1 00:00:13,920 --> 00:00:17,200 Speaker 1: Hello, and welcome to What Goes Up, a weekly markets podcast. 2 00:00:17,320 --> 00:00:20,200 Speaker 1: My name is Mike Reagan. I'm a senior editor at Bloomberg, 3 00:00:20,360 --> 00:00:23,720 Speaker 1: and I'm Aldana Higher, across Asset reporter with Bloomberg. This 4 00:00:23,800 --> 00:00:27,159 Speaker 1: week on the show, Well, despite all those doom and 5 00:00:27,200 --> 00:00:31,000 Speaker 1: gloom predictions about a recession on the horizon, the job 6 00:00:31,040 --> 00:00:34,400 Speaker 1: market remains red hot, with the unemployment rate at just 7 00:00:34,560 --> 00:00:38,840 Speaker 1: three point five yet with inflation out of four decade high. 8 00:00:38,920 --> 00:00:41,760 Speaker 1: Many economists believe that some pain in the labor market 9 00:00:41,960 --> 00:00:46,080 Speaker 1: is needed to get consumer prices under control. But is 10 00:00:46,120 --> 00:00:50,280 Speaker 1: that necessarily true. We'll get into it with a veteran economist, 11 00:00:50,680 --> 00:00:54,040 Speaker 1: but Voldonna, I have to ask you first, how many 12 00:00:54,040 --> 00:00:55,920 Speaker 1: cups of coffee do you drink? Aday? Do you want 13 00:00:55,920 --> 00:00:58,080 Speaker 1: to guess? I want to guess. I want to say 14 00:00:59,280 --> 00:01:02,959 Speaker 1: zero cups? Zero? Yeah? Zero? Yeah? How did you know? 15 00:01:03,360 --> 00:01:06,880 Speaker 1: Because I felt like it was a trick question even 16 00:01:06,880 --> 00:01:10,559 Speaker 1: though I asked it. Yeah, how could you know? Zero? 17 00:01:10,760 --> 00:01:13,280 Speaker 1: I'm so like hyper usually I know, but it's something 18 00:01:13,640 --> 00:01:18,400 Speaker 1: also very healthy with the cauliflower. I love cauliflower. If 19 00:01:18,400 --> 00:01:21,200 Speaker 1: they were cauliflower coffee, I would have that. Yeah, yeah, no, 20 00:01:21,319 --> 00:01:24,959 Speaker 1: I stopped drinking it. Earlier this year. Actually, no caffeine 21 00:01:25,000 --> 00:01:27,600 Speaker 1: at all. No caffeine really. Yeah, it was giving me 22 00:01:27,600 --> 00:01:30,840 Speaker 1: a headache every time I didn't have it. So I 23 00:01:30,840 --> 00:01:32,480 Speaker 1: don't think it's for health reason. I mean, I think 24 00:01:32,520 --> 00:01:35,320 Speaker 1: it's healthy for you. Right, Well, I don't know. I 25 00:01:36,560 --> 00:01:39,240 Speaker 1: the headache. I've never gotten past the headache I needed 26 00:01:39,280 --> 00:01:40,800 Speaker 1: every day. How do you get out of bed in 27 00:01:40,840 --> 00:01:43,000 Speaker 1: the morning. Then well, I had food poisoning, so I 28 00:01:43,040 --> 00:01:46,600 Speaker 1: couldn't eat anything like at all, and so that's when 29 00:01:46,640 --> 00:01:49,160 Speaker 1: I stopped just drinking it. I don't know now I 30 00:01:49,160 --> 00:01:51,920 Speaker 1: feel about the coffee I drink. How much coffee do 31 00:01:51,960 --> 00:01:55,200 Speaker 1: you drink? Well, the pants are you buying? If you're 32 00:01:55,240 --> 00:01:58,960 Speaker 1: buying I'm buying, Yes, then like five cops. But we're 33 00:01:59,000 --> 00:02:01,800 Speaker 1: not going to Starbucks. That's like seven dollars. Will go 34 00:02:01,960 --> 00:02:06,880 Speaker 1: to like the Little Stance, the little carts. But our 35 00:02:06,960 --> 00:02:10,600 Speaker 1: our guest, actually I think she drinks a lot of coffee. 36 00:02:09,520 --> 00:02:13,360 Speaker 1: I have a feeling. Our guest today is Nila Richardson. 37 00:02:13,360 --> 00:02:16,080 Speaker 1: She's a chief economist at ADP Miila, thanks so much 38 00:02:16,120 --> 00:02:18,680 Speaker 1: for joining us. Oh, it's great to be here with you. 39 00:02:18,800 --> 00:02:21,280 Speaker 1: Thanks for having me. Well, the I think the reason 40 00:02:21,280 --> 00:02:23,359 Speaker 1: we're talking about This is because you had a blog 41 00:02:23,360 --> 00:02:27,560 Speaker 1: post recently where you h It was titled Inflation and Coffee, 42 00:02:27,600 --> 00:02:31,000 Speaker 1: a love story about how you go through how how 43 00:02:31,040 --> 00:02:33,640 Speaker 1: prices have gone up but the Fed's not really paying 44 00:02:33,680 --> 00:02:36,679 Speaker 1: attention to things like food costs, and you said, there's 45 00:02:36,680 --> 00:02:38,560 Speaker 1: a problem with this kind of thinking. So I was 46 00:02:38,600 --> 00:02:40,720 Speaker 1: hoping we could just start out with with you talking 47 00:02:40,720 --> 00:02:45,440 Speaker 1: about this my love of coffee and my dislike of inflation. 48 00:02:46,480 --> 00:02:49,600 Speaker 1: That's a that's a great way to start. Yeah, I mean, 49 00:02:49,840 --> 00:02:53,160 Speaker 1: I do love coffee, and I think that actually coffee 50 00:02:53,240 --> 00:02:55,600 Speaker 1: is a good prop for what's going on in the 51 00:02:55,639 --> 00:03:00,640 Speaker 1: global economy, not just domestically. So coffee prices. You mentioned 52 00:03:00,639 --> 00:03:03,320 Speaker 1: that seven dollar a cup of coffee across the street. 53 00:03:03,600 --> 00:03:07,080 Speaker 1: Coffee prices are actually up almost six from a year ago. 54 00:03:07,760 --> 00:03:11,639 Speaker 1: And you know, when everything is going up, isolating one 55 00:03:11,720 --> 00:03:15,079 Speaker 1: thing seems like you're piling on. But coffee is kind 56 00:03:15,080 --> 00:03:18,320 Speaker 1: of unique because for all those years and months leading 57 00:03:18,400 --> 00:03:21,880 Speaker 1: up to the pandemic, prices were either flat or falling. 58 00:03:22,000 --> 00:03:24,600 Speaker 1: So to see this big surge and you're over your 59 00:03:24,600 --> 00:03:28,200 Speaker 1: coffee prices, it's like for a lover of coffee, it's 60 00:03:28,520 --> 00:03:33,120 Speaker 1: traumatic has been for me. Um, I won't say how 61 00:03:33,120 --> 00:03:36,960 Speaker 1: many cups I drink. I'm generally just a morning coffee person. 62 00:03:37,160 --> 00:03:40,720 Speaker 1: But um, you know, coffee is important to some of us. 63 00:03:41,120 --> 00:03:45,240 Speaker 1: But food prices just rit large have been going up. 64 00:03:45,760 --> 00:03:48,800 Speaker 1: And the point of the blog is, you know, coffee 65 00:03:48,840 --> 00:03:53,280 Speaker 1: represents a global supply chain that's quite complicated, that has 66 00:03:53,320 --> 00:03:57,800 Speaker 1: been affected by the pandemic. It represents the big surge 67 00:03:57,960 --> 00:04:00,720 Speaker 1: in food prices that we've seen over the past year. 68 00:04:01,320 --> 00:04:04,480 Speaker 1: It represents the fact that Main Street sees food and 69 00:04:04,560 --> 00:04:09,600 Speaker 1: gas as inflation. But when the Federal Reserve makes monetary policy, 70 00:04:09,640 --> 00:04:13,320 Speaker 1: they exclude food and gas prices and volatile prices and 71 00:04:13,360 --> 00:04:17,200 Speaker 1: look at core inflation, what's known as those baskets of 72 00:04:17,240 --> 00:04:20,920 Speaker 1: goods that are not affected by something that's really really volatile, 73 00:04:21,040 --> 00:04:24,320 Speaker 1: like coffee. So um, While I get a lot of 74 00:04:24,360 --> 00:04:27,359 Speaker 1: attention to coffee, the Fed doesn't. I'm sure they drink it. 75 00:04:28,680 --> 00:04:31,400 Speaker 1: I guess their argument, Neila, is that, as you say, 76 00:04:31,440 --> 00:04:34,320 Speaker 1: those prices can be so volatile. You know, if there's 77 00:04:34,400 --> 00:04:39,160 Speaker 1: a bad harvest in Columbia or if there's a hurricane, 78 00:04:39,200 --> 00:04:41,200 Speaker 1: the oil prices are going to go up. Are they 79 00:04:41,240 --> 00:04:42,640 Speaker 1: wrong to do that? Though? Do you think I mean, 80 00:04:42,640 --> 00:04:45,560 Speaker 1: should should you know, should the headline number carry more 81 00:04:45,560 --> 00:04:48,919 Speaker 1: weight for the Fed. Do you think I think the 82 00:04:49,000 --> 00:04:53,360 Speaker 1: headline number should carry more weight because it feeds consumer expectations, 83 00:04:53,720 --> 00:04:56,599 Speaker 1: and we know that the long term driver of inflation 84 00:04:57,080 --> 00:05:00,280 Speaker 1: is what people think will happen with inflation. So if 85 00:05:00,360 --> 00:05:03,560 Speaker 1: you think that prices are going up, you are going 86 00:05:03,600 --> 00:05:06,640 Speaker 1: to behave in a way that actually causes prices to 87 00:05:06,680 --> 00:05:09,360 Speaker 1: go up, Like go to trade to Jews and hoard 88 00:05:09,400 --> 00:05:12,720 Speaker 1: a bunch of coffee and your your cart because you 89 00:05:12,760 --> 00:05:15,200 Speaker 1: think that you know next month is going to be higher. 90 00:05:15,520 --> 00:05:21,080 Speaker 1: Not saying I do that. It's that that example is 91 00:05:21,120 --> 00:05:27,080 Speaker 1: a little too real. They're yeah, well, you know, experience 92 00:05:27,120 --> 00:05:30,800 Speaker 1: is our best teacher. So um with the FED. While 93 00:05:30,920 --> 00:05:34,120 Speaker 1: the Fed is not looking at coffee or food or 94 00:05:34,400 --> 00:05:38,880 Speaker 1: gas specifically, when it's really focused on its interest rate policy, 95 00:05:39,360 --> 00:05:42,760 Speaker 1: it is well aware as we all are, that consumers 96 00:05:42,760 --> 00:05:45,440 Speaker 1: see it and that's what consumers are judging. And if 97 00:05:45,480 --> 00:05:49,640 Speaker 1: that feeds back to long term inflation expectations, then we 98 00:05:49,760 --> 00:05:53,839 Speaker 1: have a problem that spirals beyond, you know, the window 99 00:05:53,920 --> 00:05:57,640 Speaker 1: that the FED is executing its policy. And well, I know, Neila, 100 00:05:57,720 --> 00:05:59,479 Speaker 1: you pay a lot of attention to consumers, so maybe 101 00:05:59,480 --> 00:06:01,640 Speaker 1: you can talk a little bit more about consumer sentiment 102 00:06:01,720 --> 00:06:04,000 Speaker 1: right now, because I wanted to ask you if it's 103 00:06:04,040 --> 00:06:07,080 Speaker 1: not the case that the wealth effect is also very 104 00:06:07,120 --> 00:06:10,560 Speaker 1: real right now where we're seeing obviously uh downturn in 105 00:06:10,600 --> 00:06:13,520 Speaker 1: the stock market and also a slowdown in the housing market, 106 00:06:13,560 --> 00:06:16,320 Speaker 1: And does that not also affect the way consumers are 107 00:06:16,320 --> 00:06:19,640 Speaker 1: thinking about things? I think it does. I think that's 108 00:06:19,680 --> 00:06:24,359 Speaker 1: an important attribute of consumers spending. You know, that's the 109 00:06:24,400 --> 00:06:30,600 Speaker 1: bulk of the economy. And so when consumers, especially wealthy consumers, 110 00:06:30,600 --> 00:06:35,000 Speaker 1: feel confident about the economy, they spend more. But at 111 00:06:35,040 --> 00:06:39,479 Speaker 1: the lower end of the income spectrum, it's not about confidence, right, Um, 112 00:06:39,520 --> 00:06:42,800 Speaker 1: you're spending on necessity, so you spend when you have 113 00:06:42,960 --> 00:06:45,960 Speaker 1: it at the lower income and so we've seen a 114 00:06:46,000 --> 00:06:50,560 Speaker 1: transition of who's driving the spending in the economy from 115 00:06:50,600 --> 00:06:54,240 Speaker 1: those people who benefited from those direct payments from the 116 00:06:54,279 --> 00:06:58,159 Speaker 1: federal government through the heart of the pandemic. That translated 117 00:06:58,200 --> 00:07:01,599 Speaker 1: into a lot of spending, which helps the US avoid 118 00:07:01,960 --> 00:07:05,359 Speaker 1: a prolonged downturn and led to a pretty speedy recovery. 119 00:07:05,920 --> 00:07:09,240 Speaker 1: Now on the other side of inflation, when things are 120 00:07:09,279 --> 00:07:12,720 Speaker 1: slowing down in the stock markets and in the housing 121 00:07:12,760 --> 00:07:15,680 Speaker 1: markets because of higher interest rates, you might start to 122 00:07:15,680 --> 00:07:19,640 Speaker 1: see a slowdown in the spending of upper income folks UM, 123 00:07:19,760 --> 00:07:24,200 Speaker 1: where the wealth effect is more prominent in their decision making. Yeah, well, 124 00:07:24,240 --> 00:07:26,920 Speaker 1: I know, Neil. And now at a DP your your 125 00:07:27,040 --> 00:07:29,560 Speaker 1: sort of laser focused on the job market too, So 126 00:07:29,840 --> 00:07:32,600 Speaker 1: let's get into that. A little bit. Wage growth has 127 00:07:32,680 --> 00:07:35,320 Speaker 1: picked up, but it is still lower than the rate 128 00:07:35,400 --> 00:07:37,480 Speaker 1: of inflation, you know, So in other words, what they 129 00:07:37,520 --> 00:07:40,840 Speaker 1: call real wage growth is negative, which means if you 130 00:07:40,840 --> 00:07:43,080 Speaker 1: get a raise, it it doesn't necessarily feel like you're 131 00:07:43,080 --> 00:07:45,840 Speaker 1: getting a raise because you're all your consumer goods are 132 00:07:46,840 --> 00:07:50,920 Speaker 1: rising even faster. And you know that obviously triggers a 133 00:07:50,920 --> 00:07:54,880 Speaker 1: lot of concern about what they call the wage costs spiral, 134 00:07:54,960 --> 00:07:58,120 Speaker 1: you know, where labor demands higher wages to keep up 135 00:07:58,160 --> 00:08:00,920 Speaker 1: with inflation. Are you seeing any signs of that? I mean, 136 00:08:00,960 --> 00:08:03,480 Speaker 1: is that is that a risk that this inflation might 137 00:08:03,560 --> 00:08:07,360 Speaker 1: prove to be stickier than um everyone's hoping. Let me 138 00:08:07,400 --> 00:08:10,320 Speaker 1: take the second part of that question about is there 139 00:08:10,360 --> 00:08:14,559 Speaker 1: a risk that inflation is stickier than we think? Yes. Now, 140 00:08:14,840 --> 00:08:17,440 Speaker 1: the second question that proceeded to that is the wage 141 00:08:17,480 --> 00:08:21,360 Speaker 1: is going to be the main driver of that stickiness. 142 00:08:21,640 --> 00:08:24,680 Speaker 1: I do think that wages because they have accelerated so 143 00:08:24,800 --> 00:08:28,320 Speaker 1: quickly over the past year and a DP data and 144 00:08:28,680 --> 00:08:31,440 Speaker 1: we have some really good data on this, as you know, 145 00:08:31,480 --> 00:08:35,280 Speaker 1: paying over twenty five million workers in the United States. 146 00:08:35,360 --> 00:08:41,280 Speaker 1: It's showing that that that wages wage growth has been 147 00:08:41,320 --> 00:08:44,880 Speaker 1: elevated and is now kind of bottling me out at 148 00:08:44,920 --> 00:08:49,560 Speaker 1: this higher level. So in our latest report for August, 149 00:08:49,679 --> 00:08:53,600 Speaker 1: we show that wage growth for the medium worker who 150 00:08:53,600 --> 00:08:56,760 Speaker 1: stayed in the same job for the past twelve months 151 00:08:56,760 --> 00:08:59,360 Speaker 1: with seven point eight percent. Now they put that in 152 00:08:59,400 --> 00:09:03,319 Speaker 1: perspective in spring of that medium wage growth would have 153 00:09:03,320 --> 00:09:06,320 Speaker 1: been around two percent, so a huge acceleration. But the 154 00:09:06,360 --> 00:09:09,200 Speaker 1: seven point eight percent is basically in line where we've 155 00:09:09,240 --> 00:09:11,840 Speaker 1: been for the past several months. So we're not seeing 156 00:09:11,880 --> 00:09:16,240 Speaker 1: it go up dramatically, um, but it is elevated, and 157 00:09:16,280 --> 00:09:20,240 Speaker 1: I think that's the story of inflation overall. Um. Perhaps 158 00:09:20,320 --> 00:09:25,079 Speaker 1: we are slowing down from acceleration, UM, but for many 159 00:09:25,240 --> 00:09:30,040 Speaker 1: items from coffee to your paycheck, Uh, those prices are 160 00:09:30,080 --> 00:09:33,120 Speaker 1: are elevated and the growth rate or is kind of 161 00:09:33,240 --> 00:09:36,880 Speaker 1: leveling out, it's still growing, right, So do do you 162 00:09:36,880 --> 00:09:40,079 Speaker 1: think there's you know, the only way to cure inflation 163 00:09:40,240 --> 00:09:44,800 Speaker 1: is in part to weaken the job market a little bit. Now, 164 00:09:44,840 --> 00:09:46,640 Speaker 1: I don't think that's the best way at all. I 165 00:09:46,720 --> 00:09:50,360 Speaker 1: think that's a horrible way to care inflation by destroying deman. 166 00:09:50,520 --> 00:09:53,200 Speaker 1: I think that's the worst way. I think a better way, 167 00:09:53,280 --> 00:09:55,760 Speaker 1: a way that you know, involves more than just the FED. 168 00:09:56,200 --> 00:10:00,520 Speaker 1: That's the fed's tool, but it's about productivity. Productivity grows 169 00:10:00,520 --> 00:10:04,320 Speaker 1: you out of inflation when more workers produce more output 170 00:10:04,520 --> 00:10:07,959 Speaker 1: for the same amount of costs. That's what productivity is. 171 00:10:08,200 --> 00:10:10,960 Speaker 1: That's what gets you out of the inflation wage price 172 00:10:11,040 --> 00:10:14,240 Speaker 1: spiral conundrum. But that takes some other muscles that the 173 00:10:14,320 --> 00:10:18,760 Speaker 1: economy hasn't really used all that well. It takes business investment, 174 00:10:18,800 --> 00:10:22,679 Speaker 1: it takes government investment in jobs and workers. It takes 175 00:10:22,720 --> 00:10:27,520 Speaker 1: more um partnerships with community colleges to build an agile 176 00:10:27,559 --> 00:10:31,080 Speaker 1: and skilled workforce in the places that the economy needs it. 177 00:10:31,400 --> 00:10:35,360 Speaker 1: So we're relying on a tool that is blunt, yes, 178 00:10:35,480 --> 00:10:38,840 Speaker 1: but also painful by its own by the fed's own words. 179 00:10:38,920 --> 00:10:42,079 Speaker 1: And there are better tools we just we we haven't 180 00:10:42,240 --> 00:10:46,839 Speaker 1: had to use them in this economy until now. So then, 181 00:10:46,920 --> 00:10:50,040 Speaker 1: can you talk a little bit more about the jobs market, 182 00:10:50,080 --> 00:10:52,800 Speaker 1: because we have been having a very strong jobs market 183 00:10:53,160 --> 00:10:55,840 Speaker 1: where we're getting numbers that are just so much better 184 00:10:55,880 --> 00:10:59,640 Speaker 1: than a lot of times what economists are expecting overall. 185 00:11:00,280 --> 00:11:02,240 Speaker 1: How long do you foresee that happening? And do you 186 00:11:02,320 --> 00:11:06,480 Speaker 1: foresee a potential slowdown in the jobs numbers? Yeah, the 187 00:11:06,520 --> 00:11:09,439 Speaker 1: slowdown isn't inevitable in the job numbers. I mean, we've 188 00:11:09,440 --> 00:11:13,160 Speaker 1: already seen it. You can't expect an economy in normal times. 189 00:11:13,160 --> 00:11:15,000 Speaker 1: They're as close to normal as we're going to get 190 00:11:15,040 --> 00:11:17,840 Speaker 1: from here on out. To produce half a million or 191 00:11:17,840 --> 00:11:20,720 Speaker 1: four hundred thousand jobs a month. That's not the US 192 00:11:20,760 --> 00:11:24,800 Speaker 1: economy or any economy I'm aware of. Um, something more 193 00:11:25,000 --> 00:11:27,720 Speaker 1: normal makes sense, and I think what you're seeing that 194 00:11:27,960 --> 00:11:32,520 Speaker 1: is not necessarily a slowdown, but a normalization of job 195 00:11:32,600 --> 00:11:36,160 Speaker 1: gains and post pandemic, right, And so we're still seeing 196 00:11:36,200 --> 00:11:39,720 Speaker 1: some really solid job growth. And what we're hearing from 197 00:11:39,760 --> 00:11:42,040 Speaker 1: clients at ADP is that they're still trying to find 198 00:11:42,120 --> 00:11:45,880 Speaker 1: qualified workers. That's the top concern of many of our 199 00:11:46,080 --> 00:11:49,760 Speaker 1: especially small business clients, who have been out competed by 200 00:11:49,920 --> 00:11:53,680 Speaker 1: larger companies who were really aggressive and hiring over the 201 00:11:53,800 --> 00:11:57,240 Speaker 1: last year. There's those large companies are slowing down, but 202 00:11:57,400 --> 00:12:01,320 Speaker 1: they're just making room for smaller companies to higher instead. 203 00:12:01,360 --> 00:12:05,360 Speaker 1: So when we think we'll see some pretty steady games ahead, um, 204 00:12:05,360 --> 00:12:08,880 Speaker 1: but slower than what we've seen over the past six months. Right. Well, 205 00:12:08,960 --> 00:12:11,400 Speaker 1: you know it's interesting. You know, I keep thinking back 206 00:12:11,480 --> 00:12:14,559 Speaker 1: to uh I forget who invented it, but it's called 207 00:12:14,600 --> 00:12:17,320 Speaker 1: the misery index, you know, and it's basically just very 208 00:12:17,320 --> 00:12:21,400 Speaker 1: simple formula. Yeah, the inflation rate to the unemployment rate, 209 00:12:21,520 --> 00:12:23,800 Speaker 1: and you know that's supposed to give us an indication 210 00:12:23,840 --> 00:12:26,200 Speaker 1: of how miserable we all are. I mean, I guess 211 00:12:26,200 --> 00:12:27,800 Speaker 1: it depends on how much coffee you had in the 212 00:12:27,880 --> 00:12:33,640 Speaker 1: day to on an individual basis, but you said it. 213 00:12:34,400 --> 00:12:38,240 Speaker 1: Let the records say I I did not say that data. 214 00:12:38,480 --> 00:12:40,640 Speaker 1: But you know, I think the of the the issue 215 00:12:40,960 --> 00:12:44,480 Speaker 1: is that the you know, the unemployment rate can obviously 216 00:12:44,520 --> 00:12:48,440 Speaker 1: be very low, but if that inflation is high, real 217 00:12:48,480 --> 00:12:53,040 Speaker 1: wage growth is negative, it sort of makes a lot 218 00:12:53,080 --> 00:12:56,800 Speaker 1: of people miserable. Rather than say, in a recession where 219 00:12:56,840 --> 00:12:59,320 Speaker 1: you get tempercent unemployment, you've got ten percent of the 220 00:12:59,320 --> 00:13:02,520 Speaker 1: people miserable, as you know what I mean, as opposed 221 00:13:02,559 --> 00:13:05,600 Speaker 1: to in this environment, you seem to have everybody miserable 222 00:13:05,640 --> 00:13:08,320 Speaker 1: with inflation. So is that the equation do you think 223 00:13:08,400 --> 00:13:11,600 Speaker 1: that the FED is trying to solve right now that 224 00:13:12,160 --> 00:13:16,160 Speaker 1: UM inflation is almost a bigger sort of destabilizing risk 225 00:13:16,720 --> 00:13:20,120 Speaker 1: in society and the economy then a recession and and 226 00:13:20,160 --> 00:13:22,760 Speaker 1: sort of, you know, a recession is the lesser of 227 00:13:22,800 --> 00:13:25,760 Speaker 1: two evils for the FED trying to trying to sort 228 00:13:25,760 --> 00:13:29,640 Speaker 1: of chart its course. Yeah. I think that's a great question, Mike. 229 00:13:29,720 --> 00:13:33,400 Speaker 1: I mean, it's always positioned as inflation or recession. But 230 00:13:33,480 --> 00:13:36,439 Speaker 1: you know, I'm embarrassing to think that you can have both, 231 00:13:37,040 --> 00:13:39,839 Speaker 1: especially when I don't have coffee. But for the for 232 00:13:39,880 --> 00:13:42,360 Speaker 1: the FED, I mean, it really is and in my 233 00:13:42,480 --> 00:13:46,080 Speaker 1: view two for the very reason that you said, inflation 234 00:13:46,160 --> 00:13:50,280 Speaker 1: is job number one for the economy because without getting 235 00:13:50,320 --> 00:13:54,400 Speaker 1: inflation under control, workers don't benefit from a growing economy. 236 00:13:54,760 --> 00:13:57,760 Speaker 1: All of their paychecks are eaten up by inflation. And 237 00:13:57,840 --> 00:14:00,880 Speaker 1: so in order to get that product ativity that leads 238 00:14:00,920 --> 00:14:04,880 Speaker 1: to growth, you have to have inflation that's manageable. The 239 00:14:04,880 --> 00:14:10,400 Speaker 1: the the economy just can't operate without having stable prices UM. 240 00:14:10,480 --> 00:14:14,000 Speaker 1: And so I think the FEDS priority list is in 241 00:14:14,040 --> 00:14:17,199 Speaker 1: the right order. It has to be about inflation until 242 00:14:17,240 --> 00:14:22,480 Speaker 1: inflation is under control. But then, Nila, how realistic or 243 00:14:22,520 --> 00:14:28,200 Speaker 1: maybe unrealistic is the FEDS to present target on inflation. Yeah, 244 00:14:28,240 --> 00:14:34,000 Speaker 1: those goal posts probably would They would love to move them. Um. 245 00:14:34,120 --> 00:14:38,200 Speaker 1: Some of those uh, disinflationary forces that we've relied on 246 00:14:38,320 --> 00:14:40,480 Speaker 1: for the past ten years leading up to the pandemic 247 00:14:40,480 --> 00:14:43,240 Speaker 1: are just not working so well anymore. The whole idea 248 00:14:43,240 --> 00:14:47,440 Speaker 1: of the globalization bringing prices down, of having just in 249 00:14:47,600 --> 00:14:51,400 Speaker 1: time inventory that kept priced and costs low, those things 250 00:14:51,440 --> 00:14:55,040 Speaker 1: are kind of fragmenting at the scenes. And the way 251 00:14:55,120 --> 00:15:01,360 Speaker 1: that we're sourcing um really um things like semiconductors around 252 00:15:01,360 --> 00:15:07,240 Speaker 1: the world. It changes the landscape for inflation um. And 253 00:15:07,280 --> 00:15:10,840 Speaker 1: so in my view, this episode of inflation is just 254 00:15:11,280 --> 00:15:15,840 Speaker 1: one of a future world where inflation is more frequent 255 00:15:15,920 --> 00:15:20,440 Speaker 1: and more persistent. It's not that the FED is doing, um, 256 00:15:20,520 --> 00:15:22,680 Speaker 1: a one and done battle with inflation. This is going 257 00:15:22,720 --> 00:15:25,400 Speaker 1: to be an ongoing war um and so what they 258 00:15:25,440 --> 00:15:28,000 Speaker 1: do now I think sets the tone for the future. 259 00:15:28,080 --> 00:15:32,880 Speaker 1: So um, Yeah, I actually forgot your original question I 260 00:15:32,920 --> 00:15:35,080 Speaker 1: got in my own tandent, But I said, how how 261 00:15:35,680 --> 00:15:38,520 Speaker 1: how unrealistic is two percent? And and so maybe just 262 00:15:38,560 --> 00:15:40,520 Speaker 1: to add to your point, how how much longer do 263 00:15:40,600 --> 00:15:42,720 Speaker 1: you foresee them? You know, if if we're going to 264 00:15:42,760 --> 00:15:46,360 Speaker 1: be continuing to seek persistent inflation fro how much longer 265 00:15:46,400 --> 00:15:49,440 Speaker 1: do you think? Yeah, I I don't have a crystal 266 00:15:49,480 --> 00:15:53,600 Speaker 1: ball in the length of time, um, but I think 267 00:15:54,280 --> 00:15:56,920 Speaker 1: it could be the inflation does stay a bit elevated, 268 00:15:57,120 --> 00:15:59,720 Speaker 1: or for the purpose of this audience, that interest rates 269 00:15:59,720 --> 00:16:04,160 Speaker 1: half to stay um at higher higher levels than they 270 00:16:04,160 --> 00:16:07,120 Speaker 1: are now in order to keep inflation under control for 271 00:16:07,560 --> 00:16:10,320 Speaker 1: several months or even you know, and the next year 272 00:16:10,440 --> 00:16:13,960 Speaker 1: or two. Uh. And that's probably not great news for 273 00:16:14,000 --> 00:16:17,120 Speaker 1: a lot of people. Um, But the two percent target, 274 00:16:18,000 --> 00:16:20,840 Speaker 1: I don't think the Federal Reserve would change that at 275 00:16:20,880 --> 00:16:24,160 Speaker 1: this point. Um. You don't change the goal post in 276 00:16:24,240 --> 00:16:26,240 Speaker 1: the middle of the game. You have to wait till after. 277 00:16:26,840 --> 00:16:31,760 Speaker 1: And that's because it's not just about inflation. It's about 278 00:16:31,760 --> 00:16:36,840 Speaker 1: the Fed's credibility and changing it to to something higher. Um. 279 00:16:36,880 --> 00:16:39,160 Speaker 1: They kind of already did that before the pandemic, but 280 00:16:39,200 --> 00:16:41,880 Speaker 1: that was to get inflation up, and now they're trying 281 00:16:41,920 --> 00:16:45,600 Speaker 1: to push it down, and so changing the target to 282 00:16:45,680 --> 00:16:49,000 Speaker 1: three or four percent, as I've seemed suggested, really would 283 00:16:49,280 --> 00:16:51,720 Speaker 1: they have their credibility would take a hit in doing that, 284 00:16:58,520 --> 00:17:00,840 Speaker 1: you know, Neila, Obviously it used to be not so 285 00:17:00,920 --> 00:17:03,600 Speaker 1: much anymore, but he used to always be. Every month 286 00:17:03,880 --> 00:17:06,879 Speaker 1: in the market, the biggest main event of the month 287 00:17:07,000 --> 00:17:11,040 Speaker 1: was the Job's report, and which means that two days earlier, 288 00:17:11,119 --> 00:17:13,240 Speaker 1: you guys come in, ADP comes in and scoops the 289 00:17:13,240 --> 00:17:16,640 Speaker 1: government with your own jobs report, and that is also 290 00:17:16,720 --> 00:17:20,280 Speaker 1: highly anticipated but by everyone and often market moving. I 291 00:17:20,359 --> 00:17:23,240 Speaker 1: understand you guys have made some changes to the methodology. 292 00:17:23,280 --> 00:17:24,959 Speaker 1: Could you tell us a little bit about you know, 293 00:17:25,000 --> 00:17:29,479 Speaker 1: about what you did. Absolutely, and honestly, Mike, the Jobs 294 00:17:29,960 --> 00:17:34,680 Speaker 1: Week is still my favorite time of the month. I'll 295 00:17:34,760 --> 00:17:37,040 Speaker 1: let you guys break down the CPI, but I'm always 296 00:17:37,040 --> 00:17:40,680 Speaker 1: looking forward to jobs Week. You can't take vacation those weeks. 297 00:17:40,720 --> 00:17:46,679 Speaker 1: I take it world. I don't have to be in 298 00:17:46,720 --> 00:17:51,040 Speaker 1: the office, but now when one to, Honestly, I miss 299 00:17:51,040 --> 00:17:55,639 Speaker 1: all the fun. But what we've realized that ADP is 300 00:17:55,760 --> 00:17:58,879 Speaker 1: the need for real time data, especially during the pandemic 301 00:17:59,200 --> 00:18:02,760 Speaker 1: um and we knew that with the scale we had 302 00:18:02,800 --> 00:18:05,160 Speaker 1: and the breath of data that we could offer paying 303 00:18:05,200 --> 00:18:10,040 Speaker 1: over twenty five million workers, that we could be more 304 00:18:10,119 --> 00:18:13,760 Speaker 1: than just a today forecast of the BLS numbers. We 305 00:18:13,800 --> 00:18:18,280 Speaker 1: could actually provide an independent estimate based on ADP client 306 00:18:18,720 --> 00:18:22,399 Speaker 1: UH actual pay of what's going on in the labor market. 307 00:18:22,480 --> 00:18:26,720 Speaker 1: So this is not survey data. This is real pay data, 308 00:18:26,840 --> 00:18:29,800 Speaker 1: and it's very well crowd source. We have we we 309 00:18:29,960 --> 00:18:33,199 Speaker 1: our whole business model is based around paying people and 310 00:18:33,240 --> 00:18:36,480 Speaker 1: paying them on time, and so it's it was an 311 00:18:36,480 --> 00:18:40,480 Speaker 1: important I think advancement and the way that we use 312 00:18:40,640 --> 00:18:43,720 Speaker 1: data as an estimate, and I think it's not going 313 00:18:43,760 --> 00:18:46,760 Speaker 1: to be the first. The need for real time data 314 00:18:46,840 --> 00:18:51,960 Speaker 1: on the economy from the private sector has grown exponent exponentially. 315 00:18:52,000 --> 00:18:56,159 Speaker 1: The government institutions realize this. They are incorporating some of 316 00:18:56,200 --> 00:19:01,359 Speaker 1: this in their own statistical infrastructure. It's just another supplement 317 00:19:02,320 --> 00:19:04,960 Speaker 1: of what's going on in the economy. There's a lot 318 00:19:04,960 --> 00:19:06,960 Speaker 1: of people who will talk about the future of work 319 00:19:07,000 --> 00:19:09,919 Speaker 1: and give you a forecast, but when you look and 320 00:19:10,080 --> 00:19:13,359 Speaker 1: see what's actually going on in the economy, that really 321 00:19:13,400 --> 00:19:17,320 Speaker 1: helps drive business decisions because it's based on something real, 322 00:19:17,760 --> 00:19:19,600 Speaker 1: on a model. Yeah, I was, yeah, I was gonna ask, 323 00:19:19,640 --> 00:19:21,840 Speaker 1: you know. Okay, So every month the government, I think 324 00:19:22,080 --> 00:19:25,520 Speaker 1: in the Establishment Survey, they survey something like a hundred 325 00:19:25,600 --> 00:19:29,800 Speaker 1: and some thousand businesses and get the responses. You guys 326 00:19:29,840 --> 00:19:33,960 Speaker 1: have the actual hard data from twenty some million pay rolls. 327 00:19:34,080 --> 00:19:36,600 Speaker 1: Isn't that a more You know, I'm kind of a 328 00:19:36,600 --> 00:19:38,919 Speaker 1: softball for you here, Nila, But isn't that a It 329 00:19:38,920 --> 00:19:42,240 Speaker 1: seems to me like you have a more accurate view 330 00:19:42,680 --> 00:19:45,760 Speaker 1: on the labor market than the government. Should the market 331 00:19:45,840 --> 00:19:49,280 Speaker 1: be paying more attention to your report than the BLS reports? 332 00:19:49,280 --> 00:19:53,000 Speaker 1: You think the market should pay a lot of attention 333 00:19:53,040 --> 00:19:55,800 Speaker 1: to the ADP National Employment Report. So I'm on record 334 00:19:55,840 --> 00:20:00,080 Speaker 1: for saying that. And it is an independent estimate, and 335 00:20:00,160 --> 00:20:03,720 Speaker 1: I would say that the b the b LS estimate 336 00:20:04,080 --> 00:20:10,560 Speaker 1: is also an important and has a long lived lifespan 337 00:20:10,760 --> 00:20:14,000 Speaker 1: in terms of providing data. So I am not on 338 00:20:14,040 --> 00:20:16,159 Speaker 1: the record is saying that this is a replacement for 339 00:20:16,200 --> 00:20:18,680 Speaker 1: government data. I don't think that. I think that this 340 00:20:18,800 --> 00:20:22,919 Speaker 1: is a private sector view, uh that is highly complementary 341 00:20:22,960 --> 00:20:25,840 Speaker 1: to government resources. And it doesn't have to be an 342 00:20:25,880 --> 00:20:28,640 Speaker 1: either or it should be an And so this audience 343 00:20:28,680 --> 00:20:31,960 Speaker 1: is sophisticated. They're really good with numbers. They can hold 344 00:20:31,960 --> 00:20:35,200 Speaker 1: two numbers together. And what we've tried to do at 345 00:20:35,240 --> 00:20:37,720 Speaker 1: a DP is make it as easy as possible. So 346 00:20:38,000 --> 00:20:41,360 Speaker 1: when we launched the new n e R, we did 347 00:20:41,400 --> 00:20:45,880 Speaker 1: it with twelve years of weekly data, cut by sector, 348 00:20:46,040 --> 00:20:51,399 Speaker 1: cut by geography, industry, and establishment size. So it's really 349 00:20:51,400 --> 00:20:55,000 Speaker 1: an opportunity dig into the numbers c where the n 350 00:20:55,040 --> 00:20:57,600 Speaker 1: E R and the BLS matchup, see where they differ, 351 00:20:57,680 --> 00:21:00,480 Speaker 1: see how it performs over the business cycle. And we're 352 00:21:00,520 --> 00:21:03,480 Speaker 1: really excited to be able to provide that level of detail. 353 00:21:03,800 --> 00:21:06,119 Speaker 1: And and last note on this, we did it in 354 00:21:06,160 --> 00:21:10,240 Speaker 1: collaboration was the Stanford Digital Economy Lab. Standard has been 355 00:21:10,280 --> 00:21:13,280 Speaker 1: a great partner, but we wanted to make the methodology 356 00:21:13,359 --> 00:21:17,320 Speaker 1: as rigorous um and transparent as possible, so partnering was 357 00:21:17,400 --> 00:21:20,639 Speaker 1: important for us. Can you talk more about the differences 358 00:21:20,680 --> 00:21:23,320 Speaker 1: between your number and the b l S number because 359 00:21:23,640 --> 00:21:26,639 Speaker 1: you because your yours comes out two days before the 360 00:21:26,680 --> 00:21:30,959 Speaker 1: b S BLS number, inevitably somebody tends to point out 361 00:21:31,000 --> 00:21:33,359 Speaker 1: that there is a discrepancy between the two, that they 362 00:21:33,359 --> 00:21:36,080 Speaker 1: don't always match up, and sometimes the gap is pretty wide. 363 00:21:36,080 --> 00:21:37,600 Speaker 1: So maybe you can tell us a little bit more 364 00:21:37,600 --> 00:21:40,960 Speaker 1: about that lately. And you shouldn't expect them to match 365 00:21:41,080 --> 00:21:44,879 Speaker 1: up because they're totally different samples. The BLS is based 366 00:21:44,880 --> 00:21:48,960 Speaker 1: on the c S Survey run by the Census Department, 367 00:21:48,960 --> 00:21:52,520 Speaker 1: which essentially asked establishments how many people did you pay 368 00:21:52,560 --> 00:21:57,159 Speaker 1: this week? Right? So to survey data, and there is 369 00:21:57,200 --> 00:22:00,800 Speaker 1: some issues around survey response rates that have been um 370 00:22:00,920 --> 00:22:03,520 Speaker 1: made more apparent during the pandemic. We're all feeling a 371 00:22:03,560 --> 00:22:08,280 Speaker 1: little survey fatigue these days, and establishments are no different. UM. 372 00:22:08,359 --> 00:22:11,840 Speaker 1: So what the ADP data does is it it says 373 00:22:12,560 --> 00:22:16,720 Speaker 1: not how many employees did you pay this week? Establishment, 374 00:22:16,760 --> 00:22:21,160 Speaker 1: but we count how many employees are actually on your payroll. 375 00:22:21,520 --> 00:22:25,600 Speaker 1: So it's a slight difference in and also perspective UM. 376 00:22:25,800 --> 00:22:29,159 Speaker 1: And it's based on actual pay data. So if you 377 00:22:29,200 --> 00:22:31,359 Speaker 1: look at your paycheck and you get that and direct 378 00:22:31,359 --> 00:22:34,879 Speaker 1: deposit UM, that's what we're counting basically for all of 379 00:22:34,920 --> 00:22:38,080 Speaker 1: our establishments. But the great thing about the number is 380 00:22:38,440 --> 00:22:41,000 Speaker 1: we have such a breath and scale that we actually 381 00:22:41,119 --> 00:22:46,480 Speaker 1: rewait that number with the Quarterly Census of Employment and Wages. 382 00:22:46,680 --> 00:22:50,080 Speaker 1: I remembered it q c W, which is a near 383 00:22:50,160 --> 00:22:53,800 Speaker 1: consensus of all the establishments in the countries, about nine 384 00:22:53,920 --> 00:22:58,040 Speaker 1: d upwards of you know, fool data on all the 385 00:22:58,080 --> 00:23:01,920 Speaker 1: businesses in the US. And so now we have something 386 00:23:02,000 --> 00:23:05,560 Speaker 1: that is a private sector view, but it is really 387 00:23:05,640 --> 00:23:09,199 Speaker 1: waited to to uh look at the national average. And 388 00:23:09,200 --> 00:23:12,760 Speaker 1: I realized that that's a long answer, so any more detail. 389 00:23:12,800 --> 00:23:15,200 Speaker 1: We have the technical note on our website ADP or 390 00:23:15,280 --> 00:23:18,280 Speaker 1: I dot not dot org. And thank you for not 391 00:23:18,400 --> 00:23:20,119 Speaker 1: like cutting me off, because I think I would have 392 00:23:20,119 --> 00:23:22,800 Speaker 1: cut myself off if I had gone on on something. 393 00:23:23,280 --> 00:23:28,640 Speaker 1: But you guys are so so polite. I'm actually not 394 00:23:28,720 --> 00:23:32,320 Speaker 1: that polite because I'm I said, inevitably somebody points out 395 00:23:32,320 --> 00:23:34,600 Speaker 1: the discrepancy between the A d P and the BLS. 396 00:23:35,040 --> 00:23:38,920 Speaker 1: I'm that person. Yeah, yeah, don't don't worry, Nila. DNA 397 00:23:39,000 --> 00:23:42,600 Speaker 1: is not played at all. I'm not sorry, Nila. Well, Nila, 398 00:23:42,720 --> 00:23:45,959 Speaker 1: I know um and in sort of past stops at 399 00:23:46,000 --> 00:23:48,679 Speaker 1: your career, maybe more so, but you definitely keep a 400 00:23:48,800 --> 00:23:51,480 Speaker 1: pretty close eye on the housing market too, and we've 401 00:23:51,560 --> 00:23:56,560 Speaker 1: seen obviously, uh some softening. They're uh not only in 402 00:23:56,640 --> 00:24:00,240 Speaker 1: home sales, but actual prices have finally seemed to come 403 00:24:00,280 --> 00:24:03,640 Speaker 1: off the boil a little bit. I forget the supperlative, 404 00:24:03,760 --> 00:24:06,800 Speaker 1: like the biggest you know, month over month drop in 405 00:24:06,800 --> 00:24:09,680 Speaker 1: in over a decade or something, the less case Shiller Index. 406 00:24:10,760 --> 00:24:15,240 Speaker 1: How do you see housing um sort of landing from 407 00:24:15,280 --> 00:24:18,600 Speaker 1: this red hot housing market that we had, And are 408 00:24:18,720 --> 00:24:23,200 Speaker 1: there sort of knock on effects to GDP and inflation 409 00:24:23,760 --> 00:24:28,720 Speaker 1: that could come as a result the tail when to 410 00:24:29,000 --> 00:24:34,199 Speaker 1: housing is long. I'll start their demographics is destiny in 411 00:24:34,200 --> 00:24:36,600 Speaker 1: the housing market. And you have a whole bunch of 412 00:24:36,640 --> 00:24:40,720 Speaker 1: young people, millennials who still want to buy a house. Yes, 413 00:24:40,760 --> 00:24:44,199 Speaker 1: they've been stunned a little by the rapid increase in 414 00:24:44,240 --> 00:24:48,360 Speaker 1: both house prices and mortgage rates, but that's demographic tail 415 00:24:48,480 --> 00:24:52,280 Speaker 1: and it's still singing loud and clear, and and so 416 00:24:53,119 --> 00:24:57,280 Speaker 1: to me, I think the fact that where we are 417 00:24:57,320 --> 00:25:00,080 Speaker 1: actually saying weakness in the economy is like the I 418 00:25:00,240 --> 00:25:04,400 Speaker 1: was hanging through right because you already had a stricken 419 00:25:04,520 --> 00:25:08,560 Speaker 1: market that has been undersupply chronic lander supply for over 420 00:25:08,600 --> 00:25:13,160 Speaker 1: a decade. So this is the supply shortage story and housing. 421 00:25:13,359 --> 00:25:16,280 Speaker 1: It's not about the pandemic. It's not about recent rises 422 00:25:16,320 --> 00:25:20,160 Speaker 1: in lumber. This has been going on for ten years 423 00:25:20,920 --> 00:25:24,120 Speaker 1: um and it was only because rates were supernaturally low 424 00:25:24,200 --> 00:25:27,000 Speaker 1: that anybody could afford a house. And now you've taken 425 00:25:27,040 --> 00:25:31,040 Speaker 1: that away. But it doesn't just affect demand, it affects supply. 426 00:25:31,119 --> 00:25:34,119 Speaker 1: If you look at home builder sentiment, it has plummeted 427 00:25:34,320 --> 00:25:38,320 Speaker 1: because not only has um the cost of constructing of 428 00:25:38,520 --> 00:25:41,720 Speaker 1: house gone up, so has their financing costs. So you're 429 00:25:41,760 --> 00:25:46,480 Speaker 1: depressing the entire housing market. With a higher interest rate, 430 00:25:46,520 --> 00:25:50,439 Speaker 1: it's become smaller, and yet you still have this huge 431 00:25:50,520 --> 00:25:53,960 Speaker 1: tail when coming. So I think of this as temporary. 432 00:25:54,359 --> 00:25:59,240 Speaker 1: Whatever we're seeing in prices, it will um readjust again 433 00:25:59,560 --> 00:26:02,320 Speaker 1: once people get over the sticker shock of a higher 434 00:26:02,359 --> 00:26:08,480 Speaker 1: mortgage um and we won't fix it unless we build 435 00:26:08,520 --> 00:26:12,639 Speaker 1: more homes, especially at the affordable sector. So last comment 436 00:26:12,720 --> 00:26:14,360 Speaker 1: on this. You know we used to have a housing 437 00:26:14,400 --> 00:26:18,480 Speaker 1: policy in the US, and you know it survived both 438 00:26:18,520 --> 00:26:24,000 Speaker 1: Democratic and Republican administrations. We don't really have a national 439 00:26:24,080 --> 00:26:27,720 Speaker 1: policy around homeownership the way we did when that you 440 00:26:27,800 --> 00:26:31,119 Speaker 1: started my career. It's almost like it's a forgotten goal 441 00:26:31,240 --> 00:26:34,320 Speaker 1: of the of the American dream to be a homeowner. 442 00:26:34,440 --> 00:26:36,439 Speaker 1: Have we given up on it? What would you like 443 00:26:36,480 --> 00:26:40,640 Speaker 1: that policy to to look like? I think it starts 444 00:26:40,680 --> 00:26:45,280 Speaker 1: with affordable housing, whether it's rental or ownership. But because 445 00:26:45,280 --> 00:26:48,160 Speaker 1: it used to be back in the olden times, like 446 00:26:50,720 --> 00:26:56,800 Speaker 1: maybe two thousands um, home ownership was your your path 447 00:26:56,880 --> 00:26:59,680 Speaker 1: to the middle class. If you bought a home and 448 00:26:59,800 --> 00:27:02,679 Speaker 1: you had that for savings and it grew over time, 449 00:27:03,040 --> 00:27:06,320 Speaker 1: then you created wealth for you and your family. Now 450 00:27:06,400 --> 00:27:08,560 Speaker 1: you need wealth to buy a house. It's like, let 451 00:27:08,560 --> 00:27:11,159 Speaker 1: me go create my wealth first, maybe in bitcoin or 452 00:27:11,200 --> 00:27:13,119 Speaker 1: the stuff market, and then I can afford a house. 453 00:27:13,640 --> 00:27:16,639 Speaker 1: We've inverted the American dream where you have to get 454 00:27:16,920 --> 00:27:20,000 Speaker 1: wealthy first before you can become a homeowner. And I 455 00:27:20,040 --> 00:27:22,600 Speaker 1: think that that's part of the discontent that you're seeing 456 00:27:22,600 --> 00:27:25,439 Speaker 1: show up in the consumer sentiment numbers, and that's not 457 00:27:25,480 --> 00:27:28,520 Speaker 1: going to be solved by just getting inflation down. That's 458 00:27:28,600 --> 00:27:30,600 Speaker 1: kind of something that we're stuck with, and we need 459 00:27:30,640 --> 00:27:49,680 Speaker 1: to actually be intentional about affordable housing. I'm really happy 460 00:27:49,720 --> 00:27:51,560 Speaker 1: you brought this up because one of the questions I 461 00:27:51,600 --> 00:27:54,200 Speaker 1: had for you is about where and how we're seeing 462 00:27:54,280 --> 00:27:59,400 Speaker 1: the unequal effects of the FED hiking rates. So housing 463 00:27:59,400 --> 00:28:01,800 Speaker 1: potentially is one area. I don't know if you had 464 00:28:01,840 --> 00:28:03,760 Speaker 1: something else on mine. I do know you tracked this 465 00:28:03,880 --> 00:28:10,639 Speaker 1: very closely. Credit card costs. I mean, uh, it's the 466 00:28:11,160 --> 00:28:14,439 Speaker 1: reason why the country has stayed a flow. It's on 467 00:28:14,480 --> 00:28:16,879 Speaker 1: the backs of the consumer. It's always the case, but 468 00:28:16,920 --> 00:28:20,520 Speaker 1: the consumer has been incredible. It's like higher egg prices, okay, 469 00:28:20,560 --> 00:28:23,960 Speaker 1: I'll buy it. Higher airline care is okay, I'll buy it. 470 00:28:24,240 --> 00:28:27,200 Speaker 1: But they're starting to buy it less out of savings 471 00:28:27,200 --> 00:28:31,640 Speaker 1: and more on credit card balances, and as someone who 472 00:28:31,720 --> 00:28:35,240 Speaker 1: has studied Canada and looked at what the effect of 473 00:28:35,320 --> 00:28:37,840 Speaker 1: consumer debt can do to an economy, and this is 474 00:28:37,880 --> 00:28:41,480 Speaker 1: before the pandemic. Are friendly neighbors to the north or 475 00:28:41,520 --> 00:28:45,240 Speaker 1: a tale sign of what could happen if consumer debt 476 00:28:45,240 --> 00:28:48,280 Speaker 1: in the United States starts to rise and then explode 477 00:28:48,560 --> 00:28:51,320 Speaker 1: to keep up with the current piece of spending. So 478 00:28:51,480 --> 00:28:55,840 Speaker 1: I think it's really a watch point, especially for those 479 00:28:55,920 --> 00:28:58,400 Speaker 1: in the lower income strata, because those are the ones 480 00:28:58,440 --> 00:29:01,480 Speaker 1: who are affected most by inflat ship, by higher rental, 481 00:29:02,080 --> 00:29:05,080 Speaker 1: higher rents, and higher food prices and gas prices. So 482 00:29:05,360 --> 00:29:09,040 Speaker 1: guess hopefully they'll get some relief on that. Well, one 483 00:29:09,080 --> 00:29:12,080 Speaker 1: area where there is uh some debt relief is the 484 00:29:12,160 --> 00:29:16,520 Speaker 1: student loan issue. Um with the you know, the Biden 485 00:29:16,560 --> 00:29:20,360 Speaker 1: program to forgive uh some student loans. How do you 486 00:29:20,360 --> 00:29:23,640 Speaker 1: see that playing out? Is that gonna add some inflationary 487 00:29:23,760 --> 00:29:27,400 Speaker 1: risks or is it you know, going to uh sort 488 00:29:27,440 --> 00:29:29,800 Speaker 1: of have a more positive effect on the on the 489 00:29:29,840 --> 00:29:32,560 Speaker 1: growth side that will would out weigh any inflation concern. 490 00:29:33,880 --> 00:29:37,080 Speaker 1: It's a great question. I don't know. I'll just say 491 00:29:37,080 --> 00:29:40,560 Speaker 1: it frankly. I wrote about student debt for goodness in 492 00:29:40,640 --> 00:29:44,160 Speaker 1: my Main Street macro blog last week. And you know, 493 00:29:44,640 --> 00:29:46,880 Speaker 1: the question of whether student did is a mountain or 494 00:29:46,920 --> 00:29:50,320 Speaker 1: a mole hill when it comes to inflation is still 495 00:29:50,360 --> 00:29:54,040 Speaker 1: to be determined, because who knows if people You know, 496 00:29:54,360 --> 00:29:58,320 Speaker 1: there's been a forbearance on student debt repayment for for 497 00:29:58,360 --> 00:30:01,800 Speaker 1: a while now, um so forgiving it out right, who 498 00:30:01,800 --> 00:30:04,160 Speaker 1: knows what effect that will have? Will people buy more 499 00:30:04,240 --> 00:30:07,600 Speaker 1: refrigerators because they don't have to pay and they haven't 500 00:30:07,600 --> 00:30:10,720 Speaker 1: been paying a student loan debt? I do not know that. Um, 501 00:30:10,760 --> 00:30:13,800 Speaker 1: I don't know what the marginal increase on inflation will be. 502 00:30:14,000 --> 00:30:16,720 Speaker 1: What I do know, though, is that people with college 503 00:30:16,760 --> 00:30:20,040 Speaker 1: degrees are much better served in the recession than people without. 504 00:30:20,520 --> 00:30:23,720 Speaker 1: I do know that college enrollment is dropping, and I 505 00:30:23,760 --> 00:30:26,520 Speaker 1: do know that productivity in the US is also on 506 00:30:26,560 --> 00:30:29,920 Speaker 1: the decline. So we need a skilled workforce that I 507 00:30:30,000 --> 00:30:33,280 Speaker 1: do know, and how to get there is an important 508 00:30:33,560 --> 00:30:37,160 Speaker 1: question to ask for the future. Whether or not college 509 00:30:37,200 --> 00:30:40,200 Speaker 1: is out of reach for people these days is another 510 00:30:40,320 --> 00:30:44,360 Speaker 1: question that I think deserves some policy consideration. So, Nila, 511 00:30:44,600 --> 00:30:46,600 Speaker 1: before the pandemic, you and I used to get together 512 00:30:46,640 --> 00:30:48,680 Speaker 1: all the time at the Bloomberg golfices and we would 513 00:30:48,680 --> 00:30:50,840 Speaker 1: talk about the stock market and drink coffee. We would 514 00:30:50,920 --> 00:30:54,240 Speaker 1: drink coffee, yes, so much coffee from the Bloomberg golfice is, 515 00:30:55,040 --> 00:30:58,080 Speaker 1: and we would talk about a love of New Jersey, right, 516 00:30:58,440 --> 00:31:01,600 Speaker 1: I think, yeah, very fond memories of that. But anyway, 517 00:31:01,600 --> 00:31:03,960 Speaker 1: you said recently in a note that the that the 518 00:31:04,000 --> 00:31:07,040 Speaker 1: market isn't necessarily in lock step with the economy, and 519 00:31:07,040 --> 00:31:08,440 Speaker 1: I wanted to ask you about this and what you 520 00:31:08,480 --> 00:31:12,800 Speaker 1: mean meant by it. I think the market is reflecting 521 00:31:12,960 --> 00:31:17,200 Speaker 1: some of the angst and the uncertainty that's been on 522 00:31:17,360 --> 00:31:20,720 Speaker 1: Main Street all along. Now, so I'm gonna actually reverse 523 00:31:20,800 --> 00:31:25,000 Speaker 1: my position on the market. I think the market was acting, 524 00:31:25,040 --> 00:31:29,040 Speaker 1: in certainty fortified by the fact that they felt like 525 00:31:29,080 --> 00:31:32,520 Speaker 1: they understood what the Fed would do, the inflation would 526 00:31:32,520 --> 00:31:35,760 Speaker 1: come down and there soon be a pivot. And I 527 00:31:35,800 --> 00:31:38,920 Speaker 1: think there's now a recognition that that may not happen, 528 00:31:39,080 --> 00:31:43,480 Speaker 1: or it may take longer to happen than previously desires. 529 00:31:43,520 --> 00:31:45,560 Speaker 1: Because what's happened I think over the course of that 530 00:31:45,600 --> 00:31:48,840 Speaker 1: month is that we got another CPI reading and the 531 00:31:48,880 --> 00:31:51,840 Speaker 1: core inflation bumped up instead of going down. And that 532 00:31:52,280 --> 00:31:56,400 Speaker 1: was surprising. Um. It was even surprising to me who 533 00:31:56,800 --> 00:32:01,760 Speaker 1: wasn't as sanguine about inflation. The inflation story is what 534 00:32:01,840 --> 00:32:04,480 Speaker 1: I what I saw in the market. So I actually 535 00:32:04,520 --> 00:32:08,400 Speaker 1: do think that the markets are reflecting uncertainty. I don't 536 00:32:08,400 --> 00:32:10,520 Speaker 1: know how long the markets will do that, but that's 537 00:32:10,560 --> 00:32:15,240 Speaker 1: the same uncertainty that mainStreet is feeling right now. Right Well, 538 00:32:15,360 --> 00:32:19,600 Speaker 1: Nila Richardson, chief economist at ADP, is always a treat 539 00:32:19,680 --> 00:32:24,560 Speaker 1: to get your take on the world and all things 540 00:32:25,080 --> 00:32:27,880 Speaker 1: involving the economy. But I have to say, as a 541 00:32:27,920 --> 00:32:29,920 Speaker 1: veteran of this show, you know, we cannot let you 542 00:32:30,000 --> 00:32:33,960 Speaker 1: go until we hear about the craziest thing you saw 543 00:32:34,120 --> 00:32:39,080 Speaker 1: in markets this week. Uh so, I'm confident you came prepared. 544 00:32:39,200 --> 00:32:41,960 Speaker 1: But let's let's start with you. Okay, you're gonna love 545 00:32:42,000 --> 00:32:45,040 Speaker 1: this one, all right. I think there's a company called 546 00:32:45,560 --> 00:32:51,200 Speaker 1: horse Kicks Kicks. They're making custom designed high end sneakers 547 00:32:51,360 --> 00:32:56,200 Speaker 1: for I give you this. No, I had to send 548 00:32:56,200 --> 00:32:58,840 Speaker 1: it to her actually because I told her, go get 549 00:32:58,880 --> 00:33:01,600 Speaker 1: your horse a sneak skis all right, Now, what's our 550 00:33:01,720 --> 00:33:04,840 Speaker 1: market angle? Well, it's just okay, the price and everything, 551 00:33:04,840 --> 00:33:06,880 Speaker 1: it's just a crazy story. So I had to I 552 00:33:06,920 --> 00:33:09,360 Speaker 1: had to use this. The company builds itself as the 553 00:33:09,400 --> 00:33:15,320 Speaker 1: world's first online custom sneaker retailer exclusively for horses. They 554 00:33:15,400 --> 00:33:20,480 Speaker 1: have hoof sized versions of classic sneakers like Air Jordan's. 555 00:33:20,720 --> 00:33:25,360 Speaker 1: I'm not joking. They're really, like, incredibly funny looking, and 556 00:33:25,480 --> 00:33:33,760 Speaker 1: they cost guess how much per shoe? A thousand per shoe, 557 00:33:33,920 --> 00:33:37,560 Speaker 1: and a horse has at least two needs to two shoes, right, 558 00:33:37,640 --> 00:33:39,680 Speaker 1: couldn't need to strap on a regular pair of Jordan. 559 00:33:41,160 --> 00:33:43,880 Speaker 1: I know you would think, yeah, no, they're actually so 560 00:33:43,920 --> 00:33:47,160 Speaker 1: when you look at the pictures, they're tiny. They're really small, 561 00:33:47,200 --> 00:33:51,280 Speaker 1: like little children sneakers or something. So four five thousands 562 00:33:51,320 --> 00:33:55,000 Speaker 1: of yeah, my goodness, Yeah, to make your horse look 563 00:33:55,240 --> 00:33:58,560 Speaker 1: very stylish. Had that all right? That's pretty good one. 564 00:33:58,960 --> 00:34:01,880 Speaker 1: I'll give you that, all right, And that's pretty stiff competition. 565 00:34:01,920 --> 00:34:03,840 Speaker 1: But but I don't know what do you got first? 566 00:34:03,840 --> 00:34:07,040 Speaker 1: You got something crazier than uh whore Sarah Jordan's. I 567 00:34:07,080 --> 00:34:09,600 Speaker 1: don't know if I can top that. I mean, I'll 568 00:34:09,600 --> 00:34:13,160 Speaker 1: stick with there's so many crazy things going on that 569 00:34:13,239 --> 00:34:17,960 Speaker 1: you are looking for crazy thing data points. I am, 570 00:34:18,000 --> 00:34:21,319 Speaker 1: I am, I'm taken with this. This idea that California 571 00:34:21,360 --> 00:34:24,480 Speaker 1: has replaced Germany as the fourth largest economy, that is 572 00:34:24,520 --> 00:34:28,360 Speaker 1: pretty interesting. Yeah, it is interesting, And I wonder what 573 00:34:28,440 --> 00:34:33,360 Speaker 1: California does with that information, because I mean, that's a 574 00:34:33,440 --> 00:34:39,279 Speaker 1: lot of responsibility for California right and right now. Um, 575 00:34:39,440 --> 00:34:42,520 Speaker 1: they've thrown a lot of political weight into the Supreme 576 00:34:42,560 --> 00:34:47,279 Speaker 1: Court of protecting pregnant pigs. I am curious. Being the 577 00:34:47,360 --> 00:34:50,879 Speaker 1: fourth largest economy in the world, what other things do 578 00:34:50,920 --> 00:34:54,080 Speaker 1: we think California will do with that kind of stature. 579 00:34:54,360 --> 00:34:57,000 Speaker 1: So I guess I posted as a question for the 580 00:34:57,040 --> 00:35:01,080 Speaker 1: markets California do next, I would saying I think that 581 00:35:01,200 --> 00:35:04,319 Speaker 1: was our own Matt Winkler here, bloombergy. That that's you 582 00:35:04,400 --> 00:35:06,640 Speaker 1: didn't see that? That? That's really good. I like, it's 583 00:35:06,640 --> 00:35:08,880 Speaker 1: pretty good. I mean it makes sense. It's you know, 584 00:35:08,960 --> 00:35:14,239 Speaker 1: it's huge land wise, it's huge population wise. Uh, it's 585 00:35:14,239 --> 00:35:15,719 Speaker 1: still a kind of valley and everything. You know, it 586 00:35:16,239 --> 00:35:20,759 Speaker 1: makes sense. Almonds, Almonds, Yeah, almonds, Yeah, almonds are a 587 00:35:20,840 --> 00:35:25,960 Speaker 1: big deal. Cauliflowers. They grew a lot of coliflowers. Oranges. 588 00:35:26,120 --> 00:35:28,439 Speaker 1: All right, two good crazy things. I like them both. 589 00:35:29,160 --> 00:35:31,640 Speaker 1: I'll give you mine. And first I have to ask, 590 00:35:32,239 --> 00:35:34,880 Speaker 1: what's the most you've ever paid for a pair of earrings? 591 00:35:36,040 --> 00:35:38,440 Speaker 1: I've never bought earrings Tom, you've never bought earrings and 592 00:35:38,480 --> 00:35:41,440 Speaker 1: you do not have pier stairs. I've never noticed you 593 00:35:41,520 --> 00:35:44,040 Speaker 1: got the headphones. You always have the headphones on, but 594 00:35:44,160 --> 00:35:47,680 Speaker 1: you never bought them, not even wants you make your own. No, 595 00:35:47,800 --> 00:35:50,640 Speaker 1: I just don't wear them. Right, But you do have 596 00:35:50,719 --> 00:35:54,120 Speaker 1: Pierce steers. But how do they stay? I don't know. 597 00:35:54,360 --> 00:35:57,640 Speaker 1: I've just never won them. More importantly, do you nil out? 598 00:35:57,760 --> 00:35:59,719 Speaker 1: I think you have, if I remember correctly, you have 599 00:35:59,760 --> 00:36:03,160 Speaker 1: song is not daughters? Right, So I have sons who 600 00:36:03,200 --> 00:36:07,319 Speaker 1: I taught to shop very well for their mama. What 601 00:36:07,400 --> 00:36:09,560 Speaker 1: do you think the most they've ever spent on a 602 00:36:09,680 --> 00:36:12,799 Speaker 1: parier rings for mom is over at that Short Hills Mall. 603 00:36:12,840 --> 00:36:14,759 Speaker 1: I know you're a high roller at the Short Hills Mall, 604 00:36:15,400 --> 00:36:19,160 Speaker 1: but my small it is a nice sman my my 605 00:36:19,239 --> 00:36:22,439 Speaker 1: sons do enjoy that. It's not my my shopping cart, 606 00:36:22,520 --> 00:36:27,200 Speaker 1: but which they do enjoy it. I would say, given there, 607 00:36:27,920 --> 00:36:30,000 Speaker 1: since I know how much they make in allowance, I 608 00:36:30,000 --> 00:36:34,239 Speaker 1: would say the most is for Christmas, maybe fifty bucks. 609 00:36:34,280 --> 00:36:37,840 Speaker 1: That sounds reasonable to me. Yeah, I have no idea. 610 00:36:38,200 --> 00:36:40,759 Speaker 1: My wife I bought one pair of diamond earrings that 611 00:36:40,800 --> 00:36:48,880 Speaker 1: were forversary, but otherwise, Okay, what if I were to 612 00:36:48,920 --> 00:36:52,439 Speaker 1: tell you don't know who Blue Ivy is Beyonce's child. 613 00:36:52,480 --> 00:36:55,720 Speaker 1: Beyonce's child. Yonce and jay Z have a child named 614 00:36:55,800 --> 00:36:58,120 Speaker 1: Blue Ivy. Everybody knows this. I thought for a second 615 00:36:58,200 --> 00:37:01,040 Speaker 1: you were trying to stump USh is ten years old. 616 00:37:01,520 --> 00:37:03,400 Speaker 1: I don't know, you know. I mean, I know I'm 617 00:37:03,440 --> 00:37:05,319 Speaker 1: a hip, hip old guy. I don't know about you, though, 618 00:37:05,360 --> 00:37:07,920 Speaker 1: I don't you know. I mean, I mean it's Beyonce, 619 00:37:08,640 --> 00:37:12,399 Speaker 1: So Beyonce's daughter, Blue Ivy and jay Z's thoughter as well. 620 00:37:13,040 --> 00:37:17,600 Speaker 1: You know. She went earring shopping at what was it is? 621 00:37:17,600 --> 00:37:20,480 Speaker 1: Some kind of it was the Wearable Art Gala in 622 00:37:20,600 --> 00:37:24,400 Speaker 1: Los Angeles. Uh an auction which gives it our market angle. 623 00:37:24,960 --> 00:37:28,160 Speaker 1: Uh And the story's courtesy of of Venity Fair. She 624 00:37:28,320 --> 00:37:33,120 Speaker 1: bought a pair of diamond ear rings. Um from some 625 00:37:33,280 --> 00:37:36,040 Speaker 1: designer who I think I should uh know who she is? 626 00:37:36,080 --> 00:37:42,160 Speaker 1: But Lorraine Schwartz, Lorene Schwartz, famous earring designer. What do 627 00:37:42,200 --> 00:37:45,440 Speaker 1: you think Blue Ivy paid for a pair of diamond 628 00:37:45,440 --> 00:37:48,759 Speaker 1: earrings at the Wearable Art Galla in Los Angeles? Why? 629 00:37:49,080 --> 00:37:53,920 Speaker 1: She's ten years old? She was the better, She had 630 00:37:53,960 --> 00:37:57,360 Speaker 1: the paddle and she she hit the bid. Uh. I 631 00:37:57,360 --> 00:37:59,719 Speaker 1: don't know. I imagine Blue Ivy's got some revenue coming 632 00:37:59,719 --> 00:38:03,359 Speaker 1: in CREP speaking engagements, and I think she you know, 633 00:38:04,920 --> 00:38:07,799 Speaker 1: sorry for the prices precise. What do you think blu 634 00:38:07,920 --> 00:38:11,240 Speaker 1: Ivy spends on a pair of diamond earrings at auction? 635 00:38:11,520 --> 00:38:15,319 Speaker 1: Am I going first? You always go first? Yes? Yes, okay, 636 00:38:15,920 --> 00:38:19,520 Speaker 1: it has to be some absurd amount. But I thought 637 00:38:19,600 --> 00:38:23,800 Speaker 1: fifty was was an absurd amount. Yeah, okay, but obviously 638 00:38:23,920 --> 00:38:28,640 Speaker 1: bluv won't spend that little. Okay, let's go with seventy dollars. 639 00:38:28,840 --> 00:38:31,839 Speaker 1: Seventy five thousand dollars. Uh, Neil, what do you think 640 00:38:31,920 --> 00:38:33,680 Speaker 1: you're taking the I'll let you. You can do the 641 00:38:33,719 --> 00:38:36,200 Speaker 1: over the under on seventy five thou, but if you 642 00:38:36,239 --> 00:38:42,239 Speaker 1: go over you and it's under, then you lose, right, Yeah, yeah, yeah, 643 00:38:42,360 --> 00:38:45,000 Speaker 1: I know. Whatever the result, my sons are going to 644 00:38:45,040 --> 00:38:51,120 Speaker 1: ask for a higher allows. Since this is a newsy thing, 645 00:38:51,160 --> 00:38:55,239 Speaker 1: I'm gonna say over. But I can't imagine how much 646 00:38:55,360 --> 00:38:58,160 Speaker 1: over it would be From seventy, I'll go up to hundred. 647 00:38:58,360 --> 00:39:01,200 Speaker 1: All right, I think you in with the over eighty 648 00:39:01,239 --> 00:39:05,239 Speaker 1: thou smackers on a pair of diamond he Wow, I 649 00:39:05,280 --> 00:39:10,040 Speaker 1: was closed, Yes, you were close, pretty close. You're pretty close. 650 00:39:10,239 --> 00:39:12,680 Speaker 1: You win. I think you win because you were closer 651 00:39:12,680 --> 00:39:14,839 Speaker 1: that way. Wait, you can't go over? Yeah I win 652 00:39:15,239 --> 00:39:20,520 Speaker 1: a right, yeah, sorry you aners. Okay, I was gonna 653 00:39:20,520 --> 00:39:22,919 Speaker 1: say ten to be honest, and then you you broke 654 00:39:22,960 --> 00:39:29,760 Speaker 1: out with the seventy five thousand. I was like, okay, 655 00:39:27,239 --> 00:39:34,280 Speaker 1: but ten year old time of hearings. Well, it'll only 656 00:39:34,320 --> 00:39:37,239 Speaker 1: go up from here. I'm sure I'll probably worth more 657 00:39:37,320 --> 00:39:39,680 Speaker 1: now that she that she owns what goes on, right, 658 00:39:39,840 --> 00:39:44,239 Speaker 1: I just cannot imagine a ten year old. Every sort 659 00:39:44,280 --> 00:39:46,880 Speaker 1: of earring or piece of jewelry my kids owned at 660 00:39:46,880 --> 00:39:51,719 Speaker 1: that age is you know, handmade. It's covered in you know, 661 00:39:51,800 --> 00:39:56,000 Speaker 1: melted gummy bears and uh made an arts and craft right, 662 00:39:56,040 --> 00:39:58,279 Speaker 1: and just completely lost. So we'll see what to keep 663 00:39:58,320 --> 00:40:00,880 Speaker 1: track of. I want to go to the playground and 664 00:40:00,920 --> 00:40:03,680 Speaker 1: just follow her around. If she's wearing those eighty dollar 665 00:40:03,760 --> 00:40:09,160 Speaker 1: earrings in case she drops, well, congratulations to Blue Ivy 666 00:40:09,239 --> 00:40:13,759 Speaker 1: on her eighty dollar diamonds, and she is welcome to 667 00:40:13,840 --> 00:40:18,760 Speaker 1: do all of our Christmas shopping. I know my girls 668 00:40:18,800 --> 00:40:21,759 Speaker 1: have like four earring holes in their ears. They keep 669 00:40:21,920 --> 00:40:24,080 Speaker 1: adding new ones, So I don't know if you need 670 00:40:24,080 --> 00:40:26,640 Speaker 1: an eighty thousand dollar pair for every you have to 671 00:40:26,719 --> 00:40:29,680 Speaker 1: raise their lawns to. Yeah, this is not good news 672 00:40:29,719 --> 00:40:34,120 Speaker 1: for me. It's the bottom lineing the father of three daughters. 673 00:40:34,160 --> 00:40:36,799 Speaker 1: But Niller Richardson, who is a Tirp by the way, 674 00:40:36,880 --> 00:40:40,480 Speaker 1: I'm very happy to say I've got a daughter econ 675 00:40:40,600 --> 00:40:43,160 Speaker 1: major at the University of Maryland, and I'm proud to 676 00:40:43,400 --> 00:40:47,080 Speaker 1: uh proud to share the the Tirp pride with Nila. 677 00:40:47,239 --> 00:40:51,920 Speaker 1: So it's an excellent economic tradition that she has just joined. 678 00:40:52,000 --> 00:40:55,200 Speaker 1: So congratulations, I agree, I agree, thank you. What do 679 00:40:55,280 --> 00:41:01,960 Speaker 1: we say? Go Tirps six and two Bowl eligible and football. 680 00:41:02,080 --> 00:41:06,279 Speaker 1: So that's that's a good record. Yeah, all right, Neil, 681 00:41:06,400 --> 00:41:08,080 Speaker 1: I think that's all our time. Thank you so much. 682 00:41:08,080 --> 00:41:10,440 Speaker 1: It's always a real pleasure to catch up with you, 683 00:41:10,480 --> 00:41:12,160 Speaker 1: and I hope we can do it again, something I 684 00:41:12,280 --> 00:41:14,560 Speaker 1: have so too. Thanks for having me. Thank you, Nila. 685 00:41:23,360 --> 00:41:25,400 Speaker 1: What goes up? We'll be back next week and so 686 00:41:25,520 --> 00:41:27,799 Speaker 1: then you can find us on the Bloomberg Terminal website 687 00:41:27,840 --> 00:41:31,200 Speaker 1: and app or wherever you get your podcasts. We love 688 00:41:31,239 --> 00:41:33,000 Speaker 1: it if you took the time to rate and review 689 00:41:33,040 --> 00:41:35,919 Speaker 1: the show on Apple Podcasts, so more listeners can find 690 00:41:36,000 --> 00:41:38,719 Speaker 1: us and you can find us on Twitter, follow me 691 00:41:38,760 --> 00:41:42,600 Speaker 1: at reag Anonymous, Bill, Donna Hirach is at Bildanna Hirach. 692 00:41:43,280 --> 00:41:47,759 Speaker 1: You can also follow Bloomberg Podcasts at Podcasts. What Goes 693 00:41:47,840 --> 00:41:50,960 Speaker 1: Up is produced by Stacy Wong. Thanks for listening, See 694 00:41:50,960 --> 00:42:07,920 Speaker 1: you next time. Before