1 00:00:00,240 --> 00:00:02,599 Speaker 1: Hi everyone. Over the past few days, I've been getting 2 00:00:02,600 --> 00:00:06,120 Speaker 1: messages asking when the next episode is coming out, Listeners 3 00:00:06,160 --> 00:00:09,600 Speaker 1: trying to switch on but couldn't. Well, truth is in 4 00:00:09,680 --> 00:00:11,719 Speaker 1: our office. We've got a really nice studio that makes 5 00:00:11,720 --> 00:00:15,000 Speaker 1: things pretty easy when you're in the office. So when 6 00:00:15,040 --> 00:00:17,279 Speaker 1: I swapped the studio for the kitchen table, it took 7 00:00:17,280 --> 00:00:19,560 Speaker 1: a minute to get set up. So here we are. 8 00:00:19,920 --> 00:00:22,439 Speaker 1: We're back, and today's show it's going to be a 9 00:00:22,440 --> 00:00:24,840 Speaker 1: bit different. You may or may not have noticed that 10 00:00:24,880 --> 00:00:27,000 Speaker 1: we do every episode based on a specific piece of 11 00:00:27,000 --> 00:00:29,440 Speaker 1: research that BENF users can then go dig into to 12 00:00:29,440 --> 00:00:32,839 Speaker 1: get the details. Today, we won't be doing that, as 13 00:00:32,880 --> 00:00:34,839 Speaker 1: you might expect. The bulk of our research right now 14 00:00:34,880 --> 00:00:37,400 Speaker 1: is either about COVID nineteen or its impact on the 15 00:00:37,400 --> 00:00:39,960 Speaker 1: industries we cover, So we figured it would be useful 16 00:00:39,960 --> 00:00:42,400 Speaker 1: to do a show about process, about how we started 17 00:00:42,400 --> 00:00:44,480 Speaker 1: to look at this monstrous thing that that's voided every 18 00:00:44,479 --> 00:00:48,120 Speaker 1: forecast out there. Today, Dana and I talked with Albert Chung, 19 00:00:48,360 --> 00:00:50,919 Speaker 1: head of research for BENF. He'll walk us through how 20 00:00:50,960 --> 00:00:52,960 Speaker 1: we started to get our heads around the problem and 21 00:00:53,000 --> 00:00:56,440 Speaker 1: frameworks BNF analysts developed to explain what's happening in to 22 00:00:56,480 --> 00:00:59,680 Speaker 1: accommodate change. He also describes how all this will show 23 00:00:59,720 --> 00:01:01,800 Speaker 1: up in our research, what to look out for, and 24 00:01:01,800 --> 00:01:03,560 Speaker 1: what to make of it. If you'd like to follow 25 00:01:03,560 --> 00:01:07,120 Speaker 1: our ongoing COVID coverage, including our popular COVID Indicators reports, 26 00:01:07,400 --> 00:01:10,280 Speaker 1: head over to benf dot com slash series, where you 27 00:01:10,280 --> 00:01:12,880 Speaker 1: can subscribe to any of our fifty plus recurring publications. 28 00:01:13,200 --> 00:01:15,240 Speaker 1: When a new report is published, you'll get an alert 29 00:01:15,360 --> 00:01:17,960 Speaker 1: the second it comes out as a reminder beif does 30 00:01:18,000 --> 00:01:20,320 Speaker 1: not provide investment of strategy advice, and you can hear 31 00:01:20,319 --> 00:01:22,640 Speaker 1: a full disclaimer at the end of the show. I'm 32 00:01:22,640 --> 00:01:24,920 Speaker 1: Mark Taylor. You're with Aana Perkins and you're listening to 33 00:01:24,959 --> 00:01:35,920 Speaker 1: Switch on the BENF podcast. Hi Albert, thanks for your 34 00:01:36,000 --> 00:01:38,720 Speaker 1: joining us today. Hey Mark, thanks for having me. So 35 00:01:38,920 --> 00:01:41,679 Speaker 1: when did it become apparent that COVID nineteen was going 36 00:01:41,720 --> 00:01:44,280 Speaker 1: to become a dominant piece of the BIS research agenda. 37 00:01:44,800 --> 00:01:46,760 Speaker 1: Like a lot of things, it was very gradual and 38 00:01:46,800 --> 00:01:49,800 Speaker 1: then very sudden. I actually first regrete about this mystery 39 00:01:49,840 --> 00:01:53,720 Speaker 1: illness in Juhan sometime in mid December, but at that 40 00:01:53,760 --> 00:01:56,120 Speaker 1: stage it didn't seem that serious. It wasn't so connecting 41 00:01:56,160 --> 00:01:59,760 Speaker 1: humans humans, so really it was probably late January, when 42 00:01:59,760 --> 00:02:02,240 Speaker 1: our entire team in China was asked to work from 43 00:02:02,240 --> 00:02:05,200 Speaker 1: home and parts of China went into lockdown. Our team 44 00:02:05,280 --> 00:02:08,040 Speaker 1: started being infected. One person was actually placed into quarantine, 45 00:02:08,120 --> 00:02:11,240 Speaker 1: so it became very real for us. And that's when 46 00:02:11,840 --> 00:02:14,400 Speaker 1: our analysts in China actually really started thinking about what 47 00:02:14,440 --> 00:02:16,600 Speaker 1: the impacts of the COVID nineteen was, and they put 48 00:02:16,600 --> 00:02:19,080 Speaker 1: out this piece actually in mid February that said, assuming 49 00:02:19,080 --> 00:02:21,880 Speaker 1: the outbreak it's contained in Q one, then GP growth 50 00:02:21,919 --> 00:02:24,360 Speaker 1: will slow from six percent to about five percent this 51 00:02:24,440 --> 00:02:28,320 Speaker 1: year in China, And clearly, with hindsight that now seems far, 52 00:02:28,400 --> 00:02:32,399 Speaker 1: far too optimistic. And the story stayed at Asia specific 53 00:02:32,400 --> 00:02:35,280 Speaker 1: story for quite a while. Even in early March, in 54 00:02:35,320 --> 00:02:38,720 Speaker 1: the global team, we were talking about impact on wind 55 00:02:38,720 --> 00:02:40,679 Speaker 1: and solar and we weren't really sure if there was 56 00:02:40,720 --> 00:02:43,040 Speaker 1: going to be an impact. It was the middle of 57 00:02:43,120 --> 00:02:46,600 Speaker 1: March when it became really sort of unavoidably obvious that 58 00:02:46,600 --> 00:02:48,960 Speaker 1: we were going to have to rework our forecasts, rework 59 00:02:49,040 --> 00:02:52,160 Speaker 1: our research agenda, because this thing was going to really 60 00:02:52,160 --> 00:02:55,560 Speaker 1: dominate our work in the fores civil future. So you 61 00:02:55,600 --> 00:02:58,160 Speaker 1: realized you had to change attack. Things are being quickly, 62 00:02:58,200 --> 00:03:00,800 Speaker 1: perhaps quickly every seen before in our circuit at least, 63 00:03:00,960 --> 00:03:02,600 Speaker 1: how did you start to get your head around situation? 64 00:03:02,600 --> 00:03:04,519 Speaker 1: How did you get started? Well, I can't take any 65 00:03:04,560 --> 00:03:07,040 Speaker 1: credit at all for this. Our analyst teams, particularly teams 66 00:03:07,040 --> 00:03:10,040 Speaker 1: in Asia, jumped on this very quickly, and I think 67 00:03:10,160 --> 00:03:12,080 Speaker 1: very rightly said Look, the first thing we need to 68 00:03:12,080 --> 00:03:14,000 Speaker 1: do is to the best that we can track what's 69 00:03:14,040 --> 00:03:16,919 Speaker 1: actually happening on the ground. We launched a series of 70 00:03:17,040 --> 00:03:21,120 Speaker 1: indicator reports, so we call them are COVID nineteen indicators, 71 00:03:21,320 --> 00:03:23,560 Speaker 1: and they cover a range of different useful data points 72 00:03:23,560 --> 00:03:26,480 Speaker 1: that we've managed to gather from different markets to keep 73 00:03:26,480 --> 00:03:29,600 Speaker 1: a near real time tab on how the pandemic is 74 00:03:29,600 --> 00:03:32,040 Speaker 1: developing and the impact that it's having in different markets. 75 00:03:32,440 --> 00:03:35,000 Speaker 1: These indication reports go out weekly. We have one that 76 00:03:35,040 --> 00:03:38,040 Speaker 1: covers road transport. We're actually using live data from tom 77 00:03:38,080 --> 00:03:42,640 Speaker 1: Tom The tracks road congestion, which is not exactly traffic. 78 00:03:42,680 --> 00:03:45,680 Speaker 1: It's a measure of how slowly traffic is moving, which 79 00:03:45,680 --> 00:03:47,960 Speaker 1: is a proxy for how much traffic there is. As 80 00:03:47,960 --> 00:03:50,040 Speaker 1: of the latest report that we've put out, Beijing and 81 00:03:50,080 --> 00:03:53,560 Speaker 1: Shanghai are actually seeing rising congestion levels in the last 82 00:03:53,560 --> 00:03:56,880 Speaker 1: few weeks now seem to be approaching roughly normal levels 83 00:03:56,880 --> 00:04:00,120 Speaker 1: of congestion, whereas places like Hong Kong and Guangzo are 84 00:04:00,160 --> 00:04:03,960 Speaker 1: still below normal levels and places like New Dahi and 85 00:04:04,040 --> 00:04:07,120 Speaker 1: Mumbai those numbers are eighty nine down on normal levels. 86 00:04:07,560 --> 00:04:11,080 Speaker 1: We've got indicators in aviation indicators and the power sector. 87 00:04:11,840 --> 00:04:14,600 Speaker 1: How do we decide which industries were going to make 88 00:04:14,600 --> 00:04:17,000 Speaker 1: the cut as an indicator in which one weren't. From 89 00:04:17,000 --> 00:04:19,520 Speaker 1: a sort of energy transition perspective and energy at large, 90 00:04:19,600 --> 00:04:23,160 Speaker 1: clearly we're interested in demand for energy commodities first and foremost. 91 00:04:23,720 --> 00:04:26,360 Speaker 1: And the first thing that happened was people stopped moving around. 92 00:04:26,640 --> 00:04:30,000 Speaker 1: And when people start moving around, that's an oil story 93 00:04:30,040 --> 00:04:33,480 Speaker 1: because liquid fields get used to transport. But over time, 94 00:04:33,760 --> 00:04:38,280 Speaker 1: as we've seen the lockdowns in different countries proceed with 95 00:04:38,320 --> 00:04:41,520 Speaker 1: people staying at home more and businesses shutting down as well, 96 00:04:41,960 --> 00:04:44,159 Speaker 1: that started to leak into the power and gas center 97 00:04:44,200 --> 00:04:48,080 Speaker 1: as well. As an example here in Great Britain, we're 98 00:04:48,160 --> 00:04:51,839 Speaker 1: running at about fift below normal expectations in terms of 99 00:04:51,839 --> 00:04:57,800 Speaker 1: power demand on the grid. In India it's down and 100 00:04:57,880 --> 00:05:01,520 Speaker 1: as much as fifty down in places Punjaba and Rochester 101 00:05:01,600 --> 00:05:05,440 Speaker 1: in particular states within India. So we're tracking really anything 102 00:05:05,440 --> 00:05:09,240 Speaker 1: that's related to energy. But those indicators are having to 103 00:05:09,240 --> 00:05:12,599 Speaker 1: do with the here and now, right, how do those 104 00:05:12,800 --> 00:05:16,560 Speaker 1: intern impact our longer TAN forecast. Yeah, So the first 105 00:05:16,640 --> 00:05:19,760 Speaker 1: revision we made was in our SOLO forecast. We've essentially 106 00:05:19,800 --> 00:05:25,280 Speaker 1: deferred a chunk of the project pipeline from particularly in China, 107 00:05:25,320 --> 00:05:27,640 Speaker 1: because there's been some policy changes which mean that projects 108 00:05:27,640 --> 00:05:30,839 Speaker 1: are likely to blow over into the next year. That 109 00:05:30,880 --> 00:05:33,880 Speaker 1: means that we've actually revised our SOLO forecast for this 110 00:05:34,000 --> 00:05:38,080 Speaker 1: year down by eight percent, and that could mean that 111 00:05:38,120 --> 00:05:41,320 Speaker 1: this year is the first time solar installations actually decline 112 00:05:41,880 --> 00:05:44,440 Speaker 1: like SOLO has never not grown before. This could be 113 00:05:44,480 --> 00:05:47,279 Speaker 1: the first year on the wind side. Actually, we thought 114 00:05:47,360 --> 00:05:49,400 Speaker 1: this year was going to be an all time record 115 00:05:49,480 --> 00:05:53,200 Speaker 1: for installations. Now we've cut that wind forecast by twelve 116 00:05:53,800 --> 00:05:58,720 Speaker 1: again differring projects in We're still forecasting a record year 117 00:05:58,880 --> 00:06:02,280 Speaker 1: at the moment, but quite obvious that there's downside risk 118 00:06:02,360 --> 00:06:05,679 Speaker 1: to that. And just yesterday, I believe our US gas 119 00:06:05,720 --> 00:06:08,880 Speaker 1: team put out a new forecast for US gas storage 120 00:06:09,440 --> 00:06:13,000 Speaker 1: and they're now calling one billion q gas and storage 121 00:06:13,000 --> 00:06:16,280 Speaker 1: by the end of next winter up compared to a 122 00:06:16,320 --> 00:06:19,280 Speaker 1: sort of no COVID based case, which is effectively a 123 00:06:19,400 --> 00:06:22,400 Speaker 1: much much loosener market than we have previously been expecting. 124 00:06:22,520 --> 00:06:25,080 Speaker 1: So those are just sort of three things on the agenda. 125 00:06:25,120 --> 00:06:28,159 Speaker 1: But we're updating all of our forecasts, and I don't 126 00:06:28,160 --> 00:06:29,480 Speaker 1: think any of them are going to stay the same 127 00:06:29,520 --> 00:06:31,760 Speaker 1: after the next few weeks. So you started with a 128 00:06:31,800 --> 00:06:35,360 Speaker 1: delay in the most basic case, I guess, and then 129 00:06:35,560 --> 00:06:38,400 Speaker 1: you move into how these things have impacked every part 130 00:06:38,440 --> 00:06:41,159 Speaker 1: of our forecast, I guess, into the more structural changes, 131 00:06:41,200 --> 00:06:43,480 Speaker 1: I guess you could say, so, not only does COVID 132 00:06:43,560 --> 00:06:49,479 Speaker 1: nineteen really change everything for these industries and therefore all 133 00:06:49,520 --> 00:06:52,880 Speaker 1: of our forecasts into the future, but to some extent, 134 00:06:52,880 --> 00:06:55,960 Speaker 1: it may also change the way that we talk about everything, 135 00:06:56,000 --> 00:06:59,960 Speaker 1: because from a time standpoint, it seems like things are 136 00:07:00,600 --> 00:07:05,560 Speaker 1: changing so quickly that a usual quarterly, half yearly may 137 00:07:05,600 --> 00:07:08,600 Speaker 1: not be enough. So how do you decide how quickly 138 00:07:08,640 --> 00:07:11,880 Speaker 1: and how often you actually need to update on some 139 00:07:12,000 --> 00:07:15,160 Speaker 1: of the industries that we're doing these indicators for. Yeah, 140 00:07:15,200 --> 00:07:17,760 Speaker 1: I mean, historically we've served a few different audiences with 141 00:07:17,880 --> 00:07:21,760 Speaker 1: different time horizons. In terms of the commodity markets, how 142 00:07:21,800 --> 00:07:24,600 Speaker 1: a gas oil, we need to be really timely in 143 00:07:24,600 --> 00:07:27,360 Speaker 1: our analysis, so we've been doing weeklies in many of 144 00:07:27,360 --> 00:07:30,400 Speaker 1: those markets, for a long time, and clearly with COVID nineteen, 145 00:07:30,760 --> 00:07:33,960 Speaker 1: that kind of real time analysis becomes even more important 146 00:07:34,000 --> 00:07:36,120 Speaker 1: because new information comes to light that changes our view 147 00:07:36,200 --> 00:07:38,760 Speaker 1: every day, and so we've got to do that really rapidly. 148 00:07:39,360 --> 00:07:41,320 Speaker 1: And then in our other sectors, if you think about 149 00:07:41,360 --> 00:07:45,160 Speaker 1: renewable energy, electric vehicles, and so on, we normally update 150 00:07:45,200 --> 00:07:48,280 Speaker 1: these numbers quarterly. Some of the EV sales numbers we 151 00:07:48,280 --> 00:07:52,480 Speaker 1: look at monthly. But the situation changing so quickly that 152 00:07:52,520 --> 00:07:54,480 Speaker 1: we just had to respond more quickly. And I think 153 00:07:54,480 --> 00:07:56,880 Speaker 1: that's the same challenge that all businesses are having right now. 154 00:07:56,920 --> 00:07:59,640 Speaker 1: It's the flow of news that's coming through every single day. 155 00:08:00,120 --> 00:08:02,160 Speaker 1: Just got to keep monstoring it and keep on all sides. 156 00:08:02,800 --> 00:08:07,120 Speaker 1: Forecasts are tough in the best of times, and we 157 00:08:07,320 --> 00:08:11,560 Speaker 1: like to do scenarios rather than forecast per se. But 158 00:08:11,640 --> 00:08:14,560 Speaker 1: even that people misconstrue those is like, Okay, we're talking 159 00:08:14,600 --> 00:08:16,600 Speaker 1: a bit about the future and what could happen there? 160 00:08:17,040 --> 00:08:19,960 Speaker 1: What point do we have enough information to actually be 161 00:08:20,040 --> 00:08:22,720 Speaker 1: able to reasonably talk about the future. And I think, 162 00:08:23,200 --> 00:08:25,640 Speaker 1: you know, maybe just even rewinding, if we're looking at 163 00:08:25,720 --> 00:08:31,160 Speaker 1: this January February March timeline from the point at which 164 00:08:31,560 --> 00:08:34,680 Speaker 1: we started to see changes in human behavior and changes 165 00:08:34,800 --> 00:08:38,640 Speaker 1: in company's behavior due to a lot more people being 166 00:08:38,679 --> 00:08:41,200 Speaker 1: at home and government regulations. At what point were we 167 00:08:41,280 --> 00:08:44,920 Speaker 1: able to start to say something meaningful in China, and 168 00:08:44,960 --> 00:08:48,480 Speaker 1: then in Europe, and then maybe in the America's I 169 00:08:48,480 --> 00:08:50,960 Speaker 1: think everybody has had to throw away that any forecast 170 00:08:51,000 --> 00:08:54,160 Speaker 1: that was made before about February March this year, they're 171 00:08:54,160 --> 00:08:58,040 Speaker 1: all wrong. And anyone who tells you that they've got 172 00:08:58,040 --> 00:09:02,680 Speaker 1: a forecast that you can invest against or really believe in, 173 00:09:03,160 --> 00:09:06,600 Speaker 1: it's just not really credible. And so that's a big 174 00:09:06,640 --> 00:09:09,280 Speaker 1: part of the reason why we're incorporating a set of 175 00:09:09,320 --> 00:09:12,000 Speaker 1: scenarios into our analysis right now. So you knew this 176 00:09:12,080 --> 00:09:14,760 Speaker 1: situation would keep evolving and you need to say smart 177 00:09:14,760 --> 00:09:17,760 Speaker 1: things about it. So you introduced this thing called scenarios 178 00:09:17,800 --> 00:09:19,880 Speaker 1: to be able to accommodate different things that could happen. 179 00:09:20,160 --> 00:09:21,720 Speaker 1: Could you tell us a bit more about those and 180 00:09:21,720 --> 00:09:23,560 Speaker 1: how those came to be? Yeah, sure, So what was 181 00:09:23,600 --> 00:09:27,040 Speaker 1: extremely obvious was that any forecast made over the last 182 00:09:27,040 --> 00:09:30,280 Speaker 1: few months probably needs to be thrown away. And so 183 00:09:30,440 --> 00:09:33,400 Speaker 1: when you're in that situation extreme uncertainty, which we all 184 00:09:33,440 --> 00:09:36,360 Speaker 1: are in, it's better from my point of view, to 185 00:09:36,440 --> 00:09:38,760 Speaker 1: embrace down certain, to acknowledge it, and actually try and 186 00:09:38,760 --> 00:09:42,000 Speaker 1: incorporate into your thinking. Scenarios a great way of doing that. 187 00:09:42,360 --> 00:09:44,560 Speaker 1: So essentially what we did was we said, we're gonna 188 00:09:44,760 --> 00:09:48,520 Speaker 1: come up with three scenarios for how the pandemic might 189 00:09:48,600 --> 00:09:52,600 Speaker 1: proceed globally and make sure that in all of our 190 00:09:52,640 --> 00:09:55,480 Speaker 1: analysis across the n F we think about all these 191 00:09:55,520 --> 00:09:58,200 Speaker 1: three scenarios and how they might impact the sectors that 192 00:09:58,240 --> 00:10:00,839 Speaker 1: we cover. And that's really powerful, but that acknowledges the 193 00:10:00,880 --> 00:10:03,040 Speaker 1: fact that we simply don't know. Nobody knows how the 194 00:10:03,040 --> 00:10:05,280 Speaker 1: pannem is going to play out. But it also means 195 00:10:05,320 --> 00:10:07,720 Speaker 1: that our forecasts will have a bit more resilience to 196 00:10:07,760 --> 00:10:11,520 Speaker 1: the changing news. Every day we can monitor the news 197 00:10:11,559 --> 00:10:13,920 Speaker 1: and talk about which of our scenarios looks like it's 198 00:10:13,960 --> 00:10:17,760 Speaker 1: becoming more or less likely as the pandemic develops. So, 199 00:10:17,800 --> 00:10:19,840 Speaker 1: in terms of how they're built, the main thing is 200 00:10:19,960 --> 00:10:22,600 Speaker 1: scenarios all about what are the key unknowns that you 201 00:10:22,640 --> 00:10:26,120 Speaker 1: want to explore, and so we wanted to explore really 202 00:10:26,120 --> 00:10:30,920 Speaker 1: the sort of medical and epidemiological unknowns which are around 203 00:10:31,200 --> 00:10:34,000 Speaker 1: how is the virus going to develop? Key things like 204 00:10:34,080 --> 00:10:36,040 Speaker 1: will it fade in warm and weather? Will it come 205 00:10:36,040 --> 00:10:38,880 Speaker 1: back for a second way next autumn or winter? Will 206 00:10:38,920 --> 00:10:42,320 Speaker 1: treatments and vaccines be found? What are the real infection rates? 207 00:10:42,320 --> 00:10:44,240 Speaker 1: For example, are they really as low as we are 208 00:10:44,280 --> 00:10:46,640 Speaker 1: being told or is it more of the population already 209 00:10:46,640 --> 00:10:48,680 Speaker 1: has it, which would actually be good news in the 210 00:10:48,720 --> 00:10:51,840 Speaker 1: long term. How quickly can countries ramp up their mass 211 00:10:51,920 --> 00:10:55,440 Speaker 1: testing and contact tracing programs, which would then mean that 212 00:10:55,480 --> 00:10:57,800 Speaker 1: we can ease some of the social distancing measures that 213 00:10:57,840 --> 00:11:01,040 Speaker 1: are currently in place. All of those things are unknown 214 00:11:01,080 --> 00:11:04,160 Speaker 1: and therefore make for really good variables in a scenario, 215 00:11:04,200 --> 00:11:08,760 Speaker 1: So we package those into three scenarios that eventually lead 216 00:11:08,800 --> 00:11:12,200 Speaker 1: to how long does the pandemic actually last? For where 217 00:11:12,240 --> 00:11:15,160 Speaker 1: are we getting that sort of information from to put 218 00:11:15,240 --> 00:11:18,800 Speaker 1: in as a variable. Because the team that you lead 219 00:11:18,920 --> 00:11:22,559 Speaker 1: our energy analysts, So presumably they've not spent a lot 220 00:11:22,559 --> 00:11:27,480 Speaker 1: of their career looking at different impacts of viruses and things. Yeah, 221 00:11:27,480 --> 00:11:30,480 Speaker 1: that's a good question. So we're not medical experts at all. 222 00:11:30,600 --> 00:11:33,360 Speaker 1: We don't have public health people on our staff, so 223 00:11:33,440 --> 00:11:37,000 Speaker 1: we're operating off the same available information that other people have. 224 00:11:37,679 --> 00:11:40,760 Speaker 1: We read, for example, the Imperial College paper that was 225 00:11:40,960 --> 00:11:44,800 Speaker 1: widely distributed over the last couple of weeks, we read 226 00:11:44,800 --> 00:11:47,920 Speaker 1: some papers about how the ninet team Spanish flu pandemic 227 00:11:47,920 --> 00:11:50,680 Speaker 1: played out globally. We've talked to one or two people 228 00:11:50,679 --> 00:11:54,520 Speaker 1: who have views as well, and we've deliberately kept our 229 00:11:54,559 --> 00:11:57,760 Speaker 1: scenarios pretty open minded in terms of what you would 230 00:11:57,800 --> 00:12:00,160 Speaker 1: have to believe feature them to come true, because we 231 00:12:00,200 --> 00:12:03,280 Speaker 1: acknowledge that we have no real epidemiological expertise, so we 232 00:12:03,400 --> 00:12:06,160 Speaker 1: just framed is sort of wide range of possibilities to 233 00:12:06,200 --> 00:12:09,560 Speaker 1: make sure that we're covering enough basis. So scenario one 234 00:12:09,720 --> 00:12:14,839 Speaker 1: is a single way pandemic, which basically assumes that most 235 00:12:14,840 --> 00:12:19,240 Speaker 1: countries have three months of pretty heavy social distancing measures 236 00:12:19,280 --> 00:12:23,160 Speaker 1: to control their outbreaks, but that after the roughly three months, 237 00:12:23,160 --> 00:12:26,360 Speaker 1: then things can start to return to normal with a 238 00:12:26,559 --> 00:12:30,200 Speaker 1: ramp up in mass testing, contact tracing, and so on. 239 00:12:30,760 --> 00:12:32,800 Speaker 1: But if you believe that, then you know, if everybody 240 00:12:32,800 --> 00:12:35,839 Speaker 1: has a three month outbreak, then probably by the second 241 00:12:35,880 --> 00:12:38,679 Speaker 1: half of the year, most of the country's have been 242 00:12:38,720 --> 00:12:42,400 Speaker 1: through that, and your economic recovery can probably start before 243 00:12:42,440 --> 00:12:45,400 Speaker 1: the end of the year. So that scenario one, Scenario 244 00:12:45,440 --> 00:12:49,840 Speaker 1: two is in a slightly less optimistic situation, you might 245 00:12:49,880 --> 00:12:53,240 Speaker 1: have multiple waves of this pandemic, and that's what happened 246 00:12:53,280 --> 00:12:55,320 Speaker 1: in nineteen eighteen. There were three waves over the course 247 00:12:55,360 --> 00:12:57,480 Speaker 1: of a year, and so we've assumed it looks a 248 00:12:57,520 --> 00:12:59,679 Speaker 1: little bit like that. Countries go through sort of one 249 00:12:59,760 --> 00:13:02,640 Speaker 1: year a shock. It might not be exactly in two 250 00:13:02,760 --> 00:13:04,720 Speaker 1: or three waves. It might be that there's sort of 251 00:13:05,040 --> 00:13:08,200 Speaker 1: many on and off cycles of social distancing that are 252 00:13:08,240 --> 00:13:12,360 Speaker 1: required to keep healthcare systems running. But essentially the outcome 253 00:13:12,400 --> 00:13:14,960 Speaker 1: of all of that is that this massive economic shock 254 00:13:15,000 --> 00:13:18,920 Speaker 1: actually lasts into the beginning and it's only the middle 255 00:13:19,840 --> 00:13:23,440 Speaker 1: where recovery begins. And this is a bit bleaker because 256 00:13:24,240 --> 00:13:26,839 Speaker 1: government stimulus can keep businesses running for three months, and 257 00:13:26,840 --> 00:13:28,960 Speaker 1: there's a three month shock, you can keep people in 258 00:13:29,000 --> 00:13:31,800 Speaker 1: their jobs. But if it's a one year shock, that 259 00:13:31,880 --> 00:13:35,160 Speaker 1: starts to look much harder, and so you're looking at 260 00:13:35,240 --> 00:13:38,240 Speaker 1: more businesses going bankrupt, workers being displaced, and so on. 261 00:13:39,120 --> 00:13:42,080 Speaker 1: And then scenario three years even worse. We call it 262 00:13:42,240 --> 00:13:46,040 Speaker 1: enduring pandemic scenario. And in that scenario, this thing drags 263 00:13:46,040 --> 00:13:50,160 Speaker 1: on for eighteen months and the end comes when a 264 00:13:50,240 --> 00:13:52,760 Speaker 1: treatment is scaled up or a vaccine is scaled up. 265 00:13:53,240 --> 00:13:56,000 Speaker 1: In this scenario, nothing else works until one of those 266 00:13:56,000 --> 00:13:59,960 Speaker 1: two things arrives, and that happens sometime around eighteen none 267 00:14:00,120 --> 00:14:03,160 Speaker 1: from now, which pushes out the economic recovery out towards 268 00:14:03,160 --> 00:14:07,199 Speaker 1: the latter half of probably the end we're really talking 269 00:14:07,200 --> 00:14:09,240 Speaker 1: about the depression at that point, you know, really not 270 00:14:09,320 --> 00:14:12,320 Speaker 1: a happy place from an economic standpoint. I mean, I 271 00:14:12,360 --> 00:14:14,800 Speaker 1: know this isn't a question maybe we should answer, but 272 00:14:14,880 --> 00:14:17,400 Speaker 1: there's been effort. Do you have a view on which 273 00:14:17,400 --> 00:14:20,800 Speaker 1: scenario could be which seems most realistic? Yeah, that's a 274 00:14:20,800 --> 00:14:24,560 Speaker 1: really tough question. A couple of observations. One is, I 275 00:14:24,600 --> 00:14:27,760 Speaker 1: think scenario one, which is currently our most optimistic one, 276 00:14:29,200 --> 00:14:33,800 Speaker 1: was probably the most pessimistic scenario that most economists would 277 00:14:33,840 --> 00:14:36,840 Speaker 1: have even entertained a month ago or two months ago. 278 00:14:37,440 --> 00:14:39,960 Speaker 1: And so I think where we are in terms of 279 00:14:40,000 --> 00:14:43,240 Speaker 1: like the consensus view, if you talk to forecasters out there, 280 00:14:43,760 --> 00:14:45,800 Speaker 1: I would probably guess that most people think we're in 281 00:14:45,800 --> 00:14:50,280 Speaker 1: scenario one already, and the signposts are pointing towards scenario 282 00:14:50,360 --> 00:14:53,720 Speaker 1: to I'll give you a couple of examples. Both Singapore 283 00:14:53,880 --> 00:14:56,640 Speaker 1: and Hong Kong, which had early outbreaks and got them 284 00:14:56,720 --> 00:15:01,640 Speaker 1: under control, have both increased their intervention measures in the 285 00:15:01,720 --> 00:15:04,240 Speaker 1: last week or two, which to me is a signpost 286 00:15:04,360 --> 00:15:06,800 Speaker 1: that says even if you control it at first, it 287 00:15:06,840 --> 00:15:08,800 Speaker 1: doesn't mean you're out of the words. It seems like 288 00:15:09,120 --> 00:15:11,800 Speaker 1: through other things, like they're having important cases from other countries, 289 00:15:12,280 --> 00:15:14,680 Speaker 1: it seems like they have to reintroduce measures. So that 290 00:15:14,760 --> 00:15:17,360 Speaker 1: to me is a signpost towards scenario too. And how 291 00:15:17,360 --> 00:15:19,240 Speaker 1: will you show up in our work? Like so, if 292 00:15:19,280 --> 00:15:21,480 Speaker 1: I'm a user looking at BINGF researcher, I mean you 293 00:15:21,520 --> 00:15:24,320 Speaker 1: said it's going to prevate like all of a report 294 00:15:24,360 --> 00:15:27,400 Speaker 1: in the coming months. Plus should I be looking for 295 00:15:27,440 --> 00:15:29,960 Speaker 1: three lines you each chart? Or how should I be 296 00:15:30,000 --> 00:15:32,440 Speaker 1: looking out for this? Wherever we have a forecast, I'm 297 00:15:32,480 --> 00:15:36,400 Speaker 1: encouraging our teams to use these three scenarios. Now, the 298 00:15:36,440 --> 00:15:39,840 Speaker 1: forecast revisions I mentioned earlier on solo wind and US casts, 299 00:15:40,280 --> 00:15:43,880 Speaker 1: those are all scenario one forecast, single way pandemic, three 300 00:15:43,880 --> 00:15:47,000 Speaker 1: month shock, end of your recovery. What you'll see as 301 00:15:47,000 --> 00:15:48,880 Speaker 1: a client in the coming month or so is that 302 00:15:48,960 --> 00:15:51,680 Speaker 1: more of our research will explore all three of the possibilities. 303 00:15:51,920 --> 00:15:53,480 Speaker 1: Some of it will be qualitated, so it might not 304 00:15:53,520 --> 00:15:56,080 Speaker 1: be aligned on a chart. It might be a commentary 305 00:15:56,160 --> 00:15:59,160 Speaker 1: on the impacts of these three possible scenarios. Some of 306 00:15:59,160 --> 00:16:01,080 Speaker 1: it will be quantity too, And you'll see minds on 307 00:16:01,120 --> 00:16:02,960 Speaker 1: tcharts and so on. And at the same time we'll 308 00:16:03,000 --> 00:16:06,320 Speaker 1: be working closely with our colleagues in bluemog Economics. They 309 00:16:06,360 --> 00:16:09,160 Speaker 1: are also updating their scenarios and we'll be working very 310 00:16:09,160 --> 00:16:11,440 Speaker 1: clessly with them and try to understand how we can 311 00:16:11,440 --> 00:16:12,960 Speaker 1: make the best use of their work in our b 312 00:16:13,080 --> 00:16:15,840 Speaker 1: network as well. I've already started to see some of 313 00:16:15,880 --> 00:16:20,000 Speaker 1: the initial data that leads to some changes also in emissions, 314 00:16:20,560 --> 00:16:24,200 Speaker 1: which is in many ways linked to the sectors that 315 00:16:24,240 --> 00:16:27,520 Speaker 1: we cover as well. Is there anything you have initially 316 00:16:27,560 --> 00:16:31,600 Speaker 1: started to see there and how does it change in 317 00:16:31,840 --> 00:16:35,640 Speaker 1: emissions play out along these three scenarios, because there is 318 00:16:35,640 --> 00:16:39,640 Speaker 1: a big difference between a blip and something that may 319 00:16:39,680 --> 00:16:43,480 Speaker 1: be a bit longer term. Yeah, I mean emissions are 320 00:16:43,480 --> 00:16:47,000 Speaker 1: definitely going to be down this year essentially, pretty substantially. Clearly, 321 00:16:47,000 --> 00:16:50,640 Speaker 1: that's nothing to celebrate. Stopping the economy and everybody's staying 322 00:16:50,640 --> 00:16:52,600 Speaker 1: at home forever. It is not the solution to climbachation. 323 00:16:52,640 --> 00:16:56,840 Speaker 1: So let's there's a school of thought that says we've 324 00:16:56,880 --> 00:17:00,000 Speaker 1: now already seen the absolute peak of man made emissions, 325 00:17:02,240 --> 00:17:05,160 Speaker 1: will now have been the peak of emissions, and we'll 326 00:17:05,160 --> 00:17:07,880 Speaker 1: never get back to that level. If that's true, we'll 327 00:17:07,920 --> 00:17:09,800 Speaker 1: have probably have brought the peak forward by six or 328 00:17:09,800 --> 00:17:12,359 Speaker 1: eight years. Like I think people were sort of thinking 329 00:17:12,480 --> 00:17:14,840 Speaker 1: emissions would be later in this decade, so so that 330 00:17:14,840 --> 00:17:18,080 Speaker 1: would be bring it forward a long way. I think 331 00:17:18,119 --> 00:17:20,200 Speaker 1: to believe that, you'd had to believe that the shock 332 00:17:20,400 --> 00:17:22,200 Speaker 1: lasts for more than a few months. I think you're 333 00:17:22,200 --> 00:17:25,080 Speaker 1: talking about our second or third scenarios, because if you 334 00:17:25,119 --> 00:17:28,359 Speaker 1: have a rapid economic recovery, I think emissions would be 335 00:17:28,359 --> 00:17:30,399 Speaker 1: back to previous trajectory. I think you'd be back onto 336 00:17:30,440 --> 00:17:33,800 Speaker 1: this growth curve. If, on the other hand, we're looking 337 00:17:33,800 --> 00:17:37,720 Speaker 1: at a more prolonged pandemic and longer recession, I think 338 00:17:37,760 --> 00:17:41,800 Speaker 1: we might find that the low carbon transition might have 339 00:17:41,920 --> 00:17:45,080 Speaker 1: proceeded further before the recovery really starts to take hold. So, 340 00:17:45,160 --> 00:17:49,800 Speaker 1: for example, if a load of high carbon infrastructure gets 341 00:17:49,840 --> 00:17:53,359 Speaker 1: retired or mothballs during a recession or a depression, and 342 00:17:53,359 --> 00:17:57,560 Speaker 1: in the meantime the costs of clean alternatives continue to decline, 343 00:17:58,040 --> 00:18:01,000 Speaker 1: then you might not see some of that legacy high 344 00:18:01,000 --> 00:18:05,480 Speaker 1: carbon infrastructure come back online when the recovery begins. The 345 00:18:05,520 --> 00:18:08,880 Speaker 1: shot onneswers nobody knows, but it's a really valid question. 346 00:18:09,000 --> 00:18:11,440 Speaker 1: I think we're going to think more about that. Well, 347 00:18:11,440 --> 00:18:14,240 Speaker 1: COVID nineteen is nothing to celebrate if we look at 348 00:18:14,280 --> 00:18:16,600 Speaker 1: emissions in isolation. The fact that we might have reached 349 00:18:16,600 --> 00:18:19,440 Speaker 1: our peak is something that could potentially be a very 350 00:18:19,440 --> 00:18:22,480 Speaker 1: good thing. As we're headed into a period where there's 351 00:18:22,520 --> 00:18:26,199 Speaker 1: going to need to be stimulus in economies around the world. 352 00:18:27,000 --> 00:18:29,240 Speaker 1: There are rumors flying about that some of this could 353 00:18:29,240 --> 00:18:34,480 Speaker 1: be tied to different green incentives. What have you heard 354 00:18:34,520 --> 00:18:37,600 Speaker 1: about green stimulus to date? Surprisingly, there's been a lot 355 00:18:37,640 --> 00:18:40,040 Speaker 1: of talk about green students. And I'd say that surprising 356 00:18:40,160 --> 00:18:43,720 Speaker 1: because the focus right now is rightly on trying to 357 00:18:44,600 --> 00:18:47,920 Speaker 1: keep businesses from going bankrupt, try to keep people employed, 358 00:18:47,920 --> 00:18:49,879 Speaker 1: and keep the house and fair, and deal with the 359 00:18:49,880 --> 00:18:53,760 Speaker 1: healthcare situation. And if this turns out to be a 360 00:18:53,800 --> 00:18:56,080 Speaker 1: deep but short recession and recovery will be a lot 361 00:18:56,119 --> 00:18:59,159 Speaker 1: easier business stay afloat. And that's the right focus, and 362 00:18:59,200 --> 00:19:00,879 Speaker 1: that's what we're seeing here in the UK, for example, 363 00:19:00,880 --> 00:19:03,440 Speaker 1: there's this three billion pound Learned Guarantee program and the 364 00:19:03,480 --> 00:19:06,960 Speaker 1: government's committing to cover employees wages if they're furloughed, etcetera. 365 00:19:07,440 --> 00:19:11,199 Speaker 1: And the US has two trillion dollar stimulus package, and 366 00:19:11,280 --> 00:19:13,720 Speaker 1: all of that is rightly focused on the short term. 367 00:19:13,760 --> 00:19:15,720 Speaker 1: Having said that, clearly there's a lot of people now 368 00:19:15,760 --> 00:19:19,359 Speaker 1: talking about what recovery packages could look like when the 369 00:19:19,400 --> 00:19:23,280 Speaker 1: time comes to start stimulating the economy again, and how 370 00:19:23,359 --> 00:19:24,840 Speaker 1: much of that should be green. So I think there 371 00:19:24,880 --> 00:19:28,480 Speaker 1: are some opportunities to push a sort of climate agenda 372 00:19:28,640 --> 00:19:31,840 Speaker 1: in any recovery package. So the things that lend themselves 373 00:19:31,840 --> 00:19:35,240 Speaker 1: really well to stimulus are projects that are quote unquote 374 00:19:35,240 --> 00:19:37,639 Speaker 1: shovel ready, they're ready to go, ready to ramp up, 375 00:19:37,800 --> 00:19:40,760 Speaker 1: and projects that create jobs. So I think things like 376 00:19:40,800 --> 00:19:46,199 Speaker 1: renewable power, energy storage, EV charging infrastructure, those are supply 377 00:19:46,280 --> 00:19:47,960 Speaker 1: chains that are ready to ramp up if they have 378 00:19:48,040 --> 00:19:50,879 Speaker 1: project developers that are ready to move forward with sites 379 00:19:51,080 --> 00:19:54,120 Speaker 1: in some cases that are already identified. So in terms 380 00:19:54,119 --> 00:19:56,160 Speaker 1: of job creation, there will be quick wins, and there'll 381 00:19:56,160 --> 00:19:59,280 Speaker 1: be quick wins for the climate as well, energy efficiency 382 00:19:59,280 --> 00:20:01,360 Speaker 1: as well as a few one we could make huge 383 00:20:01,400 --> 00:20:04,280 Speaker 1: improvements to our building stock. I would bake in huge 384 00:20:04,280 --> 00:20:06,880 Speaker 1: carbon reductions for the coming decade, and that would create 385 00:20:06,880 --> 00:20:09,679 Speaker 1: a lot of jobs in local communities as well. And 386 00:20:09,680 --> 00:20:12,080 Speaker 1: I'd also love to see some capital going into circular 387 00:20:12,119 --> 00:20:14,880 Speaker 1: economy for example, I mean, I could see increase investment 388 00:20:14,920 --> 00:20:17,560 Speaker 1: into recycling capacity. So I think there are a lot 389 00:20:17,600 --> 00:20:20,679 Speaker 1: of things that people can see aren't doable, and I 390 00:20:20,680 --> 00:20:24,040 Speaker 1: think that the early conversations we're seeing now are about 391 00:20:24,400 --> 00:20:27,280 Speaker 1: positioning some of those conversations so that they're ready to 392 00:20:27,359 --> 00:20:31,520 Speaker 1: go when we're ready to really talk about recovery. So 393 00:20:32,400 --> 00:20:33,960 Speaker 1: a lot of our clients use our research as a 394 00:20:34,040 --> 00:20:37,239 Speaker 1: guide or a data point or an input, but then 395 00:20:37,280 --> 00:20:38,760 Speaker 1: they have to still go and do their own to 396 00:20:38,800 --> 00:20:40,919 Speaker 1: figure out how things are going to impact their company 397 00:20:40,920 --> 00:20:43,800 Speaker 1: and their strategy going forward. Is there anything that you 398 00:20:43,920 --> 00:20:47,560 Speaker 1: found in doing your researchers setting the agenda for BNS 399 00:20:47,640 --> 00:20:49,679 Speaker 1: research that you'd recommend as they try to get their 400 00:20:49,680 --> 00:20:51,680 Speaker 1: head around the impact of COVID nineteen and the impact 401 00:20:51,720 --> 00:20:54,000 Speaker 1: in their company. The companies I've spoken to, the clients 402 00:20:54,040 --> 00:20:56,040 Speaker 1: I've spoken to are already asking most of the right 403 00:20:56,119 --> 00:20:58,800 Speaker 1: questions and thinking about the right issues first and foremost 404 00:20:58,800 --> 00:21:00,600 Speaker 1: worrying about that people how to keep and safe. They're 405 00:21:00,600 --> 00:21:04,560 Speaker 1: thinking about keeping their operations running wherever possible. They're thinking 406 00:21:04,960 --> 00:21:08,280 Speaker 1: crucially about their suppliers, their supplier supplies and the whole 407 00:21:08,280 --> 00:21:11,480 Speaker 1: supply chain, and whether those companies need help, because that's 408 00:21:11,560 --> 00:21:14,119 Speaker 1: quite hard because the visibility isn't always there. I've spoken 409 00:21:14,200 --> 00:21:17,320 Speaker 1: to auto companies, for example, who are really working to 410 00:21:17,359 --> 00:21:20,720 Speaker 1: try and figure out further upstream which companies and countries 411 00:21:20,760 --> 00:21:22,960 Speaker 1: are actually exposed to that they hadn't necessarily had to 412 00:21:23,000 --> 00:21:26,080 Speaker 1: think about before. But I think companies are figuring that out. 413 00:21:26,560 --> 00:21:28,480 Speaker 1: I think the only thing I would add is to 414 00:21:29,359 --> 00:21:32,840 Speaker 1: really think about signposts as a way of navigating uncertainty. 415 00:21:33,200 --> 00:21:35,840 Speaker 1: We've developed our three scenarios, so the key thing for 416 00:21:35,920 --> 00:21:38,399 Speaker 1: us now is every day every week to read the news, 417 00:21:38,880 --> 00:21:42,399 Speaker 1: look at what's happening, and ask ourselves, does today's news 418 00:21:42,560 --> 00:21:45,800 Speaker 1: move us more towards scenario one or two or three? 419 00:21:46,200 --> 00:21:48,280 Speaker 1: And how should that change what we do in our business. 420 00:21:48,720 --> 00:21:51,320 Speaker 1: I think every company will have slightly different scenarios and 421 00:21:51,359 --> 00:21:54,000 Speaker 1: slightly different signposts they should be looking for. But my 422 00:21:54,040 --> 00:21:57,159 Speaker 1: advice would be too carefully and deliberately define those and 423 00:21:57,200 --> 00:22:00,240 Speaker 1: pay attention to them over the coming months. So it's lair. 424 00:22:00,480 --> 00:22:03,199 Speaker 1: The future is uncertain, but we're tracking a number of 425 00:22:03,240 --> 00:22:05,359 Speaker 1: things to make sure that we're staying on top of 426 00:22:05,880 --> 00:22:09,800 Speaker 1: how this story of all of our lives is constantly evolving. 427 00:22:09,880 --> 00:22:12,320 Speaker 1: So Albert, thank you very much for giving us a 428 00:22:12,320 --> 00:22:16,360 Speaker 1: little bit of insight today into the research process and 429 00:22:16,400 --> 00:22:18,760 Speaker 1: how we really have had to change how we look 430 00:22:18,760 --> 00:22:22,679 Speaker 1: at the future because of everything that's happening right now. Albert, 431 00:22:22,720 --> 00:22:25,120 Speaker 1: thank you for joining Mark and I today pleasure. Thank 432 00:22:25,160 --> 00:22:30,119 Speaker 1: you for having me. Bloomberg an e F is a 433 00:22:30,160 --> 00:22:33,000 Speaker 1: service provided by Bloomberg Finance LP and its affiliates. This 434 00:22:33,040 --> 00:22:35,760 Speaker 1: recording does not constitute, nor should it be construed as 435 00:22:35,880 --> 00:22:39,760 Speaker 1: investment advice, investment recommendations, or a recommendation as to an 436 00:22:39,760 --> 00:22:42,639 Speaker 1: investment or other strategy. Bloombergun e F should not be 437 00:22:42,720 --> 00:22:46,200 Speaker 1: considered as information sufficient upon which to base an investment decision. 438 00:22:46,359 --> 00:22:49,720 Speaker 1: Neither Bloomberg Finance LP nor any of its affiliates makes 439 00:22:49,800 --> 00:22:53,080 Speaker 1: any representation or warranty as to the accuracy or completeness 440 00:22:53,080 --> 00:22:56,040 Speaker 1: of the information contained in this recording, and any liability 441 00:22:56,080 --> 00:22:58,360 Speaker 1: as a result of this recording is expressly disclaimed.