1 00:00:02,480 --> 00:00:14,000 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. 2 00:00:18,160 --> 00:00:21,919 Speaker 2: Hello and welcome to another episode of the Odd Lots podcast. 3 00:00:22,040 --> 00:00:24,440 Speaker 3: I'm Joe Wisenthal and I'm Tracy Allaway. 4 00:00:24,640 --> 00:00:28,240 Speaker 2: Tracy the number. One of the main things I'm watching 5 00:00:28,320 --> 00:00:32,920 Speaker 2: right now are those container shipping numbers that, at least 6 00:00:32,960 --> 00:00:35,559 Speaker 2: looking out at the next few weeks, it looks like 7 00:00:35,680 --> 00:00:38,600 Speaker 2: lots of actual orders are being canceled and there's the 8 00:00:38,720 --> 00:00:43,920 Speaker 2: risk of material shortage of things from China emerging in 9 00:00:44,000 --> 00:00:45,279 Speaker 2: a fairly short period of time. 10 00:00:45,560 --> 00:00:48,080 Speaker 3: Yeah, I think we're kind of getting to the rubber 11 00:00:48,200 --> 00:00:52,360 Speaker 3: meets the road portion of the tariffs, right. So everyone 12 00:00:52,440 --> 00:00:54,440 Speaker 3: was talking about the potential of some sort of trade 13 00:00:54,480 --> 00:00:57,440 Speaker 3: restrictions going into this year because we knew that Trump 14 00:00:57,520 --> 00:00:59,440 Speaker 3: had won the election and he wanted to do some 15 00:00:59,480 --> 00:01:02,240 Speaker 3: of the stuff. And so what we saw broadly for 16 00:01:02,320 --> 00:01:04,720 Speaker 3: the first quarter was people trying to get ahead of that, 17 00:01:04,880 --> 00:01:08,800 Speaker 3: so building up their inventories, ordering a bunch of stuff 18 00:01:09,000 --> 00:01:11,720 Speaker 3: before some of those restrictions were expected to get in. 19 00:01:12,160 --> 00:01:14,880 Speaker 3: But of course that can only last so long. And 20 00:01:15,280 --> 00:01:19,600 Speaker 3: on Liberation Day, April second, Trump unveiled these really quite sweeping, 21 00:01:19,680 --> 00:01:22,200 Speaker 3: quite dramatic tariffs, as we all know by now, Yes, 22 00:01:22,360 --> 00:01:25,640 Speaker 3: and so I think people are starting to get concerned 23 00:01:25,680 --> 00:01:28,680 Speaker 3: that like now is when we're really going to begin 24 00:01:28,760 --> 00:01:30,039 Speaker 3: to see some of that impact. 25 00:01:30,240 --> 00:01:30,640 Speaker 1: That's right. 26 00:01:30,680 --> 00:01:33,639 Speaker 2: So, by the way we are recording this April twenty third, 27 00:01:33,880 --> 00:01:37,760 Speaker 2: it's two to thirty six pm. Yesterday we got a 28 00:01:37,800 --> 00:01:40,360 Speaker 2: little bit of softening and Trump saying, oh, it's not 29 00:01:40,360 --> 00:01:42,440 Speaker 2: gonna be one hundred and forty five. But then today 30 00:01:43,000 --> 00:01:44,800 Speaker 2: we got stuff there's like, there's not going to be 31 00:01:44,880 --> 00:01:48,040 Speaker 2: any unilateral concessions. We don't really know. There has been 32 00:01:48,040 --> 00:01:51,360 Speaker 2: this little softening of the tone. But look, one point 33 00:01:51,440 --> 00:01:55,160 Speaker 2: of tariffs is to reduce a reliance on China, to 34 00:01:55,800 --> 00:01:59,040 Speaker 2: partially decouple, et cetera. But then when you look at 35 00:01:59,040 --> 00:02:01,960 Speaker 2: the reality of okay, well that's what we're doing. We're decoupling, 36 00:02:02,000 --> 00:02:05,600 Speaker 2: we're buying less, it looks like it's coming very sharp 37 00:02:05,720 --> 00:02:08,200 Speaker 2: and fast, and perhaps to a degree that it's not 38 00:02:08,320 --> 00:02:11,400 Speaker 2: even really about inflation per se. Right, because I'll let 39 00:02:11,440 --> 00:02:12,799 Speaker 2: you know, a year ago people were talking about this 40 00:02:12,840 --> 00:02:15,720 Speaker 2: in the abstract, what does the fedgod do inflation? People 41 00:02:15,720 --> 00:02:17,520 Speaker 2: are talking about empty shelves of a lot of things. 42 00:02:17,880 --> 00:02:20,280 Speaker 3: Well, I think this is still a big question, Like 43 00:02:20,639 --> 00:02:22,400 Speaker 3: I think there is some of this that could be 44 00:02:22,480 --> 00:02:25,880 Speaker 3: attenuated by companies just choosing to raise their prices and 45 00:02:25,960 --> 00:02:29,440 Speaker 3: maybe not order as many different types of things. But yeah, 46 00:02:29,560 --> 00:02:32,160 Speaker 3: we are seeing some analysts start to talk about the 47 00:02:32,200 --> 00:02:35,720 Speaker 3: possibility of empty shelves, and in fact, we're going. 48 00:02:35,560 --> 00:02:37,680 Speaker 2: To speak to one now, that's right, we have the 49 00:02:37,720 --> 00:02:40,040 Speaker 2: perfect guest. We are going to be speaking with Anna Wong. 50 00:02:40,160 --> 00:02:44,320 Speaker 2: She is our chief US economist at Bloomberg Economics. Thank 51 00:02:44,360 --> 00:02:48,040 Speaker 2: you for joining us. Anna, you tweeted about empty shelves 52 00:02:48,919 --> 00:02:51,320 Speaker 2: in the sort of imminent term. What is the data 53 00:02:51,360 --> 00:02:54,359 Speaker 2: you're looking at and when would you expect to see 54 00:02:54,600 --> 00:02:56,560 Speaker 2: start people really start noticing it. 55 00:02:57,000 --> 00:03:01,400 Speaker 4: Yeah, so and Tracy happy to be here again. So so, 56 00:03:02,040 --> 00:03:06,320 Speaker 4: you know, many people have been talking about how based 57 00:03:06,320 --> 00:03:10,040 Speaker 4: on the cancelation shipment and right now we have, as 58 00:03:10,080 --> 00:03:15,799 Speaker 4: you mentioned, we have seen plummeting container bookings, and already 59 00:03:16,000 --> 00:03:19,320 Speaker 4: in April, the first two weeks of April, we have 60 00:03:19,440 --> 00:03:25,640 Speaker 4: seen weekly imports data from China to US, even from 61 00:03:25,760 --> 00:03:31,959 Speaker 4: South Korea to US dropping very quickly. And and typically 62 00:03:32,360 --> 00:03:38,360 Speaker 4: when we think about holidays season retail, which is which 63 00:03:38,440 --> 00:03:43,760 Speaker 4: starts really with Halloween, uh in October, the US company 64 00:03:43,840 --> 00:03:47,560 Speaker 4: should be planning right now, right usually they plan uh 65 00:03:47,640 --> 00:03:50,560 Speaker 4: in the spring and they and then they start putting 66 00:03:50,560 --> 00:03:55,040 Speaker 4: in the orders now, especially for items like toys and 67 00:03:55,080 --> 00:04:00,760 Speaker 4: apparels and electronics longle time and so in in in 68 00:04:00,800 --> 00:04:06,520 Speaker 4: the summer, basically throughout June, July, August is when China 69 00:04:06,520 --> 00:04:10,600 Speaker 4: should be shipping these things to us. So we are 70 00:04:10,720 --> 00:04:14,560 Speaker 4: right in this period where all this planning has to happen. 71 00:04:14,680 --> 00:04:20,120 Speaker 4: Yet this is also when tariffs are implemented. So as 72 00:04:20,160 --> 00:04:27,120 Speaker 4: a result, the basically the inventory for Christmas, for Halloween 73 00:04:27,400 --> 00:04:31,520 Speaker 4: is already being disrupted right now. So even though it's 74 00:04:31,839 --> 00:04:36,160 Speaker 4: still many months away, and you know, with the ninety 75 00:04:36,279 --> 00:04:40,520 Speaker 4: day delay on the reciprocal tariffs, we are not you know, 76 00:04:41,000 --> 00:04:45,480 Speaker 4: it's not until July ninth where we have US firms 77 00:04:45,520 --> 00:04:50,120 Speaker 4: have better clarity on whether these tariffs fees of the 78 00:04:50,240 --> 00:04:54,760 Speaker 4: other country would be raised. And so basically it exactly 79 00:04:54,839 --> 00:04:58,719 Speaker 4: fell on this planning and shipping and producing period for 80 00:04:58,839 --> 00:05:02,880 Speaker 4: holiday season. So I think this is one reason why 81 00:05:03,120 --> 00:05:06,040 Speaker 4: just based on the high frequency data we have on 82 00:05:06,560 --> 00:05:10,039 Speaker 4: the volumes, on the quantities, the dropping of it, and 83 00:05:10,360 --> 00:05:15,440 Speaker 4: also just the you know, the timing of this this period, 84 00:05:15,520 --> 00:05:18,760 Speaker 4: it suggests that there's a high probability that we may 85 00:05:18,800 --> 00:05:22,760 Speaker 4: be seeing some empty shells in the holiday season, and 86 00:05:22,800 --> 00:05:29,440 Speaker 4: even with less varieties, I consider I basically consider that 87 00:05:29,640 --> 00:05:33,040 Speaker 4: part of the empty shelves just having less varieties. 88 00:05:34,040 --> 00:05:37,359 Speaker 3: So talk to us about prices here, because you know, 89 00:05:37,480 --> 00:05:40,160 Speaker 3: I sort of mentioned in the intro that one thing 90 00:05:40,200 --> 00:05:43,440 Speaker 3: you could do if you're a retailer who isn't importing 91 00:05:43,560 --> 00:05:46,280 Speaker 3: as much as you used to, you could just raise 92 00:05:46,279 --> 00:05:49,600 Speaker 3: your prices massively, right in order to try to offset 93 00:05:49,720 --> 00:05:52,479 Speaker 3: some of the loss of supply. So this kind of 94 00:05:52,480 --> 00:05:55,080 Speaker 3: goes back to the old price over volume theme that 95 00:05:55,120 --> 00:05:58,839 Speaker 3: we saw during the COVID pandemic. Is that an option 96 00:05:59,040 --> 00:06:01,200 Speaker 3: here or is it the case that you think the 97 00:06:01,320 --> 00:06:04,880 Speaker 3: uncertainty is so high that people just aren't ordering pretty 98 00:06:04,960 --> 00:06:05,520 Speaker 3: much anything. 99 00:06:07,120 --> 00:06:09,880 Speaker 4: Yeah, So we can look at some of the data, 100 00:06:09,880 --> 00:06:13,800 Speaker 4: because we already have data up to March for impro 101 00:06:13,880 --> 00:06:19,719 Speaker 4: prices PPI and CPI, and that covers basically two months 102 00:06:19,760 --> 00:06:24,119 Speaker 4: of the trade war, where US raise tariffs on China 103 00:06:24,120 --> 00:06:27,880 Speaker 4: by ten percent in February and then another ten percent 104 00:06:28,400 --> 00:06:31,719 Speaker 4: in March. That's already many times larger than in the 105 00:06:31,760 --> 00:06:34,440 Speaker 4: first trade war. So what we are seeing in the 106 00:06:34,920 --> 00:06:39,120 Speaker 4: in prices so far indicate that number one, most of 107 00:06:39,160 --> 00:06:44,520 Speaker 4: the Chinese tariffs have indeed been fully born by on 108 00:06:44,560 --> 00:06:49,520 Speaker 4: the US side, by you know whoever. But just we 109 00:06:49,560 --> 00:06:53,640 Speaker 4: can see that it's mostly one hundred percent passed through 110 00:06:53,880 --> 00:06:57,240 Speaker 4: at the border to US importers. This is with two 111 00:06:57,279 --> 00:07:01,320 Speaker 4: months of data. And second look at PPI data. This 112 00:07:01,400 --> 00:07:04,880 Speaker 4: is the next stage. Right once the US importers bring 113 00:07:05,000 --> 00:07:10,840 Speaker 4: in those products, they sell those products to intermediate firms 114 00:07:10,960 --> 00:07:16,080 Speaker 4: or even to know wholesale firms, to distributors. So the 115 00:07:16,080 --> 00:07:19,480 Speaker 4: next stage is looking at PPI. And we also have 116 00:07:19,720 --> 00:07:26,600 Speaker 4: seen a positive correlation between tariff shots across products in 117 00:07:26,720 --> 00:07:32,160 Speaker 4: February and March versus PPI increase in March. So there 118 00:07:32,240 --> 00:07:39,000 Speaker 4: is also some small pass through to PPI prices, but 119 00:07:39,120 --> 00:07:44,840 Speaker 4: not one hundred percent. So finally from PPI to CPI, 120 00:07:44,920 --> 00:07:49,800 Speaker 4: there you still have that big segment of wholesaler distributors 121 00:07:50,280 --> 00:07:54,560 Speaker 4: and this is where that passed through broke down. We 122 00:07:54,680 --> 00:07:58,400 Speaker 4: have not seen much evidence yet that it's showing up 123 00:07:58,560 --> 00:08:02,240 Speaker 4: in consumer prices. And in fact, if you plot a 124 00:08:02,320 --> 00:08:06,200 Speaker 4: similar scatter plot where you have on the vertical axis 125 00:08:06,440 --> 00:08:11,480 Speaker 4: the CPI change in March versus on the x axis 126 00:08:11,520 --> 00:08:15,520 Speaker 4: the tariff increased by product, you actually would see negative 127 00:08:15,560 --> 00:08:19,840 Speaker 4: correlation and meaning that the more China exposed it is 128 00:08:19,880 --> 00:08:23,120 Speaker 4: to that to in that good is actually the more 129 00:08:23,160 --> 00:08:27,080 Speaker 4: deflation you've seen. And we have seen that negative correlation 130 00:08:27,480 --> 00:08:30,760 Speaker 4: held over the last three months as well as for 131 00:08:30,920 --> 00:08:34,520 Speaker 4: most of last year, which suggests that there is actually 132 00:08:34,520 --> 00:08:39,320 Speaker 4: another major part to this whole trade war price pass 133 00:08:39,360 --> 00:08:43,440 Speaker 4: through story, which is China is going through a deflationary spiral, 134 00:08:43,840 --> 00:08:47,880 Speaker 4: and domestic prices in China is very very competitive right now. 135 00:08:48,800 --> 00:08:52,839 Speaker 4: So that's one element, and I think broadly these three 136 00:08:53,360 --> 00:08:57,679 Speaker 4: type of prices is consistent with what we are seeing 137 00:08:57,720 --> 00:09:01,079 Speaker 4: also in soft data, so in recent in recent days, 138 00:09:01,080 --> 00:09:05,920 Speaker 4: we have seen from Richmond FED, Philly FED, and various 139 00:09:06,040 --> 00:09:12,480 Speaker 4: manufacturing survey data that shows price paid have surged, yet 140 00:09:13,040 --> 00:09:17,120 Speaker 4: price received, even though it also has increased, has not 141 00:09:17,320 --> 00:09:22,800 Speaker 4: increased even to the amount of the price paid, which 142 00:09:22,840 --> 00:09:26,800 Speaker 4: suggests that a lot of the at least up to March, 143 00:09:27,120 --> 00:09:30,480 Speaker 4: the evidence is that much of the tariffs number one 144 00:09:30,960 --> 00:09:34,120 Speaker 4: has been born by the US side number two have 145 00:09:34,280 --> 00:09:37,680 Speaker 4: been absorbed through a compression of profit margins. 146 00:09:38,440 --> 00:09:41,560 Speaker 3: Yeah, I think this is really important and also basically 147 00:09:41,600 --> 00:09:44,000 Speaker 3: the big question here is how much of that cost 148 00:09:44,120 --> 00:09:47,240 Speaker 3: passed through actually makes it down to consumers. And I'm 149 00:09:47,240 --> 00:09:50,400 Speaker 3: so glad Anna brought up the wholesalers because they're sort 150 00:09:50,400 --> 00:09:54,800 Speaker 3: of the forgotten, the forgotten element of price passed through 151 00:09:55,000 --> 00:09:57,160 Speaker 3: in all of this. And obviously they have their own 152 00:09:57,200 --> 00:10:00,880 Speaker 3: profit margins to worry about, but if they all absorbing 153 00:10:01,040 --> 00:10:03,560 Speaker 3: potentially some of the costs, and that does add a 154 00:10:03,559 --> 00:10:06,080 Speaker 3: sort of extra cushion on for consumers. 155 00:10:06,120 --> 00:10:09,599 Speaker 2: By the way, yesterday April twenty second, in the newsletter, 156 00:10:09,679 --> 00:10:13,640 Speaker 2: I spotlighted this gap between prices received and prices paid 157 00:10:13,679 --> 00:10:16,640 Speaker 2: in some of those regional FED surveys, and Tracy was 158 00:10:16,760 --> 00:10:19,080 Speaker 2: kind enough to draw teeth on it to make it 159 00:10:19,120 --> 00:10:21,360 Speaker 2: look like the jaws of death that are coming for 160 00:10:21,440 --> 00:10:25,520 Speaker 2: your profit margins. And Okay, maybe the prices don't get 161 00:10:25,559 --> 00:10:29,760 Speaker 2: passed on to consumers fully, or maybe it's just partially 162 00:10:29,880 --> 00:10:33,560 Speaker 2: prices received just go up a lot. Tracy described it 163 00:10:33,640 --> 00:10:38,600 Speaker 2: as cushion. But what does economics tell us about when 164 00:10:38,679 --> 00:10:43,280 Speaker 2: profit margins get clobbered to profit margins go negative? What 165 00:10:43,360 --> 00:10:46,040 Speaker 2: does that do to the impulse for investment in hiring 166 00:10:46,160 --> 00:10:47,640 Speaker 2: and then the possibility of layoffs? 167 00:10:49,080 --> 00:10:53,640 Speaker 4: Yeah, exactly, that is the key question. And when profit 168 00:10:53,720 --> 00:10:58,439 Speaker 4: margins are squeezed, it means the primary burden of adjustment 169 00:10:58,520 --> 00:11:03,800 Speaker 4: to tariffs fall on stock prices and also on unemployment 170 00:11:04,120 --> 00:11:11,000 Speaker 4: and capex. So we're expecting investment to significantly slow down 171 00:11:11,320 --> 00:11:14,120 Speaker 4: in the second half of this year and responds to 172 00:11:14,240 --> 00:11:20,600 Speaker 4: lower profit. Right, everything on the investment side respond to profits, right, 173 00:11:21,520 --> 00:11:28,600 Speaker 4: And also then ultimately on employment and real wages will adjust. 174 00:11:28,640 --> 00:11:32,840 Speaker 4: So on employment we are expecting it to go up 175 00:11:32,920 --> 00:11:34,720 Speaker 4: to four point eight percent by the end of this 176 00:11:34,840 --> 00:11:38,200 Speaker 4: year and peaking at five point three percent next year, 177 00:11:38,720 --> 00:11:42,959 Speaker 4: and real wages will fall. And you know services sector 178 00:11:43,240 --> 00:11:48,960 Speaker 4: account for about two thirds of the core PCE basket. 179 00:11:49,440 --> 00:11:53,000 Speaker 4: And so when you think about how you know, at 180 00:11:53,040 --> 00:11:55,360 Speaker 4: the end of the day, maybe a year from now, 181 00:11:55,600 --> 00:11:59,880 Speaker 4: what we will see is that there's basically a reality 182 00:12:00,320 --> 00:12:04,680 Speaker 4: between prices, right, so goods prices probably will be higher 183 00:12:05,160 --> 00:12:08,319 Speaker 4: on a level basis, but at the same time, real wages, 184 00:12:08,440 --> 00:12:13,720 Speaker 4: which drives services costs, will come down significantly. And you know, 185 00:12:13,840 --> 00:12:18,720 Speaker 4: some of the most demand elastic sectors in the economy 186 00:12:19,200 --> 00:12:24,720 Speaker 4: are travel related and with elasticity of demand that's higher 187 00:12:24,760 --> 00:12:28,040 Speaker 4: than one, and also to income as well, to income 188 00:12:28,080 --> 00:12:31,559 Speaker 4: that's higher than one. That means that when the economy 189 00:12:31,600 --> 00:12:34,880 Speaker 4: slows down, we should be seeing a lot of disinflationary 190 00:12:34,920 --> 00:12:39,240 Speaker 4: pressure coming from the services sector, and in fact, I 191 00:12:39,280 --> 00:12:42,360 Speaker 4: think we already have seen some early clues of that 192 00:12:42,400 --> 00:12:48,440 Speaker 4: in the March CPI report. Hotels, car rentals, airfares have 193 00:12:48,559 --> 00:12:53,679 Speaker 4: all been plummeting, seeing deflation actually in March, and even 194 00:12:53,720 --> 00:12:56,200 Speaker 4: in the Sep. Five hundred you see that it's the 195 00:12:56,280 --> 00:12:59,600 Speaker 4: airlines stock prices that have been hit the hardest because 196 00:12:59,640 --> 00:13:03,160 Speaker 4: that's where the discretionary spending will be pulling back. 197 00:13:19,000 --> 00:13:21,839 Speaker 3: Let me just ask one question. One of the frustrations 198 00:13:21,840 --> 00:13:25,040 Speaker 3: that pretty much everyone operating in the economy right now 199 00:13:25,200 --> 00:13:28,520 Speaker 3: seems to have, including podcasters, by the way, is there 200 00:13:28,559 --> 00:13:31,160 Speaker 3: is so much uncertainty and the headlines are coming out 201 00:13:31,360 --> 00:13:34,199 Speaker 3: fast and furiously, it's really hard to keep up. And 202 00:13:34,280 --> 00:13:36,880 Speaker 3: you know, even if we get this episode out in 203 00:13:36,920 --> 00:13:39,280 Speaker 3: the next one or two days, we don't know if 204 00:13:39,320 --> 00:13:42,680 Speaker 3: the Trump administration is going to announce something completely different 205 00:13:42,720 --> 00:13:46,320 Speaker 3: when it comes to tariffs. How hard or easy will 206 00:13:46,320 --> 00:13:50,360 Speaker 3: it be to actually start to rebuild inventories if we 207 00:13:50,360 --> 00:13:54,480 Speaker 3: were to get some certainty on the Yeah, on the 208 00:13:54,559 --> 00:13:55,320 Speaker 3: Terroff question. 209 00:13:55,720 --> 00:13:59,360 Speaker 4: Going back to the planning for a holiday season, right, so, 210 00:13:59,559 --> 00:14:04,199 Speaker 4: firms should be planning now for if they want goods 211 00:14:04,200 --> 00:14:07,520 Speaker 4: to be on the shelf in October, so it takes 212 00:14:07,880 --> 00:14:11,560 Speaker 4: at least six months for the whole planning to take place. 213 00:14:11,720 --> 00:14:16,040 Speaker 4: But does anybody have enough certainty about six you know, 214 00:14:16,160 --> 00:14:21,000 Speaker 4: and even in thirty days time to know to to 215 00:14:21,360 --> 00:14:25,480 Speaker 4: be ready to potentially get hit by tariffs. So an 216 00:14:25,520 --> 00:14:29,040 Speaker 4: example is what we have seen in February March in 217 00:14:29,120 --> 00:14:32,400 Speaker 4: the import price data and mentioned that almost one hundred 218 00:14:32,440 --> 00:14:35,400 Speaker 4: percent of the tariffs on China has been passed through 219 00:14:35,400 --> 00:14:39,400 Speaker 4: through the US border. And the thing is it's because 220 00:14:39,520 --> 00:14:43,560 Speaker 4: most of those goods had been entransit already before these 221 00:14:43,600 --> 00:14:46,880 Speaker 4: tariffs were even on the horizon, so they were already 222 00:14:47,040 --> 00:14:50,240 Speaker 4: en route in January, so there was no time to 223 00:14:50,280 --> 00:14:55,560 Speaker 4: discuss between the import and exporter how to share the burden. So, 224 00:14:55,960 --> 00:15:00,400 Speaker 4: for if the US firm is thinking about restore stocking, 225 00:15:00,720 --> 00:15:03,680 Speaker 4: suppose that they have enough stock to last them until 226 00:15:03,760 --> 00:15:06,280 Speaker 4: June based on the front running we have seen in 227 00:15:06,320 --> 00:15:09,360 Speaker 4: the imports data so far, so they have enough until 228 00:15:09,400 --> 00:15:12,600 Speaker 4: June and now they're planning. Should they start to uh 229 00:15:12,840 --> 00:15:17,880 Speaker 4: plan for restocking beyond June, then they need to basically 230 00:15:17,960 --> 00:15:21,800 Speaker 4: think like a risk neutral agent. So in economics, when 231 00:15:22,080 --> 00:15:24,720 Speaker 4: one is you know, In these models, when we think 232 00:15:24,760 --> 00:15:29,600 Speaker 4: about how does a person make a decision rational decision 233 00:15:30,040 --> 00:15:34,000 Speaker 4: in the phase of uncertainty, you calculate the risk neutral 234 00:15:34,200 --> 00:15:37,400 Speaker 4: you know, optimization equation. So it would be you know, 235 00:15:37,480 --> 00:15:41,280 Speaker 4: a probability of the scenario on the tariff multiplied by 236 00:15:41,280 --> 00:15:44,680 Speaker 4: the net cost UH and then plus you know different 237 00:15:45,000 --> 00:15:49,480 Speaker 4: probability of scenarios. So right now we have seen that 238 00:15:49,600 --> 00:15:52,760 Speaker 4: tariffs on China is you know, over well over one 239 00:15:52,800 --> 00:15:57,960 Speaker 4: hundred percent, and because of that extremely high cost to 240 00:15:58,240 --> 00:16:03,920 Speaker 4: that tail outcome, like suppose that there were further escalation 241 00:16:04,080 --> 00:16:06,280 Speaker 4: between you as a China and now you know that 242 00:16:06,360 --> 00:16:11,160 Speaker 4: the probability of tariff on China could potentially even go 243 00:16:11,240 --> 00:16:13,480 Speaker 4: to two hundred percent if you know, I'm not saying 244 00:16:13,520 --> 00:16:16,480 Speaker 4: that will happen, but it seems like quite plausible. Now 245 00:16:16,520 --> 00:16:20,720 Speaker 4: anything could happen. So in that case, your loss in 246 00:16:20,800 --> 00:16:24,520 Speaker 4: this you're trying to minimize this loss function, and then 247 00:16:24,560 --> 00:16:27,080 Speaker 4: you have a massive loss. This is why we are 248 00:16:27,160 --> 00:16:32,160 Speaker 4: seeing cancelation of orders. It's because in the risk neutral optimization, 249 00:16:33,000 --> 00:16:37,800 Speaker 4: given these high risk outcome, it doesn't make sense for 250 00:16:37,920 --> 00:16:41,320 Speaker 4: you to actually take the risk of potentially you know, 251 00:16:41,480 --> 00:16:44,040 Speaker 4: having the good arrived at the border only to find 252 00:16:44,080 --> 00:16:47,280 Speaker 4: out that, oh, you are two hundred percent of the tariffs. 253 00:16:47,520 --> 00:16:50,200 Speaker 4: And this is why there's it's a high probability that, 254 00:16:50,560 --> 00:16:54,120 Speaker 4: given the uncertainty and the time it takes to plan 255 00:16:54,320 --> 00:16:57,160 Speaker 4: for the goods to be on the shelf in the fall, 256 00:16:57,280 --> 00:17:00,120 Speaker 4: that I think is the high high probability outcome that 257 00:17:00,160 --> 00:17:04,879 Speaker 4: we all have all empty shells and lack of varieties. 258 00:17:05,240 --> 00:17:08,200 Speaker 2: I just have one last question. You know, we're in 259 00:17:08,280 --> 00:17:11,720 Speaker 2: this sort of weird space where you know, we see 260 00:17:11,720 --> 00:17:13,879 Speaker 2: what's on the screen, and we see the surveys and 261 00:17:13,920 --> 00:17:15,960 Speaker 2: all that, but day to day life when I go 262 00:17:16,040 --> 00:17:19,040 Speaker 2: to the store is like pretty normal. And you know, 263 00:17:19,160 --> 00:17:21,199 Speaker 2: like we said, we haven't seen to pick up in 264 00:17:21,280 --> 00:17:24,840 Speaker 2: the layoffs data yet, even though everyone is anticipating all 265 00:17:24,840 --> 00:17:27,280 Speaker 2: the surveys are dismal. But you know, I think for most, 266 00:17:27,640 --> 00:17:30,439 Speaker 2: you know, the three of us anyway, buy and large 267 00:17:30,760 --> 00:17:33,919 Speaker 2: life goes on. Although Tracy has received emails from various 268 00:17:33,960 --> 00:17:36,120 Speaker 2: companies that she buys from. 269 00:17:36,160 --> 00:17:38,040 Speaker 3: One of the things I'm learning in all of this 270 00:17:38,240 --> 00:17:40,320 Speaker 3: is that I am on a lot of mailing us 271 00:17:40,640 --> 00:17:43,239 Speaker 3: for random stuff. So I've gotten an email from a 272 00:17:43,440 --> 00:17:47,000 Speaker 3: company that sells fake flowers saying that their prices are 273 00:17:47,000 --> 00:17:48,679 Speaker 3: probably going to go up because so much of it 274 00:17:48,760 --> 00:17:51,199 Speaker 3: is made in China. I've gotten an email from a 275 00:17:51,280 --> 00:17:54,720 Speaker 3: provider of a home battery storage system because I was 276 00:17:54,760 --> 00:17:57,400 Speaker 3: kind of interested in that, saying that prices we're also 277 00:17:57,440 --> 00:17:59,720 Speaker 3: going to go up. So we'll see, we'll see what else. 278 00:18:00,000 --> 00:18:03,159 Speaker 2: One thing about fake flowers, by the way, is that 279 00:18:03,240 --> 00:18:06,600 Speaker 2: was one of Hong Kong's very first export industries was 280 00:18:06,640 --> 00:18:09,359 Speaker 2: that they really they like current, they really like Yeah 281 00:18:09,400 --> 00:18:11,280 Speaker 2: they did. That was a huge you know. Then they 282 00:18:11,320 --> 00:18:14,920 Speaker 2: eventually did high tech things, but fake flowers was an 283 00:18:14,920 --> 00:18:17,600 Speaker 2: early uh it was an early industry. They came to 284 00:18:17,640 --> 00:18:18,280 Speaker 2: dominate this. 285 00:18:18,560 --> 00:18:20,879 Speaker 5: And one of those random oh yes, Joe, and in 286 00:18:20,920 --> 00:18:23,119 Speaker 5: fact it was the bread and butter of the richest 287 00:18:23,160 --> 00:18:28,200 Speaker 5: man in Hong kongly couching has uh got has start 288 00:18:28,320 --> 00:18:30,040 Speaker 5: with making plastic flowers. 289 00:18:30,400 --> 00:18:31,240 Speaker 1: This is so great. 290 00:18:31,320 --> 00:18:34,520 Speaker 2: I like have this random random fact stuck in my 291 00:18:34,600 --> 00:18:38,159 Speaker 2: head and you know, I don't know how you remember that. 292 00:18:38,240 --> 00:18:40,879 Speaker 2: And then you were able to the alip there between 293 00:18:40,880 --> 00:18:44,920 Speaker 2: me and a real quickly holiday season potentially very damage. 294 00:18:45,200 --> 00:18:47,000 Speaker 2: But when do you would you say, we start to 295 00:18:47,040 --> 00:18:49,400 Speaker 2: see this in sort of either our day to day 296 00:18:49,400 --> 00:18:52,119 Speaker 2: lives or at least in hard data, Well, I. 297 00:18:52,600 --> 00:18:57,320 Speaker 4: Think anecdotally it's already these stories are filtering in. I mean, 298 00:18:57,480 --> 00:19:02,119 Speaker 4: for anyone who will be having a broken AC system, 299 00:19:02,320 --> 00:19:07,960 Speaker 4: especially a central AC system, and comes summer, you'll find 300 00:19:08,000 --> 00:19:11,000 Speaker 4: that many of the parts are actually came from China, 301 00:19:11,160 --> 00:19:15,600 Speaker 4: only manufactured in China, and your service company will tell 302 00:19:15,640 --> 00:19:17,800 Speaker 4: you if they can't do nothing about it because nobody 303 00:19:17,880 --> 00:19:20,639 Speaker 4: is importing any of those parts. And you know there 304 00:19:20,640 --> 00:19:22,640 Speaker 4: will be more and more stories like that. In terms 305 00:19:22,720 --> 00:19:26,320 Speaker 4: of the hard data, I think in the April, meaning 306 00:19:27,160 --> 00:19:31,240 Speaker 4: next month, we will get the April's import volume data, 307 00:19:31,400 --> 00:19:34,160 Speaker 4: which for the whole month, and it will be clear 308 00:19:34,359 --> 00:19:39,600 Speaker 4: that the volume is already declining very quickly. And I 309 00:19:39,680 --> 00:19:43,720 Speaker 4: would I think for now, for people who collect big 310 00:19:43,840 --> 00:19:50,200 Speaker 4: data so web scraping, I think one could be scraping. 311 00:19:50,440 --> 00:19:54,240 Speaker 4: You know. You know how on Amazon it actually lists 312 00:19:54,480 --> 00:19:58,040 Speaker 4: how many of these items are remaining, Like it tells 313 00:19:58,080 --> 00:20:02,440 Speaker 4: you like three more left, more left. Start paying attention 314 00:20:02,600 --> 00:20:05,120 Speaker 4: to that, and you see that those three more left, 315 00:20:05,240 --> 00:20:08,320 Speaker 4: two more left is dwindling without increasing. 316 00:20:08,760 --> 00:20:12,280 Speaker 3: Anna, You're going to add to my already innate tendency 317 00:20:12,400 --> 00:20:16,400 Speaker 3: to stockpile things. Thank you for the advice. 318 00:20:16,320 --> 00:20:19,199 Speaker 2: Anna, think I'm sure you're as busy as we are, 319 00:20:19,359 --> 00:20:22,000 Speaker 2: updating models every day with every new headline. Thank you 320 00:20:22,080 --> 00:20:41,399 Speaker 2: so much for coming on odd Lote, No problem, Tracy, 321 00:20:41,480 --> 00:20:44,040 Speaker 2: that was unnerving. You know, this didn't actually come up. 322 00:20:44,160 --> 00:20:46,200 Speaker 2: But one of the things I've been thinking about is 323 00:20:46,840 --> 00:20:49,760 Speaker 2: the disparate impact that this will have on small versus 324 00:20:49,800 --> 00:20:52,560 Speaker 2: big businesses, because like a really big business, you know, 325 00:20:52,600 --> 00:20:55,159 Speaker 2: they can you know, could lose money right for a 326 00:20:55,240 --> 00:20:58,159 Speaker 2: quarter or two and go be you know, continue for 327 00:20:58,160 --> 00:21:01,080 Speaker 2: a while. As a going there are going to be 328 00:21:01,080 --> 00:21:05,280 Speaker 2: small businesses that literally just cannot pay that tariff bill 329 00:21:05,359 --> 00:21:06,560 Speaker 2: and that's lights out for them. 330 00:21:06,640 --> 00:21:06,840 Speaker 5: Yeah. 331 00:21:06,840 --> 00:21:08,639 Speaker 3: I think I wrote about this in the newsletter a 332 00:21:08,640 --> 00:21:11,520 Speaker 3: few weeks ago, but that seems almost certain to happen. 333 00:21:11,600 --> 00:21:14,239 Speaker 3: And also, you know, the bigger businesses obviously do have 334 00:21:14,280 --> 00:21:17,960 Speaker 3: some pricing power. They might have some ability to negotiate 335 00:21:18,200 --> 00:21:21,200 Speaker 3: with their suppliers, like I think Walmart is already trying 336 00:21:21,240 --> 00:21:23,560 Speaker 3: to do that with China at the moment. So yeah, 337 00:21:23,600 --> 00:21:26,639 Speaker 3: the scales seem very very much tipped in favor of 338 00:21:26,760 --> 00:21:29,639 Speaker 3: the big guys over at the small it is. It 339 00:21:29,720 --> 00:21:32,320 Speaker 3: is also very unsettling just to think that all of 340 00:21:32,320 --> 00:21:36,080 Speaker 3: this is by choice, right, Yeah, like this is a 341 00:21:36,080 --> 00:21:39,960 Speaker 3: policy decision by the current administration. It almost seems like 342 00:21:40,200 --> 00:21:42,560 Speaker 3: it was probably a bad time to do this, right 343 00:21:42,760 --> 00:21:46,560 Speaker 3: in the spring planning season, right before the summer shipping 344 00:21:46,600 --> 00:21:51,840 Speaker 3: season for the later retail buying season. Feels like this was, yeah, 345 00:21:52,000 --> 00:21:53,000 Speaker 3: not a great time. 346 00:21:53,119 --> 00:21:55,760 Speaker 2: Well, you know, I find it interesting that for years, 347 00:21:56,280 --> 00:21:59,600 Speaker 2: since I was a teen, culture work the war on Christmas. 348 00:21:59,640 --> 00:22:01,840 Speaker 2: This is a literal no for real, right that we've 349 00:22:01,840 --> 00:22:04,760 Speaker 2: been hearing that forever, And Anna's talking about empty shelves 350 00:22:04,800 --> 00:22:05,560 Speaker 2: over the holidays. 351 00:22:05,600 --> 00:22:06,160 Speaker 1: What is that? 352 00:22:06,680 --> 00:22:10,840 Speaker 3: It's they're winning the War on Christmas. I don't know. Like, well, 353 00:22:10,920 --> 00:22:13,240 Speaker 3: on the plus side, I guess people have been complaining 354 00:22:13,240 --> 00:22:16,480 Speaker 3: about American consumerism for a very long time. So here 355 00:22:16,520 --> 00:22:19,800 Speaker 3: we go at exercise in austerity. Shall we leave it there? 356 00:22:20,080 --> 00:22:20,840 Speaker 2: Let's leave it there. 357 00:22:21,040 --> 00:22:23,760 Speaker 3: This has been another episode of the Authoughts podcast. I'm 358 00:22:23,760 --> 00:22:26,920 Speaker 3: Tracy Alloway. You can follow me at Tracy Alloway. 359 00:22:26,600 --> 00:22:29,400 Speaker 2: And I'm Joe Wisenthal. You can follow me at The Stalwart. 360 00:22:29,600 --> 00:22:33,480 Speaker 2: Follow Anna Wong, She's at Anna Economist. Follow our producers 361 00:22:33,560 --> 00:22:36,960 Speaker 2: Carman Rodriguez at Kerman Armann, dash O Bennett at Dashbot 362 00:22:36,960 --> 00:22:40,200 Speaker 2: and kill Brooks at Kelbrooks. For our odd Laws content. 363 00:22:40,240 --> 00:22:42,520 Speaker 2: Go to Bloomberg dot com slash odd Lots, where we 364 00:22:42,600 --> 00:22:45,880 Speaker 2: have a daily newsletter and all of our episodes, and 365 00:22:46,000 --> 00:22:48,480 Speaker 2: you can chat with fellow listeners twenty four to seven. 366 00:22:48,520 --> 00:22:50,879 Speaker 2: What are you seeing out there in the real economy? 367 00:22:50,880 --> 00:22:53,280 Speaker 2: What niches are you aware of the way Tracy is 368 00:22:53,320 --> 00:22:58,320 Speaker 2: aware of artificial flowers? 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