1 00:00:04,760 --> 00:00:08,080 Speaker 1: Welcome to the Bloomberg P and L Podcast. I'm Pim Fox. 2 00:00:08,119 --> 00:00:11,200 Speaker 1: Along with my co host Lisa Abramowitz. Each day we 3 00:00:11,280 --> 00:00:14,480 Speaker 1: bring you the most important, noteworthy and useful interviews for 4 00:00:14,520 --> 00:00:16,880 Speaker 1: you and your money, whether at the grocery store or 5 00:00:16,920 --> 00:00:20,680 Speaker 1: the trading floor. Find the Bloomberg P L Podcast on iTunes, 6 00:00:20,840 --> 00:00:29,960 Speaker 1: SoundCloud and at Bloomberg dot com. Political risk in Europe 7 00:00:30,160 --> 00:00:33,559 Speaker 1: and how fund managers account for this, I want to 8 00:00:33,560 --> 00:00:36,280 Speaker 1: bring in tap On Data. He is global head of 9 00:00:36,320 --> 00:00:40,440 Speaker 1: asked Allocation for and Hewitt in London and tap On 10 00:00:40,680 --> 00:00:43,880 Speaker 1: I want to just sort of get a sense zooming out, 11 00:00:44,159 --> 00:00:46,640 Speaker 1: how do you model for the political risks that we're 12 00:00:46,640 --> 00:00:51,280 Speaker 1: experiencing or seeing, whether it's France's election or whether it's 13 00:00:51,320 --> 00:00:56,080 Speaker 1: potential attacks that disrupt a feeling of colm among investors 14 00:00:56,080 --> 00:01:00,560 Speaker 1: and residents alike. Yeah, well, to just to the chase. 15 00:01:00,600 --> 00:01:02,440 Speaker 1: I don't think it can be. I don't think it's 16 00:01:02,720 --> 00:01:05,399 Speaker 1: model able. But what you can do is do a 17 00:01:05,520 --> 00:01:11,240 Speaker 1: range of scenarios which which capture the uncertainties that are involved. 18 00:01:11,360 --> 00:01:15,160 Speaker 1: So you work on very rough rules of them in 19 00:01:15,240 --> 00:01:18,920 Speaker 1: terms of probabilities of this or that's happening. Murray and 20 00:01:18,959 --> 00:01:22,480 Speaker 1: the pen winning in France or losing, and you look 21 00:01:22,520 --> 00:01:26,400 Speaker 1: at potential market outcomes from that stant point, it's not 22 00:01:26,640 --> 00:01:32,200 Speaker 1: the best signs. What particular models are you creating right now? 23 00:01:32,240 --> 00:01:35,720 Speaker 1: What scenarios are you forecasting that are maybe out of 24 00:01:35,760 --> 00:01:40,199 Speaker 1: the mainstream consciousness, such as Alla pen Win. Yeah, Well, 25 00:01:40,400 --> 00:01:43,120 Speaker 1: one of the scenarios we're working with is that the 26 00:01:43,640 --> 00:01:50,000 Speaker 1: spopulous bandwagon essentially gathered steam, and we have a number 27 00:01:50,040 --> 00:01:56,559 Speaker 1: of such political upset which essentially bring in a strong 28 00:01:57,000 --> 00:02:00,400 Speaker 1: move towards what we call the integration in your that 29 00:02:00,560 --> 00:02:04,200 Speaker 1: is a rollback of kind of European integration and more widely, 30 00:02:04,480 --> 00:02:07,840 Speaker 1: you know, thinking about US developments as well. We work 31 00:02:08,000 --> 00:02:11,520 Speaker 1: we're working on a scenario that rolls back globalization, you know, 32 00:02:11,600 --> 00:02:13,920 Speaker 1: takes us back to a couple of decades, not necessarily 33 00:02:13,960 --> 00:02:16,519 Speaker 1: back to the thirties, but certainly a rolled back, much 34 00:02:16,520 --> 00:02:20,239 Speaker 1: more decisive rollback in globalization over and beyond what we've 35 00:02:20,240 --> 00:02:22,239 Speaker 1: already seen over the last few years. I mean, there's 36 00:02:22,280 --> 00:02:25,000 Speaker 1: already been some of that we shouldn't forget. But the 37 00:02:25,040 --> 00:02:28,639 Speaker 1: scenario we're working with takes us back some way further. 38 00:02:29,240 --> 00:02:31,200 Speaker 1: And that's what we're really talking about, and that is 39 00:02:31,240 --> 00:02:34,880 Speaker 1: probably probably not a very good outcome for financial markets 40 00:02:34,919 --> 00:02:39,080 Speaker 1: because generally speaking, asset prices have gained on the back 41 00:02:39,120 --> 00:02:43,680 Speaker 1: of greater global integration, more trade, more foreign investment, more 42 00:02:43,720 --> 00:02:46,359 Speaker 1: capital flows, all of that has generally been market positive, 43 00:02:46,800 --> 00:02:51,560 Speaker 1: and a decisive set back to that potentially brings brings 44 00:02:51,600 --> 00:02:54,440 Speaker 1: some harm to market conditions. I don't want to take 45 00:02:54,440 --> 00:02:56,800 Speaker 1: you back decades happen. I want you to just go 46 00:02:56,919 --> 00:03:01,079 Speaker 1: back to June of and the Brexit vote. Prior to that, 47 00:03:01,600 --> 00:03:04,640 Speaker 1: what was your view as to what would happen in 48 00:03:04,680 --> 00:03:08,400 Speaker 1: the United Kingdom. Well, we were working on the idea 49 00:03:08,480 --> 00:03:10,960 Speaker 1: that it would be a close from things, but we 50 00:03:11,040 --> 00:03:14,680 Speaker 1: hadn't in common with the consensus majority of view. We 51 00:03:14,760 --> 00:03:18,240 Speaker 1: hadn't worked on the idea that that Brexit was actually 52 00:03:18,240 --> 00:03:21,160 Speaker 1: going to happen. Okay, so you missed that one. We 53 00:03:21,400 --> 00:03:23,240 Speaker 1: we definitely missed that all right. Now, if you what 54 00:03:23,280 --> 00:03:25,640 Speaker 1: did you learn from that one that can be applied 55 00:03:26,280 --> 00:03:29,880 Speaker 1: currently to people's actual portfolios rather than the big thing 56 00:03:30,000 --> 00:03:33,519 Speaker 1: thirty foot view. Great, I know there's a lot of uncertainty. 57 00:03:33,639 --> 00:03:35,880 Speaker 1: No one knows has a crystal ball. We got all that, 58 00:03:36,080 --> 00:03:39,240 Speaker 1: but as a professional, you've got to make decisions. I 59 00:03:39,280 --> 00:03:41,880 Speaker 1: think it's a matter of behavioral biases because we kind 60 00:03:41,880 --> 00:03:45,280 Speaker 1: of take certain things to grant it and you you 61 00:03:45,800 --> 00:03:48,200 Speaker 1: one of the things that's that's that that has done. 62 00:03:48,600 --> 00:03:52,880 Speaker 1: It's really questioned the question the role of the hidden 63 00:03:52,880 --> 00:03:55,080 Speaker 1: biases that you have in your pots. You think, well, 64 00:03:55,120 --> 00:03:58,800 Speaker 1: this is this, this can't possibly be happening because you know, 65 00:03:59,120 --> 00:04:02,200 Speaker 1: Brexit is going to make a lot of folks worse up, 66 00:04:02,280 --> 00:04:05,080 Speaker 1: so it can't possibly be voting for it. But actually, 67 00:04:05,120 --> 00:04:07,960 Speaker 1: as it happens, um they did vote for it despite 68 00:04:07,960 --> 00:04:09,920 Speaker 1: the fact that that they were going to be worse 69 00:04:10,000 --> 00:04:14,560 Speaker 1: off from the result. So right now happen a on Hewitt, 70 00:04:14,560 --> 00:04:17,240 Speaker 1: what is your base case scenario and how are you 71 00:04:17,279 --> 00:04:20,760 Speaker 1: advising people to allocate their money? Look, our base case 72 00:04:20,800 --> 00:04:25,039 Speaker 1: scenarios that the world muddels through, that this populous bandwagon 73 00:04:25,200 --> 00:04:28,920 Speaker 1: does not um as it were strengthened, but that it's 74 00:04:29,000 --> 00:04:31,159 Speaker 1: they're out there and it is a risk that we 75 00:04:31,240 --> 00:04:34,960 Speaker 1: face and periodically there will be setbacks. But we're not 76 00:04:35,040 --> 00:04:38,880 Speaker 1: working on the view that the globalization is seriously threatened. 77 00:04:38,880 --> 00:04:42,200 Speaker 1: I think as I I mean my earlier as aurom, 78 00:04:42,279 --> 00:04:45,960 Speaker 1: my earlier mass. We think that globalizing, the basic globalization 79 00:04:45,960 --> 00:04:48,440 Speaker 1: has clearly slowed, But we're not working on a big 80 00:04:48,440 --> 00:04:53,240 Speaker 1: reversal U and on the back of that, UM, it's 81 00:04:53,360 --> 00:04:56,440 Speaker 1: difficult at this point to argue that there are major, 82 00:04:56,720 --> 00:05:00,640 Speaker 1: major risk to markets from that phenomenon, from the from 83 00:05:00,680 --> 00:05:03,680 Speaker 1: the phenomenon of more political upset. Does that mean full 84 00:05:03,720 --> 00:05:09,400 Speaker 1: and nonstocks and and and sort of sort of normal. Yeah, 85 00:05:09,480 --> 00:05:11,880 Speaker 1: that tells us that the political risk is a factor, 86 00:05:12,360 --> 00:05:16,839 Speaker 1: but it's not necessarily going to be a UM something 87 00:05:16,920 --> 00:05:19,520 Speaker 1: that that really knocks the setting out of stocks, and 88 00:05:20,320 --> 00:05:22,719 Speaker 1: stocks could be vulnerable for other reasons. You know, rising 89 00:05:22,760 --> 00:05:25,919 Speaker 1: interest rates, UM. We can think of a number of 90 00:05:25,920 --> 00:05:28,599 Speaker 1: other factors that could come into play. Well, they're always 91 00:05:28,640 --> 00:05:30,520 Speaker 1: going to be a lot of factors, we know this, 92 00:05:30,640 --> 00:05:33,520 Speaker 1: but it just look, can we just focus for just 93 00:05:33,560 --> 00:05:36,080 Speaker 1: a second. What is the market that you see in 94 00:05:36,160 --> 00:05:40,680 Speaker 1: Europe right now that is shunned by investors? The market 95 00:05:40,720 --> 00:05:45,000 Speaker 1: that is shun by investors, Well, the markets that have 96 00:05:45,120 --> 00:05:49,240 Speaker 1: been more recently shun by investors are European sovereign bombs, 97 00:05:49,400 --> 00:05:53,719 Speaker 1: where essentially spreads with the safe haven play off Germany 98 00:05:53,760 --> 00:05:58,080 Speaker 1: have risen because the market is concerned that Italy or 99 00:05:58,760 --> 00:06:03,040 Speaker 1: or even France mike away and that the sell off 100 00:06:03,080 --> 00:06:06,599 Speaker 1: has not been on a particularly large scale has to 101 00:06:06,640 --> 00:06:09,400 Speaker 1: make them particularly attractive markets in terms of that play. 102 00:06:09,680 --> 00:06:11,800 Speaker 1: But certainly those are markets that have been showing. Look, 103 00:06:11,960 --> 00:06:13,560 Speaker 1: I think the issue is that I don't think that 104 00:06:13,640 --> 00:06:15,479 Speaker 1: I think the markets working on a view that that 105 00:06:16,120 --> 00:06:19,760 Speaker 1: this that European political upset are not a serious factor. 106 00:06:19,839 --> 00:06:21,560 Speaker 1: So it depends which side of that debate you're on. 107 00:06:22,000 --> 00:06:25,200 Speaker 1: We're on the on the side of that debate in 108 00:06:25,240 --> 00:06:28,840 Speaker 1: such a way that we regard these political factors as 109 00:06:28,880 --> 00:06:31,800 Speaker 1: being out there, but that they don't completely upset the 110 00:06:31,800 --> 00:06:35,840 Speaker 1: apple tot. We're not working on what's going on. What's 111 00:06:36,120 --> 00:06:38,760 Speaker 1: the number one most attractive asset class to you right now? 112 00:06:39,839 --> 00:06:43,320 Speaker 1: The number one attractive asset classes in a broad market, 113 00:06:43,360 --> 00:06:47,200 Speaker 1: tom text remains equity markets were in particular in in 114 00:06:47,200 --> 00:06:51,719 Speaker 1: in England, in in the US, OH in a regional context, 115 00:06:51,800 --> 00:06:55,159 Speaker 1: we we prefer the markets that that are that have 116 00:06:55,520 --> 00:06:59,839 Speaker 1: more value, and there we were merging markets and merging 117 00:06:59,880 --> 00:07:03,520 Speaker 1: my keets in Japan standouts as having long term value. 118 00:07:03,680 --> 00:07:06,640 Speaker 1: Syncrisic value in terms of we we look at markets 119 00:07:07,000 --> 00:07:10,600 Speaker 1: is strongest for those markets. Um, the US probably comes 120 00:07:10,640 --> 00:07:13,720 Speaker 1: out at the bottom of the pile, simply because by 121 00:07:13,720 --> 00:07:18,520 Speaker 1: by every valuation indicator that you use USS are simply expenses, 122 00:07:18,760 --> 00:07:21,480 Speaker 1: which doesn't mean that it will roll over tomorrow, but 123 00:07:21,600 --> 00:07:24,160 Speaker 1: it does mean that expect returns from the US market 124 00:07:24,200 --> 00:07:27,880 Speaker 1: over the next few years are likely to disappoint. Whereas 125 00:07:27,920 --> 00:07:30,040 Speaker 1: we look at em or, we look at Japan and 126 00:07:30,120 --> 00:07:33,120 Speaker 1: to a degree in Europe, you know, taking into accounts 127 00:07:33,160 --> 00:07:35,560 Speaker 1: local I'm certainly know a few other factors like Brexit 128 00:07:36,120 --> 00:07:39,080 Speaker 1: into accounts, Europe doesn't look too bad either. The US 129 00:07:39,200 --> 00:07:42,320 Speaker 1: comes off relatively poorly in this in this way of 130 00:07:42,360 --> 00:07:45,440 Speaker 1: looking at markets. All right, thanks very much, it's happened. 131 00:07:45,520 --> 00:07:49,920 Speaker 1: Data Global head of Asset Allocation a On Hewitt joining 132 00:07:50,040 --> 00:08:04,960 Speaker 1: US from London him. You know, there's one big issue 133 00:08:05,040 --> 00:08:07,040 Speaker 1: that a lot of people have been pointing to as 134 00:08:07,080 --> 00:08:12,400 Speaker 1: evidence that consumer credit worthiness is deteriorating fairly rapidly. We 135 00:08:12,440 --> 00:08:17,640 Speaker 1: have seen an increase in losses on UH subprime auto loans. 136 00:08:17,720 --> 00:08:21,480 Speaker 1: We have seen an increase in lost provisions by some 137 00:08:21,600 --> 00:08:25,640 Speaker 1: of the biggest consumer finance lenders. We're talking about Ally, 138 00:08:25,720 --> 00:08:28,720 Speaker 1: We're talking about Santan Dair, We're talking about Capital One. 139 00:08:29,080 --> 00:08:31,440 Speaker 1: A lot of these new a lot of these UH 140 00:08:32,120 --> 00:08:36,679 Speaker 1: captive non captive finance arms have been definitely suffering, and 141 00:08:36,720 --> 00:08:39,240 Speaker 1: we want to talk a little bit more about what 142 00:08:39,320 --> 00:08:44,080 Speaker 1: this might mean for not only the banks and the 143 00:08:44,200 --> 00:08:46,840 Speaker 1: lenders that are you know, extending credit to some of 144 00:08:46,880 --> 00:08:50,280 Speaker 1: these UH companies, but also what this means for the 145 00:08:50,320 --> 00:08:54,040 Speaker 1: broader economy and the auto industry. I want to bring 146 00:08:54,040 --> 00:08:58,040 Speaker 1: in Ryan O'Connell. He's a senior analyst for financials covering 147 00:08:58,120 --> 00:09:01,640 Speaker 1: the Allies of the world, the Capital Ones UH and UH. 148 00:09:01,880 --> 00:09:04,880 Speaker 1: He is here with us. He's from Bloomberg Intelligence and 149 00:09:04,880 --> 00:09:06,800 Speaker 1: he's with us in our Bloomberg eleven three oh studio 150 00:09:07,120 --> 00:09:10,160 Speaker 1: in New York. Ryan, thank you so much for joining us. 151 00:09:10,200 --> 00:09:14,080 Speaker 1: You know, I was struck by allies latest results where 152 00:09:14,120 --> 00:09:19,880 Speaker 1: they increased their their expectation for loan losses. They also 153 00:09:20,040 --> 00:09:24,320 Speaker 1: decrease their expectation for resale values of used cars. Can 154 00:09:24,360 --> 00:09:26,880 Speaker 1: you tell us a little bit about the most notable 155 00:09:26,920 --> 00:09:30,479 Speaker 1: aspects of this and how severe uh this could potentially 156 00:09:31,000 --> 00:09:33,440 Speaker 1: crimp their earnings in this coming year. Oh great, Well, 157 00:09:33,559 --> 00:09:35,200 Speaker 1: first of all, thanks for having me on the show, Lisa. 158 00:09:35,640 --> 00:09:38,320 Speaker 1: Uh So with regard to Ally, and I'd say the 159 00:09:38,360 --> 00:09:41,880 Speaker 1: read through is also for Capital one UH and other 160 00:09:41,920 --> 00:09:44,600 Speaker 1: other owners like that. And i'd breaking into two parts, 161 00:09:45,200 --> 00:09:48,040 Speaker 1: I think, starting back in about June, of last year, 162 00:09:48,520 --> 00:09:52,000 Speaker 1: we started to see cracks in the market for subprime borrowers, 163 00:09:52,160 --> 00:09:54,319 Speaker 1: and so that's what this is really all about. So 164 00:09:54,720 --> 00:09:57,240 Speaker 1: no need to sound the alarm on prime borrowers. They're 165 00:09:57,280 --> 00:10:00,760 Speaker 1: still fine, healthy economy, etcetera. The reason why Allies spooked 166 00:10:00,800 --> 00:10:03,760 Speaker 1: people yesterday and they did is a couple of things. One, 167 00:10:03,800 --> 00:10:06,000 Speaker 1: they keep jacking up their estimates of how much their 168 00:10:06,000 --> 00:10:08,319 Speaker 1: credit losses are going to go up. And too, just 169 00:10:08,400 --> 00:10:11,840 Speaker 1: as you mentioned, use car sales are plumbering much fast 170 00:10:11,840 --> 00:10:15,120 Speaker 1: and people expected. Uh So people have been expecting about 171 00:10:15,160 --> 00:10:18,520 Speaker 1: five percent, it's about seven heading in the wrong direction. 172 00:10:18,920 --> 00:10:21,560 Speaker 1: So why is that important. A couple of things. One 173 00:10:21,760 --> 00:10:24,559 Speaker 1: for people a big leasing portfolios, which by the way, 174 00:10:24,559 --> 00:10:27,760 Speaker 1: is not allied. Obviously, if the prices of cars go 175 00:10:27,840 --> 00:10:30,200 Speaker 1: down when it comes off lease and you want to 176 00:10:30,200 --> 00:10:34,960 Speaker 1: resell the car, that can create some earnings hits. Uh, 177 00:10:35,000 --> 00:10:38,400 Speaker 1: Well that would be more of the captives. Uh. Capital 178 00:10:38,400 --> 00:10:41,200 Speaker 1: One actually has a fairly large leasing portfolio. I don't 179 00:10:41,240 --> 00:10:44,160 Speaker 1: cover them. JP Morgan is also involved in leasing. Uh 180 00:10:44,200 --> 00:10:46,880 Speaker 1: So those kind of companies could be looking at that. Uh. 181 00:10:46,920 --> 00:10:48,720 Speaker 1: And then the other thing is that even if you 182 00:10:48,800 --> 00:10:51,680 Speaker 1: don't have a big leasing portfolio, if you have to 183 00:10:51,920 --> 00:10:54,480 Speaker 1: repossess a car, and every once in a while the 184 00:10:54,520 --> 00:10:57,360 Speaker 1: allies of the world do. Then obviously it's the value 185 00:10:57,400 --> 00:11:00,720 Speaker 1: of that falls that can increase your credit provisions. Has 186 00:11:00,760 --> 00:11:03,520 Speaker 1: this all been can put into the context of the 187 00:11:03,559 --> 00:11:06,320 Speaker 1: price either of the bonds or the stocks that in others, 188 00:11:06,320 --> 00:11:09,720 Speaker 1: of the valuation that investors are seeking. Well, yeah, great question. 189 00:11:10,040 --> 00:11:13,040 Speaker 1: So I covered things on the bond side. Uh uh, 190 00:11:13,160 --> 00:11:15,080 Speaker 1: and there there has been a bit of a reaction. 191 00:11:15,480 --> 00:11:18,120 Speaker 1: So if you look at say Capital One, you know, 192 00:11:18,200 --> 00:11:20,720 Speaker 1: big large bank, all that kind of stuff, its bonds 193 00:11:20,720 --> 00:11:23,360 Speaker 1: are trading let's say about twenty five bases points behind 194 00:11:23,480 --> 00:11:26,760 Speaker 1: JP Morgan. They bounced around. Uh, you know, at the 195 00:11:26,760 --> 00:11:29,880 Speaker 1: wides they were liking about seventy five. They've come in 196 00:11:29,920 --> 00:11:32,800 Speaker 1: a bit. They've got squeaky clean on top of JP 197 00:11:32,960 --> 00:11:35,320 Speaker 1: Morgan people who we thought about it, and and they've moved 198 00:11:35,320 --> 00:11:39,319 Speaker 1: out allies below investment grade. So they trade about a 199 00:11:39,400 --> 00:11:44,199 Speaker 1: hundred fifty oh behind JP Morgan. Uh. Those bounds of 200 00:11:44,280 --> 00:11:47,000 Speaker 1: bounces around a lot. At the worst they're about two hundred. 201 00:11:47,040 --> 00:11:49,520 Speaker 1: They squeaked into about US a hundred. Now we're back 202 00:11:49,559 --> 00:11:54,440 Speaker 1: to hundred fifty. Can you put the increase in provisions 203 00:11:54,480 --> 00:11:57,280 Speaker 1: for for loan losses into perspective. I mean, yes, they 204 00:11:57,280 --> 00:12:01,480 Speaker 1: have increased, but how do they compare to historical periods, 205 00:12:01,600 --> 00:12:04,640 Speaker 1: not you know, necessarily the best of credit times, like 206 00:12:04,640 --> 00:12:07,839 Speaker 1: we've seen a great question. So I think, well, if 207 00:12:07,840 --> 00:12:11,560 Speaker 1: we step back in two thousands fifteen Allies loan losses, 208 00:12:11,600 --> 00:12:14,400 Speaker 1: we're running about fifty basis points a half a percentage 209 00:12:14,440 --> 00:12:17,000 Speaker 1: point in the portfolo, so really pretty great. And then 210 00:12:17,120 --> 00:12:20,160 Speaker 1: in June of last year, Allies started saying, well, you know, 211 00:12:20,440 --> 00:12:23,640 Speaker 1: life is changing a little bit. And so they ended 212 00:12:23,679 --> 00:12:25,320 Speaker 1: the year at a run rate of about let's call 213 00:12:25,360 --> 00:12:27,839 Speaker 1: it a hundred basis points, so from about fifty to 214 00:12:27,880 --> 00:12:30,480 Speaker 1: a hundred in one year. Uh. And then this year 215 00:12:30,520 --> 00:12:32,360 Speaker 1: where they're saying, well, we thought it was gonna be 216 00:12:32,400 --> 00:12:34,640 Speaker 1: one twenty, might actually be more like about one forty. 217 00:12:35,160 --> 00:12:37,160 Speaker 1: So it is trying to ratch up a lot. What 218 00:12:37,320 --> 00:12:40,760 Speaker 1: you say, one basis points, So it's like one point 219 00:12:40,760 --> 00:12:46,000 Speaker 1: four percent of their overall loan books or what is that? 220 00:12:46,080 --> 00:12:49,480 Speaker 1: What is that equal to? Is that? Sorry for the Lisa? 221 00:12:50,000 --> 00:12:52,439 Speaker 1: So yeah, about one point four percent of their auto 222 00:12:52,520 --> 00:12:56,959 Speaker 1: lease book auto loan book, which is really Ally's main business. 223 00:12:57,080 --> 00:12:59,560 Speaker 1: They have some other businesses, but they're they're not really 224 00:12:59,559 --> 00:13:03,000 Speaker 1: that important. Ryan, Is any of this connected with the 225 00:13:03,320 --> 00:13:07,800 Speaker 1: very long duration loans that were available during the financial crisis? 226 00:13:08,440 --> 00:13:12,560 Speaker 1: So I think what we're seeing here is that there 227 00:13:12,600 --> 00:13:15,800 Speaker 1: has been more competition. They own a loan market, um 228 00:13:16,120 --> 00:13:18,960 Speaker 1: and uh so they've been lengthening the terms of their loans. 229 00:13:19,520 --> 00:13:21,960 Speaker 1: Uh So, for example, some cases they are going out 230 00:13:22,000 --> 00:13:24,679 Speaker 1: to seven years. And bear in mind that a lot 231 00:13:24,720 --> 00:13:28,040 Speaker 1: of these loans are on used cars. So an allies case, 232 00:13:28,080 --> 00:13:31,760 Speaker 1: for example, about the loans are used cars. You start 233 00:13:31,760 --> 00:13:34,199 Speaker 1: out with the car that's already been out for about 234 00:13:34,240 --> 00:13:37,320 Speaker 1: three years, unless saying Ali does this and you tack 235 00:13:37,360 --> 00:13:40,280 Speaker 1: on another seven years. That's a lot of lifespan for 236 00:13:40,320 --> 00:13:43,360 Speaker 1: a car. And thanks very much for joining us my 237 00:13:43,400 --> 00:13:46,000 Speaker 1: pleasure of giving us the detail. Ryan O'Connell is a 238 00:13:46,040 --> 00:13:50,520 Speaker 1: senior analyst financials for Bloomberg Intelligence, telling us about the 239 00:13:50,520 --> 00:14:07,199 Speaker 1: automobile credit market. Pim Fox. We were talking this morning 240 00:14:07,360 --> 00:14:11,199 Speaker 1: about Beyond Meat and this is a plant based burger, 241 00:14:11,760 --> 00:14:13,520 Speaker 1: and you had the great question. You look at me 242 00:14:13,559 --> 00:14:16,520 Speaker 1: and you said, what is this? What is it meat? 243 00:14:16,520 --> 00:14:18,679 Speaker 1: Out of Um? To answer that question, let's bring in 244 00:14:18,720 --> 00:14:21,480 Speaker 1: the CEO of Beyond Meat, Ethan Brown. He comes to 245 00:14:21,560 --> 00:14:24,760 Speaker 1: us from Los Angeles, Ethan, let's start with that. What 246 00:14:25,080 --> 00:14:27,920 Speaker 1: is beyond meat? Well, first, thank you very much for 247 00:14:27,920 --> 00:14:30,080 Speaker 1: having me on the show. I appreciate it. And um, 248 00:14:30,080 --> 00:14:32,720 Speaker 1: it's a great question. So so what we're after, if 249 00:14:32,760 --> 00:14:36,920 Speaker 1: beyond meat, is taking all the great things about animal 250 00:14:36,960 --> 00:14:39,600 Speaker 1: protein or meat and building those directly from plants. And 251 00:14:39,600 --> 00:14:42,360 Speaker 1: if so, if you think about what meat is, meat 252 00:14:42,400 --> 00:14:45,840 Speaker 1: is essentially five things. It's amino acids, it's lipids, it's 253 00:14:46,000 --> 00:14:49,200 Speaker 1: very small amount of carbodrates, it's minerals, and its water. 254 00:14:49,800 --> 00:14:51,920 Speaker 1: None of those things are exclusive to the animal. They're 255 00:14:51,920 --> 00:14:54,600 Speaker 1: all present throughout the plant kingdom. And so we're doing 256 00:14:54,720 --> 00:14:59,360 Speaker 1: is essentially taking all of those resources from non animal sources, 257 00:14:59,680 --> 00:15:01,960 Speaker 1: and then we're architect ing or building them in the 258 00:15:02,040 --> 00:15:05,720 Speaker 1: same way that you would present animal protein. So we're 259 00:15:05,720 --> 00:15:09,320 Speaker 1: basically bypassing the animal and delivering a piece of meat 260 00:15:09,400 --> 00:15:12,720 Speaker 1: directly from plants. We're not suggesting it's a fake meat 261 00:15:12,880 --> 00:15:14,880 Speaker 1: or something like that. It's simply a meat that's been 262 00:15:14,920 --> 00:15:17,480 Speaker 1: built directly from plants. It has all the same parts, 263 00:15:17,560 --> 00:15:20,520 Speaker 1: it presents in the same form, statiates in the same way. 264 00:15:20,560 --> 00:15:23,320 Speaker 1: It provides the same interditional benefits well, eat and I'm 265 00:15:23,600 --> 00:15:28,800 Speaker 1: maybe just like you could explain what plants are actually 266 00:15:29,000 --> 00:15:32,400 Speaker 1: in this meat or this meat meat? What what's what 267 00:15:32,560 --> 00:15:35,640 Speaker 1: is it made of? Sure? And so what's interesting about 268 00:15:35,640 --> 00:15:37,080 Speaker 1: it is once you start to think of the plant 269 00:15:37,120 --> 00:15:39,360 Speaker 1: kingdom as a source of direct protein, not as a 270 00:15:39,360 --> 00:15:43,160 Speaker 1: source of feed for animals that then converted into protein. Uh, 271 00:15:43,360 --> 00:15:46,320 Speaker 1: you can pick uh, and you can take amino acids 272 00:15:46,360 --> 00:15:50,280 Speaker 1: or protein from a huge variety of plant sources. And 273 00:15:50,320 --> 00:15:52,440 Speaker 1: so in this case we use P protein, but you 274 00:15:52,440 --> 00:15:56,080 Speaker 1: could literally use hundreds, if not thousands, of different crops 275 00:15:56,200 --> 00:15:59,760 Speaker 1: to pull the requisite set of amino acids that you 276 00:15:59,800 --> 00:16:01,560 Speaker 1: need to create a piece of meat. All right, now 277 00:16:01,840 --> 00:16:06,000 Speaker 1: you say you use P protein. Is this food engineering? 278 00:16:06,040 --> 00:16:08,800 Speaker 1: Because isn't part of the whole reason to focus on 279 00:16:08,960 --> 00:16:13,680 Speaker 1: vegetables and fruits is that it's natural state is what 280 00:16:13,920 --> 00:16:17,560 Speaker 1: is important in terms of how it delivers the nutrients 281 00:16:17,600 --> 00:16:20,680 Speaker 1: to your body. Sure, And so that's a really great question. 282 00:16:20,760 --> 00:16:22,400 Speaker 1: And so the way I think about this is a 283 00:16:22,480 --> 00:16:26,160 Speaker 1: tale of two processes. You can either take protein directly 284 00:16:26,200 --> 00:16:28,560 Speaker 1: from a plant, and you can use what we do, 285 00:16:28,600 --> 00:16:31,400 Speaker 1: which is heating, cooling, and pressure to essentially align it 286 00:16:31,440 --> 00:16:34,920 Speaker 1: in the form of muscle or meat or you can 287 00:16:34,920 --> 00:16:36,960 Speaker 1: take that same plant matter and run it to an 288 00:16:36,960 --> 00:16:38,840 Speaker 1: animal and then that would be presented on the plate 289 00:16:38,880 --> 00:16:41,440 Speaker 1: as a piece of meat. So we argue that's actually 290 00:16:41,480 --> 00:16:44,920 Speaker 1: a more direct and less processed way of providing protein 291 00:16:44,960 --> 00:16:47,000 Speaker 1: to the center of the plate. Now, it does take 292 00:16:47,040 --> 00:16:49,360 Speaker 1: protein out of one form and put it another, but 293 00:16:49,480 --> 00:16:52,920 Speaker 1: if you've had pasta, or if you've had any number 294 00:16:53,120 --> 00:16:56,120 Speaker 1: of products like a snack bar or something like that, 295 00:16:56,200 --> 00:16:59,480 Speaker 1: it's run through the same system. It's essentially applying heating, 296 00:16:59,640 --> 00:17:03,880 Speaker 1: cool and pressure to align the proteins. They take on 297 00:17:04,040 --> 00:17:08,320 Speaker 1: the same texture and presentation of of animal protein or meat. 298 00:17:08,640 --> 00:17:11,200 Speaker 1: Even how much has your business expanded over the past 299 00:17:11,240 --> 00:17:13,760 Speaker 1: few years, you know, it's been amazing. So when I 300 00:17:13,760 --> 00:17:16,919 Speaker 1: started the business in two thousand nine, um, it was 301 00:17:17,440 --> 00:17:19,320 Speaker 1: definitely a push, you know, it was something that we 302 00:17:19,359 --> 00:17:20,840 Speaker 1: had to go out there and try to convince people 303 00:17:20,840 --> 00:17:23,720 Speaker 1: of something has happened in the last i'd say even 304 00:17:23,760 --> 00:17:28,560 Speaker 1: two to three years, whereby the American consumer is actively 305 00:17:28,640 --> 00:17:31,480 Speaker 1: looking for the solution they wanted to work. And that's 306 00:17:31,520 --> 00:17:34,200 Speaker 1: to our benefit because you know, we are not perfect yet, right, 307 00:17:34,200 --> 00:17:37,720 Speaker 1: We still have miles to travel with respect to perfectly 308 00:17:37,760 --> 00:17:40,480 Speaker 1: replicating a piece of animal protein or meat. But the 309 00:17:40,600 --> 00:17:43,160 Speaker 1: consumer is hungry for the solution. They want to continue 310 00:17:43,200 --> 00:17:47,280 Speaker 1: to enjoy uh, you know, burgers and hot dogs and steaks, 311 00:17:47,320 --> 00:17:50,320 Speaker 1: et cetera. But they're beginning to understand that there may 312 00:17:50,359 --> 00:17:54,199 Speaker 1: be a better way to produce uh those products. And 313 00:17:54,280 --> 00:17:57,960 Speaker 1: so we see an amazing level of interesting what we're doing. 314 00:17:58,000 --> 00:18:01,160 Speaker 1: And with every kind of senemy an improvement we make, 315 00:18:01,240 --> 00:18:03,879 Speaker 1: we welcome in hundreds of thousands more people to the 316 00:18:03,880 --> 00:18:06,360 Speaker 1: brand as a product get better and better, and so 317 00:18:06,480 --> 00:18:09,399 Speaker 1: we're growing, you know, at a clip of you know, 318 00:18:09,480 --> 00:18:12,520 Speaker 1: this year over last year. Um, we've had you know, 319 00:18:12,600 --> 00:18:15,679 Speaker 1: consistently over the last year problems filling orders. So it's 320 00:18:15,720 --> 00:18:18,160 Speaker 1: a wonderful position to be in and one that's very gratifying. 321 00:18:19,080 --> 00:18:23,480 Speaker 1: Is there any evidence that suggests that the combination of 322 00:18:23,520 --> 00:18:27,160 Speaker 1: amino acids, lipids, water, carbohydrates, and saw on the trace 323 00:18:27,440 --> 00:18:31,600 Speaker 1: minerals that you're describing, is there any evidence that reconstituting 324 00:18:31,640 --> 00:18:34,920 Speaker 1: them in this form of a processed food is any 325 00:18:35,040 --> 00:18:38,520 Speaker 1: better for an individual, not the environment right now, but 326 00:18:38,560 --> 00:18:41,720 Speaker 1: for the individual consuming the product and consuming the actual 327 00:18:41,800 --> 00:18:45,440 Speaker 1: meat if that's what they choose. Sure, And and so 328 00:18:45,640 --> 00:18:49,239 Speaker 1: the way I would look at that is, UM, what's missing, right, 329 00:18:49,240 --> 00:18:52,120 Speaker 1: and so we can again, we know the blueprint of meat, 330 00:18:52,359 --> 00:18:54,960 Speaker 1: we understand its composition, and we have access to those 331 00:18:55,000 --> 00:18:57,800 Speaker 1: materials from the planet Kingdom. But what can we leave out? 332 00:18:58,080 --> 00:19:00,520 Speaker 1: We can leave out cholesterol, for example, so products have 333 00:19:00,640 --> 00:19:03,960 Speaker 1: no cholesterol, and I think there's a very well established 334 00:19:04,040 --> 00:19:08,560 Speaker 1: medical literature around cholesterol and and uh. And so that's 335 00:19:08,560 --> 00:19:11,600 Speaker 1: just one example. There are other examples of the ways 336 00:19:11,640 --> 00:19:13,960 Speaker 1: which we feel we are are healthier than a piece 337 00:19:13,960 --> 00:19:17,200 Speaker 1: of animal protein. But that's the most obvious ethan. One 338 00:19:17,200 --> 00:19:20,440 Speaker 1: thing that I thought was notable is that Tyson, known 339 00:19:20,520 --> 00:19:25,440 Speaker 1: for its chickens, have a five investment a minority stake 340 00:19:25,920 --> 00:19:29,840 Speaker 1: in Beyond Meat. What was their reasoning when they when 341 00:19:29,840 --> 00:19:32,600 Speaker 1: they made this investment? Why why do they want to 342 00:19:32,640 --> 00:19:35,800 Speaker 1: go basically against the whole thesis of their company, which 343 00:19:35,840 --> 00:19:39,719 Speaker 1: is the people like meat? Right? Um, So if if 344 00:19:39,720 --> 00:19:41,520 Speaker 1: I can maybe offered just one comment on that, so 345 00:19:41,760 --> 00:19:44,920 Speaker 1: I don't view it as going against their thesis. Um, 346 00:19:44,960 --> 00:19:47,000 Speaker 1: their thesis is they're going to provide protein to the 347 00:19:47,000 --> 00:19:50,160 Speaker 1: world and UH, and our thesis also that people love 348 00:19:50,240 --> 00:19:52,240 Speaker 1: meat like so that we're not in conflict in either 349 00:19:52,320 --> 00:19:56,760 Speaker 1: of those UH agendas. We just feel that just like 350 00:19:56,920 --> 00:20:00,760 Speaker 1: you know, um, most people are using UM mobile phones 351 00:20:00,760 --> 00:20:03,919 Speaker 1: over land lines today, that there can be a transition 352 00:20:03,960 --> 00:20:06,240 Speaker 1: to a new form of meat, and Tyson sees that. 353 00:20:06,280 --> 00:20:07,679 Speaker 1: I think they're excited about it, and I have to 354 00:20:07,680 --> 00:20:09,800 Speaker 1: plaud them. I mean they are of all the companies 355 00:20:09,840 --> 00:20:12,680 Speaker 1: out there, they are leaning in heavily too. We want 356 00:20:12,680 --> 00:20:15,000 Speaker 1: to be a protein provider. We're not gonna get hung 357 00:20:15,119 --> 00:20:17,280 Speaker 1: up on the fact that you know, they have to 358 00:20:17,320 --> 00:20:19,720 Speaker 1: come from animals. It can come from directly from plants 359 00:20:19,720 --> 00:20:21,639 Speaker 1: in the case of beyond meat. So they're making an 360 00:20:21,640 --> 00:20:24,359 Speaker 1: investment and what I think they believe is a shift 361 00:20:24,400 --> 00:20:27,800 Speaker 1: toward more plant based meat. How much does this cost 362 00:20:27,960 --> 00:20:32,159 Speaker 1: compared to meat, traditional meat? Yeah, so it's an interesting questions. 363 00:20:32,200 --> 00:20:34,200 Speaker 1: So you know, if you if you look at our 364 00:20:34,240 --> 00:20:38,520 Speaker 1: production facilities, we are you know, extremely small relative to 365 00:20:38,840 --> 00:20:42,159 Speaker 1: global meat processing right. So, um, you know we're going 366 00:20:42,200 --> 00:20:45,240 Speaker 1: to have a premium because of that. But as we expand, 367 00:20:45,840 --> 00:20:48,760 Speaker 1: there's nothing to stop us from lowering our prices to 368 00:20:48,800 --> 00:20:51,680 Speaker 1: the point where we can compete and even be lower 369 00:20:51,720 --> 00:20:55,439 Speaker 1: than the price of meat because we're taken out the middleman. 370 00:20:55,480 --> 00:20:59,080 Speaker 1: If you've taken any economics course, which I'm sure you have, Uh, 371 00:20:59,119 --> 00:21:01,720 Speaker 1: you know the number one thing they say in operations 372 00:21:01,840 --> 00:21:04,080 Speaker 1: is you get rid of the bottleneck. Uh, you know, 373 00:21:04,160 --> 00:21:06,960 Speaker 1: generate efficiencies and you can lower costs. And if you 374 00:21:07,000 --> 00:21:09,199 Speaker 1: think about the animal as a bottleneck, we've taken out 375 00:21:09,240 --> 00:21:11,560 Speaker 1: a pretty big bottleneck in the production of meeting. No, 376 00:21:11,640 --> 00:21:13,520 Speaker 1: we're gonna have to leave it there, Thanks very much. 377 00:21:13,680 --> 00:21:17,879 Speaker 1: Ethan Brown is the chief executive of Beyond Meat based 378 00:21:18,000 --> 00:21:33,639 Speaker 1: in Los Angeles. Well, President Donald Trump, he was in 379 00:21:33,720 --> 00:21:36,800 Speaker 1: Detroit this week. On Wednesday, he announced a rollback of 380 00:21:36,920 --> 00:21:40,800 Speaker 1: fuel economy standards for cars and trucks and this was 381 00:21:40,840 --> 00:21:44,480 Speaker 1: all put in place by the Obama administration. The goal 382 00:21:44,960 --> 00:21:49,960 Speaker 1: fifty four and a half miles per gallon by twenty five. 383 00:21:50,320 --> 00:21:53,320 Speaker 1: Here to tell us more about this is Dr Richard Newell. 384 00:21:53,359 --> 00:21:56,440 Speaker 1: He is the president and the chief executive of Resources 385 00:21:56,520 --> 00:22:00,520 Speaker 1: for the Future, based in Washington, d c U. Dr Neill, 386 00:22:00,560 --> 00:22:02,399 Speaker 1: thank you very much for being with us. Maybe you 387 00:22:02,400 --> 00:22:06,399 Speaker 1: could just lay out the cost connections related to these 388 00:22:06,560 --> 00:22:11,360 Speaker 1: fuel economy standards and what is in your mind going 389 00:22:11,400 --> 00:22:15,960 Speaker 1: to change now? Yes, well, fuel economy standards have been 390 00:22:16,040 --> 00:22:21,160 Speaker 1: set for several decades now by the Department of Transportation 391 00:22:21,200 --> 00:22:25,480 Speaker 1: in order to increase the energy efficiency or fuel economy 392 00:22:25,640 --> 00:22:29,720 Speaker 1: of the US passenger fleet and UH In two thousand 393 00:22:29,720 --> 00:22:35,080 Speaker 1: and eleven, the Obama administration combined these fuel economy standards 394 00:22:35,119 --> 00:22:41,720 Speaker 1: with standards on carbon dioxide emissions, which were required by 395 00:22:41,840 --> 00:22:44,160 Speaker 1: a you know, a judgment of the Supreme Court that 396 00:22:44,560 --> 00:22:47,480 Speaker 1: these emissions needed to be regulated. And so since two 397 00:22:47,520 --> 00:22:51,280 Speaker 1: thousand eleven, we've had joint actions by the Department of 398 00:22:51,320 --> 00:22:57,920 Speaker 1: Transportation and the Environmental Protection Agency to reduce gasoline consumption 399 00:22:57,960 --> 00:23:02,080 Speaker 1: from automobiles really for a few different purposes. One purpose 400 00:23:02,280 --> 00:23:07,399 Speaker 1: is to simply save people money by requiring that the 401 00:23:07,400 --> 00:23:12,400 Speaker 1: automobiles that are available for purchase um will use less gasoline. 402 00:23:12,440 --> 00:23:15,600 Speaker 1: So that's one key attribute of these standards. Another is 403 00:23:15,640 --> 00:23:19,560 Speaker 1: to reduce their carbon dioxide emissions, which is views an 404 00:23:19,600 --> 00:23:24,760 Speaker 1: important um element element of these regulations to address global 405 00:23:24,800 --> 00:23:29,639 Speaker 1: climate change. And finally, another aspect of these regulations is 406 00:23:29,680 --> 00:23:34,119 Speaker 1: to improve US energy security by reducing oil imports. And 407 00:23:34,240 --> 00:23:38,119 Speaker 1: so during the standard setting process, each of these different 408 00:23:38,160 --> 00:23:42,600 Speaker 1: factors is considered by these two agencies in order to 409 00:23:42,640 --> 00:23:45,760 Speaker 1: figure out what the right level of the standard is. Well. 410 00:23:45,880 --> 00:23:50,680 Speaker 1: Dr Newell, as Pim mentioned earlier, So President Trump is 411 00:23:50,720 --> 00:23:54,040 Speaker 1: talking in Detroit with some of the leaders and is 412 00:23:54,080 --> 00:23:56,640 Speaker 1: talking and saying that he will roll back some of 413 00:23:56,680 --> 00:24:00,080 Speaker 1: these provisions that were implemented implemented by former press it 414 00:24:00,119 --> 00:24:06,040 Speaker 1: in Obama. Just how big of a rollback will this be, Well, 415 00:24:06,119 --> 00:24:08,359 Speaker 1: it will. They will need to go through the same 416 00:24:08,440 --> 00:24:12,720 Speaker 1: types of analysis that we're we're done, you know, in 417 00:24:12,800 --> 00:24:16,560 Speaker 1: two thousand eleven by the Obama administration, by the Department 418 00:24:16,600 --> 00:24:19,879 Speaker 1: of Transportation and the Environmental protection agencies. So uh uh, 419 00:24:20,280 --> 00:24:22,879 Speaker 1: standards of of this type when they're put into place. 420 00:24:22,960 --> 00:24:26,520 Speaker 1: There's many different analyses that go into it. One important 421 00:24:26,520 --> 00:24:30,119 Speaker 1: one is called a regulatory impact analysis, where the benefits 422 00:24:30,160 --> 00:24:33,720 Speaker 1: and the costs of the regulation are weighed. And so 423 00:24:34,880 --> 00:24:38,320 Speaker 1: they look like they intend to um open open up 424 00:24:38,800 --> 00:24:42,840 Speaker 1: for midterm review the corporate fuel the corporate average fuel 425 00:24:42,880 --> 00:24:46,119 Speaker 1: economy standards, and so what they will presumably be looking 426 00:24:46,160 --> 00:24:49,960 Speaker 1: at is changes that have taken place since these analyses 427 00:24:50,000 --> 00:24:52,720 Speaker 1: were first done in two thousand eleven. What has changed 428 00:24:52,760 --> 00:24:56,000 Speaker 1: since then, and what direction of change in the regulations 429 00:24:56,080 --> 00:24:58,439 Speaker 1: might that motivate. So if you look, for example, a 430 00:24:58,520 --> 00:25:01,199 Speaker 1: key attribute here was going to be changes in the 431 00:25:01,240 --> 00:25:05,240 Speaker 1: price of gasoline, and since the original analysis, the price 432 00:25:05,280 --> 00:25:08,200 Speaker 1: of oil and the price of gasoline have dropped by 433 00:25:08,280 --> 00:25:13,240 Speaker 1: about in real terms, So other things equal, this would 434 00:25:13,240 --> 00:25:16,000 Speaker 1: tend to to tend to point to a rationale for 435 00:25:16,240 --> 00:25:19,480 Speaker 1: weakening the standards relative to what was originally put into place. 436 00:25:20,880 --> 00:25:24,640 Speaker 1: Another another key factor, though, is the UM, the value 437 00:25:24,720 --> 00:25:27,960 Speaker 1: of reducing the carbon dioxide emissions that come from burning 438 00:25:27,960 --> 00:25:32,159 Speaker 1: gasoline UM. There's a number called the social cost of carbon, 439 00:25:32,359 --> 00:25:37,080 Speaker 1: which is the value the monetized value of reducing carbon 440 00:25:37,080 --> 00:25:40,879 Speaker 1: dioxide emissions UM. Since two thousand eleven, the number that 441 00:25:40,920 --> 00:25:43,959 Speaker 1: has been used by the federal government has increased actually 442 00:25:44,000 --> 00:25:47,080 Speaker 1: by about so that would point in the other direction 443 00:25:47,640 --> 00:25:52,280 Speaker 1: in terms of strengthening the standards. However, I'll add a 444 00:25:52,359 --> 00:25:55,960 Speaker 1: very important caveat there, which UM. The Trump administration has 445 00:25:56,000 --> 00:26:00,760 Speaker 1: signaled its intention to also reduce the value that it 446 00:26:00,800 --> 00:26:04,520 Speaker 1: places on hither addressing climate change. That's been quite evident 447 00:26:04,560 --> 00:26:07,120 Speaker 1: in a number of their remarks. And so depending upon 448 00:26:07,200 --> 00:26:09,639 Speaker 1: what they do there, that could point you know, I 449 00:26:09,680 --> 00:26:11,439 Speaker 1: would I would guess they would change then the way 450 00:26:11,480 --> 00:26:15,080 Speaker 1: that would point downward in terms of the regulatory stringency. 451 00:26:15,680 --> 00:26:18,480 Speaker 1: Just real quick, Dr Newell, what has the frustration been 452 00:26:18,560 --> 00:26:21,600 Speaker 1: like among your peers about that last point that you 453 00:26:21,640 --> 00:26:26,360 Speaker 1: talk about with respect to this administration's approach to climate change. Well, 454 00:26:26,400 --> 00:26:29,920 Speaker 1: they're very clearly not just on corporate advage fuel economy standards, 455 00:26:30,000 --> 00:26:33,560 Speaker 1: but on regulation of emissions from electric power plants under 456 00:26:33,840 --> 00:26:38,520 Speaker 1: the Clean Power Plan, UH, the approach towards budgets, UH, 457 00:26:38,640 --> 00:26:43,679 Speaker 1: federal budgets that invest in research related to climate change 458 00:26:43,800 --> 00:26:46,720 Speaker 1: and invest in, you know, actions taken to reduce carbon 459 00:26:46,760 --> 00:26:50,400 Speaker 1: dioxide emissions. UM. You know, there's any number of different 460 00:26:50,480 --> 00:26:53,720 Speaker 1: changes that the administration has either already put into place 461 00:26:53,920 --> 00:26:57,440 Speaker 1: or appears ready to put into place that really just 462 00:26:57,520 --> 00:27:01,480 Speaker 1: don't take the climate change threats seriously. UM. And that's 463 00:27:01,680 --> 00:27:04,640 Speaker 1: you know, there's any number of remarks made by both 464 00:27:04,640 --> 00:27:08,440 Speaker 1: the President himself as well as major leaders within the 465 00:27:08,480 --> 00:27:11,640 Speaker 1: Trump administration point in that direction. Dr Richard Newell, thank 466 00:27:11,640 --> 00:27:13,639 Speaker 1: you so much for joining us. Dr Richard Newell is 467 00:27:13,640 --> 00:27:17,880 Speaker 1: the president for President of Resources for the Future, talking 468 00:27:17,920 --> 00:27:27,399 Speaker 1: about the Trump administration's rollback of emission standards. Thanks for 469 00:27:27,480 --> 00:27:30,120 Speaker 1: listening to the Bloomberg P and L podcast. You can 470 00:27:30,119 --> 00:27:34,560 Speaker 1: subscribe and listen to interviews at iTunes, SoundCloud, or whatever 471 00:27:34,880 --> 00:27:38,360 Speaker 1: podcast platform you prefer. I'm pim Fox. I'm out there 472 00:27:38,400 --> 00:27:41,439 Speaker 1: on Twitter at pim Fox. I'm out there on Twitter 473 00:27:41,560 --> 00:27:44,520 Speaker 1: at Lisa Abramo. It's one before the podcast. You can 474 00:27:44,520 --> 00:27:47,040 Speaker 1: always catch us worldwide on Bloomberg Radio