1 00:00:04,280 --> 00:00:06,960 Speaker 1: Hello, and welcome to Stephanomics, the podcast that brings the 2 00:00:06,960 --> 00:00:15,680 Speaker 1: global economy to you. The Indian economy has grown by 3 00:00:15,720 --> 00:00:18,640 Speaker 1: at least six or seven percent in nearly every one 4 00:00:18,680 --> 00:00:21,880 Speaker 1: of the past twenty years. That's almost double the growth 5 00:00:21,960 --> 00:00:24,800 Speaker 1: rate it achieved in its first fifty years as an 6 00:00:24,800 --> 00:00:29,479 Speaker 1: independent state. But somehow that success isn't translating into jobs. 7 00:00:29,960 --> 00:00:33,400 Speaker 1: In fact, less than half of the working population is 8 00:00:33,440 --> 00:00:37,040 Speaker 1: working or even actively looking for work, and the vast 9 00:00:37,080 --> 00:00:40,400 Speaker 1: majority of Indian women are out of the workforce altogether. 10 00:00:41,040 --> 00:00:43,879 Speaker 1: So what's going wrong and how important will it be 11 00:00:43,960 --> 00:00:46,760 Speaker 1: for the newly elected Prime Minister nor Indo Moody to 12 00:00:46,880 --> 00:00:49,440 Speaker 1: fix it? While a few minutes I'll talk about it 13 00:00:49,560 --> 00:00:53,239 Speaker 1: with Bloomberg columnist and writer Mihir Shama. I'll also have 14 00:00:53,360 --> 00:00:56,320 Speaker 1: some brand new research on exactly how the US China 15 00:00:56,400 --> 00:01:00,520 Speaker 1: trade wars and tariffs are destroying economic activity the US, 16 00:01:00,720 --> 00:01:04,320 Speaker 1: China and other countries. But first, here's my colleague Aniban 17 00:01:04,440 --> 00:01:07,360 Speaker 1: Nag who took a closer look at India's job shortage 18 00:01:07,480 --> 00:01:23,000 Speaker 1: with fellow reporter Fristie p Anywell. That is the busy Promhabib, 19 00:01:23,080 --> 00:01:26,560 Speaker 1: the station here in central Mumbai with thousands of commuters 20 00:01:26,720 --> 00:01:36,920 Speaker 1: mill in and out during the morning rush hour. The 21 00:01:36,959 --> 00:01:40,560 Speaker 1: Indian railways are famous as one of the biggest employers 22 00:01:40,560 --> 00:01:44,200 Speaker 1: in the world, and this particular station is being manned 23 00:01:44,200 --> 00:01:48,040 Speaker 1: by a station master, booking clerks and a few sweepers. 24 00:01:49,480 --> 00:01:53,440 Speaker 1: These jobs don't pay much, but a staggering twenty eight 25 00:01:53,520 --> 00:01:56,640 Speaker 1: million implied to do one of them recently, and the 26 00:01:56,720 --> 00:02:02,520 Speaker 1: department that runs the railways announced agnes. One of those 27 00:02:02,800 --> 00:02:05,559 Speaker 1: who try to get a railway job was sish Kumar. 28 00:02:08,400 --> 00:02:10,600 Speaker 1: I wanted to stick to a job with computers, but 29 00:02:10,680 --> 00:02:13,800 Speaker 1: it's so difficult to land a job. If someone knows you, 30 00:02:13,919 --> 00:02:17,160 Speaker 1: then you get a job. Otherwise it's next to impossible. 31 00:02:19,160 --> 00:02:24,440 Speaker 1: About We met Sorresh there his one room, rented a 32 00:02:24,520 --> 00:02:27,960 Speaker 1: house that is a stone's throw away from an open 33 00:02:28,040 --> 00:02:31,240 Speaker 1: drain and part of one of the most densely populated 34 00:02:31,280 --> 00:02:35,880 Speaker 1: colonies of Delhi. He's medium built and dressed up for 35 00:02:35,919 --> 00:02:40,800 Speaker 1: work in a formal cotton shirt and trousers. It's morning, 36 00:02:41,280 --> 00:02:44,120 Speaker 1: but he's already starting to sweat in the Indian summer, 37 00:02:44,560 --> 00:02:47,359 Speaker 1: where temperatures can soar past hundred and ten. They raised 38 00:02:47,400 --> 00:02:51,200 Speaker 1: farre and high. He's thirty years old and holds a 39 00:02:51,280 --> 00:02:55,720 Speaker 1: diploma and computing from a private institute, but he's working 40 00:02:55,760 --> 00:02:59,320 Speaker 1: as someone's driver, his wife as a maid. I was 41 00:02:59,360 --> 00:03:02,519 Speaker 1: hoping for older than that when he moved here from 42 00:03:02,560 --> 00:03:06,760 Speaker 1: India's central region of mad Depradation. But he recognizes he's 43 00:03:06,800 --> 00:03:10,320 Speaker 1: one of the lucky ones back in the village. There's 44 00:03:10,400 --> 00:03:13,120 Speaker 1: so much poverty. We can't even open our own business 45 00:03:13,480 --> 00:03:16,080 Speaker 1: and there are no banks to offer support with loans. 46 00:03:16,639 --> 00:03:18,919 Speaker 1: In Delhi, at least you can get a job. I 47 00:03:19,000 --> 00:03:21,160 Speaker 1: am driving as I have a home to run and 48 00:03:21,280 --> 00:03:31,079 Speaker 1: send kids to school. Sy Ha's a job, but he's 49 00:03:31,160 --> 00:03:35,600 Speaker 1: under employed. India's economy is not getting the best out 50 00:03:35,640 --> 00:03:40,280 Speaker 1: of him. Twelve million Indians entered the labor market each year, 51 00:03:40,920 --> 00:03:44,200 Speaker 1: and an increasing number of them are under employed, lights 52 00:03:44,360 --> 00:03:52,560 Speaker 1: race or not in work at all. It was like 53 00:03:52,760 --> 00:03:55,800 Speaker 1: any week of December that we were told that they 54 00:03:55,800 --> 00:03:58,880 Speaker 1: will be letting go of the staff and then from 55 00:03:58,920 --> 00:04:02,080 Speaker 1: there try and if they can survive this stress, which 56 00:04:02,160 --> 00:04:05,600 Speaker 1: also did not happen because in April almost everybody was 57 00:04:05,680 --> 00:04:10,360 Speaker 1: asked to go. We found a woman we call Alia 58 00:04:10,760 --> 00:04:13,320 Speaker 1: because she did not want us to use her real name. 59 00:04:14,720 --> 00:04:16,960 Speaker 1: We met up in Bloomberg's office in New Delhi, where 60 00:04:17,000 --> 00:04:21,599 Speaker 1: she lives. Aliyah, who's in her mid thirties, lost her 61 00:04:21,680 --> 00:04:25,560 Speaker 1: job as a marketing and communications manager after her company's 62 00:04:25,600 --> 00:04:29,400 Speaker 1: sales failed to gain traction, just as the country was 63 00:04:29,520 --> 00:04:32,160 Speaker 1: put through a huge challenge of changing much of the 64 00:04:32,200 --> 00:04:35,760 Speaker 1: currency in circulation. Did they tell you what was the 65 00:04:35,839 --> 00:04:39,200 Speaker 1: reason for that? No, they just told that they were 66 00:04:39,279 --> 00:04:42,680 Speaker 1: not able to kind of sustain the operations that they 67 00:04:42,720 --> 00:04:45,640 Speaker 1: were having. Her mother isn't aware she has lost her job. 68 00:04:46,760 --> 00:04:50,560 Speaker 1: Her father knows the truth and can sometimes get despondent 69 00:04:50,880 --> 00:04:55,720 Speaker 1: about her job prospects. Aliyah says she has been able 70 00:04:55,760 --> 00:04:58,520 Speaker 1: to get some work here and there. She has even 71 00:04:58,600 --> 00:05:01,680 Speaker 1: managed to repay a Carlo, but it has been tough. 72 00:05:03,560 --> 00:05:06,840 Speaker 1: I take up freelance projects from time to time, and 73 00:05:07,000 --> 00:05:10,360 Speaker 1: I try to and obviously try to find, you know, 74 00:05:10,520 --> 00:05:13,880 Speaker 1: anything that I can apply to. So what I mostly 75 00:05:14,160 --> 00:05:16,760 Speaker 1: get as a response is that either there are too 76 00:05:16,800 --> 00:05:19,600 Speaker 1: many aspirants buying for a singular job and so the 77 00:05:19,640 --> 00:05:23,640 Speaker 1: competition is obviously increased. A part of it was also 78 00:05:23,960 --> 00:05:26,040 Speaker 1: given to the fact that you know, I'm looking for 79 00:05:26,800 --> 00:05:29,240 Speaker 1: a job role which is intermate management kind of position 80 00:05:29,279 --> 00:05:34,200 Speaker 1: and order fresh level, and also the fact that you 81 00:05:34,279 --> 00:05:38,720 Speaker 1: know the plans keep changing. A lot of positions that 82 00:05:38,839 --> 00:05:42,520 Speaker 1: are that are actually they think are available go on 83 00:05:42,640 --> 00:05:46,360 Speaker 1: hold for no reason. There's a lot of uncertainty in 84 00:05:46,560 --> 00:05:49,799 Speaker 1: terms of organizations in terms of what they they're planning 85 00:05:49,839 --> 00:05:52,440 Speaker 1: for the next six months to a New York time earlier. 86 00:05:52,680 --> 00:05:55,840 Speaker 1: Part of the official jobless numbers, and that is probably 87 00:05:55,880 --> 00:05:59,840 Speaker 1: the tip of the iceberg. The bigger problem is that 88 00:06:00,400 --> 00:06:04,760 Speaker 1: half the working age population and of women are not 89 00:06:04,960 --> 00:06:08,760 Speaker 1: even included in that official jobless total, but they're not 90 00:06:09,240 --> 00:06:13,960 Speaker 1: looking for work at all. India is not the only 91 00:06:14,040 --> 00:06:18,960 Speaker 1: developing country struggling to bring women into the workforce. What 92 00:06:19,200 --> 00:06:22,200 Speaker 1: is troubling is that the situation has been getting worse 93 00:06:23,120 --> 00:06:26,360 Speaker 1: even as the overall economy has been doing quite well. 94 00:06:27,760 --> 00:06:31,720 Speaker 1: According to the World Bank, nearly twenty million women, a 95 00:06:31,839 --> 00:06:35,520 Speaker 1: number roughly equivalent to the population of Sri Lanka, dropped 96 00:06:35,520 --> 00:06:38,640 Speaker 1: out of the workforce between two thousand and five and 97 00:06:38,760 --> 00:06:43,480 Speaker 1: two thousand and twelve. Economists tell us that this is 98 00:06:43,480 --> 00:06:47,800 Speaker 1: an enormous missed opportunity, but don't take their vote for it. 99 00:06:48,640 --> 00:06:52,080 Speaker 1: Ask Christine Lagard, the head of the International Monetary Fund, 100 00:06:53,320 --> 00:06:57,000 Speaker 1: you can increase US t DP by five because you 101 00:06:57,080 --> 00:07:01,720 Speaker 1: can increase Indian GDP by twenty seven and decent. If 102 00:07:01,760 --> 00:07:04,680 Speaker 1: you look at diversification, we have now documented evidence of 103 00:07:04,760 --> 00:07:08,200 Speaker 1: the fact that when women participate in the economy and 104 00:07:08,320 --> 00:07:10,640 Speaker 1: in the labor market as much as men do, you 105 00:07:10,720 --> 00:07:16,400 Speaker 1: have a more diversified economy. And by bringing women to 106 00:07:16,560 --> 00:07:19,280 Speaker 1: the to the labor markets, giving them access to finance, 107 00:07:19,680 --> 00:07:23,840 Speaker 1: you reduce the inequality. What would that take in India? 108 00:07:24,280 --> 00:07:28,560 Speaker 1: We asked some Toshirotra, a professor at New Dearle's Jawaharlal 109 00:07:28,640 --> 00:07:33,200 Speaker 1: Nehru University. He's an export and employment and labor issues 110 00:07:33,520 --> 00:07:37,200 Speaker 1: for girls. If you want to make sure that they 111 00:07:37,280 --> 00:07:45,280 Speaker 1: get jobs, then we have to ensure that childcare. Affordable 112 00:07:45,400 --> 00:07:51,240 Speaker 1: childcare is much more easily available. UM, public transport is 113 00:07:52,240 --> 00:07:56,720 Speaker 1: much safer than it has been in the past. UM. 114 00:07:57,560 --> 00:08:02,080 Speaker 1: And above all, of course, job growth, non agricultural job 115 00:08:02,160 --> 00:08:08,000 Speaker 1: growth has to happen in construction, in manufacturing and in services. 116 00:08:08,280 --> 00:08:11,080 Speaker 1: You wouldn't know there's a problem from the latest election results. 117 00:08:11,960 --> 00:08:14,360 Speaker 1: Prime Minister in the Rain the Remote won the country's 118 00:08:14,440 --> 00:08:18,200 Speaker 1: massive vote last month with an even larger majority than before, 119 00:08:19,280 --> 00:08:22,520 Speaker 1: but he does recognize the issue. One of the first 120 00:08:22,560 --> 00:08:25,760 Speaker 1: decisions after taking office for a second five year term 121 00:08:26,320 --> 00:08:29,720 Speaker 1: was to form a committee of senior ministers to try 122 00:08:29,840 --> 00:08:34,120 Speaker 1: and address rising on employment. Oh yeah, says it's hard 123 00:08:34,200 --> 00:08:36,520 Speaker 1: time they deal with the issue because it's a lot 124 00:08:36,600 --> 00:08:42,400 Speaker 1: bigger than the numbers indicate. Comar, the driver, blames India's 125 00:08:42,480 --> 00:08:46,760 Speaker 1: education system for the lack of opportunities. Way was that 126 00:08:46,880 --> 00:08:49,160 Speaker 1: that can't be there? Who made the English community? My 127 00:08:49,280 --> 00:08:52,440 Speaker 1: English is weak in the villages. They don't teach much English. 128 00:08:52,720 --> 00:08:55,400 Speaker 1: I started studying English only in the fifth grade and 129 00:08:55,520 --> 00:08:58,079 Speaker 1: not the first. If I have to blame anyone, it 130 00:08:58,200 --> 00:09:01,480 Speaker 1: is perhaps myself. So I think I should have more 131 00:09:01,559 --> 00:09:05,319 Speaker 1: complications of degrees. It can really need to lay out 132 00:09:06,320 --> 00:09:09,800 Speaker 1: the lack of suitable opportunities. So someone like Coomar risk 133 00:09:09,800 --> 00:09:15,199 Speaker 1: astonishing the country's image as a major investment destination. Not 134 00:09:15,400 --> 00:09:19,880 Speaker 1: only that there's a chance of social unrest. Above all, 135 00:09:20,360 --> 00:09:23,240 Speaker 1: it poses a challenge to policy makers who are keen 136 00:09:23,320 --> 00:09:27,760 Speaker 1: to read the demographic dividend of a young population, which 137 00:09:27,840 --> 00:09:31,160 Speaker 1: means it can be a major drive of economic growth. 138 00:09:32,720 --> 00:09:36,960 Speaker 1: The time is ticking, though, by the share of India's 139 00:09:37,000 --> 00:09:42,120 Speaker 1: population to that of working age will start declining. India 140 00:09:42,400 --> 00:09:44,720 Speaker 1: will have to act fast if it has to harness 141 00:09:44,760 --> 00:09:49,199 Speaker 1: that demographic dividend. By providing jobs to millions sooner rather 142 00:09:49,280 --> 00:09:53,559 Speaker 1: than later. Kumar thinks it's already too late for him, 143 00:09:54,240 --> 00:09:57,080 Speaker 1: but he's still holding out hope for the next generation. 144 00:09:58,320 --> 00:10:02,040 Speaker 1: A year, I have given up hopes of getting a 145 00:10:02,120 --> 00:10:05,000 Speaker 1: better job. I will get along with whenever it takes. 146 00:10:05,480 --> 00:10:20,920 Speaker 1: The kids should have better prospects. So I'm very happy 147 00:10:20,960 --> 00:10:24,440 Speaker 1: now that I can speak to one of Bloomberg's key 148 00:10:24,920 --> 00:10:28,959 Speaker 1: India columnists, Mihir Shama, about what this means for in 149 00:10:29,000 --> 00:10:32,839 Speaker 1: his economy and what Prime Mr Modi might be able 150 00:10:32,880 --> 00:10:35,000 Speaker 1: to do about it going forward, having just been re 151 00:10:35,160 --> 00:10:39,320 Speaker 1: elected last month. Here, I guess one question people might 152 00:10:39,360 --> 00:10:43,079 Speaker 1: be asking. I started the program mentioning that India was 153 00:10:43,080 --> 00:10:46,240 Speaker 1: an economy that had grown six or seven percent a year, 154 00:10:46,559 --> 00:10:48,920 Speaker 1: pretty much every year for the last twenty years. How 155 00:10:48,960 --> 00:10:51,679 Speaker 1: has it done so well while not finding jobs for 156 00:10:52,360 --> 00:10:56,520 Speaker 1: maybe half of its working age population. I think that 157 00:10:57,200 --> 00:11:00,720 Speaker 1: the real joblessness is a relatively recent phenol. The real 158 00:11:00,800 --> 00:11:04,719 Speaker 1: jobless growth is a relatively recent phenomenon. Um Up to 159 00:11:04,800 --> 00:11:09,559 Speaker 1: around twenty eleven, I think jobs were getting created. A 160 00:11:09,640 --> 00:11:12,240 Speaker 1: lot of those were in, for example, the construction sector, 161 00:11:12,280 --> 00:11:15,839 Speaker 1: which has traditionally managed to soak up large numbers of 162 00:11:15,920 --> 00:11:21,079 Speaker 1: relatively underskilled people, particularly from rural areas, in a rapidly 163 00:11:21,160 --> 00:11:25,679 Speaker 1: expanding urban economy. Around twenty eleven or twenty twelve, the 164 00:11:25,800 --> 00:11:29,000 Speaker 1: economy begins to slow. You know, you have the crisis, 165 00:11:29,080 --> 00:11:31,640 Speaker 1: then you have the post crisis stimulus, and then when 166 00:11:31,679 --> 00:11:35,160 Speaker 1: the stimulus over reaches in around twenty twelve, the economy slows. 167 00:11:35,200 --> 00:11:40,479 Speaker 1: Investment slows for some reason. Um that slowing is reflected 168 00:11:40,600 --> 00:11:44,559 Speaker 1: in the job growth numbers are both official and unofficial, 169 00:11:45,280 --> 00:11:47,920 Speaker 1: but is not showing up as much as one would 170 00:11:47,960 --> 00:11:51,880 Speaker 1: expect in the new GDP statistics, which has led many people, 171 00:11:51,960 --> 00:11:55,880 Speaker 1: as as it happens, to start questioning India's growth figgers themselves. 172 00:11:56,640 --> 00:12:02,199 Speaker 1: But the truth is that from after liberalized fastion, the 173 00:12:02,360 --> 00:12:08,600 Speaker 1: first ten, fifteen, even twenty years were pretty good for jobs, 174 00:12:09,480 --> 00:12:12,000 Speaker 1: not as great as they could have been, but not bad. 175 00:12:12,480 --> 00:12:15,160 Speaker 1: It's really in the past father, nor though year, that 176 00:12:15,240 --> 00:12:18,240 Speaker 1: we've begun to see something of a crisis. And if 177 00:12:18,280 --> 00:12:20,559 Speaker 1: you look at the structure of growth, I mean, is 178 00:12:20,600 --> 00:12:22,720 Speaker 1: it is it to do with the composition of growth 179 00:12:23,080 --> 00:12:26,760 Speaker 1: that you're not getting the jobs. Like our our economist 180 00:12:27,080 --> 00:12:29,880 Speaker 1: at Bloomberger, Abishek Gupta, has looked at how in a 181 00:12:30,000 --> 00:12:32,760 Speaker 1: sense the whole is not necessarily in the manufacturing silence 182 00:12:32,800 --> 00:12:35,640 Speaker 1: in service sector, and the inability to inability to unleash 183 00:12:35,720 --> 00:12:37,640 Speaker 1: the service sector is that a big part of it. 184 00:12:39,800 --> 00:12:43,760 Speaker 1: No country in history has been able to um incorporate 185 00:12:44,040 --> 00:12:49,760 Speaker 1: unskilled people from the rural economy into a growing middle 186 00:12:49,840 --> 00:12:55,360 Speaker 1: class with secure jobs without building a manufacturing sector. It 187 00:12:55,520 --> 00:12:59,080 Speaker 1: is possible, surely, perhaps to do it without but unless 188 00:12:59,080 --> 00:13:02,320 Speaker 1: you've got oil or something, you can't. There's no there's 189 00:13:02,360 --> 00:13:05,880 Speaker 1: no roadmap. It's never been done before. India has been 190 00:13:06,000 --> 00:13:11,079 Speaker 1: d industrializing since the late nineties, which means that the 191 00:13:11,200 --> 00:13:14,800 Speaker 1: contribution of industry to GDP peaked in around nine ninety 192 00:13:14,840 --> 00:13:17,520 Speaker 1: seven and since then it has been going down. That's 193 00:13:17,559 --> 00:13:22,360 Speaker 1: not okay because what that gets replaced with is, of 194 00:13:22,480 --> 00:13:26,240 Speaker 1: course an increase in the proportion of the service sector 195 00:13:26,520 --> 00:13:29,079 Speaker 1: in g d P. And the service sector is not 196 00:13:29,640 --> 00:13:34,400 Speaker 1: you know, we're not talking high level it stuff here, 197 00:13:34,559 --> 00:13:36,800 Speaker 1: all right. That maybe the image of India, But what 198 00:13:36,920 --> 00:13:41,520 Speaker 1: the service sector actually is is very very small enterprises 199 00:13:41,640 --> 00:13:45,520 Speaker 1: one person, two persons, three people working together. In the 200 00:13:45,600 --> 00:13:49,640 Speaker 1: Prime Minister's words, even a guy frying up dumplings is 201 00:13:49,679 --> 00:13:52,960 Speaker 1: also a job, right, But those aren't the kind of jobs. 202 00:13:53,040 --> 00:13:55,520 Speaker 1: I think that people think about when they want them, 203 00:13:55,800 --> 00:13:57,520 Speaker 1: and those aren't the kind of jobs that create a 204 00:13:57,520 --> 00:14:00,760 Speaker 1: sustainable middle class. There is really no on for even 205 00:14:00,960 --> 00:14:06,280 Speaker 1: right now after what could repleeve math manufacturing export oriented 206 00:14:06,320 --> 00:14:10,240 Speaker 1: math manufacturing as the creator of job So I know 207 00:14:10,360 --> 00:14:13,200 Speaker 1: you like giving primers demodi advice which he doesn't follow. 208 00:14:14,440 --> 00:14:19,480 Speaker 1: We shouldn't necessarily stop now if you're just been reelected 209 00:14:20,240 --> 00:14:24,880 Speaker 1: and have some pressure on you, maybe surprisingly not as 210 00:14:24,960 --> 00:14:26,680 Speaker 1: much pressure as you might think. I think if less 211 00:14:26,680 --> 00:14:28,720 Speaker 1: than half of the working age population in the UK 212 00:14:28,960 --> 00:14:30,840 Speaker 1: or the US we're in work, there would be that 213 00:14:30,920 --> 00:14:33,360 Speaker 1: would be the only issue on the horizon. I see 214 00:14:33,400 --> 00:14:35,440 Speaker 1: that that's not really the case in India. But if 215 00:14:35,480 --> 00:14:40,200 Speaker 1: you're under pressure to deliver m after this election victory, 216 00:14:41,280 --> 00:14:44,760 Speaker 1: what leavers can he pull? I mean, what would be 217 00:14:44,800 --> 00:14:47,480 Speaker 1: the key reformer is that you would think of to 218 00:14:47,680 --> 00:14:51,800 Speaker 1: try and change how much jobs are being created. I 219 00:14:51,880 --> 00:14:53,720 Speaker 1: think there are three things that you need to do 220 00:14:53,880 --> 00:14:57,200 Speaker 1: almost immediately because time is running out for all of them. 221 00:14:57,880 --> 00:15:02,760 Speaker 1: The first is to obstantively change what are called factor markets, 222 00:15:02,800 --> 00:15:07,440 Speaker 1: so the markets for land and labor in particular. UM, 223 00:15:07,560 --> 00:15:10,280 Speaker 1: it's very difficult to fire people in India which is 224 00:15:10,360 --> 00:15:14,320 Speaker 1: why very few people hire them. We have incredibly small 225 00:15:14,960 --> 00:15:18,840 Speaker 1: textile production facilities, like our textile factories are you know, 226 00:15:18,960 --> 00:15:21,840 Speaker 1: maybe an average of fifteen or sixteen people in India 227 00:15:22,000 --> 00:15:25,240 Speaker 1: as opposed to over two to three in just in 228 00:15:25,280 --> 00:15:28,840 Speaker 1: Bangladesh next door. And so we're uncompetitive when it comes 229 00:15:28,920 --> 00:15:33,280 Speaker 1: to producing textiles, which is a labor intensive sector. Um 230 00:15:33,960 --> 00:15:37,480 Speaker 1: So you need to change the laws that constrain the 231 00:15:37,600 --> 00:15:42,760 Speaker 1: sale of land, that constrain hiring and firing workers. That's 232 00:15:42,840 --> 00:15:45,680 Speaker 1: point one. Point two is that you have to ensure 233 00:15:45,760 --> 00:15:50,520 Speaker 1: that you get embedded into global supply chains. Currently, India is, 234 00:15:50,760 --> 00:15:53,720 Speaker 1: like many other countries around the world, moving in a 235 00:15:53,840 --> 00:15:57,360 Speaker 1: somewhat protectionist direction. We're putting up tariffs on you know, 236 00:15:57,480 --> 00:16:00,520 Speaker 1: things like mobile phones and the idea areas to try 237 00:16:00,520 --> 00:16:04,640 Speaker 1: and create a domestic electronics manufacturing sector, but obviously we 238 00:16:04,840 --> 00:16:07,520 Speaker 1: know that's not going to happen because of the way 239 00:16:07,600 --> 00:16:11,320 Speaker 1: that that manufacturing is now organized globally. Um So you 240 00:16:11,400 --> 00:16:15,000 Speaker 1: have to embed yourself in these global supply chains rather 241 00:16:15,080 --> 00:16:18,320 Speaker 1: than you know, extracting yourself from them. And the third 242 00:16:18,440 --> 00:16:20,600 Speaker 1: and I think really the most important at this point 243 00:16:21,040 --> 00:16:25,520 Speaker 1: is that you need to work on basic educational and skills. 244 00:16:26,360 --> 00:16:29,320 Speaker 1: We have some of the worst schools in the world. 245 00:16:29,840 --> 00:16:33,120 Speaker 1: According to many studies, there are kids in class eight 246 00:16:33,360 --> 00:16:35,280 Speaker 1: in the you know, in their eights here of schooling 247 00:16:35,280 --> 00:16:37,800 Speaker 1: in the eighth grade who cannot do maths at a 248 00:16:37,840 --> 00:16:40,800 Speaker 1: second grade level, and that's the majority of So you 249 00:16:40,880 --> 00:16:43,600 Speaker 1: need to intervene both of the primary level and with 250 00:16:43,720 --> 00:16:45,800 Speaker 1: those who have already left school and are and are 251 00:16:45,880 --> 00:16:49,720 Speaker 1: currently underskilled. So those interventions have to be massive and immediate, 252 00:16:49,920 --> 00:16:52,880 Speaker 1: the educational ones. And you did mention we had at 253 00:16:52,920 --> 00:16:56,280 Speaker 1: the end of that segment as well. This question is 254 00:16:56,320 --> 00:16:59,200 Speaker 1: the time pressure. Um. You know, you might think India 255 00:16:59,240 --> 00:17:01,480 Speaker 1: had all the time in the world given the scale 256 00:17:01,520 --> 00:17:03,160 Speaker 1: of its economy and a number of people, but this 257 00:17:03,800 --> 00:17:07,080 Speaker 1: key demographic point that you have a sweet spot as 258 00:17:07,080 --> 00:17:10,399 Speaker 1: an economy where you have a sort of peak a 259 00:17:10,560 --> 00:17:15,119 Speaker 1: number of working age people with fewer children, having fewer children, 260 00:17:15,200 --> 00:17:18,680 Speaker 1: but no longer, not not getting older yet. How important 261 00:17:18,800 --> 00:17:20,960 Speaker 1: is it for India to get this right before it 262 00:17:21,080 --> 00:17:24,560 Speaker 1: starts seeing that demographic change and the aging that we've 263 00:17:24,600 --> 00:17:27,720 Speaker 1: seen in that obviously in other countries. So one of 264 00:17:27,760 --> 00:17:31,359 Speaker 1: the crucial questions in development of can a country get 265 00:17:31,480 --> 00:17:35,280 Speaker 1: rich before it gets old? Right? And the truth is 266 00:17:35,400 --> 00:17:39,240 Speaker 1: that we are a much younger country than a lot 267 00:17:39,320 --> 00:17:41,440 Speaker 1: of others where our average age is still in the 268 00:17:41,480 --> 00:17:47,800 Speaker 1: twenties where within China, Japan, But that obviously won't last forever. 269 00:17:48,680 --> 00:17:52,000 Speaker 1: As birth rates begin to fall going forward, our average 270 00:17:52,040 --> 00:17:55,119 Speaker 1: age will increase, which means that the proportion of people 271 00:17:55,800 --> 00:17:58,680 Speaker 1: in the working age population as opposed to those out 272 00:17:58,720 --> 00:18:01,440 Speaker 1: of it, will begin to Right now, we are seeing 273 00:18:01,640 --> 00:18:04,520 Speaker 1: a lot of growth and a lot of dynamism precisely 274 00:18:04,600 --> 00:18:10,520 Speaker 1: because that working age population is increasing in composition, in size, 275 00:18:10,800 --> 00:18:14,639 Speaker 1: in proportion. That will not be the case going forward. 276 00:18:15,119 --> 00:18:17,560 Speaker 1: And the bad news is it is already the case 277 00:18:17,760 --> 00:18:21,200 Speaker 1: that we are facing demographic demographic pressure in some of 278 00:18:21,240 --> 00:18:24,320 Speaker 1: the more advanced and developed parts of India. States along 279 00:18:24,359 --> 00:18:27,359 Speaker 1: the coast in the south of India, which have higher 280 00:18:27,520 --> 00:18:30,800 Speaker 1: human capital levels, which are more integrated with the global 281 00:18:30,840 --> 00:18:35,240 Speaker 1: economy um which have better skills, those areas are in 282 00:18:35,440 --> 00:18:40,119 Speaker 1: fact already beginning to see this demographic change. They're getting older. 283 00:18:41,000 --> 00:18:43,399 Speaker 1: Where population growth is really coming from, where we have 284 00:18:43,560 --> 00:18:46,960 Speaker 1: our current youth bulge, all these working age population, working 285 00:18:47,000 --> 00:18:49,359 Speaker 1: age people applying for these jobs in the railways and 286 00:18:49,359 --> 00:18:51,879 Speaker 1: so on and so forth. That's in the north, in 287 00:18:52,000 --> 00:18:55,280 Speaker 1: the interior, and that's not that's not a part of 288 00:18:55,320 --> 00:18:58,440 Speaker 1: the country that is properly connected to the global economy. 289 00:18:58,440 --> 00:19:01,320 Speaker 1: It's not connected to markets. These are people who are underskilled. 290 00:19:01,520 --> 00:19:06,040 Speaker 1: So there is this a regional disparity in how things 291 00:19:06,080 --> 00:19:10,119 Speaker 1: are turning out that evolved a problem. Some people listening 292 00:19:10,160 --> 00:19:11,560 Speaker 1: may have the same experience that I have that the 293 00:19:11,720 --> 00:19:16,879 Speaker 1: the Indian business people that one sees at conferences or 294 00:19:17,280 --> 00:19:20,680 Speaker 1: interviewed often on Bloomberg or in anywhere else, you get 295 00:19:20,720 --> 00:19:25,320 Speaker 1: the sense of an incredibly dynamic economy really digitally switched 296 00:19:25,400 --> 00:19:29,479 Speaker 1: on developing things that actually are ahead in many cases 297 00:19:29,600 --> 00:19:34,840 Speaker 1: of advanced economies on the digital front um, and even 298 00:19:34,920 --> 00:19:39,280 Speaker 1: on applying it to some public sector challenges. Is that 299 00:19:39,480 --> 00:19:41,800 Speaker 1: just are we seeing just a tiny fraction, Because if 300 00:19:41,800 --> 00:19:43,600 Speaker 1: you listen to those people, you would think, wow, India 301 00:19:43,680 --> 00:19:45,399 Speaker 1: is going to be able to ride the wave of 302 00:19:45,440 --> 00:19:47,840 Speaker 1: all these technological changes that are happening around the world 303 00:19:47,880 --> 00:19:51,840 Speaker 1: that everyone fears India is going to clean up as 304 00:19:51,880 --> 00:19:54,240 Speaker 1: a result of those changes. Well, I mean there are 305 00:19:54,280 --> 00:19:57,239 Speaker 1: two things to be said there. The first is one 306 00:19:57,280 --> 00:20:00,480 Speaker 1: should never trust what people in Indian business see, only 307 00:20:00,560 --> 00:20:04,840 Speaker 1: what they do and when they start investing in India, 308 00:20:05,640 --> 00:20:08,919 Speaker 1: then I will take their claims that India India has 309 00:20:08,920 --> 00:20:11,480 Speaker 1: a bright future. Seriously, we have a crisis and private 310 00:20:11,520 --> 00:20:15,240 Speaker 1: investment has been shrinking for for years as a proportional GDP, 311 00:20:15,920 --> 00:20:18,639 Speaker 1: and that doesn't appear to have cleared up yet, so 312 00:20:18,960 --> 00:20:21,119 Speaker 1: they don't appear to have confidence in where they're putting 313 00:20:21,119 --> 00:20:25,439 Speaker 1: their money. So I don't believe anything they say about 314 00:20:25,560 --> 00:20:27,080 Speaker 1: you know, when when they make all these sort of 315 00:20:27,160 --> 00:20:29,840 Speaker 1: claims about India's future. The other thing about you know, 316 00:20:30,160 --> 00:20:33,200 Speaker 1: can India righte the you know, automation digital wave of 317 00:20:33,280 --> 00:20:36,240 Speaker 1: the future. Everybody else is worrying because they're losing jobs. 318 00:20:36,680 --> 00:20:38,680 Speaker 1: I don't know. I suppose you can be more optimistic 319 00:20:38,720 --> 00:20:41,159 Speaker 1: about it when you've never had the jobs in the 320 00:20:41,200 --> 00:20:44,600 Speaker 1: first place. If you see the entire world moving towards 321 00:20:44,680 --> 00:20:47,720 Speaker 1: an economy, you know, which is precarious when nobody has 322 00:20:47,720 --> 00:20:49,520 Speaker 1: a real job where you have to work three things, 323 00:20:50,160 --> 00:20:52,440 Speaker 1: and you know you have service sector jobs that don't 324 00:20:52,480 --> 00:20:55,440 Speaker 1: pay enough. Well, we've lived that already. But the truth 325 00:20:55,600 --> 00:20:58,480 Speaker 1: is that we are worth off because we need to 326 00:20:58,560 --> 00:21:01,200 Speaker 1: at least have a phase of those manufacturing jobs in 327 00:21:01,359 --> 00:21:03,639 Speaker 1: order to build the middle cloths that can then complain 328 00:21:04,600 --> 00:21:06,639 Speaker 1: we've never built the middle cloth that can complain, so 329 00:21:06,920 --> 00:21:11,280 Speaker 1: you're not hearing any completely well uh here, that's many 330 00:21:11,280 --> 00:21:13,600 Speaker 1: people who read your college would say that's a characteristically 331 00:21:13,720 --> 00:21:17,000 Speaker 1: blunt assessment of the situation for India's economy. But thanks 332 00:21:17,080 --> 00:21:27,359 Speaker 1: very much for joining us. Thanks so Some people would 333 00:21:27,359 --> 00:21:30,119 Speaker 1: say that we talk too much about trade wars on 334 00:21:30,240 --> 00:21:32,719 Speaker 1: this podcast, but we have a lot to say about them, 335 00:21:33,000 --> 00:21:36,000 Speaker 1: and this week is no exception because we have a 336 00:21:36,080 --> 00:21:40,200 Speaker 1: really interesting analysis by our economists who are part of 337 00:21:40,240 --> 00:21:44,760 Speaker 1: Bloomberg Economics, of the impact that trade wars are having already, 338 00:21:45,000 --> 00:21:49,120 Speaker 1: particularly in China, but also on production levels and sales 339 00:21:49,400 --> 00:21:52,080 Speaker 1: in the US. And I'm very glad that I can 340 00:21:52,119 --> 00:21:54,479 Speaker 1: talk a bit with one of the people who crunched 341 00:21:54,520 --> 00:21:57,520 Speaker 1: the numbers on this, one of our Eurozone economists, maybe 342 00:21:57,520 --> 00:21:59,919 Speaker 1: a Kuza maybe. Thank you very much for joining us 343 00:22:00,000 --> 00:22:02,840 Speaker 1: from Zurich, Hasty if any, thanks for inviting me. So 344 00:22:03,000 --> 00:22:05,000 Speaker 1: tell me a little bit about this research, because what 345 00:22:05,119 --> 00:22:08,680 Speaker 1: was interesting to me is that although often people have 346 00:22:08,800 --> 00:22:12,560 Speaker 1: talked about the big picture potential impact of trade wars 347 00:22:12,680 --> 00:22:17,080 Speaker 1: on global growth, you took a micro approach looking at 348 00:22:17,200 --> 00:22:19,679 Speaker 1: the imports that have been affected by tariffs. What did 349 00:22:19,720 --> 00:22:22,520 Speaker 1: you find so yes, we used very detailed data from 350 00:22:22,560 --> 00:22:25,359 Speaker 1: the US International Trade Commission, and we looked at the 351 00:22:25,440 --> 00:22:30,800 Speaker 1: different categories, the six thousand plus categories of products that 352 00:22:30,960 --> 00:22:34,640 Speaker 1: have been imposed some tarifts by the US on US 353 00:22:34,760 --> 00:22:38,720 Speaker 1: on imports from China. And what we've found first is 354 00:22:38,760 --> 00:22:41,560 Speaker 1: that when you look at the value of imports from 355 00:22:41,680 --> 00:22:45,520 Speaker 1: China across those categories which have been parift since Juday 356 00:22:45,680 --> 00:22:49,040 Speaker 1: to September twenty eighteen Juday to September last year, if 357 00:22:49,080 --> 00:22:50,920 Speaker 1: you look at the time series, you can see a 358 00:22:51,000 --> 00:22:54,280 Speaker 1: sharp top which happens just after the introduction of the 359 00:22:54,359 --> 00:22:58,120 Speaker 1: different waves of tariffs. And in total, if you look 360 00:22:58,280 --> 00:23:01,920 Speaker 1: at the value of US imports from China across those 361 00:23:02,000 --> 00:23:05,360 Speaker 1: categories in the first quarter of twenty nineteen, so after 362 00:23:05,520 --> 00:23:07,880 Speaker 1: the introduction of all the tariffs of the first wave 363 00:23:07,960 --> 00:23:11,240 Speaker 1: of tariffs, and you compare with what happened a year earlier, 364 00:23:11,600 --> 00:23:14,560 Speaker 1: that is value on those goods is done by twenty 365 00:23:14,640 --> 00:23:18,399 Speaker 1: six percent. That's fifteen point eight billion dollars worth of 366 00:23:19,000 --> 00:23:23,679 Speaker 1: Chinese imports that have not entered the US across across 367 00:23:23,720 --> 00:23:27,800 Speaker 1: those those products. What's interesting as well is that when 368 00:23:28,119 --> 00:23:31,440 Speaker 1: we looked at what happened to imports of those products 369 00:23:31,720 --> 00:23:34,200 Speaker 1: from the rest of the world. They have increased a 370 00:23:34,240 --> 00:23:37,240 Speaker 1: little bit, but only by five point four billion dollars 371 00:23:37,760 --> 00:23:41,200 Speaker 1: in the year to UH the first quarter of twenty nineteen. 372 00:23:41,280 --> 00:23:43,240 Speaker 1: So in total, it's a gap of ten point four 373 00:23:43,320 --> 00:23:47,240 Speaker 1: billion dollar worth of imports that has not entered the 374 00:23:47,400 --> 00:23:51,280 Speaker 1: US and those categories that have been tariffed for China. 375 00:23:52,920 --> 00:23:55,639 Speaker 1: Have you seen any evidence of this diversion of trade 376 00:23:55,800 --> 00:23:58,120 Speaker 1: as a result of these harriffs that you just get 377 00:23:58,200 --> 00:24:01,320 Speaker 1: the same products coming in from other countries rather than 378 00:24:01,359 --> 00:24:04,240 Speaker 1: the reduction in imports overall. So we've seen a little 379 00:24:04,280 --> 00:24:08,399 Speaker 1: bit of that, indeed, of diverge, diversion from them away 380 00:24:08,440 --> 00:24:11,600 Speaker 1: from China and to other countries um as you can see, 381 00:24:11,600 --> 00:24:14,800 Speaker 1: because there's still a ten billion gap in imports across 382 00:24:14,800 --> 00:24:18,400 Speaker 1: those categories. It does only partly of set the impact 383 00:24:18,600 --> 00:24:21,480 Speaker 1: of lower trade with China, but we've seen some of that. 384 00:24:21,600 --> 00:24:24,360 Speaker 1: We've seen in particular if you look across the main 385 00:24:25,720 --> 00:24:28,399 Speaker 1: trade partners for the US and the main countries in 386 00:24:28,520 --> 00:24:34,159 Speaker 1: the Asian subplate chain, countries like Vietnam, Vietnam, Taiwan, and 387 00:24:34,840 --> 00:24:38,560 Speaker 1: South Korea, I've seen an acceleration of their exports to 388 00:24:38,720 --> 00:24:41,639 Speaker 1: the of their exports to the US. I noticed in 389 00:24:41,720 --> 00:24:44,000 Speaker 1: your report that they also looked like there were just 390 00:24:44,080 --> 00:24:47,640 Speaker 1: some sort of creative ways around these tarriers that were 391 00:24:47,680 --> 00:24:50,040 Speaker 1: being found, like, for example, those big surge in the 392 00:24:50,119 --> 00:24:53,560 Speaker 1: number of TVs coming in from China to the US 393 00:24:53,680 --> 00:24:56,359 Speaker 1: which are not subject to tarriers, and a reduction in 394 00:24:56,440 --> 00:24:59,879 Speaker 1: the number of TV parts coming in because those are 395 00:25:00,080 --> 00:25:03,440 Speaker 1: subject to tariffs. But you would say that there's still 396 00:25:03,560 --> 00:25:07,639 Speaker 1: been a real impact on Chinese producers. Yes, I think so. 397 00:25:07,960 --> 00:25:10,879 Speaker 1: I think there has been a little bit of moving 398 00:25:10,920 --> 00:25:16,360 Speaker 1: across categories from from tarift categories to nontarift categories at 399 00:25:16,400 --> 00:25:19,280 Speaker 1: the margin, but overall, I think that's on the top. 400 00:25:19,359 --> 00:25:24,240 Speaker 1: And indeed, um total Chinese imports, total imports from China 401 00:25:24,359 --> 00:25:27,800 Speaker 1: to the US acrourse tarift and learned tarift categories of 402 00:25:27,960 --> 00:25:31,280 Speaker 1: decline from the first quarter of twenty eighteen to the 403 00:25:31,320 --> 00:25:34,920 Speaker 1: first quarter of because I mean President Trump would say 404 00:25:35,240 --> 00:25:37,960 Speaker 1: this is all great, because it's going to provide room 405 00:25:38,040 --> 00:25:40,480 Speaker 1: for all these US manufacturers to get in and start 406 00:25:40,560 --> 00:25:45,359 Speaker 1: producing things themselves. Have we seen domestically made goods filling 407 00:25:45,440 --> 00:25:48,440 Speaker 1: the gap? So unfortunately we can't see that from the 408 00:25:48,520 --> 00:25:51,359 Speaker 1: data we have because there are childe data, so we 409 00:25:51,600 --> 00:25:55,200 Speaker 1: only imports. What I would say is that when you 410 00:25:55,280 --> 00:25:58,399 Speaker 1: look at them at this imports number, it has clearly 411 00:25:58,640 --> 00:26:04,119 Speaker 1: has had a very disruptive effect on US imports from China. 412 00:26:04,840 --> 00:26:08,719 Speaker 1: It has had a disruptive effect on US imports total 413 00:26:08,920 --> 00:26:12,479 Speaker 1: total imports from the world in total, as we can 414 00:26:12,520 --> 00:26:16,560 Speaker 1: see these ten billions worth of goods that didn't enter 415 00:26:16,640 --> 00:26:20,080 Speaker 1: the US. And that's because China was such a dominant player, 416 00:26:20,240 --> 00:26:23,480 Speaker 1: such a big player across those categories that as the 417 00:26:23,600 --> 00:26:25,480 Speaker 1: rest of factories in the rest of the world, we're 418 00:26:25,520 --> 00:26:28,480 Speaker 1: not big enough to pick up the slack and to 419 00:26:28,600 --> 00:26:31,680 Speaker 1: HaVeset the effect. And because many of those goods are 420 00:26:31,680 --> 00:26:35,399 Speaker 1: actually intermediate goods, good that US factories would use in 421 00:26:35,480 --> 00:26:39,120 Speaker 1: their production process, it is likely to have a creeping 422 00:26:39,160 --> 00:26:42,800 Speaker 1: impact on US industry because basically what happens is that 423 00:26:42,920 --> 00:26:45,680 Speaker 1: part of the supply chain, the backward looking part of 424 00:26:46,480 --> 00:26:50,159 Speaker 1: their access to supply has been broken. Thank you very much. 425 00:26:50,160 --> 00:26:52,520 Speaker 1: I hope we have you on again as we track 426 00:26:52,760 --> 00:26:59,000 Speaker 1: the impact of this trade will thank you thanks for 427 00:26:59,080 --> 00:27:01,359 Speaker 1: listening to Stephanomic. Join us next week for more on 428 00:27:01,440 --> 00:27:04,399 Speaker 1: the ground insight into the global economy. In the meantime, 429 00:27:04,480 --> 00:27:07,160 Speaker 1: you can find us on the Bloomberg Terminal, website, app 430 00:27:07,320 --> 00:27:09,959 Speaker 1: or wherever you get your podcasts. We'd love it if 431 00:27:09,960 --> 00:27:11,800 Speaker 1: you took the time to rate and review our show 432 00:27:11,880 --> 00:27:14,120 Speaker 1: so it can reach more people. And for more news 433 00:27:14,160 --> 00:27:17,359 Speaker 1: and analysis through the week from Bloomberg Economics, you just 434 00:27:17,440 --> 00:27:20,520 Speaker 1: have to follow us Economics on Twitter. You can also 435 00:27:20,640 --> 00:27:24,920 Speaker 1: find me on at my Stephanomics. This episode was written 436 00:27:24,920 --> 00:27:28,639 Speaker 1: and reported by Anaban Nag and Rishti beneval I should 437 00:27:28,680 --> 00:27:30,600 Speaker 1: mention that you also heard a clip in that piece 438 00:27:30,640 --> 00:27:33,280 Speaker 1: from Christine Leguard, which was actually recorded at a Bloomberg 439 00:27:33,359 --> 00:27:37,000 Speaker 1: event in December six. It was produced by Magnus Hendrickson 440 00:27:37,080 --> 00:27:40,600 Speaker 1: and edited by Nastrine Syria and Scott Laman, who's also 441 00:27:40,680 --> 00:27:44,440 Speaker 1: the executive producer of Stephanomics Special thanks to Mehir Sharma 442 00:27:44,680 --> 00:27:48,480 Speaker 1: and Mahiva Kuzan. Francesco Levy is the head of Bloomberg 443 00:27:48,560 --> 00:27:49,000 Speaker 1: Podcast