1 00:00:00,280 --> 00:00:07,240 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:08,280 --> 00:00:10,840 Speaker 2: Everyone's going to be happy, and we're going to be 3 00:00:10,880 --> 00:00:12,000 Speaker 2: able to keep people. 4 00:00:11,760 --> 00:00:14,120 Speaker 3: In our country that are going to be very productive people, 5 00:00:14,640 --> 00:00:16,680 Speaker 3: and in many cases these companies are going to pay 6 00:00:16,720 --> 00:00:28,320 Speaker 3: a lot of money for that. I'm Stephanie Flanders, head 7 00:00:28,320 --> 00:00:32,240 Speaker 3: of Government and Economics at Bloomberg, and welcome to Trumponomics, 8 00:00:32,240 --> 00:00:34,760 Speaker 3: the podcast that looks at the economic world of Donald Trump, 9 00:00:35,120 --> 00:00:38,040 Speaker 3: how he's already shaped the global economy, and what on 10 00:00:38,120 --> 00:00:41,680 Speaker 3: earth is going to happen next. Well. Over the weekend, 11 00:00:41,800 --> 00:00:45,320 Speaker 3: Donald Trump surprised the world by placing one hundred thousand 12 00:00:45,400 --> 00:00:48,680 Speaker 3: dollars fee on the cost of an H one B 13 00:00:49,000 --> 00:00:53,400 Speaker 3: visa for new employees entering the US. The short term 14 00:00:53,440 --> 00:00:57,200 Speaker 3: result was travel chaos. Thousands of skilled employees working in 15 00:00:57,240 --> 00:00:59,040 Speaker 3: the US on an H one B who happened to 16 00:00:59,080 --> 00:01:01,840 Speaker 3: be traveling abroad were told to get back on US 17 00:01:01,880 --> 00:01:05,360 Speaker 3: soil by midnight Sunday just to make sure they weren't stranded. 18 00:01:05,959 --> 00:01:06,119 Speaker 4: Now. 19 00:01:06,160 --> 00:01:09,080 Speaker 3: Eventually, the White House Press Secretary cleared up the confusion. 20 00:01:09,200 --> 00:01:12,039 Speaker 3: The fee would only apply to new applicants, but that 21 00:01:12,200 --> 00:01:15,199 Speaker 3: still left a big question hanging over the US tech 22 00:01:15,240 --> 00:01:18,800 Speaker 3: companies who depend on these skilled workers and those visas 23 00:01:19,160 --> 00:01:22,520 Speaker 3: to keep America at the forefront of global tech innovation, 24 00:01:23,120 --> 00:01:25,880 Speaker 3: and with India accounting for seventy percent of them, it 25 00:01:26,000 --> 00:01:29,440 Speaker 3: also causes a massive headache for the Indian software companies 26 00:01:29,560 --> 00:01:32,039 Speaker 3: who are a big part of Indian Prime Minister Mody's 27 00:01:32,080 --> 00:01:35,399 Speaker 3: growth strategy for the country. So that leads us to 28 00:01:35,520 --> 00:01:41,000 Speaker 3: a big, quite complicated question about that one policy. Who 29 00:01:41,080 --> 00:01:44,199 Speaker 3: gains and who loses from President Trump putting a big 30 00:01:44,240 --> 00:01:48,120 Speaker 3: price tag on skilled foreign talent working in the US. 31 00:01:50,240 --> 00:01:52,160 Speaker 3: Of course, it's not just the H one B change. 32 00:01:52,160 --> 00:01:54,120 Speaker 3: A few weeks ago we saw another example of a 33 00:01:54,160 --> 00:01:57,040 Speaker 3: business getting caught in the crosshairs of an America first 34 00:01:57,080 --> 00:02:02,720 Speaker 3: immigration policy with that ice raid a Hyundai plant in Georgia. 35 00:02:02,800 --> 00:02:05,920 Speaker 3: So do expensive visas and raids like that one actively 36 00:02:06,040 --> 00:02:09,760 Speaker 3: undermine the Trump administration's effort to attract foreign investment and 37 00:02:09,800 --> 00:02:11,480 Speaker 3: in the end, could they actually be good news for 38 00:02:11,520 --> 00:02:15,880 Speaker 3: countries and companies outside the US, including maybe India, who 39 00:02:15,960 --> 00:02:20,600 Speaker 3: can offer those skilled workers an alternative home. Well, we 40 00:02:20,639 --> 00:02:22,919 Speaker 3: have a lot of strands to unpit here and I'm 41 00:02:22,919 --> 00:02:25,680 Speaker 3: delighted that we can talk about both sides of this 42 00:02:25,760 --> 00:02:29,919 Speaker 3: policy today with Michael Deng geoeconomics technology analyst at Bloomberg 43 00:02:29,960 --> 00:02:34,320 Speaker 3: Economics sitting in Washington today. And Chetna Kumar are geoeconomics 44 00:02:34,360 --> 00:02:37,200 Speaker 3: analyst for South Asia who's joining us from New Delhi. 45 00:02:37,320 --> 00:02:39,240 Speaker 3: And I should say, I'm sitting in New York and 46 00:02:39,280 --> 00:02:47,960 Speaker 3: it's Tuesday morning, US time, But I think it's probably 47 00:02:48,080 --> 00:02:52,520 Speaker 3: useful to start with some context on how important this 48 00:02:52,639 --> 00:02:56,280 Speaker 3: visa has become for the US and indeed its relevance 49 00:02:56,320 --> 00:02:58,720 Speaker 3: to India. So Michael just sort of talk us through 50 00:02:59,360 --> 00:03:02,280 Speaker 3: the kind of companies that have relied on this visa 51 00:03:02,440 --> 00:03:05,720 Speaker 3: and how important they are to America's tech industry. 52 00:03:06,480 --> 00:03:09,160 Speaker 1: I think primarily most of the companies that have been 53 00:03:09,240 --> 00:03:11,520 Speaker 1: using H one b's, I would say probably two thirds 54 00:03:11,560 --> 00:03:14,040 Speaker 1: are the software and IT sectors. So you have the 55 00:03:14,040 --> 00:03:17,480 Speaker 1: IT contracting and service companies Tata, Infosits, etc. But you 56 00:03:17,520 --> 00:03:20,360 Speaker 1: also have Big Tech to a significant degree, relying on 57 00:03:20,400 --> 00:03:22,960 Speaker 1: these H one b's to bring in software talent from overseas. 58 00:03:23,639 --> 00:03:26,280 Speaker 1: These companies are going to be the ones most directly 59 00:03:26,360 --> 00:03:29,200 Speaker 1: hit by this H one B fee change for IT 60 00:03:29,440 --> 00:03:31,480 Speaker 1: services specifically, the impact is going to be greater just 61 00:03:31,480 --> 00:03:34,160 Speaker 1: because it hits their business model directly. Big Tech in 62 00:03:34,200 --> 00:03:36,960 Speaker 1: terms of software may be more capable of absorbing that hit. 63 00:03:37,400 --> 00:03:42,000 Speaker 1: But outside of these directly computer related industries, there's also adjacent, 64 00:03:42,520 --> 00:03:46,760 Speaker 1: smaller but also critical industries like semiconductors, for example, which 65 00:03:47,040 --> 00:03:49,560 Speaker 1: don't necessarily need to bring in a huge bulk of 66 00:03:49,880 --> 00:03:52,560 Speaker 1: foreign talent, but they do need to bring in a 67 00:03:52,640 --> 00:03:57,160 Speaker 1: smaller group of highly specialized engineers to support their design, 68 00:03:57,240 --> 00:04:01,360 Speaker 1: equipment and materials, manufacturing initiatives, etc. Which all kind of 69 00:04:01,360 --> 00:04:03,680 Speaker 1: coincide with this huge restoring push that's going on in 70 00:04:03,680 --> 00:04:07,120 Speaker 1: the US. So across the board, you're seeing software and 71 00:04:07,160 --> 00:04:10,920 Speaker 1: it computer related occupations being hit hard first, but then 72 00:04:11,000 --> 00:04:14,520 Speaker 1: a lot of other more niche industries that need foreign 73 00:04:14,560 --> 00:04:17,840 Speaker 1: talent to support their own growth into the future also 74 00:04:17,920 --> 00:04:18,599 Speaker 1: being impacted. 75 00:04:19,760 --> 00:04:23,640 Speaker 3: The broad response that the administration might have, and I've 76 00:04:23,640 --> 00:04:26,200 Speaker 3: heard even in the last few days, is these are 77 00:04:26,279 --> 00:04:31,400 Speaker 3: easy ways for US tech companies to bring in cheaper 78 00:04:31,880 --> 00:04:37,240 Speaker 3: foreign workers rather than pay American skilled workers, and it's 79 00:04:37,360 --> 00:04:40,480 Speaker 3: undercutting American skilled workers, and that's what they're trying to 80 00:04:40,520 --> 00:04:42,839 Speaker 3: prevent with this by putting this one hundred thousand dollars 81 00:04:42,920 --> 00:04:44,280 Speaker 3: wedge in there. 82 00:04:44,960 --> 00:04:47,680 Speaker 1: I do think that's true to some degree. We've started 83 00:04:47,720 --> 00:04:51,679 Speaker 1: to see the market for especially junior entry level computer 84 00:04:51,720 --> 00:04:55,520 Speaker 1: science software developers get a little soft. Recently, the stat 85 00:04:55,600 --> 00:04:58,400 Speaker 1: for recent graduates who are majoring in computer science and 86 00:04:58,400 --> 00:05:00,359 Speaker 1: the unemployment rate is around six percent, as one of 87 00:05:00,360 --> 00:05:03,599 Speaker 1: the highest in the US currently. So I think specifically 88 00:05:03,640 --> 00:05:06,279 Speaker 1: for that segment and this computer industry that this H 89 00:05:06,320 --> 00:05:09,960 Speaker 1: one B policy is targeting, it is true to an extent. 90 00:05:10,040 --> 00:05:12,880 Speaker 1: I think this could help that segment specifically. The fear 91 00:05:12,960 --> 00:05:15,760 Speaker 1: is that this kind of blunt change also pulls in 92 00:05:16,040 --> 00:05:18,160 Speaker 1: a lot of the other strategic industries that don't rely 93 00:05:18,200 --> 00:05:20,840 Speaker 1: on this model of labor to support their workforce, and 94 00:05:20,960 --> 00:05:23,839 Speaker 1: that they need the more highly specialized workforce that the 95 00:05:23,920 --> 00:05:26,839 Speaker 1: H ANDEB is supposed to fulfill, and one hundred thousand 96 00:05:26,960 --> 00:05:29,839 Speaker 1: is quite a big barrier in many cases they do 97 00:05:29,920 --> 00:05:32,920 Speaker 1: require specialized talent, but that fee may be too big 98 00:05:32,960 --> 00:05:34,919 Speaker 1: of a barrier in terms of bringing in foreign talent, 99 00:05:35,000 --> 00:05:37,920 Speaker 1: and you could inadvertently harm US tech ambitions in the 100 00:05:37,960 --> 00:05:38,719 Speaker 1: long run as well. 101 00:05:39,040 --> 00:05:41,400 Speaker 3: I was struct that Read Hastings, the co founder of 102 00:05:41,480 --> 00:05:44,440 Speaker 3: Netflix and certainly no great supporter of Donald Trump. He's 103 00:05:44,440 --> 00:05:46,719 Speaker 3: been a sort of prominent back of the Democrats in 104 00:05:46,760 --> 00:05:49,040 Speaker 3: recent years. He came out saying he thought this was 105 00:05:49,080 --> 00:05:51,720 Speaker 3: a good idea this hundred thousand dollar fee for some 106 00:05:51,760 --> 00:05:54,640 Speaker 3: of the reasons that you just suggested. But we can 107 00:05:54,680 --> 00:05:58,000 Speaker 3: get into whether there might be exemptions and whether there's 108 00:05:58,040 --> 00:06:00,400 Speaker 3: a way in which this could be more targeted in 109 00:06:00,440 --> 00:06:02,799 Speaker 3: a second. But I wanted to get to you because 110 00:06:03,160 --> 00:06:05,479 Speaker 3: my impression from reading some of the coverage was that 111 00:06:05,520 --> 00:06:07,960 Speaker 3: there was really a lot of concern around this over 112 00:06:08,000 --> 00:06:10,920 Speaker 3: the weekend, and it's still raising questions about a big 113 00:06:11,000 --> 00:06:12,280 Speaker 3: chunk of Indian industry. 114 00:06:13,960 --> 00:06:17,560 Speaker 4: That's right, Stephanie. The one hundred thousand dollars fee impacts 115 00:06:17,600 --> 00:06:21,559 Speaker 4: primarily Indian tech workers and Indian tech companies in the US, 116 00:06:22,040 --> 00:06:23,800 Speaker 4: because we know seventy percent of the H and B 117 00:06:23,920 --> 00:06:26,839 Speaker 4: talent comes from India, but traditionally it was Indian tech 118 00:06:26,880 --> 00:06:30,080 Speaker 4: companies the Data Cognizant emphasis which have been the greatest 119 00:06:30,080 --> 00:06:33,000 Speaker 4: beneficiaries of the H and D program, and their business 120 00:06:33,040 --> 00:06:35,839 Speaker 4: model relies on being able to hire these Indian tech 121 00:06:35,880 --> 00:06:38,279 Speaker 4: workers and bringing them to the US to service on 122 00:06:38,480 --> 00:06:42,159 Speaker 4: site contracts. So not being able to hire modified workforce 123 00:06:42,240 --> 00:06:44,640 Speaker 4: is going to dent their pricing how they're able to 124 00:06:44,640 --> 00:06:47,719 Speaker 4: offer services, and we've seen some of that impact show 125 00:06:47,800 --> 00:06:50,120 Speaker 4: up in Indian stock prices and ID stock prices over 126 00:06:50,160 --> 00:06:52,520 Speaker 4: the weekend and over this week particularly because of that. 127 00:06:53,040 --> 00:06:56,200 Speaker 4: I think the second concern is broader about US and 128 00:06:56,240 --> 00:06:58,720 Speaker 4: your relations and what this means for the broader trajectory 129 00:06:58,720 --> 00:07:00,480 Speaker 4: of the relationship. I think we can and ignore the 130 00:07:00,520 --> 00:07:04,000 Speaker 4: context within which this is happening. Tariffs on India have 131 00:07:04,040 --> 00:07:06,520 Speaker 4: been doubled to fifty percent. There have been some other 132 00:07:06,600 --> 00:07:10,840 Speaker 4: moves by the US administration attacking India, including provoking exemption 133 00:07:10,920 --> 00:07:13,680 Speaker 4: leavers for India's investments in the Iranian pot of Chapahar 134 00:07:13,760 --> 00:07:16,560 Speaker 4: and others, which make it seem like President Trump is 135 00:07:16,600 --> 00:07:18,600 Speaker 4: tightening the squeeze on India. 136 00:07:18,400 --> 00:07:18,880 Speaker 2: Quite a bit. 137 00:07:19,160 --> 00:07:22,240 Speaker 4: There was a notion that perhaps India could withstand the 138 00:07:22,280 --> 00:07:25,160 Speaker 4: fifty percent tariffs and a whole firm because it wasn't 139 00:07:25,200 --> 00:07:28,000 Speaker 4: really a goods manufacturing goods exporting countries. 140 00:07:28,400 --> 00:07:31,680 Speaker 2: But targeting services is really the engine of India's economy. 141 00:07:31,920 --> 00:07:36,160 Speaker 4: So for scale, India exports about two hundred billion dollars 142 00:07:36,160 --> 00:07:38,480 Speaker 4: worth of ID services every year, and about one hundred 143 00:07:38,480 --> 00:07:41,480 Speaker 4: billion of that goes to the US, So targeting H 144 00:07:41,560 --> 00:07:43,360 Speaker 4: and B workers is sort of seen as a strike 145 00:07:43,520 --> 00:07:44,840 Speaker 4: on that entire industry. 146 00:07:45,280 --> 00:07:47,680 Speaker 3: You know, when people think of Indian outsourcing we think 147 00:07:47,760 --> 00:07:51,360 Speaker 3: of inevitably, we think of call centers. I know they've 148 00:07:51,400 --> 00:07:53,720 Speaker 3: developed a lot since the early days of call centers, 149 00:07:53,720 --> 00:07:56,600 Speaker 3: and there's lots of other services that these companies are providing. 150 00:07:56,800 --> 00:08:00,520 Speaker 3: But this particular policies, if it's about people all coming 151 00:08:00,560 --> 00:08:02,760 Speaker 3: to the States, why are they affected. You're just talking 152 00:08:02,800 --> 00:08:05,520 Speaker 3: about the people who are helping coordinate on the ground 153 00:08:05,560 --> 00:08:06,440 Speaker 3: in the US. 154 00:08:07,520 --> 00:08:11,760 Speaker 4: So that's about three hundred thousand Indian H ONEB workers 155 00:08:11,800 --> 00:08:14,760 Speaker 4: in the US currently, and that's about a tenth of 156 00:08:14,880 --> 00:08:16,400 Speaker 4: the total Indian diaspora. 157 00:08:16,640 --> 00:08:20,320 Speaker 3: That's a tenth of the diaspora in America. 158 00:08:20,400 --> 00:08:21,800 Speaker 2: In the US, that's right. 159 00:08:21,960 --> 00:08:25,320 Speaker 4: These Indian companies have relied initially because of the cost 160 00:08:25,480 --> 00:08:28,600 Speaker 4: arbitrage of being able to hire Indian workers and bring 161 00:08:28,600 --> 00:08:31,640 Speaker 4: them to the US. But there's also some advantages culturally 162 00:08:31,680 --> 00:08:34,160 Speaker 4: and being able to efficiencies to being able to bring 163 00:08:34,200 --> 00:08:37,040 Speaker 4: workers from India to service. A lot of the consulting 164 00:08:37,040 --> 00:08:39,800 Speaker 4: and it contracts on site, and many of these contracts 165 00:08:39,840 --> 00:08:43,000 Speaker 4: do require the service provider to be on site. And 166 00:08:43,040 --> 00:08:45,319 Speaker 4: that's why you see the surge of sort of Indian 167 00:08:45,360 --> 00:08:47,800 Speaker 4: workers in the US. It's not as much of a 168 00:08:47,880 --> 00:08:51,160 Speaker 4: rude shock as it seems because Indian companies have been 169 00:08:51,200 --> 00:08:54,040 Speaker 4: preparing and have been expecting the change of policy. Now 170 00:08:54,120 --> 00:08:57,720 Speaker 4: for a while, President Trump did try to ban the 171 00:08:57,840 --> 00:08:59,800 Speaker 4: H one D program in its first administration. 172 00:09:00,000 --> 00:09:01,040 Speaker 2: I was not successful. 173 00:09:01,400 --> 00:09:03,199 Speaker 4: But since then, of the last ten years, we've sort 174 00:09:03,200 --> 00:09:06,160 Speaker 4: of seen Indian companies actually scale back their alliance on 175 00:09:06,280 --> 00:09:08,760 Speaker 4: H one D visas for workers in the US. They're 176 00:09:08,760 --> 00:09:10,960 Speaker 4: about thirty percent of the last decade, which is a 177 00:09:11,000 --> 00:09:13,880 Speaker 4: sizeable reduction. And at the same time, we've seen actually 178 00:09:13,960 --> 00:09:17,439 Speaker 4: US tech companies rely more on the Indian workforce in 179 00:09:17,440 --> 00:09:20,840 Speaker 4: Indian deck workers like the Meta, Google, Netflix, et cetera, 180 00:09:20,840 --> 00:09:23,160 Speaker 4: to sort of bridge their own skills gaps. So we've 181 00:09:23,200 --> 00:09:24,679 Speaker 4: seen a little bit of the shift happened in the 182 00:09:24,760 --> 00:09:27,520 Speaker 4: last ten years of US companies increasing their alliance on 183 00:09:27,559 --> 00:09:27,960 Speaker 4: EAH one. 184 00:09:27,920 --> 00:09:31,520 Speaker 3: D's Okay, now, Michael, given that a lot of things 185 00:09:31,559 --> 00:09:34,880 Speaker 3: that come out of the administration, shall we say, don't 186 00:09:34,920 --> 00:09:38,080 Speaker 3: turn out to be kind of hard and fast, is 187 00:09:38,120 --> 00:09:40,480 Speaker 3: there a perception that there could be quite a lot 188 00:09:40,480 --> 00:09:42,240 Speaker 3: of holes in this Do you see that as being 189 00:09:42,240 --> 00:09:44,840 Speaker 3: the first reaction of US companies to just see if 190 00:09:44,840 --> 00:09:46,960 Speaker 3: they can get an exemption. We've certainly seen a lot 191 00:09:47,000 --> 00:09:49,720 Speaker 3: of companies looking for exemptions in tariffs, for example. 192 00:09:50,160 --> 00:09:54,280 Speaker 1: Yes, I think in the absence of clear criteria and timelines, 193 00:09:54,320 --> 00:09:56,520 Speaker 1: the first instinct for a lot of companies, I would argue, 194 00:09:56,520 --> 00:09:59,160 Speaker 1: with the exception of maybe the IT consulting services companies 195 00:09:59,160 --> 00:10:03,120 Speaker 1: because they were cifically targeted in the proclamation. But any 196 00:10:03,160 --> 00:10:07,080 Speaker 1: other company like tangentially tech Related, STEM related is certainly 197 00:10:07,080 --> 00:10:10,360 Speaker 1: going to press for an exemption first because that circumvents 198 00:10:10,400 --> 00:10:12,840 Speaker 1: the entire issue for them, and I think in critical 199 00:10:12,840 --> 00:10:17,280 Speaker 1: strategic industries like semiconductors, AI infrastructure, that's probably not going 200 00:10:17,320 --> 00:10:19,360 Speaker 1: to be an issue for them. The key is whether 201 00:10:19,400 --> 00:10:23,520 Speaker 1: this administration, at least in these critical technology ecosystems, understands 202 00:10:23,520 --> 00:10:26,400 Speaker 1: the full scope of industries and companies that would need 203 00:10:26,440 --> 00:10:29,400 Speaker 1: to be exempted, and do the understand all the labor 204 00:10:29,480 --> 00:10:32,400 Speaker 1: dynamics and the workforce shortages that affect all the supporting 205 00:10:32,400 --> 00:10:35,760 Speaker 1: industries that aren't just the headline flagship firms. Certainly, I 206 00:10:35,800 --> 00:10:37,679 Speaker 1: don't think they're going to miss like an Nvidia or 207 00:10:37,679 --> 00:10:41,880 Speaker 1: an open AI for example, But a lot of smaller companies, suppliers, etc. 208 00:10:42,440 --> 00:10:45,680 Speaker 1: Also face workforce issues, and this gets into another issue 209 00:10:45,679 --> 00:10:47,640 Speaker 1: that's persisted over the past decade, and that many of 210 00:10:47,679 --> 00:10:52,480 Speaker 1: these non software STEM industries have traditionally had trouble attracting 211 00:10:52,520 --> 00:10:55,840 Speaker 1: domestic US graduates because they've all gone to software, and 212 00:10:55,920 --> 00:10:58,000 Speaker 1: so that foreign talent pipeline has been the way that 213 00:10:58,040 --> 00:10:59,600 Speaker 1: they've kept their workforce sufficient. 214 00:11:00,080 --> 00:11:01,640 Speaker 3: And what kind of job would that be? 215 00:11:02,160 --> 00:11:05,640 Speaker 1: So specialist engineers in terms of chip design, chip manufacturing, 216 00:11:05,640 --> 00:11:08,160 Speaker 1: for example, I'm using semiconductors because I'm more familiar with 217 00:11:08,200 --> 00:11:08,720 Speaker 1: the industry. 218 00:11:09,040 --> 00:11:11,880 Speaker 3: Why would you not attract American workers into that sector. 219 00:11:11,920 --> 00:11:13,679 Speaker 3: It seems like that would be just as attractive as 220 00:11:13,720 --> 00:11:16,280 Speaker 3: some of the other sort of STEM sectors. 221 00:11:15,920 --> 00:11:18,680 Speaker 1: Mainly because software is so much more attractive in terms 222 00:11:18,720 --> 00:11:21,920 Speaker 1: of the lifestyle and the salaries. And so there's that 223 00:11:22,040 --> 00:11:24,400 Speaker 1: gap there that was best filled for a while in 224 00:11:24,440 --> 00:11:27,439 Speaker 1: many cases by foreign researchers and foreign graduates. And I 225 00:11:27,480 --> 00:11:30,720 Speaker 1: think the stat even for semiconductor related fields is greater 226 00:11:30,760 --> 00:11:33,440 Speaker 1: than fifty or sixty percent of researchers all come from 227 00:11:33,520 --> 00:11:36,319 Speaker 1: outside of the US, and so cutting off that pipeline 228 00:11:36,360 --> 00:11:40,679 Speaker 1: right now would be pretty harmful for US tech competitiveness 229 00:11:40,679 --> 00:11:43,280 Speaker 1: in these leading industries that really reply on a smaller 230 00:11:43,320 --> 00:11:45,200 Speaker 1: pool of specialized labor, and. 231 00:11:45,120 --> 00:11:47,640 Speaker 3: Just as as obvious question. If there is such scarcity, 232 00:11:48,040 --> 00:11:50,400 Speaker 3: can't they just pay the one hundred thousand dollars The 233 00:11:50,440 --> 00:11:53,480 Speaker 3: assumption of the US this administration has been in quite 234 00:11:53,480 --> 00:11:55,560 Speaker 3: a lot of areas that the rest of the world 235 00:11:55,600 --> 00:11:58,559 Speaker 3: is willing to pay up for access to the US 236 00:11:58,559 --> 00:12:00,479 Speaker 3: in whatever form. 237 00:12:00,840 --> 00:12:04,480 Speaker 1: I do think for certain industries they probably are okay 238 00:12:04,520 --> 00:12:07,240 Speaker 1: with paying it. Unfortunately, those industries also happen to be 239 00:12:07,400 --> 00:12:09,840 Speaker 1: the flagship firms and industries that are probably most likely 240 00:12:09,880 --> 00:12:13,360 Speaker 1: going to get an exemption, like big tech companies are 241 00:12:13,360 --> 00:12:14,960 Speaker 1: not going to have that much of an issue paying 242 00:12:14,960 --> 00:12:17,079 Speaker 1: one hundred thousand barrier if they really need the talent 243 00:12:17,080 --> 00:12:17,640 Speaker 1: they require. 244 00:12:17,800 --> 00:12:19,760 Speaker 3: But they could just go and have dinner with Donald 245 00:12:19,800 --> 00:12:21,360 Speaker 3: Trump again and maybe sort it out. 246 00:12:21,520 --> 00:12:24,959 Speaker 1: Yes, Yes, and same thing for the headlining semiconductor firms 247 00:12:24,960 --> 00:12:28,920 Speaker 1: for example. But if you dive down more into semiconductor manufacturing, 248 00:12:29,080 --> 00:12:31,520 Speaker 1: when we're trying to reshore US fabs at a time 249 00:12:31,559 --> 00:12:34,720 Speaker 1: when there's already a pretty significant cost delta with Asia fabs, 250 00:12:35,120 --> 00:12:37,960 Speaker 1: adding one hundred thousand dollars barriers to the sort of 251 00:12:38,280 --> 00:12:40,880 Speaker 1: core engineers you need to ramp up capacity in US 252 00:12:40,920 --> 00:12:45,199 Speaker 1: fabs is not very beneficial to reshoring and it's sort 253 00:12:45,240 --> 00:12:49,160 Speaker 1: of this layer underneath, this middle core of engineering talent 254 00:12:49,200 --> 00:12:50,839 Speaker 1: in the US is going to be most affected by 255 00:12:50,880 --> 00:12:51,400 Speaker 1: this barrier. 256 00:12:51,640 --> 00:12:54,880 Speaker 3: I love the phrase that the cost delta with Asia FABS, 257 00:12:54,920 --> 00:12:56,640 Speaker 3: but I guess we should sort of spell out that's 258 00:12:56,679 --> 00:12:59,880 Speaker 3: just the fact that Asian companies producing chips are cheaper 259 00:13:00,040 --> 00:13:03,600 Speaker 3: and US ones. Yes, yes, yes, but we can stick 260 00:13:03,640 --> 00:13:05,880 Speaker 3: with FABS. I mean, just sort of teasing out the 261 00:13:05,960 --> 00:13:09,680 Speaker 3: implications of what Michael was saying. It suggests that in 262 00:13:09,720 --> 00:13:13,640 Speaker 3: these kind of high tech areas where the US has 263 00:13:14,120 --> 00:13:18,160 Speaker 3: kind of significant ambitions, it seems like either they'll pay 264 00:13:18,280 --> 00:13:21,240 Speaker 3: the US companies to get this talent or they will 265 00:13:21,280 --> 00:13:26,120 Speaker 3: get an exemption. And that leaves the IT services sector, which, 266 00:13:26,160 --> 00:13:30,080 Speaker 3: as you've described, is something that has been very important 267 00:13:30,080 --> 00:13:33,040 Speaker 3: to some of India's biggest companies in the last few years. 268 00:13:33,120 --> 00:13:35,640 Speaker 3: So does this come down to more of a sort 269 00:13:35,679 --> 00:13:41,479 Speaker 3: of underhand way to tax those Indian exports of services 270 00:13:41,520 --> 00:13:43,520 Speaker 3: without saying upfront that that's what we're doing. 271 00:13:44,360 --> 00:13:47,560 Speaker 4: Definitely is hard to see a what of motivating this administration, 272 00:13:47,800 --> 00:13:50,640 Speaker 4: but it does seem like it's one of the ways 273 00:13:50,720 --> 00:13:53,880 Speaker 4: to tipen the squeze on India. The fifty percentatus have 274 00:13:54,000 --> 00:13:57,560 Speaker 4: not led to India keething on goods or stopping buying 275 00:13:57,600 --> 00:14:00,600 Speaker 4: Russian oil. It's not let a big change. There's sort 276 00:14:00,600 --> 00:14:05,840 Speaker 4: of policy and agricultural market access. So targeting India's IT services, 277 00:14:05,880 --> 00:14:08,440 Speaker 4: it's best performing companies and bring a lot of revenue 278 00:14:08,880 --> 00:14:12,400 Speaker 4: is possibly one way of President Trump indicating the US 279 00:14:12,440 --> 00:14:14,679 Speaker 4: as pharm mow leverage over India than India has over 280 00:14:14,720 --> 00:14:17,920 Speaker 4: the US. But what the impact of this is then, 281 00:14:17,960 --> 00:14:19,760 Speaker 4: whether it will actually be your tax or not. I 282 00:14:19,760 --> 00:14:21,600 Speaker 4: think it's going to play out over a long term, 283 00:14:21,640 --> 00:14:24,360 Speaker 4: and I think immediately though, yes, there will be a 284 00:14:24,400 --> 00:14:27,080 Speaker 4: margin squeeze for some of these Indian companies. They will 285 00:14:27,120 --> 00:14:29,920 Speaker 4: have to shift and think rethink their business models and 286 00:14:30,200 --> 00:14:34,240 Speaker 4: pricing strategies. There might actually be some structural advantages for India. 287 00:14:34,280 --> 00:14:37,520 Speaker 4: India and President Trump actually might be doing India a 288 00:14:37,520 --> 00:14:40,680 Speaker 4: good turn by sort of restricting H one B visas 289 00:14:40,680 --> 00:14:43,360 Speaker 4: for these kinds of jobs and others. How So, to 290 00:14:43,400 --> 00:14:47,520 Speaker 4: start with fewer H one B visas means there's opportunity 291 00:14:47,560 --> 00:14:49,600 Speaker 4: for a lot of these investments to go back into 292 00:14:49,680 --> 00:14:53,320 Speaker 4: jobs in India. We've seen over the last decade a 293 00:14:53,400 --> 00:14:56,840 Speaker 4: boom in global capability centers, which is the newer kind 294 00:14:56,840 --> 00:14:59,200 Speaker 4: of outsourcing that you were speaking to. These are not 295 00:14:59,240 --> 00:15:02,600 Speaker 4: the BPOs of the nineteen nineties. They are more advanced 296 00:15:02,600 --> 00:15:06,440 Speaker 4: captive centers that everybody from US banks like JP Morgan 297 00:15:07,320 --> 00:15:11,960 Speaker 4: in Goldman Sachs to US companies and chip design companies 298 00:15:12,080 --> 00:15:14,640 Speaker 4: have built and used in India and they provide everything 299 00:15:14,680 --> 00:15:19,520 Speaker 4: from advanced chip designing, engineering, data analysis, and even product development. 300 00:15:20,160 --> 00:15:23,040 Speaker 4: So what started as cost arbitrage in India sort of 301 00:15:23,080 --> 00:15:26,920 Speaker 4: turning into value and innovation in India. And there's an 302 00:15:26,960 --> 00:15:29,960 Speaker 4: expectation that because H and B pisas are going to 303 00:15:29,960 --> 00:15:33,080 Speaker 4: become cost there, some of these jobs might find their 304 00:15:33,120 --> 00:15:36,840 Speaker 4: way back to India and contribute to this booming GCC economy. 305 00:15:36,880 --> 00:15:51,480 Speaker 3: There one observation that's been made about China over the years, 306 00:15:51,520 --> 00:15:55,080 Speaker 3: and particularly in response to the first Trump term and 307 00:15:55,120 --> 00:15:59,080 Speaker 3: the trade war with China then, was that the initial 308 00:15:59,120 --> 00:16:04,480 Speaker 3: punishment also inspires a policy reaction within China. We've seen 309 00:16:04,960 --> 00:16:08,280 Speaker 3: where there's a sort of greater determination to reduce reliance 310 00:16:08,320 --> 00:16:11,880 Speaker 3: on the US, and now as we've come into the 311 00:16:11,920 --> 00:16:15,280 Speaker 3: second Trump term, we've seen various ways in which China 312 00:16:15,320 --> 00:16:18,200 Speaker 3: has kind of long prepared for this moment and has 313 00:16:18,400 --> 00:16:22,680 Speaker 3: has ways of mitigating the effects of the very high tariffs. 314 00:16:23,000 --> 00:16:25,440 Speaker 3: You know, wouldn't we say the same thing about India? 315 00:16:25,560 --> 00:16:27,880 Speaker 3: And that's somewhat embedded in what you just said. But 316 00:16:28,040 --> 00:16:30,880 Speaker 3: is there not a slightly different Moody growth strategy that 317 00:16:30,960 --> 00:16:33,160 Speaker 3: comes out of this that is actually less beholden to 318 00:16:33,200 --> 00:16:33,680 Speaker 3: the US. 319 00:16:34,520 --> 00:16:37,120 Speaker 4: Possibly, And I think we're already seeing some of the 320 00:16:37,160 --> 00:16:40,160 Speaker 4: signals that the Prime Minister is sending about improving india 321 00:16:40,200 --> 00:16:43,160 Speaker 4: self alliance or people, or the government is seeing about 322 00:16:43,160 --> 00:16:45,680 Speaker 4: wanting to support people who are losing h mend jobs 323 00:16:45,680 --> 00:16:47,880 Speaker 4: coming back to India. But I do want to say 324 00:16:48,080 --> 00:16:49,760 Speaker 4: the case with India is a little bit different than 325 00:16:49,840 --> 00:16:54,000 Speaker 4: China in the sense that India's technology capabilities and India's 326 00:16:54,000 --> 00:16:57,840 Speaker 4: tech industry is so complementary and deeply linked with the US. 327 00:16:58,080 --> 00:17:01,440 Speaker 4: They're trying to unravel this relationship back hurts both for 328 00:17:01,520 --> 00:17:04,120 Speaker 4: a considerable period of time. Yes, India is a big 329 00:17:04,200 --> 00:17:06,600 Speaker 4: value exporter to the US, but not a big market 330 00:17:06,640 --> 00:17:09,359 Speaker 4: for US firms. It's a big sort of place of 331 00:17:09,400 --> 00:17:13,840 Speaker 4: operations for US companies, So I think unraveling this relationship 332 00:17:13,920 --> 00:17:16,040 Speaker 4: is harder. And I think service is a little bit 333 00:17:16,080 --> 00:17:18,399 Speaker 4: trickier than goods in terms of trying to replace and 334 00:17:18,440 --> 00:17:21,680 Speaker 4: build talent pools and supply chains so quickly. Yes, and no, 335 00:17:21,800 --> 00:17:23,440 Speaker 4: I think there's going to be a different growth strategy. 336 00:17:23,440 --> 00:17:26,840 Speaker 4: And yes, India's exports are somewhat diversified, its services industries 337 00:17:26,840 --> 00:17:30,120 Speaker 4: a lot more maturity. Its talent is wanted in other 338 00:17:30,119 --> 00:17:32,200 Speaker 4: parts of the world, and there might be some sort 339 00:17:32,240 --> 00:17:34,840 Speaker 4: of urgency in other countries trying to tap up Indian talent. 340 00:17:35,000 --> 00:17:37,400 Speaker 4: But I think in the long run, there's enough drivers 341 00:17:37,400 --> 00:17:40,680 Speaker 4: and complementalees between these two industries, and these two countries 342 00:17:40,800 --> 00:17:43,040 Speaker 4: trying to break away may not be beneficial to either. 343 00:17:44,000 --> 00:17:46,200 Speaker 3: Michael, I guess just pulling out on that very quickly. 344 00:17:46,320 --> 00:17:48,280 Speaker 3: Apart from that longer term point, I mean, will other 345 00:17:48,280 --> 00:17:49,800 Speaker 3: countries just take advantage of this? 346 00:17:50,200 --> 00:17:52,920 Speaker 1: I think to a small degree, yes, And like we've 347 00:17:52,960 --> 00:17:57,280 Speaker 1: seen small signals of the UK, Germany, Canada, for example, 348 00:17:57,359 --> 00:18:01,600 Speaker 1: where skilled worker immigration isn't quite as let's say, arbitrary 349 00:18:01,680 --> 00:18:04,439 Speaker 1: or difficult as the US that there's some science that 350 00:18:04,520 --> 00:18:06,880 Speaker 1: small quantities may go there, But the US is really 351 00:18:06,880 --> 00:18:10,679 Speaker 1: the core of this global tech talent migration. And whatever 352 00:18:10,720 --> 00:18:13,280 Speaker 1: happens on the H one B side moving forward, how 353 00:18:13,280 --> 00:18:16,200 Speaker 1: they decide the exemptions, what industries they work with or 354 00:18:16,280 --> 00:18:19,159 Speaker 1: what industries they don't really will shape the flow of 355 00:18:19,160 --> 00:18:19,840 Speaker 1: global talent. 356 00:18:20,240 --> 00:18:22,280 Speaker 3: But I guess for those countries who worry about the 357 00:18:22,280 --> 00:18:25,119 Speaker 3: brain drain of their most skilled talent, I heard Canadian 358 00:18:25,160 --> 00:18:27,440 Speaker 3: Prime Minister Mark Carney talk about this earlier this week, 359 00:18:27,480 --> 00:18:30,600 Speaker 3: that they have a large number of very highly trained 360 00:18:30,760 --> 00:18:34,159 Speaker 3: people in advanced STEM courses in Canada and then a 361 00:18:34,160 --> 00:18:36,359 Speaker 3: big chunk of them go to the US. It's going 362 00:18:36,440 --> 00:18:37,920 Speaker 3: to be easier for these countries to hold on to 363 00:18:38,000 --> 00:18:38,800 Speaker 3: their skilled talent. 364 00:18:39,359 --> 00:18:41,360 Speaker 1: Yes, But I would say the reason for a lot 365 00:18:41,359 --> 00:18:43,879 Speaker 1: of this brain drain is just the much higher compensation 366 00:18:43,920 --> 00:18:45,959 Speaker 1: and benefits in the US in the first place, And 367 00:18:46,040 --> 00:18:49,360 Speaker 1: so that doesn't fully go away even with this fee 368 00:18:49,400 --> 00:18:51,520 Speaker 1: in place. If they're still hiring roughly the same amount 369 00:18:51,520 --> 00:18:54,040 Speaker 1: of H one b's per year, it maybe shift in 370 00:18:54,119 --> 00:18:56,439 Speaker 1: terms of the industry that they hire through, right, and 371 00:18:56,480 --> 00:18:59,119 Speaker 1: so in terms of the overall quantity. If this H 372 00:18:59,160 --> 00:19:02,880 Speaker 1: one B is properly executed, I don't see a huge 373 00:19:02,880 --> 00:19:05,320 Speaker 1: shift happening to other countries, just in terms of the 374 00:19:05,320 --> 00:19:07,160 Speaker 1: reasons why they come to the US in the first. 375 00:19:06,920 --> 00:19:09,920 Speaker 3: Place, Okay, and just on the sort of longer term 376 00:19:10,000 --> 00:19:12,600 Speaker 3: question and we faced this issue also in the sort 377 00:19:12,640 --> 00:19:16,680 Speaker 3: of Bidenomics era, that there was a great desire in 378 00:19:16,720 --> 00:19:20,639 Speaker 3: the administration for speed in building up US domestic industries 379 00:19:20,640 --> 00:19:24,800 Speaker 3: in certain sectors, semiconductors being one, but also a big 380 00:19:24,840 --> 00:19:26,960 Speaker 3: desire to have it all be home grown and be 381 00:19:27,359 --> 00:19:32,800 Speaker 3: aware a vehicle for upgrading US born talent. And there's 382 00:19:32,800 --> 00:19:36,119 Speaker 3: clearly a tension between those things. If you want to 383 00:19:36,160 --> 00:19:38,320 Speaker 3: have it all the US workers, as one person said 384 00:19:38,320 --> 00:19:39,800 Speaker 3: to me, well we could do that in five years. 385 00:19:39,840 --> 00:19:41,280 Speaker 3: If you want to do it in one or two years, 386 00:19:41,280 --> 00:19:42,880 Speaker 3: then there's going to be a lot of people will 387 00:19:42,920 --> 00:19:46,119 Speaker 3: be bringing in from overseas. Has that tension increased in 388 00:19:46,160 --> 00:19:47,960 Speaker 3: the second Trump administration. 389 00:19:48,880 --> 00:19:52,960 Speaker 1: Yes, So above all else, what the domestic semiconductor and 390 00:19:53,040 --> 00:19:56,520 Speaker 1: wider tech ecosystem needs is time to build up these 391 00:19:56,720 --> 00:19:59,320 Speaker 1: workforce programs to get graduates and employees into the right 392 00:19:59,359 --> 00:20:03,439 Speaker 1: industries firms. The Trump administration nominally has promised a lot 393 00:20:03,480 --> 00:20:06,880 Speaker 1: of support for workforce issues, but some of their actions 394 00:20:06,920 --> 00:20:10,119 Speaker 1: had a chilling effect on supporting these industries properly, the 395 00:20:10,200 --> 00:20:12,359 Speaker 1: Kanda Ice Reid being one example, just in terms of 396 00:20:12,640 --> 00:20:15,200 Speaker 1: making sure foreign talent can come in as a transition 397 00:20:15,680 --> 00:20:19,080 Speaker 1: to patch that pipeline and tel domestic talent can come online. 398 00:20:19,280 --> 00:20:22,080 Speaker 1: For the semiconductor space, specifically, what happened with what's known 399 00:20:22,119 --> 00:20:26,280 Speaker 1: as GNATCAST or the NSTC, which was responsible for administering 400 00:20:26,640 --> 00:20:29,359 Speaker 1: roughly seven to eight billion dollars in semi conductor research 401 00:20:29,359 --> 00:20:33,000 Speaker 1: and development funding was also not great for workforce develment development. 402 00:20:33,080 --> 00:20:35,200 Speaker 1: There was a sizable portion of that was aimed at 403 00:20:35,440 --> 00:20:39,119 Speaker 1: further building out domestic workforce initiatives. So this sort of 404 00:20:39,160 --> 00:20:42,639 Speaker 1: inconsistency at a time when we really want to accelerate 405 00:20:42,680 --> 00:20:45,119 Speaker 1: this pace at getting the domestic workforce online is a 406 00:20:45,160 --> 00:20:45,800 Speaker 1: little troubling. 407 00:20:46,160 --> 00:20:48,720 Speaker 3: We started off asking about who the losers and who 408 00:20:48,720 --> 00:20:50,760 Speaker 3: the gainers are. I think we've identified that the big 409 00:20:50,800 --> 00:20:53,080 Speaker 3: loser is going to be integration, or at least the 410 00:20:53,119 --> 00:20:55,919 Speaker 3: sort of the flow of workers from one country to another, 411 00:20:56,960 --> 00:21:00,320 Speaker 3: and that Trump administration would say that's exactly the point 412 00:21:00,640 --> 00:21:03,520 Speaker 3: that we're trying to have less of this kind of 413 00:21:03,560 --> 00:21:08,000 Speaker 3: free flowing global labor market. But che, I mean people 414 00:21:08,000 --> 00:21:12,560 Speaker 3: in India just reading this as an attack on Modi administration. 415 00:21:13,800 --> 00:21:17,000 Speaker 4: I think President Trump has not been particularly friendly to 416 00:21:17,080 --> 00:21:20,400 Speaker 4: any of his former partners and allies or US partners, 417 00:21:20,560 --> 00:21:23,600 Speaker 4: so in one way, He's not treating India any differently. 418 00:21:24,040 --> 00:21:26,080 Speaker 4: But I think the fall for India has been from 419 00:21:26,119 --> 00:21:28,240 Speaker 4: such a great height that it's hard to ignore. I 420 00:21:28,240 --> 00:21:31,919 Speaker 4: think this term sadden on the expectation of this relationship 421 00:21:31,960 --> 00:21:35,320 Speaker 4: or mutual appreciation between these two leaders leading to less 422 00:21:35,320 --> 00:21:38,600 Speaker 4: affrictions between them, or an early harbor, a straight deal 423 00:21:38,680 --> 00:21:41,200 Speaker 4: even and that's not happened. And I think the fact 424 00:21:41,200 --> 00:21:43,879 Speaker 4: that primis to more these shares this close relationship or 425 00:21:43,880 --> 00:21:46,440 Speaker 4: did share this close relationship with President Trump is increasing 426 00:21:46,440 --> 00:21:49,879 Speaker 4: the pressure on him. Certainly, the H one B visa 427 00:21:50,320 --> 00:21:52,880 Speaker 4: sort of holders in India are a small but very 428 00:21:53,000 --> 00:21:57,000 Speaker 4: visible and aspirational minority for the country. Getting this H 429 00:21:57,040 --> 00:21:59,280 Speaker 4: and B job and moving to the US and eventually 430 00:21:59,320 --> 00:22:01,760 Speaker 4: a pathway to green cord. We're seen as sort of 431 00:22:01,760 --> 00:22:04,960 Speaker 4: a hallmarket success for many young Indian students, and I 432 00:22:05,000 --> 00:22:08,120 Speaker 4: think that big impact. In addition to the very tough 433 00:22:08,240 --> 00:22:11,080 Speaker 4: rhetoric that we've seen from President Trump calling the Indian 434 00:22:11,119 --> 00:22:15,520 Speaker 4: economy dead, or his advisors calling the Ukraine war Modi's 435 00:22:15,600 --> 00:22:18,040 Speaker 4: war or in your laundromat for Russia, I think, putting 436 00:22:18,080 --> 00:22:21,800 Speaker 4: it all together, it's certainly added to the census that 437 00:22:21,840 --> 00:22:23,919 Speaker 4: India is not a special partner of the US anymore, 438 00:22:23,920 --> 00:22:26,440 Speaker 4: and it's not expecting to be treated any differently from 439 00:22:26,480 --> 00:22:28,879 Speaker 4: other partners that have in the expectation that sort of 440 00:22:28,920 --> 00:22:31,720 Speaker 4: its relationship between the leaders who sort of get in 441 00:22:31,760 --> 00:22:33,600 Speaker 4: their better deal and sort of faded away. 442 00:22:33,960 --> 00:22:37,440 Speaker 3: It's a reminder that you can put this one piece 443 00:22:37,480 --> 00:22:41,879 Speaker 3: of grit, this charge in the wheels of the global economy, 444 00:22:41,920 --> 00:22:44,879 Speaker 3: and it just tens of thousands, hundreds of thousands of 445 00:22:45,040 --> 00:22:48,040 Speaker 3: people and companies can be affected for quite a long 446 00:22:48,080 --> 00:22:51,240 Speaker 3: time to come. Chetner, Michael, thank you so much. 447 00:22:51,600 --> 00:23:01,880 Speaker 2: Thank you, Thanks Stephanie, thanks. 448 00:23:01,680 --> 00:23:04,199 Speaker 3: For listening to Trumpomics from Bloomberg. It was hosted by 449 00:23:04,200 --> 00:23:07,040 Speaker 3: me Stephanie Flanders. I was joined by Michael Deng and 450 00:23:07,119 --> 00:23:12,520 Speaker 3: Chetna Kumar of Bloomberg Economics. Trumpnomics was produced as ever 451 00:23:12,600 --> 00:23:16,600 Speaker 3: by Samasadi Moses and m and Avil Brown, with help 452 00:23:16,640 --> 00:23:20,040 Speaker 3: from Amy Keen and special thanks this week to Rachel 453 00:23:20,080 --> 00:23:25,200 Speaker 3: Lewis Chriskey. Sound designed for the shows by Blake Maples 454 00:23:25,240 --> 00:24:03,120 Speaker 3: and Kelly Gary and Sage Bowman is Bloomberg's head of Podcasts.