WEBVTT - Chinese Workers Are Saying Enough Is Enough, and Xi Is Not Amused 0:00:00.280 --> 0:00:06.480 Wow, she was like sugar red, qunchy like chips and 0:00:06.519 --> 0:00:16.159 stuff like that. Actually, the days are crickets. Hello and 0:00:16.200 --> 0:00:19.000 welcome to Stephanomics, the podcast that brings the global economy 0:00:19.040 --> 0:00:21.680 to you. What you heard there might well be your 0:00:21.720 --> 0:00:24.759 Christmas dinner in a few years time. Keep listening to 0:00:24.800 --> 0:00:27.639 find out what those lucky people were tasting why it 0:00:27.760 --> 0:00:31.480 might just save the world. We also tell you about 0:00:31.480 --> 0:00:34.760 a new treasure trove of data showing just how much 0:00:34.840 --> 0:00:37.879 federal stimulus checks have boosted the spending of black and 0:00:37.920 --> 0:00:42.160 Hispanic families and how inflation and a slower economy could 0:00:42.159 --> 0:00:45.959 take them back to square one. But first tune in, 0:00:46.240 --> 0:00:50.240 drop out, Live flat. Their parents may have worked twelve 0:00:50.320 --> 0:00:54.720 hour days for decades, supporting China's breakneck economic growth, but 0:00:54.800 --> 0:00:57.840 a growing number of young people in this famously industrious 0:00:57.920 --> 0:01:01.160 nation would rather not work at all. You could say 0:01:01.520 --> 0:01:05.040 it was the Asian counterpart to the Great Resignation that 0:01:05.120 --> 0:01:08.480 has business executives scratching their heads in the US and Europe. 0:01:09.000 --> 0:01:11.319 But the life flat movement also tells us quite a 0:01:11.319 --> 0:01:15.280 lot about how Chinese society has changed, and it could 0:01:15.280 --> 0:01:18.240 even put the government's grand plans for the future at risk. 0:01:19.000 --> 0:01:21.640 In a minute, I'll discuss all of that with Bloomberg 0:01:21.640 --> 0:01:24.759 opinion columnist Truly Rehn. But first here is our Hong 0:01:24.840 --> 0:01:35.000 Kong based China economy reporter Tom Hancock. In what has 0:01:35.040 --> 0:01:38.800 been branded as the Great Resignation, US workers are quitting 0:01:38.840 --> 0:01:42.280 their jobs in record numbers. More than twenty four million 0:01:42.360 --> 0:01:45.840 did so from April to September this year. Millions have 0:01:45.920 --> 0:01:49.720 dropped permanently out of the labor force, and similar trends 0:01:49.800 --> 0:01:53.559 are being seen in parts of Europe. But even in China, 0:01:53.920 --> 0:01:57.200 where coronavirus has been kept largely under control and the 0:01:57.240 --> 0:02:00.559 economy has doubled in size in the last decade, people 0:02:00.680 --> 0:02:05.480 are having similar feelings. The country's live flat movement, jump 0:02:05.560 --> 0:02:09.160 started by a social media post, is also about opting out. 0:02:09.760 --> 0:02:12.320 It's a reaction against the system in which are grueling 0:02:12.440 --> 0:02:16.480 nine six work schedule nine am to nine pm, six 0:02:16.560 --> 0:02:20.600 days a week is common in industries like technology, so 0:02:20.800 --> 0:02:24.760 is unrelenting pressure from family, society, and even the government 0:02:24.960 --> 0:02:30.400 to keep climbing the ladder. In October, thousands of employees 0:02:30.440 --> 0:02:33.800 at Chinese tech giants, including Ali Baba Group and the 0:02:33.840 --> 0:02:36.960 owner of TikTok groused about their long work hours in 0:02:37.000 --> 0:02:41.200 an online campaign called workers Lives Matter and It's not 0:02:41.280 --> 0:02:44.520 just a white color phenomenon. In the southern city of Shenjen, 0:02:44.880 --> 0:02:48.440 migrant workers from the countryside, once celebrated for being willing 0:02:48.480 --> 0:02:52.280 to work tough jobs in manufacturing, are rejecting manual jobs 0:02:52.400 --> 0:02:55.520 and sometimes prefer to spend their time playing online games, 0:02:55.840 --> 0:02:59.880 picking up day jobs as needed. Some see parallels between 0:03:00.000 --> 0:03:03.240 lie flat sentiment in China and similar ideas that emerged 0:03:03.280 --> 0:03:06.560 in Japan in the ninety nineties after its economic growth 0:03:06.639 --> 0:03:12.280 slowed sharply, suggesting China might be facing impending Japan style stagnation, 0:03:14.560 --> 0:03:17.240 but others argue it's more like the nineteen sixties style 0:03:17.320 --> 0:03:20.240 counterculture movements that cropped up in the US and Europe 0:03:20.400 --> 0:03:23.600 in a period of affluence, with ordinary people seeking a 0:03:23.639 --> 0:03:27.639 lower pressure society that's more focused on personal development the 0:03:27.840 --> 0:03:31.720 material success. That's the view of Chenza Young, a twenty 0:03:31.760 --> 0:03:34.240 five year old who lives in shen Jen while studying 0:03:34.320 --> 0:03:39.000 for a master's degree online. The society needs more definition 0:03:39.040 --> 0:03:42.040 about sucsass at the people around you are doing so well, 0:03:42.160 --> 0:03:44.840 or you are all competing for the same job or 0:03:44.960 --> 0:03:48.480 for the same kind of success, so you kind of 0:03:48.560 --> 0:03:52.440 like fear you are gonna laughed out, so some people 0:03:52.520 --> 0:03:55.880 just give up. Even though China, the US and Europe 0:03:55.880 --> 0:03:59.280 are very different economies, we can connect China's lying flat 0:03:59.280 --> 0:04:03.040 discussion with the concept of the great resignation in developed countries, 0:04:03.320 --> 0:04:06.520 says Young Bio, director of the Max Planck Institute for 0:04:06.600 --> 0:04:10.960 Social Anthropology in Germany. Both are about questioning the pursuit 0:04:11.040 --> 0:04:14.560 of wealth at an individual and a social level. They 0:04:15.520 --> 0:04:18.400 emerge at at the same time, and we can make 0:04:18.440 --> 0:04:22.599 a connection and the even links to bigger idea such 0:04:22.720 --> 0:04:27.520 as the growths such as a sustainability and this is 0:04:27.560 --> 0:04:31.640 somehow all related because it is about the overheating about 0:04:31.720 --> 0:04:34.520 US society. They become a excessively completed too, and just 0:04:34.680 --> 0:04:39.200 not as sustainable, not only in terms of environmental extraction, 0:04:39.279 --> 0:04:44.560 but also the mental the mental abendance is not as sustainable. 0:04:45.120 --> 0:04:48.440 Among the new dropouts is Melana Cooler, a twenty six 0:04:48.520 --> 0:04:50.839 year old from Germany who lost her job at the 0:04:50.880 --> 0:04:54.080 height of the pandemic last year. She has chosen to 0:04:54.120 --> 0:04:58.320 set up an environmentally sustainable commune in the countryside rather 0:04:58.360 --> 0:05:01.760 than seeking full time work. Am I enough just the 0:05:01.800 --> 0:05:07.440 way I am? Or do I constantly needs new equipment, 0:05:08.160 --> 0:05:12.840 new material, new goods in my life, new experiences to 0:05:13.080 --> 0:05:18.120 feel full in some form. So that's something I've really changed. 0:05:18.160 --> 0:05:23.560 Here in developed countries, pressure has been building for decades. 0:05:24.120 --> 0:05:28.560 Incomes of stagnated, job security has become precarious, and the 0:05:28.640 --> 0:05:32.080 costs of housing and education of sword making it harder 0:05:32.120 --> 0:05:36.440 to build a financially stable life. Melana story indicates how 0:05:36.440 --> 0:05:41.080 the pandemic has sometimes converted those simmering concerns into action. 0:05:43.040 --> 0:05:45.720 Will the Great Resignation and Life Let have a longer 0:05:45.839 --> 0:05:49.280 term impact. While they are a challenge to conventional ideas 0:05:49.400 --> 0:05:53.000 about work and consumption, Cimball points out that they seem 0:05:53.040 --> 0:05:57.279 to lack specific demands about how to change society. Many 0:05:57.320 --> 0:06:00.480 will be waiting to see if those ideas emerge. For 0:06:00.560 --> 0:06:10.240 Bloomberg News, I'm Tom Hancock in Hong Kong, so I 0:06:10.279 --> 0:06:12.919 wanted to talk a bit more about lying Flat and 0:06:13.200 --> 0:06:17.000 what it tells us about China's future with Bloomberg Opinion 0:06:17.040 --> 0:06:21.040 columnists Shuli Wren in Hong Kong. Shuli, welcome to Stephanomics. 0:06:21.560 --> 0:06:23.760 I love the opening line of a columny wrote the 0:06:23.760 --> 0:06:27.640 other day, China's young people are stressed out. I mean, 0:06:27.640 --> 0:06:31.520 there are there are concrete forces making young people's lives 0:06:31.560 --> 0:06:35.480 more stressful in China and the live flat movement, it's 0:06:35.520 --> 0:06:39.640 just one reaction to that, so tell us more absolutely 0:06:39.800 --> 0:06:44.480 definitely so so like after the Chinese governments a big 0:06:44.480 --> 0:06:48.960 tack and big real estate developer crackdown like that actually 0:06:49.279 --> 0:06:53.960 ruined a lot of the job prospects for China's young people, 0:06:54.080 --> 0:06:58.080 especially those fresh university graduates. I mean, China has been 0:06:58.120 --> 0:07:03.479 training about ten million university graduates every year, and in 0:07:03.520 --> 0:07:06.440 the past they already struggled to find good jobs, and 0:07:06.480 --> 0:07:09.840 now the jobs are even fewer than before. And then 0:07:09.880 --> 0:07:14.480 like in the graduating class of only one third decided 0:07:14.520 --> 0:07:17.320 to go into the job market, with another third saying, oh, 0:07:17.480 --> 0:07:20.320 I'm just going to try to, you know, go out 0:07:20.360 --> 0:07:23.560 to grad school because you know, like when there's a reception, 0:07:23.880 --> 0:07:27.200 everyone applies for grass school, right, some young people they 0:07:27.240 --> 0:07:29.480 just say, oh, I'm just going to take some time off, 0:07:29.720 --> 0:07:32.480 lie on my parents cultures, and figure out what they 0:07:32.520 --> 0:07:34.880 want to do. And I guess one of the one 0:07:34.880 --> 0:07:38.200 of the things that's happening is that you know, China's 0:07:38.800 --> 0:07:41.320 getting richer as a country and now it can have 0:07:41.560 --> 0:07:43.760 dropouts just the way that you know, the US had 0:07:43.800 --> 0:07:48.520 dropouts in the sixties. Absolutely, I mean being able to 0:07:48.600 --> 0:07:51.400 life flat, to be honest, it's a luxury good, right. 0:07:52.320 --> 0:07:56.680 And also like that the cost of of UH consumption 0:07:56.800 --> 0:07:59.160 for a lot of young people is coming down, like 0:07:59.200 --> 0:08:03.480 a China's a chancy just like elsewhere in US and 0:08:03.520 --> 0:08:06.360 then the UK. They don't need very much money or 0:08:06.440 --> 0:08:09.000 like they spend a lot of time on the internet 0:08:09.120 --> 0:08:13.160 right surfing on the internet, chat rooms and playing video games. 0:08:13.360 --> 0:08:16.280 It doesn't cost very much money, so they don't need 0:08:16.320 --> 0:08:19.520 to really earn that much, so they can afford it 0:08:19.560 --> 0:08:22.480 in a way. And also the parents. China has this 0:08:22.680 --> 0:08:25.320 major like only child policy, right, so the parents will 0:08:25.360 --> 0:08:27.920 be like, oh, that's my baby, and what can I do? 0:08:28.000 --> 0:08:30.280 I have to let them life that I want to 0:08:30.280 --> 0:08:34.120 get on with two what how the government's responded. But 0:08:34.240 --> 0:08:36.880 before I get to that, I wanted to ask you 0:08:36.920 --> 0:08:42.319 about young women facing particular challenges in this labor force. 0:08:42.520 --> 0:08:45.480 Tell us a bit more about that. So the best 0:08:45.559 --> 0:08:49.200 jobs for young women are in the services industries such 0:08:49.240 --> 0:08:54.120 as financial industry like UH and the media industry. And 0:08:54.160 --> 0:08:57.800 then like in China as in South Korea, like when 0:08:57.920 --> 0:09:00.839 when the young people apply for jobs they they need, 0:09:01.000 --> 0:09:04.600 they oftentimes are asked to attach a photo of themselves, right, 0:09:04.840 --> 0:09:07.720 So so young women start to feel that, oh, you know, 0:09:07.840 --> 0:09:10.880 if I I look better that that that makes me 0:09:10.960 --> 0:09:13.440 look a little bit more presentable. So a lot of 0:09:13.480 --> 0:09:16.920 them start to do a lot of clusters surgery like facelifts, 0:09:16.920 --> 0:09:19.480 you know, those jobs, so on, so forth, which is 0:09:19.559 --> 0:09:22.520 quite awful. H A while back, I also wrote about 0:09:22.559 --> 0:09:25.160 like aesthetics medicine in China, and then most of the 0:09:25.280 --> 0:09:28.960 demand don't come from older women but from eighteen to 0:09:29.040 --> 0:09:32.080 twenty four year olds, and it has become such a problem. 0:09:32.240 --> 0:09:34.760 And then like basically a facelift costs a lot of 0:09:34.800 --> 0:09:37.480 money and they don't have money for that, right, So 0:09:37.480 --> 0:09:41.000 so there are e commerce websites such as Ali baba 0:09:41.160 --> 0:09:46.160 um that uh, that give young women so called consumer 0:09:46.240 --> 0:09:51.839 loans to do those um a statics medicine procedures um. 0:09:52.000 --> 0:09:54.160 And then the government is calling a stop to that. 0:09:54.200 --> 0:09:58.240 They said that, you know, companies can no longer sell 0:09:58.320 --> 0:10:05.839 asset back securities which are backed by plastic facelift loans. Unbelievable. 0:10:06.400 --> 0:10:11.520 It's clearly alarming, I would think for China's government that 0:10:11.559 --> 0:10:14.720 has such big plans to to lead the world in 0:10:15.360 --> 0:10:20.720 several critical industries and become bigger and better and more 0:10:20.800 --> 0:10:24.520 skilled as a nation. To have young people dropping out 0:10:24.559 --> 0:10:28.800 like this, and how's the government responded, I mean present 0:10:28.880 --> 0:10:32.920 Shinping is very very worried that he he openly talked 0:10:32.960 --> 0:10:37.640 about like the lying flat problem phenomenon in China. And 0:10:37.679 --> 0:10:41.000 then like in October, so so like China that the 0:10:41.040 --> 0:10:45.280 State Council proposed this so called deal training program. It's 0:10:45.320 --> 0:10:49.040 it's essentially the German model. Like basically, China thinks that 0:10:49.000 --> 0:10:52.840 that the society is turning out too many fresh university 0:10:52.840 --> 0:10:55.400 graduates who just don't want to go to the factory 0:10:55.440 --> 0:10:57.959 flaws because they feel like, oh I I did four 0:10:58.000 --> 0:11:00.200 years of undergraduate that why do I want to go 0:11:00.280 --> 0:11:03.679 to the manufacturing sector? Right, So as a result, they 0:11:03.720 --> 0:11:07.040 decide to life flat and China things that society has 0:11:07.080 --> 0:11:09.600 too many of these people, and they want to have 0:11:09.800 --> 0:11:13.480 more young people go into um like so called the 0:11:13.559 --> 0:11:17.160 vocational training, like you know, you spend a few years 0:11:17.480 --> 0:11:20.080 learning skills in the school, but also a few more 0:11:20.160 --> 0:11:23.200 years you know, doing on the job training at the 0:11:23.280 --> 0:11:27.040 biggest blue chip companies such as Huawei or the China's 0:11:27.240 --> 0:11:31.280 power grid and that seems to be their their their solutions. 0:11:31.320 --> 0:11:34.600 They want more young people to go into high end 0:11:34.600 --> 0:11:39.520 manufacturing that does you know, electric evy supply chains or 0:11:39.600 --> 0:11:42.599 like chip manufacturing, and the China doesn't have enough of 0:11:42.679 --> 0:11:47.520 that right now. Is any of that working? Well, this 0:11:47.640 --> 0:11:51.120 is just a start. They just proposed this so called 0:11:51.120 --> 0:11:54.160 the German model in October. One problem is like, um, 0:11:54.880 --> 0:11:57.520 there is a little bit of a stigma when it 0:11:57.559 --> 0:12:01.360 comes to working on the factory floors, and the China's 0:12:01.559 --> 0:12:04.200 middle class families they don't really want their children to 0:12:04.240 --> 0:12:08.160 go into vocational school training, right, I mean the US 0:12:08.160 --> 0:12:12.400 that that hasn't been very successful either. So so what 0:12:12.600 --> 0:12:16.160 the state Council proposes that you know, some high, very 0:12:16.240 --> 0:12:19.679 high end like vocational schools. They should be able to 0:12:19.760 --> 0:12:23.000 offer bachelor's degrees as well. So so even though you 0:12:23.000 --> 0:12:26.679 are technically going to you know, um, the German model, 0:12:26.720 --> 0:12:30.479 you're still have a degree. So perhaps that will persuade 0:12:30.480 --> 0:12:33.840 the China's middle class families to allow their children to 0:12:33.920 --> 0:12:38.119 go into this kind of German uh deal track training programs. 0:12:39.000 --> 0:12:40.680 There's an awful lot of countries that have tried to 0:12:40.720 --> 0:12:44.600 be more German in particularly this respect. For many decades. 0:12:44.640 --> 0:12:47.160 Anybody who ever looks at the UK economy always concludes 0:12:47.160 --> 0:12:49.200 that we should be more German in our approach to 0:12:49.360 --> 0:12:54.880 education and have exactly this emphasis on technical skills and 0:12:54.960 --> 0:12:59.839 giving the same amount of esteem and regard to people 0:13:00.000 --> 0:13:03.600 doing engineering and working on the shop floors to people 0:13:03.640 --> 0:13:05.680 in universities. And it hasn't worked. They've been trying to 0:13:05.679 --> 0:13:09.640 do it for decades. Yeah, China will trial as well, 0:13:09.679 --> 0:13:13.480 I guess, but it certainly seems like the consequence of 0:13:13.480 --> 0:13:15.880 a new kind of China. When you say that, people 0:13:16.000 --> 0:13:18.680 say that it is demeaning to work on the shop 0:13:18.800 --> 0:13:21.200 on the shop floor in factories. Presumibly its people's parents 0:13:21.240 --> 0:13:23.600 originally did that. I mean, all of this development has 0:13:23.640 --> 0:13:29.280 happened in very few generations. I mean absolutely. My my 0:13:29.320 --> 0:13:32.640 father was a chemical engineer and that he did pretty well, 0:13:32.679 --> 0:13:35.920 like you know, like in the last two decades and 0:13:36.040 --> 0:13:42.640 basically exporting pollution, like you know, polluting the exporting products 0:13:42.640 --> 0:13:45.160 and stuff, and he did well. But he absolutely does 0:13:45.280 --> 0:13:48.120 not want me to go into engineering. He said it's 0:13:48.160 --> 0:13:51.080 tough work. And then he rather me you know, writing instead. 0:13:51.280 --> 0:13:54.400 Like the parents, they just don't want their children to 0:13:54.440 --> 0:13:56.760 go out to factory for and I think it's a 0:13:56.800 --> 0:14:01.319 sign that China is no longer really the typical virgin market. 0:14:01.679 --> 0:14:04.760 It kind of has emerged in a way, you know, 0:14:04.840 --> 0:14:08.840 like and you're and you're part of the problem, it seems, yeah, exactly, 0:14:08.960 --> 0:14:10.840 And the whole of time, I'm afraid cannot all work 0:14:10.880 --> 0:14:17.120 at Bloomberg. I'm afraid that Uliman, thank you so much 0:14:17.120 --> 0:14:28.600 for joining us, Thanks for having me so. Bloomberg has 0:14:28.640 --> 0:14:31.760 recently published a series of articles under the tagline of 0:14:31.880 --> 0:14:35.520 Race and Recovery, looking at how America's economic recovery is 0:14:35.560 --> 0:14:39.200 playing out in minority communities. There's some really eye opening 0:14:39.280 --> 0:14:41.920 data and stories about life in different parts of the 0:14:41.960 --> 0:14:45.640 economy in this series, and the final article came out 0:14:45.680 --> 0:14:48.920 this week and seemed to me particularly timely as the 0:14:49.000 --> 0:14:51.640 US Central Bank starts to talk about raising interest rates 0:14:52.080 --> 0:14:54.680 and we enter what feels like a new phase of 0:14:54.720 --> 0:14:59.360 the recovery. Andre Tartar is a data journalist for Bloomberg 0:14:59.480 --> 0:15:02.120 based in New York, and he's with me now. And 0:15:03.000 --> 0:15:06.200 the data you pulled together for this piece with Christopher 0:15:06.280 --> 0:15:11.280 Cannon this week paid a fascinating picture of US household 0:15:11.280 --> 0:15:16.080 spending through this pandemic period and particularly impact that government 0:15:16.160 --> 0:15:20.080 stimulus money has had on particular parts of the population. 0:15:20.280 --> 0:15:22.360 So just give us some of the big headlines from 0:15:22.400 --> 0:15:25.400 those numbers, sure thing, and thank you so much for 0:15:25.440 --> 0:15:29.000 having me. So we got access to spending data for 0:15:29.200 --> 0:15:33.840 just over a ten million people, a constant sample over 0:15:33.920 --> 0:15:36.560 time that allowed us to really kind of look for 0:15:36.640 --> 0:15:39.880 those trends and changes in spending behaviors. And the thing 0:15:39.960 --> 0:15:42.280 that we really kind of struck us was just how 0:15:42.360 --> 0:15:46.920 much spending had surged, in particular among black and lower 0:15:46.960 --> 0:15:51.360 income families, um And we could see the very clear 0:15:51.960 --> 0:15:57.280 uh impact of those federal stimulus checks, in part because 0:15:57.360 --> 0:16:00.600 both of those groups, black and lower income groups are 0:16:00.680 --> 0:16:03.480 much more reliant on debit card spending. And we could 0:16:03.480 --> 0:16:07.000 see in this data just how much the debit card 0:16:07.120 --> 0:16:10.440 usage kind of rows around the time of the stimulus 0:16:10.520 --> 0:16:12.640 checks because you're already spending what you have. You can 0:16:12.680 --> 0:16:14.400 only spend what you have in your account because you 0:16:14.440 --> 0:16:18.080 don't necessarily get credit exactly right. Whereas whereas, for instance, 0:16:18.120 --> 0:16:20.680 if you look at higher income spenders or you know, 0:16:20.760 --> 0:16:23.440 which you know also will capture a large portion of 0:16:23.520 --> 0:16:26.640 white and agent spenders, their use of credit is much 0:16:26.720 --> 0:16:29.760 much higher. They were clearly in this data and and 0:16:29.920 --> 0:16:33.160 other research has shown that they that those groups were 0:16:33.280 --> 0:16:36.320 much more able to hold back spending right in those 0:16:36.600 --> 0:16:39.400 first few months waiting this out, which is much harder 0:16:39.480 --> 0:16:42.480 for those groups which live a bit tighter, you know, 0:16:42.720 --> 0:16:46.240 month to month. What kind of numbers are we talking 0:16:46.240 --> 0:16:48.360 about in terms of just the impact of the of 0:16:48.440 --> 0:16:51.960 the stimulus packages relative to what they would have spent 0:16:52.120 --> 0:16:55.200 would have been spending in say, in the case of 0:16:55.280 --> 0:16:59.720 say spending by the black people in our sample, it 0:16:59.840 --> 0:17:03.760 was up almost um this past kind of spring and 0:17:03.800 --> 0:17:08.280 summer compared to twenty m minting levels, which is, you know, 0:17:08.359 --> 0:17:10.760 a trend that would not be seen normally, you know, 0:17:10.960 --> 0:17:14.199 even factoring in just normal economic growth, normal inflation, that 0:17:14.280 --> 0:17:17.879 is a really significant bump up um, you know, and 0:17:17.920 --> 0:17:20.280 there certainly are other factors at play, but you know, 0:17:20.359 --> 0:17:24.080 given kind of this, given the scope of that of 0:17:24.080 --> 0:17:28.320 that injection of cash really into into parts of economy, 0:17:28.320 --> 0:17:31.359 it was significant, and across the sample, I think it 0:17:31.400 --> 0:17:35.360 was even it was increase in spending, which only which 0:17:35.400 --> 0:17:39.080 only came back a certain amount when things like the 0:17:39.160 --> 0:17:44.879 unemployment benefits ran out in in the full absolutely, I 0:17:44.920 --> 0:17:48.200 mean as of October, which was the last month that 0:17:48.240 --> 0:17:52.439 we had data for overall spending across this group of 0:17:52.440 --> 0:17:56.560 about ten million Americans was still up about fifteen compared 0:17:56.600 --> 0:17:59.959 to twenty miniting levels. And we should just say briefly 0:18:00.080 --> 0:18:02.040 what this what this data was? Where did you get 0:18:02.080 --> 0:18:04.760 hold of these numbers? So this DADA comes from from 0:18:04.760 --> 0:18:08.560 a company called Affinity Solutions, Inc. Which have been incredibly 0:18:08.560 --> 0:18:11.399 generous in working with us and often partner with the 0:18:11.440 --> 0:18:16.760 FED academics to provide access to their data, which nationally 0:18:17.119 --> 0:18:20.520 covers more than a hundred million debit and credit cards 0:18:20.680 --> 0:18:23.720 UM and has an incredible amount of depth to it. 0:18:23.840 --> 0:18:27.040 So you know, it was really great Chricket access to 0:18:27.160 --> 0:18:30.320 this UM and being able to also use the data 0:18:30.400 --> 0:18:34.600 that they have linking demographics and income into this data, 0:18:34.600 --> 0:18:37.760 which is a very kind of complicated process that they 0:18:38.000 --> 0:18:41.040 undertake UM on their end, so you know, it really 0:18:41.040 --> 0:18:43.439 gives a lot of insights that otherwise are hard to 0:18:43.440 --> 0:18:47.959 get at that at that level of detail. It's so 0:18:48.000 --> 0:18:50.280 exciting when you get hold of a big, meaty data 0:18:50.320 --> 0:18:52.720 set like this and to have it been relatively timely 0:18:52.720 --> 0:18:55.480 as well as going through to October. And I have 0:18:55.520 --> 0:18:57.800 to say you do a fantastic job of making it 0:18:57.840 --> 0:19:00.720 come alive with some really lovely colorful graphics, which we're 0:19:00.760 --> 0:19:04.359 not doing justice too on the podcast. Right a shout 0:19:04.400 --> 0:19:06.919 out to Christopher Cannon on the graphics who made all 0:19:06.920 --> 0:19:11.000 those beautiful graphics and definitely recommend folks to go and 0:19:11.080 --> 0:19:15.560 a metical look. I mean, inflation poses a risk to 0:19:15.640 --> 0:19:18.200 this big increase in spending power. Right when we look 0:19:18.240 --> 0:19:22.840 forward to next year, are we potentially seeing this big 0:19:22.880 --> 0:19:26.800 improvement in in particularly black and Hispanic households spending power 0:19:26.920 --> 0:19:32.480 being being really hit by both inflation and potentially a 0:19:32.480 --> 0:19:37.120 slowing economy. I mean absolutely right. So this really kind 0:19:37.119 --> 0:19:41.960 of that injection of that federals federal simulus really closed 0:19:42.080 --> 0:19:45.560 a huge consumption gap and also showed us the kind 0:19:45.560 --> 0:19:49.640 of untapped potential right that exists in those communities who 0:19:49.840 --> 0:19:52.720 who just tend to have lower incomes and lower access 0:19:53.160 --> 0:19:56.280 to credit. So both so both kind of the fact 0:19:56.440 --> 0:19:59.800 that now most of that you know, additional cash has 0:20:00.000 --> 0:20:02.239 have been spent, and as you mentioned, inflation is going 0:20:02.280 --> 0:20:05.040 to begin to eat in to some of those core 0:20:05.119 --> 0:20:09.520 spending staple groups that just can't be avoided. Certainly foods, 0:20:09.520 --> 0:20:13.040 certainly gas are ones where you know, groups who have 0:20:13.119 --> 0:20:15.760 to go physically into work, who don't have a lot 0:20:15.920 --> 0:20:19.879 of ability to hold off spending or access credit. I 0:20:19.920 --> 0:20:22.840 think we will certainly see a very you know, a 0:20:22.960 --> 0:20:26.320 very likely a kind of a tempering or even a 0:20:26.400 --> 0:20:29.040 full on slow down of the spending recovery, which as 0:20:29.080 --> 0:20:32.240 we know, powers the vast majority of the U. S economy. 0:20:32.520 --> 0:20:34.560 So you know, it both has implications for the kind 0:20:34.560 --> 0:20:37.000 of equity side of the picture, but also just for 0:20:37.119 --> 0:20:41.119 the recovery more broadly. Yeah, and there's certainly a lesson 0:20:41.119 --> 0:20:42.919 if you if you want to stimulate the economy and 0:20:42.920 --> 0:20:44.920 get people to spend, give it to pull people who 0:20:44.960 --> 0:20:47.000 don't have enough money to buy the things they want 0:20:47.040 --> 0:20:49.920 to buy. There actually are some fascinating studies out there 0:20:49.920 --> 0:20:53.320 which have really shown though that that stimulus money, if 0:20:53.359 --> 0:20:55.960 you were a wealth your household, you basically saved it 0:20:56.000 --> 0:20:58.040 all right, So I mean, really it wasn't doing what 0:20:58.160 --> 0:21:00.480 it was meant to do. Of course, for reasons of 0:21:00.600 --> 0:21:03.960 you know, of efficiency, the idea was to just give 0:21:04.359 --> 0:21:06.840 checks all around. But as you mentioned, I mean, this 0:21:06.920 --> 0:21:09.639 data really shows that you can get the biggest bang 0:21:09.720 --> 0:21:12.880 for your stimulus buck by really sending it to those 0:21:12.960 --> 0:21:15.760 lower income households and communities of color, you know who 0:21:15.800 --> 0:21:18.080 kind of aren't being able to tap into their full 0:21:18.119 --> 0:21:21.959 consumption potential. It's a difficult challenge for the Federal reserver, 0:21:22.200 --> 0:21:24.119 right because they're supposed to be they're supposed to be 0:21:24.200 --> 0:21:29.440 focused on both stable inflation and full employment. They've said 0:21:29.440 --> 0:21:33.679 they're going to focus more on everybody's unemployment rate, not 0:21:33.800 --> 0:21:36.480 just the headline rate, and of course on black unemployment 0:21:36.520 --> 0:21:39.520 is still quite a lot higher, um than the than 0:21:39.560 --> 0:21:42.760 the average for the rest of the country, but they're 0:21:42.840 --> 0:21:46.040 kind of weighing up. Inflation hurts poor people, digs into 0:21:46.040 --> 0:21:50.960 their spending power, but not getting those jobs created, not 0:21:51.040 --> 0:21:55.960 bringing down unemployment hurts them too. It's a difficult challenge absolutely, um, 0:21:55.960 --> 0:21:58.320 I mean, and on top of that, there's also you know, 0:21:58.400 --> 0:22:01.560 there's a machine momentum that um, we are in where 0:22:01.600 --> 0:22:04.639 we have I think it's something like a ten million 0:22:04.720 --> 0:22:08.520 unful jobs, and yet we're still not seeing really that 0:22:08.600 --> 0:22:12.560 broad based, you know, decline in unemployment. So it really 0:22:12.600 --> 0:22:17.080 does present a very difficult obstacle course for the Fed policymakers, 0:22:18.760 --> 0:22:22.440 but also fantastic time to be doing data journalism. Thanks 0:22:22.480 --> 0:22:33.760 so much, Thank you, definitely, I really appreciate it. M H. Finally, 0:22:34.200 --> 0:22:36.320 at the start of the program. I think I promised 0:22:36.320 --> 0:22:39.360 to you the future of food is Hong Kong reporter 0:22:39.840 --> 0:22:45.480 Juan ha. It has the rain natty taste. That's Malaysian 0:22:45.560 --> 0:22:49.560 entrepreneur Kevin Wou describing the perfect burger that he wants 0:22:49.600 --> 0:22:52.639 to put into restaurants and grocery stores. So we added 0:22:52.680 --> 0:22:55.679 some spices to give it that kind of familiar beefy taste, 0:22:55.840 --> 0:22:59.720 the grounded beef taste. And we've added certain kind of 0:23:00.040 --> 0:23:04.040 hats like mushroom seasoning to give you that umami flavor. 0:23:04.440 --> 0:23:09.600 And the secret ingredient. We've perized our crickets, you heard right, 0:23:10.080 --> 0:23:14.560 crickets roasted and processed into a fine brown powder, and 0:23:14.600 --> 0:23:17.399 then we mix it with other plant based protein source. 0:23:17.920 --> 0:23:20.919 I think it's pretty tasty, especially when you when you 0:23:20.960 --> 0:23:23.000 look at the burglar, it looks at normal burger, small, 0:23:23.240 --> 0:23:29.280 normal burger, even sizzles like a normal burger. Who's the 0:23:29.320 --> 0:23:33.080 founder and CEO of Ento based in Kuala Lumpur. He's 0:23:33.080 --> 0:23:36.719 an evangelist for protein made from insects, and he's not alone. 0:23:37.119 --> 0:23:40.240 Startups from Europe, Asia and North America are joining the 0:23:40.320 --> 0:23:43.840 race for alternative proteins and say bugs are making their 0:23:43.840 --> 0:23:47.520 way to our dinner plates. It's the next big frontier 0:23:47.640 --> 0:23:51.639 for planet friendly sustainable protein after fake meat. If you 0:23:51.680 --> 0:23:54.840 were to compare one kilogram of beef versus one kilogram 0:23:55.000 --> 0:23:58.560 of cricket powder um, it will require tolf times last feet, 0:23:58.960 --> 0:24:02.480 twenty times less land, two thousand times less water, and 0:24:02.520 --> 0:24:06.040 amid two thousand times less greenhouse gas emissions. So, in 0:24:06.119 --> 0:24:09.440 its most natural form, insect based protein has already high 0:24:09.760 --> 0:24:13.199 enriched levels of proteins and other macro nutrients. And in 0:24:13.240 --> 0:24:16.560 an into promotional video, taste testers who tried the company's 0:24:16.600 --> 0:24:21.119 cricket snacks gave it a thumbs up. There's like sugars, 0:24:22.760 --> 0:24:26.560 red clunchy like chips and stuff like that. Actually thottle 0:24:26.560 --> 0:24:32.119 taste are crickets. There's also a sustainability reason why edible 0:24:32.160 --> 0:24:35.639 bugs are on the menu. Constant Tetter is CEO of 0:24:35.720 --> 0:24:39.320 Fly Farm. You know protein is needed, It's going to 0:24:39.320 --> 0:24:42.639 be an increasing need as the human population expands. His 0:24:42.800 --> 0:24:46.040 company is setting up industrial farms to harvest black Soldier 0:24:46.040 --> 0:24:49.920