1 00:00:00,240 --> 00:00:03,120 Speaker 1: Brought to you by Bank of America. Merrill Lynch Seeing 2 00:00:03,120 --> 00:00:05,600 Speaker 1: what others have seen, but uncovering what others may not. 3 00:00:06,000 --> 00:00:09,680 Speaker 1: Global Research that helps you harness disruption voted top global 4 00:00:09,720 --> 00:00:13,000 Speaker 1: research from five years running. Merrill Lynch, Pierce, Fenner and 5 00:00:13,080 --> 00:00:16,279 Speaker 1: Smith Incorporated. If all things were equal, you know, and 6 00:00:16,320 --> 00:00:18,080 Speaker 1: you worked an eight hour day and you made enough 7 00:00:18,120 --> 00:00:20,919 Speaker 1: money to pay your bills, it would be a decent job. 8 00:00:21,079 --> 00:00:23,080 Speaker 1: Because you're out, You're out on the road. I mean, 9 00:00:23,120 --> 00:00:24,759 Speaker 1: there is the freedom. One of the reasons I drove 10 00:00:24,800 --> 00:00:35,800 Speaker 1: a truck is because I don't like sitting behind a desk. Hello, 11 00:00:35,880 --> 00:00:39,440 Speaker 1: and welcome back to Bloomberg Benchmark Show about the Global economy. 12 00:00:39,880 --> 00:00:44,159 Speaker 1: It's Thursday October. I'm Scott Landman, an economics editor with 13 00:00:44,159 --> 00:00:46,720 Speaker 1: Bloomberg and News in Washington, and I'm Keith Smith, an 14 00:00:46,800 --> 00:00:49,760 Speaker 1: editor with Bloomberg in New York. Today we're going to 15 00:00:49,800 --> 00:00:52,680 Speaker 1: turn our attention to one of the biggest economic puzzles 16 00:00:52,720 --> 00:00:55,880 Speaker 1: of our time, one that seems to be a microcosm 17 00:00:56,040 --> 00:00:58,880 Speaker 1: of the U. S. Labor market. It seems like a 18 00:00:58,880 --> 00:01:01,560 Speaker 1: lot of numbers show it's in great shape, but below 19 00:01:01,600 --> 00:01:05,440 Speaker 1: the surface, some funky things are going on. And one 20 00:01:05,480 --> 00:01:07,840 Speaker 1: of those kind of funky things that you're talking about, Scott, 21 00:01:07,920 --> 00:01:10,880 Speaker 1: is where have all the truck drivers gone? That's right. 22 00:01:11,160 --> 00:01:14,120 Speaker 1: We'll be talking first with Justin Fox, a columnist for 23 00:01:14,240 --> 00:01:17,200 Speaker 1: Bloomberg View who has written about this issue, and then 24 00:01:17,240 --> 00:01:20,120 Speaker 1: with an actual truck driver who happens to be a 25 00:01:20,319 --> 00:01:24,480 Speaker 1: close relative of mine. What actually sparked this discussion is 26 00:01:24,520 --> 00:01:27,360 Speaker 1: a recent article by one of our U S economy reporters, 27 00:01:27,600 --> 00:01:31,640 Speaker 1: Patricia Eliah. She wrote that one trucking company is getting 28 00:01:31,680 --> 00:01:35,199 Speaker 1: so desperate for new drivers that they're handing out all 29 00:01:35,280 --> 00:01:39,080 Speaker 1: kinds of bonuses, including signing bonuses of up to five 30 00:01:39,200 --> 00:01:42,280 Speaker 1: thousand dollars. And Scott, when I read that, there was 31 00:01:42,319 --> 00:01:45,200 Speaker 1: just so fascinating to me because the idea of, you know, 32 00:01:45,280 --> 00:01:49,440 Speaker 1: the signing bonus here in the economy is just it's 33 00:01:49,480 --> 00:01:51,880 Speaker 1: so unheard of. That's I mean, that's something that's like 34 00:01:51,880 --> 00:01:55,200 Speaker 1: reserved for the NFL or the NBA or something like that, 35 00:01:55,320 --> 00:01:58,280 Speaker 1: certainly not truck drivers from what I would assume. Yeah, 36 00:01:58,280 --> 00:02:00,320 Speaker 1: I mean I was thinking of these draft picks that 37 00:02:00,520 --> 00:02:02,960 Speaker 1: get like a million dollar bonus if they're going to 38 00:02:03,040 --> 00:02:06,640 Speaker 1: be the next hot quarterback or something like that. But um, 39 00:02:06,800 --> 00:02:09,280 Speaker 1: you know, it's not just the shortage, the shortage of 40 00:02:09,360 --> 00:02:13,960 Speaker 1: labor that's driving up these bonuses and wage costs for companies. 41 00:02:14,160 --> 00:02:15,600 Speaker 1: And Patty explained to me there are a lot of 42 00:02:15,639 --> 00:02:18,760 Speaker 1: other factors going on. There's an age restriction, you have 43 00:02:18,840 --> 00:02:21,360 Speaker 1: to be at least twenty one to drive across state lines. 44 00:02:21,760 --> 00:02:26,320 Speaker 1: Certifications are expensive, truck drivers are aging, It's not an 45 00:02:26,320 --> 00:02:28,520 Speaker 1: easy job to do, and you're away from home a 46 00:02:28,560 --> 00:02:32,880 Speaker 1: lot um. So what gives here though? Is there really 47 00:02:32,960 --> 00:02:35,680 Speaker 1: a worker shortage or are they just not offering high 48 00:02:35,800 --> 00:02:40,160 Speaker 1: enough wages or something deeper going on. I want to 49 00:02:40,200 --> 00:02:42,760 Speaker 1: bring in Justin Fox, who's sitting with Kate in our 50 00:02:42,760 --> 00:02:46,400 Speaker 1: New York studio. Justin's a calumnist for Bloomberg View and 51 00:02:46,680 --> 00:02:50,519 Speaker 1: used to be the editorial director at the Harvard Business Review. Justin, 52 00:02:50,600 --> 00:02:53,600 Speaker 1: thanks for joining us, Thanks for having me so, Justin, 53 00:02:53,760 --> 00:02:56,640 Speaker 1: you also wrote a column of after seeing Patty's story, 54 00:02:56,720 --> 00:02:58,840 Speaker 1: and it was trying to figure out what's going on 55 00:02:58,840 --> 00:03:01,160 Speaker 1: with all of these truck drivers. So I mean, talk 56 00:03:01,200 --> 00:03:03,080 Speaker 1: to us about kind of some of your main theories. 57 00:03:03,080 --> 00:03:04,119 Speaker 1: What do you what do you think is the most 58 00:03:04,120 --> 00:03:07,760 Speaker 1: plausible here? Well, everybody's been talking a lot about this 59 00:03:07,840 --> 00:03:12,000 Speaker 1: looming threat of automation, um in trucks and cars and 60 00:03:12,040 --> 00:03:14,960 Speaker 1: everything else. And I mean one of the interesting things 61 00:03:15,040 --> 00:03:18,400 Speaker 1: is truck driving. In a time when manufacturing employment has 62 00:03:18,440 --> 00:03:21,839 Speaker 1: been on this long decline, truck driving has made up 63 00:03:21,880 --> 00:03:23,640 Speaker 1: for a lot of that, and it's something you don't 64 00:03:23,680 --> 00:03:26,399 Speaker 1: necessarily need a college education to be able to do. 65 00:03:26,720 --> 00:03:30,040 Speaker 1: Traditionally the pay was pretty good and so um. I 66 00:03:30,080 --> 00:03:32,840 Speaker 1: Actually it happened to be that Patricia's story came out 67 00:03:32,880 --> 00:03:36,000 Speaker 1: the day before the monthly jobs report for September, and 68 00:03:36,040 --> 00:03:38,360 Speaker 1: so I like to dig around in the job's report 69 00:03:38,480 --> 00:03:40,800 Speaker 1: to look at things that other people aren't paying attention 70 00:03:41,120 --> 00:03:43,160 Speaker 1: to every month, and so I was just I thought, oh, 71 00:03:43,200 --> 00:03:46,680 Speaker 1: I'll look at trucking employment. And one interesting and somewhat 72 00:03:46,720 --> 00:03:49,720 Speaker 1: odd thing is it hasn't actually grown since mid two 73 00:03:49,720 --> 00:03:52,840 Speaker 1: thousand fifteen. There was a big recovery from the recession, 74 00:03:53,160 --> 00:03:55,000 Speaker 1: and then it's been pretty much flat since then. And 75 00:03:55,000 --> 00:03:58,000 Speaker 1: what is that? Because there, you know, maybe there's demand 76 00:03:58,040 --> 00:03:59,880 Speaker 1: in this one place. I think it was in floor 77 00:04:00,040 --> 00:04:02,240 Speaker 1: to the Patricia wrote about maybe it's not national, or 78 00:04:02,280 --> 00:04:05,040 Speaker 1: maybe it's just that trucking companies are having so much 79 00:04:05,040 --> 00:04:09,480 Speaker 1: trouble getting people. So then I looked at wages in trucking, 80 00:04:10,040 --> 00:04:13,920 Speaker 1: and I mean that should there's no dramatic developments in 81 00:04:13,960 --> 00:04:16,440 Speaker 1: that lately. They haven't suddenly gone way up, although you 82 00:04:16,520 --> 00:04:19,560 Speaker 1: might not capture these kind of signing bonuses thing in 83 00:04:19,560 --> 00:04:23,880 Speaker 1: that data anyway, but put some context, So what kind 84 00:04:23,920 --> 00:04:26,440 Speaker 1: of would be the range of truck driving wages? I'm 85 00:04:26,440 --> 00:04:28,920 Speaker 1: just I'm just curious if I've totally picked the wrong 86 00:04:28,960 --> 00:04:32,839 Speaker 1: career choice here. I mean, it's currently looks to be 87 00:04:32,920 --> 00:04:37,240 Speaker 1: around a little over twenty dollars an hour average hourly 88 00:04:37,279 --> 00:04:42,040 Speaker 1: earnings of production and non supervisory employees in the trucking industry. 89 00:04:42,080 --> 00:04:44,360 Speaker 1: And now the interesting thing is in nineties there was 90 00:04:44,400 --> 00:04:46,920 Speaker 1: a big truckers made a bunch more than most workers, 91 00:04:47,800 --> 00:04:53,200 Speaker 1: um and then somewhere around after two thousand that slid 92 00:04:53,279 --> 00:04:57,000 Speaker 1: down to where it's almost identical to the average private, 93 00:04:57,120 --> 00:05:00,560 Speaker 1: non farm, non supervisory worker. And how much war was 94 00:05:00,600 --> 00:05:03,080 Speaker 1: it back in kind of what you were saying, I mean, 95 00:05:03,080 --> 00:05:05,000 Speaker 1: I'm eyeballing a charge here. It looks like it was 96 00:05:05,000 --> 00:05:10,200 Speaker 1: about thirteen dollars to ten dollars. It was significant. One thing, 97 00:05:10,279 --> 00:05:13,360 Speaker 1: one other thing in Patty's story justin was that, uh, 98 00:05:13,480 --> 00:05:17,280 Speaker 1: some some companies, trucking companies were also reporting that they 99 00:05:17,600 --> 00:05:20,280 Speaker 1: needed to find workers, but they were unable to raise 100 00:05:20,360 --> 00:05:23,760 Speaker 1: wages because they couldn't really raise the prices they were charging. 101 00:05:23,960 --> 00:05:26,840 Speaker 1: Is that, you know, a broader conundrum in the economy 102 00:05:26,880 --> 00:05:31,840 Speaker 1: or dilemma? Um, I mean it definitely. These have not 103 00:05:32,000 --> 00:05:35,440 Speaker 1: been a great few years for trucking companies, and I'm 104 00:05:35,440 --> 00:05:37,640 Speaker 1: not exactly sure why that is. I think part of 105 00:05:37,640 --> 00:05:42,600 Speaker 1: it is just the recession came and sort of goods 106 00:05:42,640 --> 00:05:47,000 Speaker 1: trade volumes never quite boomed back to where they were before. 107 00:05:47,400 --> 00:05:51,200 Speaker 1: Maybe people are spending more time buying apps than buying stuff, 108 00:05:51,880 --> 00:05:55,800 Speaker 1: um so, and and trucking companies in general just had 109 00:05:55,800 --> 00:05:59,160 Speaker 1: a really tough time, So I would imagine that, I mean, 110 00:05:59,200 --> 00:06:02,479 Speaker 1: a it's just it's still a competitive enough, competitive enough 111 00:06:02,520 --> 00:06:06,240 Speaker 1: industry that, um, you know, they can't just set prices 112 00:06:06,279 --> 00:06:09,120 Speaker 1: as they will be. There's these new players coming in, 113 00:06:09,279 --> 00:06:14,360 Speaker 1: like most notably Amazon, that are probably making life tougher 114 00:06:14,520 --> 00:06:17,320 Speaker 1: for some of the incumbents. And it's also hard to 115 00:06:17,400 --> 00:06:21,120 Speaker 1: kind of talk about, you know, something like trucking industry. Right, 116 00:06:21,200 --> 00:06:23,920 Speaker 1: so it doesn't necessarily require a college degree, but it's 117 00:06:23,920 --> 00:06:26,960 Speaker 1: a steady job, it can pay pretty much. And like 118 00:06:27,160 --> 00:06:29,720 Speaker 1: as we've been watching this election, unfold. That's one thing 119 00:06:29,760 --> 00:06:31,680 Speaker 1: that keeps getting brought up. All our jobs are gone, 120 00:06:31,680 --> 00:06:34,080 Speaker 1: all our jobs are gone. But in reality it sounds 121 00:06:34,080 --> 00:06:36,120 Speaker 1: like we're talking about a job where they're having a 122 00:06:36,120 --> 00:06:39,240 Speaker 1: hard time attracting people. Yeah, but part of that is 123 00:06:39,320 --> 00:06:41,160 Speaker 1: it's no longer as good a job as it used 124 00:06:41,160 --> 00:06:42,960 Speaker 1: to be. I mean, the pay used to be better, 125 00:06:43,000 --> 00:06:45,359 Speaker 1: and we may be hearing later that the work conditions 126 00:06:45,360 --> 00:06:47,559 Speaker 1: aren't as good. I don't know about that. What about 127 00:06:47,600 --> 00:06:50,320 Speaker 1: these stories that have been coming out recently. There's there's 128 00:06:50,360 --> 00:06:55,839 Speaker 1: one study by former Obama economic advisor Alan Krueger saying 129 00:06:55,880 --> 00:06:59,080 Speaker 1: that men are men who are out of the labor force, 130 00:06:59,120 --> 00:07:01,599 Speaker 1: a lot of them are on pain medication. And there's 131 00:07:01,640 --> 00:07:04,720 Speaker 1: other people citing a study saying men would rather play 132 00:07:04,839 --> 00:07:06,599 Speaker 1: video games. These are people who have kind of be 133 00:07:06,640 --> 00:07:09,720 Speaker 1: in the prime age for a trucking job. What do 134 00:07:09,720 --> 00:07:12,360 Speaker 1: you make of that? I mean, it's really this this 135 00:07:12,440 --> 00:07:15,840 Speaker 1: puzzle of why there's so many more men out of 136 00:07:15,840 --> 00:07:18,400 Speaker 1: the labor force than there used to be. I mean, 137 00:07:18,440 --> 00:07:21,760 Speaker 1: it's been the steady growth since the sixties, but pretty 138 00:07:21,840 --> 00:07:25,920 Speaker 1: dramatic um since two thousand and you know, there's a 139 00:07:25,960 --> 00:07:28,920 Speaker 1: bunch of different different explanations one of them. Part of 140 00:07:28,960 --> 00:07:31,760 Speaker 1: it is clearly on the the sort of demand for 141 00:07:31,800 --> 00:07:36,200 Speaker 1: their labor. So manufacturing jobs have declined, trucking jobs are 142 00:07:36,240 --> 00:07:38,360 Speaker 1: still there, but the pay is not as good. And 143 00:07:38,400 --> 00:07:40,640 Speaker 1: then there have been these other theories about I mean, 144 00:07:40,720 --> 00:07:44,560 Speaker 1: one big one is, um, the incarceration boom. They're just 145 00:07:44,600 --> 00:07:47,160 Speaker 1: a lot more people with criminal records than there used 146 00:07:47,200 --> 00:07:50,080 Speaker 1: to be. It's hard for them to get jobs. Um. 147 00:07:50,520 --> 00:07:56,080 Speaker 1: This video game theory from Eric Hurst, Chicago economist, is 148 00:07:56,160 --> 00:07:59,280 Speaker 1: just that, I mean, there is evidence that men who 149 00:07:59,320 --> 00:08:01,120 Speaker 1: are out of the lay refore spend a lot of 150 00:08:01,160 --> 00:08:05,880 Speaker 1: time playing games or watching TV. And one and I've 151 00:08:05,920 --> 00:08:08,080 Speaker 1: been thinking about this. When I was a kid and 152 00:08:08,160 --> 00:08:10,200 Speaker 1: I would be sick home from school, all it was 153 00:08:10,280 --> 00:08:13,480 Speaker 1: on TV was game shows and soap operas. Now, if 154 00:08:13,520 --> 00:08:15,640 Speaker 1: you're stuck at home, there's a lot of fun stuff 155 00:08:15,680 --> 00:08:17,920 Speaker 1: you can do. And so there is some argument that 156 00:08:18,040 --> 00:08:20,360 Speaker 1: actually there are other things out there if you've got 157 00:08:20,480 --> 00:08:22,840 Speaker 1: enough money to get by on and I don't know, 158 00:08:22,880 --> 00:08:25,280 Speaker 1: you're living in your parents basement and your twenty seven 159 00:08:25,800 --> 00:08:27,520 Speaker 1: you know the balance wing g Do I want to 160 00:08:27,520 --> 00:08:30,760 Speaker 1: go drive a truck all day and all night or 161 00:08:30,840 --> 00:08:32,720 Speaker 1: do I want to play video games? In the basement. 162 00:08:32,920 --> 00:08:35,120 Speaker 1: Maybe maybe that's a little bit of it, but I 163 00:08:35,640 --> 00:08:39,120 Speaker 1: can't believe. I mean, they're really big differences in male 164 00:08:39,240 --> 00:08:42,559 Speaker 1: labor force participation now between the US and a lot 165 00:08:42,600 --> 00:08:45,680 Speaker 1: of other wealthy countries. And I think the video games 166 00:08:45,720 --> 00:08:47,880 Speaker 1: are just as good in Japan and Germany as they 167 00:08:47,880 --> 00:08:49,680 Speaker 1: are in the US. So I don't know that that 168 00:08:50,000 --> 00:08:52,800 Speaker 1: explains a whole lot of it. We keep saying male 169 00:08:53,240 --> 00:08:56,960 Speaker 1: is obviously this the female statistics don't match well. The 170 00:08:57,000 --> 00:08:59,640 Speaker 1: problem with the female statistics, it's not problem, is just 171 00:08:59,720 --> 00:09:02,439 Speaker 1: that when you there's this category of people who are 172 00:09:02,480 --> 00:09:04,480 Speaker 1: not in the labor force, which means you don't have 173 00:09:04,520 --> 00:09:07,640 Speaker 1: a job, you're not looking for a job, and UM, 174 00:09:07,679 --> 00:09:10,280 Speaker 1: in the female category, people who are not in the 175 00:09:10,360 --> 00:09:15,120 Speaker 1: labor force, half of them are working, but unpaid, work 176 00:09:15,120 --> 00:09:17,400 Speaker 1: at home, they're taking care of kids, they're taking care 177 00:09:17,440 --> 00:09:20,920 Speaker 1: of elderly family members. Very small percentage of the men 178 00:09:20,960 --> 00:09:23,120 Speaker 1: who aren't in the labor force are doing that. And 179 00:09:23,200 --> 00:09:24,920 Speaker 1: so all it is is it just makes it hard 180 00:09:24,960 --> 00:09:27,320 Speaker 1: to compare the two. I think general sense, like with 181 00:09:27,360 --> 00:09:30,120 Speaker 1: the pain killers, if if you cut out those women 182 00:09:30,160 --> 00:09:33,640 Speaker 1: who are not in the labor force but are actually working, um, 183 00:09:33,679 --> 00:09:36,280 Speaker 1: the percentage of men and women who are taking pain 184 00:09:36,360 --> 00:09:38,480 Speaker 1: killers and aren't in the labor force is about probably 185 00:09:38,480 --> 00:09:42,480 Speaker 1: about the same. Interesting All right, well, Justin and Kate, 186 00:09:42,559 --> 00:09:44,640 Speaker 1: we're going to take a quick break now for a 187 00:09:44,640 --> 00:09:47,000 Speaker 1: word from our sponsor, and when we're back, we are 188 00:09:47,120 --> 00:09:49,680 Speaker 1: going to talk with my uncle who spent his whole 189 00:09:49,720 --> 00:10:00,920 Speaker 1: career as a truck driver. Brought to you by Bank 190 00:10:00,920 --> 00:10:03,920 Speaker 1: of America Merrill Lynch. Seeing what others have seen, but 191 00:10:04,040 --> 00:10:06,959 Speaker 1: uncovering what others may not. Global Research that helps you 192 00:10:07,000 --> 00:10:11,120 Speaker 1: Harness disruption voted top global research from five years running. 193 00:10:11,440 --> 00:10:24,000 Speaker 1: Merrill Lynch, Pierce, Venner and Smith Incorporated. Welcome back. Now 194 00:10:24,080 --> 00:10:26,640 Speaker 1: we're going to bring in a very special guest, someone 195 00:10:26,679 --> 00:10:29,480 Speaker 1: who knows a lot about the trucking industry because he 196 00:10:29,559 --> 00:10:32,800 Speaker 1: spent thirty seven years as a truck driver himself and 197 00:10:33,080 --> 00:10:36,440 Speaker 1: actually now drives a minibus locally. He happens to be 198 00:10:36,520 --> 00:10:39,679 Speaker 1: my uncle. Kenny Han joins us from his home on 199 00:10:39,679 --> 00:10:42,920 Speaker 1: Long Island in Central Islip, New York. Hey, uncle Kenny, 200 00:10:42,920 --> 00:10:45,640 Speaker 1: how's it going. It's going great. How's it going with you? Scott? 201 00:10:45,880 --> 00:10:49,040 Speaker 1: All right? So can you just give us a quick 202 00:10:49,040 --> 00:10:51,960 Speaker 1: recap of your career as a driver and how you 203 00:10:52,000 --> 00:10:57,000 Speaker 1: got started, Well, um, it was sort of something I 204 00:10:57,040 --> 00:10:59,080 Speaker 1: had to do. When I was about seventeen years old, 205 00:10:59,120 --> 00:11:02,080 Speaker 1: I got married and uh I believe it or not, 206 00:11:02,200 --> 00:11:05,000 Speaker 1: and so I just took whatever job I could get, 207 00:11:05,040 --> 00:11:07,600 Speaker 1: you know, and I started driving first. I first started 208 00:11:07,679 --> 00:11:11,800 Speaker 1: driving a van for florist, but I drove a truck 209 00:11:11,840 --> 00:11:14,599 Speaker 1: starting when I was eighteen, I started driving for a 210 00:11:14,679 --> 00:11:19,280 Speaker 1: kitchen cabinet distributor, and then back when around nineteen eighty 211 00:11:19,360 --> 00:11:22,320 Speaker 1: I got my my tractor trailer license and started driving 212 00:11:22,320 --> 00:11:26,280 Speaker 1: over the road and then became a teamster in four 213 00:11:27,240 --> 00:11:29,920 Speaker 1: and worked for the same company for twenty six years. 214 00:11:29,920 --> 00:11:33,439 Speaker 1: Retired from there and in two thousand and eight, and 215 00:11:33,480 --> 00:11:36,040 Speaker 1: then got my job with the town of Iliad driving 216 00:11:36,080 --> 00:11:41,400 Speaker 1: a minibus transporting seniors. So, Uncle Kenny, if I can 217 00:11:41,440 --> 00:11:42,880 Speaker 1: ask you a little bit about kind of what does 218 00:11:42,920 --> 00:11:44,600 Speaker 1: it take to be a truck driver. I mean, I've 219 00:11:44,600 --> 00:11:47,000 Speaker 1: read some I've read some stories that Bloomberg has written, 220 00:11:47,040 --> 00:11:48,880 Speaker 1: some some other ones. It sounds like it's a really 221 00:11:48,880 --> 00:11:51,440 Speaker 1: tough job. It is a tough job. It's not an 222 00:11:51,440 --> 00:11:54,120 Speaker 1: easy job. It's not one that everybody's gonna like. You're 223 00:11:54,160 --> 00:11:56,240 Speaker 1: you're on the road all the time. I mean I 224 00:11:56,320 --> 00:12:01,400 Speaker 1: spent probably most of my career in twelve to fourteen 225 00:12:01,400 --> 00:12:04,440 Speaker 1: hour days every you know, five days a week, sometimes 226 00:12:04,559 --> 00:12:08,320 Speaker 1: even six days. And uh, you know, it's tough on 227 00:12:08,360 --> 00:12:10,880 Speaker 1: your back, it's tough on your on your home life. 228 00:12:11,559 --> 00:12:14,400 Speaker 1: It's uh, it's a very difficult job to do. You 229 00:12:14,440 --> 00:12:17,320 Speaker 1: have to constantly be a you're driving, you know, anybody 230 00:12:17,320 --> 00:12:19,960 Speaker 1: who drives, even to work knows that it can be 231 00:12:19,960 --> 00:12:23,120 Speaker 1: pretty stressful. You're doing this with a with a forty 232 00:12:23,200 --> 00:12:26,400 Speaker 1: eight thousand pound vehicle. You know that that splits in 233 00:12:26,400 --> 00:12:28,960 Speaker 1: the middle and can spin around if you don't if 234 00:12:28,960 --> 00:12:30,800 Speaker 1: you're not careful, and you've got people cutting you off 235 00:12:30,880 --> 00:12:34,640 Speaker 1: all day. So it's a very stressful, stressful job. How 236 00:12:34,679 --> 00:12:37,840 Speaker 1: did you how did you balance you know, that job 237 00:12:37,920 --> 00:12:41,439 Speaker 1: with you know the obviously had had two kids and 238 00:12:41,880 --> 00:12:44,439 Speaker 1: you know, taking care of them part of the time too. Well. 239 00:12:44,480 --> 00:12:46,640 Speaker 1: I was divorced when I was twenty one and a half, 240 00:12:46,679 --> 00:12:49,920 Speaker 1: so you know, but I did have I did see 241 00:12:50,000 --> 00:12:52,800 Speaker 1: my kids on weekends, and uh, yeah, it was tough. 242 00:12:52,840 --> 00:12:54,880 Speaker 1: I mean I was married the second time, and I 243 00:12:54,920 --> 00:12:58,520 Speaker 1: was married for twenty years, and uh, I think one 244 00:12:58,559 --> 00:13:00,800 Speaker 1: of the reasons I got divorced the second time was 245 00:13:00,800 --> 00:13:03,640 Speaker 1: because I was never home and uh, you know, I 246 00:13:03,679 --> 00:13:06,880 Speaker 1: was always you know, when I came home, I said, 247 00:13:06,880 --> 00:13:08,760 Speaker 1: come home at eight o'clock at night. I'd have to 248 00:13:08,760 --> 00:13:10,080 Speaker 1: go to sleep because I have to be back at 249 00:13:10,120 --> 00:13:14,440 Speaker 1: work at six the next morning. So it was it 250 00:13:14,480 --> 00:13:17,440 Speaker 1: affected my home life a real lot. The pay, Like 251 00:13:17,720 --> 00:13:19,600 Speaker 1: you know, I was listening to what you guys were saying, 252 00:13:19,679 --> 00:13:22,200 Speaker 1: and uh, I could tell you that I started as 253 00:13:22,240 --> 00:13:24,520 Speaker 1: a teamster. And now, when I started driving a truck 254 00:13:24,559 --> 00:13:26,960 Speaker 1: back in nineteen seventy two, you know, the pay was, 255 00:13:27,360 --> 00:13:30,600 Speaker 1: you know, on par with what most people were making 256 00:13:30,640 --> 00:13:33,600 Speaker 1: in in you know, in lower level jobs like that. 257 00:13:33,679 --> 00:13:36,000 Speaker 1: But when I when I became a teamster in the 258 00:13:36,840 --> 00:13:41,000 Speaker 1: night four, the pay scale was thirteen twenty three an hour. Now, 259 00:13:41,040 --> 00:13:43,720 Speaker 1: I worked for the same companies as a teamster for 260 00:13:43,760 --> 00:13:47,680 Speaker 1: twenty six years, and when I retired, my pay scale 261 00:13:47,720 --> 00:13:50,040 Speaker 1: was only up to twenty one dollars and changing out, 262 00:13:50,080 --> 00:13:53,040 Speaker 1: which means in twenty six years we are pay only 263 00:13:53,040 --> 00:13:55,480 Speaker 1: went up eight dollars an hour. Now, the way I 264 00:13:55,520 --> 00:13:57,640 Speaker 1: made up for that was by working only over time, 265 00:13:57,640 --> 00:14:00,720 Speaker 1: because luckily for me, being a teamster was an early job. 266 00:14:01,200 --> 00:14:03,600 Speaker 1: But this driver is that you know that like he 267 00:14:03,679 --> 00:14:05,679 Speaker 1: was saying twenty dollars an hour, you make it twenty 268 00:14:05,720 --> 00:14:07,839 Speaker 1: dollars an hour. And there's a lot of these trucking 269 00:14:07,880 --> 00:14:10,480 Speaker 1: companies that don't want to pay you when you have 270 00:14:10,559 --> 00:14:12,280 Speaker 1: to sit around. They don't want to pay you when 271 00:14:12,280 --> 00:14:15,160 Speaker 1: you when you're on layover. And so these guys are 272 00:14:15,160 --> 00:14:17,640 Speaker 1: working twenty four hours around the clock on the road 273 00:14:18,040 --> 00:14:20,640 Speaker 1: and really not really only getting paid for like maybe 274 00:14:20,640 --> 00:14:23,440 Speaker 1: ten of those hours. Are that teamsters as active in 275 00:14:23,440 --> 00:14:26,000 Speaker 1: the industry now as they work during your time. Well, 276 00:14:26,000 --> 00:14:31,280 Speaker 1: the teams have been decimated by by the regulation from UM. 277 00:14:31,320 --> 00:14:33,440 Speaker 1: When I first started driving, there was a hundred and 278 00:14:33,480 --> 00:14:36,840 Speaker 1: sixty two trucking companies teams to trucking companies, and we're 279 00:14:36,880 --> 00:14:38,720 Speaker 1: down to two now. One of them is a company 280 00:14:38,760 --> 00:14:41,040 Speaker 1: I worked for, a BF and the other one is 281 00:14:41,120 --> 00:14:44,040 Speaker 1: Yellow Roadway, which is a combination of two major companies 282 00:14:44,040 --> 00:14:46,880 Speaker 1: that had to combine because they weren't making any money 283 00:14:47,120 --> 00:14:50,920 Speaker 1: and uh, you know, they can't find drivers anymore to 284 00:14:51,000 --> 00:14:53,440 Speaker 1: be teams. Is because the pension plans are going into 285 00:14:53,480 --> 00:14:57,160 Speaker 1: the toilet. And uh, you know, my pension in particular 286 00:14:57,600 --> 00:15:01,360 Speaker 1: has been cut by nineteen hundred dollars because they because 287 00:15:01,400 --> 00:15:05,040 Speaker 1: the pension is going broke. So even those were the 288 00:15:05,080 --> 00:15:09,400 Speaker 1: best jobs in trucking, and those jobs stink. So you 289 00:15:09,440 --> 00:15:11,720 Speaker 1: can only imagine, you know, working for companies like J 290 00:15:11,880 --> 00:15:14,000 Speaker 1: Beyond that want to work you like a dog and 291 00:15:14,040 --> 00:15:16,360 Speaker 1: not pay you anything for for your for your efforts, 292 00:15:16,640 --> 00:15:18,840 Speaker 1: how hard it is for them to find drivers. If 293 00:15:18,880 --> 00:15:21,320 Speaker 1: I can jump in. That just doesn't seem like a 294 00:15:21,360 --> 00:15:23,320 Speaker 1: long term model, you know. I mean we were talking 295 00:15:23,320 --> 00:15:25,960 Speaker 1: about how you know you can't these people are having 296 00:15:26,000 --> 00:15:28,280 Speaker 1: a hard time hiring drivers. I mean, you've been in 297 00:15:28,320 --> 00:15:31,120 Speaker 1: the industry for quite a long time, you know it intimately. 298 00:15:31,480 --> 00:15:33,400 Speaker 1: I mean that just seems like a kick go on 299 00:15:33,520 --> 00:15:35,360 Speaker 1: for very long. It's just not a not a good 300 00:15:35,360 --> 00:15:37,760 Speaker 1: long term model. It's not it's not a good long 301 00:15:37,880 --> 00:15:40,520 Speaker 1: term model, and it's not good for you know. I mean, 302 00:15:41,120 --> 00:15:43,760 Speaker 1: if if all things were equal, you know, and you 303 00:15:43,800 --> 00:15:45,680 Speaker 1: worked an eight hour day and you made enough money 304 00:15:45,760 --> 00:15:49,120 Speaker 1: to pay your bills, um, it would be a decent job. 305 00:15:49,320 --> 00:15:51,320 Speaker 1: Because you're out there, you're out on the road. I mean, 306 00:15:51,320 --> 00:15:53,000 Speaker 1: there is the freedom. One of the reasons I drove 307 00:15:53,000 --> 00:15:55,480 Speaker 1: a truck is because I don't like sitting behind the desk. 308 00:15:56,000 --> 00:15:58,120 Speaker 1: But you know, and there is that freedom. But you know, 309 00:15:58,160 --> 00:15:59,920 Speaker 1: you're not working an eight hour that you're working a 310 00:16:00,240 --> 00:16:03,800 Speaker 1: call up the fourteen hour day and you're and and 311 00:16:03,840 --> 00:16:08,160 Speaker 1: it's very hard work. So it's a poor model to 312 00:16:08,240 --> 00:16:10,520 Speaker 1: begin with. It's always been a poor and to drive 313 00:16:10,520 --> 00:16:13,360 Speaker 1: a truck. You know where the old wagon train people 314 00:16:13,400 --> 00:16:16,760 Speaker 1: again know peas where a horse uh where you know 315 00:16:17,160 --> 00:16:19,640 Speaker 1: they control the horses on on a horse and wagon. 316 00:16:19,680 --> 00:16:24,320 Speaker 1: You know, so we're still there. So it is it 317 00:16:24,440 --> 00:16:27,240 Speaker 1: is one of these jobs that you know, people can 318 00:16:27,480 --> 00:16:29,640 Speaker 1: can do. It's not it's not it's not a job 319 00:16:29,680 --> 00:16:33,640 Speaker 1: that's going to move to China or overseas or somewhere else. 320 00:16:33,640 --> 00:16:36,960 Speaker 1: They're they're going to need truckers to move goods around 321 00:16:36,960 --> 00:16:40,520 Speaker 1: the country no matter what. You know, it's probably gonna 322 00:16:40,560 --> 00:16:44,440 Speaker 1: take a long time to become truly automated. I mean, 323 00:16:44,480 --> 00:16:47,960 Speaker 1: why why can't the Why do you think wages are 324 00:16:47,960 --> 00:16:50,400 Speaker 1: going to stay low? Why won't they go up? Well, 325 00:16:50,440 --> 00:16:55,640 Speaker 1: because because there's competition from all corners, you know, the deregulation. 326 00:16:56,120 --> 00:16:58,920 Speaker 1: Anybody and everybody opens up a trucking company. You know, 327 00:16:59,040 --> 00:17:01,320 Speaker 1: the reason why somebody drug companies went out of business 328 00:17:01,400 --> 00:17:04,160 Speaker 1: was because, uh, you know, when when there was when 329 00:17:04,200 --> 00:17:06,959 Speaker 1: trucking was regulated, they could control their prices and they 330 00:17:06,960 --> 00:17:08,840 Speaker 1: could you know, and they were making a decent living there. 331 00:17:09,280 --> 00:17:12,000 Speaker 1: Prices were set and you know, shippers could not take 332 00:17:12,040 --> 00:17:14,639 Speaker 1: advantage of one truck and company over another because there 333 00:17:14,680 --> 00:17:16,679 Speaker 1: were there was you know, lanes that they had to 334 00:17:16,720 --> 00:17:19,440 Speaker 1: deal with. But now it's you know, whoever gives them 335 00:17:19,440 --> 00:17:22,119 Speaker 1: the best price, and there's you know, there's there's like 336 00:17:22,240 --> 00:17:24,679 Speaker 1: in any other industry, there's dogs out there. They are 337 00:17:24,720 --> 00:17:26,840 Speaker 1: going to go in there and undercut whoever they can 338 00:17:26,920 --> 00:17:30,080 Speaker 1: undercutt and uh, you know something, and it doesn't seem 339 00:17:30,119 --> 00:17:32,640 Speaker 1: to be that service matters as much as how much 340 00:17:32,640 --> 00:17:35,320 Speaker 1: the pain for the shipping. Kenny, thanks so much for 341 00:17:35,400 --> 00:17:37,359 Speaker 1: joining us. We're gonna leave it there. Did you want 342 00:17:37,400 --> 00:17:39,200 Speaker 1: to get in a plug for your own radio show? 343 00:17:39,359 --> 00:17:41,600 Speaker 1: A show? I do a Blue Show on w USB 344 00:17:41,760 --> 00:17:46,040 Speaker 1: ninety one FM on Long Island and at Stonybrook University 345 00:17:46,480 --> 00:17:49,960 Speaker 1: every other week from ten pm to midnight. It's a 346 00:17:50,000 --> 00:17:53,040 Speaker 1: great show. I do my friend Jovi, and uh you 347 00:17:53,080 --> 00:17:55,720 Speaker 1: can listen to it online for anybody who's listening around 348 00:17:55,720 --> 00:17:59,160 Speaker 1: the country or around the world at w USB dot fm. 349 00:17:59,240 --> 00:18:01,959 Speaker 1: It's streams. So yeah, thanks for letting me do that 350 00:18:02,040 --> 00:18:04,800 Speaker 1: because I really love that. That's my that's my passion. Now, 351 00:18:05,800 --> 00:18:09,480 Speaker 1: all right, I'm gonna check that out. Thank you, Thanks well. 352 00:18:09,680 --> 00:18:12,040 Speaker 1: Benchmark will be back next week and until then, you 353 00:18:12,040 --> 00:18:15,280 Speaker 1: can find us on the Bloomberg Terminal and Bloomberg dot com, 354 00:18:15,320 --> 00:18:18,520 Speaker 1: as well as on iTunes, pocket casts, and Stitcher. While 355 00:18:18,560 --> 00:18:20,520 Speaker 1: you're there, take a minute to rate and review the 356 00:18:20,560 --> 00:18:23,359 Speaker 1: show so more listeners can find us and let us 357 00:18:23,400 --> 00:18:24,960 Speaker 1: know what you thought of the show. You can talk 358 00:18:25,000 --> 00:18:26,720 Speaker 1: to us and follow us on Twitter, and you can 359 00:18:26,760 --> 00:18:29,840 Speaker 1: find Scott at Scott Landman. You can find me at 360 00:18:29,840 --> 00:18:32,439 Speaker 1: by Keate Smith, and you can find our guest Justin 361 00:18:32,600 --> 00:18:35,439 Speaker 1: at a Fox just and my uncle is also on 362 00:18:35,480 --> 00:18:40,120 Speaker 1: Twitter at at blues Lover three one two Thanks a lot. 363 00:18:47,320 --> 00:18:50,200 Speaker 1: Brought to you by Bank of America. Meryll Lynch seeing 364 00:18:50,200 --> 00:18:52,680 Speaker 1: what others have seen, but I'm covering what others may not. 365 00:18:53,080 --> 00:18:56,760 Speaker 1: Global Research that helps you Harness disruption voted top global 366 00:18:56,800 --> 00:19:00,080 Speaker 1: research from five years running. Merrill Lynch, Piers, Spender and 367 00:19:00,200 --> 00:19:01,240 Speaker 1: Smith Incorporated