1 00:00:00,080 --> 00:00:02,160 Speaker 1: I was talking to one agriculture company about whether it 2 00:00:02,200 --> 00:00:06,160 Speaker 1: would help to get prisoners to collect the harvest, and 3 00:00:06,200 --> 00:00:08,320 Speaker 1: they said there are a number of problems, including that 4 00:00:08,960 --> 00:00:10,880 Speaker 1: they might not be very good at it. They might, 5 00:00:11,240 --> 00:00:14,120 Speaker 1: you know, you need particular set of skills, especially if 6 00:00:14,160 --> 00:00:17,560 Speaker 1: you're picking soft fruits, for example, and also sometimes the 7 00:00:17,600 --> 00:00:26,360 Speaker 1: prisoners run away, which is another problem. Hello, and welcome 8 00:00:26,360 --> 00:00:29,319 Speaker 1: to Stephanomics, the podcast that brings the global economy to you. 9 00:00:29,920 --> 00:00:33,960 Speaker 1: I'm Stephanie Flanders, and this week we're investigating why employers 10 00:00:34,000 --> 00:00:37,560 Speaker 1: on different sides of the Atlantic are considering extreme solutions 11 00:00:37,640 --> 00:00:40,839 Speaker 1: to their labor shortages. But an economy with millions of 12 00:00:40,880 --> 00:00:43,879 Speaker 1: jobs they can see can still somehow be one in 13 00:00:43,920 --> 00:00:47,960 Speaker 1: which unemployed people struggle to find work. It's all the 14 00:00:48,000 --> 00:00:51,880 Speaker 1: flip side, the human side of the supply chain snarl 15 00:00:51,960 --> 00:00:54,840 Speaker 1: ups we come across so often these days, the post 16 00:00:54,880 --> 00:00:58,800 Speaker 1: COVID economy with demands still gaining pace and inflation and 17 00:00:58,880 --> 00:01:02,640 Speaker 1: wages heading up, but at least four million fewer people 18 00:01:02,720 --> 00:01:05,679 Speaker 1: in work today in the US than before the pandemic. 19 00:01:06,440 --> 00:01:10,160 Speaker 1: Later on, I'll ask Jason Furman, previously President Obama's top 20 00:01:10,200 --> 00:01:13,360 Speaker 1: economic advisor, to help me solve the riddle of the 21 00:01:13,400 --> 00:01:18,120 Speaker 1: missing American worker. I'm also here why agricultural companies in 22 00:01:18,200 --> 00:01:21,360 Speaker 1: Russia are weighing the pros and cons of using prisoners 23 00:01:21,480 --> 00:01:24,400 Speaker 1: to bring in the crops. But first we asked US 24 00:01:24,440 --> 00:01:27,840 Speaker 1: economy reporter Jill Sharp to give us a taste of 25 00:01:27,880 --> 00:01:40,080 Speaker 1: the US jobs market at ground level. Well, I think 26 00:01:40,080 --> 00:01:43,480 Speaker 1: that right now everybody is hiring, but they're only hiring 27 00:01:43,640 --> 00:01:49,080 Speaker 1: for lopaying job. They're hiring for positions as only one 28 00:01:49,160 --> 00:01:51,960 Speaker 1: day a week, two days a week, and people cannot 29 00:01:52,400 --> 00:01:55,279 Speaker 1: make it off of that. That's Precious Briggs, a thirty 30 00:01:55,320 --> 00:01:57,520 Speaker 1: two year old whose stream of working as a Las 31 00:01:57,640 --> 00:02:00,680 Speaker 1: Vegas cocktail server came to a sudden halt last April 32 00:02:01,080 --> 00:02:06,680 Speaker 1: after COVID nineteen shut down America's gambling paradise. After restrictions lifted, 33 00:02:06,760 --> 00:02:09,600 Speaker 1: she expected her former employer to hire her back, but 34 00:02:09,680 --> 00:02:13,600 Speaker 1: the call never came. Today, Precious is among over four 35 00:02:13,639 --> 00:02:17,080 Speaker 1: million Americans who are unemployed were missing from the labor 36 00:02:17,120 --> 00:02:21,040 Speaker 1: market compared to pre pandemic levels. Like many others, she's 37 00:02:21,160 --> 00:02:24,320 Speaker 1: used up her unemployment and pandemic benefits from the government, 38 00:02:24,720 --> 00:02:28,160 Speaker 1: and she's getting by on rental assistance, Medicaid, and support 39 00:02:28,200 --> 00:02:31,040 Speaker 1: from her family. She's hopeful that she'll land a full 40 00:02:31,080 --> 00:02:35,119 Speaker 1: time job as Vegas continues to reopen. I definitely want 41 00:02:35,120 --> 00:02:37,639 Speaker 1: to be in the casino. I love the people and 42 00:02:37,760 --> 00:02:40,400 Speaker 1: I love the atmosphere there, So that's definitely something that 43 00:02:40,440 --> 00:02:42,080 Speaker 1: I love, and that's that. It was a dream of 44 00:02:42,120 --> 00:02:46,320 Speaker 1: mine to leave Little Louisiana, my little town, and come 45 00:02:46,360 --> 00:02:52,720 Speaker 1: here in Tacktail emborsing here. When the pandemic arrived in 46 00:02:52,760 --> 00:02:56,840 Speaker 1: the US last year, millions of American workers abruptly lost 47 00:02:56,880 --> 00:03:01,000 Speaker 1: their jobs. Now, as the economy recovers, a puzzle has 48 00:03:01,040 --> 00:03:04,799 Speaker 1: emerged in the labor market. The country at over ten 49 00:03:04,840 --> 00:03:07,600 Speaker 1: million job openings at the end of August, according to 50 00:03:07,639 --> 00:03:10,639 Speaker 1: federal government data, and that number might have increased over 51 00:03:10,639 --> 00:03:15,160 Speaker 1: the last two months. The job posting website indeed estimates 52 00:03:15,200 --> 00:03:18,560 Speaker 1: there may now be as many as eleven million unfilled openings. 53 00:03:19,639 --> 00:03:22,480 Speaker 1: But while hiring is picked up just recently with over 54 00:03:22,480 --> 00:03:26,679 Speaker 1: five hundred thousand jobs added in October, millions remain unemployed 55 00:03:26,800 --> 00:03:29,480 Speaker 1: or have left the labor market since the pandemics started. 56 00:03:30,160 --> 00:03:34,720 Speaker 1: Economists and policymakers are all wondering where they've gone. Here's 57 00:03:34,800 --> 00:03:39,240 Speaker 1: Julia Pollock, chief economist at the online Jobs marketplace zip recruiter, 58 00:03:40,320 --> 00:03:43,440 Speaker 1: the labor markets, the matching market where you have to 59 00:03:43,640 --> 00:03:46,760 Speaker 1: choose something and be chosen by it, and where all 60 00:03:46,800 --> 00:03:48,920 Speaker 1: the jobs are very very differential, the works are very 61 00:03:48,960 --> 00:03:51,680 Speaker 1: very different and so having you know the same number 62 00:03:51,680 --> 00:03:56,280 Speaker 1: of job openings and of unemployed or underemployed workers does 63 00:03:56,360 --> 00:04:00,680 Speaker 1: not imply that there will be a very simple direct match. 64 00:04:01,520 --> 00:04:05,240 Speaker 1: For example, while job postings and warehousing and transportation and 65 00:04:05,360 --> 00:04:09,880 Speaker 1: e commerce related companies have exploded, there's been a decline 66 00:04:09,880 --> 00:04:13,400 Speaker 1: in brick and mortar retail postings during the pandemic. Workers 67 00:04:13,440 --> 00:04:16,159 Speaker 1: can't swap out their old job for new one quickly. 68 00:04:16,480 --> 00:04:19,839 Speaker 1: It takes time for people to build up the networks 69 00:04:19,839 --> 00:04:21,960 Speaker 1: down the skills that allow them to move from one 70 00:04:21,960 --> 00:04:26,520 Speaker 1: intitut chunnel. In interviews, out of work Americans described myriad 71 00:04:26,640 --> 00:04:29,880 Speaker 1: challenges preventing them from seeking or winning full time jobs 72 00:04:30,800 --> 00:04:34,240 Speaker 1: like precious. Some say employers are offering fewer hours and 73 00:04:34,320 --> 00:04:39,000 Speaker 1: lower wages. Others are caring for children or elderly family members, 74 00:04:39,080 --> 00:04:42,560 Speaker 1: limiting their ability to work. Many are scared of contracting 75 00:04:42,560 --> 00:04:46,320 Speaker 1: the coronavirus, and some have rethought their careers and opted 76 00:04:46,320 --> 00:04:50,680 Speaker 1: out of traditional employment. Altogether, they're getting by through patchwork 77 00:04:50,720 --> 00:04:55,040 Speaker 1: of help, state jobless benefits, federal and local safety net programs, 78 00:04:55,360 --> 00:05:02,159 Speaker 1: help from family and friends. A lucky few, like Josh 79 00:05:02,360 --> 00:05:05,839 Speaker 1: Organ of Omaha, Nebraska, of ditch their workaday lives for 80 00:05:05,960 --> 00:05:09,920 Speaker 1: riches in cryptocurrency. So it was really hard sitting in 81 00:05:09,960 --> 00:05:13,040 Speaker 1: my office making a few dollars a day or whatever 82 00:05:13,080 --> 00:05:18,000 Speaker 1: it was, and then you know, taking a trade on break, 83 00:05:18,360 --> 00:05:20,320 Speaker 1: on my lunch break and making you know, my whole 84 00:05:20,400 --> 00:05:24,279 Speaker 1: day's age in five minutes. During the pandemic, the thirty 85 00:05:24,320 --> 00:05:26,840 Speaker 1: one year old who used to trade crypto on the side, 86 00:05:26,960 --> 00:05:30,599 Speaker 1: began to feel increasingly frustrated with his day job. He's 87 00:05:30,640 --> 00:05:33,480 Speaker 1: trained as a pediatric nurse and was managing a hospital 88 00:05:33,480 --> 00:05:37,760 Speaker 1: dialysis unit. Last summer, he hired a financial advisor after 89 00:05:37,839 --> 00:05:41,520 Speaker 1: his wife insisted quit his job and jumped full time 90 00:05:41,560 --> 00:05:45,520 Speaker 1: into the fast paced world of crypto. I do remember 91 00:05:45,640 --> 00:05:49,000 Speaker 1: quitting my job and then the next week I made 92 00:05:49,040 --> 00:05:51,760 Speaker 1: like eighty thou dollars on a trade, like in just 93 00:05:51,839 --> 00:05:53,320 Speaker 1: in the first week, And I was like, okay, cool, 94 00:05:53,440 --> 00:05:56,919 Speaker 1: I just made my whole yearly salary at my job 95 00:05:57,000 --> 00:05:59,640 Speaker 1: in a week after quitting crypto. And that was right 96 00:05:59,680 --> 00:06:03,400 Speaker 1: back when the market really started to boom right. Since then, 97 00:06:03,480 --> 00:06:06,160 Speaker 1: he's made more than seven figures and the family has 98 00:06:06,200 --> 00:06:09,039 Speaker 1: been able to purchase a vacation home. He loves the 99 00:06:09,040 --> 00:06:11,719 Speaker 1: flexibility of choosing his own hours and being able to 100 00:06:11,760 --> 00:06:14,599 Speaker 1: care for his newborn. He also has more time for 101 00:06:14,680 --> 00:06:17,760 Speaker 1: exercise and meditation, which he says he ignored for the 102 00:06:17,760 --> 00:06:20,559 Speaker 1: better part of the last decade. Now I'm like starting 103 00:06:20,600 --> 00:06:22,359 Speaker 1: to take care of myself a little bit more too, 104 00:06:22,400 --> 00:06:25,200 Speaker 1: and like trying to be more healthy, um so that 105 00:06:25,240 --> 00:06:27,840 Speaker 1: way I can obviously live longer, just for my family 106 00:06:27,880 --> 00:06:32,000 Speaker 1: and my son. To be sure, many aren't so fortunate, 107 00:06:32,200 --> 00:06:34,640 Speaker 1: and a survey of job seekers that zip Recruiter did 108 00:06:34,640 --> 00:06:37,680 Speaker 1: in September, many people said they're relying on friends and 109 00:06:37,720 --> 00:06:40,680 Speaker 1: family to make ends meet, and more people than ever 110 00:06:40,839 --> 00:06:44,400 Speaker 1: also want a remote job, but those jobs remain concentrated 111 00:06:44,480 --> 00:06:48,600 Speaker 1: in specific industries, so that's another source of the mismatch. 112 00:06:48,600 --> 00:06:52,200 Speaker 1: Wh people are are holding out for remote work opportunities 113 00:06:52,200 --> 00:06:57,359 Speaker 1: which have exploded in business and financial services and insurance 114 00:06:57,400 --> 00:07:00,920 Speaker 1: and tech, but which are non existing in in other 115 00:07:00,960 --> 00:07:05,440 Speaker 1: industries um like. But now people actually have a realistic 116 00:07:05,480 --> 00:07:09,560 Speaker 1: prospect possibly finding a remote job. Those people are are 117 00:07:10,120 --> 00:07:13,080 Speaker 1: waiting out for those jobs in part because the labor 118 00:07:13,120 --> 00:07:15,800 Speaker 1: market is tight. People are also more empowered to be 119 00:07:15,880 --> 00:07:20,880 Speaker 1: picky about respondents in a recent ZIP recruiter survey, so 120 00:07:20,960 --> 00:07:23,560 Speaker 1: they don't feel the financial pressure to accept the first 121 00:07:23,640 --> 00:07:29,840 Speaker 1: job offer they receive. And one final reason Americans are 122 00:07:29,840 --> 00:07:33,800 Speaker 1: staying home their kids. Parents have pointed to the erratic 123 00:07:33,880 --> 00:07:36,800 Speaker 1: nature of school closings and the high cost of childcare 124 00:07:37,040 --> 00:07:40,840 Speaker 1: for their reluctance to re enter the workforce. Zack McGrath 125 00:07:41,040 --> 00:07:43,040 Speaker 1: is a single father of an eleven year old son 126 00:07:43,120 --> 00:07:45,800 Speaker 1: with special needs. He used to work in TV and 127 00:07:45,840 --> 00:07:49,000 Speaker 1: film production before the pandemic and is now looking outside 128 00:07:49,000 --> 00:07:51,840 Speaker 1: the industry because the hours don't give him the flexibility 129 00:07:51,880 --> 00:07:54,720 Speaker 1: to look after a son. If classrooms shut down because 130 00:07:54,760 --> 00:08:00,280 Speaker 1: of COVID cases, the school closing, you know, and even 131 00:08:00,360 --> 00:08:04,440 Speaker 1: just the random four day quarantines are like the sword 132 00:08:04,480 --> 00:08:09,520 Speaker 1: of Damocles. And even if I find this ideal situation, 133 00:08:09,960 --> 00:08:13,000 Speaker 1: you know that it's clearly not out there. That's something 134 00:08:13,040 --> 00:08:16,720 Speaker 1: that no employer is gonna want to deal with. You know, 135 00:08:16,920 --> 00:08:19,520 Speaker 1: just for three days, I can't come in, I can't 136 00:08:19,560 --> 00:08:28,400 Speaker 1: do anything. It's not gonna happen. So in a minute, 137 00:08:28,480 --> 00:08:30,600 Speaker 1: I'm going to talk to the former head of President 138 00:08:30,600 --> 00:08:34,079 Speaker 1: Obama's Council of Economic Advisors, about what's happening to the 139 00:08:34,200 --> 00:08:38,200 Speaker 1: US labor market and just how this great mismatch between 140 00:08:38,320 --> 00:08:41,160 Speaker 1: jobs and workers is going to get resolved, if it 141 00:08:41,200 --> 00:08:43,480 Speaker 1: gets resolved. But first I want to head over the 142 00:08:43,520 --> 00:08:48,400 Speaker 1: Atlantic to tell you about another country also looking for workers, Russia. 143 00:08:49,000 --> 00:08:52,840 Speaker 1: Bloomberg Economy reporter on your Quinn in Moscow is here 144 00:08:52,840 --> 00:08:56,839 Speaker 1: to explain on your thanks for joining Stephanomics. Russia is 145 00:08:57,160 --> 00:09:01,560 Speaker 1: facing a similar problem filling jobs across the economy. But 146 00:09:01,640 --> 00:09:04,880 Speaker 1: I guess in this case it's no mystery where the 147 00:09:04,880 --> 00:09:08,400 Speaker 1: workers have gone, is it. Yeah, that's right, it's definitely so. 148 00:09:09,320 --> 00:09:12,680 Speaker 1: Russia has long had a problem with its aging population 149 00:09:12,920 --> 00:09:16,160 Speaker 1: because of low birth rates during the turmoil in the 150 00:09:16,240 --> 00:09:19,760 Speaker 1: nine nineties after the fall of the Soviet Union UM, 151 00:09:20,000 --> 00:09:22,800 Speaker 1: but now it's got more things that are adding to that. 152 00:09:22,920 --> 00:09:28,240 Speaker 1: So for a long time the UM it relied on 153 00:09:28,720 --> 00:09:32,480 Speaker 1: migrant workers coming from poorer countries that were part of 154 00:09:32,520 --> 00:09:36,840 Speaker 1: the Soviet Union like Uzbekistan, Tajikistan and Kyrgyzstan to fill 155 00:09:36,880 --> 00:09:40,800 Speaker 1: the gap that it couldn't fill with domestic workers. But 156 00:09:40,920 --> 00:09:43,720 Speaker 1: after the pandemic that got a lot more difficult because 157 00:09:44,120 --> 00:09:46,760 Speaker 1: traveling was more difficult and countries closed borders, and a 158 00:09:46,760 --> 00:09:48,920 Speaker 1: lot of those people have gone home. So before the 159 00:09:48,960 --> 00:09:52,880 Speaker 1: pandemic um it was estimated there about four point five 160 00:09:53,200 --> 00:09:56,320 Speaker 1: million migrant workers in Russia, which makes it one of 161 00:09:56,360 --> 00:09:59,560 Speaker 1: the top four destinations for migrant workers in the world. 162 00:10:00,400 --> 00:10:04,960 Speaker 1: But now we think it's about three million people um 163 00:10:05,000 --> 00:10:08,959 Speaker 1: and all that has been made worse by high death 164 00:10:09,080 --> 00:10:13,240 Speaker 1: rates from coronavirus as the government has been reluctant to 165 00:10:14,040 --> 00:10:20,240 Speaker 1: lockdown the economy and vaccine hesitancy has been a big problem. 166 00:10:20,320 --> 00:10:24,240 Speaker 1: How was it manifesting itself? This this shortage of labor? 167 00:10:24,320 --> 00:10:26,720 Speaker 1: Where where do you see that? I know you're often, 168 00:10:26,760 --> 00:10:30,840 Speaker 1: I'm sure talking to businesses across the economy. Yeah, so 169 00:10:31,080 --> 00:10:35,559 Speaker 1: like in some other countries. At first there were big 170 00:10:35,600 --> 00:10:40,280 Speaker 1: shortages in agriculture, but now that's spreading across the economy. 171 00:10:40,440 --> 00:10:44,880 Speaker 1: So retail companies are also struggling to get enough people. 172 00:10:45,800 --> 00:10:50,000 Speaker 1: Another factor is that coreer services are growing really fast, 173 00:10:50,160 --> 00:10:52,920 Speaker 1: and they would have been staffed a lot by migrant 174 00:10:52,920 --> 00:10:56,000 Speaker 1: workers in the past, but because those people aren't around 175 00:10:56,040 --> 00:11:00,520 Speaker 1: anymore than people are shifting to work as carriers and 176 00:11:00,600 --> 00:11:04,800 Speaker 1: leaving gaps in other parts of the economy. So UM. 177 00:11:04,920 --> 00:11:08,080 Speaker 1: For example, X five Group, which is one of Russia's 178 00:11:08,120 --> 00:11:13,600 Speaker 1: biggest retailers, said that high mortality rates are causing problems 179 00:11:13,679 --> 00:11:18,760 Speaker 1: for its labor supply. UM and russ Agar, which is 180 00:11:18,960 --> 00:11:22,559 Speaker 1: one of Russia's biggest agriculture companies, has been increasing wages 181 00:11:22,640 --> 00:11:25,520 Speaker 1: to try and to try and get enough people and 182 00:11:26,440 --> 00:11:29,480 Speaker 1: has had to try and automate some more of its 183 00:11:29,520 --> 00:11:34,640 Speaker 1: work as it struggled to find enough stuff. And obviously 184 00:11:34,720 --> 00:11:37,000 Speaker 1: one of the questions, you know, there's the there's been 185 00:11:37,040 --> 00:11:40,840 Speaker 1: a talk of labor shortages and lots of different countries 186 00:11:41,160 --> 00:11:45,400 Speaker 1: and UM. One of the question marks is about how 187 00:11:45,480 --> 00:11:47,800 Speaker 1: much is going to feed into wages and how much 188 00:11:47,880 --> 00:11:51,480 Speaker 1: that will then feed inflation and make this inflation that 189 00:11:51,480 --> 00:11:53,280 Speaker 1: we're seeing in a lot of countries not so as 190 00:11:53,320 --> 00:11:57,480 Speaker 1: not as temporary as as people were hoping. How is 191 00:11:57,520 --> 00:12:00,439 Speaker 1: that playing out in Russia? Wages go up, is that 192 00:12:00,520 --> 00:12:04,199 Speaker 1: pushing up inflation? Yeah? So, like I said, rus I 193 00:12:04,280 --> 00:12:09,960 Speaker 1: grow say they've raised wages UM up to ten percent. 194 00:12:10,800 --> 00:12:15,400 Speaker 1: In some sectors wags have been increasing more than that, 195 00:12:15,720 --> 00:12:20,000 Speaker 1: and that's definitely feeding into inflation and inflation here is 196 00:12:20,480 --> 00:12:24,760 Speaker 1: UM is a political problem for put into because um, 197 00:12:25,080 --> 00:12:29,440 Speaker 1: it really hits living standards. And at the moment, uh, 198 00:12:30,040 --> 00:12:32,680 Speaker 1: it's how high is it now? At the moment, it's 199 00:12:32,720 --> 00:12:35,960 Speaker 1: at the highest in five years. It's about eight percent, 200 00:12:36,400 --> 00:12:39,920 Speaker 1: which is a way above the Bank of Russia's target. 201 00:12:40,520 --> 00:12:45,680 Speaker 1: And so Bank of Russia has been aggressively hiking rates 202 00:12:45,760 --> 00:12:49,640 Speaker 1: to try and bring inflation down, but so far it 203 00:12:49,679 --> 00:12:52,880 Speaker 1: doesn't seem to be having much of an effect. So 204 00:12:53,160 --> 00:12:57,679 Speaker 1: this isn't just a problem for the economy. It also 205 00:12:57,760 --> 00:13:02,720 Speaker 1: has the potential to slow down growth in Russia and 206 00:13:03,640 --> 00:13:08,080 Speaker 1: even undermine Putin's popularity. Yeah, if you can't get so, 207 00:13:08,080 --> 00:13:10,320 Speaker 1: you've got some you've got inflation and wages going up. 208 00:13:10,320 --> 00:13:13,760 Speaker 1: But also the central bank kind of slamming on the brakes, 209 00:13:13,760 --> 00:13:17,720 Speaker 1: slowing economy exactly. And people remember when there was runaway 210 00:13:17,800 --> 00:13:21,760 Speaker 1: inflation in the nineties and how that hit living standards. 211 00:13:21,800 --> 00:13:23,360 Speaker 1: That means that it's much more of the front of 212 00:13:23,360 --> 00:13:26,880 Speaker 1: people's minds here and consistently and polls people say that 213 00:13:28,040 --> 00:13:32,679 Speaker 1: rising prices are the biggest problem. So one of the 214 00:13:32,679 --> 00:13:35,080 Speaker 1: reasons the story had caught my eye was that there 215 00:13:35,200 --> 00:13:40,280 Speaker 1: was some pretty aggressive tactics that the Russians. Russia being Russia, 216 00:13:40,920 --> 00:13:44,000 Speaker 1: there's been some pretty extreme solutions to this problem that 217 00:13:44,040 --> 00:13:45,960 Speaker 1: they've come up with over the years. And I guess 218 00:13:45,960 --> 00:13:50,680 Speaker 1: and maybe looking to now. Yeah, so earlier this year, 219 00:13:51,080 --> 00:13:56,760 Speaker 1: prisoners were brought in to work on railroad upgrades, UM, 220 00:13:56,920 --> 00:14:04,480 Speaker 1: for for like cold transportation. UM. And that's kind of 221 00:14:04,520 --> 00:14:08,280 Speaker 1: particularly scary here because it brings back echoes of labor 222 00:14:08,280 --> 00:14:11,200 Speaker 1: camps and Soviet times where prisoners had to work in 223 00:14:11,280 --> 00:14:15,480 Speaker 1: mining or forestry or well reconstruction. So for so far 224 00:14:15,640 --> 00:14:20,080 Speaker 1: that's on a pretty small scale, but people are consistently 225 00:14:20,080 --> 00:14:24,480 Speaker 1: talking about how to solve this with getting more prisoners 226 00:14:24,520 --> 00:14:28,800 Speaker 1: to work. UM. In agriculture, they were looking at getting 227 00:14:28,920 --> 00:14:32,720 Speaker 1: students to help with the harvest, and last year prisoners 228 00:14:32,760 --> 00:14:37,400 Speaker 1: also helped with the harvest. And in some regions, UM, 229 00:14:37,680 --> 00:14:40,400 Speaker 1: the government has also looked at bringing in the army 230 00:14:40,480 --> 00:14:45,200 Speaker 1: to work on some construction projects. We've gotta worry when 231 00:14:45,200 --> 00:14:48,840 Speaker 1: people start bringing the army to do anything. And I 232 00:14:48,840 --> 00:14:50,920 Speaker 1: can imagine, Yeah, that's sort of shades of some of 233 00:14:50,960 --> 00:14:53,680 Speaker 1: those sort of false labor camps and everything. Yeah, well 234 00:14:53,720 --> 00:14:57,240 Speaker 1: all of those as well. I think companies aren't necessarily 235 00:14:57,280 --> 00:14:59,440 Speaker 1: that keen on these ideas. Like I remember I was 236 00:14:59,480 --> 00:15:01,760 Speaker 1: talking to one agricultural company about whether it would help 237 00:15:01,800 --> 00:15:05,520 Speaker 1: to get prisoners to um collect the harvest, and they 238 00:15:05,520 --> 00:15:08,280 Speaker 1: said there were a number of problems, including that they 239 00:15:08,360 --> 00:15:10,640 Speaker 1: might not be very good at it. They might, you know, 240 00:15:10,680 --> 00:15:13,800 Speaker 1: you need particular set of skills, especially if you're picking 241 00:15:13,840 --> 00:15:17,680 Speaker 1: soft fruits, for example, and also sometimes prisoners run away, 242 00:15:17,680 --> 00:15:22,000 Speaker 1: which is another problem. Then I can see that. And 243 00:15:22,040 --> 00:15:25,520 Speaker 1: what about I mean the immigrants. Obviously it's part of 244 00:15:25,520 --> 00:15:28,560 Speaker 1: the issue is that they're not coming back from from 245 00:15:28,560 --> 00:15:31,440 Speaker 1: Central Asia in these places where they had previously come 246 00:15:31,560 --> 00:15:34,640 Speaker 1: from to work in Russia. Are there any efforts underway 247 00:15:34,720 --> 00:15:40,920 Speaker 1: to encourage them back. Yeah, so, um, they're looking at 248 00:15:41,480 --> 00:15:46,200 Speaker 1: potentially putting on charter trains that would bring migrant workers 249 00:15:46,280 --> 00:15:49,720 Speaker 1: from Tasha, Kent and Uzbekistan to Russia, which would take 250 00:15:49,760 --> 00:15:52,640 Speaker 1: several days on the train. And there's also recently an 251 00:15:52,680 --> 00:15:57,240 Speaker 1: amnesty which meant that migrants who had previously been expelled 252 00:15:58,160 --> 00:16:02,200 Speaker 1: for various reasons be allowed back in now. But at 253 00:16:02,200 --> 00:16:05,480 Speaker 1: the same time, there's a lot of stories and state 254 00:16:05,520 --> 00:16:10,920 Speaker 1: media about migrant workers and crime, which looks like it's 255 00:16:10,960 --> 00:16:14,720 Speaker 1: pushing the other way, even if the situation now is 256 00:16:14,800 --> 00:16:18,440 Speaker 1: pretty extreme. Well on you, as we said that things 257 00:16:18,440 --> 00:16:22,800 Speaker 1: are often extreme in Russia. But I appreciate you you 258 00:16:22,960 --> 00:16:25,880 Speaker 1: telling us about this, uh, this challenge that Russia is 259 00:16:25,920 --> 00:16:30,280 Speaker 1: facing on your Quinn great, Thanks very much, m H. 260 00:16:37,600 --> 00:16:40,040 Speaker 1: Now we're going to shift the focus back west to 261 00:16:40,160 --> 00:16:43,240 Speaker 1: the US and the labor market conundrum we heard about 262 00:16:43,280 --> 00:16:46,080 Speaker 1: at the start of the program, and I'm delighted to 263 00:16:46,160 --> 00:16:48,800 Speaker 1: have joining as Jason Furman, Professor of the Practice of 264 00:16:48,840 --> 00:16:51,920 Speaker 1: Economic Policy at Harvard University and the Kennedy School of 265 00:16:51,920 --> 00:16:55,320 Speaker 1: Government and a senior researcher at the Peterson Institute in Washington, 266 00:16:55,560 --> 00:17:00,960 Speaker 1: but previously chair of President Obama's Council of Economic Advice US. Jason, 267 00:17:01,080 --> 00:17:04,760 Speaker 1: thank you for joining Stephanomics once again. And the picture 268 00:17:04,800 --> 00:17:07,639 Speaker 1: we had at the start of the program was an economy, 269 00:17:07,680 --> 00:17:10,840 Speaker 1: a US economy in which there were job vacancies everywhere, 270 00:17:10,880 --> 00:17:14,200 Speaker 1: it seemed, but no work for the unemployed. How would 271 00:17:14,240 --> 00:17:17,760 Speaker 1: you characterize it? It's a labor market like none of 272 00:17:17,840 --> 00:17:20,640 Speaker 1: us have ever seen before. Where about you know, six 273 00:17:20,720 --> 00:17:23,080 Speaker 1: or seven million jobs short of where we should be, 274 00:17:24,000 --> 00:17:28,080 Speaker 1: but there's still millions and millions of job openings, and 275 00:17:28,160 --> 00:17:32,120 Speaker 1: so overall the problem looks more like labor supply than 276 00:17:32,160 --> 00:17:35,600 Speaker 1: the problem we're more used to normally, which is labor demand. 277 00:17:37,440 --> 00:17:39,800 Speaker 1: And of course some say this isn't when people talk 278 00:17:39,840 --> 00:17:46,200 Speaker 1: about job shortages, real worker shortages, that it's really it's 279 00:17:46,200 --> 00:17:49,520 Speaker 1: not a shortage of of workers, it's a shortage of 280 00:17:50,000 --> 00:17:53,040 Speaker 1: good jobs that if the wages will hire, people would 281 00:17:53,080 --> 00:17:55,359 Speaker 1: be doing these jobs. Yeah, I mean, you do have 282 00:17:55,400 --> 00:17:59,800 Speaker 1: to ask why two years ago people were doing these 283 00:18:00,040 --> 00:18:02,840 Speaker 1: jobs at a certain wage and now they don't want 284 00:18:02,840 --> 00:18:05,280 Speaker 1: to do those jobs at the same wage, only want 285 00:18:05,320 --> 00:18:08,080 Speaker 1: to do them at a higher wage. The way I 286 00:18:08,160 --> 00:18:11,639 Speaker 1: teach my introductory economics students, we would describe that as 287 00:18:11,640 --> 00:18:14,160 Speaker 1: a shift of the supply curve. To get the same 288 00:18:14,200 --> 00:18:17,280 Speaker 1: amount of labor as before. You can only get there 289 00:18:17,640 --> 00:18:20,119 Speaker 1: if you're doing it at a higher wage than it 290 00:18:20,280 --> 00:18:22,960 Speaker 1: was before. And how do you think that's going to 291 00:18:23,040 --> 00:18:25,960 Speaker 1: play Is he going to just play out in wages 292 00:18:26,080 --> 00:18:28,720 Speaker 1: reaching a higher level or are they going to be 293 00:18:29,280 --> 00:18:32,800 Speaker 1: you know, are there sort of deeper skill mismatches at 294 00:18:32,800 --> 00:18:36,240 Speaker 1: work where the people who are looking for jobs are 295 00:18:36,280 --> 00:18:39,919 Speaker 1: just not the same, just not the right people for 296 00:18:40,280 --> 00:18:43,239 Speaker 1: these many vacancies that are there. Right, So, first of all, 297 00:18:43,680 --> 00:18:47,480 Speaker 1: large dose of humility, as in order. No one predicted 298 00:18:47,520 --> 00:18:50,680 Speaker 1: that the labor markets were gonna look nearly this extreme 299 00:18:50,760 --> 00:18:53,560 Speaker 1: at this point in time. I certainly didn't, and so 300 00:18:53,680 --> 00:18:55,280 Speaker 1: I'm not going to tell you I know for sure 301 00:18:55,320 --> 00:18:57,639 Speaker 1: what it's going to look like. UM a year or 302 00:18:57,680 --> 00:19:01,480 Speaker 1: two from now. UM, if forced to my best guess, 303 00:19:01,840 --> 00:19:06,240 Speaker 1: I think there are enough temporary factors that explain where 304 00:19:06,280 --> 00:19:10,400 Speaker 1: we are now related to COVID, coming out of COVID 305 00:19:10,760 --> 00:19:13,680 Speaker 1: and in the United States, the policy response to COVID 306 00:19:14,080 --> 00:19:17,600 Speaker 1: that I think we'll get of the way back to 307 00:19:17,680 --> 00:19:21,240 Speaker 1: where we were. Um, it just may take a year 308 00:19:21,320 --> 00:19:24,320 Speaker 1: or two to get there, But you know, there's a 309 00:19:24,400 --> 00:19:26,040 Speaker 1: risk to that and a risk that this is a 310 00:19:26,040 --> 00:19:29,880 Speaker 1: more permanent change. And I guess one of the ways 311 00:19:29,920 --> 00:19:32,280 Speaker 1: that we get from here to there would be wages 312 00:19:32,640 --> 00:19:36,360 Speaker 1: going up and then inflation going up, potentially staying up. 313 00:19:36,760 --> 00:19:40,080 Speaker 1: You know, we had another round of pretty eye popping 314 00:19:40,400 --> 00:19:43,040 Speaker 1: US inflation numbers this week. Do you think that is 315 00:19:43,080 --> 00:19:45,080 Speaker 1: going to play a part that we will see more 316 00:19:45,200 --> 00:19:50,600 Speaker 1: during enduring inflation driven by wages another place where humility 317 00:19:50,680 --> 00:19:54,480 Speaker 1: is in order. UM, we haven't seen wage price spirals 318 00:19:54,520 --> 00:19:57,840 Speaker 1: for a very long time. If there's anything that could 319 00:19:57,840 --> 00:20:01,240 Speaker 1: bring a wage price spiral back, it is what we've 320 00:20:01,280 --> 00:20:07,960 Speaker 1: seen with extremely high inflation this past year, and um, 321 00:20:08,000 --> 00:20:10,960 Speaker 1: you know the way that's affecting workers and labor markets 322 00:20:11,000 --> 00:20:15,120 Speaker 1: and businesses. So I think that's a distinct upward risk 323 00:20:15,600 --> 00:20:19,399 Speaker 1: for inflation at this point in time. I guess we 324 00:20:19,400 --> 00:20:22,520 Speaker 1: should have a little pause just to sort of reflect 325 00:20:22,600 --> 00:20:27,120 Speaker 1: on on those latest inflation numbers, just to put them 326 00:20:27,119 --> 00:20:29,479 Speaker 1: in put it in perspective for us, just what happened 327 00:20:29,520 --> 00:20:32,920 Speaker 1: one month, let alone what's happened on the twelve month horizon. Yeah, 328 00:20:33,359 --> 00:20:36,320 Speaker 1: so in October the cp I went up zero point 329 00:20:36,400 --> 00:20:39,919 Speaker 1: nine percent. A bunch of that was gasoline more expensive, 330 00:20:40,000 --> 00:20:43,679 Speaker 1: that's something global. But you strip out the vaulatile components, 331 00:20:43,720 --> 00:20:46,960 Speaker 1: the core cp I was up zero point six um. 332 00:20:47,000 --> 00:20:50,680 Speaker 1: And that's a real blow to the transitory stories which 333 00:20:50,720 --> 00:20:53,960 Speaker 1: had been pointing out the slowing. Of course c p 334 00:20:54,119 --> 00:20:58,639 Speaker 1: I projecting more slowing, of course c p I. So 335 00:20:58,680 --> 00:21:02,360 Speaker 1: I think this report, broadly speaking, says, buckle your seat belts. 336 00:21:02,640 --> 00:21:08,359 Speaker 1: You know, this isn't slowing down dramatically anytime soon. And 337 00:21:08,400 --> 00:21:10,560 Speaker 1: as you suggest, I mean that's even after taking out 338 00:21:10,640 --> 00:21:12,400 Speaker 1: quite a few things. I mean, sometimes when people talk 339 00:21:12,440 --> 00:21:14,960 Speaker 1: about the core and taking out the volatile things, you know, 340 00:21:15,440 --> 00:21:17,399 Speaker 1: for some people that's taking out all the things they 341 00:21:17,440 --> 00:21:21,240 Speaker 1: actually want to buy on a given day. Oh yeah. Oh. Politically, 342 00:21:22,240 --> 00:21:24,880 Speaker 1: what matters actually is almost the opposite of core. It's 343 00:21:24,920 --> 00:21:29,320 Speaker 1: what's happening to food prices and gasoline prices. UM. Core 344 00:21:29,400 --> 00:21:32,840 Speaker 1: is a good construct analytically because it gives you a 345 00:21:32,880 --> 00:21:35,600 Speaker 1: better prediction of where inflation will be a year from now. 346 00:21:35,880 --> 00:21:39,360 Speaker 1: But to understand what people have experienced over the last year, Um, 347 00:21:39,359 --> 00:21:44,159 Speaker 1: they've experienced prices up six point two percent, and and 348 00:21:44,240 --> 00:21:47,760 Speaker 1: they hate that. And I know we're going to you're 349 00:21:47,760 --> 00:21:51,479 Speaker 1: gonna start talking about humility again. But when you have 350 00:21:51,640 --> 00:21:54,000 Speaker 1: you know, you're sitting in sitting at Harvard at least 351 00:21:54,000 --> 00:21:56,720 Speaker 1: some of the time, and you know, with your with 352 00:21:56,840 --> 00:21:59,840 Speaker 1: that more academic kind of long term perspective, I just 353 00:22:00,080 --> 00:22:03,119 Speaker 1: under what you were thinking now about the legacy of 354 00:22:03,359 --> 00:22:05,800 Speaker 1: COVID for the for the labor market. I mean, when 355 00:22:05,800 --> 00:22:07,480 Speaker 1: a lot of people lose their jobs, and it was 356 00:22:07,520 --> 00:22:10,679 Speaker 1: a really a lot of unprecedented number of people in 357 00:22:10,720 --> 00:22:13,680 Speaker 1: a short time last year, we tend to worry about 358 00:22:13,760 --> 00:22:17,440 Speaker 1: not just the immediate loss of output that they aren't 359 00:22:17,480 --> 00:22:19,600 Speaker 1: able to produce because they're not in work, but the 360 00:22:19,800 --> 00:22:22,160 Speaker 1: know how that they've built up in those jobs which 361 00:22:22,240 --> 00:22:25,720 Speaker 1: might be lost forever might affect their human capital and 362 00:22:25,760 --> 00:22:28,920 Speaker 1: the human capital of the country. UM. We had hoped 363 00:22:28,920 --> 00:22:31,000 Speaker 1: that that would not be such a factor this time, 364 00:22:31,080 --> 00:22:34,960 Speaker 1: because not least because it was a relatively brief crisis, 365 00:22:35,040 --> 00:22:38,840 Speaker 1: but also a lot of the most affected sectors were 366 00:22:38,880 --> 00:22:42,040 Speaker 1: places where there weren't a lot of specific skills to 367 00:22:42,119 --> 00:22:44,960 Speaker 1: be lost. UM, what do you what do you think 368 00:22:45,000 --> 00:22:48,840 Speaker 1: one year on about the sort of human capital cost 369 00:22:49,000 --> 00:22:51,680 Speaker 1: of that enormous spike in unemployment we had last year. 370 00:22:52,240 --> 00:22:55,719 Speaker 1: I think it's likely meaningful. There's been a lot of 371 00:22:55,800 --> 00:23:00,360 Speaker 1: long term unemployment. People really do lose skills, they lose 372 00:23:00,400 --> 00:23:03,479 Speaker 1: out on the training they were getting on the job, 373 00:23:04,200 --> 00:23:07,720 Speaker 1: they get dislocated in a certain way. All the evidence 374 00:23:07,720 --> 00:23:10,200 Speaker 1: we've had from the past is that can have long 375 00:23:10,320 --> 00:23:15,960 Speaker 1: term impacts on sustainable unemployment rates, on wages, and on 376 00:23:16,119 --> 00:23:20,639 Speaker 1: productivity in the economy. That's compounded by the fact that 377 00:23:20,640 --> 00:23:23,840 Speaker 1: we've had low business investment for the last year and 378 00:23:23,840 --> 00:23:26,479 Speaker 1: a half and some of the steps you'll need to 379 00:23:26,520 --> 00:23:30,400 Speaker 1: take to harden against COVID. It's possible that work from 380 00:23:30,440 --> 00:23:35,040 Speaker 1: home and you know, doing teleconferences rather than flying places 381 00:23:35,400 --> 00:23:39,440 Speaker 1: will make up for all of that, But I would 382 00:23:39,440 --> 00:23:42,199 Speaker 1: go with the evidence we have from the past, and 383 00:23:42,200 --> 00:23:46,280 Speaker 1: the evidence we have from the past says experience here 384 00:23:46,320 --> 00:23:49,520 Speaker 1: is quite negative. There's a bit of hope. Um, I 385 00:23:49,560 --> 00:23:52,440 Speaker 1: hope that hope triumphs over experience, but I wouldn't I 386 00:23:52,480 --> 00:23:55,240 Speaker 1: wouldn't count on it. But it's interesting. This was something 387 00:23:55,280 --> 00:23:59,080 Speaker 1: that that I had thought about for some papers that 388 00:23:59,080 --> 00:24:01,480 Speaker 1: we've put together for for the New Economy Forum that 389 00:24:01,520 --> 00:24:05,240 Speaker 1: Bloomberg's holding in Singapore next week. At this sense of 390 00:24:05,280 --> 00:24:08,800 Speaker 1: this idea of whether what the long term impact on 391 00:24:08,840 --> 00:24:11,960 Speaker 1: productivity and output might be of this crisis, and whether 392 00:24:12,000 --> 00:24:14,680 Speaker 1: it might be different from other recessions. As you say, 393 00:24:14,920 --> 00:24:17,560 Speaker 1: you know, the lesson usually is recessions always cause some 394 00:24:17,640 --> 00:24:22,160 Speaker 1: permanent damage, especially to human capital, but also the investment 395 00:24:22,240 --> 00:24:25,119 Speaker 1: base of the country. But you do have you know, 396 00:24:25,160 --> 00:24:29,760 Speaker 1: the International Monetary Fund and some other important forecasters now 397 00:24:29,840 --> 00:24:32,840 Speaker 1: suggesting some kind of COVID dividend for at least some 398 00:24:32,960 --> 00:24:36,639 Speaker 1: of the advanced economies, including the US that actually whether 399 00:24:36,720 --> 00:24:41,000 Speaker 1: it's the infrastructure investments by the US administration post COVID, 400 00:24:41,640 --> 00:24:44,840 Speaker 1: or some of the productivity changes that you talked about 401 00:24:44,880 --> 00:24:49,000 Speaker 1: working from home, faster digitalization all of US, or maybe 402 00:24:49,200 --> 00:24:51,880 Speaker 1: companies using automation more. But all of us using kind 403 00:24:51,920 --> 00:24:55,359 Speaker 1: of teller teller working and all the things more that 404 00:24:55,480 --> 00:24:57,600 Speaker 1: all of that was actually going to put the economy, 405 00:24:57,680 --> 00:25:00,760 Speaker 1: the economy at least in a better place than it 406 00:25:01,080 --> 00:25:04,720 Speaker 1: than we would have expected pre COVID. Do you does 407 00:25:04,800 --> 00:25:06,760 Speaker 1: that make any sense to you? Or do you think 408 00:25:06,800 --> 00:25:09,919 Speaker 1: that there's an we're underestimating some of the negatives that 409 00:25:09,960 --> 00:25:13,720 Speaker 1: you just mentioned. Yeah, I think that's certainly possible. Um, 410 00:25:13,760 --> 00:25:16,720 Speaker 1: we could have a COVID dividend coming out of this. Now. 411 00:25:16,760 --> 00:25:18,520 Speaker 1: I should point out the I, M F and other 412 00:25:18,560 --> 00:25:22,000 Speaker 1: forecasters we're expecting for the United States that we'd see 413 00:25:22,000 --> 00:25:26,040 Speaker 1: that dividend as soon as Q four of one. They 414 00:25:26,080 --> 00:25:29,119 Speaker 1: had a forecast for g d P post pandemic that 415 00:25:29,240 --> 00:25:33,280 Speaker 1: was higher than their pre pandemic forecast. Um, that's not 416 00:25:33,600 --> 00:25:37,640 Speaker 1: I'm going to materialize. So the schedule for this dividend materializing, 417 00:25:37,640 --> 00:25:42,200 Speaker 1: at least in the United States m keeps getting pushed out. 418 00:25:42,240 --> 00:25:47,280 Speaker 1: But I do broadly think that anyone saying that is 419 00:25:47,520 --> 00:25:50,600 Speaker 1: has a sort of hopeful narrative about the present that 420 00:25:50,680 --> 00:25:53,360 Speaker 1: we don't really have any evidence or data for this logic, 421 00:25:53,440 --> 00:25:56,359 Speaker 1: this theory. There's intuition, but there's no hard data, and 422 00:25:56,359 --> 00:25:59,119 Speaker 1: that that's going to overcome the very very strong data 423 00:25:59,160 --> 00:26:02,880 Speaker 1: we have about what's happened historically when we've had periods 424 00:26:02,880 --> 00:26:08,120 Speaker 1: of prolonged high unemployment and under investment. Clearly there has 425 00:26:08,240 --> 00:26:13,879 Speaker 1: been great concern that during the pandemic, but potentially also 426 00:26:13,920 --> 00:26:17,840 Speaker 1: in the legacy of the pandemic, inequalities that we already 427 00:26:17,840 --> 00:26:21,600 Speaker 1: had are going to have been entrenched and even accelerated 428 00:26:21,640 --> 00:26:25,320 Speaker 1: intensified in some cases, and you've almost highlighted them in 429 00:26:25,359 --> 00:26:27,520 Speaker 1: some of the things that you've You've said, you know 430 00:26:27,560 --> 00:26:31,040 Speaker 1: that the potential for people to lose human capital having 431 00:26:31,080 --> 00:26:35,119 Speaker 1: lost jobs, just as actually some of the more skilled 432 00:26:35,520 --> 00:26:39,359 Speaker 1: and well positioned members of the workforce are actually enjoying 433 00:26:39,400 --> 00:26:44,399 Speaker 1: more productivity, enjoying working from home, potentially even relocating to 434 00:26:45,000 --> 00:26:48,920 Speaker 1: bigger houses outside the city and other things. So how 435 00:26:48,920 --> 00:26:53,280 Speaker 1: do you see that sort of inequality impact of COVID. Yeah, 436 00:26:53,359 --> 00:26:55,560 Speaker 1: the last two years have been a huge blow to 437 00:26:55,760 --> 00:27:00,960 Speaker 1: market incomes for households towards the bottom of the economics spectrum, 438 00:27:01,000 --> 00:27:05,200 Speaker 1: but a hugely progressive response that at least temporarily helped 439 00:27:05,240 --> 00:27:08,320 Speaker 1: them much more than it helped anyone else. Um, of course, 440 00:27:08,359 --> 00:27:11,880 Speaker 1: that response is mostly ending except for money for children, 441 00:27:11,920 --> 00:27:14,600 Speaker 1: which looks like it will last at least another year. 442 00:27:14,760 --> 00:27:19,679 Speaker 1: I hope longer than that. Um, you have seen faster 443 00:27:19,760 --> 00:27:23,000 Speaker 1: wage growth for lower wage workers than higher wage workers. 444 00:27:23,040 --> 00:27:26,159 Speaker 1: We saw that before the pandemic, We've seen that during 445 00:27:26,200 --> 00:27:32,080 Speaker 1: the pandemic, So you know, all in I think it 446 00:27:32,160 --> 00:27:36,959 Speaker 1: will be roughly neutral for income inequality and has raised 447 00:27:37,000 --> 00:27:40,960 Speaker 1: wealth inequality because we've seen what's happened to equity markets 448 00:27:41,200 --> 00:27:45,359 Speaker 1: and the like. And finally, I think we spoke at 449 00:27:45,359 --> 00:27:48,959 Speaker 1: the beginning of the year when the history of the 450 00:27:49,160 --> 00:27:52,560 Speaker 1: Biden administration was a book that had still all empty 451 00:27:52,600 --> 00:27:57,040 Speaker 1: pages and there was we were thinking about how transformational 452 00:27:57,240 --> 00:28:04,520 Speaker 1: their President Biden's economic policies might be and considering the 453 00:28:04,560 --> 00:28:07,439 Speaker 1: economic yeah, the economic impact of this one year and 454 00:28:07,480 --> 00:28:10,200 Speaker 1: the programs that were unveiled in the first few months 455 00:28:10,240 --> 00:28:13,560 Speaker 1: of the administration, it's it's been a pretty hard slog 456 00:28:14,640 --> 00:28:16,480 Speaker 1: I know, you won't want to knock the people who 457 00:28:16,480 --> 00:28:18,119 Speaker 1: are doing some of the jobs that you've done in 458 00:28:18,119 --> 00:28:20,199 Speaker 1: the past, but we know where are where do you 459 00:28:20,200 --> 00:28:23,480 Speaker 1: think we are now? And how are we doing relative 460 00:28:23,560 --> 00:28:26,679 Speaker 1: to that kind of transformative hope that some people might 461 00:28:26,720 --> 00:28:29,240 Speaker 1: have had at the beginning of the year, given the 462 00:28:29,359 --> 00:28:33,880 Speaker 1: political hand the White House has been dealt. They're running 463 00:28:33,880 --> 00:28:37,600 Speaker 1: ahead of my expectations for what they'd be able to pass. 464 00:28:37,720 --> 00:28:41,320 Speaker 1: They need to get unanimity for one part of their agenda, 465 00:28:41,360 --> 00:28:43,120 Speaker 1: which is going to be really hard to do, but 466 00:28:43,200 --> 00:28:45,080 Speaker 1: it looks like they're probably going to do it. And 467 00:28:45,080 --> 00:28:48,640 Speaker 1: they actually got bipartisan support, especially in the Senate um 468 00:28:48,720 --> 00:28:51,600 Speaker 1: for another part of their agenda. So they're getting more 469 00:28:51,640 --> 00:28:56,040 Speaker 1: done than I expected. They're getting, you know, of what 470 00:28:56,120 --> 00:28:58,800 Speaker 1: the President wanted done, and he wanted quite a lot, 471 00:28:58,880 --> 00:29:02,120 Speaker 1: and of a lot art is still a decent amount. 472 00:29:02,480 --> 00:29:05,280 Speaker 1: But no, it's not going to change everything. Um. It's 473 00:29:05,320 --> 00:29:08,080 Speaker 1: not going to set climate change. It's not going to 474 00:29:08,200 --> 00:29:11,960 Speaker 1: make even preschool universal, so um. But it's it's I 475 00:29:12,000 --> 00:29:14,080 Speaker 1: think it's a good start, um for in terms of 476 00:29:14,160 --> 00:29:17,760 Speaker 1: medium and long run fiscal fillers. A good note to it. 477 00:29:17,960 --> 00:29:31,800 Speaker 1: Jason Firman, thank you very much. Thank you. That's it 478 00:29:31,840 --> 00:29:34,560 Speaker 1: for this episode of Stephanomics. Next week we'll be in 479 00:29:34,640 --> 00:29:39,520 Speaker 1: Singapore with special episodes from the Bloomberg New Economy Forum, including, 480 00:29:39,680 --> 00:29:43,360 Speaker 1: among other highlights, Larry Summers on inflation and the dangers 481 00:29:43,440 --> 00:29:47,200 Speaker 1: of woke central banking, the future of cities, where the 482 00:29:47,280 --> 00:29:50,680 Speaker 1: green finance really can save the world, So tune in 483 00:29:50,680 --> 00:29:53,480 Speaker 1: for all that and follow at economics on Twitter for 484 00:29:53,560 --> 00:29:56,520 Speaker 1: more news and analysis from Bloomberg Economics, from the New 485 00:29:56,520 --> 00:30:00,160 Speaker 1: Economy Forum and around the world. This episode, it was 486 00:30:00,200 --> 00:30:02,880 Speaker 1: produced by Mangus Hendrickson, and the story from the US 487 00:30:03,000 --> 00:30:07,240 Speaker 1: was reported by Jill Shah and Katia Dmitrieva. Special thanks 488 00:30:07,280 --> 00:30:11,320 Speaker 1: also to Anya Quinn and Jason Furman. Mike Sasso is 489 00:30:11,360 --> 00:30:14,560 Speaker 1: executive producer of Stephanomics and the head of Bloomberg Podcast 490 00:30:14,800 --> 00:30:15,680 Speaker 1: is Francesco Levi.