1 00:00:13,640 --> 00:00:14,960 Speaker 1: This is Wall Street Week. 2 00:00:15,160 --> 00:00:19,360 Speaker 2: I'm David Weston bringing you stories of capitalism. This week, 3 00:00:19,400 --> 00:00:23,560 Speaker 2: the price of regulating competition around the world. We spoke 4 00:00:23,600 --> 00:00:27,400 Speaker 2: with former EU Commissioner Margareta Vesteier on her very last 5 00:00:27,480 --> 00:00:29,920 Speaker 2: day and the job, about what she has meant for 6 00:00:30,000 --> 00:00:34,880 Speaker 2: Europe's tech industry and a growing threat for the data 7 00:00:34,920 --> 00:00:38,959 Speaker 2: at the center of our economy. How US statistical agencies 8 00:00:39,000 --> 00:00:42,400 Speaker 2: are grappling with shrinking budgets even before cuts to the 9 00:00:42,440 --> 00:00:46,800 Speaker 2: overall federal budget. But we begin with a story about 10 00:00:46,840 --> 00:00:50,240 Speaker 2: one hundred and five trillion dollars. That is the size 11 00:00:50,280 --> 00:00:54,400 Speaker 2: of the gross domestic product of the entire world, and 12 00:00:54,640 --> 00:00:58,040 Speaker 2: also the amount of money researchers tell us Americans will 13 00:00:58,080 --> 00:01:01,320 Speaker 2: inherit over the next twenty five five years. If that 14 00:01:01,360 --> 00:01:03,920 Speaker 2: seems large, that's because it is. 15 00:01:06,200 --> 00:01:09,959 Speaker 3: It's definitely the biggest number we've ever seen. We've been 16 00:01:09,959 --> 00:01:12,440 Speaker 3: looking at this research for over a decade now. 17 00:01:13,080 --> 00:01:16,960 Speaker 2: Chase Horton is a senior analyst that Cerooly Associates, and 18 00:01:17,000 --> 00:01:20,080 Speaker 2: he's the lead author of a new report quantifying how 19 00:01:20,160 --> 00:01:22,360 Speaker 2: much wealth in the US will be given out or 20 00:01:22,400 --> 00:01:25,399 Speaker 2: passed on over the next two and a half decades. 21 00:01:26,240 --> 00:01:28,560 Speaker 2: It's a big jump from the numbers to really found 22 00:01:28,600 --> 00:01:31,400 Speaker 2: a few years ago, and he thinks he knows why. 23 00:01:32,120 --> 00:01:34,760 Speaker 3: It's really a confluence of three trends. Over the past 24 00:01:35,440 --> 00:01:38,120 Speaker 3: dozen or so years, we've seen a substantial amount of 25 00:01:38,200 --> 00:01:41,959 Speaker 3: wealth creation, So privately held wealth by households in the 26 00:01:42,040 --> 00:01:46,000 Speaker 3: United States has increased essentially one hundred percent since we 27 00:01:46,000 --> 00:01:48,160 Speaker 3: were looked at this in twenty eleven, and that's on 28 00:01:48,200 --> 00:01:51,760 Speaker 3: an inflation adjusted basis. In addition, we also have seen 29 00:01:51,920 --> 00:01:56,360 Speaker 3: wealth become increasingly concentrated among fewer wealthier households, and those 30 00:01:56,400 --> 00:02:00,560 Speaker 3: wealthier households are more likely to be survived by their assets, 31 00:02:00,680 --> 00:02:02,880 Speaker 3: so they're not going to be spending those assets down 32 00:02:03,000 --> 00:02:05,960 Speaker 3: like the rest of us. And we've also seen wealth 33 00:02:05,960 --> 00:02:09,840 Speaker 3: concentration among older households, so more wealth is held today 34 00:02:09,880 --> 00:02:12,080 Speaker 3: by households that are over the age of sixty than 35 00:02:12,120 --> 00:02:14,400 Speaker 3: we've seen in a long time. And it's also the 36 00:02:14,480 --> 00:02:17,320 Speaker 3: highest portion. If you look at the ratio of expected 37 00:02:17,360 --> 00:02:19,799 Speaker 3: to wealth transfer in the next twenty five years as 38 00:02:19,800 --> 00:02:23,160 Speaker 3: a ratio of overall wealth held today, we see about 39 00:02:23,440 --> 00:02:26,080 Speaker 3: eighty percent of the wealth held today going to be 40 00:02:26,080 --> 00:02:28,320 Speaker 3: in motion over the course of the next twenty five years. 41 00:02:28,600 --> 00:02:31,200 Speaker 3: And when we first looked at this about a decade ago, 42 00:02:31,520 --> 00:02:34,640 Speaker 3: that ratio is closer to fifty percent of assets in motion. 43 00:02:34,880 --> 00:02:38,200 Speaker 3: So the ratio of wealth expected to be changing hands 44 00:02:38,200 --> 00:02:40,880 Speaker 3: in the next twenty five years is significant and much 45 00:02:40,919 --> 00:02:43,120 Speaker 3: greater than what we even saw a decade ago. 46 00:02:43,919 --> 00:02:47,400 Speaker 2: More money getting passed down over a relatively short time, 47 00:02:47,960 --> 00:02:50,760 Speaker 2: and for the one in five who receive any inheritance 48 00:02:50,800 --> 00:02:53,760 Speaker 2: at all, the share of their net worth coming from 49 00:02:53,760 --> 00:02:57,560 Speaker 2: that inheritance rather than their earned income is on the rise. 50 00:02:58,240 --> 00:03:02,200 Speaker 2: A new Bloomberg analysis shows today your financial status has 51 00:03:02,240 --> 00:03:04,400 Speaker 2: more to do with who your parents are than at 52 00:03:04,440 --> 00:03:08,840 Speaker 2: any time in recent history. That inherited money now accounts 53 00:03:08,840 --> 00:03:11,000 Speaker 2: for at least a quarter of the wealth for the 54 00:03:11,080 --> 00:03:15,960 Speaker 2: average inheritor, but many economists think that figure is much higher, 55 00:03:16,400 --> 00:03:20,800 Speaker 2: including former Treasury Secretary than Wall Street Week contributor Larry Summers. 56 00:03:21,200 --> 00:03:24,760 Speaker 4: If you account what happens when somebody gets an inheritance 57 00:03:24,840 --> 00:03:27,760 Speaker 4: and then they invest it, and that builds up more wealth, 58 00:03:28,200 --> 00:03:32,079 Speaker 4: that probably the vast majority is certainly a majority of 59 00:03:32,120 --> 00:03:36,640 Speaker 4: the wealth in our economy is related to inheritance, and 60 00:03:37,120 --> 00:03:39,680 Speaker 4: that's of course a complicated thing. On the one hand, 61 00:03:39,760 --> 00:03:43,800 Speaker 4: family values are good, on the other hand, it's not 62 00:03:43,880 --> 00:03:47,440 Speaker 4: like it's equally distributed. It's not like it's even as 63 00:03:47,560 --> 00:03:51,400 Speaker 4: unequally distributed as income. It's not even like it's as 64 00:03:51,480 --> 00:03:56,160 Speaker 4: unequally distributed as the rest of wealth. It's really very 65 00:03:56,280 --> 00:04:01,520 Speaker 4: much a phenomenon about a very small action of the population. 66 00:04:02,880 --> 00:04:06,040 Speaker 2: Given how much wealth is being transferred, one might think 67 00:04:06,080 --> 00:04:09,360 Speaker 2: we may see a wider distribution of that wealth as well, 68 00:04:10,000 --> 00:04:11,360 Speaker 2: but don't count on it. 69 00:04:12,240 --> 00:04:16,599 Speaker 3: We constantly get asked, will this be redistributive in terms 70 00:04:16,600 --> 00:04:19,080 Speaker 3: of wealth in the United States, And from what we've 71 00:04:19,120 --> 00:04:22,000 Speaker 3: seen in the numbers is we don't really think that 72 00:04:22,000 --> 00:04:25,359 Speaker 3: that's an expectation that people should have. You know, we 73 00:04:25,440 --> 00:04:28,279 Speaker 3: see a significant amount of the wealth, over fifty percent 74 00:04:28,320 --> 00:04:30,400 Speaker 3: is held by high net worth households, so those that 75 00:04:30,440 --> 00:04:33,160 Speaker 3: are ten million or more in net worth, and that 76 00:04:33,240 --> 00:04:36,200 Speaker 3: makes up around two percent of the population, and we 77 00:04:36,279 --> 00:04:38,279 Speaker 3: expect a lot of that wealth to go to the 78 00:04:38,279 --> 00:04:41,760 Speaker 3: top two percent of inheritors. So we don't really see 79 00:04:41,800 --> 00:04:44,640 Speaker 3: any sort of reason or thing to make us believe 80 00:04:44,680 --> 00:04:47,760 Speaker 3: that this is going to be, you know, widely distributed 81 00:04:47,960 --> 00:04:50,360 Speaker 3: beneficially for all Americans. 82 00:04:51,320 --> 00:04:54,600 Speaker 2: All that concentrated wealth being passed down echoes what the 83 00:04:54,760 --> 00:04:57,839 Speaker 2: United States saw back in the Gilded Age of the 84 00:04:57,920 --> 00:05:01,680 Speaker 2: late nineteenth century, which led President Teddy Roosevelt to call 85 00:05:01,760 --> 00:05:06,400 Speaker 2: for a graduated inheritance tax on big fortunes properly safeguarded 86 00:05:06,560 --> 00:05:11,040 Speaker 2: against evasion. And Andrew Carnegie, who became the richest man 87 00:05:11,120 --> 00:05:13,680 Speaker 2: in the world in nineteen oh one when he sold 88 00:05:13,720 --> 00:05:18,120 Speaker 2: his steel company to John D. Rockefeller, agreed saying, of 89 00:05:18,200 --> 00:05:23,359 Speaker 2: all forms of taxation, this seems the wisest. In nineteen sixteen, 90 00:05:23,560 --> 00:05:26,760 Speaker 2: Congress enacted the federal estate tax that's been with us 91 00:05:26,800 --> 00:05:30,040 Speaker 2: in some form or another ever since. But today that 92 00:05:30,120 --> 00:05:33,240 Speaker 2: tax doesn't apply to the vast majority of the one 93 00:05:33,360 --> 00:05:36,160 Speaker 2: hundred and five trillion dollars passing hands. 94 00:05:36,880 --> 00:05:38,840 Speaker 4: I think there's a lot of good that's come in 95 00:05:38,839 --> 00:05:44,520 Speaker 4: this country out of family businesses, family farms, of family assets. 96 00:05:45,120 --> 00:05:49,800 Speaker 4: I do think the extent to which this avoids taxation, 97 00:05:50,320 --> 00:05:54,640 Speaker 4: even among the very wealthiest people is something that is 98 00:05:55,600 --> 00:05:59,640 Speaker 4: very bizarre. Your study estimated that there'll be about two 99 00:05:59,680 --> 00:06:03,040 Speaker 4: and a half trillion dollars of wealth passing this year. 100 00:06:03,760 --> 00:06:07,080 Speaker 4: The collections on the inheritance tax are only going to 101 00:06:07,080 --> 00:06:10,200 Speaker 4: be about one percent of that two and a half 102 00:06:11,080 --> 00:06:18,039 Speaker 4: trillion dollars. Of course, relatively limited inheritances shouldn't get taxed. 103 00:06:18,520 --> 00:06:23,719 Speaker 4: Of course, you have to treat family farms in appropriate ways. 104 00:06:24,200 --> 00:06:27,919 Speaker 4: But two and a half trillion dollars passing and the 105 00:06:28,040 --> 00:06:32,880 Speaker 4: vast majority of that being among five percent or one 106 00:06:32,920 --> 00:06:36,440 Speaker 4: percent of the people who die, and only collecting one 107 00:06:36,520 --> 00:06:39,400 Speaker 4: percent of it in taxes. I do think we can 108 00:06:39,440 --> 00:06:39,880 Speaker 4: do better. 109 00:06:40,520 --> 00:06:43,400 Speaker 2: There is little reason to expect that the inheritors will 110 00:06:43,400 --> 00:06:46,800 Speaker 2: pay any more in taxes under the next Trump administration. 111 00:06:47,400 --> 00:06:50,320 Speaker 2: In his first term, mister Trump worked with Congress to 112 00:06:50,400 --> 00:06:52,919 Speaker 2: cut the number of people subject to the tax to 113 00:06:53,040 --> 00:06:56,760 Speaker 2: near historic lows, and in campaigning for a second term, 114 00:06:57,040 --> 00:07:01,840 Speaker 2: advocated eliminating it altogether. But there is one way the 115 00:07:01,839 --> 00:07:06,600 Speaker 2: great wealth Transfer will reduce inequality. Women are set to 116 00:07:06,640 --> 00:07:08,960 Speaker 2: inherit more money than ever before. 117 00:07:09,880 --> 00:07:12,280 Speaker 5: Enormous amounts of this are going to women, because first, 118 00:07:12,320 --> 00:07:14,400 Speaker 5: you have to think that men and women have different 119 00:07:14,440 --> 00:07:18,080 Speaker 5: life expectancies, So first the money goes to the wife. 120 00:07:18,840 --> 00:07:22,160 Speaker 2: Emily Green is head of wealth management at Elevest, a 121 00:07:22,160 --> 00:07:27,320 Speaker 2: financial firm that focuses on working with women. Wealth advisors, brokers, 122 00:07:27,480 --> 00:07:30,680 Speaker 2: real estate agents and others could be well positioned for 123 00:07:30,720 --> 00:07:34,160 Speaker 2: a windfall as the wealth transfer accelerates in the next 124 00:07:34,200 --> 00:07:37,600 Speaker 2: few years, and Green says she and her team have 125 00:07:37,680 --> 00:07:41,720 Speaker 2: seen firsthand the shift from men to women and this. 126 00:07:41,760 --> 00:07:44,400 Speaker 5: Next generation millennials and such, there's a lot more single 127 00:07:44,440 --> 00:07:46,920 Speaker 5: women there have been in prior generation, So there's a 128 00:07:46,960 --> 00:07:50,440 Speaker 5: lot more women controlling the wealth as this inheritance comes 129 00:07:50,480 --> 00:07:53,840 Speaker 5: down than there was previously. It's really going to change 130 00:07:53,840 --> 00:07:57,400 Speaker 5: the way that we invest, spend, give all these different 131 00:07:57,440 --> 00:07:59,520 Speaker 5: types of things because women are going to get this 132 00:08:00,080 --> 00:08:01,080 Speaker 5: huge amount of money. 133 00:08:01,560 --> 00:08:03,880 Speaker 2: How far along are we in the process of this 134 00:08:04,080 --> 00:08:04,680 Speaker 2: wealth transfer. 135 00:08:04,800 --> 00:08:06,960 Speaker 5: We're still really early. We're still really early. 136 00:08:07,840 --> 00:08:11,240 Speaker 2: Until now, women have gotten a smaller share of inherited 137 00:08:11,240 --> 00:08:14,640 Speaker 2: wealth than men, but Soorooly estimates that over the next 138 00:08:14,720 --> 00:08:18,280 Speaker 2: quarter century, gen Z women will become the first to 139 00:08:18,320 --> 00:08:21,920 Speaker 2: receive at least half of the country's inheritance, and that 140 00:08:22,080 --> 00:08:25,680 Speaker 2: Green says, has major implications for the way that money 141 00:08:25,720 --> 00:08:28,560 Speaker 2: will be spent and invested in the future. 142 00:08:29,440 --> 00:08:31,840 Speaker 5: And you have seen women tend to hire, women tend 143 00:08:31,880 --> 00:08:35,840 Speaker 5: to give philanthropically, women tend to invest more in other women. 144 00:08:35,960 --> 00:08:38,120 Speaker 5: They can give more politically, they can look to make 145 00:08:38,160 --> 00:08:41,040 Speaker 5: sure that the people in office are reflecting them. You 146 00:08:41,120 --> 00:08:44,320 Speaker 5: think about businesses and so the more women can start 147 00:08:44,320 --> 00:08:47,079 Speaker 5: their own businesses and do these things, that changes society 148 00:08:47,080 --> 00:08:49,440 Speaker 5: as well. If you look at women business owner numbers, 149 00:08:49,440 --> 00:08:52,559 Speaker 5: they're great entrepreneurs. Women have the money to create businesses. 150 00:08:52,640 --> 00:08:55,240 Speaker 5: They can create businesses that serve them. So even think 151 00:08:55,240 --> 00:08:58,880 Speaker 5: about healthcare healthcare. For a long time, drugs were only 152 00:08:58,920 --> 00:09:01,440 Speaker 5: tested on men, and so when we think about healthcare, 153 00:09:01,480 --> 00:09:04,280 Speaker 5: if women can create healthcare companies that are focusing on 154 00:09:04,360 --> 00:09:07,199 Speaker 5: fifty percent of the population as well, you are changing things. 155 00:09:07,240 --> 00:09:10,080 Speaker 5: There's a lot of opportunity within these spaces because there's 156 00:09:10,080 --> 00:09:13,439 Speaker 5: a lot of companies that just aren't focusing on women 157 00:09:13,520 --> 00:09:15,080 Speaker 5: and how they're actually thinking about this. 158 00:09:15,600 --> 00:09:18,280 Speaker 2: An economy that's better suited to fulfill the needs of 159 00:09:18,320 --> 00:09:21,720 Speaker 2: the whole population rather than just fifty percent of it 160 00:09:21,760 --> 00:09:24,920 Speaker 2: is certainly an improvement. But what about the eighty percent 161 00:09:24,920 --> 00:09:28,880 Speaker 2: of Americans who don't stand to inherit anything? Will rising 162 00:09:28,920 --> 00:09:31,560 Speaker 2: inequality way on economic dynamism? 163 00:09:32,120 --> 00:09:33,440 Speaker 1: How much does it matter? 164 00:09:34,280 --> 00:09:37,440 Speaker 2: Big questions and easy enough to ask, But when it 165 00:09:37,440 --> 00:09:40,120 Speaker 2: comes to answering them, what's best for the US economy 166 00:09:40,200 --> 00:09:43,560 Speaker 2: might not be what's best for your family, and one 167 00:09:43,600 --> 00:09:47,840 Speaker 2: of those will always come first. Just to push it 168 00:09:47,880 --> 00:09:49,760 Speaker 2: and get a little personal here. You wrote a paper 169 00:09:49,760 --> 00:09:51,960 Speaker 2: in nineteen eighty one. I think you were still a 170 00:09:51,960 --> 00:09:55,960 Speaker 2: PhD candidate at the time. Now you've had a very 171 00:09:55,960 --> 00:09:59,840 Speaker 2: successful career, I hope done reasonably well, have a fan, 172 00:10:00,720 --> 00:10:01,600 Speaker 2: have a granddaughter. 173 00:10:02,360 --> 00:10:03,599 Speaker 6: Have your views. 174 00:10:03,440 --> 00:10:08,520 Speaker 2: Changed on the intergenerational transfer wealth sort of that late 175 00:10:08,559 --> 00:10:10,320 Speaker 2: in your career as opposed at the very beginning. 176 00:10:10,840 --> 00:10:13,280 Speaker 4: I think at the very beginning, I didn't really think 177 00:10:13,360 --> 00:10:15,680 Speaker 4: of it as a personal issue at all. I thought 178 00:10:15,720 --> 00:10:19,000 Speaker 4: about it as just part of understanding the savings process 179 00:10:19,679 --> 00:10:26,040 Speaker 4: in the economy. Now I think about wanting to help 180 00:10:26,120 --> 00:10:30,920 Speaker 4: my children now that I have a grandchild, help my grandchild, 181 00:10:31,440 --> 00:10:34,480 Speaker 4: but certainly not to the point where they're not living 182 00:10:34,520 --> 00:10:40,000 Speaker 4: their own lives professionally and doing their own work. Is 183 00:10:40,040 --> 00:10:45,800 Speaker 4: the philosophy that I have. I take advantage of the 184 00:10:45,920 --> 00:10:51,040 Speaker 4: law as it is written, and I find it troubling 185 00:10:51,360 --> 00:10:55,680 Speaker 4: that the law affords me as many opportunities to avoid 186 00:10:55,800 --> 00:10:59,920 Speaker 4: paying taxes in completely legal ways. 187 00:11:00,200 --> 00:11:00,880 Speaker 7: As it does. 188 00:11:01,440 --> 00:11:05,679 Speaker 4: And I think there are all kinds of changes in 189 00:11:05,720 --> 00:11:10,240 Speaker 4: the estate tax law that would make that law function 190 00:11:10,920 --> 00:11:13,160 Speaker 4: in a fairer and more equitable way. 191 00:11:14,640 --> 00:11:18,240 Speaker 2: Those changes are unlikely to come soon, if at all, 192 00:11:18,640 --> 00:11:22,240 Speaker 2: and until they do, the economy may grow more dynastic, 193 00:11:22,920 --> 00:11:25,200 Speaker 2: forcing us to come to grips with how much of 194 00:11:25,240 --> 00:11:28,720 Speaker 2: our wealth is truly ours and how much we owe 195 00:11:28,800 --> 00:11:34,040 Speaker 2: to future generations coming up. As Europe struggles to get 196 00:11:34,080 --> 00:11:36,640 Speaker 2: its tech sector on the map, we examine the role 197 00:11:36,720 --> 00:11:40,360 Speaker 2: that competition policy may play and the trade offs between 198 00:11:40,440 --> 00:11:44,960 Speaker 2: taking the lead in regulation and spurring innovation. That's next 199 00:11:45,080 --> 00:11:46,000 Speaker 2: on Wall Street Week. 200 00:11:47,720 --> 00:11:51,120 Speaker 6: You're listening to Bloomberg Wall Street Week with David Weston 201 00:11:51,240 --> 00:12:10,560 Speaker 6: from Bloomberg Radio. This is Bloomberg Wall Street Week with 202 00:12:10,720 --> 00:12:13,120 Speaker 6: David Weston from Bloomberg Radio. 203 00:12:15,000 --> 00:12:18,360 Speaker 2: This is a story about trade offs, in particular the 204 00:12:18,440 --> 00:12:22,480 Speaker 2: tradeoff between making sure firms don't dominate an industry and 205 00:12:22,559 --> 00:12:25,320 Speaker 2: making sure that those same firms have the incentives to 206 00:12:25,400 --> 00:12:28,440 Speaker 2: innovate and grow so that they can drive the economy. 207 00:12:29,000 --> 00:12:31,640 Speaker 2: It's a tradeoff being made differently in the US and 208 00:12:31,800 --> 00:12:35,080 Speaker 2: Europe when it comes to the tech sector. Bloomberg's Max 209 00:12:35,160 --> 00:12:38,640 Speaker 2: Ramsey tells us about the EU's self assigned role as 210 00:12:38,679 --> 00:12:40,520 Speaker 2: the world's regulator in chief. 211 00:12:43,760 --> 00:12:46,679 Speaker 8: The European economy is facing a slow agony as it 212 00:12:46,760 --> 00:12:49,920 Speaker 8: struggles to compete with the US and China. So said 213 00:12:49,960 --> 00:12:54,199 Speaker 8: none other than former ECB President Mario Draghi in September, 214 00:12:54,480 --> 00:12:57,120 Speaker 8: pointing to sluggish growth and productivity. 215 00:12:57,920 --> 00:13:03,280 Speaker 9: Growth has been slowly down for a long time in Europe, 216 00:13:03,960 --> 00:13:07,480 Speaker 9: but we've ignored it. We until I would say, until 217 00:13:07,480 --> 00:13:10,520 Speaker 9: two years ago, we would never have such a conversation 218 00:13:10,679 --> 00:13:14,320 Speaker 9: as the one we're having today because things were sort 219 00:13:14,400 --> 00:13:19,160 Speaker 9: of going well. And now we cannot ignore it any longer. 220 00:13:19,240 --> 00:13:26,600 Speaker 9: Now conditions have changed. Europe is nowadays stuck in a 221 00:13:26,640 --> 00:13:33,200 Speaker 9: static industrial structure populated by meat technology companies which are 222 00:13:33,400 --> 00:13:38,360 Speaker 9: already mature. The problem is not that we lack smart people, 223 00:13:39,040 --> 00:13:42,880 Speaker 9: and we don't lack certainly good ideas, but there are 224 00:13:42,920 --> 00:13:48,960 Speaker 9: too many barriers to commercialize in innovations and scaling the 225 00:13:49,040 --> 00:13:50,760 Speaker 9: map in the European Union. 226 00:13:51,600 --> 00:13:54,160 Speaker 8: The numbers helped show the scale of the gap between 227 00:13:54,200 --> 00:13:57,960 Speaker 8: Europe and the US despite having a larger population. The 228 00:13:58,000 --> 00:14:02,920 Speaker 8: European Union's GDP sits around nineteen trillion dollars. That's compared 229 00:14:02,960 --> 00:14:06,319 Speaker 8: to twenty nine trillion dollars for the US. The stock 230 00:14:06,400 --> 00:14:10,640 Speaker 8: six hundred's market cap is about fourteen trillion dollars versus 231 00:14:10,720 --> 00:14:13,920 Speaker 8: over fifty trillion for the S and P five hundred. 232 00:14:14,160 --> 00:14:17,800 Speaker 8: One criticism has been that Brussel's aggressive approach to regulation, 233 00:14:18,520 --> 00:14:23,000 Speaker 8: especially with big technology companies, has held corporate Europe back 234 00:14:23,160 --> 00:14:26,560 Speaker 8: versus its global rivals. The person at the center of 235 00:14:26,560 --> 00:14:30,000 Speaker 8: this policy for the past decade is Margreta Vestaya, the 236 00:14:30,040 --> 00:14:33,560 Speaker 8: EU's Format Competition Commissioner. We spoke to her on her 237 00:14:33,640 --> 00:14:36,760 Speaker 8: final day as the bloc's top antitrust enforcer. 238 00:14:37,200 --> 00:14:42,560 Speaker 10: What that has been sort of mid live in Danish politics, 239 00:14:42,600 --> 00:14:46,240 Speaker 10: in European politics, was to make sure that everybody has 240 00:14:46,240 --> 00:14:49,840 Speaker 10: a fair chance of making it and making sure that 241 00:14:49,880 --> 00:14:53,520 Speaker 10: the market provides for thats that the market serves customers. 242 00:14:54,200 --> 00:14:56,880 Speaker 10: That has been you know, the thrend of these ten 243 00:14:57,000 --> 00:14:57,480 Speaker 10: years from me. 244 00:14:57,720 --> 00:14:59,560 Speaker 8: It's a mancha that has resulted in some of the 245 00:14:59,640 --> 00:15:02,880 Speaker 8: toughest rules in the world for big tech. Another way 246 00:15:02,880 --> 00:15:05,400 Speaker 8: to put it, if you can't beat Silicon Valley at 247 00:15:05,400 --> 00:15:09,000 Speaker 8: its own game, regulate it. Vestia has overseen some of 248 00:15:09,040 --> 00:15:12,320 Speaker 8: the EU's most high profile cases, taking on the world's 249 00:15:12,440 --> 00:15:16,600 Speaker 8: biggest companies and issuing over twenty five billion euros in 250 00:15:16,720 --> 00:15:20,280 Speaker 8: fines for abuses of dominance and cartel violations. 251 00:15:20,640 --> 00:15:21,880 Speaker 7: Today is a big win. 252 00:15:22,280 --> 00:15:25,720 Speaker 8: She won a record thirteen billion euro tax judgment against 253 00:15:25,760 --> 00:15:30,160 Speaker 8: Apple and oversaw one of the Eve's landmark pieces of regulation, 254 00:15:30,480 --> 00:15:34,400 Speaker 8: the Digital Markets Act. We asked about her rise from 255 00:15:34,520 --> 00:15:38,680 Speaker 8: Danish politician to perhaps the most feared name in Silicon Valley. 256 00:15:39,280 --> 00:15:42,240 Speaker 10: I don't really know how to prepare for being on 257 00:15:42,240 --> 00:15:45,240 Speaker 10: the front page of one of the US main papers. 258 00:15:45,440 --> 00:15:48,000 Speaker 10: It's important to figure out how to go with it. 259 00:15:48,840 --> 00:15:52,360 Speaker 10: I came, of course from executive positions in Denmark. I 260 00:15:52,440 --> 00:15:57,160 Speaker 10: was the Deputy Prime Minister. That several experiences as a minister. 261 00:15:57,760 --> 00:15:59,920 Speaker 10: But I think the most important point is that you've 262 00:16:00,040 --> 00:16:03,000 Speaker 10: believe in what you do. That's the cases that we 263 00:16:03,160 --> 00:16:06,960 Speaker 10: have thoughts, that they have been fought with great work 264 00:16:06,960 --> 00:16:10,040 Speaker 10: by the teams, with very strong evidence. I think that's 265 00:16:10,080 --> 00:16:12,840 Speaker 10: the kind of preparedness that you need, that you believe 266 00:16:12,880 --> 00:16:15,200 Speaker 10: that this is a strong case and you have something 267 00:16:15,520 --> 00:16:16,680 Speaker 10: valuable to say. 268 00:16:17,600 --> 00:16:20,480 Speaker 8: And from her point of view, things have gotten better. 269 00:16:20,960 --> 00:16:23,960 Speaker 10: I definitely think that we have made progress. The world 270 00:16:24,080 --> 00:16:28,239 Speaker 10: was different ten years ago. How we looked at technology 271 00:16:28,360 --> 00:16:31,840 Speaker 10: was very different. Ten years ago, nobody was really asking 272 00:16:31,920 --> 00:16:35,480 Speaker 10: questions to say is this really fair? Is this a 273 00:16:35,520 --> 00:16:39,280 Speaker 10: good way to behave in the marketplace? That has changed completely. 274 00:16:39,800 --> 00:16:43,160 Speaker 10: You know, now people have much more nuanced views. I 275 00:16:43,200 --> 00:16:45,600 Speaker 10: think seeing all the good things that comes with technology, 276 00:16:45,920 --> 00:16:48,760 Speaker 10: but also realizing that we really need to take care 277 00:16:49,800 --> 00:16:52,600 Speaker 10: both to make sure that the market remains open, but 278 00:16:52,680 --> 00:16:57,840 Speaker 10: also that technology is not addictive, is not providing rapid 279 00:16:57,880 --> 00:17:03,200 Speaker 10: holes or dark patterns or anything else that may manipulate 280 00:17:04,080 --> 00:17:08,040 Speaker 10: us as humans in ways that undermine how society works. 281 00:17:08,440 --> 00:17:11,639 Speaker 8: But today, Vestia's legacy faces a challenge from those who 282 00:17:11,720 --> 00:17:15,720 Speaker 8: say regulation has her Europe, stopping it from creating massive 283 00:17:15,760 --> 00:17:20,000 Speaker 8: technology companies to rival the US or China. We put 284 00:17:20,000 --> 00:17:22,840 Speaker 8: this to Roxanne Vasa, a woman at the very heart 285 00:17:22,920 --> 00:17:24,440 Speaker 8: of Europe's tech scene. 286 00:17:25,040 --> 00:17:26,000 Speaker 7: What I sum up. 287 00:17:27,560 --> 00:17:31,720 Speaker 11: Versus europe regulation, Well, I mean I think Europe definitely 288 00:17:31,760 --> 00:17:35,200 Speaker 11: has the image and the reputation of always wanting to regulate, 289 00:17:36,040 --> 00:17:36,879 Speaker 11: and they're good at it. 290 00:17:40,280 --> 00:17:43,720 Speaker 8: Vasa is the director of Station F, a startup campus 291 00:17:43,840 --> 00:17:47,239 Speaker 8: in Paris. She's also a scout for Sequoia Capital and 292 00:17:47,320 --> 00:17:48,920 Speaker 8: an angel investor herself. 293 00:17:49,240 --> 00:17:54,560 Speaker 11: And I definitely think regulation does in some cases slow 294 00:17:54,640 --> 00:17:57,800 Speaker 11: things down. It creates complexity. In some cases, it's not 295 00:17:57,880 --> 00:18:00,760 Speaker 11: even clear when the regulations are first coming out exactly 296 00:18:00,840 --> 00:18:03,199 Speaker 11: what they apply to and what we need to do 297 00:18:03,280 --> 00:18:05,400 Speaker 11: to comply with them, so it can be quite quite 298 00:18:05,440 --> 00:18:09,120 Speaker 11: difficult to navigate, especially for young innovative companies that don't 299 00:18:09,119 --> 00:18:10,600 Speaker 11: have a lot of resources and a lot of time 300 00:18:10,640 --> 00:18:11,880 Speaker 11: to spend on that kind of thing. 301 00:18:12,160 --> 00:18:15,560 Speaker 8: All that she says can bring some disadvantages for companies 302 00:18:15,600 --> 00:18:18,679 Speaker 8: in Europe compared to their rivals in North America. 303 00:18:19,000 --> 00:18:21,920 Speaker 11: I think in the US there's a lot more flexibility. 304 00:18:21,960 --> 00:18:25,359 Speaker 11: The consumer is potentially less protected because of those discrepancies, 305 00:18:26,600 --> 00:18:29,040 Speaker 11: but as we mentioned, there's less room for innovators to 306 00:18:29,040 --> 00:18:33,480 Speaker 11: play with. So I think there are two very different approaches, 307 00:18:33,520 --> 00:18:38,120 Speaker 11: and I think the European approach will naturally dissuade some 308 00:18:38,160 --> 00:18:39,880 Speaker 11: types of innovation from happening here. 309 00:18:40,320 --> 00:18:42,600 Speaker 8: Margaret Tavastaya takes a different view. 310 00:18:43,200 --> 00:18:47,000 Speaker 10: We're talking a lot these days about competitiveness. The paradox 311 00:18:47,160 --> 00:18:51,000 Speaker 10: is that you can have competition without having competitiveness, but 312 00:18:51,040 --> 00:18:56,560 Speaker 10: you cannot have competitiveness without competition. So really important to 313 00:18:56,720 --> 00:19:02,520 Speaker 10: maintain that strive that everybody should challenged. If you achieve 314 00:19:02,600 --> 00:19:07,360 Speaker 10: a very strong market position, it comes with responsibility. So 315 00:19:07,520 --> 00:19:09,760 Speaker 10: to some degree, I think a lot of people can 316 00:19:09,800 --> 00:19:13,040 Speaker 10: mirror themselves in what we are asking your market participants 317 00:19:13,400 --> 00:19:17,280 Speaker 10: in their own lives. If someone is rich and powerful, 318 00:19:17,480 --> 00:19:21,280 Speaker 10: they have responsibility. If someone is small with very few 319 00:19:21,320 --> 00:19:24,400 Speaker 10: means well they should have a better chance of making it. 320 00:19:25,000 --> 00:19:28,480 Speaker 8: This view has informed the flagship technology regulation for the 321 00:19:28,520 --> 00:19:31,840 Speaker 8: EU and by extension, much of the world over the 322 00:19:31,880 --> 00:19:32,800 Speaker 8: past ten years. 323 00:19:33,119 --> 00:19:36,639 Speaker 10: I think it's important here to see while some regulation 324 00:19:36,840 --> 00:19:40,360 Speaker 10: like the dinal Markets Act is opening the marketplace. 325 00:19:40,520 --> 00:19:42,399 Speaker 7: Regulation like the AI. 326 00:19:42,040 --> 00:19:45,439 Speaker 10: ADS makes AI safe to use, which means again that 327 00:19:45,520 --> 00:19:48,720 Speaker 10: it opens the market for many more use cases where 328 00:19:48,760 --> 00:19:52,200 Speaker 10: people may otherwise scare off. So I think it's important 329 00:19:52,240 --> 00:19:55,840 Speaker 10: to look at regulation and say, okay, that is market creating, 330 00:19:55,920 --> 00:19:59,960 Speaker 10: that is market opening, that is enabling innovation. And then 331 00:20:00,119 --> 00:20:04,359 Speaker 10: look at regulation where you have reporting obligations that you 332 00:20:04,440 --> 00:20:08,040 Speaker 10: may not need or that implementation have been done in 333 00:20:08,080 --> 00:20:12,000 Speaker 10: a way that was overly strict, where with new technology 334 00:20:12,200 --> 00:20:15,879 Speaker 10: or going through things, I would say, why did we 335 00:20:15,960 --> 00:20:17,919 Speaker 10: do that in such a complicated manner? 336 00:20:17,960 --> 00:20:19,400 Speaker 7: There are much easier ways to. 337 00:20:19,359 --> 00:20:21,760 Speaker 10: Do this, So I think it's really important to do that, 338 00:20:21,800 --> 00:20:25,040 Speaker 10: And the new Commission has obliged itself to go through 339 00:20:25,080 --> 00:20:28,320 Speaker 10: the entire. 340 00:20:27,320 --> 00:20:29,120 Speaker 7: Body of regulation to. 341 00:20:29,200 --> 00:20:33,439 Speaker 10: Weed out the overlaps what is unnecessary in order to 342 00:20:33,480 --> 00:20:35,360 Speaker 10: make life easier for businesses speak and. 343 00:20:35,320 --> 00:20:37,000 Speaker 1: Small station FSA. 344 00:20:37,040 --> 00:20:41,680 Speaker 8: Vasa also says that while regulation can sometimes slow tech innovation, 345 00:20:41,880 --> 00:20:45,959 Speaker 8: it can also create opportunities, and she's optimistic about the 346 00:20:46,000 --> 00:20:47,960 Speaker 8: future of Europe's startup culture. 347 00:20:48,320 --> 00:20:48,879 Speaker 7: I think it's. 348 00:20:48,760 --> 00:20:51,760 Speaker 11: Interesting we don't also talk about the opportunities that some 349 00:20:52,040 --> 00:20:55,760 Speaker 11: regulations can create. And when I say that something specifically 350 00:20:56,480 --> 00:21:00,439 Speaker 11: of climate tech, the climate tech industry, I do think 351 00:21:00,480 --> 00:21:03,520 Speaker 11: that the regulation obviously is causing a lot of headache 352 00:21:03,560 --> 00:21:05,920 Speaker 11: for some companies that have to comply, but it is 353 00:21:05,960 --> 00:21:08,720 Speaker 11: also creating a lot more opportunity and a lot more 354 00:21:08,800 --> 00:21:12,000 Speaker 11: interest for this category in Europe. I would say actually 355 00:21:12,160 --> 00:21:16,200 Speaker 11: that Europe has made a huge cultural shift, maybe over 356 00:21:16,320 --> 00:21:19,840 Speaker 11: the last five years. If I'm looking specifically at France, 357 00:21:19,920 --> 00:21:22,639 Speaker 11: ten years ago, it was definitely not a thing to 358 00:21:22,680 --> 00:21:25,840 Speaker 11: be an entrepreneur. It was almost considered crazy, why don't 359 00:21:25,880 --> 00:21:29,360 Speaker 11: you go get a real job essentially, but that has 360 00:21:29,680 --> 00:21:32,480 Speaker 11: one hundred percent change today and I think just about 361 00:21:32,520 --> 00:21:35,000 Speaker 11: everybody wants to be a founder. So I think this 362 00:21:35,119 --> 00:21:37,960 Speaker 11: cultural shift that we're seeing in France and the rest 363 00:21:37,960 --> 00:21:41,040 Speaker 11: of Europe is also catching up with It has changed 364 00:21:41,080 --> 00:21:42,520 Speaker 11: a lot of things. And when I actually look at 365 00:21:42,560 --> 00:21:45,399 Speaker 11: how people build companies in the US and in Europe, 366 00:21:45,400 --> 00:21:48,840 Speaker 11: I mean obviously structurally in Europe, things are very different. 367 00:21:48,920 --> 00:21:53,440 Speaker 11: It means something very different to build a company buttural, 368 00:21:54,040 --> 00:21:58,560 Speaker 11: the kind of mindset of entrepreneurs is almost identical. I 369 00:21:58,560 --> 00:22:01,560 Speaker 11: would say it's actually maybe become even a little bit 370 00:22:01,560 --> 00:22:04,879 Speaker 11: more balanced recently. I think with AI, we've seen the 371 00:22:05,040 --> 00:22:07,679 Speaker 11: US having to step in a bit more, deciding to 372 00:22:07,720 --> 00:22:09,520 Speaker 11: regulate a bit more now, or have to see if 373 00:22:09,520 --> 00:22:11,119 Speaker 11: that continues with the new presidency. 374 00:22:11,480 --> 00:22:15,680 Speaker 8: The u's tough approach to regulation hasn't always pleased its partners. 375 00:22:16,160 --> 00:22:20,159 Speaker 8: President Trump notably attacked the Stayre, saying she hates the 376 00:22:20,280 --> 00:22:24,040 Speaker 8: United States, perhaps worse than any person I've ever met. 377 00:22:24,359 --> 00:22:27,800 Speaker 8: Now she hands over to her successor today, Saidribeta of Spain. 378 00:22:28,040 --> 00:22:35,320 Speaker 8: With massive antitrust decisions to take against American companies Apple, Alphabets, Google, Meta, 379 00:22:35,520 --> 00:22:39,080 Speaker 8: and X, owned by Trump confidant Elon Musk, could face 380 00:22:39,240 --> 00:22:43,640 Speaker 8: billions in fines or even mandatory divestment orders. We ask 381 00:22:43,720 --> 00:22:46,560 Speaker 8: Drewbera how she hopes to deal with the new administration. 382 00:22:47,080 --> 00:22:52,480 Speaker 12: I will try to anticipate how to say cooperative relations 383 00:22:52,520 --> 00:22:55,639 Speaker 12: in this fields. I think that all American consumers and 384 00:22:55,680 --> 00:23:00,720 Speaker 12: European consumers worldwide consumers to benefit when we pay attention 385 00:23:00,920 --> 00:23:06,639 Speaker 12: on how the market does work, and I was said, 386 00:23:06,840 --> 00:23:12,400 Speaker 12: and this is quite clear that before in the previous 387 00:23:12,440 --> 00:23:16,440 Speaker 12: Trump bandit there was also some involvement, relevant involvement and 388 00:23:16,760 --> 00:23:22,960 Speaker 12: coordination between the competitition competition policies and decisions between the 389 00:23:23,000 --> 00:23:25,320 Speaker 12: two authorities. So I hope that we can work together. 390 00:23:25,600 --> 00:23:28,080 Speaker 8: As for Vestias, she may be backing away from the 391 00:23:28,080 --> 00:23:32,040 Speaker 8: front lines of antitrust enforcement, but she's hardly fading away. 392 00:23:32,280 --> 00:23:35,840 Speaker 10: Well, what the future brings, I don't know. What I 393 00:23:35,920 --> 00:23:40,359 Speaker 10: know is that I bought myself a domain, which is 394 00:23:40,520 --> 00:23:45,240 Speaker 10: dot eu because it may be that the European Commission 395 00:23:45,320 --> 00:23:45,920 Speaker 10: is done with me. 396 00:23:45,960 --> 00:23:47,760 Speaker 7: But I'm so not done with Europe. 397 00:23:50,080 --> 00:23:53,440 Speaker 2: Coming up, numbers make the world of Wall Street go around, 398 00:23:53,960 --> 00:23:57,000 Speaker 2: but the reliability of those numbers may be at risk 399 00:23:57,080 --> 00:24:00,960 Speaker 2: as we continue to cut government costs. Next on Wall 400 00:24:00,960 --> 00:24:01,720 Speaker 2: Street Week. 401 00:24:22,760 --> 00:24:27,000 Speaker 6: This is Bloomberg Wall Street Week with David Weston from 402 00:24:27,119 --> 00:24:28,040 Speaker 6: Bloomberg Radio. 403 00:24:29,320 --> 00:24:33,120 Speaker 2: This is a story about numbers here at Bloomberg. Numbers 404 00:24:33,200 --> 00:24:36,880 Speaker 2: are our business. They move markets and help us understand 405 00:24:36,880 --> 00:24:40,080 Speaker 2: the economy, and so we need them to be timely 406 00:24:40,280 --> 00:24:43,520 Speaker 2: and accurate. Our colleague Molly Smith tells us about the 407 00:24:43,640 --> 00:24:46,600 Speaker 2: risk of not getting the numbers that we need. 408 00:24:49,320 --> 00:24:52,560 Speaker 13: One of President elect Donald Trump's earliest priorities. When he 409 00:24:52,600 --> 00:24:55,440 Speaker 13: steps back into the Oval office in January, We'll be 410 00:24:55,520 --> 00:24:59,600 Speaker 13: shrinking the government by cutting regulations, spending, and headcount. 411 00:25:01,040 --> 00:25:03,600 Speaker 14: For God, this is an important day. It's the beginning 412 00:25:03,640 --> 00:25:05,920 Speaker 14: of a journey. You've heard what DOGE is all about, 413 00:25:06,000 --> 00:25:09,520 Speaker 14: the Department of Government and efficiency. It's a new thing, 414 00:25:09,880 --> 00:25:12,080 Speaker 14: and this is a new day in Washington and a 415 00:25:12,080 --> 00:25:13,000 Speaker 14: new day in America. 416 00:25:13,040 --> 00:25:15,720 Speaker 13: A slim down federal government could present a threat to 417 00:25:15,760 --> 00:25:18,840 Speaker 13: a handful of statistical agencies that have been sounding the 418 00:25:18,880 --> 00:25:22,240 Speaker 13: alarm on their cash crunch for years. The Census Bureau, 419 00:25:22,520 --> 00:25:25,400 Speaker 13: the Bureau of Economic Analysis, and the Bureau of Labor 420 00:25:25,440 --> 00:25:29,760 Speaker 13: Statistics are all under financial strain. The BLS collects and 421 00:25:29,840 --> 00:25:33,359 Speaker 13: analyzes US employment data, and it lays claim to what 422 00:25:33,600 --> 00:25:37,199 Speaker 13: could be the single most important piece of information in 423 00:25:37,240 --> 00:25:39,919 Speaker 13: the world of finance, the monthly Jobs Report. 424 00:25:40,440 --> 00:25:47,719 Speaker 15: Every year, BLS lost purchasing power right salaries for the workers. 425 00:25:47,760 --> 00:25:52,040 Speaker 15: We're going up, but the budget was not. 426 00:25:53,320 --> 00:25:57,200 Speaker 13: Erica Groschen is intimately familiar with the BLS's fight for funding. 427 00:25:57,600 --> 00:26:00,960 Speaker 13: She served as its commissioner under President Obama from twenty 428 00:26:01,000 --> 00:26:02,560 Speaker 13: thirteen to twenty seventeen. 429 00:26:02,800 --> 00:26:07,760 Speaker 15: You start almost two years beforehand, so one you've got 430 00:26:07,760 --> 00:26:10,439 Speaker 15: one budget kind of in process, and you're pulling together 431 00:26:10,520 --> 00:26:14,919 Speaker 15: the next year's budget. The department sends that budget to 432 00:26:15,040 --> 00:26:19,240 Speaker 15: OMB and from all of the departments, so the Department 433 00:26:19,280 --> 00:26:23,960 Speaker 15: of Commerce, Labor, et cetera. The OMB helps the White 434 00:26:24,000 --> 00:26:27,080 Speaker 15: House pull together what's called the President's budget. Then it 435 00:26:27,119 --> 00:26:30,120 Speaker 15: goes to the House and to the Senate, and each 436 00:26:30,160 --> 00:26:34,280 Speaker 15: of those appropriations committees winnows it down further. So it's 437 00:26:34,800 --> 00:26:39,159 Speaker 15: a long drawn out, complicated process where you're continually giving 438 00:26:39,240 --> 00:26:46,480 Speaker 15: up on ideas and necessities that you really wanted to 439 00:26:46,480 --> 00:26:47,000 Speaker 15: be funded. 440 00:26:47,359 --> 00:26:51,240 Speaker 13: The BLS, Census Bureau and the BEEA how to combine 441 00:26:51,240 --> 00:26:55,040 Speaker 13: two point two billion dollar budget last year just zero 442 00:26:55,160 --> 00:26:59,600 Speaker 13: points zero three percent of federal spending after adjusting for inflation. 443 00:27:00,160 --> 00:27:03,840 Speaker 13: BLS funding has slumped almost twenty percent since twenty ten. 444 00:27:04,200 --> 00:27:09,280 Speaker 16: Congress, unlike its predecessors in the nineteenth century, has lost sight, 445 00:27:09,680 --> 00:27:12,800 Speaker 16: in my opinion, of the value of the statistical system. 446 00:27:13,240 --> 00:27:16,680 Speaker 13: Andrew Reemer at George Washington University has been researching the 447 00:27:16,760 --> 00:27:19,919 Speaker 13: role of policy and agency funding for twenty years. 448 00:27:20,359 --> 00:27:22,480 Speaker 16: Back in the day two hundred plus years ago, the 449 00:27:22,520 --> 00:27:27,720 Speaker 16: primary customer for the data was Congress. There was no internet. 450 00:27:28,600 --> 00:27:31,240 Speaker 16: Data were if it was published, it was published way late. 451 00:27:31,359 --> 00:27:34,520 Speaker 16: No one could really use it. Our world has changed, 452 00:27:34,600 --> 00:27:38,320 Speaker 16: and so we're on Wall Street week. The first Friday 453 00:27:38,320 --> 00:27:40,879 Speaker 16: of every month, the stock market does something on the 454 00:27:40,880 --> 00:27:44,320 Speaker 16: basis of the numbers that come out on Friday morning 455 00:27:44,600 --> 00:27:46,400 Speaker 16: regarding unemployment and jobs. 456 00:27:46,760 --> 00:27:49,119 Speaker 1: The FED needs that data. 457 00:27:49,359 --> 00:27:51,400 Speaker 16: The second thing that happens when that data come out 458 00:27:51,600 --> 00:27:54,240 Speaker 16: first Friday of the month is that Chairman Powell goes 459 00:27:54,280 --> 00:27:56,080 Speaker 16: in front of the cameras and says what it means 460 00:27:56,119 --> 00:27:59,160 Speaker 16: for the FED cutting or not cutting interest rates up 461 00:27:59,160 --> 00:28:01,840 Speaker 16: the street from me as a target. Target relied on 462 00:28:02,520 --> 00:28:05,680 Speaker 16: census data to determine it's going to be in my neighborhood. 463 00:28:06,320 --> 00:28:11,320 Speaker 16: Every business, every retail business, every factory uses federal data 464 00:28:11,359 --> 00:28:13,760 Speaker 16: to figure out where it's going to invest and how 465 00:28:13,840 --> 00:28:17,080 Speaker 16: much it's going to invest. If those data are bad, 466 00:28:17,720 --> 00:28:18,879 Speaker 16: companies lose money. 467 00:28:19,359 --> 00:28:22,400 Speaker 13: The data isn't just important on paper. It has real 468 00:28:22,440 --> 00:28:25,760 Speaker 13: market consequences, which we saw play out when a weaker 469 00:28:25,760 --> 00:28:29,720 Speaker 13: than expected print helped trigger a six point four trillion 470 00:28:29,800 --> 00:28:31,600 Speaker 13: dollar global wipeout in August. 471 00:28:32,000 --> 00:28:34,160 Speaker 1: Well, here is a downside surprise. It's going to catch 472 00:28:34,200 --> 00:28:35,000 Speaker 1: the market's attention. 473 00:28:35,119 --> 00:28:39,160 Speaker 16: One hundred and fourteen thousand jobs created last month, according 474 00:28:39,160 --> 00:28:40,080 Speaker 16: to the BLS. 475 00:28:40,800 --> 00:28:44,040 Speaker 13: Michael Collins at PGIM Fixed Income sees the difference in 476 00:28:44,080 --> 00:28:46,560 Speaker 13: the quality of the data and the effect it has 477 00:28:46,640 --> 00:28:48,800 Speaker 13: on how he makes his investment decisions. 478 00:28:49,200 --> 00:28:53,440 Speaker 17: The data is probably less reliable today than it's been, 479 00:28:53,520 --> 00:28:56,240 Speaker 17: But that being said, we have so much more data 480 00:28:56,680 --> 00:28:58,600 Speaker 17: right than we've ever had. I mean, you think back, 481 00:28:58,840 --> 00:29:01,040 Speaker 17: you know, the nineteen to forties, fifties and sixties, and 482 00:29:01,040 --> 00:29:03,400 Speaker 17: you look at the old newspaper clippings, I mean the 483 00:29:03,720 --> 00:29:07,000 Speaker 17: limited amount and the and the poor timeliness of the data. 484 00:29:07,480 --> 00:29:10,160 Speaker 17: People are still managing money and making you know, big 485 00:29:10,200 --> 00:29:14,360 Speaker 17: investments on those releases. Today we're actually, you know, have 486 00:29:14,440 --> 00:29:19,280 Speaker 17: the benefit of having so much macro data, micro data, 487 00:29:19,960 --> 00:29:23,600 Speaker 17: uh you know, contemporaneous data, leading data, lagging data, and 488 00:29:23,640 --> 00:29:26,680 Speaker 17: so we have the flexibility to put it all together 489 00:29:27,040 --> 00:29:29,280 Speaker 17: and try to, you know, paint a bigger picture. And 490 00:29:29,320 --> 00:29:31,800 Speaker 17: we're really looking, you know, at each piece of data 491 00:29:31,880 --> 00:29:34,600 Speaker 17: as a as a component to the bigger picture. 492 00:29:34,600 --> 00:29:36,800 Speaker 1: Does it support our thesis or. 493 00:29:36,760 --> 00:29:39,760 Speaker 17: Does it you know, make us think twice about our 494 00:29:39,800 --> 00:29:42,960 Speaker 17: thesis and maybe pause before we put on a trade 495 00:29:43,040 --> 00:29:45,680 Speaker 17: or an investment that that will benefit from from from 496 00:29:45,720 --> 00:29:47,840 Speaker 17: our view, and by the time you get the revisions 497 00:29:48,040 --> 00:29:50,840 Speaker 17: right that it is so backward looking that it doesn't 498 00:29:50,880 --> 00:29:53,760 Speaker 17: reflect market behavior going forward. 499 00:29:53,840 --> 00:29:53,920 Speaker 3: Right. 500 00:29:54,000 --> 00:29:58,640 Speaker 17: The markets are very forward looking beasts, as you know, Uh, 501 00:29:58,680 --> 00:30:02,120 Speaker 17: they will take each data point and try to extrapolate 502 00:30:03,040 --> 00:30:06,400 Speaker 17: the trend up or down on any of these different 503 00:30:06,600 --> 00:30:09,920 Speaker 17: indicators or series. So when you do a revision, all 504 00:30:09,960 --> 00:30:13,400 Speaker 17: it does is kind of reset maybe the level, but 505 00:30:13,440 --> 00:30:14,240 Speaker 17: it doesn't really. 506 00:30:14,160 --> 00:30:15,640 Speaker 1: Change the forward looking trend. 507 00:30:16,320 --> 00:30:19,600 Speaker 17: So either way, the data to investors like us, long 508 00:30:19,680 --> 00:30:21,000 Speaker 17: term investors. 509 00:30:20,760 --> 00:30:22,680 Speaker 1: Are not that important. 510 00:30:23,320 --> 00:30:25,800 Speaker 17: What's important is how the markets are going to respond 511 00:30:26,120 --> 00:30:29,320 Speaker 17: to activity in the future. So we're always trying to 512 00:30:29,320 --> 00:30:32,600 Speaker 17: stay obviously one step ahead of the data, right, to 513 00:30:32,640 --> 00:30:35,640 Speaker 17: try to take the data and again try to paint 514 00:30:35,640 --> 00:30:40,520 Speaker 17: a picture of the direction of these different indicators, and 515 00:30:40,560 --> 00:30:43,480 Speaker 17: we will certainly make investments and put on trades and 516 00:30:43,520 --> 00:30:46,960 Speaker 17: put on positions that we think are consistent with our 517 00:30:47,080 --> 00:30:50,560 Speaker 17: view on which way the data is pointing. If you 518 00:30:50,600 --> 00:30:54,320 Speaker 17: get a revision, by then it's real, it's really moot. 519 00:30:54,640 --> 00:30:58,360 Speaker 13: In August of this year, the BLS found itself unprepared 520 00:30:58,480 --> 00:31:01,800 Speaker 13: to handle a delay in releasing a scheduled revision to 521 00:31:01,880 --> 00:31:05,280 Speaker 13: its jobs data. The figures were finally released about thirty 522 00:31:05,320 --> 00:31:07,920 Speaker 13: minutes after they were supposed to come out, but not 523 00:31:08,000 --> 00:31:11,040 Speaker 13: before a handful of firms, including B and P, Prryba, 524 00:31:11,240 --> 00:31:14,400 Speaker 13: and Mazuo got the numbers because they called the BLS 525 00:31:14,400 --> 00:31:17,240 Speaker 13: and asked. The follout from the glitch was made worse 526 00:31:17,280 --> 00:31:21,360 Speaker 13: by the massive revision, highlighting another issue plaguing the BLS 527 00:31:21,600 --> 00:31:25,720 Speaker 13: and other statistical agencies, declining response rates to surveys. 528 00:31:26,240 --> 00:31:30,240 Speaker 15: Because response rates are falling, then you're not actually getting 529 00:31:30,280 --> 00:31:35,760 Speaker 15: sixty thousand households every month, you're getting substantially less than that, 530 00:31:36,320 --> 00:31:43,160 Speaker 15: and so you're really missing out on smaller groups, racial groups, 531 00:31:44,200 --> 00:31:49,480 Speaker 15: industry groups, veterans, etc. If you want to know what's 532 00:31:49,520 --> 00:31:53,960 Speaker 15: going on with the various groups, the information just won't 533 00:31:54,000 --> 00:31:57,600 Speaker 15: be as good. Response rates are falling for all surveys 534 00:31:57,800 --> 00:32:03,960 Speaker 15: all across the world, all kinds of surveys. There's what it's. 535 00:32:03,400 --> 00:32:04,160 Speaker 7: Called in the field. 536 00:32:04,200 --> 00:32:06,760 Speaker 15: It's called survey fatigue. So people get a lot of 537 00:32:06,800 --> 00:32:10,280 Speaker 15: requests and when it first started, there were very few surveys. 538 00:32:10,320 --> 00:32:13,840 Speaker 15: And another factor in all of this has been the 539 00:32:13,880 --> 00:32:15,440 Speaker 15: demonization of government. 540 00:32:16,120 --> 00:32:18,520 Speaker 13: Grosshan says the lack of trust in the government and 541 00:32:18,560 --> 00:32:21,920 Speaker 13: its data creates a feedback loop of low response rates 542 00:32:21,960 --> 00:32:23,320 Speaker 13: and inaccurate data. 543 00:32:23,400 --> 00:32:30,240 Speaker 15: So a conversion of the top ranks of the staff 544 00:32:30,840 --> 00:32:37,959 Speaker 15: in the statistical agencies to political appointees threatens to undermine 545 00:32:38,040 --> 00:32:42,760 Speaker 15: trust in the agencies. And when you undermine trust, you 546 00:32:42,840 --> 00:32:45,080 Speaker 15: interfere with their ability to fulfill their mission. 547 00:32:46,160 --> 00:32:48,800 Speaker 16: If you had come here a few years ago, these 548 00:32:48,800 --> 00:32:50,000 Speaker 16: streets didn't exist it. 549 00:32:50,160 --> 00:32:53,680 Speaker 13: Zach Brandon and Aaron Olver saw firsthand how data from 550 00:32:53,680 --> 00:32:58,800 Speaker 13: statistical agencies turned into cash for their hometown of Madison, Wisconsin, but. 551 00:32:58,800 --> 00:33:02,240 Speaker 18: Really start earlier in two thousand and five, two thousand 552 00:33:02,240 --> 00:33:05,880 Speaker 18: and four. But the report that I think set the 553 00:33:05,920 --> 00:33:08,840 Speaker 18: groundwork for what came out of the Chips Act was 554 00:33:08,960 --> 00:33:11,840 Speaker 18: this the study that came from Brookies in twenty nineteen. 555 00:33:12,000 --> 00:33:15,400 Speaker 18: They looked at population, they looked at types of jobs, 556 00:33:15,440 --> 00:33:18,719 Speaker 18: they looked at share of bachelor's degrees, They looked at 557 00:33:19,160 --> 00:33:21,920 Speaker 18: stem R and D investments, they looked at. 558 00:33:21,840 --> 00:33:23,120 Speaker 1: PhDs per capita. 559 00:33:23,720 --> 00:33:26,360 Speaker 18: So all that is federal data that's collected, and so 560 00:33:26,400 --> 00:33:32,240 Speaker 18: those data sets become important to put together the composite. 561 00:33:31,080 --> 00:33:35,479 Speaker 13: Fifteen Wisconsin companies specializing in healthcare technology as well as 562 00:33:35,560 --> 00:33:39,280 Speaker 13: higher education institutions came together last year to seek the 563 00:33:39,320 --> 00:33:42,360 Speaker 13: designation as a so called tech hub under the Chips 564 00:33:42,360 --> 00:33:45,920 Speaker 13: and Science Act. The state earned forty nine million dollars 565 00:33:45,920 --> 00:33:49,440 Speaker 13: in federal funding, which is expected to create nine billion 566 00:33:49,520 --> 00:33:53,600 Speaker 13: dollars worth of economic development and more than thirty thousand jobs. 567 00:33:53,920 --> 00:33:57,600 Speaker 18: There's sexy headlines and then there's discernible data, right, and 568 00:33:57,640 --> 00:33:59,960 Speaker 18: so you have to look past the headlines, and also 569 00:34:00,160 --> 00:34:03,280 Speaker 18: to look past scale, because if you just looked at size, 570 00:34:03,320 --> 00:34:04,920 Speaker 18: if you just said, you know, well, who has the 571 00:34:05,000 --> 00:34:07,760 Speaker 18: most of these employees, you would just stay in those 572 00:34:07,800 --> 00:34:10,600 Speaker 18: five cities, you know, you'd go to New York wherever 573 00:34:10,640 --> 00:34:13,440 Speaker 18: there was scale. But what you're really looking for is 574 00:34:13,640 --> 00:34:15,680 Speaker 18: a bit of a needle in the haystack. You're looking 575 00:34:15,680 --> 00:34:18,600 Speaker 18: for density. What you're looking for is where is this 576 00:34:18,640 --> 00:34:21,400 Speaker 18: bubbling up now? And that if you could add an 577 00:34:21,400 --> 00:34:23,880 Speaker 18: accelerant to it, So where has the spark occurred? And 578 00:34:23,880 --> 00:34:26,280 Speaker 18: if we could add an accelerant, where will it catch fire? 579 00:34:26,480 --> 00:34:29,719 Speaker 18: What are the solutions to global challenges that the US 580 00:34:29,840 --> 00:34:33,600 Speaker 18: can develop? So health being one of those, So personalized medicine, 581 00:34:34,000 --> 00:34:36,120 Speaker 18: thinking about BioHealth is going to be a big part 582 00:34:36,160 --> 00:34:38,560 Speaker 18: of the future economy in this country. 583 00:34:39,080 --> 00:34:41,640 Speaker 1: So where are those companies? Where does that research exist? 584 00:34:41,640 --> 00:34:44,200 Speaker 18: And I think that's what you saw in this technology 585 00:34:44,239 --> 00:34:47,320 Speaker 18: hub that's developed within Wisconsin, is that if you start 586 00:34:47,320 --> 00:34:49,839 Speaker 18: in Milwaukee and you make your way to Madison, you've 587 00:34:49,840 --> 00:34:53,080 Speaker 18: got more than one hundred companies that touch health in 588 00:34:53,160 --> 00:34:55,560 Speaker 18: some way. And some of the largest companies in the 589 00:34:55,600 --> 00:34:59,560 Speaker 18: world that are doing health care, health delivery, health research, 590 00:35:00,080 --> 00:35:03,600 Speaker 18: health R and D happen to be based in this corridor. 591 00:35:03,840 --> 00:35:06,200 Speaker 1: But if you weren't looking at data, you wouldn't have 592 00:35:06,280 --> 00:35:06,719 Speaker 1: noticed that. 593 00:35:07,520 --> 00:35:11,040 Speaker 13: Brandon says that despite his city's rapid tech growth, it 594 00:35:11,080 --> 00:35:14,680 Speaker 13: could stumble without federal support, and other cities could miss 595 00:35:14,719 --> 00:35:19,200 Speaker 13: out on future investment if statistical agencies continue to lose resources. 596 00:35:19,600 --> 00:35:25,600 Speaker 1: It's really hard to be the dominant innovation economy in 597 00:35:25,640 --> 00:35:29,000 Speaker 1: the world. It's not that hard to undo. 598 00:35:28,760 --> 00:35:33,040 Speaker 18: It, right, and slowly ticking away, knocking off pieces of 599 00:35:33,080 --> 00:35:35,920 Speaker 18: what got us here will set us on us certainly 600 00:35:36,000 --> 00:35:38,480 Speaker 18: on a downward trajectory. And so if you're worried about 601 00:35:38,480 --> 00:35:42,400 Speaker 18: global competitiveness, if you're worried about understanding China's rise and 602 00:35:42,440 --> 00:35:45,320 Speaker 18: innovation and matching that against the US rise and innovation, 603 00:35:45,760 --> 00:35:48,000 Speaker 18: you need data to be able to understand what the 604 00:35:48,040 --> 00:35:48,839 Speaker 18: future looks like. 605 00:35:49,200 --> 00:35:52,560 Speaker 13: Understanding that future as best we can will always be valuable, 606 00:35:52,760 --> 00:35:55,160 Speaker 13: no matter whose data we use to do it. So, 607 00:35:55,239 --> 00:35:58,040 Speaker 13: if the government can't survey and put out its own figures, 608 00:35:58,360 --> 00:36:01,760 Speaker 13: can the private sector pick up the slack? Erica Groschen says, 609 00:36:01,960 --> 00:36:02,920 Speaker 13: It's not so simple. 610 00:36:03,280 --> 00:36:07,480 Speaker 15: It's a huge opportunity, but it's not a substitute. Why 611 00:36:08,040 --> 00:36:11,960 Speaker 15: a private sector company would never have the incentive to 612 00:36:12,080 --> 00:36:16,560 Speaker 15: create the long history of data that the statistical agencies 613 00:36:16,640 --> 00:36:20,120 Speaker 15: do that really help you to put current conditions in perspective. 614 00:36:20,680 --> 00:36:24,200 Speaker 15: They don't have the incentive to be as transparent. 615 00:36:24,800 --> 00:36:28,400 Speaker 13: For now, government data and private surveys continue to go 616 00:36:28,520 --> 00:36:32,080 Speaker 13: hand in hand, but no matter who generates them, good 617 00:36:32,160 --> 00:36:36,200 Speaker 13: numbers will always cost money. The question is do we 618 00:36:36,280 --> 00:36:42,840 Speaker 13: value them enough to keep paying the bill. 619 00:36:40,800 --> 00:36:42,799 Speaker 2: That does it for us? Here at Wall Street Week, 620 00:36:42,960 --> 00:36:45,600 Speaker 2: I'm David Weston. This is Bloomberg. See you next week 621 00:36:45,640 --> 00:37:02,480 Speaker 2: for more stories of capitalism.