WEBVTT - What Makes Some Emerging Markets Always Win? 0:00:02.120 --> 0:00:06.760 Emerging markets are where the growth is no weight. Emerging 0:00:06.800 --> 0:00:09.560 markets are being hit by US interest rates and a 0:00:09.640 --> 0:00:14.400 trade war? Can both be true? How do you separate 0:00:14.560 --> 0:00:28.600 emerging market wheat from chaff? Welcome to Bensons. I'm Daniel Moss, 0:00:28.960 --> 0:00:34.599 columnist at Bloomberg Opinion in New York. What actually is 0:00:35.080 --> 0:00:38.560 an emerging market? And how do the really good ones 0:00:39.000 --> 0:00:43.880 stay hot? Here to help us find out is Anu Madgavta, 0:00:44.240 --> 0:00:48.920 a partner at McKinsey Global Institute in Mumbai. Now, Annu 0:00:49.080 --> 0:00:52.760 is really the perfect person to help steer us through 0:00:52.840 --> 0:00:56.040 this e M thicket. She's the lead author of a 0:00:56.120 --> 0:01:02.160 McKinsey report called out Performers, high growth Emerging Economies and 0:01:02.200 --> 0:01:05.640 the companies that propel them and who thanks for joining us. 0:01:06.560 --> 0:01:10.240 Happy to be here. Let's start with a basic question 0:01:10.840 --> 0:01:15.160 for which I rarely get a clear answer. What is 0:01:15.680 --> 0:01:19.640 an emerging market? I mean, it's tough to say that 0:01:19.760 --> 0:01:24.520 Mexico equals Malaysia equals Malawi? How should we be thinking 0:01:24.560 --> 0:01:28.959 about this question? So you're right, Dan, emerging markets. You know, 0:01:29.000 --> 0:01:31.600 there are a very large number of economies that are 0:01:32.080 --> 0:01:35.440 variously called emerging or developing, and they're all actually very 0:01:35.480 --> 0:01:40.320 different from one another. So we actually have focused on 0:01:40.400 --> 0:01:45.320 the idea of economies that are growing rapidly. So growth 0:01:45.400 --> 0:01:48.480 momentum is, you know, the most exciting feature of an 0:01:48.520 --> 0:01:52.320 emerging economy for us. So we start by looking back 0:01:52.360 --> 0:01:56.400 in time and really thinking about emerging markets as those 0:01:56.480 --> 0:02:00.600 that weren't rich to begin with, and then really asking 0:02:00.600 --> 0:02:03.960 the question of how fast are these economies narrowing the 0:02:04.000 --> 0:02:08.720 gap between themselves and other richer countries. So looking back 0:02:08.760 --> 0:02:12.119 to the mid eighties, we really look at which countries 0:02:12.160 --> 0:02:16.080 weren't high income countries basically defined as at the level 0:02:16.120 --> 0:02:19.639 of about six thousand dollars per capita of GDP at 0:02:19.720 --> 0:02:23.160 that time, and we have a universe of about seventy 0:02:23.200 --> 0:02:27.800 significantly large economies that sort of meet that criterion, and 0:02:27.840 --> 0:02:30.680 then we filter from there a set that have actually 0:02:30.720 --> 0:02:34.920 sustained very rapid per capita GDP growth over a twenty 0:02:34.919 --> 0:02:37.320 to fifty year periods. So going back to the mid 0:02:37.360 --> 0:02:41.080 sixties or then starting from the early nineties, over twenty 0:02:41.080 --> 0:02:44.960 to fifty years, some of these countries seemed to become 0:02:45.320 --> 0:02:50.000 very buzzy for a while, like Poland or Brazil, and 0:02:50.040 --> 0:02:54.519 then fall on challenging times. What makes for a sustained 0:02:55.160 --> 0:03:01.080 successful performance. Not many of these have actually stained performance 0:03:01.120 --> 0:03:04.680 over long periods of time. We found just eighteen countries, 0:03:05.160 --> 0:03:08.000 of which seven actually did it over fifty years and 0:03:08.040 --> 0:03:12.240 another eleven did it over twenty years. So staying turbo 0:03:12.360 --> 0:03:16.400 charged for long periods of time actually requires you know, 0:03:16.480 --> 0:03:21.080 two or three essential elements. The most important of these 0:03:21.200 --> 0:03:24.200 is actually a sort of culture and a set of 0:03:24.280 --> 0:03:29.480 institutions that inspire and facilitate people to save and companies 0:03:29.480 --> 0:03:34.000 to invest. So the whole savings and investment, the productive 0:03:34.120 --> 0:03:37.119 use of the accumulation of capital, and then the productive 0:03:37.240 --> 0:03:42.080 use of that capital typically has accounted for sixty or 0:03:42.200 --> 0:03:47.440 more of growth amongst these eighteen outperformer economies that have 0:03:47.520 --> 0:03:50.720 sustained growth over long periods of time. And then the 0:03:50.800 --> 0:03:54.200 other aspect of what it takes to succeed is really 0:03:54.720 --> 0:04:00.240 institutions that have fostered competition and innovation and therefore growth 0:04:00.280 --> 0:04:05.400 in total factor productivity. And that's another roughly of growth. Well, 0:04:05.400 --> 0:04:09.440 when you start talking about total factor productivity, you're starting 0:04:09.480 --> 0:04:12.880 to lose me. I'm just a journalist looking only with 0:04:13.000 --> 0:04:17.480 this list of eighteen, the vast majority of them allocated 0:04:17.520 --> 0:04:21.360 in Asia. Is there a secret source for that region. 0:04:22.560 --> 0:04:25.760 The set of countries that we call long term outperformers 0:04:25.800 --> 0:04:30.080 who have grown over about fifty years are actually all 0:04:30.520 --> 0:04:34.159 based in Asia. So here we include countries like China, 0:04:34.279 --> 0:04:38.760 South Korea, Singapore, and then Malaysia, Indonesia, Thailand and so on. 0:04:39.839 --> 0:04:43.360 So there is something about a sort of regional factor, 0:04:43.520 --> 0:04:45.840 the fact that you know, one or two large economies 0:04:45.880 --> 0:04:49.359 took off and that seems to have created some kinds 0:04:49.360 --> 0:04:52.520 of kind of ripple effect around the region. But if 0:04:52.560 --> 0:04:55.200 we look at the more recent set of out performers, 0:04:55.200 --> 0:04:58.640 which are the twenty growth stories, we do find some 0:04:58.800 --> 0:05:03.760 regional diversity there. We do have India and Vietnam, Cambodia, 0:05:03.880 --> 0:05:07.599 Laos from Asia. But then you also have Central Asian 0:05:07.640 --> 0:05:13.800 countries like Kazakhstan, Uzbekistan and Penistan which have grown over 0:05:13.839 --> 0:05:16.560 a period of time on the back of very different drivers. 0:05:17.200 --> 0:05:19.920 And then you actually have Ethiopia, which is in Africa, 0:05:19.960 --> 0:05:24.159 of course, so not not really close close to Asia 0:05:24.200 --> 0:05:27.000 in that sense. I'm so glad I knew that you 0:05:27.120 --> 0:05:30.719 mentioned Ethiopia. For those of us who came of age 0:05:30.760 --> 0:05:34.520 in the nineteen eighties, that seems like a head scratcher. 0:05:35.200 --> 0:05:39.280 We're used to pictures of famine and live aid rock concerts. 0:05:40.040 --> 0:05:45.800 What's going on with Ethiopia. I think Ethiopia has um. 0:05:46.000 --> 0:05:48.560 While it doesn't have you know, it's not in Asia, 0:05:48.600 --> 0:05:51.320 so it doesn't have the locational advantage of being near 0:05:51.400 --> 0:05:55.279 a very large growth country or a growth cluster, but 0:05:55.400 --> 0:05:59.960 it does have at least one other really important characteristic 0:06:00.040 --> 0:06:02.640 tick that we see in common across the out performers, 0:06:02.680 --> 0:06:06.400 and this is a set of very purposeful reforms that 0:06:06.440 --> 0:06:09.840 have actually opened up the market as well as created 0:06:09.880 --> 0:06:13.839 conditions conducive to investment. So Ethiopia came out of a 0:06:13.960 --> 0:06:17.800 very difficult civil war phase, but then in the eighties 0:06:18.200 --> 0:06:22.160 really started its first phase of reforms, which was very 0:06:22.200 --> 0:06:26.120 farming and agriculture oriented. In the early two thousands they 0:06:26.120 --> 0:06:29.880 actually moved into a much more infrastructure lad wave of 0:06:29.960 --> 0:06:32.240 reforms and growth, and on the back of that have 0:06:32.320 --> 0:06:35.880 been investing in a whole set of sectors and industries 0:06:36.040 --> 0:06:40.880 across logistics, you know, different kinds of manufacturing, including labor 0:06:40.880 --> 0:06:44.919 intensive manufacturing and so forth. So, like some of the 0:06:44.960 --> 0:06:48.479 other recent outperformers, there is work still to be done 0:06:48.600 --> 0:06:52.360 to sustain and in fact increased growth momentum. It's not 0:06:52.480 --> 0:06:56.160 that Ethiopia or any of the other countries can declare victory. 0:06:56.760 --> 0:07:00.279 But it's quite interesting that at least one country in 0:07:00.320 --> 0:07:04.000 the Sub Saharan Africa region has actually taken off over 0:07:04.040 --> 0:07:09.640 this period. How important is tried to being an emerging 0:07:09.720 --> 0:07:15.000 market star. Trade is an important aspect of or a 0:07:15.080 --> 0:07:19.000 common sort of aspect right of most if not all 0:07:19.040 --> 0:07:23.720 of our out performers, simply because I think being connected 0:07:23.840 --> 0:07:26.800 to the global economy has helped them do two things. 0:07:27.320 --> 0:07:31.760 One is tap very rapidly into new sources of demand. 0:07:32.320 --> 0:07:35.480 It's not the only source of demands, so domestic demand 0:07:35.560 --> 0:07:39.440 has played a big role. Domestic consumption and investment has 0:07:39.480 --> 0:07:42.280 played a big role in the growth of most out performers. 0:07:42.640 --> 0:07:47.400 But trade has given a very very attractive growth opportunity 0:07:47.440 --> 0:07:50.480 to many companies coming out of the emerging out of 0:07:50.520 --> 0:07:53.800 the out performers. And then the other thing that global 0:07:54.040 --> 0:07:57.200 connectedness has done, and I would say more, you know, 0:07:57.240 --> 0:08:00.240 even more than trade. It's just being connected with the 0:08:00.280 --> 0:08:03.880 rest of the world through all kinds of global flows 0:08:03.920 --> 0:08:08.480 that include um, you know, flows of information data, financial, 0:08:08.520 --> 0:08:14.200 flows of technology transfers f d I. It's just being 0:08:14.200 --> 0:08:19.320 connected that is actually also encouraged and enabled more innovation 0:08:19.480 --> 0:08:22.120 in many of the outperforming economies. So we would think 0:08:22.160 --> 0:08:26.440 global connectedness is actually quite an important driver in addition 0:08:26.480 --> 0:08:29.960 to the capital accumulation we already talked about. Sitting here 0:08:30.000 --> 0:08:34.280 in New York and looking at headlines about tariffs, a 0:08:34.360 --> 0:08:38.800 reasonable person might think that it was all over for trade. 0:08:39.720 --> 0:08:44.240 There is the trendy narrative about deglobalization. What did you 0:08:44.320 --> 0:08:50.080 discover when you drilled down about the dynamic of world 0:08:50.080 --> 0:08:54.760 trade patterns? So it's certainly true that the top line 0:08:54.880 --> 0:08:58.200 or the aggregate global trade as a share of GDP, 0:08:58.480 --> 0:09:02.680 you know, just that one number has indeed declined ever 0:09:02.760 --> 0:09:06.280 since two thousand and eight. But as you say, right, 0:09:06.320 --> 0:09:09.160 if we drill down, what we do find is that, 0:09:10.040 --> 0:09:13.120 first of all, it's really a goods trade that has 0:09:13.160 --> 0:09:16.240 taken most of the hit UH and and most of that, 0:09:16.320 --> 0:09:18.600 if not all of it, is really the value of 0:09:18.720 --> 0:09:24.800 commodities within goods trade, so manufactured goods, particularly labor intensive ones, 0:09:25.240 --> 0:09:28.040 you know, exports or trade, and these is still growing. 0:09:28.640 --> 0:09:31.520 Services trade is still growing as a share of GDP. 0:09:32.840 --> 0:09:36.240 The second important aspect is that the corridors of trade 0:09:36.240 --> 0:09:39.680 are really shifting, and this is quite a profound shift. 0:09:39.880 --> 0:09:43.960 So if we look at what we call broadly South 0:09:44.040 --> 0:09:48.880 South trade, which is trade amongst between emerging economies as 0:09:48.920 --> 0:09:53.320 opposed to emerging versus rich economies. So South South trade 0:09:53.360 --> 0:09:57.120 has actually grown as a share of you know, global 0:09:57.160 --> 0:10:00.839 trade and goods from something like eight percent to above 0:10:02.120 --> 0:10:05.320 over the last fifteen years or so, and that's actually 0:10:05.400 --> 0:10:08.400 quite dramatic. It's grown at you know, two to two 0:10:08.440 --> 0:10:11.520 to three times the volume of all the other corridors 0:10:11.559 --> 0:10:45.160 of trade that you can imagine what role does China 0:10:45.480 --> 0:10:49.520 playing all this is China now important stuff that it 0:10:49.760 --> 0:10:53.280 used to make. There are many interesting ways actually in 0:10:53.320 --> 0:10:56.920 which China is reshaping not just it's trade or it's 0:10:56.920 --> 0:10:59.800 trade with the US, but you know, some of these 0:11:00.000 --> 0:11:04.920 obal trade corridors and opportunities. One one trend that we 0:11:05.000 --> 0:11:08.240 see is that China is focusing more and more on 0:11:08.960 --> 0:11:12.960 manufacturing and export of more knowledge intensive or R and 0:11:13.040 --> 0:11:18.120 D intensive goods, particularly in the high tech electronics computers, 0:11:18.160 --> 0:11:21.719 those kinds of spaces, and in a way receding or 0:11:21.840 --> 0:11:27.160 seeding space in the lower value added types of manufacturing 0:11:27.320 --> 0:11:31.320 like textiles and leather and so on. And some of 0:11:31.480 --> 0:11:35.160 that export volume is actually moving moving to lower labor 0:11:35.200 --> 0:11:39.360 cost countries like Vietnam and Bangladesh. So that's one shift. 0:11:40.360 --> 0:11:43.320 The other important shift is that we think that China 0:11:43.440 --> 0:11:47.000 is an engine of global consumption is also growing very rapidly. 0:11:47.640 --> 0:11:51.439 Emerging markets overall will drive something like sixt of global 0:11:51.480 --> 0:11:57.040 consumption out to thirty so they are collectively important as 0:11:57.120 --> 0:12:00.960 drivers of global consumption. But China's role then that is 0:12:00.960 --> 0:12:05.800 particularly large and important, and there will be parts of 0:12:05.880 --> 0:12:09.280 that consumption that are actually going to be sourced from 0:12:09.559 --> 0:12:14.200 other lower labor cost markets as well, because domestic consumption 0:12:14.200 --> 0:12:17.840 of manufactured goods in China will pretty much continuously increase 0:12:17.880 --> 0:12:24.160 for the next twenty years. People often talk about favorable 0:12:24.320 --> 0:12:29.880 demographics in emerging markets. By that they usually mean young 0:12:29.960 --> 0:12:34.960 populations or populations that are younger than in the developed world. 0:12:36.000 --> 0:12:38.560 Can you drill down a bit for us, are some 0:12:38.640 --> 0:12:43.120 of these societies starting to age and does that matter? 0:12:44.040 --> 0:12:48.920 I think the demographics of emerging markets very quite a bit. 0:12:49.080 --> 0:12:51.760 Going back to your opening question about you know, how 0:12:51.760 --> 0:12:54.320 can you speak about them in the same breath, and 0:12:54.360 --> 0:12:57.880 that's equally true of the aging profile. So you do 0:12:58.000 --> 0:13:02.120 have in our universe the countries in the northern and 0:13:02.120 --> 0:13:07.000 eastern part of Asia the Central Asian countries, these definitely, 0:13:07.280 --> 0:13:10.360 uh you know, are going to see and are fairly 0:13:10.440 --> 0:13:14.240 rapidly going to see aging, whereas you have South Asia 0:13:14.280 --> 0:13:17.000 and then you have Africa where this is not going 0:13:17.040 --> 0:13:20.880 to be the case. Right, But as you step back 0:13:20.920 --> 0:13:24.319 and think about the drivers of growth, we did actually 0:13:24.360 --> 0:13:27.920 find that you know, growth in labor supply was was 0:13:28.080 --> 0:13:33.000 was a very very small part of the total growth 0:13:33.040 --> 0:13:35.960 that that took place in the out performance. So growth 0:13:36.000 --> 0:13:40.680 in productivity per worker is actually much more important. And therefore, 0:13:40.760 --> 0:13:45.600 even as economies age, there are very important drivers of 0:13:45.640 --> 0:13:51.079 productivity that still represent opportunities for unlock. In other words, 0:13:51.120 --> 0:13:55.160 you have economies that are not completely urbanized, and we 0:13:55.240 --> 0:13:58.600 know that urbanization actually lifts productivity by two to three 0:13:58.600 --> 0:14:02.240 times compared to you know, living in rural areas. You 0:14:02.320 --> 0:14:06.800 have economies where you know, financial access and financial inclusion 0:14:06.920 --> 0:14:09.520 is not complete, and this is true even in regions 0:14:09.559 --> 0:14:12.680 like Latin America, and we know that encouraging savings and 0:14:12.760 --> 0:14:17.800 investment actually does drive up productivity. Many emerging markets have 0:14:18.559 --> 0:14:24.840 big conglomerates that are either state owned or privatized to 0:14:25.040 --> 0:14:30.320 government friendly groups. Is the way that these corporations have 0:14:31.240 --> 0:14:35.200 a benefit for emerging markets or is it a hassle? 0:14:36.880 --> 0:14:40.840 We think that the outperformer economy is actually many of 0:14:40.880 --> 0:14:43.240 them for for whom you know, we have the data 0:14:43.280 --> 0:14:46.120 and can study this feature. But we do find that 0:14:46.200 --> 0:14:49.720 one really striking feature of these economies is the role 0:14:49.840 --> 0:14:54.960 that companies of of a significant size have played in 0:14:55.120 --> 0:14:59.240 driving their growth. Now, are these state owned or are 0:14:59.280 --> 0:15:04.880 they private is but with substantial state or quasi state interests. 0:15:05.520 --> 0:15:09.840 Our data set essentially covered companies that are publicly listed, 0:15:10.240 --> 0:15:13.720 so whether they have a majority you know, state shareholding 0:15:13.840 --> 0:15:16.840 or or a private shareholding, as long as they're publicly 0:15:16.880 --> 0:15:21.400 listed and in some ways unswerable or their data as transparent, 0:15:21.560 --> 0:15:24.800 that's the universe we looked at. But looking at such companies, 0:15:24.840 --> 0:15:29.200 we find that the outperformers actually had twice the number 0:15:29.440 --> 0:15:35.160 of large companies as other emerging economies did. That these 0:15:35.280 --> 0:15:39.520 had actually grown much faster. So they had grown from 0:15:40.120 --> 0:15:42.920 revenue to GDP of something like you know, in the 0:15:42.960 --> 0:15:48.400 mid twenty percent region to the mid sixty percent region, 0:15:48.960 --> 0:15:52.040 which is extremely rapid growth just in terms of sheer, 0:15:52.040 --> 0:15:55.960 scale and scope, and there is there is reason to 0:15:56.040 --> 0:16:01.360 believe that these companies are competitive in the US, we 0:16:01.440 --> 0:16:06.000 wrestle with the role that automation and robots will play 0:16:06.120 --> 0:16:12.360 as technology advances and as our workforce ages. When does 0:16:12.400 --> 0:16:16.760 this become a problem for emerging markets and are they 0:16:16.800 --> 0:16:21.600 equipped to deal with it? Automation and technology are fundamentally 0:16:21.720 --> 0:16:26.760 very powerful opportunities to drive productivity in emerging economies, and 0:16:26.800 --> 0:16:31.200 then because they do change the nature of work, they 0:16:31.280 --> 0:16:35.320 also result in a new set of work opportunities or 0:16:35.360 --> 0:16:42.040 a new type of job. Unemployment impact right now. Now, 0:16:42.080 --> 0:16:45.800 how exactly this plays out depends to some extent on 0:16:45.880 --> 0:16:49.920 the economic cost and benefit of deploying technology. So if 0:16:49.920 --> 0:16:52.800 you think about a labor cost as a proxy for that, 0:16:53.640 --> 0:16:56.520 we find that there are i think a large number 0:16:56.600 --> 0:17:02.440 of low labor cost emerging trees, typically those where per 0:17:02.480 --> 0:17:05.240 capita GDP is less than five thousand dollars or so, 0:17:06.040 --> 0:17:09.480 where even over the next you know, ten to fifteen years, 0:17:09.520 --> 0:17:14.080 these countries would in our opinion, have the potential to 0:17:14.280 --> 0:17:20.240 raise both employment as well as GDP from manufacturing activities. 0:17:20.440 --> 0:17:23.160 So the deployment of technology would allow them to raise 0:17:23.920 --> 0:17:28.359 value add and productivity in manufacturing but also employment. Not 0:17:28.520 --> 0:17:31.720 all countries fall into this bucket, So there are you know, 0:17:31.760 --> 0:17:35.040 the higher, higher income emerging economies where this would not 0:17:35.080 --> 0:17:38.439 be the case and where the questions around you know, 0:17:38.440 --> 0:17:43.000 how can you actually create productive jobs in services? How 0:17:43.000 --> 0:17:46.840 can you actually reskill and redeploy people from what they're 0:17:46.840 --> 0:17:50.440 doing to the new and emerging areas within services sectors 0:17:50.640 --> 0:17:54.639 is going to be actually one of the central challenges 0:17:54.920 --> 0:17:57.800 as well as opportunities for emerging economies as as you 0:17:57.840 --> 0:18:02.400 think about inclusive growth. Aw thank you for walking us 0:18:02.480 --> 0:18:07.199 through the world of emerging markets. It's a pleasure. Thank you. 0:18:11.400 --> 0:18:14.600 Benchmark will be back next week. Until then, you can 0:18:14.640 --> 0:18:18.280 find us on the Bloomberg terminal, Bloomberg dot com, our 0:18:18.359 --> 0:18:23.440 Bloomberg app, as well as podcast destinations such as Apple Podcasts, 0:18:23.840 --> 0:18:27.639 Spotify or wherever you listen. We'd love it if you 0:18:27.760 --> 0:18:30.760 took the time to rate and review the show so 0:18:30.920 --> 0:18:34.400 more listeners can find us, and you can follow me 0:18:34.560 --> 0:18:39.880 on Twitter at moss Underscore. Echo. Benchmark is produced by 0:18:39.920 --> 0:18:44.720 Turf of Foreheads, the head of Bloomberg Podcasts. This Francesca leaving, 0:18:45.240 --> 0:19:00.040 Thanks for listening. To see you next time on