1 00:00:00,080 --> 00:00:02,480 Speaker 1: This episode is brought to you by Nadex, the Binary 2 00:00:02,520 --> 00:00:05,680 Speaker 1: Options Exchange. Binary Options let you limit your risk and 3 00:00:05,720 --> 00:00:08,520 Speaker 1: trade stock in dissees, commodities, for x and more from 4 00:00:08,560 --> 00:00:12,240 Speaker 1: a single account. Nat X is a CFTC regulated exchange 5 00:00:12,600 --> 00:00:16,840 Speaker 1: with transparency, free market data, and fairness guaranteed. The future 6 00:00:16,840 --> 00:00:19,280 Speaker 1: of trading is here now at n A d e 7 00:00:19,520 --> 00:00:22,560 Speaker 1: x dot com futures, options and swaps. Trading involves risk 8 00:00:22,640 --> 00:00:28,080 Speaker 1: and may not be appropriate for all investors manufacturing. What 9 00:00:28,120 --> 00:00:31,680 Speaker 1: does it look like these days? Dying or on the 10 00:00:31,720 --> 00:00:34,720 Speaker 1: cusp of a renaissance? That's what we'll try to take 11 00:00:34,760 --> 00:00:38,400 Speaker 1: a part this week. Does anyone else pronounce it renaissances? 12 00:00:38,440 --> 00:00:40,000 Speaker 1: That just see you? Dan? I think it's to do 13 00:00:40,040 --> 00:00:45,760 Speaker 1: with that convict ship. Hi, and welcome back to Bloomberg Benchmark, 14 00:00:45,800 --> 00:00:49,520 Speaker 1: a podcast about the global economy. It is Thursday, November five. 15 00:00:49,600 --> 00:00:53,559 Speaker 1: I'm Tory Stillwell and economics reporter with Bloomberg News in Washington, 16 00:00:53,680 --> 00:00:56,040 Speaker 1: d C. And I'm joined by my colleagues and co 17 00:00:56,160 --> 00:01:00,360 Speaker 1: host Dan Moss, our executive editor for International Economics Average, 18 00:01:00,400 --> 00:01:03,600 Speaker 1: who is in New York today, and Akido, our editor 19 00:01:03,680 --> 00:01:07,479 Speaker 1: for a Benchmark in San Francisco. Hello, Hi, Hey, guys. 20 00:01:07,840 --> 00:01:12,120 Speaker 1: So Dan, I was scouring the internet one day when 21 00:01:12,160 --> 00:01:16,679 Speaker 1: I see this great article about how the Australian accent 22 00:01:17,200 --> 00:01:19,839 Speaker 1: as a result of like you guys drinking too much 23 00:01:19,920 --> 00:01:24,919 Speaker 1: when you first settled Australia, and that you guys speak 24 00:01:24,959 --> 00:01:29,200 Speaker 1: with just two thirds capacity, with one third of your 25 00:01:30,160 --> 00:01:33,800 Speaker 1: mouth muscles sedentary. There's a couple of versions of that. 26 00:01:33,880 --> 00:01:36,960 Speaker 1: One is that this is the kind of English that 27 00:01:37,160 --> 00:01:42,280 Speaker 1: convicts spoke in late eighteenth century. The other version is 28 00:01:42,360 --> 00:01:45,440 Speaker 1: when the first male convict ship arrived a few days 29 00:01:45,480 --> 00:01:50,040 Speaker 1: before the first female convict ship, they were all going crazy. 30 00:01:50,160 --> 00:01:54,600 Speaker 1: Then when the first female convict ship arrived to join 31 00:01:54,720 --> 00:01:58,840 Speaker 1: the first male convict ship, there was this massive, massive 32 00:01:59,000 --> 00:02:02,279 Speaker 1: night with rum and nothing was ever the same. Again, 33 00:02:02,840 --> 00:02:05,480 Speaker 1: it's fair to say that some of the first European 34 00:02:05,480 --> 00:02:12,000 Speaker 1: Australians were conceived that night. But that's an incredible story. Well, 35 00:02:12,280 --> 00:02:14,880 Speaker 1: moving on, I guess this is sort of related. Let's 36 00:02:14,919 --> 00:02:18,840 Speaker 1: talk about babies. This was the first piece of news 37 00:02:18,880 --> 00:02:21,919 Speaker 1: I saw when I woke up on Thursday morning last week, 38 00:02:22,120 --> 00:02:25,480 Speaker 1: and I was so stunned I think I audibly gasped. 39 00:02:25,880 --> 00:02:29,000 Speaker 1: China got rid of its one child policy last week, 40 00:02:29,320 --> 00:02:32,080 Speaker 1: so now Chinese families are allowed to have up to 41 00:02:32,160 --> 00:02:34,720 Speaker 1: two kids. And this is a big deal because, like 42 00:02:34,840 --> 00:02:37,440 Speaker 1: we mentioned in Our and Our China episode a few 43 00:02:37,440 --> 00:02:42,079 Speaker 1: weeks back, um our guests Kenneth Lieberthal mentioned the one 44 00:02:42,160 --> 00:02:44,919 Speaker 1: child policy as part of the reason why their their 45 00:02:44,960 --> 00:02:49,919 Speaker 1: population growth has been slowing, and why that that's fed 46 00:02:49,960 --> 00:02:55,000 Speaker 1: into overall growth of their economy. Population growth is slowing, 47 00:02:55,280 --> 00:02:58,679 Speaker 1: but what's happening with the part of the population that's 48 00:02:58,680 --> 00:03:03,639 Speaker 1: in the workforce that has in certain age groups already 49 00:03:03,680 --> 00:03:07,480 Speaker 1: begun to contract. And it's really consistent with one of 50 00:03:07,520 --> 00:03:09,920 Speaker 1: the things ken told us that day, which is this 51 00:03:10,520 --> 00:03:13,200 Speaker 1: image we've had for a long time of China as 52 00:03:13,240 --> 00:03:19,560 Speaker 1: this giant, giant, giant pool of workers. It's really increasingly 53 00:03:20,000 --> 00:03:25,720 Speaker 1: less true. In some ways, that policy became too successful 54 00:03:25,800 --> 00:03:29,840 Speaker 1: for its own good, because as the population has slowed 55 00:03:30,040 --> 00:03:35,520 Speaker 1: and the working age population has shrunk, wages in China 56 00:03:35,760 --> 00:03:41,200 Speaker 1: actually have been increasing, and for many manufacturing jobs, it 57 00:03:41,320 --> 00:03:44,160 Speaker 1: just doesn't make sense to be in China anymore. There 58 00:03:44,200 --> 00:03:47,280 Speaker 1: are other places you can go. Yeah, and from my 59 00:03:47,440 --> 00:03:51,080 Speaker 1: proach on our Economic Indicators team, the week has been 60 00:03:51,120 --> 00:03:55,240 Speaker 1: dominated by manufacturing data, and that leads nicely into our 61 00:03:55,240 --> 00:03:59,640 Speaker 1: topic for today's show sure does. On this show, we've 62 00:03:59,680 --> 00:04:03,760 Speaker 1: taught in previous episodes about the stronger dollar, We've talked 63 00:04:03,800 --> 00:04:07,320 Speaker 1: about China. We've even talked about robots are doing to 64 00:04:07,400 --> 00:04:10,800 Speaker 1: your job. We've touched on all these topics that affect 65 00:04:10,800 --> 00:04:15,720 Speaker 1: the manufacturing sector without talking and devoting a show too 66 00:04:16,200 --> 00:04:20,400 Speaker 1: well manufacturing itself. What does it look like these days? 67 00:04:21,120 --> 00:04:24,800 Speaker 1: Dying or on the cusp of a renaissance? That's what 68 00:04:24,880 --> 00:04:27,520 Speaker 1: we'll try to take a part this week. Does anyone 69 00:04:27,560 --> 00:04:30,359 Speaker 1: else pronounce it renaissanswers that just see you, Dan? I 70 00:04:30,360 --> 00:04:35,160 Speaker 1: think it's to do with that convict ship. Well, hopefully 71 00:04:35,200 --> 00:04:37,920 Speaker 1: by the end of this episode will have answered this 72 00:04:38,000 --> 00:04:43,520 Speaker 1: question of whether manufacturing even matters for an economy like ours, 73 00:04:43,560 --> 00:04:47,560 Speaker 1: for an an advanced post industrialized economy. I think some 74 00:04:47,600 --> 00:04:50,279 Speaker 1: of our listeners will be listening to this and think, gosh, 75 00:04:50,279 --> 00:04:54,880 Speaker 1: I'm a teacher or a firefighter, or a lawyer or 76 00:04:54,920 --> 00:04:59,160 Speaker 1: an app developer and manufacturing just sounds so twentieth century. 77 00:04:59,279 --> 00:05:02,160 Speaker 1: So will be digging into this question as well, and 78 00:05:02,200 --> 00:05:05,599 Speaker 1: we will also have a very special guest to tell 79 00:05:05,680 --> 00:05:07,680 Speaker 1: us a little bit more about it at the bottom 80 00:05:07,680 --> 00:05:10,520 Speaker 1: of the show, so stay tuned there. But first, things. First, 81 00:05:10,560 --> 00:05:14,039 Speaker 1: let's run through what the manufacturing data are saying currently. 82 00:05:14,760 --> 00:05:17,120 Speaker 1: So this week we got a couple of big pieces 83 00:05:17,160 --> 00:05:19,800 Speaker 1: of news, and I want everyone to put on their 84 00:05:19,839 --> 00:05:22,680 Speaker 1: nerd caps for a second. Mine is always on when 85 00:05:22,720 --> 00:05:26,240 Speaker 1: talking about economic indicators. But among the first day points 86 00:05:26,279 --> 00:05:29,000 Speaker 1: that where we get on the economy every month is 87 00:05:29,080 --> 00:05:32,839 Speaker 1: actually concentrated on manufacturing. It's called the Institute for Supply 88 00:05:33,120 --> 00:05:37,320 Speaker 1: Management Manufacturing Survey, and that name is so boring, but 89 00:05:37,760 --> 00:05:41,600 Speaker 1: the information that it has is very interesting. Basically, these 90 00:05:41,600 --> 00:05:45,120 Speaker 1: are just comments from purchasing managers in manufacturing, and you're 91 00:05:45,160 --> 00:05:49,280 Speaker 1: probably wondering what a purchasing manager is. Uh. Factories need 92 00:05:49,320 --> 00:05:51,559 Speaker 1: a lot of supplies to make what they make, and 93 00:05:51,760 --> 00:05:54,880 Speaker 1: purchasing managers are in charge of making sure they have 94 00:05:55,120 --> 00:05:58,839 Speaker 1: those supplies. So if managers think there's gonna be a 95 00:05:58,880 --> 00:06:02,200 Speaker 1: pickup in demand for whatever the factory makes, whatever widgets 96 00:06:02,200 --> 00:06:04,560 Speaker 1: they produce, they're gonna be making sure that they have 97 00:06:04,800 --> 00:06:07,640 Speaker 1: ordered more raw materials that they need to make them. 98 00:06:07,680 --> 00:06:09,440 Speaker 1: If they think there's gonna be a slowdown, they're gonna 99 00:06:09,520 --> 00:06:11,800 Speaker 1: they're gonna trail off their orders for those raw materials. 100 00:06:11,839 --> 00:06:14,440 Speaker 1: So these people are really at the helm of being 101 00:06:14,480 --> 00:06:20,200 Speaker 1: able to monitor factory activity. So it's a leading indicator exactly, 102 00:06:20,920 --> 00:06:23,839 Speaker 1: and the data goes back to so we've got a 103 00:06:23,839 --> 00:06:26,080 Speaker 1: lot of history to work with, which is crucial for 104 00:06:26,120 --> 00:06:29,800 Speaker 1: economic indicators. Every month, they mail up this questionnaire to 105 00:06:29,960 --> 00:06:32,520 Speaker 1: hundreds of their members and about twenty industries. These are, 106 00:06:32,720 --> 00:06:35,880 Speaker 1: you know, textiles, leather, plastics, producers, and they asked them 107 00:06:35,920 --> 00:06:38,599 Speaker 1: all these questions and all these like wonky things that 108 00:06:38,640 --> 00:06:42,640 Speaker 1: economists want to get super specific information on. But the 109 00:06:42,720 --> 00:06:46,360 Speaker 1: broad overarching index, it compiles the most important parts of 110 00:06:46,400 --> 00:06:48,479 Speaker 1: that survey. That's the number that we we really like 111 00:06:48,560 --> 00:06:52,280 Speaker 1: to look at first. And that index was little changed 112 00:06:52,400 --> 00:06:57,479 Speaker 1: at fifty point one for October, after fifty point two 113 00:06:57,520 --> 00:07:01,360 Speaker 1: in September. So a number over fifty means that it's expanding, 114 00:07:01,480 --> 00:07:05,200 Speaker 1: right exactly. It's good that it's over fifty, but it's 115 00:07:05,240 --> 00:07:07,720 Speaker 1: basically kind of neutral. To give you guys a little 116 00:07:07,720 --> 00:07:10,960 Speaker 1: bit more context, this main index was at fifty eight 117 00:07:11,000 --> 00:07:13,760 Speaker 1: point one in August of last year, and that was 118 00:07:14,160 --> 00:07:16,720 Speaker 1: right when the dollars started to go off on a tear. 119 00:07:17,200 --> 00:07:19,240 Speaker 1: And there's been a few swings, but for the most part, 120 00:07:19,280 --> 00:07:21,760 Speaker 1: it's just been a straight line down ever since then. 121 00:07:22,320 --> 00:07:25,520 Speaker 1: I think the good news about last month's number was 122 00:07:25,600 --> 00:07:27,400 Speaker 1: a lot of people thought that it was going to 123 00:07:27,600 --> 00:07:30,280 Speaker 1: dip below that fifty threshold Hockey. They thought it was 124 00:07:30,320 --> 00:07:33,720 Speaker 1: going to dip into contractionary territory. That would have been 125 00:07:33,840 --> 00:07:36,760 Speaker 1: very worrisome, but it kind of held on, so that 126 00:07:36,840 --> 00:07:39,480 Speaker 1: was actually a small positive thing. I guess if you 127 00:07:39,480 --> 00:07:42,600 Speaker 1: look at the market p m I number, that increased 128 00:07:42,600 --> 00:07:46,240 Speaker 1: the fifty four point one in October from fifty three 129 00:07:46,240 --> 00:07:51,480 Speaker 1: point one in September. So I guess manufacturing isn't completely 130 00:07:51,520 --> 00:07:54,520 Speaker 1: depressed right now, but it sounds like it's not doing 131 00:07:54,560 --> 00:07:56,960 Speaker 1: too well either. And just to put this into some 132 00:07:57,040 --> 00:08:01,160 Speaker 1: broader context tory, the Institute for Supply Lawn Management also 133 00:08:01,280 --> 00:08:04,840 Speaker 1: publishes a non manufacturing index. Tell us what happened to 134 00:08:04,880 --> 00:08:09,000 Speaker 1: that this month? Right, Well, so the services indexes nine 135 00:08:09,120 --> 00:08:13,000 Speaker 1: points higher than that factory gauge, and that's the widest 136 00:08:13,040 --> 00:08:16,160 Speaker 1: differential since two thousands, So that just really speaks to 137 00:08:16,320 --> 00:08:19,760 Speaker 1: how much better the services side the economy is doing 138 00:08:19,840 --> 00:08:22,640 Speaker 1: compared to the factory side. So we really live in 139 00:08:22,640 --> 00:08:26,200 Speaker 1: a services world, at least for this month. Right, So 140 00:08:26,280 --> 00:08:30,640 Speaker 1: let's talk about how manufacturing got this way. Uh, let's 141 00:08:30,680 --> 00:08:33,760 Speaker 1: start short term, how do we get here. Well, Tori, 142 00:08:33,880 --> 00:08:37,240 Speaker 1: you talked about the strong dollar right right exactly. We've 143 00:08:37,280 --> 00:08:40,959 Speaker 1: we've seen the dollar appreciating and that makes our goods 144 00:08:41,240 --> 00:08:46,000 Speaker 1: more expensive for people abroad who want to buy manufactured products. 145 00:08:46,600 --> 00:08:48,960 Speaker 1: And one of the reasons why the dollar has been 146 00:08:49,000 --> 00:08:52,960 Speaker 1: so strong recently is because other economies around the world 147 00:08:53,040 --> 00:08:56,640 Speaker 1: aren't doing that well. And so you see this real 148 00:08:56,679 --> 00:09:00,760 Speaker 1: slowdown and global demand, and that means us smaller market 149 00:09:00,960 --> 00:09:05,120 Speaker 1: for American manufacturers. And then we've also seen the energy 150 00:09:05,320 --> 00:09:10,199 Speaker 1: sector kind of throw a wrench in the manufacturing industry 151 00:09:10,240 --> 00:09:14,480 Speaker 1: as well. When oil prices plunge, it means that oil 152 00:09:14,520 --> 00:09:18,600 Speaker 1: companies don't really need to buy more heavy equipment. They 153 00:09:18,600 --> 00:09:21,480 Speaker 1: don't need to invest in more equipment to be able 154 00:09:21,520 --> 00:09:23,760 Speaker 1: to access that oil or energy or whatever they're mining 155 00:09:23,800 --> 00:09:27,160 Speaker 1: for um, So it hurts the factories that produced that stuff. 156 00:09:27,160 --> 00:09:31,479 Speaker 1: What about longer term, Dan, it's facing issues of technology, 157 00:09:32,200 --> 00:09:36,440 Speaker 1: it's facing issues of cost. You know, we've got this 158 00:09:36,520 --> 00:09:41,080 Speaker 1: global supply chain happening where a manufacturing company might happen 159 00:09:41,120 --> 00:09:45,960 Speaker 1: to be headquartered in the United States, but the components 160 00:09:46,160 --> 00:09:50,640 Speaker 1: for their product are manufactured in one country, they're assembled 161 00:09:50,800 --> 00:09:55,920 Speaker 1: in a second, then shipped to a third for export. Now, 162 00:09:55,920 --> 00:09:59,800 Speaker 1: that doesn't necessarily mean that American export as are dead 163 00:09:59,880 --> 00:10:04,160 Speaker 1: or American manufacturers are dead. It may mean they're not 164 00:10:04,240 --> 00:10:09,600 Speaker 1: doing the manufacturing and the exporting from the US. I'm wondering, 165 00:10:09,960 --> 00:10:13,880 Speaker 1: why do we care about manufacturing so much in the 166 00:10:13,960 --> 00:10:17,360 Speaker 1: first place if our future is in services. Part of 167 00:10:17,400 --> 00:10:20,760 Speaker 1: it this iconic grip it's got on the American imagination, 168 00:10:20,840 --> 00:10:26,000 Speaker 1: you know, Henry Ford and the tremendous industrialization we saw 169 00:10:26,200 --> 00:10:30,880 Speaker 1: in waves the nineteenth century, then again the conversion of 170 00:10:31,160 --> 00:10:35,400 Speaker 1: auto plants during World War Two to produce bombers and 171 00:10:35,520 --> 00:10:39,720 Speaker 1: tanks and planes that became the so called arsenal of democracy. 172 00:10:40,880 --> 00:10:43,600 Speaker 1: I think it's like farming in some ways. It has 173 00:10:43,679 --> 00:10:48,800 Speaker 1: this grip on people's psyche, this view of how they 174 00:10:48,960 --> 00:10:51,839 Speaker 1: feel about the country they're in, in the world they're in. 175 00:10:52,200 --> 00:10:55,679 Speaker 1: Some of this services stuff can sometimes seem a little ephemeral, 176 00:10:56,240 --> 00:10:59,800 Speaker 1: right right, Well, And to give you some context, manufacturing 177 00:10:59,800 --> 00:11:04,679 Speaker 1: now accounts for about twelve GDP. It was almost so 178 00:11:04,760 --> 00:11:07,720 Speaker 1: a big drop there. But I think to help answer 179 00:11:07,800 --> 00:11:10,960 Speaker 1: your question, ay, we should bring on someone who really 180 00:11:11,000 --> 00:11:14,520 Speaker 1: knows a lot more about the manufacturing industry. But first 181 00:11:14,679 --> 00:11:21,720 Speaker 1: a word from our sponsor. 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That's 190 00:11:49,440 --> 00:11:51,920 Speaker 1: why we think binary options are the future of trading, 191 00:11:52,480 --> 00:11:54,560 Speaker 1: and it's here now at n A d e X 192 00:11:54,679 --> 00:11:57,800 Speaker 1: dot com, Futures options and swaps. Trading involves risk and 193 00:11:57,800 --> 00:12:06,080 Speaker 1: may not be appropriate for all investors. Well, since none 194 00:12:06,080 --> 00:12:09,880 Speaker 1: of us on this show have actually held a manufacturing job, 195 00:12:10,200 --> 00:12:14,000 Speaker 1: we have a surprise guest on the line to share 196 00:12:14,120 --> 00:12:22,120 Speaker 1: her firsthand experiences. Hi. Mom, Hi, I'm good, Thanks for 197 00:12:22,320 --> 00:12:26,200 Speaker 1: joining us. Oh, you're welcome. Glad that I could do 198 00:12:26,280 --> 00:12:29,280 Speaker 1: it me too. We wanted to talk to you because 199 00:12:29,320 --> 00:12:32,920 Speaker 1: we thought you would just have really great personal experience 200 00:12:33,200 --> 00:12:35,520 Speaker 1: with the manufacturing industry and we just wanted to learn 201 00:12:35,559 --> 00:12:38,439 Speaker 1: a little bit more about it from you. So to start, 202 00:12:38,720 --> 00:12:41,959 Speaker 1: how long have you worked in manufacturing. Well, I have 203 00:12:42,160 --> 00:12:46,920 Speaker 1: been in manufacturing basically all my life. And we're gonna 204 00:12:46,960 --> 00:12:50,240 Speaker 1: say that's rough. Really, uh, forty three years I've been 205 00:12:50,280 --> 00:12:53,439 Speaker 1: in manufacturing. I went into manufacturing right after I graduated 206 00:12:53,440 --> 00:12:56,000 Speaker 1: from my school. And has that been in North Carolina 207 00:12:56,080 --> 00:13:00,719 Speaker 1: the whole time? Debbie, You've had a number of jobs, right. 208 00:13:01,000 --> 00:13:03,960 Speaker 1: Tory was telling us that you've worked at a bunch 209 00:13:04,000 --> 00:13:07,720 Speaker 1: of different factories before you actually started working at your 210 00:13:07,760 --> 00:13:13,000 Speaker 1: current company. Yes, I went into the manufacturing field. Was 211 00:13:13,120 --> 00:13:16,640 Speaker 1: in nineteen and seventy two. I went into furniture and 212 00:13:16,880 --> 00:13:20,240 Speaker 1: I worked in furniture for a few years, and then 213 00:13:20,920 --> 00:13:25,800 Speaker 1: I twitched Ubbord and went into the hushry textile area. 214 00:13:26,080 --> 00:13:30,000 Speaker 1: I did that and I was probably in the hushry 215 00:13:30,080 --> 00:13:34,640 Speaker 1: textile area about fifteen years. Then I decided to venture 216 00:13:34,640 --> 00:13:38,520 Speaker 1: out and try something different and I went into working 217 00:13:38,600 --> 00:13:41,719 Speaker 1: with a company that did security systems. That was with 218 00:13:41,840 --> 00:13:45,280 Speaker 1: that company about thirteen fourteen years aftil I left there. 219 00:13:45,760 --> 00:13:50,199 Speaker 1: I went on another adventure and I worked at a hospital, 220 00:13:50,840 --> 00:13:54,800 Speaker 1: and uh, I did two different things at that hospital. 221 00:13:55,400 --> 00:13:58,600 Speaker 1: One area I worked in the cafeteria and then another 222 00:13:58,679 --> 00:14:02,880 Speaker 1: area is I worked within the hospital itself in another 223 00:14:03,040 --> 00:14:06,680 Speaker 1: area doing housekeeping and stuff like that. But then after 224 00:14:06,800 --> 00:14:10,000 Speaker 1: I left there, I went in back into the manufacturing 225 00:14:10,080 --> 00:14:13,400 Speaker 1: fields and I went into automotives. I worked there for 226 00:14:13,480 --> 00:14:16,120 Speaker 1: about two years, and then now I am working in 227 00:14:16,679 --> 00:14:20,680 Speaker 1: heavy equipment hydraulic maintenance. So one of the things we've 228 00:14:20,760 --> 00:14:24,280 Speaker 1: talked about on this show is not just how manufacturing 229 00:14:24,360 --> 00:14:28,480 Speaker 1: has changed, but how proportionately it accounts for a small 230 00:14:28,600 --> 00:14:32,160 Speaker 1: share of the American workforce than it really does. Have 231 00:14:32,320 --> 00:14:35,760 Speaker 1: you noticed that playout in your life and in the 232 00:14:35,880 --> 00:14:39,240 Speaker 1: careers of your college. Oh? Yes, especially the area that 233 00:14:39,320 --> 00:14:42,040 Speaker 1: Toy was born and raised. Then it's a little small 234 00:14:42,160 --> 00:14:45,760 Speaker 1: rural area and picker in North Carolina. It is a 235 00:14:45,960 --> 00:14:49,680 Speaker 1: very important part because that is the main uh sence 236 00:14:49,840 --> 00:14:53,200 Speaker 1: of the majority of the people's income there, especially the 237 00:14:53,280 --> 00:14:57,240 Speaker 1: people my age and maybe the next generation down. That 238 00:14:57,440 --> 00:14:59,800 Speaker 1: was basically the thing they've done. They went, they went 239 00:14:59,840 --> 00:15:02,520 Speaker 1: to school, they graduated from high school, they got married, 240 00:15:02,600 --> 00:15:04,840 Speaker 1: they got a job, they got married, they had children, 241 00:15:05,320 --> 00:15:10,520 Speaker 1: and back in two thousand eight nine, whenever the job 242 00:15:10,640 --> 00:15:14,080 Speaker 1: market really drops, I had I've seen personally a lot 243 00:15:14,160 --> 00:15:17,240 Speaker 1: of people lose their homes, lose everything they had because 244 00:15:17,560 --> 00:15:20,960 Speaker 1: they lost their job. At a point when Tory was 245 00:15:21,000 --> 00:15:23,600 Speaker 1: still in high school. I lost my job and I 246 00:15:23,720 --> 00:15:27,920 Speaker 1: wasn't without a job for several months without a jobs. Thankfully, 247 00:15:28,280 --> 00:15:30,360 Speaker 1: we had a place to stay. But I've seen a 248 00:15:30,400 --> 00:15:33,600 Speaker 1: lot of people lose their homes, and it was basically 249 00:15:33,680 --> 00:15:36,440 Speaker 1: because of the furniture we in the area that we 250 00:15:36,560 --> 00:15:40,320 Speaker 1: live in, Hugh cre is a big furniture market area, 251 00:15:40,840 --> 00:15:44,480 Speaker 1: and a lot of the furniture companies had quit, had 252 00:15:44,640 --> 00:15:49,680 Speaker 1: closed their doors, moved to Mexico, China, wherever, and people 253 00:15:49,720 --> 00:15:51,880 Speaker 1: didn't have jobs. And there were a lot of those 254 00:15:51,960 --> 00:15:54,680 Speaker 1: people that worked there for all their lives. I mean 255 00:15:55,040 --> 00:15:58,240 Speaker 1: sometimes some people had worked our thirty five years, that's 256 00:15:58,240 --> 00:16:00,760 Speaker 1: the only job that they ever had. Thank goodness, were 257 00:16:00,840 --> 00:16:03,840 Speaker 1: past the depth of two thousand, two thousand and nine. 258 00:16:04,760 --> 00:16:10,240 Speaker 1: But on the ground, how much of a substantial or 259 00:16:10,360 --> 00:16:13,880 Speaker 1: if any return to pre two thousand and eight has 260 00:16:13,960 --> 00:16:16,640 Speaker 1: there been? Have most of the people who you mentioned 261 00:16:17,040 --> 00:16:21,320 Speaker 1: found other jobs, have jobs at those same places come back, 262 00:16:21,480 --> 00:16:24,880 Speaker 1: or have new employers moved in. Well that some new 263 00:16:25,000 --> 00:16:28,680 Speaker 1: companies have moved in. Not very many of the all 264 00:16:28,840 --> 00:16:32,280 Speaker 1: factories have moved back. There's a few that have came back, 265 00:16:32,680 --> 00:16:38,360 Speaker 1: but mostly everybody else has went to another field. Like 266 00:16:38,600 --> 00:16:41,760 Speaker 1: and olso the textile, the hosi business that really drops 267 00:16:42,160 --> 00:16:45,480 Speaker 1: during that time, and we really don't have a lot 268 00:16:45,560 --> 00:16:48,960 Speaker 1: of textiles and hosie around here anymore. But a lot 269 00:16:49,040 --> 00:16:52,400 Speaker 1: of places offered the people to go to school. And 270 00:16:52,960 --> 00:16:57,080 Speaker 1: we had a program during that with the Unemployment Commission 271 00:16:57,200 --> 00:16:59,920 Speaker 1: that the Employment Commission that we could go to school 272 00:17:00,280 --> 00:17:03,000 Speaker 1: if you if you chose to just lant a new trade. 273 00:17:03,600 --> 00:17:06,240 Speaker 1: And a lot of people did that. But and then 274 00:17:06,320 --> 00:17:09,840 Speaker 1: there's there's others that just feeling they didn't do theydn't 275 00:17:09,880 --> 00:17:13,920 Speaker 1: do anything, you know, so right now they're still out 276 00:17:14,000 --> 00:17:18,120 Speaker 1: there trying to find a job. I think, Mom would 277 00:17:18,160 --> 00:17:21,720 Speaker 1: be really interesting to hear sort of what a typical 278 00:17:21,960 --> 00:17:24,800 Speaker 1: day for you is like, because I'm not sure that 279 00:17:25,280 --> 00:17:28,080 Speaker 1: too many people know. You know, what it's like to 280 00:17:28,160 --> 00:17:31,440 Speaker 1: work in a factory. Um, what's it? What's it like 281 00:17:31,840 --> 00:17:35,120 Speaker 1: for you as a as a factory worker? In my position, 282 00:17:35,400 --> 00:17:38,720 Speaker 1: I'm a kind of a supervisor overseer over a production 283 00:17:38,920 --> 00:17:41,520 Speaker 1: area in the in the company that I work for, 284 00:17:42,160 --> 00:17:45,399 Speaker 1: and I just have to go in every day and 285 00:17:45,720 --> 00:17:49,800 Speaker 1: I've got to make sure that all of the I 286 00:17:49,920 --> 00:17:52,560 Speaker 1: have all these the products the supplies that I need 287 00:17:52,680 --> 00:17:56,400 Speaker 1: to make our our products. UH. In the meantime, while 288 00:17:56,400 --> 00:17:59,280 Speaker 1: I'm doing this, I'm also running different kind of machinery 289 00:17:59,359 --> 00:18:03,680 Speaker 1: that we have to do, and it's constant all the time, 290 00:18:04,080 --> 00:18:07,560 Speaker 1: something to do. It's fast paced, and you've got age. 291 00:18:07,600 --> 00:18:10,240 Speaker 1: You can't be fast with your job. You're not gonna 292 00:18:10,280 --> 00:18:13,040 Speaker 1: make it there along because they want people that that 293 00:18:13,320 --> 00:18:16,800 Speaker 1: have space and are interested in London and want to learn. 294 00:18:17,280 --> 00:18:20,280 Speaker 1: You know, Debbie, it was so interesting listening to you 295 00:18:20,400 --> 00:18:22,639 Speaker 1: talk about all the different jobs that you've held that 296 00:18:22,760 --> 00:18:26,800 Speaker 1: you moved from furniture to textiles, to autos to now 297 00:18:26,880 --> 00:18:30,840 Speaker 1: heavy equipment, because that's really a story of the shifts 298 00:18:30,960 --> 00:18:33,959 Speaker 1: in American manufacturing over the last few decades. You can 299 00:18:34,040 --> 00:18:39,080 Speaker 1: really see this move from UH less profitable, lower value 300 00:18:39,160 --> 00:18:43,400 Speaker 1: added UM industries to UH something like heavy equipment that's 301 00:18:43,400 --> 00:18:47,680 Speaker 1: a lot more profitable and involves higher technology. I guess, 302 00:18:47,960 --> 00:18:50,119 Speaker 1: but I was wondering, did you ever have to go 303 00:18:50,359 --> 00:18:54,360 Speaker 1: back to school to transition between these jobs or get 304 00:18:54,400 --> 00:18:58,480 Speaker 1: additional training? Personally myself, I have it, but I have 305 00:18:58,680 --> 00:19:01,919 Speaker 1: known people that how went back to school so they 306 00:19:01,960 --> 00:19:05,520 Speaker 1: can learn how to runch machines and stuff. And when 307 00:19:05,600 --> 00:19:09,199 Speaker 1: they've returned from school, have they kept their employment at 308 00:19:09,200 --> 00:19:12,479 Speaker 1: the same place. Yes, and they usually get a bit 309 00:19:12,520 --> 00:19:16,199 Speaker 1: of a real nice pay rate when they actively complete 310 00:19:16,240 --> 00:19:20,040 Speaker 1: their schooling, because that's why they send them to schools 311 00:19:20,160 --> 00:19:23,640 Speaker 1: to learn how to operate a very high tech machine. 312 00:19:24,359 --> 00:19:27,200 Speaker 1: Is the common person coming off the street can't run it, 313 00:19:27,280 --> 00:19:29,960 Speaker 1: and you have to go to school to to know 314 00:19:30,119 --> 00:19:36,280 Speaker 1: how to maintain, how to operate it, and everything about it. Dad, 315 00:19:36,400 --> 00:19:40,760 Speaker 1: we've been wrestling with two competing narratives. One says that 316 00:19:41,720 --> 00:19:46,440 Speaker 1: manufacturing in the US is back, there's this manufacturing renaissance. 317 00:19:47,160 --> 00:19:49,119 Speaker 1: Then on the other side of the fence, you've got 318 00:19:49,160 --> 00:19:53,240 Speaker 1: a school of thought that says manufacturing is really history 319 00:19:53,320 --> 00:19:59,000 Speaker 1: in the US. So from your perspective, which is true, Well, 320 00:19:59,600 --> 00:20:03,679 Speaker 1: from perspective, I believe it could be in the middle. 321 00:20:04,520 --> 00:20:07,840 Speaker 1: Right now, I think manufacturing is still a part of 322 00:20:07,880 --> 00:20:11,119 Speaker 1: our lives and in and it will be for a while. 323 00:20:11,680 --> 00:20:15,080 Speaker 1: But I think further on down the road to say, 324 00:20:15,160 --> 00:20:19,960 Speaker 1: like by the time maybe tories forty or so, maybe 325 00:20:20,520 --> 00:20:26,320 Speaker 1: when is that exactly, Let's say, five, ten or twenty years. 326 00:20:26,480 --> 00:20:31,840 Speaker 1: I'm not fifteen or twenty years down the road. Uh, 327 00:20:32,320 --> 00:20:36,240 Speaker 1: I could I could see it, Bason now, Well, Mom, yes, 328 00:20:36,880 --> 00:20:40,399 Speaker 1: thank you so much as anyone else have any other questions, Debbie, 329 00:20:40,400 --> 00:20:44,520 Speaker 1: I have one more question, how the skill of once attend? 330 00:20:44,600 --> 00:20:48,080 Speaker 1: How proud are you of Tori for being an internationally 331 00:20:48,240 --> 00:20:55,080 Speaker 1: famous podcaster? That would be a one chen very very 332 00:20:55,200 --> 00:21:00,880 Speaker 1: proud of Toy. I am so glad that she decided 333 00:21:00,920 --> 00:21:04,520 Speaker 1: to go to college and do what she does and 334 00:21:06,119 --> 00:21:10,440 Speaker 1: not be living there because her generations, the ones that 335 00:21:10,560 --> 00:21:14,439 Speaker 1: live there, they're falling in the same the same mode 336 00:21:14,760 --> 00:21:17,680 Speaker 1: that their parents and their grandparents are there out here 337 00:21:17,720 --> 00:21:20,040 Speaker 1: trying to find a factory job, you know. And that's 338 00:21:20,119 --> 00:21:23,080 Speaker 1: that's one thing I'm proud of about Tory. But when 339 00:21:23,119 --> 00:21:25,480 Speaker 1: Tori was a little girl, I came home one day 340 00:21:25,760 --> 00:21:29,480 Speaker 1: and she said, when I grow up, I'm not working 341 00:21:29,520 --> 00:21:32,720 Speaker 1: for Peanuts. And I said what, And she said, I'm 342 00:21:32,800 --> 00:21:35,800 Speaker 1: not working for Peanuts when I grow up. And she 343 00:21:36,640 --> 00:21:39,560 Speaker 1: followed her green and her boat. And I am very 344 00:21:39,600 --> 00:21:42,320 Speaker 1: proud of her. We're coming up to annual review time. 345 00:21:44,359 --> 00:21:47,800 Speaker 1: I'll keep I'll keep the I'll keep the Peanuts thing 346 00:21:47,880 --> 00:21:51,960 Speaker 1: in mind for Tories. I mean, just that laugh alone 347 00:21:52,160 --> 00:21:54,880 Speaker 1: is worth being proud of it. I don't believe there's 348 00:21:54,880 --> 00:21:58,160 Speaker 1: another Laft in the world like that. Laft. Well, thank 349 00:21:58,200 --> 00:22:00,480 Speaker 1: you so much for joining us today. It's been a 350 00:22:00,560 --> 00:22:03,080 Speaker 1: real privilege to have you on the show. Has been 351 00:22:03,080 --> 00:22:06,040 Speaker 1: a privilege to talk to you all too. All right, Mom, 352 00:22:06,160 --> 00:22:08,960 Speaker 1: love you, thank you, love you too, and talk to 353 00:22:09,000 --> 00:22:14,159 Speaker 1: you later. Okay. Bye. So I guess to answer your 354 00:22:14,280 --> 00:22:17,200 Speaker 1: question Aki, that you posed at the beginning of the show, 355 00:22:17,520 --> 00:22:21,760 Speaker 1: I would say, yes, manufacturing does still matter in America. 356 00:22:24,720 --> 00:22:27,800 Speaker 1: Thanks again for listening to Bloomberg Benchmark. We will be 357 00:22:27,920 --> 00:22:30,280 Speaker 1: back next week and until then you can find us 358 00:22:30,320 --> 00:22:32,880 Speaker 1: on the Bloomberg Terminal and Bloomberg dot com, as well 359 00:22:32,920 --> 00:22:37,680 Speaker 1: as on iTunes, pocket Cast, Stitcher, Google Play. And while 360 00:22:37,720 --> 00:22:40,200 Speaker 1: you're there, take a minute to rate and review the 361 00:22:40,240 --> 00:22:42,600 Speaker 1: show so more listeners can find us. And a very 362 00:22:42,680 --> 00:22:45,480 Speaker 1: special thank you to Debbie. Let us see what you 363 00:22:45,560 --> 00:22:47,200 Speaker 1: thought of the show. You can talk to us and 364 00:22:47,359 --> 00:22:50,840 Speaker 1: follow us on Twitter at Aki epos seven, Acrey still 365 00:22:50,880 --> 00:22:54,360 Speaker 1: Well and Daniel mass d C. Thanks again. We'll see 366 00:22:54,400 --> 00:23:00,480 Speaker 1: you next week, hopefully we can talk this one. PS 367 00:23:00,600 --> 00:23:04,240 Speaker 1: two pass by pas best pass stor