1 00:00:00,200 --> 00:00:03,240 Speaker 1: There's a well known gap between men and women when 2 00:00:03,279 --> 00:00:06,120 Speaker 1: it comes to how much people get paid. But here's 3 00:00:06,160 --> 00:00:10,240 Speaker 1: a statistic that's really eye opening. Workers at men's clothing 4 00:00:10,280 --> 00:00:14,360 Speaker 1: stores earned fifty six percent more than employees at retailers 5 00:00:14,360 --> 00:00:17,560 Speaker 1: of women's wear. It's a huge gap and seems troubling 6 00:00:17,600 --> 00:00:20,080 Speaker 1: on the surface, but much of it can be chalked 7 00:00:20,160 --> 00:00:24,160 Speaker 1: up to that classic phrase in economics, supply and demand. 8 00:00:33,479 --> 00:00:37,360 Speaker 1: Welcome to Benchmark. I'm Scott Landman, economics editor with Bloomberg 9 00:00:37,400 --> 00:00:40,840 Speaker 1: News in Washington, and now I'm Daniel Moss, economics writer 10 00:00:40,960 --> 00:00:44,839 Speaker 1: and editor at Bloomberg View in New York. So, Dan, 11 00:00:44,920 --> 00:00:47,080 Speaker 1: let's talk a little bit about something that we don't 12 00:00:47,159 --> 00:00:49,920 Speaker 1: cover too much on this show. Can you tell me 13 00:00:50,000 --> 00:00:52,519 Speaker 1: how you normally shop for clothes? Do you do you 14 00:00:52,560 --> 00:00:54,680 Speaker 1: go to the big department stores or do you frequent 15 00:00:54,760 --> 00:00:57,400 Speaker 1: some of those boutiques that are springing up all over 16 00:00:57,440 --> 00:01:01,880 Speaker 1: your Brooklyn neighborhood. Well, in our idiot neighborhood, it's mainly 17 00:01:02,200 --> 00:01:06,199 Speaker 1: bars and restaurants, so not a lot of clothes shopping there. 18 00:01:06,840 --> 00:01:09,720 Speaker 1: I did buy something the weekend before last, but I 19 00:01:09,840 --> 00:01:13,320 Speaker 1: used a gift card that I was given for Christmas. 20 00:01:13,680 --> 00:01:16,360 Speaker 1: As for me. I don't really shop at stores that 21 00:01:16,400 --> 00:01:19,160 Speaker 1: cater just two men specifically, I probably go to places 22 00:01:19,200 --> 00:01:22,520 Speaker 1: that sell to both men and women. But we're gonna 23 00:01:22,560 --> 00:01:26,520 Speaker 1: talk today about stores that are catering more to high 24 00:01:26,640 --> 00:01:31,240 Speaker 1: end customers and why that's driving this wage gap that 25 00:01:31,319 --> 00:01:33,880 Speaker 1: I was talking about at the top. So let's bring 26 00:01:33,959 --> 00:01:37,160 Speaker 1: in two colleagues who will be our guests today. Katya 27 00:01:37,280 --> 00:01:41,039 Speaker 1: Dmitrieva is a reporter in our Washington bureau covering the 28 00:01:41,080 --> 00:01:44,840 Speaker 1: US economy who recently transferred here from Canada. It's actually 29 00:01:44,840 --> 00:01:47,840 Speaker 1: her second time on the podcast. Last time she was 30 00:01:47,880 --> 00:01:51,640 Speaker 1: in Toronto talking about the crazy real estate market there. Katia, 31 00:01:51,680 --> 00:01:54,560 Speaker 1: thanks for joining us, glad to be here. And our 32 00:01:54,640 --> 00:01:57,360 Speaker 1: other guest is Lindsay Rupp. She's a reporter in our 33 00:01:57,400 --> 00:02:01,400 Speaker 1: New York office covering retail, and she also recently concluded 34 00:02:01,400 --> 00:02:04,919 Speaker 1: a run as co host of Bloomberg's Material World podcast. 35 00:02:05,320 --> 00:02:07,480 Speaker 1: You can listen to all of those episodes wherever you 36 00:02:07,520 --> 00:02:10,280 Speaker 1: like to find podcasts. Lindsay, thanks so much for being 37 00:02:10,320 --> 00:02:13,120 Speaker 1: with us on Benchmark. Thanks for having me. So I 38 00:02:13,120 --> 00:02:15,520 Speaker 1: wanted to talk a little bit about how we got 39 00:02:15,520 --> 00:02:19,560 Speaker 1: this story first. This was pretty simple. We were looking 40 00:02:19,600 --> 00:02:22,880 Speaker 1: at wage data that the Labor Department provides and put 41 00:02:22,919 --> 00:02:25,880 Speaker 1: it into all into a spreadsheet, sorted it by industry, 42 00:02:25,919 --> 00:02:29,120 Speaker 1: and something really funny came up. I noticed that men's 43 00:02:29,160 --> 00:02:33,360 Speaker 1: clothing stores were showing huge increases in wages and the 44 00:02:33,360 --> 00:02:37,800 Speaker 1: wages that women's clothing stores were actually declining. So I 45 00:02:37,840 --> 00:02:39,799 Speaker 1: went to Katya and I said, why don't we write 46 00:02:39,800 --> 00:02:42,800 Speaker 1: an article about this? Could you look into it? So Catchia, 47 00:02:42,840 --> 00:02:45,720 Speaker 1: tell us a little bit about what you found out. Yeah, 48 00:02:45,720 --> 00:02:48,560 Speaker 1: and I remember you bringing that up in the newsroom, 49 00:02:48,560 --> 00:02:51,960 Speaker 1: and I think the reaction was all very shocked, because 50 00:02:52,040 --> 00:02:54,400 Speaker 1: you would think that at least in this industry that's 51 00:02:54,440 --> 00:02:57,320 Speaker 1: been so traditionally catered to women, you would have that 52 00:02:57,600 --> 00:03:01,160 Speaker 1: potentially be reversed. But instead, what I found is that 53 00:03:01,200 --> 00:03:04,320 Speaker 1: if you work at a men's clothing store, especially right now, 54 00:03:04,440 --> 00:03:08,040 Speaker 1: you're likely to be paid a lot more than women's stores. 55 00:03:08,120 --> 00:03:10,799 Speaker 1: And some of it is related to the gender wage gap. 56 00:03:10,960 --> 00:03:13,960 Speaker 1: You see this all across industries in North America, but 57 00:03:14,360 --> 00:03:17,919 Speaker 1: it doesn't really explain in particular, like you said, this 58 00:03:18,240 --> 00:03:22,320 Speaker 1: huge difference that's happened, especially in the last two years. 59 00:03:22,760 --> 00:03:27,239 Speaker 1: So I started to call economists as well as Heidi Hartman, 60 00:03:27,360 --> 00:03:32,200 Speaker 1: who specializes in labor economics, and we talked about this 61 00:03:32,280 --> 00:03:37,360 Speaker 1: issue and when I mentioned supply and demand as affecting 62 00:03:37,400 --> 00:03:40,960 Speaker 1: this market, what can you tell us about that? Well, 63 00:03:41,080 --> 00:03:44,000 Speaker 1: the reality is that there's just a smaller pool of 64 00:03:44,640 --> 00:03:48,640 Speaker 1: men's clothing store workers. There's a smaller pool of men 65 00:03:48,720 --> 00:03:50,920 Speaker 1: to choose from to work in these clothing stores. And 66 00:03:51,040 --> 00:03:53,120 Speaker 1: especially at a time when the labor market is so 67 00:03:53,240 --> 00:03:56,920 Speaker 1: tight already and you're dealing with this smaller pool of workers, 68 00:03:57,440 --> 00:03:59,600 Speaker 1: you have to pay up in order to get them. 69 00:04:00,080 --> 00:04:02,360 Speaker 1: As you said, supplying demand. So if you want to 70 00:04:02,400 --> 00:04:06,720 Speaker 1: get those highly skilled workers for these stores like Hugh 71 00:04:06,800 --> 00:04:10,360 Speaker 1: and Cry where I went in Georgetown in Washington, then 72 00:04:10,440 --> 00:04:13,240 Speaker 1: you're going to have to pay them more. And not 73 00:04:13,360 --> 00:04:17,320 Speaker 1: only are is the demand for these workers higher or 74 00:04:17,320 --> 00:04:20,000 Speaker 1: there's a smaller pool of them, but the sales at 75 00:04:20,080 --> 00:04:24,400 Speaker 1: men's stores are rising and women's where retailers are kind 76 00:04:24,400 --> 00:04:26,520 Speaker 1: of struggling. Lindsey, could you tell us a little bit 77 00:04:26,520 --> 00:04:30,080 Speaker 1: about that. Yeah, absolutely, So. One thing I've been hearing 78 00:04:30,120 --> 00:04:32,840 Speaker 1: a lot in the industry lately is that men are 79 00:04:32,880 --> 00:04:35,640 Speaker 1: the new women all the sudden. Men care a little 80 00:04:35,640 --> 00:04:37,840 Speaker 1: bit more about how they look, and that's showing up 81 00:04:37,839 --> 00:04:40,800 Speaker 1: in beauty it's showing up in apparel, and that's not 82 00:04:40,880 --> 00:04:44,599 Speaker 1: all men, but men of a certain wealth level in particular. 83 00:04:45,120 --> 00:04:47,560 Speaker 1: So that kind of explains a little bit why their 84 00:04:47,680 --> 00:04:51,200 Speaker 1: sales might be rising at a faster rate. But keep 85 00:04:51,200 --> 00:04:54,200 Speaker 1: in mind there's still not a huge portion of the 86 00:04:54,240 --> 00:04:57,720 Speaker 1: overall retail sales. Women still do the bulk of the purchasing, 87 00:04:57,839 --> 00:05:00,200 Speaker 1: they do the bulk of the spending. They're also just 88 00:05:00,279 --> 00:05:03,719 Speaker 1: a lot more women's apparel stores. I mean, apparel retail 89 00:05:03,839 --> 00:05:07,560 Speaker 1: right now is going through this existential crisis. I mean 90 00:05:07,920 --> 00:05:11,240 Speaker 1: it's in total upheaval. In a lot of places, there 91 00:05:11,240 --> 00:05:13,640 Speaker 1: are too many stores, so everybody's trying to figure out, 92 00:05:13,680 --> 00:05:15,960 Speaker 1: how can I have the right number of stores in 93 00:05:16,000 --> 00:05:20,159 Speaker 1: the right locations. They're trying to grapple with online retailers 94 00:05:20,200 --> 00:05:23,000 Speaker 1: who are springing up almost out of nowhere, have very 95 00:05:23,040 --> 00:05:25,960 Speaker 1: low barriers to entry, and even if they only sell 96 00:05:26,440 --> 00:05:29,440 Speaker 1: a couple hundred thousand dollars worth of goods, they're still 97 00:05:29,440 --> 00:05:32,720 Speaker 1: taking away incremental business from these bigger guys. So it's 98 00:05:32,720 --> 00:05:35,360 Speaker 1: a tough time. And just to be clear what we're 99 00:05:35,400 --> 00:05:40,120 Speaker 1: talking about here, are we talking about two employees same store, 100 00:05:40,760 --> 00:05:44,640 Speaker 1: one male, one female. The female gets less or are 101 00:05:44,680 --> 00:05:49,560 Speaker 1: we saying that stores that kate predominantly to men pay 102 00:05:49,640 --> 00:05:53,880 Speaker 1: more than stores that kater predominantly to women. It's stores 103 00:05:53,920 --> 00:05:58,440 Speaker 1: that cater predominantly to men or women. But at these stores, 104 00:05:58,880 --> 00:06:02,160 Speaker 1: what I was told is they're more likely to employ 105 00:06:02,320 --> 00:06:05,640 Speaker 1: people of the same sex. So if it's a men's 106 00:06:05,640 --> 00:06:08,440 Speaker 1: clothing store, they're more likely to hire more men. If 107 00:06:08,440 --> 00:06:12,120 Speaker 1: it's a women's clothing store, more likely to have more women. 108 00:06:12,800 --> 00:06:14,960 Speaker 1: And can you tell us a little bit catya about 109 00:06:15,000 --> 00:06:17,640 Speaker 1: the store you're mentioning. It's called Hugh and Cry and 110 00:06:17,680 --> 00:06:21,560 Speaker 1: it's in DC, and it's kind of a microcosm maybe 111 00:06:21,560 --> 00:06:25,080 Speaker 1: of what's happening in this market right now. Yeah, it 112 00:06:25,160 --> 00:06:28,880 Speaker 1: was very interesting because you are on this main drag 113 00:06:29,600 --> 00:06:32,480 Speaker 1: Wisconsin Avenue, and it's full of retail shops and a 114 00:06:32,480 --> 00:06:35,840 Speaker 1: lot of them are of women's specific retail. And then 115 00:06:35,839 --> 00:06:38,640 Speaker 1: you kind of turn this side street and then down 116 00:06:38,640 --> 00:06:42,040 Speaker 1: a bricklined alleyway, narrow alleyway, you come to the end 117 00:06:42,040 --> 00:06:44,840 Speaker 1: to this door. It's almost like a secret club, and 118 00:06:45,120 --> 00:06:48,320 Speaker 1: here is Human Cry. It's a men's boutique and it's 119 00:06:48,360 --> 00:06:53,120 Speaker 1: outfitted in a very mid century modern furniture, lots of 120 00:06:53,279 --> 00:06:57,160 Speaker 1: hanging art on the wall and you go around. If 121 00:06:57,200 --> 00:06:59,920 Speaker 1: you're shopping there, you just pick items off the shelf, 122 00:07:00,040 --> 00:07:02,640 Speaker 1: can try on in the store. You can also order 123 00:07:02,680 --> 00:07:04,320 Speaker 1: it online if they don't have it, and get it 124 00:07:04,360 --> 00:07:07,120 Speaker 1: delivered to your door or in the store. And it's 125 00:07:07,279 --> 00:07:11,680 Speaker 1: very specific to the client. It's not your traditional you 126 00:07:11,720 --> 00:07:14,880 Speaker 1: walk into a retailer and you know, hey, how's it going. 127 00:07:14,880 --> 00:07:16,720 Speaker 1: Can help you find anything? Can I tell you about 128 00:07:16,720 --> 00:07:18,920 Speaker 1: all the discounts we have in the store. It's more like, 129 00:07:19,000 --> 00:07:20,880 Speaker 1: you come in, do you want me to get you 130 00:07:20,920 --> 00:07:23,520 Speaker 1: anything to drink? Um? What are you looking for? They 131 00:07:23,520 --> 00:07:25,680 Speaker 1: can tell what your size is by looking at you. 132 00:07:26,200 --> 00:07:28,760 Speaker 1: And then they have some clients who come in the 133 00:07:28,840 --> 00:07:31,800 Speaker 1: day of their wedding and they're looking for a white shirt, 134 00:07:32,400 --> 00:07:34,280 Speaker 1: or if they're working on the hill and they happen 135 00:07:34,320 --> 00:07:36,680 Speaker 1: to spill some coffee, they can get a shirt within 136 00:07:36,720 --> 00:07:40,000 Speaker 1: the next couple of hours. So it's it's definitely what's 137 00:07:40,000 --> 00:07:42,840 Speaker 1: happening across the board this trend. Let me take a 138 00:07:42,880 --> 00:07:46,120 Speaker 1: step back, you know, Lindsay, for a couple of years, 139 00:07:46,280 --> 00:07:50,040 Speaker 1: I've been hearing in news meetings and hearing on TV 140 00:07:50,600 --> 00:07:54,240 Speaker 1: that retail is dying, the death of them all, the 141 00:07:54,360 --> 00:07:58,040 Speaker 1: death of retailing. So if this is going out, why 142 00:07:58,120 --> 00:08:01,320 Speaker 1: does it really matter anyway. I don't think retail is 143 00:08:01,360 --> 00:08:03,840 Speaker 1: ever going to go away. I think the death of 144 00:08:03,920 --> 00:08:08,320 Speaker 1: retail has been largely overstated. It's definitely changing and a 145 00:08:08,320 --> 00:08:11,520 Speaker 1: lot of retailers will die. Um. Don't get me wrong. 146 00:08:11,560 --> 00:08:14,360 Speaker 1: We've seen a record number of bankruptcies and we're probably 147 00:08:14,360 --> 00:08:17,040 Speaker 1: going to continue to see a lot of bankruptcies in 148 00:08:17,080 --> 00:08:20,000 Speaker 1: retail in the next two to five years. Everyone seems 149 00:08:20,000 --> 00:08:21,520 Speaker 1: to be on the same page about that. A lot 150 00:08:21,560 --> 00:08:23,200 Speaker 1: of malls are going to go away. We have too 151 00:08:23,200 --> 00:08:26,120 Speaker 1: many malls and too many stores, and that's a difficult 152 00:08:26,120 --> 00:08:29,119 Speaker 1: business to correct when you're this far down the line. 153 00:08:29,280 --> 00:08:31,480 Speaker 1: It's also really easy to get into this business, so 154 00:08:31,520 --> 00:08:35,400 Speaker 1: there's more competition than ever before. But that said, people 155 00:08:35,400 --> 00:08:37,880 Speaker 1: are still buying things. They want to buy things. They're 156 00:08:37,920 --> 00:08:41,200 Speaker 1: just buying things differently, or they're spending less money on 157 00:08:41,240 --> 00:08:45,040 Speaker 1: apparel and more money on things like technology, eating out, 158 00:08:45,360 --> 00:08:49,360 Speaker 1: going on a cool vacation. As purchases migrate to the web, 159 00:08:50,760 --> 00:08:54,839 Speaker 1: isn't gender disparity in wages going to go away? I mean, 160 00:08:55,040 --> 00:08:57,640 Speaker 1: if you're doing this from your computer or your tablet 161 00:08:57,720 --> 00:09:00,520 Speaker 1: or your phone, you don't know who the person at 162 00:09:00,559 --> 00:09:04,080 Speaker 1: the other end is. It could be anyone anywhere. Why 163 00:09:04,120 --> 00:09:07,000 Speaker 1: does it matter? Or it could get worse if more 164 00:09:07,160 --> 00:09:10,720 Speaker 1: men are working at online sites and they're the ones 165 00:09:10,840 --> 00:09:13,600 Speaker 1: making more money. Could that happen to right? But if 166 00:09:13,640 --> 00:09:17,160 Speaker 1: you're talking about someone who's behind a click at a site, 167 00:09:18,200 --> 00:09:21,680 Speaker 1: then the employee is not necessarily going to care whether 168 00:09:21,720 --> 00:09:24,520 Speaker 1: they hire a man or a woman, are they? It 169 00:09:24,600 --> 00:09:27,040 Speaker 1: depends on the job probably. I mean a lot of 170 00:09:27,040 --> 00:09:31,000 Speaker 1: these web retailers they don't necessarily even own any inventory. 171 00:09:31,040 --> 00:09:33,840 Speaker 1: They might have some designers, some web folks, and then they, 172 00:09:34,120 --> 00:09:36,760 Speaker 1: you know, contract out to people in China or Asia 173 00:09:36,840 --> 00:09:39,040 Speaker 1: who make the goods, and they contract out to people 174 00:09:39,080 --> 00:09:41,640 Speaker 1: to ship the goods. They contract out to a distribution 175 00:09:41,920 --> 00:09:45,000 Speaker 1: center and a warehouse. So who knows who that retailer 176 00:09:45,040 --> 00:09:49,160 Speaker 1: actually employs directly. Um. You know, warehouse and shipping jobs 177 00:09:49,160 --> 00:09:51,880 Speaker 1: do tend to be male dominated. Right now. The retail 178 00:09:51,960 --> 00:09:55,319 Speaker 1: industry is a heavily female industry. The bulk of people 179 00:09:55,320 --> 00:09:59,439 Speaker 1: who work in retail are women, often women of color. Um, 180 00:09:59,520 --> 00:10:02,920 Speaker 1: So we are going to see that job change as 181 00:10:03,000 --> 00:10:06,559 Speaker 1: the retail landscape of America changes, that's for sure. Well, 182 00:10:06,600 --> 00:10:08,920 Speaker 1: for a store that Kate is too main. Why does 183 00:10:08,960 --> 00:10:11,920 Speaker 1: it matter to a man whether the person serving them 184 00:10:11,920 --> 00:10:14,360 Speaker 1: in the store is a man or a woman. I mean, 185 00:10:14,360 --> 00:10:17,200 Speaker 1: you just said most of the workers are female. What 186 00:10:17,360 --> 00:10:21,000 Speaker 1: why is that a lot of stores sell women's goods. 187 00:10:21,960 --> 00:10:24,760 Speaker 1: Retail has always been seen as sort of a women's 188 00:10:25,040 --> 00:10:28,480 Speaker 1: dominated industry, you know, and that it's a lot of 189 00:10:28,480 --> 00:10:31,920 Speaker 1: women who shop. Women make up something like of the 190 00:10:32,040 --> 00:10:36,240 Speaker 1: purchasing decisions and actual execution. And it's also seen as 191 00:10:36,280 --> 00:10:41,319 Speaker 1: you know, sort of low skill work. It's highly interpersonal work. 192 00:10:41,800 --> 00:10:45,680 Speaker 1: So it's been a largely female industry for a long time. 193 00:10:45,720 --> 00:10:48,079 Speaker 1: I don't necessarily know that a man would walk into 194 00:10:48,120 --> 00:10:50,520 Speaker 1: a men's boutique and say, oh, I don't want to 195 00:10:50,520 --> 00:10:54,040 Speaker 1: shop here because only women are associates. I don't know 196 00:10:54,080 --> 00:10:57,160 Speaker 1: that it's even that overt. I think you want to 197 00:10:57,160 --> 00:11:00,040 Speaker 1: talk to someone who you feel has a connection to 198 00:11:00,120 --> 00:11:03,320 Speaker 1: what you're buying, can understand, can give you a personal advice, 199 00:11:03,440 --> 00:11:06,800 Speaker 1: can say, you know, I wear this size jacket and 200 00:11:06,800 --> 00:11:09,240 Speaker 1: it's a little short in the risks, and he's going 201 00:11:09,280 --> 00:11:11,120 Speaker 1: to know exactly what that means. It's not that a 202 00:11:11,120 --> 00:11:14,040 Speaker 1: woman couldn't do that job, but like tends to look 203 00:11:14,080 --> 00:11:17,480 Speaker 1: for like and if you're a men's retailer catering two men, 204 00:11:17,679 --> 00:11:21,600 Speaker 1: you might hire more men. That's exactly what James Majuski 205 00:11:21,760 --> 00:11:24,680 Speaker 1: from Human Christ said as well. He said there employees 206 00:11:24,720 --> 00:11:27,560 Speaker 1: tend to be like mannequins for their clothing. So when 207 00:11:27,559 --> 00:11:30,840 Speaker 1: guys come in, they look at the person in front 208 00:11:30,880 --> 00:11:32,960 Speaker 1: of them and they might say, Hey, that's a nice jacket. 209 00:11:33,000 --> 00:11:35,920 Speaker 1: Where did you get that? Oh, your own store? Can 210 00:11:35,960 --> 00:11:39,800 Speaker 1: you show me? Can I try it on? All right, 211 00:11:39,960 --> 00:11:43,240 Speaker 1: let's turn to the national implications of this story that 212 00:11:43,320 --> 00:11:46,120 Speaker 1: we've been talking about. We write a lot about the 213 00:11:46,200 --> 00:11:50,440 Speaker 1: national labor market about wages here at Bloomberg, and one 214 00:11:50,440 --> 00:11:53,960 Speaker 1: story we've been covering pretty closely is that wage growth 215 00:11:54,000 --> 00:11:57,640 Speaker 1: for workers on a whole has been fairly weak during 216 00:11:58,080 --> 00:12:01,520 Speaker 1: this recovery, at least at the late stage. With the 217 00:12:01,600 --> 00:12:04,559 Speaker 1: unemployment rate just over four percent, which is the lowest 218 00:12:04,640 --> 00:12:07,839 Speaker 1: level since two thousand. Some people think that wages should 219 00:12:07,840 --> 00:12:11,520 Speaker 1: be rising at a faster clip, and yet this men's 220 00:12:11,559 --> 00:12:14,560 Speaker 1: clothing market seems to show that if sales are rising 221 00:12:14,679 --> 00:12:18,320 Speaker 1: and you have a relatively small labor pool, then wages 222 00:12:18,360 --> 00:12:21,720 Speaker 1: can actually pick up at a fairly rapid clip. Cat 223 00:12:21,960 --> 00:12:25,680 Speaker 1: What did people tell you about whether this means that 224 00:12:25,960 --> 00:12:29,120 Speaker 1: wages might pick up more broadly, Well, you're right, it 225 00:12:29,280 --> 00:12:32,160 Speaker 1: is showing the same dynamics that we've been seeing and 226 00:12:32,200 --> 00:12:35,520 Speaker 1: hearing about for some time in the US economy. At 227 00:12:35,520 --> 00:12:40,120 Speaker 1: a time when you've got this low unemployment rate, why 228 00:12:40,280 --> 00:12:44,400 Speaker 1: aren't companies paying more to retain workers or to attract workers? 229 00:12:44,440 --> 00:12:47,960 Speaker 1: And here in specifically in men's clothing, we're seeing that 230 00:12:48,040 --> 00:12:51,600 Speaker 1: playing out. So the question is when are we going 231 00:12:51,640 --> 00:12:55,239 Speaker 1: to see that in the broader economy in other sectors. 232 00:12:55,920 --> 00:12:59,880 Speaker 1: This is perhaps not going to mean an immediate effect. 233 00:13:00,240 --> 00:13:06,040 Speaker 1: This is not like our Bloomberg economist Yelena said on 234 00:13:06,080 --> 00:13:07,920 Speaker 1: the phone to me. She said, you can't draw a 235 00:13:07,960 --> 00:13:12,760 Speaker 1: direct correlation, but there's certainly the same dynamics playing out. 236 00:13:12,880 --> 00:13:16,560 Speaker 1: So it does show. It's should provide people with some 237 00:13:16,640 --> 00:13:20,920 Speaker 1: optimism that we can start to see wage growth picking up. Lindsay, 238 00:13:21,000 --> 00:13:25,480 Speaker 1: is this something that's unique to clothing retailing in the 239 00:13:25,520 --> 00:13:28,640 Speaker 1: United States or is this part of a worldwide picture 240 00:13:29,520 --> 00:13:32,800 Speaker 1: the wage question. I don't know the answer to that. Actually, 241 00:13:33,160 --> 00:13:37,480 Speaker 1: the US has a really specific apparel retailing landscape that's 242 00:13:37,600 --> 00:13:39,400 Speaker 1: that's a lot different than it is in Europe or 243 00:13:39,440 --> 00:13:41,840 Speaker 1: in Asia. You know, in Asia, people are much more 244 00:13:41,880 --> 00:13:45,400 Speaker 1: comfortable shopping online, and Europe there are a fewer stores generally. 245 00:13:45,760 --> 00:13:49,640 Speaker 1: So the US really is in a special situation and 246 00:13:49,679 --> 00:13:53,200 Speaker 1: that has too many stores. There's too much supply, and 247 00:13:53,240 --> 00:13:56,520 Speaker 1: I'm sure that that's affected wages accordingly. Um, But you know, 248 00:13:56,640 --> 00:14:00,520 Speaker 1: retailers are raising their wages because as they need to 249 00:14:00,559 --> 00:14:03,080 Speaker 1: compete for better talent. I think a lot of times 250 00:14:03,120 --> 00:14:05,800 Speaker 1: this is seen as an entry level job. About one 251 00:14:05,840 --> 00:14:09,200 Speaker 1: in three people, it's estimated, start their careers in retail. 252 00:14:09,520 --> 00:14:12,840 Speaker 1: That's an astounding fact in the US. But you know, 253 00:14:12,920 --> 00:14:16,200 Speaker 1: as we close stores and have fewer retail associates, that 254 00:14:16,520 --> 00:14:20,640 Speaker 1: is likely to change. How unionized is apparel retailing and 255 00:14:20,680 --> 00:14:24,680 Speaker 1: other unions doing anything about this, That's a great question. 256 00:14:25,080 --> 00:14:28,920 Speaker 1: It's not a highly unionized industry. The unions are very 257 00:14:29,000 --> 00:14:32,760 Speaker 1: vocal about pay, especially because you know, retail talks about 258 00:14:32,840 --> 00:14:36,240 Speaker 1: how they need to have better experiences and service in 259 00:14:36,240 --> 00:14:40,360 Speaker 1: their stores. They need to offer more customization. If you're 260 00:14:40,360 --> 00:14:42,240 Speaker 1: actually going to walk into their store, you have to 261 00:14:42,280 --> 00:14:44,840 Speaker 1: walk away saying like, Wow, what a great time I 262 00:14:44,920 --> 00:14:47,320 Speaker 1: had in that apparel store. But at the same time, 263 00:14:47,320 --> 00:14:50,680 Speaker 1: they're not paying people to provide that better service or 264 00:14:50,720 --> 00:14:53,320 Speaker 1: recognizing the skills it takes to do that. Um. So 265 00:14:53,360 --> 00:14:55,800 Speaker 1: the unions have been very vocal, but so far not 266 00:14:55,920 --> 00:14:58,240 Speaker 1: very effective because these people are seen as you know, 267 00:14:58,600 --> 00:15:02,000 Speaker 1: disposable or I don't want to give them benefits. I 268 00:15:02,040 --> 00:15:04,560 Speaker 1: don't want to provide people with you know, full time 269 00:15:04,560 --> 00:15:07,560 Speaker 1: schedules and hours. I don't want to raise wages because 270 00:15:08,680 --> 00:15:12,160 Speaker 1: I'm really strapped for cash and there's going to be 271 00:15:12,200 --> 00:15:14,240 Speaker 1: somebody else in line to take that job if this 272 00:15:14,280 --> 00:15:17,960 Speaker 1: person leaves. So Lindsay or Caca, is there an opportunity 273 00:15:18,040 --> 00:15:21,320 Speaker 1: for women's clothing retail to kind of go down the 274 00:15:21,440 --> 00:15:25,080 Speaker 1: road that men's has gone down or are they just 275 00:15:25,160 --> 00:15:29,520 Speaker 1: going to basically stay permanently different markets. Well, I think 276 00:15:29,520 --> 00:15:32,320 Speaker 1: that there are a lot of apparel retailers that cater 277 00:15:32,440 --> 00:15:35,120 Speaker 1: to women who are a lot like human cry who 278 00:15:35,200 --> 00:15:39,040 Speaker 1: you know, are small, they have a specific customer. That 279 00:15:39,080 --> 00:15:42,800 Speaker 1: customer is very loyal, and probably they have higher wages 280 00:15:42,840 --> 00:15:47,240 Speaker 1: and strong margins. But I think women's apparel overall, the 281 00:15:47,320 --> 00:15:50,400 Speaker 1: key is to have a compelling product that people want 282 00:15:50,440 --> 00:15:53,720 Speaker 1: to pay full price for. Whether you're a Gap or 283 00:15:53,880 --> 00:15:57,840 Speaker 1: Jay Crew or Nemon Marcus. You know, that's the ultimate goal, 284 00:15:57,960 --> 00:16:00,520 Speaker 1: is to have the best product at a price that 285 00:16:00,560 --> 00:16:03,640 Speaker 1: people see as fair. Um, that's part of the reason 286 00:16:03,720 --> 00:16:05,320 Speaker 1: people love t J Max. I mean, when's the last 287 00:16:05,360 --> 00:16:07,080 Speaker 1: time he walked into a t J Max and said, 288 00:16:07,160 --> 00:16:10,680 Speaker 1: what great customer service I'm having. It's just a very 289 00:16:10,760 --> 00:16:14,120 Speaker 1: different value proposition. And it's interesting that you pointed out 290 00:16:14,520 --> 00:16:17,760 Speaker 1: that stores like Human Cry do exist in women's wear. 291 00:16:18,360 --> 00:16:20,800 Speaker 1: During the reporting of this story, when I went across 292 00:16:20,800 --> 00:16:24,240 Speaker 1: the street from Human Cry to the Loft store, which 293 00:16:24,280 --> 00:16:26,360 Speaker 1: I used as an example, and then right beside it 294 00:16:26,400 --> 00:16:30,360 Speaker 1: is made Well and made Well's parent, Jay Crew has 295 00:16:30,400 --> 00:16:33,760 Speaker 1: had several consecutive quarters of losses, but made Well is 296 00:16:33,800 --> 00:16:37,240 Speaker 1: doing very well. So you do have examples in women's 297 00:16:37,240 --> 00:16:40,560 Speaker 1: where where you know the growth is continuing and their 298 00:16:40,600 --> 00:16:44,040 Speaker 1: employees might actually be compensated for that as well. What's 299 00:16:44,080 --> 00:16:49,000 Speaker 1: the industry doing about this absolutely shocking pr they've got here. 300 00:16:49,720 --> 00:16:53,440 Speaker 1: It's not just that wages a low, but that there 301 00:16:53,520 --> 00:16:56,880 Speaker 1: is this gender disparity which seems like a relic from 302 00:16:57,120 --> 00:17:01,800 Speaker 1: well the mad Men era talking about suits. The industry 303 00:17:02,400 --> 00:17:04,479 Speaker 1: doesn't really seem to have much of a response. I mean, 304 00:17:04,520 --> 00:17:06,760 Speaker 1: the people that I reached out for the story didn't 305 00:17:06,800 --> 00:17:09,360 Speaker 1: really have anything to say. I mean, I just don't 306 00:17:09,359 --> 00:17:13,800 Speaker 1: think that the industry is very focused on wages, especially 307 00:17:13,800 --> 00:17:16,000 Speaker 1: at a gender level right now. I think they have 308 00:17:16,480 --> 00:17:19,439 Speaker 1: more existential issues to focus on in a lot of 309 00:17:19,480 --> 00:17:23,120 Speaker 1: cases and staying in business, figuring out how to close stores. 310 00:17:23,520 --> 00:17:26,120 Speaker 1: I mean, I think that they would argue that they 311 00:17:26,119 --> 00:17:30,119 Speaker 1: pay competitively and that they have equal opportunity hiring practices. 312 00:17:30,440 --> 00:17:32,720 Speaker 1: I think that they would take issue with the data 313 00:17:32,800 --> 00:17:35,720 Speaker 1: at large and say, oh, that's a bigger problem, but 314 00:17:35,800 --> 00:17:38,200 Speaker 1: that's not me push you a little bit on that. 315 00:17:38,400 --> 00:17:41,480 Speaker 1: I mean, they've hurried in the past to get ahead 316 00:17:41,520 --> 00:17:47,480 Speaker 1: of bad pr When ten story sweatshops making T shirts 317 00:17:47,520 --> 00:17:51,640 Speaker 1: in the US in Bangladesh have collapsed and not only 318 00:17:51,680 --> 00:17:53,560 Speaker 1: have all the people died, but all the dyes have 319 00:17:53,640 --> 00:17:56,840 Speaker 1: gone under the river and poison the village water, etcetera, etcetera. 320 00:17:56,880 --> 00:18:00,560 Speaker 1: There's a big organic clothing fair trade clothings going on. 321 00:18:01,000 --> 00:18:03,480 Speaker 1: They didn't have any problem getting ahead of that, or 322 00:18:03,600 --> 00:18:06,600 Speaker 1: rather responding quickly, Well, this probably doesn't rise to the 323 00:18:06,680 --> 00:18:09,560 Speaker 1: level of some major scandals yet, Dan, would you say 324 00:18:09,720 --> 00:18:13,240 Speaker 1: or lindsay, well, look, I mean you've seen retailers like 325 00:18:13,280 --> 00:18:15,720 Speaker 1: Walmart come out and say, oh, thanks to the US 326 00:18:15,800 --> 00:18:20,199 Speaker 1: tax overhaul, we're going to raise our starting minimum wage. 327 00:18:20,600 --> 00:18:22,600 Speaker 1: That's great, but I think a lot of people are 328 00:18:22,600 --> 00:18:26,040 Speaker 1: doing that because they need to raise wages to be competitive. 329 00:18:26,080 --> 00:18:29,200 Speaker 1: So you've seen retail at large start to raise its wages. 330 00:18:29,240 --> 00:18:31,200 Speaker 1: But retail has been at the bottom of the barrel 331 00:18:31,280 --> 00:18:33,880 Speaker 1: and pay for a long time, and they've never been 332 00:18:33,880 --> 00:18:36,919 Speaker 1: penalized for it before. Ultimately, your shopper walks into the 333 00:18:36,960 --> 00:18:39,600 Speaker 1: store and cares whether you have the right pair of 334 00:18:39,680 --> 00:18:42,280 Speaker 1: jeans at a price that they think is fair, and 335 00:18:42,320 --> 00:18:43,840 Speaker 1: whether or not they have to wait in line for 336 00:18:43,880 --> 00:18:46,280 Speaker 1: a long time to get them. They don't think about 337 00:18:46,320 --> 00:18:48,240 Speaker 1: how much the person behind the counter or the person 338 00:18:48,280 --> 00:18:50,840 Speaker 1: who helps him into the fitting room is necessarily making. 339 00:18:51,280 --> 00:18:54,360 Speaker 1: They just want to buy their product. And as callous 340 00:18:54,359 --> 00:18:56,320 Speaker 1: as that sounds, that's what we've seen with fair trade 341 00:18:56,320 --> 00:19:00,280 Speaker 1: apparel to people say, oh, it's horrible about factory collapse ups, 342 00:19:00,320 --> 00:19:02,200 Speaker 1: but they still walk into H and M and bio 343 00:19:02,280 --> 00:19:06,440 Speaker 1: four dollar bikini. There's just still a disconnect in our society. 344 00:19:06,880 --> 00:19:08,800 Speaker 1: So what it's really going to take is for us 345 00:19:08,840 --> 00:19:12,600 Speaker 1: to value that service more, to value the jobs that 346 00:19:12,720 --> 00:19:15,800 Speaker 1: these people are doing more as a society, to really 347 00:19:15,800 --> 00:19:18,960 Speaker 1: see the wages rise along with them. All right, Well, 348 00:19:19,000 --> 00:19:20,600 Speaker 1: why don't we come back in a year and see 349 00:19:20,640 --> 00:19:24,720 Speaker 1: whether this wage gap has widened even further or if 350 00:19:24,800 --> 00:19:28,119 Speaker 1: Amazon and t J Max have just destroyed everybody in 351 00:19:28,119 --> 00:19:31,359 Speaker 1: the meantime, Katia Dmitrieva and Lindsay Ruth, thank you so 352 00:19:31,440 --> 00:19:34,480 Speaker 1: much for joining us today. Thank you, thank you. I 353 00:19:34,520 --> 00:19:36,640 Speaker 1: think we'll have to come back and talk about how 354 00:19:36,680 --> 00:19:40,359 Speaker 1: the death of retail was exaggerated. That's the real takeaway 355 00:19:40,440 --> 00:19:47,879 Speaker 1: here some recanting from the retail team. Benchmark will be 356 00:19:47,920 --> 00:19:50,080 Speaker 1: back next week. Until then, you can find us on 357 00:19:50,119 --> 00:19:53,320 Speaker 1: the Bloomberg terminal, Bloomberg dot com, our Bloomberg app, as 358 00:19:53,320 --> 00:19:57,920 Speaker 1: well as wherever you enjoy podcasts, including Apple podcasts, overcasting, Stitcher. 359 00:19:58,359 --> 00:20:00,520 Speaker 1: Please take the time to rate and you the show, 360 00:20:00,760 --> 00:20:02,840 Speaker 1: and you can also find us on Twitter. You can 361 00:20:02,880 --> 00:20:07,479 Speaker 1: follow me at at Scott's Landman. Dan You're at most 362 00:20:07,720 --> 00:20:12,720 Speaker 1: under School, Ko, Katia, You're at Katia d m I. 363 00:20:13,440 --> 00:20:18,480 Speaker 1: And Lindsay your Twitter handle is l c rup. Benchmark 364 00:20:18,560 --> 00:20:21,400 Speaker 1: is produced by Toper foreheas the head of Bloomberg Podcast 365 00:20:21,480 --> 00:20:24,240 Speaker 1: is Francesca Levie. Thanks for listening. See you next time.