1 00:00:00,080 --> 00:00:04,760 Speaker 1: We can't continue to allow China to rape our country, 2 00:00:04,760 --> 00:00:08,160 Speaker 1: and that's what they're doing. It's the greatest theft in 3 00:00:08,200 --> 00:00:11,000 Speaker 1: the history of the world. That's Donald Trump speaking at 4 00:00:11,000 --> 00:00:14,200 Speaker 1: a rally almost a year ago. His message that China 5 00:00:14,320 --> 00:00:18,400 Speaker 1: stole American jobs by taking away factories and using unfair 6 00:00:18,440 --> 00:00:22,400 Speaker 1: trade practices resonated so well that it helped deliver a 7 00:00:22,440 --> 00:00:27,480 Speaker 1: surprise election victory. In fact, China has provided a lifeline 8 00:00:27,560 --> 00:00:32,520 Speaker 1: to manufacturing in some of America's hardest hit cities. Take Moraine, Ohio, 9 00:00:32,880 --> 00:00:36,199 Speaker 1: where a Chinese company took over a closed General Motors 10 00:00:36,240 --> 00:00:39,400 Speaker 1: plant and turned it into a center for windshield glass. 11 00:00:40,000 --> 00:00:42,800 Speaker 1: As Trump prepares this week for his first ever meeting 12 00:00:42,880 --> 00:00:46,640 Speaker 1: with Chinese President shi Jinping, we're taking a closer look 13 00:00:46,640 --> 00:00:50,520 Speaker 1: today at the relationship between the world's two largest economies. 14 00:00:50,880 --> 00:00:53,559 Speaker 1: The truth is that it's a lot more complicated than 15 00:00:53,600 --> 00:01:07,800 Speaker 1: you might suspect. Welcome to Benchmark. I'm Scott Landman. Joining 16 00:01:07,840 --> 00:01:10,720 Speaker 1: me as a guest co host is my colleague Andrew Mayetta, 17 00:01:11,000 --> 00:01:15,080 Speaker 1: Bloomberg reporter here in Washington who covers international economics and trade. 18 00:01:15,440 --> 00:01:18,120 Speaker 1: Will also speak with a local official in Moraine who 19 00:01:18,120 --> 00:01:21,319 Speaker 1: helped bring in the Chinese investment. Then we'll talk with 20 00:01:21,360 --> 00:01:25,000 Speaker 1: an economics professor in Ohio to give us some more perspective. 21 00:01:25,640 --> 00:01:29,840 Speaker 1: But first, Andrew, thanks for being here, Thanks for having me. So, Andrew, 22 00:01:29,920 --> 00:01:33,280 Speaker 1: you visited this plant, the fu Yea Glass factory last 23 00:01:33,319 --> 00:01:35,840 Speaker 1: year and wrote about it. What did you find there? 24 00:01:36,360 --> 00:01:41,000 Speaker 1: It was really interesting, as you mentioned that plant had 25 00:01:41,080 --> 00:01:44,800 Speaker 1: previously been empty for empty for several years. It was 26 00:01:44,880 --> 00:01:49,640 Speaker 1: previously a GM plant that produced Chevy trailblazers, I believe, 27 00:01:50,760 --> 00:01:54,800 Speaker 1: but it was closed in GM's restructure and following the 28 00:01:54,840 --> 00:01:58,600 Speaker 1: financial crisis, and a Chinese company called fu Yeau Glass 29 00:01:59,080 --> 00:02:02,840 Speaker 1: came in and at that facility and has since been 30 00:02:02,920 --> 00:02:07,800 Speaker 1: raped ramping up hiring. They make UH car windshields there, 31 00:02:08,280 --> 00:02:11,919 Speaker 1: um and virtually everyone that I talked to in town 32 00:02:11,960 --> 00:02:13,400 Speaker 1: thought it was a good thing. I mean, what a 33 00:02:13,400 --> 00:02:17,000 Speaker 1: lot of people said was, you know, those jobs don't 34 00:02:17,040 --> 00:02:19,680 Speaker 1: pay quite as well as the jobs at GM, but 35 00:02:19,760 --> 00:02:22,239 Speaker 1: it's better than an empty plant. That was the kind 36 00:02:22,240 --> 00:02:25,200 Speaker 1: of overwhelming message that I got from people. And you know, 37 00:02:25,280 --> 00:02:29,840 Speaker 1: I think it's an interesting illustration of the complexities of 38 00:02:29,919 --> 00:02:34,160 Speaker 1: Chinese investment in the US. I mean, as on one hand, 39 00:02:34,280 --> 00:02:40,560 Speaker 1: you have politicians on campaign trails kind of vilifying Chinese investment. 40 00:02:40,600 --> 00:02:44,440 Speaker 1: On the other hand, you have places like Moreno, Ohio 41 00:02:44,440 --> 00:02:48,640 Speaker 1: looking for capital, looking for investors in in their economies. Yeah, 42 00:02:48,680 --> 00:02:51,040 Speaker 1: it really was a contrast when we are hearing all 43 00:02:51,040 --> 00:02:53,680 Speaker 1: this rhetoric during the campaign season, not just from Trump, 44 00:02:53,720 --> 00:02:55,680 Speaker 1: but you know also from some of it from the 45 00:02:55,760 --> 00:02:59,720 Speaker 1: Democratic side that uh, you know, critical of China and 46 00:02:59,760 --> 00:03:02,000 Speaker 1: the and the need to level the playing field, bring 47 00:03:02,000 --> 00:03:06,600 Speaker 1: manufacturing jobs back and so forth. Well, let's find out 48 00:03:06,639 --> 00:03:10,000 Speaker 1: more from somebody who's been closely involved in this issue. 49 00:03:10,639 --> 00:03:14,919 Speaker 1: Michael Davis, director of Economic Development for the City of Moraine, 50 00:03:15,280 --> 00:03:18,000 Speaker 1: is joining us on the phone now. Mike, thanks for 51 00:03:18,080 --> 00:03:22,560 Speaker 1: being with us today. You're welcome. I'm happy to join in. Mike. 52 00:03:22,600 --> 00:03:25,519 Speaker 1: Can you tell us a little bit first about the 53 00:03:25,639 --> 00:03:29,560 Speaker 1: history of manufacturing in your area and what's happened to 54 00:03:29,680 --> 00:03:33,079 Speaker 1: it over the past years, kind of setting the scene 55 00:03:33,160 --> 00:03:38,000 Speaker 1: for us. Sure, we we have always had kind of 56 00:03:38,040 --> 00:03:41,760 Speaker 1: a significant presence of manufacturing in some respects. You could 57 00:03:41,760 --> 00:03:45,040 Speaker 1: have called us a GM town. We are a entering 58 00:03:45,120 --> 00:03:50,400 Speaker 1: suburb of Dayton, Ohio, and uh at one time in 59 00:03:50,440 --> 00:03:54,840 Speaker 1: the seventies and eighties, GM was probably employing when you 60 00:03:54,880 --> 00:03:58,160 Speaker 1: include their suppliers upwards the twenty people in the city. 61 00:03:59,200 --> 00:04:04,920 Speaker 1: UM as years went by and various consolidations and UM everything. 62 00:04:05,000 --> 00:04:07,600 Speaker 1: As we pushed into the two thousand's, GM was still 63 00:04:07,640 --> 00:04:11,920 Speaker 1: employing about four thousand people, and it was very prevalent 64 00:04:12,000 --> 00:04:17,640 Speaker 1: operation manufacturing, manufacturing operation in our community. And then in 65 00:04:17,680 --> 00:04:21,600 Speaker 1: two thousand nine is when we were hit with the 66 00:04:21,680 --> 00:04:26,440 Speaker 1: closure of the plant. UM leading to that at the 67 00:04:26,520 --> 00:04:30,240 Speaker 1: time of their closure, they were building I believe his reference, 68 00:04:30,320 --> 00:04:36,080 Speaker 1: the Chevy Trailblazer, the GMC envoy, UM, the SOB nine X, 69 00:04:36,160 --> 00:04:40,320 Speaker 1: and a couple of others or utility vehicles. And so 70 00:04:40,480 --> 00:04:43,080 Speaker 1: how did the deal with FU Yeah, then come about 71 00:04:43,120 --> 00:04:45,760 Speaker 1: after the closure and how did how did you help 72 00:04:45,800 --> 00:04:48,760 Speaker 1: make that happen? When when some of the economic downturn happened, 73 00:04:48,800 --> 00:04:51,200 Speaker 1: you could kind of say that Moraine was the microcosm 74 00:04:51,240 --> 00:04:54,440 Speaker 1: of the national economy. We UM, really all you had 75 00:04:54,480 --> 00:04:56,200 Speaker 1: to do was take a look at Moraine and see 76 00:04:56,240 --> 00:04:59,200 Speaker 1: what was going on across the entire country. And so 77 00:04:59,240 --> 00:05:01,320 Speaker 1: the first thing that we did is we really we 78 00:05:01,360 --> 00:05:04,640 Speaker 1: went out to try to understand maybe what other communities 79 00:05:04,680 --> 00:05:07,600 Speaker 1: across the country had done or had experience when they 80 00:05:07,640 --> 00:05:11,400 Speaker 1: had a large manufacturer closed. And really what we did 81 00:05:11,440 --> 00:05:13,719 Speaker 1: is we said, Okay, we have a talented workforce, we 82 00:05:13,800 --> 00:05:18,600 Speaker 1: have over four million square feet of existing manufacturing space. UM. 83 00:05:18,640 --> 00:05:21,080 Speaker 1: You know, instead of harping on these as negatives, let's 84 00:05:21,080 --> 00:05:25,120 Speaker 1: turn around and use these as resources and positives to say, 85 00:05:25,160 --> 00:05:26,880 Speaker 1: you know, this is why you need to come here. 86 00:05:26,960 --> 00:05:30,400 Speaker 1: We we have the skill, labor already in place, and 87 00:05:30,720 --> 00:05:34,160 Speaker 1: we've got space that UM is located in good proximity 88 00:05:34,160 --> 00:05:38,599 Speaker 1: on Interstate seventy and reasonable and cost and had received 89 00:05:38,600 --> 00:05:41,279 Speaker 1: a lot of updates over the years as general motors 90 00:05:41,320 --> 00:05:44,039 Speaker 1: continue to invest money into the facility, so it was 91 00:05:44,080 --> 00:05:48,760 Speaker 1: in relatively good shape UM. Based upon that, we just 92 00:05:48,839 --> 00:05:52,159 Speaker 1: continued to try to increase the visibility working with the 93 00:05:52,200 --> 00:05:58,120 Speaker 1: State Ohio, and we had finally in had received kind 94 00:05:58,160 --> 00:06:01,800 Speaker 1: of a state uh so I selection inquiry for a 95 00:06:01,920 --> 00:06:05,560 Speaker 1: project called Projects Southbound, and that's really what led to 96 00:06:06,160 --> 00:06:10,080 Speaker 1: the initial communication and the startup and trying to attract 97 00:06:10,320 --> 00:06:13,159 Speaker 1: what would ultimately be if we a and did you 98 00:06:13,200 --> 00:06:16,360 Speaker 1: have were their incentives involved that either Moraine or your 99 00:06:16,360 --> 00:06:19,960 Speaker 1: county or the state provided uh all that this was 100 00:06:20,000 --> 00:06:23,400 Speaker 1: definitely a collaborative effort. A lot of partnership went into this, 101 00:06:23,520 --> 00:06:26,680 Speaker 1: and there there were incentives at the state level, and 102 00:06:26,720 --> 00:06:29,280 Speaker 1: then we had to you know, initially, I think there 103 00:06:29,320 --> 00:06:31,840 Speaker 1: was about five to seven states that were competing for 104 00:06:31,880 --> 00:06:34,600 Speaker 1: this effort, and there was more than one site, even 105 00:06:34,640 --> 00:06:37,600 Speaker 1: in the state of Ohio. So the state and syentioms 106 00:06:37,680 --> 00:06:41,320 Speaker 1: were based on those final two sites in Ohio, and 107 00:06:41,400 --> 00:06:44,600 Speaker 1: we were still competing against Michigan as well and h 108 00:06:44,720 --> 00:06:48,039 Speaker 1: ultimately Montgomery County. The city of Moraine had to step 109 00:06:48,080 --> 00:06:51,080 Speaker 1: in and provide additional assistance to kind of separate ourselves 110 00:06:51,160 --> 00:06:54,200 Speaker 1: out from the other competing site that was that was 111 00:06:54,240 --> 00:06:57,440 Speaker 1: in Ohio. Michael, what would you say has been the 112 00:06:57,480 --> 00:07:00,560 Speaker 1: effect on the community, On the local community of Moraine. 113 00:07:00,920 --> 00:07:02,680 Speaker 1: I mean, as I mentioned, a lot of folks that 114 00:07:02,720 --> 00:07:05,120 Speaker 1: I talked to said they thought it was a good 115 00:07:05,160 --> 00:07:07,760 Speaker 1: thing that the Chinese were coming in and investing in 116 00:07:07,839 --> 00:07:09,960 Speaker 1: that plan. But you know, from time to time I 117 00:07:09,960 --> 00:07:13,400 Speaker 1: did run into people and said, hey, look sure sure 118 00:07:13,600 --> 00:07:17,240 Speaker 1: look back wistfully on those on those well planing uh 119 00:07:17,520 --> 00:07:20,480 Speaker 1: GM jobs with the defined benefit pension plans. I mean, 120 00:07:21,320 --> 00:07:23,920 Speaker 1: what would you say the overall effect has been. I 121 00:07:23,960 --> 00:07:26,600 Speaker 1: think the overall effect has been positive from the standpoint 122 00:07:26,600 --> 00:07:29,480 Speaker 1: that when we did the initial attraction it was going 123 00:07:29,520 --> 00:07:32,040 Speaker 1: to be a two hundred million dollar investment in about 124 00:07:32,080 --> 00:07:36,280 Speaker 1: eight hundred jobs, and after working with the Chairman and 125 00:07:36,480 --> 00:07:40,160 Speaker 1: his staff and understanding the success they're gonna happen here, 126 00:07:40,200 --> 00:07:44,640 Speaker 1: the acquisition of a glassmaking facility in mal Zion, which 127 00:07:44,680 --> 00:07:49,480 Speaker 1: is outside of Chicago in Illinois, and that proximity really 128 00:07:49,560 --> 00:07:52,560 Speaker 1: encouraged the chairman to take a look at both the 129 00:07:52,600 --> 00:07:55,040 Speaker 1: production for the new vehicle glass but as well as 130 00:07:55,080 --> 00:07:59,560 Speaker 1: the aftermarket, and then encouraged the second investment announcement literally 131 00:07:59,720 --> 00:08:03,440 Speaker 1: year later. The first was in January fourteen, the follow 132 00:08:03,520 --> 00:08:07,760 Speaker 1: up was in January fift and so what ultimately has 133 00:08:07,800 --> 00:08:10,160 Speaker 1: happened is we now have two thousand folks that are 134 00:08:10,160 --> 00:08:13,760 Speaker 1: employed in the facility. There's been six hundred million dollars 135 00:08:13,760 --> 00:08:18,000 Speaker 1: pumped into it, and that investment continues to increase um. 136 00:08:18,160 --> 00:08:21,000 Speaker 1: What we've seen the overall impact on the community is that, 137 00:08:21,200 --> 00:08:23,960 Speaker 1: you know, Moraine took a hit that was well over 138 00:08:25,360 --> 00:08:28,040 Speaker 1: of our operating budget, and we've now been able to 139 00:08:28,600 --> 00:08:32,000 Speaker 1: really kind of infuse some of those dollars from this 140 00:08:32,120 --> 00:08:37,160 Speaker 1: investment back in the community with capital improvements, road infrastructure 141 00:08:38,280 --> 00:08:42,360 Speaker 1: and various things that are benefit to both are corporate 142 00:08:42,400 --> 00:08:45,079 Speaker 1: citizens and the folks who drive into the city every 143 00:08:45,160 --> 00:08:47,719 Speaker 1: day as well as our citizens who live here. Well, 144 00:08:47,760 --> 00:08:50,280 Speaker 1: that really sounds like it's been a net positive for 145 00:08:50,400 --> 00:08:54,680 Speaker 1: the community. But Mike, what about the political side of things? 146 00:08:54,720 --> 00:08:58,240 Speaker 1: That anger over China really touched a vein not only 147 00:08:58,280 --> 00:09:02,440 Speaker 1: in Ohio but across the country. Trump won the state 148 00:09:02,480 --> 00:09:05,640 Speaker 1: of Ohio by eight percentage points, which really was an 149 00:09:05,679 --> 00:09:10,000 Speaker 1: unexpectedly large margin. Do you think that people in your 150 00:09:10,040 --> 00:09:13,760 Speaker 1: area might have less anger towards China as a result 151 00:09:13,920 --> 00:09:17,400 Speaker 1: of this investment by Fuya? You know, that's probably kind 152 00:09:17,400 --> 00:09:19,640 Speaker 1: of hard to gauge. UM. I think a little more 153 00:09:19,640 --> 00:09:22,080 Speaker 1: time would be needed to to to understand that. What 154 00:09:22,120 --> 00:09:25,800 Speaker 1: I will say is that, um, this investment, you know, 155 00:09:25,960 --> 00:09:30,199 Speaker 1: kind of is relatively new, and even though it's substantial 156 00:09:30,200 --> 00:09:32,680 Speaker 1: and one of the largest direct foreign investments in the 157 00:09:32,679 --> 00:09:35,840 Speaker 1: country over the past ten years, UM, at the time, 158 00:09:35,960 --> 00:09:39,160 Speaker 1: I think that the entire presidential race and everything was ongoing, 159 00:09:39,760 --> 00:09:41,840 Speaker 1: was I don't think there was enough exposure on this 160 00:09:41,880 --> 00:09:44,720 Speaker 1: investment to where it was maybe as well known to 161 00:09:44,840 --> 00:09:47,680 Speaker 1: the national community and economy as it should have been. 162 00:09:48,040 --> 00:09:52,480 Speaker 1: And I also think that Chairman Chow deserves a lot 163 00:09:52,480 --> 00:09:55,440 Speaker 1: of credit in really initiating such a large investment that 164 00:09:55,520 --> 00:09:58,920 Speaker 1: we believe and from what we're hearing is spurring other 165 00:09:59,120 --> 00:10:01,760 Speaker 1: folks to take a look and other Chinese companies to 166 00:10:01,800 --> 00:10:04,719 Speaker 1: take a look at investing here and realizing that they 167 00:10:04,720 --> 00:10:07,520 Speaker 1: can be successful. Yeah. Can you talk a little bit 168 00:10:07,559 --> 00:10:11,479 Speaker 1: more about what it's like to work with the Chinese investors? 169 00:10:11,520 --> 00:10:13,840 Speaker 1: I mean you talked about Chairman Chow, I mean I 170 00:10:13,880 --> 00:10:19,079 Speaker 1: interviewed him. How different was the actual experience on the 171 00:10:19,080 --> 00:10:23,320 Speaker 1: shop floor than what has perhaps depicted when people think about, 172 00:10:23,440 --> 00:10:29,520 Speaker 1: you know, what Chinese investors are like. I think, first, um, 173 00:10:29,559 --> 00:10:34,840 Speaker 1: my experience has been nothing but positive throughout the entire process. 174 00:10:34,960 --> 00:10:38,880 Speaker 1: They were very deliberate and understanding. But you know, you're 175 00:10:38,920 --> 00:10:44,120 Speaker 1: looking at this uh ginormous property with three acres and 176 00:10:44,280 --> 00:10:47,320 Speaker 1: you know, four million square feet, so they really got 177 00:10:47,360 --> 00:10:51,600 Speaker 1: down to the details to understand the operational cost uh 178 00:10:51,800 --> 00:10:54,480 Speaker 1: the utilities. You know, we we bring out, brought a 179 00:10:54,480 --> 00:10:57,760 Speaker 1: lot of partners in, and then we had to work 180 00:10:57,800 --> 00:11:00,040 Speaker 1: through the understanding of Okay, what can we do to 181 00:11:00,800 --> 00:11:05,920 Speaker 1: be cost competitive on all aspects utilities and workforce to 182 00:11:06,000 --> 00:11:09,720 Speaker 1: make this happen. Um, as far as you know, on 183 00:11:09,800 --> 00:11:14,160 Speaker 1: the on the workstop floor, it's my understanding that things 184 00:11:14,200 --> 00:11:17,480 Speaker 1: over there, they're ironing out you know, the maybe some 185 00:11:17,520 --> 00:11:19,960 Speaker 1: communication efforts, and there were also you know, in the 186 00:11:20,000 --> 00:11:26,520 Speaker 1: middle of this monster development and huge expenditure that there's 187 00:11:26,600 --> 00:11:29,360 Speaker 1: kind of a learning curve as they're pushing forward. UM. 188 00:11:30,960 --> 00:11:33,959 Speaker 1: You know, their commitment the actual acquisition and closing of 189 00:11:34,000 --> 00:11:38,160 Speaker 1: the property was in twenty in May. We're almost at 190 00:11:38,160 --> 00:11:42,079 Speaker 1: three years and they've invested again nearly six hundred million dollars. 191 00:11:42,440 --> 00:11:45,080 Speaker 1: They are up and running, they're employing two thousand people, 192 00:11:45,840 --> 00:11:49,040 Speaker 1: and uh, you know, the hope is that in eighteen 193 00:11:49,120 --> 00:11:52,280 Speaker 1: they actually be turning a profit. And in that process, 194 00:11:52,320 --> 00:11:56,440 Speaker 1: you know, there there there's been two editions of over 195 00:11:56,480 --> 00:12:00,440 Speaker 1: two thousand square feet that's been added, and there has 196 00:12:00,480 --> 00:12:03,880 Speaker 1: also been the leasing of the remaining portion of the 197 00:12:03,920 --> 00:12:07,439 Speaker 1: GM facility that was divided out, which I think they're 198 00:12:07,440 --> 00:12:10,520 Speaker 1: releasing about another two d and sixty thousand square feet there. 199 00:12:10,800 --> 00:12:13,880 Speaker 1: So yeah, i'd say there's been some growing pains in 200 00:12:13,960 --> 00:12:17,280 Speaker 1: respect to UM understanding what they initially we're going to 201 00:12:17,360 --> 00:12:21,040 Speaker 1: need and where they are now. As far as you know, 202 00:12:21,240 --> 00:12:25,360 Speaker 1: a labor on the manufacturing floor, I'm not really able 203 00:12:25,400 --> 00:12:28,079 Speaker 1: to comment on that. I do know that interviews are 204 00:12:28,080 --> 00:12:30,840 Speaker 1: held here often and most people are very excited that 205 00:12:30,880 --> 00:12:34,880 Speaker 1: they're here and happy to to be an employee of 206 00:12:34,880 --> 00:12:38,120 Speaker 1: of who you one last question before we wrap up, Mike, 207 00:12:38,880 --> 00:12:42,320 Speaker 1: should President Trump come and see this factory in Moraine? 208 00:12:42,320 --> 00:12:44,840 Speaker 1: Have you invited him to come out there? I what 209 00:12:44,960 --> 00:12:47,400 Speaker 1: I can tell you is in October of last year 210 00:12:47,600 --> 00:12:49,920 Speaker 1: there was a grand opening. I know there were a 211 00:12:50,000 --> 00:12:53,520 Speaker 1: lot of Chinese dignitaries that were here, and there were 212 00:12:53,520 --> 00:12:56,280 Speaker 1: a lot of folks from Washington, d C. That we're invited, 213 00:12:56,679 --> 00:13:00,320 Speaker 1: and several of our congressmen also attended. I do not 214 00:13:00,480 --> 00:13:04,959 Speaker 1: know at that time if whether President Obama or Hillary 215 00:13:05,040 --> 00:13:09,360 Speaker 1: Clinton or Donald Trump were invited to that UM. What 216 00:13:09,480 --> 00:13:11,760 Speaker 1: I would say is that if you want to showcase 217 00:13:11,800 --> 00:13:17,080 Speaker 1: across the nation UM a beautiful direct foreign investment that 218 00:13:17,160 --> 00:13:21,040 Speaker 1: has proven to be tremendously successful and is continuing to grow. 219 00:13:21,160 --> 00:13:24,720 Speaker 1: I think I think anybody UM they would like to 220 00:13:24,720 --> 00:13:27,199 Speaker 1: see that replicated across the country should come and take 221 00:13:27,240 --> 00:13:30,840 Speaker 1: a look. And that train whistle sounds like it's time 222 00:13:30,880 --> 00:13:33,760 Speaker 1: to wrap up here. Mike, thanks so much for taking 223 00:13:33,760 --> 00:13:43,559 Speaker 1: the time to speak with us today. You're welcome. Now 224 00:13:43,640 --> 00:13:47,680 Speaker 1: for some broader perspective, let's go to Susan Helper. She 225 00:13:47,840 --> 00:13:51,760 Speaker 1: has been an economics professor at Case Western Reserve University 226 00:13:51,840 --> 00:13:55,640 Speaker 1: in Cleveland for twenty years, and also recently served as 227 00:13:55,760 --> 00:13:59,360 Speaker 1: chief economist at the U S Commerce Department. Her research 228 00:13:59,400 --> 00:14:04,000 Speaker 1: has focused on how to revitalize US manufacturing. Sue, thanks 229 00:14:04,080 --> 00:14:07,679 Speaker 1: for being with us today. Thank you. Now, we've been 230 00:14:07,840 --> 00:14:11,040 Speaker 1: talking about the fu y Out glass factory in Moraine, 231 00:14:11,120 --> 00:14:14,160 Speaker 1: hearing the story about that. How would you sum up 232 00:14:14,200 --> 00:14:18,240 Speaker 1: the bigger picture with manufacturing in Ohio and across the 233 00:14:18,320 --> 00:14:24,000 Speaker 1: United States in recent years? So across the US, um 234 00:14:24,160 --> 00:14:27,840 Speaker 1: we've seen since between about nineteen sixty and about two 235 00:14:27,840 --> 00:14:32,600 Speaker 1: thousand UM there were between fifteen and seventeen million manufacturing 236 00:14:32,680 --> 00:14:36,000 Speaker 1: jobs and just sort of fluctuated regularly with the business cycle. 237 00:14:37,080 --> 00:14:40,160 Speaker 1: Starting in two thousand, there was this historic decline. We 238 00:14:40,280 --> 00:14:44,000 Speaker 1: lost of manufacturing jobs between two thousand and two thousand 239 00:14:44,040 --> 00:14:47,680 Speaker 1: and ten, and then about eight hundred thousand of those 240 00:14:48,200 --> 00:14:53,600 Speaker 1: came back or have come back since two thousand and then. 241 00:14:53,680 --> 00:14:58,360 Speaker 1: It's been kind of stable since then. In Ohio is 242 00:14:58,640 --> 00:15:03,000 Speaker 1: part of that. Pick sure, there's been a general move 243 00:15:03,240 --> 00:15:08,280 Speaker 1: of manufacturing both out of cities and out of the North, 244 00:15:09,160 --> 00:15:14,960 Speaker 1: and so existing cities manufacturing heavy cities like Cleveland and 245 00:15:15,240 --> 00:15:19,440 Speaker 1: Dayton and Toledo have been hurt a lot um the 246 00:15:19,560 --> 00:15:24,880 Speaker 1: suburbs less so of those cities, But overall, I think 247 00:15:24,920 --> 00:15:29,280 Speaker 1: the manufacturing employment in Ohio has been slightly worse than 248 00:15:29,360 --> 00:15:32,520 Speaker 1: those national trends that I've stated. So, so when you 249 00:15:32,640 --> 00:15:35,920 Speaker 1: talk about the decline of those manufacturing jobs, both in 250 00:15:35,960 --> 00:15:39,040 Speaker 1: Ohio and across the nation, how much of a villain 251 00:15:39,160 --> 00:15:43,320 Speaker 1: has China been in that decline? Well, this is quite 252 00:15:43,360 --> 00:15:49,120 Speaker 1: a contentious topic. I think that the best research has 253 00:15:49,160 --> 00:15:52,920 Speaker 1: been done by David Otter of m I T and 254 00:15:53,000 --> 00:15:59,120 Speaker 1: colleagues Gordon Hanson and David Dorne, and they've found um 255 00:15:59,160 --> 00:16:02,720 Speaker 1: about twenties I percent of this decline that I mentioned 256 00:16:02,760 --> 00:16:07,160 Speaker 1: in manufacturing overall can be attributed to the rise of China. 257 00:16:08,600 --> 00:16:11,000 Speaker 1: There's a couple of other studies that find using a 258 00:16:11,040 --> 00:16:16,440 Speaker 1: different method, that find a similar decline. There's these studies 259 00:16:16,480 --> 00:16:18,720 Speaker 1: have been challenged, but but I think that that that 260 00:16:18,960 --> 00:16:21,640 Speaker 1: it's the auditor enhancing has filled the gold standards, so 261 00:16:21,680 --> 00:16:25,120 Speaker 1: it's it's a significant a part of the decline is 262 00:16:25,200 --> 00:16:27,800 Speaker 1: due to China. See what do you make of the 263 00:16:27,960 --> 00:16:32,720 Speaker 1: argument that President Trump has made as president on the 264 00:16:32,800 --> 00:16:37,320 Speaker 1: campaign trail that he can bring the jobs back to America, 265 00:16:37,680 --> 00:16:41,480 Speaker 1: based on your understanding of how the manufacturing sector works, 266 00:16:42,200 --> 00:16:46,400 Speaker 1: the history of the sector, how realistic is that? So 267 00:16:46,480 --> 00:16:50,240 Speaker 1: I think the jobs could be brought back. I'm not 268 00:16:50,320 --> 00:16:54,120 Speaker 1: sure that any of the policies that Trump has announced 269 00:16:54,160 --> 00:16:57,920 Speaker 1: so far as the administration, you know, would be sufficient 270 00:16:57,960 --> 00:17:01,239 Speaker 1: to do that. But those are two very different questions. 271 00:17:02,360 --> 00:17:04,920 Speaker 1: One of the things so, so eight hundred thousand jobs, 272 00:17:05,119 --> 00:17:07,800 Speaker 1: manufacturing jobs came back to the US between two thousand 273 00:17:07,800 --> 00:17:11,000 Speaker 1: and twenty fifteen, and there's some analysis done by the 274 00:17:11,040 --> 00:17:13,680 Speaker 1: White House Council of Economic Advisors at that time that 275 00:17:13,840 --> 00:17:16,639 Speaker 1: showed that a lot of that was because of a 276 00:17:16,680 --> 00:17:21,119 Speaker 1: structural change and the way companies thought about manufacturing in 277 00:17:21,119 --> 00:17:25,000 Speaker 1: the US, partly as a result of government programs, partly 278 00:17:25,040 --> 00:17:28,840 Speaker 1: as a result of changes abroad, and partly as a 279 00:17:28,880 --> 00:17:32,320 Speaker 1: result of companies doing a better job of understanding their 280 00:17:32,359 --> 00:17:35,520 Speaker 1: own costs. Um So, one of the things that companies 281 00:17:35,560 --> 00:17:39,520 Speaker 1: measure really well is their direct costs of factory labor. 282 00:17:40,160 --> 00:17:42,439 Speaker 1: And that's the one cost that falls when you go 283 00:17:42,480 --> 00:17:46,040 Speaker 1: to a company a country like China. Uh. Lots of 284 00:17:46,080 --> 00:17:48,560 Speaker 1: other costs rise, but they rise in ways that are 285 00:17:48,560 --> 00:17:51,399 Speaker 1: really hard to capture in existing accounting systems. You know, 286 00:17:51,480 --> 00:17:54,720 Speaker 1: so you may take longer to debug apart because you're 287 00:17:54,760 --> 00:17:59,359 Speaker 1: talking to somebody at different time zone in a different language. Um, 288 00:17:59,440 --> 00:18:01,920 Speaker 1: your engineer travel there, and then they lose a bunch 289 00:18:01,960 --> 00:18:03,840 Speaker 1: of time both there and on the way back to 290 00:18:04,000 --> 00:18:08,960 Speaker 1: the jet leg Uh, you have a lot longer lead time. UM. 291 00:18:09,080 --> 00:18:11,400 Speaker 1: These are things that have been very hard to value. 292 00:18:11,440 --> 00:18:15,680 Speaker 1: And Uh. Increasingly companies are understanding that those costs are 293 00:18:15,720 --> 00:18:19,040 Speaker 1: are actually quite high. And then the costs that they 294 00:18:19,080 --> 00:18:22,840 Speaker 1: do measure are also rising. So, particularly wages in China 295 00:18:22,880 --> 00:18:27,520 Speaker 1: are rising. Um. And so there's a bunch of factors 296 00:18:27,560 --> 00:18:30,000 Speaker 1: that are causing companies to come back. And then I 297 00:18:30,040 --> 00:18:33,320 Speaker 1: think under Obama there were some policies that that helped 298 00:18:33,440 --> 00:18:38,480 Speaker 1: with that, so creating of programs that facilitate the creation 299 00:18:38,480 --> 00:18:42,720 Speaker 1: and introduction of new manufacturing technologies, that helped train skilled 300 00:18:42,760 --> 00:18:47,680 Speaker 1: manufacturing workers, um, et cetera. Now you've mentioned that there 301 00:18:47,720 --> 00:18:52,280 Speaker 1: were eight hundred thousand manufacturing jobs that came back. Can 302 00:18:52,320 --> 00:18:54,880 Speaker 1: we get to a point where you restore the many 303 00:18:55,000 --> 00:18:58,000 Speaker 1: millions that have been lost over the last twenty years? 304 00:18:58,080 --> 00:19:01,400 Speaker 1: Is that even possible? It seems to be what President 305 00:19:01,440 --> 00:19:05,000 Speaker 1: Trump wants. And how much of a role could Chinese 306 00:19:05,040 --> 00:19:10,399 Speaker 1: investment such as the glass investment. How much can that 307 00:19:10,480 --> 00:19:14,359 Speaker 1: play a role in boosting these manufacturing jobs within the 308 00:19:14,400 --> 00:19:18,040 Speaker 1: borders of the United States. So yeah, so I think 309 00:19:18,040 --> 00:19:22,280 Speaker 1: it's unrealistic to bring back, uh, you know, five million jobs. 310 00:19:23,040 --> 00:19:25,439 Speaker 1: And I guess I occupy somewhat of an odd space 311 00:19:25,480 --> 00:19:27,879 Speaker 1: in this debate. You know, it seems like the polls 312 00:19:27,880 --> 00:19:31,920 Speaker 1: are either zero jobs can be brought back, um because 313 00:19:31,960 --> 00:19:34,600 Speaker 1: it's changed, or you know, they can all come back, 314 00:19:34,640 --> 00:19:36,400 Speaker 1: and I, you know, I think that some could come back. 315 00:19:36,440 --> 00:19:40,400 Speaker 1: I mean, so if you think about a country like Germany, uh, 316 00:19:40,720 --> 00:19:42,919 Speaker 1: wages are higher than they are in the US, and 317 00:19:42,960 --> 00:19:47,600 Speaker 1: they have of their GDP and manufacturing, we have about 318 00:19:47,640 --> 00:19:51,800 Speaker 1: twelve So you know, let's say we I don't think 319 00:19:51,840 --> 00:19:54,000 Speaker 1: it would be a stretch with good policy to say 320 00:19:54,040 --> 00:19:56,439 Speaker 1: we could get you know, fifteen to eighteen percent of 321 00:19:56,440 --> 00:20:00,920 Speaker 1: our GDP and manufacturing UM, and that would you raise 322 00:20:01,000 --> 00:20:04,679 Speaker 1: the percentage of employment. So manufacturing is more productive on average, 323 00:20:04,680 --> 00:20:07,720 Speaker 1: so it's about nine percent of employment is in manufacturing. 324 00:20:07,760 --> 00:20:10,720 Speaker 1: So you know, maybe we get to twelve percent of 325 00:20:10,760 --> 00:20:15,800 Speaker 1: employment or something in manufacturing. That's uh, that's a few 326 00:20:15,800 --> 00:20:21,200 Speaker 1: million jobs more than more than nothing, more than nothing, UM. 327 00:20:21,240 --> 00:20:24,399 Speaker 1: I guess I also care about the kind of jobs 328 00:20:24,440 --> 00:20:30,760 Speaker 1: that we bring back, and dangerous low wage jobs that 329 00:20:30,800 --> 00:20:34,920 Speaker 1: don't have much of a career path. You know, I'm 330 00:20:34,960 --> 00:20:37,640 Speaker 1: I don't see a reason to kind of prioritize those 331 00:20:37,720 --> 00:20:40,280 Speaker 1: jobs in whatever sector they're in. You know, the reason 332 00:20:40,359 --> 00:20:43,639 Speaker 1: that I'm interested in bringing back manufacturing jobs is that, 333 00:20:43,800 --> 00:20:47,880 Speaker 1: on average, manufacturing jobs pay more, have a career path 334 00:20:47,960 --> 00:20:51,879 Speaker 1: for people of a variety of educational backgrounds, tend to 335 00:20:51,920 --> 00:20:56,440 Speaker 1: be associated with innovation. Um. But if the manufacturing jobs 336 00:20:56,440 --> 00:20:58,840 Speaker 1: in question don't do those things, then you know, I 337 00:20:59,280 --> 00:21:02,480 Speaker 1: personally am less interested in policy that brings them back. So, Sue, 338 00:21:02,520 --> 00:21:05,040 Speaker 1: what do you think the American rust belt is going 339 00:21:05,080 --> 00:21:08,960 Speaker 1: to look like in fifteen to twenty years? Um? Kind 340 00:21:08,960 --> 00:21:10,720 Speaker 1: of described to us what you think it's going to 341 00:21:10,840 --> 00:21:13,639 Speaker 1: look like? And can you also weave in how you 342 00:21:13,680 --> 00:21:18,399 Speaker 1: see China fitting into that equation? So I guess I see, 343 00:21:19,440 --> 00:21:23,400 Speaker 1: you know, two paths, a good path and a bad path, 344 00:21:23,520 --> 00:21:25,840 Speaker 1: And to some extent you know you can see mixes, 345 00:21:26,560 --> 00:21:30,040 Speaker 1: but to some extent you know their trajectories and with 346 00:21:30,440 --> 00:21:36,240 Speaker 1: their own virtuous, ambitious cycles. UM. So I think the 347 00:21:37,000 --> 00:21:40,800 Speaker 1: positive path is well to step back. I think the 348 00:21:40,840 --> 00:21:44,760 Speaker 1: issues with American manufacturing have been that, you know, we're 349 00:21:44,800 --> 00:21:48,199 Speaker 1: kind of stuck in the middle. We're not innovative as 350 00:21:48,280 --> 00:21:53,360 Speaker 1: innovative as Germany, and we're not as low wages Mexico 351 00:21:53,480 --> 00:21:55,920 Speaker 1: or China. And you know, I personally would love to 352 00:21:55,920 --> 00:21:59,560 Speaker 1: see us move in a Germany direction. UM obviously not 353 00:21:59,640 --> 00:22:03,680 Speaker 1: imitate eat in Germany, but but adopting some of the 354 00:22:03,720 --> 00:22:06,479 Speaker 1: things that seem appropriate and giving them American twist. And 355 00:22:06,520 --> 00:22:07,879 Speaker 1: you know what could that could mean is there's a 356 00:22:07,960 --> 00:22:10,680 Speaker 1: lot of new technologies that are that are possible, So 357 00:22:11,520 --> 00:22:17,800 Speaker 1: things like robotics, things like additive manufacturing, uh, things like 358 00:22:18,280 --> 00:22:20,920 Speaker 1: what's called industry four point, where you have a add 359 00:22:20,920 --> 00:22:24,800 Speaker 1: a lot more data in the manufacturing UM and this, 360 00:22:25,080 --> 00:22:27,920 Speaker 1: you know, makes it possible. One way of adopting all 361 00:22:27,920 --> 00:22:31,159 Speaker 1: this technology is a way that complements workers and so 362 00:22:31,240 --> 00:22:34,320 Speaker 1: then workers have access to the data these sensors are 363 00:22:34,359 --> 00:22:37,920 Speaker 1: providing and they can themselves make tweaks the production process. 364 00:22:38,640 --> 00:22:42,720 Speaker 1: And so then you get UM workers that are extremely 365 00:22:42,760 --> 00:22:47,200 Speaker 1: productive and they're tied in both detail with detailed knowledge 366 00:22:47,200 --> 00:22:51,639 Speaker 1: to the shop floor, but also have an understanding of 367 00:22:51,680 --> 00:22:54,600 Speaker 1: what they're doing. The principles that can be promoted to 368 00:22:54,760 --> 00:22:57,760 Speaker 1: be supervisors or go on and get further education and 369 00:22:57,800 --> 00:23:02,040 Speaker 1: to say becoming engineers. UM. So this is not this 370 00:23:02,160 --> 00:23:05,320 Speaker 1: is somewhat like the path of a Siemens plant that 371 00:23:05,359 --> 00:23:08,240 Speaker 1: I visited in North Carolina, where they basically invest a 372 00:23:08,240 --> 00:23:12,440 Speaker 1: couple hundred thousand dollars in an apprentice uh and these 373 00:23:12,480 --> 00:23:16,280 Speaker 1: people when they complete the apprenticeship, they're making about sixty 374 00:23:16,680 --> 00:23:19,880 Speaker 1: dollars a year. UM. So these are you know, good jobs. 375 00:23:20,280 --> 00:23:22,040 Speaker 1: They had the option to go on and get further 376 00:23:22,080 --> 00:23:25,960 Speaker 1: school and become a degreed engineers. So that's you know, 377 00:23:26,000 --> 00:23:28,639 Speaker 1: I think a path that would be great for individual 378 00:23:28,680 --> 00:23:31,400 Speaker 1: workers be great for the economies in which they're employed. 379 00:23:31,960 --> 00:23:36,520 Speaker 1: I think there's another path, which is um. You know, 380 00:23:36,560 --> 00:23:39,600 Speaker 1: the US still has a lot of population density it 381 00:23:40,080 --> 00:23:48,960 Speaker 1: uh uh is an attractive market. UM. As wages rise 382 00:23:49,440 --> 00:23:53,960 Speaker 1: abroad in countries like China and Vietnam and Mexico, as 383 00:23:54,080 --> 00:24:00,960 Speaker 1: shipping costs rise, uh, it becomes attractive to bring assembly 384 00:24:01,400 --> 00:24:06,639 Speaker 1: of heavy stuff back to the US. And typically those 385 00:24:06,760 --> 00:24:10,800 Speaker 1: jobs aren't done in a particularly skilled way. You're just 386 00:24:10,880 --> 00:24:16,080 Speaker 1: kind of snapping stuff together. UM. Companies try to do 387 00:24:16,119 --> 00:24:18,760 Speaker 1: it very quickly and without a lot of training, and 388 00:24:18,840 --> 00:24:21,679 Speaker 1: you know, pay people eight to ten to twelve dollars 389 00:24:21,720 --> 00:24:26,239 Speaker 1: an hour. Uh, that's another path. Well let's talk well, 390 00:24:26,359 --> 00:24:29,800 Speaker 1: let's talk about that. That is the I think the 391 00:24:29,920 --> 00:24:33,119 Speaker 1: key point the Fuyout glass plant as uh, you know, 392 00:24:33,200 --> 00:24:36,560 Speaker 1: as the local official told us, it's it's brought jobs back. 393 00:24:36,600 --> 00:24:39,719 Speaker 1: It's been it's been a net positive for the local 394 00:24:39,760 --> 00:24:44,040 Speaker 1: economy there. You know clearly, um, you know, bringing a 395 00:24:44,080 --> 00:24:47,840 Speaker 1: dead General Motors plant back to life is something that, uh, 396 00:24:48,000 --> 00:24:51,760 Speaker 1: that that can help the community. But are those the 397 00:24:51,880 --> 00:24:55,120 Speaker 1: kinds of jobs? Is this is this investment by big 398 00:24:55,200 --> 00:24:58,760 Speaker 1: Chinese company a you know, really a net positive for 399 00:24:58,800 --> 00:25:02,199 Speaker 1: the economy and work or is it or or is 400 00:25:02,240 --> 00:25:06,400 Speaker 1: it not the kind of manufacturing that would really help 401 00:25:06,440 --> 00:25:10,440 Speaker 1: the economy. You know, it's got elements of both. So 402 00:25:10,520 --> 00:25:13,240 Speaker 1: it's paying you know, twelve dollars an hour, which is 403 00:25:13,560 --> 00:25:18,159 Speaker 1: above the Ohio minimum age or the federal minimum age. Um. 404 00:25:18,240 --> 00:25:22,359 Speaker 1: On the other hand, I guess I don't understand, you know, 405 00:25:22,440 --> 00:25:26,560 Speaker 1: so much about the path for advancement. We know that 406 00:25:26,600 --> 00:25:30,119 Speaker 1: it's been a pretty dangerous plant that you know, Ocean 407 00:25:30,280 --> 00:25:33,480 Speaker 1: doesn't go after a lot of plants, and the fact 408 00:25:33,520 --> 00:25:37,040 Speaker 1: that they've had repeated investigations and paid a couple hundred 409 00:25:37,040 --> 00:25:41,640 Speaker 1: thousand dollars and find that, again not typical UH Ocean's 410 00:25:41,680 --> 00:25:46,639 Speaker 1: finding power is quite low. So I think that we 411 00:25:46,680 --> 00:25:51,960 Speaker 1: need to push harder on these well on all employers. UM. 412 00:25:52,000 --> 00:25:54,640 Speaker 1: I think that there are attractions, you know, I think 413 00:25:54,720 --> 00:26:00,000 Speaker 1: Chinese companies have discovered as American companies have that it's 414 00:25:59,800 --> 00:26:02,320 Speaker 1: you want to supply the US market. There's a lot 415 00:26:02,359 --> 00:26:06,600 Speaker 1: of advantages to doing it from the US. And you 416 00:26:06,680 --> 00:26:11,480 Speaker 1: can imagine even that plant adopting different kinds of production 417 00:26:11,560 --> 00:26:14,440 Speaker 1: recipes where you have more productive workers who are well 418 00:26:14,480 --> 00:26:21,000 Speaker 1: trained UH and UM, able to innovate, and able to 419 00:26:21,040 --> 00:26:25,320 Speaker 1: sell higher end products. So I would you know, push 420 00:26:25,640 --> 00:26:29,360 Speaker 1: particularly before giving that company any more incentives to expand 421 00:26:29,400 --> 00:26:33,719 Speaker 1: that that they UH, you know, at a minimum, fully 422 00:26:33,720 --> 00:26:37,200 Speaker 1: correct these safety violations. I know they've invested several million 423 00:26:37,200 --> 00:26:40,000 Speaker 1: dollars in doing so is that enough, I don't know. 424 00:26:40,760 --> 00:26:43,000 Speaker 1: And then push, you know, let's create a career path, 425 00:26:43,160 --> 00:26:48,000 Speaker 1: let's figure out you know, involving workers in UH innovation 426 00:26:48,480 --> 00:26:52,280 Speaker 1: and in debugging of new processes is a way to 427 00:26:52,880 --> 00:26:56,639 Speaker 1: both justify higher wages and benefit the company. So so, 428 00:26:57,440 --> 00:26:59,640 Speaker 1: just to wrap up, what would you say is kind 429 00:26:59,680 --> 00:27:02,600 Speaker 1: of the big picture here for Chinese investment in the 430 00:27:02,720 --> 00:27:05,560 Speaker 1: U s economy, in particularly the manufacturing sector. If I'm 431 00:27:05,600 --> 00:27:10,879 Speaker 1: a worker in Moraine, Ohio at the moment, how optimistic 432 00:27:10,920 --> 00:27:13,640 Speaker 1: should I be about these types of investments, especially with 433 00:27:13,720 --> 00:27:17,119 Speaker 1: the President Trump and Chinese President Hijin pingg about to 434 00:27:17,840 --> 00:27:20,840 Speaker 1: meet now. So I think there's gonna there's reasons for 435 00:27:20,920 --> 00:27:23,520 Speaker 1: the Chinese to want to invest in the US. UM. 436 00:27:23,600 --> 00:27:26,320 Speaker 1: You know, it's an attractive market, and UM, it's going 437 00:27:26,359 --> 00:27:29,359 Speaker 1: to be attractive for them to supply it from the US. 438 00:27:29,480 --> 00:27:34,120 Speaker 1: And I think it's incumbent upon policymakers to make sure 439 00:27:34,160 --> 00:27:37,400 Speaker 1: that those are good jobs and that the Chinese adapt 440 00:27:37,480 --> 00:27:42,560 Speaker 1: to the characteristics of the American workforce, which is more 441 00:27:42,720 --> 00:27:46,720 Speaker 1: educated than perhaps the workforce that they've been exposed to 442 00:27:46,840 --> 00:27:50,639 Speaker 1: in China, and that they contribute to educating that workforce. 443 00:27:50,680 --> 00:27:52,960 Speaker 1: And you know, I think there's a potential for a 444 00:27:53,080 --> 00:27:57,960 Speaker 1: usually beneficial relationship and uh, maybe pushing a little harder 445 00:27:58,040 --> 00:28:01,480 Speaker 1: on both the safety and the wage questions. UM can 446 00:28:01,680 --> 00:28:03,600 Speaker 1: can do that, UM, And I think we've you know, 447 00:28:03,600 --> 00:28:06,640 Speaker 1: we've seen a few Chinese companies that have actually moved 448 00:28:06,640 --> 00:28:09,720 Speaker 1: in that direction. All right, Well, we'll see how that 449 00:28:09,760 --> 00:28:13,240 Speaker 1: plays out. And thank you very much for joining us today, 450 00:28:13,320 --> 00:28:22,639 Speaker 1: Professor Helper. So, Andrew, what's your takeaway from all this? 451 00:28:22,720 --> 00:28:24,840 Speaker 1: What what did what did we learn about that that 452 00:28:24,880 --> 00:28:28,359 Speaker 1: you didn't pick up during your reporting trip out there? Well, 453 00:28:28,359 --> 00:28:31,840 Speaker 1: what I heard is that these towns like Moreno Ohio, 454 00:28:32,000 --> 00:28:36,560 Speaker 1: they want the capital, and China has deep pockets and 455 00:28:36,560 --> 00:28:40,160 Speaker 1: it has lots of capital. So it's a natural relationship. 456 00:28:40,320 --> 00:28:44,680 Speaker 1: It's a mutually beneficial relationship. What I took away from 457 00:28:45,040 --> 00:28:49,760 Speaker 1: Sue at Case Western was it what's good for companies 458 00:28:50,440 --> 00:28:53,920 Speaker 1: and what's good for a town's revenue base is not 459 00:28:54,000 --> 00:28:58,480 Speaker 1: necessarily good for the American worker. Yeah, Andrew, it's really remarkable. 460 00:28:58,720 --> 00:29:00,560 Speaker 1: I mean, if we could see President and Trump go 461 00:29:00,600 --> 00:29:03,800 Speaker 1: out there, uh, for example, and visit that plan and 462 00:29:03,840 --> 00:29:06,760 Speaker 1: get a different perspective from somebody who talked so much 463 00:29:06,840 --> 00:29:11,240 Speaker 1: during the campaign about China raping, uh, raping this country, 464 00:29:11,880 --> 00:29:14,840 Speaker 1: all the unfair trade practices and so on and so forth. 465 00:29:14,960 --> 00:29:17,360 Speaker 1: I mean, he softened some of that rhetoric since he 466 00:29:17,400 --> 00:29:21,640 Speaker 1: became president. He's meeting with President Chief and paying very shortly. 467 00:29:22,080 --> 00:29:26,000 Speaker 1: But you know, there's definitely more wrinkles in this relationship 468 00:29:26,080 --> 00:29:30,320 Speaker 1: between the two countries than most people know about. Yeah, 469 00:29:30,320 --> 00:29:32,240 Speaker 1: I think he would see that that those some of 470 00:29:32,240 --> 00:29:35,440 Speaker 1: those jobs have come back. But I think the other 471 00:29:35,440 --> 00:29:37,200 Speaker 1: thing he will see is on that assembly line, there's 472 00:29:37,240 --> 00:29:39,440 Speaker 1: a heck of a lot more automation than there used 473 00:29:39,480 --> 00:29:43,000 Speaker 1: to be. There's a lot of robots putting together those windshields. 474 00:29:43,760 --> 00:29:46,240 Speaker 1: So bringing jobs back is not as simple as just 475 00:29:46,400 --> 00:29:50,280 Speaker 1: moving pieces around on a map. When you bring jobs 476 00:29:50,320 --> 00:29:53,200 Speaker 1: back over the borders, sometimes those jobs changed. So I 477 00:29:53,240 --> 00:29:55,920 Speaker 1: think that the picture he would see would be perhaps 478 00:29:55,920 --> 00:29:58,440 Speaker 1: a lot more complicated than the one he has conveyed. 479 00:29:58,640 --> 00:30:02,280 Speaker 1: But bringing those jobs could definitely use from some help 480 00:30:02,320 --> 00:30:04,960 Speaker 1: from China, at least as we've seen from this investment. 481 00:30:05,000 --> 00:30:10,240 Speaker 1: For sure. Right, China is not simply a villain, that's 482 00:30:10,280 --> 00:30:13,560 Speaker 1: for sure in this story. All Right, Benchmark will be 483 00:30:13,600 --> 00:30:15,760 Speaker 1: back next week, and until then, you can find us 484 00:30:15,760 --> 00:30:18,920 Speaker 1: on the Bloomberg terminal, Bloomberg dot com, or Bloomberg App, 485 00:30:18,960 --> 00:30:22,480 Speaker 1: as well as on iTunes, pocketcasts, and Stitcher. While you're there, 486 00:30:22,520 --> 00:30:24,480 Speaker 1: take a minute to rate and review the show so 487 00:30:24,560 --> 00:30:27,280 Speaker 1: more listeners can find us and let us know what 488 00:30:27,320 --> 00:30:29,120 Speaker 1: you thought of the show. You can follow me on 489 00:30:29,160 --> 00:30:33,560 Speaker 1: Twitter at Scott Landman and Andrew. You are at a 490 00:30:33,960 --> 00:30:37,320 Speaker 1: M A Y E D a Benchmark is produced by 491 00:30:37,320 --> 00:30:41,040 Speaker 1: Sarah Patterson and the head of Bloomberg Podcast is Alec McCabe. 492 00:30:41,440 --> 00:31:02,680 Speaker 1: Thanks for listening, See you next time. Four