29,589 Speaker 2: what are called intra Indust industry spillovers. So supposing that 506 00:28:29,599 --> 00:28:32,170 Speaker 2: there's FT I in your industry, 507 00:28:32,780 --> 00:28:36,379 Speaker 2: are there spillovers to firms which didn't receive that FT 508 00:28:36,390 --> 00:28:39,219 Speaker 2: I just because they happen to be in that industry. 509 00:28:39,270 --> 00:28:42,550 Speaker 2: So intra industry spillovers. Second, 510 00:28:43,260 --> 00:28:46,189 Speaker 2: are there spillovers to the firm because it's a supplier 511 00:28:46,199 --> 00:28:51,319 Speaker 2: firm to somebody downstream who is getting FD I? And third, 512 00:28:51,329 --> 00:28:54,050 Speaker 2: um you know, are you getting spillovers because you are 513 00:28:54,270 --> 00:28:58,469 Speaker 2: the user of products um of some firms upstream which 514 00:28:58,479 --> 00:29:00,800 Speaker 2: are getting FD I. So essentially you can use this 515 00:29:00,810 --> 00:29:04,500 Speaker 2: data to measure what are called intra industry spillovers, forward 516 00:29:04,510 --> 00:29:06,640 Speaker 2: linkages and backward linkages. 517 00:29:07,510 --> 00:29:10,989 Speaker 2: And when we do this using this big uh database, we, 518 00:29:11,020 --> 00:29:13,619 Speaker 2: we find some striking results. First, 519 00:29:14,369 --> 00:29:18,420 Speaker 2: there are positive intra industries spillovers, but those are restricted 520 00:29:18,430 --> 00:29:21,949 Speaker 2: to advanced economies. That's interesting to begin with. Why 521 00:29:22,670 --> 00:29:26,599 Speaker 2: here's how we rationalize that result in an advanced economy. 522 00:29:26,609 --> 00:29:27,530 Speaker 2: When you get 523 00:29:27,839 --> 00:29:31,890 Speaker 2: FD I inside an industry, the other firms in that 524 00:29:31,900 --> 00:29:36,569 Speaker 2: industry are normally at a similar technological level. So when 525 00:29:36,579 --> 00:29:40,060 Speaker 2: one firm, let's say gets FD I, this induces the 526 00:29:40,069 --> 00:29:42,650 Speaker 2: others to become more competitive, we call this the pro 527 00:29:42,719 --> 00:29:45,739 Speaker 2: competition effect, right? They have to up their game in 528 00:29:45,750 --> 00:29:48,140 Speaker 2: order to kind of keep up with the firm that's 529 00:29:48,150 --> 00:29:51,459 Speaker 2: getting the FD I. So this is a pro competition effect, 530 00:29:51,469 --> 00:29:52,790 Speaker 2: which is a positive spillover. 531 00:29:53,989 --> 00:29:58,209 Speaker 2: We do not find this effect. Paul EMD, why that, 532 00:29:58,219 --> 00:30:01,849 Speaker 2: why might that be? Because we think in EMD, the 533 00:30:01,859 --> 00:30:06,119 Speaker 2: market stealing effect could be stronger than the pro competition effect. 534 00:30:06,130 --> 00:30:09,560 Speaker 2: So let's say that the other firms in the industry 535 00:30:09,630 --> 00:30:12,569 Speaker 2: are not quite at the same technological level as the 536 00:30:12,579 --> 00:30:15,180 Speaker 2: favored firm, which is getting the FD I. Well, in 537 00:30:15,189 --> 00:30:17,060 Speaker 2: that case, the FD to the favored firm 538 00:30:17,155 --> 00:30:20,214 Speaker 2: could cause the other firms to fall further behind and 539 00:30:20,224 --> 00:30:23,785 Speaker 2: lose market share to the firm that's getting FD I. 540 00:30:24,005 --> 00:30:26,944 Speaker 2: And if the market stealing effect is stronger than the 541 00:30:26,954 --> 00:30:30,604 Speaker 2: pro competition effect, then you won't find any, any positive 542 00:30:30,614 --> 00:30:34,364 Speaker 2: coefficient there. And that's what we find for em Ds. Now, 543 00:30:34,905 --> 00:30:37,984 Speaker 2: what we do find very power powerfully for em DS and, 544 00:30:37,994 --> 00:30:41,525 Speaker 2: and not for advanced economies is backward linkages. 545 00:30:41,920 --> 00:30:43,729 Speaker 2: What does this mean? It, it means that if you 546 00:30:43,739 --> 00:30:46,160 Speaker 2: have FD I in a, in a particular firm or 547 00:30:46,170 --> 00:30:50,560 Speaker 2: a particular sector, there are positive productivity spillovers to supply 548 00:30:50,569 --> 00:30:53,890 Speaker 2: of firms which are upstream. So all those firms which 549 00:30:53,900 --> 00:30:57,099 Speaker 2: are supplying inputs to the firms which are getting FD 550 00:30:57,109 --> 00:31:01,569 Speaker 2: I seem to get productivity spillovers. And this is just 551 00:31:01,579 --> 00:31:04,459 Speaker 2: like a classic channel in the development literature. This is 552 00:31:04,469 --> 00:31:07,219 Speaker 2: what we expect. This is what we see. So not 553 00:31:07,229 --> 00:31:09,719 Speaker 2: only does FD I help the firms that you're directly 554 00:31:09,729 --> 00:31:11,250 Speaker 2: investing in. But 555 00:31:11,650 --> 00:31:14,910 Speaker 2: it means that the firm now becomes a more exacting 556 00:31:15,119 --> 00:31:19,050 Speaker 2: demander of skilled inputs. And so it forces all the 557 00:31:19,060 --> 00:31:22,900 Speaker 2: input suppliers to up their technology, to up their productivity, 558 00:31:22,910 --> 00:31:25,550 Speaker 2: to up the sophistication of what they're supplying. 559 00:31:25,829 --> 00:31:28,839 Speaker 2: So there is this this positive restraint. So those are the, 560 00:31:28,849 --> 00:31:32,250 Speaker 2: those are the kind of main um results that we 561 00:31:32,260 --> 00:31:34,810 Speaker 2: find um you know, happy to elaborate more. 562 00:31:35,339 --> 00:31:39,430 Speaker 1: So Shekhar you said that uh in the intra industry spillover, 563 00:31:39,439 --> 00:31:42,390 Speaker 1: it's more uh robust in the case, or you find 564 00:31:42,550 --> 00:31:45,859 Speaker 1: such a significant coefficient in the case of developed markets, 565 00:31:45,869 --> 00:31:48,359 Speaker 1: but not for emerging markets. But what about the uh 566 00:31:48,369 --> 00:31:51,410 Speaker 1: download linkage and upper linkage those areas E MD M 567 00:31:51,420 --> 00:31:52,569 Speaker 1: similar effects. 568 00:31:53,219 --> 00:31:55,839 Speaker 2: So we find these very strong backward linkages for E 569 00:31:55,849 --> 00:31:58,349 Speaker 2: MD ES not for advanced economies. 570 00:31:59,290 --> 00:32:03,069 Speaker 1: OK. Fascinating. So exactly what a development literature would suggest. 571 00:32:03,750 --> 00:32:06,939 Speaker 2: Absolutely, I mean, because there's they are further from the 572 00:32:06,949 --> 00:32:10,109 Speaker 2: technological frontier. So when they get the FD I, there 573 00:32:10,119 --> 00:32:13,770 Speaker 2: are these strong incentives for firms which are, you know, 574 00:32:13,780 --> 00:32:16,250 Speaker 2: at different parts of the value chain to kind of 575 00:32:16,260 --> 00:32:19,229 Speaker 2: up their game to participate fully in it, 576 00:32:19,869 --> 00:32:24,310 Speaker 1: right? And if we are talking about types of FD I, 577 00:32:24,319 --> 00:32:26,219 Speaker 1: because you touched upon the issue that you know, your 578 00:32:26,229 --> 00:32:28,569 Speaker 1: database also allows you to look at FD I in 579 00:32:28,579 --> 00:32:31,369 Speaker 1: the form of cross border MN A. Um is that 580 00:32:31,380 --> 00:32:35,140 Speaker 1: more potent or less potent than a typical rec congestion 581 00:32:35,150 --> 00:32:36,010 Speaker 1: of capital in the company. 582 00:32:37,040 --> 00:32:39,359 Speaker 2: So we actually find that the MN A data is 583 00:32:39,369 --> 00:32:44,079 Speaker 2: a lot noisier and our estimates are far less precise 584 00:32:44,089 --> 00:32:46,339 Speaker 2: when it comes to M and A compared to Greenfield. 585 00:32:46,819 --> 00:32:48,949 Speaker 2: Um As far as we're aware, we are the first 586 00:32:48,959 --> 00:32:51,349 Speaker 2: study to actually put them side by side. So most 587 00:32:51,359 --> 00:32:54,579 Speaker 2: of the studies are on Greenfield and don't consider MN 588 00:32:54,589 --> 00:32:58,199 Speaker 2: A at all. We also find some some. So, so 589 00:32:58,209 --> 00:33:01,949 Speaker 2: we can confirm for MN A, the positive intra industries 590 00:33:01,959 --> 00:33:05,959 Speaker 2: spillovers result for a a for for advanced economies, right, 591 00:33:05,969 --> 00:33:09,520 Speaker 2: which I talked about for Greenfield, that result is still there. 592 00:33:09,839 --> 00:33:13,719 Speaker 2: Uh But the backward linkages for em DS they disappear. 593 00:33:14,410 --> 00:33:17,520 Speaker 2: So we do not find that for MN A, um 594 00:33:17,530 --> 00:33:20,910 Speaker 2: we can only speculate on why that might be um 595 00:33:21,000 --> 00:33:24,229 Speaker 2: one speculation is the following. You know, when you have 596 00:33:24,239 --> 00:33:25,619 Speaker 2: Greenfield investment 597 00:33:26,290 --> 00:33:31,060 Speaker 2: in an emerging economy, almost by definition, you are expanding 598 00:33:31,069 --> 00:33:34,010 Speaker 2: the market for local suppliers, right? Because we are you 599 00:33:34,020 --> 00:33:36,510 Speaker 2: are you are adding new business activities. So there's more 600 00:33:36,520 --> 00:33:37,979 Speaker 2: business for the local suppliers 601 00:33:38,369 --> 00:33:40,869 Speaker 2: if you've got ma what you're doing is essentially you're 602 00:33:40,880 --> 00:33:44,530 Speaker 2: taking over something that already exists. So you're not necessarily 603 00:33:44,540 --> 00:33:48,060 Speaker 2: adding to the demand for local suppliers in the same 604 00:33:48,069 --> 00:33:51,229 Speaker 2: way that Greenfield is. And in fact, if you're taking 605 00:33:51,239 --> 00:33:55,119 Speaker 2: over an existing firm, you may disrupt um you may 606 00:33:55,130 --> 00:33:59,430 Speaker 2: disrupt existing local supplier relationships. For example, you may 607 00:33:59,594 --> 00:34:03,334 Speaker 2: to import your inputs. Um you know, compared to the 608 00:34:03,344 --> 00:34:06,275 Speaker 2: old system where you were looking to local suppliers. So 609 00:34:06,285 --> 00:34:08,875 Speaker 2: these may be some reasons why we do not find 610 00:34:08,885 --> 00:34:12,014 Speaker 2: for MN A, the same backward linkages that we found 611 00:34:12,024 --> 00:34:14,344 Speaker 2: for Greenfield. But I think this is an area that's 612 00:34:14,354 --> 00:34:16,685 Speaker 2: going to take a lot of further research to actually 613 00:34:16,695 --> 00:34:19,864 Speaker 2: sort out and explain uh some of these, some of 614 00:34:19,875 --> 00:34:20,694 Speaker 2: these results 615 00:34:21,810 --> 00:34:26,429 Speaker 1: here, I'm thinking aloud if the types of industry make 616 00:34:26,439 --> 00:34:29,260 Speaker 1: a difference like FD I going into oil and gas, 617 00:34:29,270 --> 00:34:31,520 Speaker 1: which has, you know, all sorts of negative external its 618 00:34:32,080 --> 00:34:34,510 Speaker 1: and may not be the passion of, you know, improvement 619 00:34:34,520 --> 00:34:38,109 Speaker 1: in productivity given that they are largely mechanized industries. Anyway, 620 00:34:38,209 --> 00:34:41,679 Speaker 1: maybe we don't get as much productivity bang or spill 621 00:34:41,689 --> 00:34:45,909 Speaker 1: over there. As opposed to say FD I going into 622 00:34:45,919 --> 00:34:49,330 Speaker 1: high tech industries which would immediately diffuse into the rest 623 00:34:49,340 --> 00:34:51,020 Speaker 1: of the sector. What's your thought on that? 624 00:34:52,688 --> 00:34:56,108 Speaker 2: Yeah, I think that's, that's a fascinating area for research. 625 00:34:56,118 --> 00:35:00,368 Speaker 2: We don't have the kind of finely grained sector decompositions 626 00:35:00,378 --> 00:35:03,269 Speaker 2: that you would need to answer that type of question. 627 00:35:03,529 --> 00:35:05,698 Speaker 2: But I think that this is very relevant. You know, 628 00:35:05,708 --> 00:35:09,989 Speaker 2: a lot of people are also talking about strategic sectors 629 00:35:09,998 --> 00:35:13,378 Speaker 2: and you know, whether, you know, you're, you're aware that 630 00:35:13,388 --> 00:35:17,018 Speaker 2: in things like trade disputes and FD I restrictions, there's 631 00:35:17,029 --> 00:35:18,428 Speaker 2: a lot of concern that 632 00:35:18,969 --> 00:35:22,070 Speaker 2: you know about strategic sectors in pa in particular. And 633 00:35:22,080 --> 00:35:24,250 Speaker 2: these strategic sectors are often the kind of high tech 634 00:35:24,260 --> 00:35:27,929 Speaker 2: sectors that you mentioned. So, so yeah, I think, I 635 00:35:27,939 --> 00:35:30,879 Speaker 2: think the profession will need to try to discriminate between 636 00:35:30,889 --> 00:35:34,600 Speaker 2: these different sectors and, and look at how important spillovers 637 00:35:34,610 --> 00:35:36,669 Speaker 2: are from a heterogeneous point of view. 638 00:35:37,489 --> 00:35:40,989 Speaker 1: Oh, that's a very good segue to my final question. 639 00:35:41,000 --> 00:35:44,189 Speaker 1: Trigger on industrial policy because the moment you said, you know, 640 00:35:44,199 --> 00:35:46,810 Speaker 1: strategic sectors and so on, I mean, look, it's so 641 00:35:46,820 --> 00:35:49,419 Speaker 1: much in vogue now it was something that East Asian 642 00:35:49,429 --> 00:35:52,029 Speaker 1: countries did and now everybody wants to do it. So 643 00:35:52,280 --> 00:35:55,509 Speaker 1: what's your thought on industrial policy? 644 00:35:57,790 --> 00:36:00,320 Speaker 2: So, so look, I I think first of all, like, 645 00:36:00,330 --> 00:36:03,830 Speaker 2: you know, everybody uses industrial policy in a different way 646 00:36:03,840 --> 00:36:07,330 Speaker 2: and they mean different things and the conversation can often 647 00:36:07,340 --> 00:36:10,830 Speaker 2: get derailed because the participants in it mean fundamentally different 648 00:36:10,840 --> 00:36:14,419 Speaker 2: things by industrial policy. So let me perhaps start by 649 00:36:14,429 --> 00:36:15,169 Speaker 2: saying that, 650 00:36:16,090 --> 00:36:19,370 Speaker 2: you know, I would be in favor of industrial policy 651 00:36:20,590 --> 00:36:23,530 Speaker 2: if you defined it in a certain way, as I'm 652 00:36:23,540 --> 00:36:28,569 Speaker 2: sure would be 99.9% of professional economists. So if the 653 00:36:28,580 --> 00:36:33,569 Speaker 2: idea was that sometimes there are externalities and governments need 654 00:36:33,580 --> 00:36:37,279 Speaker 2: to have public policy measures to cure these externalities. Let 655 00:36:37,290 --> 00:36:41,229 Speaker 2: me give you an example. Climate change is perhaps the 656 00:36:41,239 --> 00:36:44,449 Speaker 2: biggest externality of our generation 657 00:36:44,879 --> 00:36:49,100 Speaker 2: to the extent that governments try to have public incentives 658 00:36:49,110 --> 00:36:53,419 Speaker 2: to channel resources into industries, which would combat climate change. 659 00:36:53,699 --> 00:36:57,620 Speaker 2: I think an overwhelming majority of economists would say that 660 00:36:57,629 --> 00:37:01,379 Speaker 2: that's fine. That's good. That's what the econ 11 textbook 661 00:37:01,389 --> 00:37:02,820 Speaker 2: suggests that you should be doing. 662 00:37:03,570 --> 00:37:08,989 Speaker 2: So, you know, if it's simply incentivizing the private sector 663 00:37:09,000 --> 00:37:12,840 Speaker 2: to tackle something to, to overcome an externality, I think 664 00:37:12,850 --> 00:37:15,169 Speaker 2: we can all be in favor of that. I think 665 00:37:15,179 --> 00:37:20,090 Speaker 2: what's much more insidious is trying to pick winners and 666 00:37:20,100 --> 00:37:25,709 Speaker 2: losers among particular firms and particular industries. Um when there's 667 00:37:25,719 --> 00:37:29,610 Speaker 2: no obvious externality when it's just the government, 668 00:37:30,030 --> 00:37:32,280 Speaker 2: you know, thinking that this is the sector of the 669 00:37:32,290 --> 00:37:34,659 Speaker 2: future and we have to support it. First of all, 670 00:37:34,669 --> 00:37:37,070 Speaker 2: we know that governments have a terrible track record with 671 00:37:37,080 --> 00:37:40,419 Speaker 2: picking winners and losers. And it's not obvious that they 672 00:37:40,429 --> 00:37:45,529 Speaker 2: have a better crystal ball um than Wall Street and financiers. 673 00:37:45,540 --> 00:37:48,530 Speaker 2: So if there's no obvious externality, it's not clear why 674 00:37:48,540 --> 00:37:52,479 Speaker 2: the government should be involved. Um And, you know, 675 00:37:53,139 --> 00:37:56,899 Speaker 2: my personal history is, I'm from India, I lived through 676 00:37:56,909 --> 00:38:00,840 Speaker 2: the era of Nehru and socialism where, you know Indian 677 00:38:00,850 --> 00:38:04,800 Speaker 2: planners were constantly trying to channel resources to favored sectors. 678 00:38:04,969 --> 00:38:07,759 Speaker 2: You had government monopolies in the commanding heights of the 679 00:38:07,770 --> 00:38:11,739 Speaker 2: economy and it wasn't such a successful experiment, right? It 680 00:38:11,750 --> 00:38:15,120 Speaker 2: took the liberalization of the mid 19 eighties and the 681 00:38:15,129 --> 00:38:17,830 Speaker 2: mid 19 nineties to get away from that mindset. 682 00:38:18,179 --> 00:38:21,089 Speaker 2: And once that was in the rearview mirror, you had 683 00:38:21,100 --> 00:38:23,739 Speaker 2: a step change in economic growth, you had a massive 684 00:38:23,750 --> 00:38:26,699 Speaker 2: reduction in poverty, you had all kinds of things that 685 00:38:26,709 --> 00:38:29,790 Speaker 2: weren't going on. Uh you know, during what you might 686 00:38:29,800 --> 00:38:33,239 Speaker 2: call the industrial policy era. Now, you know, people have 687 00:38:33,250 --> 00:38:37,428 Speaker 2: pointed to successful examples of industrial policy. Uh South Korea 688 00:38:37,439 --> 00:38:41,409 Speaker 2: is often mentioned, but uh again, I think one needs 689 00:38:41,419 --> 00:38:44,120 Speaker 2: to go into the nitty gritty of it. Um First 690 00:38:44,129 --> 00:38:44,698 Speaker 2: of all, 691 00:38:45,219 --> 00:38:47,659 Speaker 2: I think one needs to have an honest effort at 692 00:38:47,669 --> 00:38:52,080 Speaker 2: the counterfactual, you know, South Korea had a highly educated population, 693 00:38:52,219 --> 00:38:55,790 Speaker 2: it had clean standards of governance, it had excellent rule 694 00:38:55,800 --> 00:38:58,850 Speaker 2: of law. Um So it's not clear to me that 695 00:38:58,860 --> 00:39:01,569 Speaker 2: in a counterfactual where they didn't do industrial policy, they 696 00:39:01,580 --> 00:39:03,669 Speaker 2: wouldn't have done equally well, maybe they would have done 697 00:39:03,679 --> 00:39:06,429 Speaker 2: even better, right? Given that they had all these other 698 00:39:06,629 --> 00:39:09,699 Speaker 2: conditions for for growth which we know are very important 699 00:39:09,709 --> 00:39:10,149 Speaker 2: for growth. 700 00:39:10,790 --> 00:39:15,489 Speaker 2: Secondly, to the extent that they subsidize the table, 701 00:39:16,139 --> 00:39:19,560 Speaker 2: it should be noted that the c were export oriented 702 00:39:19,570 --> 00:39:24,479 Speaker 2: firms which faced market discipline in international markets and global 703 00:39:24,489 --> 00:39:28,399 Speaker 2: competition from other world leading technology firms. So I think 704 00:39:28,409 --> 00:39:32,260 Speaker 2: that's one important lesson like if you must do industrial policy, 705 00:39:32,550 --> 00:39:36,060 Speaker 2: at least do it in an export oriented sector which 706 00:39:36,070 --> 00:39:39,989 Speaker 2: faces natural competition from outside, you know, in India, the 707 00:39:40,000 --> 00:39:42,010 Speaker 2: industrial policy was for 708 00:39:42,360 --> 00:39:45,178 Speaker 2: was for companies which were supposed to service the domestic 709 00:39:45,189 --> 00:39:48,699 Speaker 2: market and essentially had no competition. And then of course, 710 00:39:48,709 --> 00:39:51,500 Speaker 2: there's the danger that you're just throwing bad money off 711 00:39:51,510 --> 00:39:54,530 Speaker 2: to good and there's no competitive pressure to make sure 712 00:39:54,540 --> 00:39:56,419 Speaker 2: that there's any kind of actual advancement. 713 00:39:56,760 --> 00:39:59,060 Speaker 2: So Yeah, it's a subtle issue. Um, I think it 714 00:39:59,070 --> 00:40:02,279 Speaker 2: depends on what exactly you mean by industrial policy. If 715 00:40:02,290 --> 00:40:06,439 Speaker 2: it's a matter of getting the basics right. Um, incentivizing, uh, 716 00:40:06,449 --> 00:40:10,060 Speaker 2: public externalities to be, to be combated, then I think 717 00:40:10,070 --> 00:40:13,389 Speaker 2: it's an excellent idea. If it's about picking winners and losers, 718 00:40:13,399 --> 00:40:16,820 Speaker 2: individual firms in individual industries, then no. 719 00:40:17,570 --> 00:40:21,209 Speaker 1: Yes. Also there is a issue related to survival bias. 720 00:40:21,219 --> 00:40:24,310 Speaker 1: We've looked at certain industries in Japan and Korea that 721 00:40:24,320 --> 00:40:28,760 Speaker 1: succeeded ignoring the fact that many, many billions of dollars 722 00:40:28,770 --> 00:40:32,290 Speaker 1: were wasted in corruption or poor investment ideas. Because to 723 00:40:32,300 --> 00:40:35,320 Speaker 1: your point, bureaucrats can't really pick winners and losers that 724 00:40:35,330 --> 00:40:40,070 Speaker 1: efficiently Shekhar. What about the lesson from China, which of 725 00:40:40,080 --> 00:40:41,350 Speaker 1: course has also been, 726 00:40:41,600 --> 00:40:44,610 Speaker 1: you know, designating industrial champions. But I think one thing 727 00:40:44,620 --> 00:40:49,149 Speaker 1: that characters somewhat differently from others, it's a big economy 728 00:40:49,159 --> 00:40:54,260 Speaker 1: and which allows it to have substantial interprovincial competition. 729 00:40:54,590 --> 00:40:58,010 Speaker 1: Uh so capital can go to certain industries here and there. 730 00:40:58,020 --> 00:41:00,290 Speaker 1: But then it's not just for one company and many 731 00:41:00,300 --> 00:41:03,239 Speaker 1: companies fight each other, which we're seeing with Chinese EVs 732 00:41:03,250 --> 00:41:06,280 Speaker 1: for example. So would that be a kind of a 733 00:41:06,290 --> 00:41:08,310 Speaker 1: lesson that you would take that if somebody wants to 734 00:41:08,320 --> 00:41:12,469 Speaker 1: pursue industrial policy, that they would, they should ensure that 735 00:41:12,479 --> 00:41:13,870 Speaker 1: competition stays? 736 00:41:14,770 --> 00:41:17,320 Speaker 2: Absolutely. I mean, II I think you couldn't have said 737 00:41:17,330 --> 00:41:19,540 Speaker 2: it better. Let me first say that the point you 738 00:41:19,550 --> 00:41:21,969 Speaker 2: made about survival bias I think is a very important 739 00:41:21,979 --> 00:41:24,590 Speaker 2: one and I think it's kind of related to the 740 00:41:24,600 --> 00:41:27,909 Speaker 2: point that I'm making about counterfactual, right? One doesn't know 741 00:41:28,070 --> 00:41:30,340 Speaker 2: what the counterfactual would have been in the absence of 742 00:41:30,350 --> 00:41:31,310 Speaker 2: industrial policy. 743 00:41:31,600 --> 00:41:36,080 Speaker 2: Um Yeah, so I indeed, so you're pointing to alternative mechanisms, 744 00:41:36,090 --> 00:41:39,540 Speaker 2: so competition can occur at the export level where you're 745 00:41:39,550 --> 00:41:42,739 Speaker 2: competing with other countries and other global firms, but it 746 00:41:42,750 --> 00:41:47,120 Speaker 2: can occur internally as well in terms of interprovincial competition. 747 00:41:47,850 --> 00:41:50,060 Speaker 2: However, whatever the source of the competition, I think it's 748 00:41:50,070 --> 00:41:54,389 Speaker 2: extremely important to keep competition alive if you've got industrial 749 00:41:54,399 --> 00:41:58,590 Speaker 2: policy because industrial policy without the competition is almost a 750 00:41:58,600 --> 00:42:02,459 Speaker 2: guarantee that, you know, you're just sending bad, good money 751 00:42:02,469 --> 00:42:06,110 Speaker 2: after bad and there's no accountability and no sense in 752 00:42:06,120 --> 00:42:09,070 Speaker 2: which an inefficient firm will ever exit the market. So, 753 00:42:09,080 --> 00:42:11,219 Speaker 2: so one must try to avoid that at all costs. 754 00:42:12,439 --> 00:42:16,229 Speaker 1: Um I've been thinking about this issue of tech related 755 00:42:16,239 --> 00:42:20,100 Speaker 1: industrial policy lately that the US and its allies are 756 00:42:20,110 --> 00:42:23,029 Speaker 1: very keen to make sure certain leading as technology does 757 00:42:23,040 --> 00:42:24,979 Speaker 1: not fall into the hands of the Chinese that they 758 00:42:24,989 --> 00:42:27,699 Speaker 1: don't have the capability of replicating some of the, 759 00:42:28,010 --> 00:42:32,379 Speaker 1: you know, tiniest chips that's out there. Uh And uh and, 760 00:42:32,389 --> 00:42:35,040 Speaker 1: and I hear these arguments that it's really not possible 761 00:42:35,050 --> 00:42:39,139 Speaker 1: to fragment the world that way anymore. Uh chips are 762 00:42:39,149 --> 00:42:43,199 Speaker 1: available in open markets, they can leak into China even 763 00:42:43,209 --> 00:42:46,750 Speaker 1: if the West is keen on preventing it. And therefore 764 00:42:47,030 --> 00:42:50,389 Speaker 1: this just creates inefficiencies, but ultimately, it is futile. Uh 765 00:42:50,399 --> 00:42:51,429 Speaker 1: Any thoughts. 766 00:42:52,899 --> 00:42:55,889 Speaker 2: Yeah, I I think that there's two different things going 767 00:42:55,899 --> 00:42:59,600 Speaker 2: on here. So one is kind of the technological element 768 00:42:59,610 --> 00:43:03,310 Speaker 2: that you refer to. So is it really possible when 769 00:43:03,320 --> 00:43:07,169 Speaker 2: you have, let's say dual use technology for chips to 770 00:43:07,179 --> 00:43:12,120 Speaker 2: kind of distinguish between chips that have military applications and chips, 771 00:43:12,129 --> 00:43:15,379 Speaker 2: which are high tech without being military, maybe technologically, it's 772 00:43:15,389 --> 00:43:17,069 Speaker 2: just not possible to do that division 773 00:43:18,120 --> 00:43:20,959 Speaker 2: but the the danger that I see as even greater 774 00:43:20,969 --> 00:43:25,060 Speaker 2: than that is the political economy danger. Because once you, 775 00:43:25,129 --> 00:43:28,179 Speaker 2: once you tell a politician that yeah, you know, you can, 776 00:43:28,189 --> 00:43:30,489 Speaker 2: you can ban this or you can put non tariff 777 00:43:30,500 --> 00:43:35,219 Speaker 2: barriers uh by appealing to national security. Then very quickly, 778 00:43:35,229 --> 00:43:39,770 Speaker 2: the definition of national national security becomes extremely elastic. So 779 00:43:39,780 --> 00:43:42,319 Speaker 2: I would remind you of, of the Trump tariffs on 780 00:43:42,330 --> 00:43:43,449 Speaker 2: steel and aluminum, 781 00:43:43,770 --> 00:43:48,388 Speaker 2: these were imposed on national security grounds, right? I mean, 782 00:43:48,399 --> 00:43:50,790 Speaker 2: this is something that hadn't been used, I think for 783 00:43:50,800 --> 00:43:52,370 Speaker 2: 20 or 30 years before that 784 00:43:53,360 --> 00:43:58,449 Speaker 2: national security grounds, but steel and aluminum across the board, 785 00:43:58,969 --> 00:44:02,839 Speaker 2: including from the Eu and Japan. So that's a very 786 00:44:02,850 --> 00:44:05,709 Speaker 2: elastic definition of national security. 787 00:44:06,399 --> 00:44:10,810 Speaker 2: Recently, the Joe Biden administration was raising questions about Nippon 788 00:44:10,820 --> 00:44:15,229 Speaker 2: steel investing in the steel sector in, in, in the US. So, 789 00:44:15,239 --> 00:44:18,320 Speaker 2: you know, when you're talking about, about things like security 790 00:44:18,330 --> 00:44:21,280 Speaker 2: in the context of Japan, there's hardly a closer ally 791 00:44:21,290 --> 00:44:24,540 Speaker 2: that the US has, it becomes very elastic. So my 792 00:44:24,550 --> 00:44:26,529 Speaker 2: concern is not just the tech 793 00:44:26,774 --> 00:44:30,564 Speaker 2: logical point you're raising about whether you can distinguish national 794 00:44:30,574 --> 00:44:34,764 Speaker 2: security related trade from, from other types of trade. But 795 00:44:34,774 --> 00:44:38,283 Speaker 2: also the political economy dimension is very tempting for politicians 796 00:44:38,294 --> 00:44:42,205 Speaker 2: to just become protectionist under the guise of national security. 797 00:44:42,215 --> 00:44:44,245 Speaker 2: So I think it's very dangerous path to go down. 798 00:44:45,340 --> 00:44:48,689 Speaker 1: Ok. That's a very, very apt note to end on Shekhar. 799 00:44:48,699 --> 00:44:50,429 Speaker 1: I know you've been nursing a call. So I'm really 800 00:44:50,439 --> 00:44:52,159 Speaker 1: grateful that you made the time to come to this 801 00:44:52,169 --> 00:44:54,729 Speaker 1: podcast and talk about these two very important subjects. So 802 00:44:54,739 --> 00:44:56,678 Speaker 1: thank you very much for your time and insights. 803 00:44:57,550 --> 00:44:59,959 Speaker 2: Thank you, Temur. Thanks for inviting me. Great to be 804 00:44:59,969 --> 00:45:00,359 Speaker 2: with you. 805 00:45:00,780 --> 00:45:03,889 Speaker 1: Fantastic. And thanks to our listeners and viewers as well. 806 00:45:04,179 --> 00:45:07,138 Speaker 1: Copy time was produced by Ken Delbridge at Spy Studios, 807 00:45:07,179 --> 00:45:10,409 Speaker 1: Violet Le and Daisy Sharma provided additional assistance. It is 808 00:45:10,419 --> 00:45:13,600 Speaker 1: for information only and does not represent any trade recommendations. 809 00:45:13,830 --> 00:45:17,379 Speaker 1: All 130 episodes of the podcast are available on youtube 810 00:45:17,510 --> 00:45:21,719 Speaker 1: and on all major podcast platforms including Apple and Spotify. 811 00:45:21,889 --> 00:45:24,959 Speaker 1: As for our research publications, webinars and live streams, you 812 00:45:24,969 --> 00:45:27,899 Speaker 1: can find them all by Googling devious research library. Have 813 00:45:27,909 --> 00:45:28,639 Speaker 1: a great day.