1 00:00:03,920 --> 00:00:07,880 Speaker 1: June just rains and never stops thirty days and spoils 2 00:00:07,920 --> 00:00:12,800 Speaker 1: the crops. Hello Stephanomics, here the podcast that brings you 3 00:00:12,840 --> 00:00:16,400 Speaker 1: the global economy, and if you'll forgive the indulgence, a 4 00:00:16,480 --> 00:00:19,400 Speaker 1: bit of Flanders and Swan. That was from the Song 5 00:00:19,440 --> 00:00:22,520 Speaker 1: of the Weather, written back in the nineteen fifties by 6 00:00:22,640 --> 00:00:26,040 Speaker 1: my father Michael Flanders and his partner Donald Swan. We 7 00:00:26,200 --> 00:00:29,480 Speaker 1: Brits were famous for talking about the weather long before 8 00:00:29,480 --> 00:00:33,640 Speaker 1: it was fashionable. But now everyone's doing it and it's 9 00:00:33,680 --> 00:00:38,120 Speaker 1: no joke. Climate change is an inescapable part of our 10 00:00:38,200 --> 00:00:41,279 Speaker 1: daily lives, with a growing impact on the economy and 11 00:00:41,400 --> 00:00:46,280 Speaker 1: policy in most of the world. Increasingly extreme weather gets 12 00:00:46,360 --> 00:00:49,960 Speaker 1: top billing on the nightly news. We're also becoming better 13 00:00:50,000 --> 00:00:54,279 Speaker 1: informed about weather phenomena such as El Nino. So as 14 00:00:54,320 --> 00:00:57,560 Speaker 1: you probably already know, al Nino is a period of 15 00:00:57,600 --> 00:01:00,440 Speaker 1: warmer temperatures in the eastern part of the Pacific around 16 00:01:00,440 --> 00:01:03,360 Speaker 1: the Equator, which can have knock on effects for the 17 00:01:03,400 --> 00:01:07,000 Speaker 1: weather and much else in many different parts of the world. 18 00:01:07,600 --> 00:01:11,760 Speaker 1: Recent Alninio's have seemed to become more intense, and the 19 00:01:11,880 --> 00:01:15,000 Speaker 1: US Climate Protection Center has said there is a more 20 00:01:15,040 --> 00:01:18,360 Speaker 1: than ninety percent chance of one unfolding later this year 21 00:01:18,640 --> 00:01:22,360 Speaker 1: for the first time in four years. If basic crops 22 00:01:22,400 --> 00:01:26,080 Speaker 1: are affected in poorer economies and food prices go up 23 00:01:26,120 --> 00:01:29,560 Speaker 1: as they have in the past, that would be bad news. Indeed, 24 00:01:29,640 --> 00:01:31,959 Speaker 1: after everything the global economy has been through in the 25 00:01:32,000 --> 00:01:35,320 Speaker 1: past few years. In a few minutes, I'll hear more 26 00:01:35,360 --> 00:01:38,520 Speaker 1: about what we might have to expect from a strategist 27 00:01:38,560 --> 00:01:41,880 Speaker 1: at Deutsche Bank who's looked at the historical record. I'll 28 00:01:41,920 --> 00:01:45,200 Speaker 1: also talk to a global economist from Bloomberg Economics who's 29 00:01:45,200 --> 00:01:48,880 Speaker 1: made a stab at estimating exactly how prices and growth 30 00:01:48,920 --> 00:01:51,960 Speaker 1: could be affected in different parts of the world. But first, 31 00:01:52,320 --> 00:01:56,680 Speaker 1: here's Bloomberg's LAWA Curtis with related news from that crucial 32 00:01:56,960 --> 00:01:59,880 Speaker 1: artery of global trade, the Panama Canal. 33 00:02:02,920 --> 00:02:05,840 Speaker 2: Water levels in Panama's Gatoon Lake are falling fast and 34 00:02:05,880 --> 00:02:08,280 Speaker 2: are projected to hit historic clothes by the end of July. 35 00:02:09,040 --> 00:02:12,600 Speaker 2: Making matters worse, an al Nino system is forming, which 36 00:02:12,639 --> 00:02:16,080 Speaker 2: typically makes the region hotter and drier than usual, and 37 00:02:16,120 --> 00:02:19,720 Speaker 2: the water shortages could stretch into twenty twenty four. But wait, 38 00:02:20,080 --> 00:02:22,640 Speaker 2: this is a podcast about economics, so why are we 39 00:02:22,680 --> 00:02:26,560 Speaker 2: talking about a drought in Central America? Well, remember just 40 00:02:26,600 --> 00:02:28,560 Speaker 2: a few short years ago, when we were all waiting 41 00:02:28,560 --> 00:02:31,760 Speaker 2: out the pandemic. Stuck in our houses as we waited 42 00:02:31,800 --> 00:02:34,600 Speaker 2: months for the new sofas and grills and other consumer 43 00:02:34,600 --> 00:02:38,440 Speaker 2: goods to arrive, all that stuff was stuck on ships 44 00:02:38,520 --> 00:02:42,040 Speaker 2: and in containers as a supply chain seized under pandemic 45 00:02:42,080 --> 00:02:46,519 Speaker 2: pressure and consumer demand. We know now that the crunch 46 00:02:46,600 --> 00:02:49,440 Speaker 2: caused shortages and delays that caused a huge spike in 47 00:02:49,480 --> 00:02:52,760 Speaker 2: shipping costs and eventually helped spur the inflation rate to 48 00:02:52,800 --> 00:02:55,760 Speaker 2: a four decade high, which the Federal Reserve has only 49 00:02:55,840 --> 00:02:57,320 Speaker 2: just started to get under control. 50 00:02:57,639 --> 00:03:01,520 Speaker 3: The Panamacanal is one of the essential what we call 51 00:03:01,600 --> 00:03:08,320 Speaker 3: maritime chokepoints, because this basically cuts massive sailing distances very 52 00:03:08,320 --> 00:03:12,200 Speaker 3: short when you can transit the Panama Canal. The Seuiz 53 00:03:12,240 --> 00:03:15,640 Speaker 3: Canal is another one. Turkish straits a third one. 54 00:03:16,200 --> 00:03:20,120 Speaker 2: That's Peter Sand, chief analyst at freight data company Zanita. 55 00:03:20,200 --> 00:03:24,440 Speaker 3: It involves all kinds of supply chains of energy and commodities, 56 00:03:24,800 --> 00:03:29,800 Speaker 3: and naturally also for containers shipping. It's a vital artery 57 00:03:30,680 --> 00:03:35,480 Speaker 3: for containers traveling from far Eastern manufacturers into the US 58 00:03:35,520 --> 00:03:38,080 Speaker 3: East Coast if they do not go via the Zeus. 59 00:03:37,880 --> 00:03:42,200 Speaker 2: Canal, Cattuned Lake feeds the Panama Canal with fresh water 60 00:03:42,320 --> 00:03:45,360 Speaker 2: to lift huge container ships eighty five feet above sea 61 00:03:45,440 --> 00:03:48,200 Speaker 2: level and through twelve locks from the Pacific Ocean to 62 00:03:48,280 --> 00:03:52,120 Speaker 2: the Caribbean. To manage low water levels, the canal has 63 00:03:52,160 --> 00:03:55,880 Speaker 2: started to impose surcharges and draft limits, or how low 64 00:03:55,880 --> 00:03:58,320 Speaker 2: the vessels can sit in the water, and that means 65 00:03:58,320 --> 00:03:59,560 Speaker 2: they can carry less stuff. 66 00:04:00,320 --> 00:04:07,120 Speaker 4: We have a really very volatile supply chain infrastructure. 67 00:04:08,000 --> 00:04:11,000 Speaker 2: Stephanie Loomis is head of Ocean product for the Americas 68 00:04:11,080 --> 00:04:14,920 Speaker 2: at Germany based Rina's Logistics. They're a freight forwarder, or, 69 00:04:14,960 --> 00:04:18,040 Speaker 2: as she describes it, a travel agent for cargo. She's 70 00:04:18,040 --> 00:04:21,039 Speaker 2: not too concerned about the drought just yet. There's just 71 00:04:21,080 --> 00:04:24,000 Speaker 2: so much more capacity available on ocean liners compared to 72 00:04:24,040 --> 00:04:27,839 Speaker 2: this time last year, and shipping rates are low for now. 73 00:04:28,640 --> 00:04:31,120 Speaker 2: But there are other things worth watching that could compound 74 00:04:31,160 --> 00:04:32,840 Speaker 2: the risk to supply chains. 75 00:04:33,520 --> 00:04:38,800 Speaker 4: It doesn't take much to knock it off center and 76 00:04:38,960 --> 00:04:44,480 Speaker 4: right now we've got several pretty major things brewing that 77 00:04:44,600 --> 00:04:47,719 Speaker 4: if they should all come to the surface at the 78 00:04:47,760 --> 00:04:51,200 Speaker 4: same time, we could be in deep trouble again. 79 00:04:51,800 --> 00:04:53,920 Speaker 2: For those of you listening in Europe, some of this 80 00:04:54,000 --> 00:04:57,440 Speaker 2: may sound familiar. The Rhine River, which stretches hundreds of 81 00:04:57,520 --> 00:05:00,000 Speaker 2: miles from the Alps to the North Sea, is all 82 00:05:00,000 --> 00:05:03,760 Speaker 2: already seeing water levels low enough this season to restrict trade, 83 00:05:04,040 --> 00:05:08,200 Speaker 2: and fuel shipping costs have skyrocketed. The river is used 84 00:05:08,200 --> 00:05:10,840 Speaker 2: to transport millions of tons of oil products and other 85 00:05:10,920 --> 00:05:14,560 Speaker 2: vital commodities across Europe. Last year it got so low 86 00:05:14,680 --> 00:05:19,120 Speaker 2: that trade was severely disrupted, affecting oil refining, power generation, 87 00:05:19,360 --> 00:05:25,640 Speaker 2: and more. The supply chain world led out a collective 88 00:05:25,680 --> 00:05:28,680 Speaker 2: sigh of relief last week when US West Coast dock 89 00:05:28,760 --> 00:05:32,080 Speaker 2: workers and their employers reached a tentative contract agreement after 90 00:05:32,160 --> 00:05:34,840 Speaker 2: more than a year of talks, but the deal is 91 00:05:34,880 --> 00:05:37,800 Speaker 2: still subject to approval by the union's local chapters. 92 00:05:39,800 --> 00:05:41,360 Speaker 1: It took a two week wave. 93 00:05:41,120 --> 00:05:44,640 Speaker 2: Of labor disruptions to ultimately get the White House involved, 94 00:05:45,160 --> 00:05:48,240 Speaker 2: and those port slowdowns had a knock on effect. At 95 00:05:48,240 --> 00:05:49,120 Speaker 2: the Panama Canal. 96 00:05:49,360 --> 00:05:53,400 Speaker 3: On first June, there was no waiting time whatsoever around 97 00:05:53,560 --> 00:05:58,359 Speaker 3: the new Panamax looks going northbound as from from Asia 98 00:05:58,400 --> 00:06:02,400 Speaker 3: to the US East Coast bound. But what we have 99 00:06:02,560 --> 00:06:04,960 Speaker 3: right now in the middle of June, we have five 100 00:06:05,040 --> 00:06:06,200 Speaker 3: to six days of waiting. 101 00:06:07,040 --> 00:06:10,040 Speaker 2: As draft restrictions continue to tighten through the summer, will 102 00:06:10,160 --> 00:06:13,440 Speaker 2: likely see more congestion and higher fees. For now, the 103 00:06:13,480 --> 00:06:16,880 Speaker 2: canal limits are manageable for most shippers, especially the largest 104 00:06:16,960 --> 00:06:20,279 Speaker 2: US retailers bringing in backpacks and kids shoes ahead of 105 00:06:20,279 --> 00:06:25,120 Speaker 2: the back to school season. The businesses moving around heavier 106 00:06:25,160 --> 00:06:28,880 Speaker 2: stuff like building materials and machinery could already be feeling 107 00:06:28,880 --> 00:06:29,560 Speaker 2: the pinch. 108 00:06:30,560 --> 00:06:37,239 Speaker 4: So you could see tile and granite and marble. If 109 00:06:37,320 --> 00:06:39,760 Speaker 4: the freight costs, I mean, if you have to split 110 00:06:39,839 --> 00:06:43,880 Speaker 4: that container, you have to split that shipment into two containers, 111 00:06:44,240 --> 00:06:47,560 Speaker 4: you're essentially doubling your freight costs just like that. So 112 00:06:48,520 --> 00:06:53,159 Speaker 4: this could impact some of these commodities costs to the consumer. 113 00:06:53,880 --> 00:06:56,880 Speaker 2: Costly isn't a word that inflation hawks at the Federal 114 00:06:56,920 --> 00:06:59,760 Speaker 2: Reserve want to hear. Even as the fight against in 115 00:06:59,800 --> 00:07:03,880 Speaker 2: flat has been helped by falling shipping prices, price pressures 116 00:07:03,920 --> 00:07:06,279 Speaker 2: are still proving to be stickier than many had hoped, 117 00:07:06,720 --> 00:07:09,840 Speaker 2: running at about double the Central Bank's target of two percent. 118 00:07:11,560 --> 00:07:15,720 Speaker 2: Georgetown economics professor and former IMF official Jonathan Austry says 119 00:07:15,760 --> 00:07:18,280 Speaker 2: policymakers should keep an eye on the supply chain. 120 00:07:18,920 --> 00:07:23,280 Speaker 5: First up, What we discovered was that the impact of 121 00:07:23,440 --> 00:07:27,720 Speaker 5: rising shipping costs are much more persistent than the impact 122 00:07:27,800 --> 00:07:31,000 Speaker 5: of rising energy and food prices, which is what we're 123 00:07:31,000 --> 00:07:33,920 Speaker 5: grabbing the headlines in late twenty twenty one. In the 124 00:07:33,920 --> 00:07:35,080 Speaker 5: second half of twenty. 125 00:07:34,840 --> 00:07:37,760 Speaker 2: Twenty one, Austria and his colleagues found that the twenty 126 00:07:37,840 --> 00:07:40,960 Speaker 2: twenty one bottlenecks, which caused a six hundred percent spike 127 00:07:41,080 --> 00:07:43,480 Speaker 2: in the cost of shipping containers over the ocean from 128 00:07:43,560 --> 00:07:47,800 Speaker 2: pre COVID levels, increased consumer price inflation globally by more 129 00:07:47,840 --> 00:07:51,160 Speaker 2: than two percentage points in twenty twenty two, and for 130 00:07:51,280 --> 00:07:54,440 Speaker 2: remote small island nations in the Pacific and Caribbean that 131 00:07:54,480 --> 00:07:58,120 Speaker 2: rely heavily on imported goods, it added nearly another five 132 00:07:58,200 --> 00:07:59,360 Speaker 2: percentage points. 133 00:08:00,160 --> 00:08:03,840 Speaker 5: Shipping costs are a canary in the coal mine. They 134 00:08:03,880 --> 00:08:06,360 Speaker 5: do tell us about future inflation. 135 00:08:06,720 --> 00:08:09,560 Speaker 2: Ostre says, even with low base prices, a shipping cost 136 00:08:09,640 --> 00:08:13,000 Speaker 2: increase of twenty percent boost the inflation rate yo point 137 00:08:13,000 --> 00:08:14,840 Speaker 2: one to five percentage point a year later. 138 00:08:15,680 --> 00:08:18,160 Speaker 5: I think the warning is here. If the drought and 139 00:08:18,280 --> 00:08:24,200 Speaker 5: El Nino converge to cause shipping costs to again spike. 140 00:08:24,360 --> 00:08:28,760 Speaker 5: In the second half of twenty twenty three, that should 141 00:08:28,800 --> 00:08:34,400 Speaker 5: be in top of mind for FED policy makers, because 142 00:08:34,880 --> 00:08:37,640 Speaker 5: again what we would expect is that that would be 143 00:08:37,880 --> 00:08:43,480 Speaker 5: a contributing factor that weighs against the fed's disinflation effort. 144 00:08:44,440 --> 00:08:46,640 Speaker 2: Sand and Loomis say if this drought had hit the 145 00:08:46,679 --> 00:08:49,559 Speaker 2: canal last year, when the pandemic cargo surge was in 146 00:08:49,640 --> 00:08:53,440 Speaker 2: full swing, it would have been a complete disaster. But 147 00:08:53,520 --> 00:08:56,679 Speaker 2: with cargo volumes back closer to twenty nineteen levels, there's 148 00:08:56,800 --> 00:08:59,800 Speaker 2: enough slack in global trade lanes to ensure presents are 149 00:08:59,840 --> 00:09:02,760 Speaker 2: on store shelves in time for the holidays. But water 150 00:09:02,840 --> 00:09:05,800 Speaker 2: levels in panama are still projected to hit record lows 151 00:09:05,800 --> 00:09:09,200 Speaker 2: by July, and for businesses that just realign their supply 152 00:09:09,280 --> 00:09:11,760 Speaker 2: chains to be closer to consumers on the East Coast 153 00:09:12,320 --> 00:09:16,040 Speaker 2: or to distribution centers on the Gulf Coast, rerouting all 154 00:09:16,040 --> 00:09:19,959 Speaker 2: that stuff back through California Port could be an expensive headache. 155 00:09:20,440 --> 00:09:23,520 Speaker 3: I'm not calling doom and gloom here, but I think 156 00:09:23,520 --> 00:09:26,520 Speaker 3: we need to look further ahead also into twenty four 157 00:09:27,960 --> 00:09:33,000 Speaker 3: because that's when the next dry season is about to 158 00:09:34,000 --> 00:09:38,360 Speaker 3: see in Panamaica. Now and if we do not see 159 00:09:38,400 --> 00:09:41,400 Speaker 3: the watershed filled up during the second half of this year, 160 00:09:42,000 --> 00:09:45,840 Speaker 3: going into an ear year that is likely to bring 161 00:09:45,880 --> 00:09:50,600 Speaker 3: around a longer low, say drought season or dry season 162 00:09:51,280 --> 00:09:53,720 Speaker 3: than a normal year. We could end up with even 163 00:09:53,840 --> 00:09:56,840 Speaker 3: lower water levels in twenty twenty four. So this may 164 00:09:56,880 --> 00:10:01,800 Speaker 3: be the starter for full dinner ser next year. 165 00:10:02,400 --> 00:10:05,160 Speaker 2: For Bloomberg News. I'm Laura Curtis in Los Angeles. 166 00:10:14,800 --> 00:10:17,040 Speaker 1: Now you heard there that the Federal Reserve and other 167 00:10:17,080 --> 00:10:20,520 Speaker 1: central banks might have reason to worry if Al Nino 168 00:10:20,600 --> 00:10:23,480 Speaker 1: in the second half of this year ends up raising 169 00:10:23,559 --> 00:10:26,920 Speaker 1: shipping costs. So what are the chances of that happening, 170 00:10:27,040 --> 00:10:31,520 Speaker 1: and more broadly, how bad could those impacts be. Well, 171 00:10:31,600 --> 00:10:33,560 Speaker 1: I can talk to two people now who've spent some 172 00:10:33,640 --> 00:10:37,280 Speaker 1: time looking at this from the economic standpoint, Henry Allen, 173 00:10:37,440 --> 00:10:41,040 Speaker 1: Macro's strategist at Deutsche Bank in London, and our own 174 00:10:41,080 --> 00:10:45,000 Speaker 1: Barga vi Shaq Develle from Bloomberg Economics, a global economist. 175 00:10:45,480 --> 00:10:48,560 Speaker 1: Welcome to both of you. Henry, since you're our guest, 176 00:10:49,040 --> 00:10:52,520 Speaker 1: why don't you give us some context for thinking about this. 177 00:10:52,600 --> 00:10:58,199 Speaker 1: How often have we seen El Nino have a significant 178 00:10:58,320 --> 00:11:01,200 Speaker 1: impact on the economy in the last sort of generation 179 00:11:01,360 --> 00:11:02,680 Speaker 1: or so. 180 00:11:02,679 --> 00:11:05,480 Speaker 6: So the El Nino is a warming of the sea 181 00:11:05,559 --> 00:11:08,760 Speaker 6: surface temperatures, in the Pacific, and that might sound kind 182 00:11:08,760 --> 00:11:10,960 Speaker 6: of quite benign on one level, but the problem is 183 00:11:10,960 --> 00:11:14,480 Speaker 6: that that causes the jet stream to move south, and 184 00:11:14,520 --> 00:11:18,000 Speaker 6: that in turn is correlated with a higher frequency of 185 00:11:18,120 --> 00:11:22,360 Speaker 6: natural disasters. Now, normally this is a regular cyclical pattern 186 00:11:22,400 --> 00:11:25,080 Speaker 6: that happens around every two to seven years on average. 187 00:11:25,320 --> 00:11:28,920 Speaker 6: But what's really generating concerned this time are predictions from 188 00:11:28,920 --> 00:11:32,480 Speaker 6: a number of climate agencies that this particular episode is 189 00:11:32,520 --> 00:11:34,640 Speaker 6: going to be a strong one. So for instance, we 190 00:11:34,679 --> 00:11:36,920 Speaker 6: last saw an El NINU in twenty eighteen nineteen, but 191 00:11:36,960 --> 00:11:40,080 Speaker 6: that was quite a weak one. But this, at least 192 00:11:40,120 --> 00:11:42,600 Speaker 6: according to the US Climate Prediction Center, could be for 193 00:11:42,720 --> 00:11:45,520 Speaker 6: just the third time in the twenty first century, a 194 00:11:45,679 --> 00:11:47,840 Speaker 6: strong EL NINU, and they're saying they think there's a 195 00:11:47,880 --> 00:11:50,800 Speaker 6: fifty six percent chance that it will hit that strong 196 00:11:50,920 --> 00:11:55,080 Speaker 6: threshold deeper into this year, around December January time. 197 00:11:56,040 --> 00:11:59,920 Speaker 1: I think that the most recent sort of serious time 198 00:12:00,880 --> 00:12:03,240 Speaker 1: in your piece you discussed was sort of between twenty 199 00:12:03,320 --> 00:12:06,240 Speaker 1: fourteen and twenty sixteen. So what kind of impacts do 200 00:12:06,360 --> 00:12:06,960 Speaker 1: we see there? 201 00:12:07,720 --> 00:12:10,360 Speaker 6: So there were several Firstly, you had actually in twenty 202 00:12:10,360 --> 00:12:14,000 Speaker 6: sixteen in particular, the biggest upward temperature anomaly on record 203 00:12:14,000 --> 00:12:16,360 Speaker 6: at the time, that was the highest EPP temperature that 204 00:12:16,440 --> 00:12:19,199 Speaker 6: the world had seen. You saw a higher frequency of 205 00:12:19,280 --> 00:12:22,080 Speaker 6: hurricanes in the Pacific. In both twenty fourteen and twenty fifteen, 206 00:12:22,679 --> 00:12:25,960 Speaker 6: that Pacific hurricane season had sixteen hurricanes, the joint highest 207 00:12:26,040 --> 00:12:30,280 Speaker 6: number on record. Further afield, in Africa, you had the 208 00:12:30,320 --> 00:12:33,120 Speaker 6: worst drought in decades in Ethiopia, a great deal of famine, 209 00:12:33,440 --> 00:12:36,520 Speaker 6: and one study even found that because it created conditions 210 00:12:36,520 --> 00:12:39,960 Speaker 6: that were beneficial for mosquito borne transmission, it even contributed 211 00:12:40,000 --> 00:12:42,360 Speaker 6: to the spread of the Zeka virus. So a number 212 00:12:42,360 --> 00:12:44,600 Speaker 6: of quite nasty effects for coming together there. 213 00:12:45,600 --> 00:12:48,120 Speaker 1: That's one of the things that comes through in every 214 00:12:48,400 --> 00:12:51,200 Speaker 1: bit of research that I look at is that the 215 00:12:51,240 --> 00:12:54,439 Speaker 1: sheer range of impacts and the sort of unexpected consequences. 216 00:12:54,520 --> 00:12:56,480 Speaker 1: And in another one that people are talking about currently 217 00:12:56,559 --> 00:13:00,880 Speaker 1: is the very very high temperatures in South Asia that 218 00:13:01,000 --> 00:13:07,120 Speaker 1: are potentially related to this kind of environment are pushing 219 00:13:07,160 --> 00:13:10,120 Speaker 1: countries to be even more dependent on Russian energy, just 220 00:13:10,160 --> 00:13:12,760 Speaker 1: at a time when we might have been wanting them 221 00:13:12,760 --> 00:13:16,400 Speaker 1: to follow the US led sanctions. I guess the most 222 00:13:16,440 --> 00:13:21,400 Speaker 1: significant time before twenty fourteen you mentioned was ninety seven 223 00:13:21,920 --> 00:13:23,679 Speaker 1: ninety eight, so what happened. 224 00:13:23,360 --> 00:13:27,000 Speaker 6: Then, so a bit like with the most recent one, 225 00:13:27,080 --> 00:13:29,480 Speaker 6: the most reason very strong one in twenty fourteen to sixteen. 226 00:13:29,520 --> 00:13:32,120 Speaker 6: You also had what was at the time again a 227 00:13:32,160 --> 00:13:35,600 Speaker 6: global record temperature year in nineteen ninety eight, the warmest 228 00:13:35,600 --> 00:13:38,679 Speaker 6: to date so far. For instance, there were massive rainfalls 229 00:13:38,720 --> 00:13:43,760 Speaker 6: in California, San Francisco, so it's wettest rainfall season in 230 00:13:43,800 --> 00:13:46,720 Speaker 6: over a century. You had major droughts in Indonesia, and 231 00:13:46,720 --> 00:13:48,760 Speaker 6: similarly you actually saw quite a bit of disease as well. 232 00:13:48,800 --> 00:13:52,000 Speaker 6: For instance, after major flooding in East Africa, you had 233 00:13:52,040 --> 00:13:55,760 Speaker 6: an outbreak of rift valley fever in several countries, including Kenya. 234 00:13:56,600 --> 00:13:59,040 Speaker 1: And we're talking about it this year. As you mentioned, 235 00:13:59,080 --> 00:14:03,439 Speaker 1: the US Climate Center has put the probability of an 236 00:14:03,480 --> 00:14:06,960 Speaker 1: al Nino pattern unfolding at more than ninety percent, but 237 00:14:07,040 --> 00:14:10,439 Speaker 1: as you said, it's a question at how severe it 238 00:14:10,520 --> 00:14:13,840 Speaker 1: is likely to be. You're a strategist looking at market 239 00:14:13,840 --> 00:14:17,960 Speaker 1: impacts as well as the economy. Are we already seeing 240 00:14:18,080 --> 00:14:21,960 Speaker 1: signs of potential impacts in the markets or people anticipating 241 00:14:22,040 --> 00:14:23,160 Speaker 1: impacts from El Ninia? 242 00:14:24,160 --> 00:14:27,040 Speaker 6: Definitely, I mean the most obvious impact has been among 243 00:14:27,120 --> 00:14:30,800 Speaker 6: certain agricultural commodities, so One example is coffee futures have 244 00:14:30,840 --> 00:14:34,280 Speaker 6: recently hit their highest level since one particular contract began 245 00:14:34,400 --> 00:14:36,960 Speaker 6: in two thousand and eight. You've got sugar prices that 246 00:14:37,040 --> 00:14:39,720 Speaker 6: are already around their highest level in around a decade, 247 00:14:39,880 --> 00:14:42,960 Speaker 6: and coco is at a seven year high as well. 248 00:14:43,560 --> 00:14:47,080 Speaker 6: And that's consistent with what we've seen around previous Elmineo cycles, 249 00:14:47,120 --> 00:14:50,640 Speaker 6: whereby in particular agricultural commodities see a big upward shock 250 00:14:50,960 --> 00:14:54,960 Speaker 6: and that puts upward pressure on inflation intern and. 251 00:14:54,960 --> 00:14:56,800 Speaker 1: It is I mean when you say those things, of course, 252 00:14:56,800 --> 00:15:00,800 Speaker 1: that's people worrying about their coffee, chocolate. We'd certainly have 253 00:15:02,080 --> 00:15:06,120 Speaker 1: concerns about rice prices, barga vie. I mean, there's the 254 00:15:06,200 --> 00:15:08,960 Speaker 1: sheer range of impacts that we've talked about so far, 255 00:15:09,080 --> 00:15:12,040 Speaker 1: whether it's flooding in East Africa or hurricanes in the Pacific, 256 00:15:12,080 --> 00:15:16,280 Speaker 1: the spread of the Zeka virus in past times. Coming 257 00:15:16,320 --> 00:15:18,880 Speaker 1: on top of the last twelve months where of course 258 00:15:18,880 --> 00:15:22,320 Speaker 1: we also had the impact on food prices of Russia's 259 00:15:22,320 --> 00:15:27,239 Speaker 1: invasion on Ukraine. How should we think about the potential 260 00:15:27,240 --> 00:15:31,560 Speaker 1: impact of El Nino this year, on top of all 261 00:15:31,600 --> 00:15:33,880 Speaker 1: those previous things that have happened in the global economy. 262 00:15:35,880 --> 00:15:39,800 Speaker 7: It has been pretty worrying because the only unit, as 263 00:15:39,920 --> 00:15:44,800 Speaker 7: Henry already mentioned, is going to definitely cause inflationary pressures everywhere. 264 00:15:46,160 --> 00:15:49,120 Speaker 7: We did like a very simple modeling exercise where we 265 00:15:49,240 --> 00:15:53,120 Speaker 7: looked at a few countries eleven countries, including the euro area, 266 00:15:53,640 --> 00:15:59,240 Speaker 7: and tried to understand how this atmospheric pressure that is 267 00:15:59,360 --> 00:16:03,040 Speaker 7: cost when the minor event occurs, could affect these countries. 268 00:16:03,360 --> 00:16:06,880 Speaker 7: And what we found was that almost certainly irrespective of 269 00:16:06,920 --> 00:16:09,480 Speaker 7: which part of the country, which part of the continent 270 00:16:09,560 --> 00:16:12,680 Speaker 7: the country belongs to, there would be inflationary pressures, whereas 271 00:16:13,400 --> 00:16:16,640 Speaker 7: it would definitely be much higher among countries that are 272 00:16:16,640 --> 00:16:20,400 Speaker 7: in the tropics and the southern hemisphere specifically because these 273 00:16:20,400 --> 00:16:23,880 Speaker 7: are the countries that I deal primarily with primary sector 274 00:16:23,880 --> 00:16:27,560 Speaker 7: so agricultural commodity exports, So we would expect that there 275 00:16:27,560 --> 00:16:30,040 Speaker 7: to be high inflation and lower growth. 276 00:16:30,960 --> 00:16:33,040 Speaker 1: And just to put just to put some numbers on this, 277 00:16:33,600 --> 00:16:37,440 Speaker 1: I mean, obviously there's a lot of uncertainty, but at 278 00:16:37,440 --> 00:16:41,640 Speaker 1: the global level, are we going to notice this the 279 00:16:41,680 --> 00:16:46,200 Speaker 1: impact on inflation or so, and certainly on commodity prices. 280 00:16:46,240 --> 00:16:48,760 Speaker 1: What kind of numbers would we potentially talk about. 281 00:16:49,560 --> 00:16:52,880 Speaker 7: Well, I think certain countries would definitely see high increases 282 00:16:52,920 --> 00:16:58,640 Speaker 7: to Argentina, Brazil, India, Philippines, all these countries would definitely 283 00:16:58,640 --> 00:17:02,320 Speaker 7: see higher inflation on a more global scale, depending on 284 00:17:02,360 --> 00:17:04,399 Speaker 7: how severe the only NEA turns out to be, I 285 00:17:04,400 --> 00:17:07,479 Speaker 7: think it could be even larger some of these effects. So, 286 00:17:07,760 --> 00:17:09,960 Speaker 7: for example, in Argentina and Brussel, we expect about a 287 00:17:10,040 --> 00:17:14,840 Speaker 7: zero point five percentage point higher inflation at an animal level, 288 00:17:15,119 --> 00:17:17,439 Speaker 7: and depending on how severe and how long the El 289 00:17:17,520 --> 00:17:21,720 Speaker 7: Nino event actually exists, it could be much much greater. 290 00:17:22,160 --> 00:17:24,960 Speaker 7: And given that there are significant spillover effects both from 291 00:17:25,000 --> 00:17:28,960 Speaker 7: trade and financial linkages, this could easily seep through even 292 00:17:29,000 --> 00:17:33,920 Speaker 7: to like developed countries or countries that are not directly 293 00:17:33,960 --> 00:17:35,440 Speaker 7: impacted by these weather phenomena. 294 00:17:36,680 --> 00:17:39,639 Speaker 1: And I mean, Henry, I guess the various numbers. I 295 00:17:39,680 --> 00:17:42,160 Speaker 1: think the sort of we could potentially be adding nearly 296 00:17:42,600 --> 00:17:46,800 Speaker 1: four percentage points to non energy commodity prices. Obviously much 297 00:17:47,400 --> 00:17:49,760 Speaker 1: that's going to have to translate into a much smaller 298 00:17:49,760 --> 00:17:53,240 Speaker 1: impact on global inflation. But as Bargavi said, it varies 299 00:17:53,280 --> 00:17:55,920 Speaker 1: a lot country by country. Does that sort of broadly 300 00:17:56,480 --> 00:17:59,080 Speaker 1: tally with what you've been thinking at Deutsche BAC. 301 00:18:00,040 --> 00:18:02,119 Speaker 6: Yes, absolutely, I mean One of the things that makes 302 00:18:02,160 --> 00:18:04,639 Speaker 6: this El Nino phenomenon so hard to predict is that 303 00:18:04,720 --> 00:18:07,119 Speaker 6: the effects are so variable. So there are parts of 304 00:18:07,119 --> 00:18:10,240 Speaker 6: the world, for instance, like the southern United States, where 305 00:18:10,240 --> 00:18:12,080 Speaker 6: it makes flooding a lot more likely. But there are 306 00:18:12,080 --> 00:18:13,680 Speaker 6: other parts of the world, toicularly the other side of 307 00:18:13,680 --> 00:18:16,639 Speaker 6: the Pacific, like Indonesian and Australia, where it makes drought 308 00:18:16,640 --> 00:18:19,119 Speaker 6: more likely. So it's very hard to kind of find 309 00:18:19,320 --> 00:18:22,800 Speaker 6: a single aggregate global effect that it has because that 310 00:18:22,840 --> 00:18:25,840 Speaker 6: impact is so variable according to different regions, and. 311 00:18:25,840 --> 00:18:27,439 Speaker 1: I noticed them. And of course when you think about 312 00:18:27,960 --> 00:18:32,720 Speaker 1: possible places that where it's beneficial to have, for example, 313 00:18:32,840 --> 00:18:36,200 Speaker 1: more rain. I mean, you know, if you're an avocado 314 00:18:36,400 --> 00:18:40,880 Speaker 1: or an almond almond grower in California, it's actually quite 315 00:18:40,920 --> 00:18:43,080 Speaker 1: good news to have more rain. But it's striking when 316 00:18:43,119 --> 00:18:46,840 Speaker 1: you go through the list the iniquity of how the 317 00:18:46,880 --> 00:18:49,640 Speaker 1: pain gets distributed Barga Vie. I mean, this is by 318 00:18:49,680 --> 00:18:51,840 Speaker 1: and large going to be a much more negative impact 319 00:18:51,920 --> 00:18:54,600 Speaker 1: and certainly have a bigger impact on inflation in the 320 00:18:54,640 --> 00:18:55,959 Speaker 1: poorer parts of the world. 321 00:18:56,840 --> 00:18:59,879 Speaker 7: And we look at things like how it affects economic growth. 322 00:19:00,200 --> 00:19:03,639 Speaker 7: We found that Indian and Argentina about zero point five 323 00:19:03,640 --> 00:19:06,240 Speaker 7: percentage points and that GDP got knocked off, but the 324 00:19:06,280 --> 00:19:08,880 Speaker 7: effect is going to be much larger for Argentina than 325 00:19:09,280 --> 00:19:12,119 Speaker 7: a country like India, which has extremely high GDP growth 326 00:19:12,160 --> 00:19:15,439 Speaker 7: in general, So even if they're equally impacted, I think 327 00:19:15,480 --> 00:19:20,840 Speaker 7: the smaller, poorer countries whose primary sources of revenue are 328 00:19:20,880 --> 00:19:25,119 Speaker 7: like output generation, is due to these commodity experts. 329 00:19:27,520 --> 00:19:31,080 Speaker 1: And I was struck that we had some even more 330 00:19:31,119 --> 00:19:37,240 Speaker 1: extreme estimates by some Earth scientists at Dartmouth College in 331 00:19:37,280 --> 00:19:42,160 Speaker 1: the US, Christopher Callahan and Justin Mankin, who estimated that 332 00:19:42,400 --> 00:19:44,720 Speaker 1: what Henry was talking about in the late nineties that 333 00:19:44,920 --> 00:19:48,320 Speaker 1: El Nina had led to nearly six trillion dollars in 334 00:19:48,400 --> 00:19:51,040 Speaker 1: lost GDP, So that's about a hundred times more than 335 00:19:51,480 --> 00:19:56,000 Speaker 1: the previously thought. And their point was that economists are 336 00:19:56,000 --> 00:19:59,520 Speaker 1: sort of only measuring what we could see got damaged, 337 00:19:59,720 --> 00:20:02,800 Speaker 1: or we could see that the slowdown in growth that 338 00:20:02,960 --> 00:20:05,920 Speaker 1: was very clear and apparent at that time, and we're 339 00:20:05,960 --> 00:20:09,119 Speaker 1: not recognizing that the sort of variability in the weather 340 00:20:09,520 --> 00:20:12,359 Speaker 1: can hurt economic growth in a prolonged way. So you 341 00:20:12,440 --> 00:20:17,920 Speaker 1: get persistent shortfalls in output that only unfold over several years, 342 00:20:18,359 --> 00:20:21,600 Speaker 1: and as a result of taking those into account. They 343 00:20:21,640 --> 00:20:25,800 Speaker 1: think you could see a cumulative shortfall in GDP over 344 00:20:25,840 --> 00:20:28,800 Speaker 1: the next century of maybe eighty trillion dollars or about 345 00:20:28,840 --> 00:20:33,679 Speaker 1: one percent of global GDP, just because of El Nino. Bargave. 346 00:20:33,800 --> 00:20:35,480 Speaker 1: You and I were sort of joking that these were 347 00:20:35,520 --> 00:20:40,920 Speaker 1: just madly big numbers earlier. But do you accept that 348 00:20:41,960 --> 00:20:44,560 Speaker 1: we are potentially only looking at the tip of the 349 00:20:44,560 --> 00:20:48,520 Speaker 1: iceberg when we do these straightforward analyses of the impact 350 00:20:48,560 --> 00:20:50,120 Speaker 1: on food prices or growth. 351 00:20:51,040 --> 00:20:54,960 Speaker 7: Yeah, definitely for starters. We haven't even started thinking about 352 00:20:56,040 --> 00:20:58,879 Speaker 7: other kinds of still over effects of direct effects on 353 00:20:59,400 --> 00:21:02,879 Speaker 7: these natural as asters bring about them if depending on 354 00:21:02,880 --> 00:21:05,440 Speaker 7: the severity of the ol ninio, so there definitely could 355 00:21:05,520 --> 00:21:12,080 Speaker 7: be other reasons that create negative impacts on commodities and 356 00:21:12,119 --> 00:21:16,920 Speaker 7: therefore causing inflation. But again, like we joked about earlier, 357 00:21:17,119 --> 00:21:19,560 Speaker 7: I don't necessarily know if it's going to be that large, 358 00:21:19,640 --> 00:21:23,439 Speaker 7: but for sure, our simple analysis only looks at the 359 00:21:23,480 --> 00:21:25,879 Speaker 7: direct effects, and there could be a lot more beneath 360 00:21:25,880 --> 00:21:26,360 Speaker 7: the iceberg. 361 00:21:27,040 --> 00:21:30,679 Speaker 6: Henry, Yeah, I think that's absolutely correct. I mean, one 362 00:21:30,760 --> 00:21:32,760 Speaker 6: thing that I was quite surprised about reading about the 363 00:21:32,800 --> 00:21:34,960 Speaker 6: old linear phenomenon was that it didn't just seem to 364 00:21:34,960 --> 00:21:39,359 Speaker 6: have an impact on food commodities. It was also energy commodities. 365 00:21:39,359 --> 00:21:41,399 Speaker 6: There seemed to be a positive correlation too. There was 366 00:21:41,440 --> 00:21:44,320 Speaker 6: one paper, for instance, by the IMF a few years 367 00:21:44,320 --> 00:21:47,000 Speaker 6: back that found that there was a statistical effect on 368 00:21:47,160 --> 00:21:50,199 Speaker 6: energy and oil prices. For instance, if you have droughts 369 00:21:50,240 --> 00:21:53,560 Speaker 6: that means you get less electricity from hydroelectric dams, you 370 00:21:53,600 --> 00:21:56,000 Speaker 6: need to find that from other sources. Another thing is 371 00:21:56,040 --> 00:21:58,760 Speaker 6: that farmers in trout areas need more water for irrigating 372 00:21:58,840 --> 00:22:02,840 Speaker 6: their crops. So actually the spillover effects don't just stick 373 00:22:02,880 --> 00:22:04,879 Speaker 6: with food, but they can spread to other categories the 374 00:22:04,920 --> 00:22:05,919 Speaker 6: inflation baskets. 375 00:22:05,920 --> 00:22:08,919 Speaker 1: Well, and I guess, as you mentioned at the starts, 376 00:22:09,000 --> 00:22:14,000 Speaker 1: is it's technically a warmer phase for the eastern Equatorial Pacific. 377 00:22:14,240 --> 00:22:16,439 Speaker 1: You know, in many ways it is a sneak preview 378 00:22:16,560 --> 00:22:20,960 Speaker 1: of what we might see with climate change as we go. 379 00:22:21,160 --> 00:22:23,479 Speaker 1: As we go forward, and as we get better at 380 00:22:23,520 --> 00:22:25,720 Speaker 1: measuring the impact of climate change, I guess we get 381 00:22:25,760 --> 00:22:28,120 Speaker 1: a bit better at measuring the impact of al ninia. 382 00:22:28,600 --> 00:22:33,359 Speaker 1: Henry Allen and Barga Vi Satjevelle, thank you very much. 383 00:22:33,920 --> 00:22:34,280 Speaker 6: Thank you. 384 00:22:36,760 --> 00:22:39,480 Speaker 1: Well, that's it for this episode of Stephanomics. Next week 385 00:22:39,560 --> 00:22:42,159 Speaker 1: we'll have more. In the meantime, you can get a 386 00:22:42,160 --> 00:22:45,760 Speaker 1: lot more economic insight and news from the Bloomberg Terminal 387 00:22:45,960 --> 00:22:49,320 Speaker 1: website or app. And for those of you wondering what 388 00:22:49,359 --> 00:22:52,040 Speaker 1: the weather's like the rest of the year in. 389 00:22:52,000 --> 00:22:55,760 Speaker 6: July and Sunny's hot is in shiny now it's not. 390 00:23:00,119 --> 00:23:01,720 Speaker 4: Of col and dank and wait. 391 00:23:02,880 --> 00:23:05,959 Speaker 1: This episode was produced by Magnus Henrickson, Yang Yang and 392 00:23:06,000 --> 00:23:09,480 Speaker 1: Summer Sadie, with help from Oscar Boyd. Special thanks to 393 00:23:09,560 --> 00:23:13,800 Speaker 1: Laura Curtis, Henry Allen, Barga, v Shaq Develle, and Michael 394 00:23:13,840 --> 00:23:17,320 Speaker 1: Flanders and Donald Swamp. The executive producer of Stephanomics is 395 00:23:17,359 --> 00:23:21,359 Speaker 1: Molly Smith, and the head of Bloomberg Podcast is Sage Bone. 396 00:23:25,800 --> 00:23:26,200 Speaker 4: Bloody. 397 00:23:26,440 --> 00:23:35,040 Speaker 6: Januinely again, I hope that's been helpful for those of 398 00:23:35,160 --> 00:23:36,240 Speaker 6: you are planning your holidays