1 00:00:00,040 --> 00:00:01,960 Speaker 1: It was a toll of thirty five years that I 2 00:00:02,120 --> 00:00:04,440 Speaker 1: was in that I was didn't do this like I said. 3 00:00:04,400 --> 00:00:11,760 Speaker 1: I started in the Martian and then I begin to 4 00:00:11,880 --> 00:00:15,000 Speaker 1: do four times and I stayed in the same location 5 00:00:15,160 --> 00:00:30,440 Speaker 1: until the unfortunate closing March twelve of Hello and welcome 6 00:00:30,480 --> 00:00:33,720 Speaker 1: to Stephanomics, the podcast that brings the COVID global economy 7 00:00:33,760 --> 00:00:36,880 Speaker 1: to you. And that was Isaac Thomas, who closed the 8 00:00:36,960 --> 00:00:40,120 Speaker 1: doors of his taekwondo studio in Atlanta in mid March 9 00:00:40,479 --> 00:00:43,880 Speaker 1: and will not be reopening him. More than three million 10 00:00:44,080 --> 00:00:47,600 Speaker 1: small businesses have shut in the US since February. The 11 00:00:47,680 --> 00:00:51,360 Speaker 1: global tally must run into the tens of millions. In 12 00:00:51,440 --> 00:00:54,200 Speaker 1: a little while, I'll be asking Bloomberg chief economist Tom 13 00:00:54,320 --> 00:00:57,319 Speaker 1: Orlick how much of the economic damage we've seen from 14 00:00:57,400 --> 00:01:01,320 Speaker 1: COVID nineteen is likely to be quick. He reversed, he 15 00:01:01,520 --> 00:01:05,480 Speaker 1: has some new research suggesting depressingly that nearly one in 16 00:01:05,720 --> 00:01:07,840 Speaker 1: three of the jobs lost in the US due to 17 00:01:07,880 --> 00:01:12,479 Speaker 1: the crisis may not be coming back. But first, we're 18 00:01:12,520 --> 00:01:15,160 Speaker 1: going to hear more about Isaac Thomas, because his experience 19 00:01:15,360 --> 00:01:18,440 Speaker 1: also speaks to the particularly high price that African Americans 20 00:01:18,480 --> 00:01:21,880 Speaker 1: have paid for COVID nineteen in Atlanta and across the US, 21 00:01:22,520 --> 00:01:25,600 Speaker 1: the National Bureau of Economic Research reckons the number of 22 00:01:25,720 --> 00:01:31,360 Speaker 1: black entrepreneurs in America fell by forty between February and April. 23 00:01:31,720 --> 00:01:34,200 Speaker 1: That's more than twice the decline in the number of 24 00:01:34,240 --> 00:01:38,800 Speaker 1: white owned businesses. US Economy reporter in Atlanta, Mike Sasso 25 00:01:39,080 --> 00:01:42,839 Speaker 1: has dug deeper into this story, and he's with me now. Mike. 26 00:01:43,280 --> 00:01:45,800 Speaker 1: Listeners will remember we last spoke to you back in April, 27 00:01:45,959 --> 00:01:48,960 Speaker 1: when the governor of Georgia was reopening the economy well 28 00:01:49,040 --> 00:01:51,680 Speaker 1: ahead of everyone else. I'd like to hear that's going. 29 00:01:51,840 --> 00:01:54,120 Speaker 1: But first tell me about the story you wrote with 30 00:01:54,320 --> 00:01:58,360 Speaker 1: your colleague Sajo Kishan. What did you find out. Well, Yeah, 31 00:01:58,400 --> 00:02:02,160 Speaker 1: African American businesses have been really hit hard by the 32 00:02:02,440 --> 00:02:06,800 Speaker 1: the COVID nineteen pandemic, to much greater extent than white 33 00:02:07,200 --> 00:02:11,520 Speaker 1: and frankly other uh several other ethnic groups. African American 34 00:02:11,880 --> 00:02:15,600 Speaker 1: owned businesses about forty one percent, or more than four 35 00:02:15,720 --> 00:02:19,600 Speaker 1: and ten have closed at least temporarily through the pandemic. 36 00:02:20,160 --> 00:02:23,520 Speaker 1: That's more than double the rate of white owned businesses. 37 00:02:23,919 --> 00:02:27,280 Speaker 1: About seventeen percent of all white owned businesses have shot 38 00:02:27,560 --> 00:02:31,320 Speaker 1: at least temporarily during the pandemic. Uh and some even 39 00:02:31,400 --> 00:02:33,959 Speaker 1: even more so than in other hard hit groups like 40 00:02:34,320 --> 00:02:37,639 Speaker 1: immigrant in Hispanic owned businesses are each around thirty or 41 00:02:37,720 --> 00:02:41,600 Speaker 1: thirty five percent, and the numbers involved are enormous. I mean, 42 00:02:41,600 --> 00:02:45,959 Speaker 1: we're talking about four hundred and forty thousand black small 43 00:02:46,040 --> 00:02:51,600 Speaker 1: businesses closing between February and April. M We know that 44 00:02:51,720 --> 00:02:55,800 Speaker 1: a lot of African American owned businesses, that entrepreneurs find 45 00:02:55,880 --> 00:02:59,639 Speaker 1: it harder. But what are the factors that researches a 46 00:02:59,720 --> 00:03:03,200 Speaker 1: looking at when they try and think why so many 47 00:03:03,280 --> 00:03:05,600 Speaker 1: black owned businesses have gone bust? I mean, it is 48 00:03:05,680 --> 00:03:09,639 Speaker 1: partly about the sectors they're in. I guess, yeah, there's 49 00:03:09,639 --> 00:03:13,280 Speaker 1: a there's a range of of ideas about this one. 50 00:03:13,480 --> 00:03:16,519 Speaker 1: They have been hit by this pandemic, partly because you know, 51 00:03:16,760 --> 00:03:20,520 Speaker 1: African Americans in general have been hit hard by the pandemic. 52 00:03:21,040 --> 00:03:24,440 Speaker 1: You know, just healthwise. Only about thirty two or thirty 53 00:03:24,520 --> 00:03:28,720 Speaker 1: five percent of the population of Atlanta is African American, 54 00:03:29,200 --> 00:03:31,640 Speaker 1: which is higher than the nation at large, but still 55 00:03:32,040 --> 00:03:36,000 Speaker 1: a minority of of Atlanta's population, and yet eighty percent 56 00:03:36,240 --> 00:03:40,280 Speaker 1: of the hospitalized patients in the Atlanta area where African 57 00:03:40,280 --> 00:03:44,640 Speaker 1: American so a huge disproportionate number of them are being 58 00:03:44,720 --> 00:03:48,320 Speaker 1: hit by health wise. Uh. And then there are longer 59 00:03:48,400 --> 00:03:52,520 Speaker 1: standing issues with with financing of their businesses. Um, they 60 00:03:52,560 --> 00:03:57,040 Speaker 1: have had a historically harder time getting loans. Even recently, 61 00:03:57,160 --> 00:04:00,000 Speaker 1: only about twenty nine or thirty percent of African American 62 00:04:00,040 --> 00:04:03,240 Speaker 1: in businesses have been able to get a bank loan. UH. 63 00:04:03,320 --> 00:04:07,480 Speaker 1: That's meanwhile, white owned businesses are closer about two thirds 64 00:04:07,840 --> 00:04:11,400 Speaker 1: able to tap into bank credit. So that's a major issue. 65 00:04:12,320 --> 00:04:14,120 Speaker 1: And then there are you know, they do tend to 66 00:04:14,200 --> 00:04:19,320 Speaker 1: be in industries that are getting hit harder by this. Basically, 67 00:04:19,400 --> 00:04:22,400 Speaker 1: the best small business to be in in America right 68 00:04:22,440 --> 00:04:27,520 Speaker 1: now is agriculture. Unfortunately, African Americans are not, you know, 69 00:04:27,680 --> 00:04:32,160 Speaker 1: significantly in agriculture in any great numbers. They are in 70 00:04:32,600 --> 00:04:36,200 Speaker 1: in what they call this broad category called personal services. 71 00:04:36,600 --> 00:04:40,679 Speaker 1: So think of dry cleaners and hair salons and whatnot, 72 00:04:41,040 --> 00:04:44,480 Speaker 1: and those are among the most hardest hit businesses. So 73 00:04:44,880 --> 00:04:48,760 Speaker 1: there are a lot of factors, both historic and more recent, 74 00:04:49,160 --> 00:04:52,000 Speaker 1: contributing to this. Well, I know you looked at a 75 00:04:52,080 --> 00:04:54,320 Speaker 1: lot of research, but you also talked to quite a 76 00:04:54,400 --> 00:04:59,960 Speaker 1: few local African American business owners, including Isaac Thomas. Let's 77 00:05:00,000 --> 00:05:02,360 Speaker 1: there a bit more now, I was still always been 78 00:05:02,480 --> 00:05:07,760 Speaker 1: fascinated with this martial arts. So I began to to 79 00:05:07,880 --> 00:05:11,159 Speaker 1: study off and on, and then I got very serious 80 00:05:11,200 --> 00:05:14,440 Speaker 1: about it in nineteen seventy nine. And when I tell 81 00:05:14,560 --> 00:05:16,560 Speaker 1: my black daughter, I always wanted to be a teacher. 82 00:05:17,080 --> 00:05:23,320 Speaker 1: That's how Atlanta Tykwandos started back in nineteen What happened 83 00:05:23,480 --> 00:05:29,200 Speaker 1: starting take me back to earlier or mid March. On 84 00:05:29,400 --> 00:05:32,200 Speaker 1: March fourteenth, I said, I told my wife, I said, 85 00:05:32,240 --> 00:05:36,760 Speaker 1: I know my body something's wrong. So I drove myself 86 00:05:36,839 --> 00:05:41,839 Speaker 1: to the Veteran's Administrations Hospital and Claremont Road, and that's 87 00:05:41,880 --> 00:05:45,880 Speaker 1: when they determined that I had a fever. Uh. They 88 00:05:45,960 --> 00:05:50,760 Speaker 1: took X ray blood work me for the COVID nineteen 89 00:05:50,960 --> 00:05:55,640 Speaker 1: and I always diagnosed positives. March fourth I got the 90 00:05:55,720 --> 00:05:58,640 Speaker 1: results on marching teams. So that was I get the 91 00:05:58,760 --> 00:06:04,120 Speaker 1: beginning of the end. My wife herself, she was in 92 00:06:04,200 --> 00:06:08,000 Speaker 1: the hospital for eighteen days on a ventrilator for toil 93 00:06:08,760 --> 00:06:11,280 Speaker 1: and that was a very trying time there. So but 94 00:06:11,440 --> 00:06:15,760 Speaker 1: the the governor and also the the mayor of Atlanta, 95 00:06:15,839 --> 00:06:18,839 Speaker 1: the mayor of East Point, they just shut everything down, 96 00:06:19,000 --> 00:06:21,400 Speaker 1: so that that caused me not to be able to 97 00:06:21,520 --> 00:06:25,280 Speaker 1: make any income. Whatsoever from from my place of business. 98 00:06:25,320 --> 00:06:27,360 Speaker 1: So that was again, like I said, that was the 99 00:06:27,440 --> 00:06:32,520 Speaker 1: beginning of my end. So we had that Isaac was 100 00:06:32,800 --> 00:06:35,800 Speaker 1: one of those business owners that got sick and that 101 00:06:35,920 --> 00:06:37,520 Speaker 1: was part of the reason he couldn't keep up the 102 00:06:37,560 --> 00:06:41,160 Speaker 1: business and his wife did as well. Yeah, Isaac is 103 00:06:41,240 --> 00:06:46,920 Speaker 1: really compelling case. Uh. He he has started his taekwondo 104 00:06:47,120 --> 00:06:51,400 Speaker 1: studio in in a predominantly African American area of Atlanta 105 00:06:51,520 --> 00:06:55,200 Speaker 1: thirty five years ago. However, he admitted it has been 106 00:06:55,240 --> 00:06:57,800 Speaker 1: a labor of love more so than a big money 107 00:06:57,839 --> 00:07:01,159 Speaker 1: maker for him. He never was able to get much 108 00:07:01,200 --> 00:07:06,000 Speaker 1: in terms of bank loans. He described how on occasion 109 00:07:06,160 --> 00:07:08,960 Speaker 1: banks and other lenders would come to him offering money, 110 00:07:09,040 --> 00:07:10,760 Speaker 1: but it was at times when he didn't need it, 111 00:07:11,160 --> 00:07:13,680 Speaker 1: and at those periods when he did need it, Uh, 112 00:07:13,840 --> 00:07:16,880 Speaker 1: they were not willing to come forward with money. Uh. 113 00:07:16,960 --> 00:07:20,680 Speaker 1: And then you take that historic trouble getting credit and 114 00:07:21,240 --> 00:07:24,320 Speaker 1: compounded with his own illness, and it just didn't make 115 00:07:24,360 --> 00:07:27,640 Speaker 1: any sense any longer to Isaac to keep going. He 116 00:07:27,760 --> 00:07:31,200 Speaker 1: didn't have the money. Financing was a struggle and there 117 00:07:31,240 --> 00:07:36,040 Speaker 1: were challenges to business. I mean the social distancing requirements 118 00:07:36,120 --> 00:07:39,160 Speaker 1: put on by local governments, how you know he was 119 00:07:39,240 --> 00:07:41,520 Speaker 1: not allowed to have more than ten people in his 120 00:07:41,640 --> 00:07:45,160 Speaker 1: studio at any time. How do you operate a business 121 00:07:45,440 --> 00:07:47,960 Speaker 1: a a tae kwondo studio where you need to have 122 00:07:48,960 --> 00:07:51,160 Speaker 1: a number of you know, certain number of clients. How 123 00:07:51,200 --> 00:07:52,680 Speaker 1: do you do that when you have to limit it 124 00:07:52,760 --> 00:07:55,000 Speaker 1: to ten people? And and we did here, I mean 125 00:07:55,080 --> 00:07:58,520 Speaker 1: partly because of that experience with getting credit when he 126 00:07:58,560 --> 00:08:02,000 Speaker 1: really needed it in the park, asked he hadn't even 127 00:08:02,240 --> 00:08:06,960 Speaker 1: tried to get access to the government loan schemes since 128 00:08:07,040 --> 00:08:09,440 Speaker 1: the pandemic struck because he didn't want to get into 129 00:08:09,840 --> 00:08:11,480 Speaker 1: more debt. And I guess he wasn't even sure he 130 00:08:11,520 --> 00:08:13,560 Speaker 1: was going to get it. And that is something else 131 00:08:13,600 --> 00:08:15,200 Speaker 1: that was brought out in your story that there was 132 00:08:15,280 --> 00:08:20,880 Speaker 1: quite surveys of black and Hispanic business owners. Most of 133 00:08:20,920 --> 00:08:22,880 Speaker 1: them were saying they weren't able to get or they 134 00:08:22,920 --> 00:08:26,240 Speaker 1: hadn't yet been able to get assistance from the government. 135 00:08:26,680 --> 00:08:29,000 Speaker 1: And you did ask him though, about what he thought 136 00:08:29,040 --> 00:08:31,200 Speaker 1: about the future. So maybe let's just hear a little 137 00:08:31,240 --> 00:08:32,640 Speaker 1: bit about that, and then I want to hear from 138 00:08:32,679 --> 00:08:34,760 Speaker 1: you what you think things are like on the ground 139 00:08:34,840 --> 00:08:38,120 Speaker 1: in Atlanta. Do you think that they will be able 140 00:08:38,200 --> 00:08:43,160 Speaker 1: to rebound quickly when maybe this virus gets under control, 141 00:08:43,400 --> 00:08:46,760 Speaker 1: or do you do you foresee a longer, more difficult 142 00:08:47,280 --> 00:08:51,559 Speaker 1: come back in most instances is probably going to be 143 00:08:51,720 --> 00:08:55,839 Speaker 1: longer because uh, we're probably not gonna be able to 144 00:08:56,040 --> 00:08:59,760 Speaker 1: get the amount of fan anything or the amount of 145 00:09:00,120 --> 00:09:05,280 Speaker 1: loan they would really need. And it's understandable somewhat because 146 00:09:05,480 --> 00:09:08,079 Speaker 1: like I say, they couldn't extend to me just a 147 00:09:08,360 --> 00:09:12,520 Speaker 1: uh large amount of loan when I'm not bringing in 148 00:09:12,960 --> 00:09:17,400 Speaker 1: that kind of money. So I understand the economics. So 149 00:09:17,800 --> 00:09:20,760 Speaker 1: that's why I think that was gonna be a little 150 00:09:20,800 --> 00:09:25,040 Speaker 1: bit behind unless you get hopefully you've got those businesses 151 00:09:25,120 --> 00:09:28,200 Speaker 1: out there who are making good money and they can 152 00:09:28,240 --> 00:09:30,760 Speaker 1: get these loans and get themselves back on their feet. 153 00:09:30,800 --> 00:09:33,600 Speaker 1: And I really applaud them, the ones who are hanging 154 00:09:33,640 --> 00:09:40,560 Speaker 1: in there to make it through. And what's in your future, well, 155 00:09:40,640 --> 00:09:44,400 Speaker 1: that's it's it's it's really uncertain right now. I have 156 00:09:44,880 --> 00:09:47,800 Speaker 1: many of my students want me to uh I use 157 00:09:47,880 --> 00:09:49,920 Speaker 1: the term like from the mood of Blues Brothers. They 158 00:09:49,920 --> 00:09:52,800 Speaker 1: want me to get the band back together and then 159 00:09:52,960 --> 00:09:55,679 Speaker 1: uh and I talked to him, and I may start 160 00:09:55,800 --> 00:10:00,200 Speaker 1: doing something on a smaller scale, but the the what's 161 00:10:00,240 --> 00:10:03,840 Speaker 1: important thing right now as my family, like my wife, 162 00:10:05,080 --> 00:10:08,960 Speaker 1: I may do it on a smaller scale, but probably 163 00:10:09,080 --> 00:10:14,040 Speaker 1: not to the scale that's before. The last time we spoke, 164 00:10:14,480 --> 00:10:19,600 Speaker 1: you had braved the waffle house. When the Georgian governor 165 00:10:20,200 --> 00:10:24,120 Speaker 1: had opened up restaurants bars. I think it was tattoo 166 00:10:24,240 --> 00:10:29,319 Speaker 1: parlors Neil Salance, way ahead of expert advice. How is 167 00:10:29,360 --> 00:10:31,640 Speaker 1: that going and things getting back to normal? Have you 168 00:10:31,760 --> 00:10:36,120 Speaker 1: seen um COVID cases continuing to rise as I know 169 00:10:36,240 --> 00:10:41,160 Speaker 1: you have in some states in the US. Yeah, you're right. 170 00:10:41,240 --> 00:10:44,720 Speaker 1: Georgia was the first American state to open in any 171 00:10:44,880 --> 00:10:49,959 Speaker 1: meaningful way back you know, it was late late April. 172 00:10:50,840 --> 00:10:54,319 Speaker 1: I will say it's it's fairly you know, seems to 173 00:10:54,720 --> 00:10:59,040 Speaker 1: feel like getting back to normal here. There's a restaurant 174 00:10:59,080 --> 00:11:02,920 Speaker 1: booking service Open Table, where you go in you book 175 00:11:03,760 --> 00:11:08,920 Speaker 1: tables in advance at restaurants, particularly in the South. Bookings 176 00:11:09,000 --> 00:11:13,880 Speaker 1: are are increasing at a restaurants, particularly in Florida. I 177 00:11:14,040 --> 00:11:19,559 Speaker 1: was just looking about fifty five percent of uh the 178 00:11:19,840 --> 00:11:23,000 Speaker 1: Florida restaurants rather have picked up about fifty five percent 179 00:11:23,200 --> 00:11:25,880 Speaker 1: of their previous business, so they're only down about forty 180 00:11:26,800 --> 00:11:29,000 Speaker 1: I guess I have to ask you you I wanted 181 00:11:29,040 --> 00:11:31,440 Speaker 1: to know whether your favorite restaurant had opened yet last time, 182 00:11:31,480 --> 00:11:33,040 Speaker 1: and it hadn't opened. Have you been able to go 183 00:11:33,240 --> 00:11:36,079 Speaker 1: to your what was it the Korean restaurant that you 184 00:11:36,200 --> 00:11:39,559 Speaker 1: talked about? You know, honestly, it's a good question. I 185 00:11:39,640 --> 00:11:42,400 Speaker 1: haven't been by there. I have a little seven seven 186 00:11:42,480 --> 00:11:48,359 Speaker 1: year old daughter who loves kind of schlocky chain restaurants. 187 00:11:48,480 --> 00:11:52,880 Speaker 1: There's uh one called Chilis here in America and Applebee's, 188 00:11:52,960 --> 00:11:56,280 Speaker 1: and while they're not my favorite, um she she, she 189 00:11:56,760 --> 00:11:59,480 Speaker 1: loves the chains, and so we're kind of dominated by 190 00:11:59,520 --> 00:12:02,679 Speaker 1: what my what my seven year old what's in Korean? 191 00:12:02,760 --> 00:12:07,400 Speaker 1: Tagos are not yet her favorite. I can just imagine 192 00:12:07,520 --> 00:12:11,199 Speaker 1: sitting in lockdown craving your first meal, and then the 193 00:12:11,280 --> 00:12:14,880 Speaker 1: first meal is at Chili's. Um. Not that there's anything 194 00:12:14,960 --> 00:12:25,280 Speaker 1: wrong with that, Thank you very much, Mike Sass. So 195 00:12:25,400 --> 00:12:27,920 Speaker 1: we touched there on a massive question hanging over not 196 00:12:28,040 --> 00:12:32,040 Speaker 1: only business owners like Isaac Thomas, but governments around the world, 197 00:12:32,160 --> 00:12:35,319 Speaker 1: well everyone really, as they try to look to the future. 198 00:12:35,880 --> 00:12:37,959 Speaker 1: What we all want to know is how many of 199 00:12:38,040 --> 00:12:40,439 Speaker 1: the jobs and businesses we've lost in the past few 200 00:12:40,480 --> 00:12:44,000 Speaker 1: months will automatically come back as lockdowns are eased, and 201 00:12:44,120 --> 00:12:46,520 Speaker 1: how many might be gone for good or at least 202 00:12:46,559 --> 00:12:49,280 Speaker 1: a long time. Well, our chief economist Tom Warlick, great 203 00:12:49,280 --> 00:12:51,920 Speaker 1: friend of Stephanomics, just published some work on this with 204 00:12:52,040 --> 00:12:55,880 Speaker 1: two colleagues beyond Von Roy and Scott Johnson. Tom, welcome back. 205 00:12:56,160 --> 00:12:58,200 Speaker 1: I know this was quite a sophisticated model, but can 206 00:12:58,240 --> 00:13:01,040 Speaker 1: you briefly explain the approach you took and what some 207 00:13:01,240 --> 00:13:05,199 Speaker 1: of the key conclusions were. Great to be back, Stephanie. So, 208 00:13:05,360 --> 00:13:09,319 Speaker 1: the key question in terms of the unemployment impact of 209 00:13:09,400 --> 00:13:13,199 Speaker 1: the COVID nineteen recession is how much of this is 210 00:13:13,320 --> 00:13:17,320 Speaker 1: just a supply and demand shock. Jobs that are gone 211 00:13:17,760 --> 00:13:20,800 Speaker 1: but which will come back quite quickly once the lockdown 212 00:13:20,960 --> 00:13:24,880 Speaker 1: ends and stimulus starts hitting the economy, and what share 213 00:13:24,960 --> 00:13:30,079 Speaker 1: of them represent what economists call a reallocation shock, So 214 00:13:30,240 --> 00:13:33,480 Speaker 1: a shock that comes because consumers are going to change 215 00:13:33,520 --> 00:13:36,319 Speaker 1: their behavior. They're not going to go back to restaurants, 216 00:13:36,320 --> 00:13:38,640 Speaker 1: they're not going to go back to nightclubs, they're not 217 00:13:38,679 --> 00:13:41,560 Speaker 1: going to go on and fly on airlines, and those 218 00:13:41,640 --> 00:13:44,559 Speaker 1: jobs which are the result of the reallocation shock. The 219 00:13:44,640 --> 00:13:47,559 Speaker 1: assumption is, well, they might be gone for good, or 220 00:13:47,600 --> 00:13:50,880 Speaker 1: at least gone for a protracted period of time. So 221 00:13:51,040 --> 00:13:53,800 Speaker 1: what we did was we looked at flows in and 222 00:13:53,920 --> 00:13:57,520 Speaker 1: out of the US labor market, of the US labor 223 00:13:57,600 --> 00:14:01,160 Speaker 1: market on a sector basis, and what we did was 224 00:14:01,240 --> 00:14:05,840 Speaker 1: we said, Okay, if a particular sector has a lot 225 00:14:05,920 --> 00:14:09,319 Speaker 1: of job separations, a lot of people getting kicked out 226 00:14:09,360 --> 00:14:12,400 Speaker 1: of work, but not a lot of vacancies, that's a 227 00:14:12,480 --> 00:14:15,400 Speaker 1: supply and demand shock and those jobs could come back 228 00:14:15,520 --> 00:14:19,440 Speaker 1: pretty quickly once the lockdown ends. But if a sector 229 00:14:19,880 --> 00:14:23,640 Speaker 1: has a lot of job separations but also a lot 230 00:14:23,720 --> 00:14:28,720 Speaker 1: of vacancies, then that's evidence that there's a reallocation shock underway, 231 00:14:29,120 --> 00:14:31,600 Speaker 1: and those jobs are going to take longer to come 232 00:14:31,680 --> 00:14:34,720 Speaker 1: back because people are going to need training, they're going 233 00:14:34,800 --> 00:14:37,240 Speaker 1: to need to build connections with new firms, they might 234 00:14:37,320 --> 00:14:40,880 Speaker 1: need to move around the country before they find employment. 235 00:14:41,680 --> 00:14:45,600 Speaker 1: So it's a it's a compelling model, but really it's 236 00:14:45,600 --> 00:14:47,720 Speaker 1: only a model, so we have to take the results 237 00:14:48,320 --> 00:14:51,840 Speaker 1: with a grain of salt. But what they're suggesting is 238 00:14:51,920 --> 00:14:56,440 Speaker 1: that actually we're facing a pretty significant reallocation shock. Around 239 00:14:56,600 --> 00:14:59,560 Speaker 1: thirty of the jobs in the US which have been 240 00:14:59,640 --> 00:15:04,160 Speaker 1: lost between February and May are the result of reallocation. 241 00:15:04,880 --> 00:15:07,000 Speaker 1: And what that suggests is we're going to see the 242 00:15:07,080 --> 00:15:09,560 Speaker 1: beginning of a V shaped recovery in the labor market. 243 00:15:09,840 --> 00:15:11,840 Speaker 1: A lot of jobs are going to come back quite quickly, 244 00:15:12,440 --> 00:15:16,320 Speaker 1: but for around thirty of the newly unemployed, UM, there's 245 00:15:16,320 --> 00:15:19,480 Speaker 1: going to be a long slog back to back to employment. 246 00:15:20,240 --> 00:15:22,840 Speaker 1: Just just so we have a way of thinking about this. 247 00:15:23,160 --> 00:15:27,400 Speaker 1: If you were in a in a retail or restaurant industry, 248 00:15:27,520 --> 00:15:29,880 Speaker 1: for example, if you're getting rid of a lot of 249 00:15:30,000 --> 00:15:32,920 Speaker 1: waiters because you think it's going to be quite a 250 00:15:32,960 --> 00:15:35,400 Speaker 1: long time before you can have people back in the restaurants, 251 00:15:35,920 --> 00:15:40,120 Speaker 1: but you have increased your online business and your delivery 252 00:15:40,200 --> 00:15:42,040 Speaker 1: business with that, with that kind of shop, is that 253 00:15:42,120 --> 00:15:44,160 Speaker 1: the kind of reallocation shock are we talking about or 254 00:15:44,160 --> 00:15:48,320 Speaker 1: we're talking about something more lasting than that, right? So, yeah, 255 00:15:48,360 --> 00:15:51,480 Speaker 1: an intuitive way of thinking about it would be the 256 00:15:51,600 --> 00:15:57,280 Speaker 1: Amazon effect. We've got a local grocery store that used 257 00:15:57,320 --> 00:15:59,920 Speaker 1: to have a bunch of staff dealing face to face 258 00:16:00,480 --> 00:16:03,320 Speaker 1: with customers who would come in to buy their vegetables 259 00:16:03,400 --> 00:16:06,520 Speaker 1: and their milk and so on. But because of COVID, 260 00:16:06,920 --> 00:16:10,000 Speaker 1: people have decided, you know what, I want to minimize 261 00:16:10,400 --> 00:16:12,720 Speaker 1: my contagion risks. I don't want to go to the 262 00:16:12,800 --> 00:16:16,400 Speaker 1: grocery store. So I'm going to switch my grocery purchases 263 00:16:16,680 --> 00:16:21,240 Speaker 1: from the grocery store to Amazon Amazon Prime, and I'm 264 00:16:21,280 --> 00:16:24,120 Speaker 1: going to get everything delivered. So we see some jobs 265 00:16:24,160 --> 00:16:28,000 Speaker 1: disappearing in that local grocery store. We see some jobs 266 00:16:28,080 --> 00:16:31,920 Speaker 1: being created in the Amazon warehouse and the delivery company. 267 00:16:32,440 --> 00:16:36,320 Speaker 1: That's the reallocation shock. Now that anecdote and the one 268 00:16:36,360 --> 00:16:40,000 Speaker 1: which you sort of shared about the restaurant switching to online, 269 00:16:40,560 --> 00:16:43,800 Speaker 1: what that suggests is that the reallocation happens, in a 270 00:16:43,880 --> 00:16:48,400 Speaker 1: sense in a seamless way. Right, So person A walks 271 00:16:48,440 --> 00:16:51,800 Speaker 1: out of a job on day one and into another job, 272 00:16:51,960 --> 00:16:55,400 Speaker 1: maybe with the same company, in day two. The trouble 273 00:16:55,600 --> 00:17:00,200 Speaker 1: is that reallocation rarely happens in such a smooth way. 274 00:17:00,800 --> 00:17:05,359 Speaker 1: We see businesses dying, we see other businesses growing and 275 00:17:05,480 --> 00:17:10,359 Speaker 1: other businesses being created. We see people moving from companies 276 00:17:10,640 --> 00:17:14,800 Speaker 1: and from between sectors and between locations. But these things 277 00:17:14,920 --> 00:17:19,399 Speaker 1: take a considerable period of time. Most people don't stop 278 00:17:19,440 --> 00:17:21,399 Speaker 1: being a waiter on day one and start being a 279 00:17:21,480 --> 00:17:26,760 Speaker 1: delivery person on day two. That transition takes weeks, months, 280 00:17:26,840 --> 00:17:30,320 Speaker 1: sometimes even longer. What are the most vulnerable sectors? If 281 00:17:30,359 --> 00:17:33,200 Speaker 1: we I mean we've already mentioned retail. Is that where 282 00:17:33,240 --> 00:17:37,600 Speaker 1: the reallocation looks like it's taken place retail, hospitality, or 283 00:17:37,680 --> 00:17:41,360 Speaker 1: is it broader than that. We actually took two approaches 284 00:17:41,760 --> 00:17:45,200 Speaker 1: to looking at this question. The first one I just described, 285 00:17:45,280 --> 00:17:47,720 Speaker 1: that's where we look at flows in and out of 286 00:17:47,760 --> 00:17:51,359 Speaker 1: the labor market. The second one, and this was the 287 00:17:51,400 --> 00:17:55,200 Speaker 1: work pursued by Scott Johnson, is where we looked at 288 00:17:55,520 --> 00:17:59,440 Speaker 1: the dispersion of equity market returns. And the idea there 289 00:18:00,119 --> 00:18:04,440 Speaker 1: that if you see equity market investors making a big 290 00:18:04,560 --> 00:18:09,080 Speaker 1: bet on profits in one sector but getting really cautious 291 00:18:09,200 --> 00:18:12,639 Speaker 1: or pessimistic on profits in another sector, then that's an 292 00:18:12,720 --> 00:18:16,920 Speaker 1: early signal that there's going to be a reallocation taking place. 293 00:18:17,720 --> 00:18:20,440 Speaker 1: So we use both approaches to look at the size 294 00:18:20,480 --> 00:18:23,600 Speaker 1: of the reallocation shock and where the reallocation shock is 295 00:18:23,600 --> 00:18:27,320 Speaker 1: going to be biggest. And yes, retail shows up big 296 00:18:27,400 --> 00:18:32,600 Speaker 1: and in both approaches. Hospitality shows up big in both approaches. 297 00:18:33,440 --> 00:18:36,720 Speaker 1: But there's also sectors like oil and gas, for example, 298 00:18:37,119 --> 00:18:40,720 Speaker 1: which are not so directly related to the COVID shock. 299 00:18:41,040 --> 00:18:43,320 Speaker 1: They're not going to be affected by people's preference for 300 00:18:43,400 --> 00:18:46,560 Speaker 1: face to face contact or not. But because the COVID 301 00:18:46,680 --> 00:18:50,480 Speaker 1: shock has hammered oil prices. That is also going to 302 00:18:50,600 --> 00:18:54,119 Speaker 1: lead to a significant reallocation within the oil and gas sector. 303 00:18:54,560 --> 00:18:57,280 Speaker 1: There's going to be some high cost producers that go 304 00:18:57,400 --> 00:18:59,920 Speaker 1: out of business, there's going to be some low cost 305 00:19:00,040 --> 00:19:03,600 Speaker 1: producers that start doing more. And of course, when you're 306 00:19:03,600 --> 00:19:08,000 Speaker 1: thinking about a sector like that, the reallocation between firms, 307 00:19:08,480 --> 00:19:11,160 Speaker 1: the cost to workers of losing their job and finding 308 00:19:11,200 --> 00:19:14,840 Speaker 1: another one starts to look much higher than in that 309 00:19:15,080 --> 00:19:18,440 Speaker 1: kind of intuitive example about the shift from the waiter 310 00:19:18,480 --> 00:19:21,680 Speaker 1: to delivery person, where you know, one might hope that 311 00:19:21,800 --> 00:19:29,000 Speaker 1: that happened more quickly. Tom, you said at the start, 312 00:19:29,080 --> 00:19:31,200 Speaker 1: we should take the results of this with a pinch 313 00:19:31,240 --> 00:19:33,680 Speaker 1: of salt. It's just an economic model. I guess some 314 00:19:33,760 --> 00:19:37,320 Speaker 1: people would say what you're calling a reallocation shock is 315 00:19:37,359 --> 00:19:43,159 Speaker 1: a behavioral change by consumers that could disappear if we 316 00:19:43,320 --> 00:19:45,000 Speaker 1: have a vaccine, if we have an end to this 317 00:19:45,119 --> 00:19:49,040 Speaker 1: crisis sooner than people are expecting. And that's true, right. 318 00:19:49,080 --> 00:19:52,840 Speaker 1: There is a lot of uncertainty here, absolutely, Stephanie, and 319 00:19:53,119 --> 00:19:56,520 Speaker 1: I think I flag a few things. So the first is, 320 00:19:56,720 --> 00:19:59,080 Speaker 1: and this is what you just mentioned, if this all 321 00:19:59,160 --> 00:20:02,960 Speaker 1: comes back under control really quickly, Um, and it turns 322 00:20:03,000 --> 00:20:05,920 Speaker 1: out people have short memories and they decide this was 323 00:20:06,000 --> 00:20:09,480 Speaker 1: a one off and their behavior essentially goes back to normal. 324 00:20:10,000 --> 00:20:14,040 Speaker 1: Then the reallocation shock could well be significantly smaller than 325 00:20:14,119 --> 00:20:17,760 Speaker 1: our model suggests. But I'd point to a couple of 326 00:20:17,840 --> 00:20:22,399 Speaker 1: cautions before before jumping to that optimistic conclusion. So the 327 00:20:22,480 --> 00:20:26,320 Speaker 1: first one is, actually, if we look at what's happening 328 00:20:26,400 --> 00:20:29,760 Speaker 1: with the disease case cone around the world, that doesn't 329 00:20:29,760 --> 00:20:32,480 Speaker 1: seem to be how things are playing out UM. And 330 00:20:32,600 --> 00:20:35,520 Speaker 1: if we look at how people behave in countries like 331 00:20:35,720 --> 00:20:40,720 Speaker 1: Sweden and Korea UM, which don't have the same type 332 00:20:40,760 --> 00:20:45,080 Speaker 1: restrictions in place, what we see is that actually, even 333 00:20:45,119 --> 00:20:49,200 Speaker 1: when lockdown's ease, fear of contagion continues to be a 334 00:20:49,280 --> 00:20:54,399 Speaker 1: factor that changes behavior. And the second thing is, Okay, 335 00:20:54,480 --> 00:20:56,800 Speaker 1: let's say we have an optimistic scenario where this thing's 336 00:20:57,080 --> 00:21:00,800 Speaker 1: things come under control and the disease stops being an 337 00:21:00,840 --> 00:21:03,640 Speaker 1: issue in in three months or in six months time. Well, 338 00:21:04,119 --> 00:21:06,879 Speaker 1: there's a lot of businesses that sadly are just not 339 00:21:06,960 --> 00:21:10,720 Speaker 1: going to make it that distance. So even if the 340 00:21:10,800 --> 00:21:13,840 Speaker 1: disease gets taken out of the equation, we're still going 341 00:21:13,920 --> 00:21:18,520 Speaker 1: to have reallocation because of what economists call the sort 342 00:21:18,560 --> 00:21:21,560 Speaker 1: of the Matthew effect, to him that hath shall be 343 00:21:21,680 --> 00:21:24,000 Speaker 1: given to him, that hath not shall be taken away. 344 00:21:25,000 --> 00:21:27,960 Speaker 1: And we're seeing that playing out really viciously in this 345 00:21:28,160 --> 00:21:31,399 Speaker 1: COVID shock. Lots of small bricks and mortar business is 346 00:21:31,480 --> 00:21:36,000 Speaker 1: going under, lots of big e commerce platforms grabbing more 347 00:21:36,119 --> 00:21:39,080 Speaker 1: market share. And what that suggests to me is that 348 00:21:39,400 --> 00:21:42,000 Speaker 1: even when the disease comes under control, there's still going 349 00:21:42,040 --> 00:21:46,560 Speaker 1: to be some significant reallocation that's taken place. Clearly, governments 350 00:21:46,600 --> 00:21:48,520 Speaker 1: can't hope for the best, even if there is a 351 00:21:48,560 --> 00:21:51,920 Speaker 1: possibility that some of this will turn out to be overstated. 352 00:21:52,359 --> 00:21:54,880 Speaker 1: What are the implications if a third of these job 353 00:21:55,000 --> 00:22:00,080 Speaker 1: losses give or take, are more structural in nature, at 354 00:22:00,119 --> 00:22:04,560 Speaker 1: least potentially more lasting. What what should governments be doing 355 00:22:04,640 --> 00:22:08,320 Speaker 1: to try and mitigate that. Are we talking training programs? 356 00:22:08,359 --> 00:22:11,240 Speaker 1: What do you think would be most effective. That's a 357 00:22:11,320 --> 00:22:13,800 Speaker 1: great question, um, and it sort of speaks to the 358 00:22:13,880 --> 00:22:17,840 Speaker 1: difficulty which governments have in framing the right policy response. UM. 359 00:22:18,160 --> 00:22:21,360 Speaker 1: If you've got essentially a demand shock where the problem 360 00:22:21,520 --> 00:22:26,280 Speaker 1: for employment is there's not enough spending taking place, then 361 00:22:26,359 --> 00:22:31,040 Speaker 1: what government should be doing is very very aggressively supporting demand, 362 00:22:31,480 --> 00:22:35,040 Speaker 1: putting more money into people's pockets, paying businesses to keep 363 00:22:35,119 --> 00:22:38,360 Speaker 1: hold of their workers through the lockdown. UM. If we're 364 00:22:38,359 --> 00:22:43,239 Speaker 1: actually looking at a significant reallocation shock, painful though it is, UM, 365 00:22:43,840 --> 00:22:48,120 Speaker 1: what's needed is for governments to get out of the way, UM, 366 00:22:48,440 --> 00:22:52,879 Speaker 1: allow a period of higher unemployment, allow some business bankruptcies 367 00:22:52,960 --> 00:22:57,480 Speaker 1: to take place to speed that reallocation UM. And in 368 00:22:57,600 --> 00:23:02,840 Speaker 1: that circumstance, massive support for demand would actually create more 369 00:23:02,880 --> 00:23:05,760 Speaker 1: problems in the longer term. I mean my feeling is 370 00:23:06,160 --> 00:23:10,320 Speaker 1: the complexity is through sequencing. Right now in the lockdown, 371 00:23:10,800 --> 00:23:14,160 Speaker 1: clearly the supply and demand shock is dominating, and that's 372 00:23:14,200 --> 00:23:18,200 Speaker 1: the period for massive government support. Once the lockdown starts 373 00:23:18,240 --> 00:23:21,440 Speaker 1: to ease, will get a clearer picture of the size 374 00:23:21,480 --> 00:23:25,119 Speaker 1: of the reallocation shock and where it's particularly important, and 375 00:23:25,320 --> 00:23:27,359 Speaker 1: that is when governments are going to have to start 376 00:23:27,880 --> 00:23:30,560 Speaker 1: being a bit more nuanced and differentiating a bit more 377 00:23:30,600 --> 00:23:33,040 Speaker 1: in terms of where they provide support and where they 378 00:23:33,080 --> 00:23:36,240 Speaker 1: step out of the way. And that difference is exactly 379 00:23:36,600 --> 00:23:39,960 Speaker 1: the contrast that Jason Furman drew between Europe and the 380 00:23:40,080 --> 00:23:43,200 Speaker 1: US last week, and I think we've we're seeing it 381 00:23:43,280 --> 00:23:45,320 Speaker 1: play out in real time, and we are, as you say, 382 00:23:45,400 --> 00:23:48,760 Speaker 1: only just beginning to find out which might be more affective. 383 00:23:48,800 --> 00:23:52,480 Speaker 1: But Tom, thanks very much, thanks for having me on Stephanie. 384 00:23:53,040 --> 00:23:59,439 Speaker 1: Please don't reallocate me. Thanks for listening to Stephanis. We'll 385 00:23:59,480 --> 00:24:02,360 Speaker 1: be back next week with more on how COVID nineteen 386 00:24:02,920 --> 00:24:06,199 Speaker 1: is turning the global economy upside down. Remember you can 387 00:24:06,240 --> 00:24:09,280 Speaker 1: always find us on the Bloomberg Terminal, website, app or 388 00:24:09,320 --> 00:24:12,000 Speaker 1: wherever you get your podcasts, and for more news and 389 00:24:12,040 --> 00:24:17,320 Speaker 1: analysis from Bloomberg Economics, follow at Economics on Twitter. This 390 00:24:17,440 --> 00:24:20,680 Speaker 1: episode was produced by Magnus Hendrickson, with special thanks to 391 00:24:20,800 --> 00:24:25,520 Speaker 1: Mike Sasso, Segel Kishan, Tom Orlick, Jorn Van Roy, and 392 00:24:25,640 --> 00:24:29,440 Speaker 1: Scott Johnson. Lucy Meekin is the acting executive producer of 393 00:24:29,480 --> 00:24:33,000 Speaker 1: Stephanomics and the head of Bloomberg Podcasts is Francesca Leading