1 00:00:05,800 --> 00:00:08,720 Speaker 1: Welcome to the Bloomberg p m L Podcast. I'm pim Fox. 2 00:00:08,760 --> 00:00:11,560 Speaker 1: Along with my co host Lisa Abramowitz. Each day we 3 00:00:11,640 --> 00:00:15,120 Speaker 1: bring you the most important, noteworthy, and useful interviews for 4 00:00:15,200 --> 00:00:17,840 Speaker 1: you and your money, whether you're at the grocery store 5 00:00:17,960 --> 00:00:20,720 Speaker 1: or the trading floor. Find the Bloomberg p m L 6 00:00:20,840 --> 00:00:32,800 Speaker 1: Podcast on Apple Podcasts, SoundCloud, and Bloomberg dot Com. The 7 00:00:32,840 --> 00:00:37,400 Speaker 1: International Monetary Fund estimates that the inflation in Venezuela could 8 00:00:37,520 --> 00:00:43,479 Speaker 1: reach more than thirteen thousand percent this year. Two pounds 9 00:00:43,560 --> 00:00:47,159 Speaker 1: of chicken or beef costs as much as the monthly 10 00:00:47,400 --> 00:00:51,680 Speaker 1: minimum wage package, and that includes food coupons that are 11 00:00:51,720 --> 00:00:55,240 Speaker 1: worth about two and a half dollars. And yet President 12 00:00:55,320 --> 00:00:59,640 Speaker 1: Nicholas Maduro one re election on Sunday. Here to tell 13 00:00:59,720 --> 00:01:03,520 Speaker 1: us more were about the country and its economic predicament 14 00:01:03,680 --> 00:01:06,640 Speaker 1: is Ricardo Houseman is the former Minister of Planning for 15 00:01:06,720 --> 00:01:11,399 Speaker 1: Venezuela and director of the Center for International Development and Economics, 16 00:01:11,400 --> 00:01:16,400 Speaker 1: professor at Harvard's Kennedy School of the Government. Ricardo Houseman, 17 00:01:16,440 --> 00:01:19,560 Speaker 1: thank you very much for being with us. Maybe you 18 00:01:19,600 --> 00:01:22,880 Speaker 1: could just give us your thoughts and reactions to Sunday's 19 00:01:22,880 --> 00:01:27,959 Speaker 1: election and what that means for the future of your country. Well, 20 00:01:28,000 --> 00:01:31,319 Speaker 1: the first thing is that the election was a sham. 21 00:01:31,840 --> 00:01:35,039 Speaker 1: It was an election in which the three major opposition 22 00:01:35,080 --> 00:01:41,800 Speaker 1: parties were outlawed. The two major opposition candidates were disqualified 23 00:01:42,720 --> 00:01:48,200 Speaker 1: in the opposition boycotted the election two candidates. The government 24 00:01:48,280 --> 00:01:52,560 Speaker 1: got two candidates to participate in the election, and that 25 00:01:52,720 --> 00:01:55,559 Speaker 1: we're in the fringes of the opposition. Those two count 26 00:01:55,680 --> 00:02:00,440 Speaker 1: candidates denounced the result as being fraudulent, being the national 27 00:02:00,480 --> 00:02:04,840 Speaker 1: community has decided not to recognize these results. So the novelty, 28 00:02:04,880 --> 00:02:08,000 Speaker 1: the only novelty, is that Madudu is still the president 29 00:02:08,040 --> 00:02:12,760 Speaker 1: of Venezuela, but that his international elecitimacy is even further eroded. 30 00:02:13,480 --> 00:02:17,239 Speaker 1: On the economic front, the government went on a spending 31 00:02:17,360 --> 00:02:21,360 Speaker 1: spree in the months to the elections. They didn't have 32 00:02:21,400 --> 00:02:24,840 Speaker 1: the money to spend, so they just printed it in. 33 00:02:25,480 --> 00:02:28,799 Speaker 1: The money supply increased by sixty one in the four 34 00:02:28,880 --> 00:02:32,800 Speaker 1: weeks to the election. That's an annualized rate of fifty 35 00:02:33,400 --> 00:02:42,760 Speaker 1: percent a year. In monthly inflation is running at an 36 00:02:42,800 --> 00:02:48,960 Speaker 1: annual equivalent of something like fifty percent also, so so 37 00:02:49,600 --> 00:02:51,400 Speaker 1: I think that the I M F numbers that you 38 00:02:51,560 --> 00:02:58,000 Speaker 1: just quoted at now look extremely optimistic. So I think 39 00:02:58,040 --> 00:03:02,440 Speaker 1: that it will just be the continuous deterioration of the 40 00:03:02,520 --> 00:03:06,440 Speaker 1: country until there is regime change, and all those numbers 41 00:03:06,520 --> 00:03:10,480 Speaker 1: somehow get overshadowed by the images that we've seen, not 42 00:03:10,520 --> 00:03:14,799 Speaker 1: only the lines, but of children and others just completely emaciated, 43 00:03:15,240 --> 00:03:18,000 Speaker 1: lacking food. I'm wondering, what do you think that the 44 00:03:18,040 --> 00:03:22,280 Speaker 1: international community should do in response? Well, I think there 45 00:03:22,400 --> 00:03:26,120 Speaker 1: was a very quick response by this LIMA group that 46 00:03:26,240 --> 00:03:29,640 Speaker 1: is composed of the US, Canada and the major Latin 47 00:03:29,680 --> 00:03:32,960 Speaker 1: American countries. They have decided not to recognize the result. 48 00:03:33,400 --> 00:03:36,440 Speaker 1: They have decided to recall their ambassadors, to lower the 49 00:03:37,280 --> 00:03:41,840 Speaker 1: degree of diplomatic interaction, to call for an Organization of 50 00:03:41,880 --> 00:03:46,240 Speaker 1: American States meeting, and they are they are a little 51 00:03:46,240 --> 00:03:50,880 Speaker 1: bit shell shocked by the magnitude of the immigration, of 52 00:03:50,960 --> 00:03:55,360 Speaker 1: the refugee crisis that is occurring in in Venezuela. This 53 00:03:56,000 --> 00:04:00,560 Speaker 1: last week, the government of Colombia gave you announced the 54 00:04:00,640 --> 00:04:05,920 Speaker 1: results of having given Venezuelans a month to register last year. 55 00:04:05,960 --> 00:04:08,120 Speaker 1: They had given them a month to register and sixty 56 00:04:08,160 --> 00:04:12,080 Speaker 1: thou people registered. This year. They gave the ones that 57 00:04:12,160 --> 00:04:14,320 Speaker 1: were not registered last year, they gave them a month 58 00:04:14,400 --> 00:04:16,680 Speaker 1: to register. So long as they had entered the country 59 00:04:16,800 --> 00:04:20,880 Speaker 1: legally over two hundred thousand registers. So so this is 60 00:04:21,880 --> 00:04:27,479 Speaker 1: a lower estimate of the amount of new outmigration into Colombia. 61 00:04:27,560 --> 00:04:32,120 Speaker 1: But most people continue on to through Chile, Argentina, Brazil, 62 00:04:32,240 --> 00:04:36,200 Speaker 1: Uruguay and Central America. You know in Panama, there's a 63 00:04:36,200 --> 00:04:39,440 Speaker 1: big community in Costa Rica, and or they go to 64 00:04:39,440 --> 00:04:45,360 Speaker 1: the US, Spain another destination. So so right now this 65 00:04:45,520 --> 00:04:50,160 Speaker 1: is promises to be a refugee crisis of Syrian magnitudes, 66 00:04:50,839 --> 00:04:55,680 Speaker 1: and and that means that the international community needs to 67 00:04:55,760 --> 00:04:59,320 Speaker 1: act because it is becoming a very serious domestic policy issue. 68 00:05:00,040 --> 00:05:03,919 Speaker 1: When we talk about actions, one has been just boycotting 69 00:05:04,120 --> 00:05:08,000 Speaker 1: Venezuela and oil, oil being one of their mainstays of 70 00:05:08,040 --> 00:05:10,520 Speaker 1: the entire economy. And we are seeing Petaviasa, the state 71 00:05:10,520 --> 00:05:14,719 Speaker 1: owned oil producer, its bonds falling as people expect them 72 00:05:14,760 --> 00:05:20,520 Speaker 1: to continue to suffer with your output. Uh, I'm just wondering, 73 00:05:20,560 --> 00:05:22,360 Speaker 1: I mean, is that the right response given the fact 74 00:05:22,400 --> 00:05:26,760 Speaker 1: that that you know, potentially could go to feeding people well, 75 00:05:26,920 --> 00:05:32,120 Speaker 1: and there are essentially no sanctions on Perisa. The problems 76 00:05:32,160 --> 00:05:36,680 Speaker 1: in Perisa are self are self inflicted. It is the 77 00:05:36,720 --> 00:05:40,560 Speaker 1: fact that the government decided to use the vious as 78 00:05:40,560 --> 00:05:43,880 Speaker 1: a cash cow and not to invest in oil, and 79 00:05:43,920 --> 00:05:48,160 Speaker 1: that has caused a catastrophic collapse in production. The sanctions 80 00:05:48,200 --> 00:05:52,160 Speaker 1: that have most piped our individual sanctions on and people 81 00:05:52,200 --> 00:05:56,520 Speaker 1: who have been narco trafficking, laundering money and so on. 82 00:05:57,400 --> 00:05:59,840 Speaker 1: And that includes, you know, the vice president of a 83 00:06:00,000 --> 00:06:06,760 Speaker 1: country who in the Office of Foreign Asset Control of 84 00:06:07,000 --> 00:06:14,400 Speaker 1: fact freeze from nine hundred million dollars in assets to 85 00:06:14,560 --> 00:06:17,480 Speaker 1: his name or to the name of his his secretar. 86 00:06:17,640 --> 00:06:21,880 Speaker 1: So there they have now issued the other sanctions to 87 00:06:22,160 --> 00:06:26,320 Speaker 1: other top officials and that's complicating their life. That the 88 00:06:26,360 --> 00:06:29,719 Speaker 1: problems of the oil company are not the consequence of 89 00:06:29,800 --> 00:06:34,599 Speaker 1: international action, they're the consequence of self inflicted wounds. What 90 00:06:34,720 --> 00:06:38,960 Speaker 1: do you believe is the ultimate strategy or of a 91 00:06:39,120 --> 00:06:43,599 Speaker 1: president Medora, Well, I just I think he just needs 92 00:06:43,640 --> 00:06:47,719 Speaker 1: to he's just trying to hang on and he's betting 93 00:06:47,720 --> 00:06:51,800 Speaker 1: on the idea that this economic catastrophe, which is right 94 00:06:51,800 --> 00:06:55,280 Speaker 1: now it's running at twice the size of the US 95 00:06:55,360 --> 00:06:59,599 Speaker 1: grade depression, so it's twice as large decline and output 96 00:06:59,760 --> 00:07:05,200 Speaker 1: as US great depression, that that it will weaken society 97 00:07:05,800 --> 00:07:08,920 Speaker 1: faster than it weakens the government, so that the relative 98 00:07:08,960 --> 00:07:12,120 Speaker 1: power of the government Pisa, the society does not change. 99 00:07:12,480 --> 00:07:16,520 Speaker 1: I think I think the situation is just unsustainable, and 100 00:07:16,600 --> 00:07:19,920 Speaker 1: unsustainable situations tend not to be sustained. So I think 101 00:07:19,920 --> 00:07:23,440 Speaker 1: eventually there will be a regime change. But right now 102 00:07:23,840 --> 00:07:26,640 Speaker 1: in what I think will happen is that because there 103 00:07:26,720 --> 00:07:30,400 Speaker 1: is no short term electoral solution, there's no short term 104 00:07:30,480 --> 00:07:34,960 Speaker 1: dates for elections, the need for other forms of regime 105 00:07:35,080 --> 00:07:38,160 Speaker 1: change will have to be put on the table. You're 106 00:07:38,200 --> 00:07:42,200 Speaker 1: talking about the refugee crisis that may eclipse what's happening 107 00:07:42,200 --> 00:07:45,960 Speaker 1: in Syria, And I'm wondering, uh, from your personal perspective, professor, 108 00:07:46,040 --> 00:07:48,679 Speaker 1: because you are the form of Venezuelan, Minister of Planning, 109 00:07:48,960 --> 00:07:51,760 Speaker 1: former head of the Presidential Office of Coordination and Planning. 110 00:07:52,640 --> 00:07:54,440 Speaker 1: Do you think it's the right move for people to 111 00:07:54,560 --> 00:07:57,320 Speaker 1: just leave there as quickly as they can or do 112 00:07:57,360 --> 00:07:59,600 Speaker 1: you think that there is anybody there who could go 113 00:07:59,800 --> 00:08:02,920 Speaker 1: for to change? I mean, would you go back? Well, 114 00:08:03,120 --> 00:08:05,760 Speaker 1: I mean I think that if I went back, it 115 00:08:05,880 --> 00:08:08,440 Speaker 1: is a very good likelihood that I'll end up in prison, 116 00:08:08,520 --> 00:08:13,960 Speaker 1: so as as as are many political leaders. So I 117 00:08:14,000 --> 00:08:19,240 Speaker 1: think that people need to survive and their families need 118 00:08:19,320 --> 00:08:21,720 Speaker 1: to survive. And and one way to do so is 119 00:08:21,720 --> 00:08:23,760 Speaker 1: for somebody in the family to leave and try to 120 00:08:23,800 --> 00:08:28,040 Speaker 1: earn some income, because you know, the minimum wages less 121 00:08:28,040 --> 00:08:33,120 Speaker 1: than three dollars a month, and it doesn't it doesn't 122 00:08:34,160 --> 00:08:38,800 Speaker 1: buy enough calories to feed a single person, much less 123 00:08:38,800 --> 00:08:42,720 Speaker 1: a family. And the median worker earns the minimum wage. 124 00:08:42,720 --> 00:08:46,520 Speaker 1: So the minimum wage in Manezuela is hard to earn 125 00:08:47,080 --> 00:08:50,200 Speaker 1: and it doesn't feed anybody. So so just a stampede. 126 00:08:50,400 --> 00:08:53,600 Speaker 1: The oil company is unable to retain its workers. It's 127 00:08:53,640 --> 00:08:57,600 Speaker 1: lost some thirty five workers in the last year. The 128 00:08:57,600 --> 00:09:02,319 Speaker 1: electricity companies are unable to retain its workers. They're leaving 129 00:09:02,360 --> 00:09:06,120 Speaker 1: the country and growths. So now there's a water crisis. 130 00:09:06,960 --> 00:09:10,160 Speaker 1: The water system was not maintained and and so there's 131 00:09:10,160 --> 00:09:15,199 Speaker 1: a big water crisis that is having you know, delitorious 132 00:09:15,240 --> 00:09:18,000 Speaker 1: effects on the health standards of people. So it's just 133 00:09:18,160 --> 00:09:24,760 Speaker 1: a really serious catastrophic situation in um Uh. You know, 134 00:09:24,800 --> 00:09:29,360 Speaker 1: the international community in essence is telling the Venezuela Armed 135 00:09:29,360 --> 00:09:32,440 Speaker 1: forces that if they were to act, you know, they 136 00:09:32,480 --> 00:09:36,280 Speaker 1: would see it as a as a reasonable action on 137 00:09:36,360 --> 00:09:43,120 Speaker 1: their side in and they I think that the internal 138 00:09:43,160 --> 00:09:45,760 Speaker 1: cohesion of the government is going to be further weekend, 139 00:09:46,160 --> 00:09:50,960 Speaker 1: they already had a significant number of people leaving, you know, 140 00:09:51,040 --> 00:09:56,880 Speaker 1: their political system and political coalition. Um and and so 141 00:09:56,920 --> 00:10:01,520 Speaker 1: I see, I see just a of their weakening at 142 00:10:01,600 --> 00:10:06,480 Speaker 1: an enormous humanitarian cost until there is regime change. Can 143 00:10:06,520 --> 00:10:10,840 Speaker 1: you tell us about the military in Venezuela and do 144 00:10:10,840 --> 00:10:14,920 Speaker 1: you believe that there are individuals and positions of power 145 00:10:15,280 --> 00:10:18,719 Speaker 1: that will take it into their own hands to alleviate 146 00:10:18,800 --> 00:10:22,640 Speaker 1: the crisis that the country is going through. Well, you know, 147 00:10:22,760 --> 00:10:29,559 Speaker 1: the top brass is deeply involved in narco trafficking, money laundering, smuggling, 148 00:10:30,200 --> 00:10:33,400 Speaker 1: in all sorts of different criminal activities, and many of 149 00:10:33,440 --> 00:10:37,480 Speaker 1: them have been sanctioned by the US, Canada, European Union 150 00:10:37,520 --> 00:10:43,960 Speaker 1: and so on. In they are involved in in significant, 151 00:10:45,080 --> 00:10:49,600 Speaker 1: you know, financial crimes. They have violated human rights enormously. 152 00:10:49,679 --> 00:10:54,200 Speaker 1: So the question is will the middle ranking officers that 153 00:10:54,240 --> 00:10:58,960 Speaker 1: are also starving decide to to follow the orders of 154 00:10:59,040 --> 00:11:01,960 Speaker 1: this top brass or will there be a break in 155 00:11:02,240 --> 00:11:07,000 Speaker 1: military discipline that could itself be relatively messy. Ricardo Houseman, 156 00:11:07,080 --> 00:11:09,400 Speaker 1: thank you so much for being with us, and we 157 00:11:09,679 --> 00:11:12,200 Speaker 1: need to have you back as this situation progresses. He 158 00:11:12,280 --> 00:11:14,640 Speaker 1: is director of the Center for International Development and professor 159 00:11:14,679 --> 00:11:18,080 Speaker 1: of the Practice of Economic Development that Harvard's Kennedy School. 160 00:11:18,120 --> 00:11:35,000 Speaker 1: He's also the former Minister of Planning for Venezuela. President 161 00:11:35,000 --> 00:11:38,320 Speaker 1: Trump tweeted this morning, China has agreed to buy massive 162 00:11:38,360 --> 00:11:43,520 Speaker 1: amounts of additional farm slash agricultural products. Would be one 163 00:11:43,559 --> 00:11:46,240 Speaker 1: of the best things to happen to our farmers in 164 00:11:46,480 --> 00:11:50,880 Speaker 1: many years. Certainly, people who trade futures on soybeans and 165 00:11:50,920 --> 00:11:54,720 Speaker 1: corn seemed enthusiastic by thawing of trade tensions between the 166 00:11:54,800 --> 00:11:58,559 Speaker 1: US and China, with futures popping ahead of trading, considering 167 00:11:58,600 --> 00:12:02,280 Speaker 1: to see some of arise in early trading in the market. 168 00:12:02,280 --> 00:12:05,559 Speaker 1: Allam Buerka joins is now he's agricultural reporter for Bloomberg 169 00:12:05,600 --> 00:12:08,520 Speaker 1: News and Bloomberg Radio host Ellen, thank you so much 170 00:12:08,559 --> 00:12:10,880 Speaker 1: for being with us. I would love to get your take, 171 00:12:11,240 --> 00:12:13,959 Speaker 1: first of all, on what we've seen between the US 172 00:12:14,080 --> 00:12:16,640 Speaker 1: and China and kind of just to sort of emphasize 173 00:12:16,679 --> 00:12:20,600 Speaker 1: how important this is for US agricultural industries. I think 174 00:12:20,640 --> 00:12:23,000 Speaker 1: one thing that's important to remember with agriculture and some 175 00:12:23,080 --> 00:12:25,280 Speaker 1: of its reaction to the Trump administration's move is what's 176 00:12:25,280 --> 00:12:27,640 Speaker 1: now become the famous phrase. You know, folks in the 177 00:12:27,679 --> 00:12:31,400 Speaker 1: media take Trump literally but not seriously, whereas his followers 178 00:12:31,440 --> 00:12:34,880 Speaker 1: take him seriously but not literally. Um, when you take 179 00:12:34,880 --> 00:12:36,800 Speaker 1: a look at agriculture markets and everything that's been going 180 00:12:36,800 --> 00:12:40,160 Speaker 1: on with China, when Trump rattles the saber, of course 181 00:12:40,320 --> 00:12:43,560 Speaker 1: people get concerned with sorghum prices and soybean prices and 182 00:12:43,600 --> 00:12:45,840 Speaker 1: such and so. But they don't they don't they don't 183 00:12:45,840 --> 00:12:48,400 Speaker 1: think there's an impending catastrophe. You know, they're not necessarily 184 00:12:48,400 --> 00:12:51,720 Speaker 1: following the headlines as closely. You're seeing the same thing today. 185 00:12:51,760 --> 00:12:54,000 Speaker 1: I mean, obviously the president tweeting that this is good 186 00:12:54,040 --> 00:12:56,240 Speaker 1: for farmers and there could be some massive new increases 187 00:12:56,240 --> 00:12:59,120 Speaker 1: in agriculture are bullish for markets, and you're seeing that 188 00:12:59,160 --> 00:13:02,480 Speaker 1: market reaction. But like so many things with this administration, um, 189 00:13:02,520 --> 00:13:04,920 Speaker 1: there's a very much a weight and see attitude. You 190 00:13:05,000 --> 00:13:08,440 Speaker 1: don't know if the trade talk will turn sour in 191 00:13:08,480 --> 00:13:10,320 Speaker 1: a couple three months. When the President is trying to 192 00:13:10,320 --> 00:13:13,160 Speaker 1: show up reelection campaigns with perhaps some anti China rhetoric, 193 00:13:13,559 --> 00:13:17,680 Speaker 1: you haven't actually seen the sales materialize. That said, there 194 00:13:17,720 --> 00:13:20,679 Speaker 1: is reason to be bullish because this is actually an 195 00:13:20,679 --> 00:13:23,040 Speaker 1: area where, indeed, if China wanted to try to reduce 196 00:13:23,040 --> 00:13:25,600 Speaker 1: its trade deficit with the US. Agriculture would be a 197 00:13:25,600 --> 00:13:27,600 Speaker 1: logical place to go because this is a case where 198 00:13:27,600 --> 00:13:30,280 Speaker 1: the US does have a supply of something for which 199 00:13:30,320 --> 00:13:32,800 Speaker 1: there is demand in China, and so there probably is 200 00:13:32,840 --> 00:13:35,160 Speaker 1: something real behind this rhetoric. At this point of course, 201 00:13:35,160 --> 00:13:38,160 Speaker 1: the question is how real is it going to be? Okay, 202 00:13:38,200 --> 00:13:40,200 Speaker 1: at the same time, we don't have a farm bill, 203 00:13:40,280 --> 00:13:43,040 Speaker 1: do we know we don't have a farm bill? And um, 204 00:13:43,120 --> 00:13:45,520 Speaker 1: that's another part of this narrative. And and this is 205 00:13:45,559 --> 00:13:47,840 Speaker 1: the exactly the narrative that the President is trying to 206 00:13:47,960 --> 00:13:51,680 Speaker 1: counter with this China announcement that Republican leadership and a 207 00:13:51,720 --> 00:13:55,080 Speaker 1: Republican White House hasn't necessarily been a blessing for the 208 00:13:55,120 --> 00:13:58,560 Speaker 1: farmers that voted for the president. UM On Friday, you 209 00:13:58,640 --> 00:14:01,720 Speaker 1: saw the House Farm Bill, which looked like it was 210 00:14:01,880 --> 00:14:04,360 Speaker 1: on a path to passage. It was people were starting 211 00:14:04,360 --> 00:14:06,640 Speaker 1: to become more optimistic that this thing that did not 212 00:14:06,760 --> 00:14:09,040 Speaker 1: have any Democratic support could actually get through the House. 213 00:14:09,600 --> 00:14:12,440 Speaker 1: When it got derailed by the House Freedom Caucus UM, 214 00:14:12,520 --> 00:14:15,319 Speaker 1: which wants to use the farm bill basically as leveraged 215 00:14:15,360 --> 00:14:18,440 Speaker 1: to have a vote on a controversial immigration plan. The 216 00:14:18,440 --> 00:14:20,480 Speaker 1: farm bill, is this nice sort of mid range bill 217 00:14:20,480 --> 00:14:22,880 Speaker 1: where it's not so absolutely important that it must be 218 00:14:22,920 --> 00:14:26,040 Speaker 1: passed immediately, but it's not so unimportant that it can't 219 00:14:26,040 --> 00:14:29,320 Speaker 1: be taken hostage. And he used to be extracted for concessions. 220 00:14:29,360 --> 00:14:33,800 Speaker 1: That's what happened. The concern with rural Republicans, especially Republicans 221 00:14:33,800 --> 00:14:37,840 Speaker 1: in rural districts, were expressed by a guy, freshman Congressman 222 00:14:37,880 --> 00:14:42,840 Speaker 1: Jody Arrington, he represents the Lubbock West, Texas Abilene area, saying, 223 00:14:42,920 --> 00:14:45,080 Speaker 1: you know, farmers have to be scratching their heads over 224 00:14:45,120 --> 00:14:48,000 Speaker 1: some of the actions that this Republican Congress and Republican 225 00:14:48,000 --> 00:14:51,560 Speaker 1: administration have been taking that have not necessarily been playing 226 00:14:51,600 --> 00:14:54,680 Speaker 1: into the interests of what agriculture might want. This is 227 00:14:54,720 --> 00:14:57,880 Speaker 1: a constituency that survey show voted about two thirds for 228 00:14:57,880 --> 00:15:01,480 Speaker 1: the president, and thus far, whenever there's a problem a 229 00:15:01,600 --> 00:15:04,680 Speaker 1: decision made between rust belt rural and farm belt rural, 230 00:15:04,960 --> 00:15:07,320 Speaker 1: it always seems like the farm belt gets the short end. 231 00:15:07,360 --> 00:15:10,920 Speaker 1: We'll see if this China decision just recently that that 232 00:15:10,960 --> 00:15:12,960 Speaker 1: starts to push a counter narrative. All right, so let's 233 00:15:13,000 --> 00:15:17,000 Speaker 1: put into perspective how much agricultural America depends on China 234 00:15:17,080 --> 00:15:19,480 Speaker 1: for its well being quite a heck of a lot. 235 00:15:19,840 --> 00:15:22,600 Speaker 1: Thanks for asking that question. About all right, about one 236 00:15:22,680 --> 00:15:25,920 Speaker 1: third of all US soybeans go straight to China um 237 00:15:26,000 --> 00:15:29,000 Speaker 1: and sorghum. It's actually a higher proportion cotton. It's also 238 00:15:29,040 --> 00:15:31,720 Speaker 1: I think about one quarter. And some of these markets 239 00:15:31,720 --> 00:15:34,640 Speaker 1: have really emerged. I mean, there was very little sorghum 240 00:15:35,080 --> 00:15:38,440 Speaker 1: exported to China before eleven, and now it's become incredibly 241 00:15:38,480 --> 00:15:41,400 Speaker 1: dependent on it. Um. China, of course, has been this 242 00:15:41,440 --> 00:15:43,480 Speaker 1: big source of growth. And when you saw that big 243 00:15:43,520 --> 00:15:48,840 Speaker 1: agricultural boom sort of in the late two thousands, it 244 00:15:48,920 --> 00:15:52,000 Speaker 1: was being driven by ethanol and by China. What's kind 245 00:15:52,000 --> 00:15:53,840 Speaker 1: of interesting about this announcement is when you take a 246 00:15:53,840 --> 00:15:57,240 Speaker 1: look at how China might be buying more US agricultural goods, 247 00:15:57,440 --> 00:15:59,360 Speaker 1: one of the things that China is looking at is 248 00:15:59,440 --> 00:16:03,080 Speaker 1: putting more or ethanol in its cars. Interesting. If ethanol 249 00:16:03,120 --> 00:16:05,880 Speaker 1: becomes a driver of corn demand in China the way 250 00:16:05,920 --> 00:16:08,200 Speaker 1: it was a driver of corn demand in the US, 251 00:16:08,240 --> 00:16:11,480 Speaker 1: that has profound impacts on corn markets. We haven't seen 252 00:16:11,600 --> 00:16:14,920 Speaker 1: the markets react quite to that yet, but I'm sure 253 00:16:15,040 --> 00:16:16,960 Speaker 1: suddenly a bunch of traders are going to become big 254 00:16:17,000 --> 00:16:19,600 Speaker 1: experts on China ethanol policy, because that's one place where 255 00:16:19,640 --> 00:16:22,360 Speaker 1: money can move quickly. That's fascinating. I'm just wondering as 256 00:16:22,360 --> 00:16:26,520 Speaker 1: we heard about these uh curtains of US agricultural produce 257 00:16:26,640 --> 00:16:29,800 Speaker 1: just rotting in the ports because China didn't want to 258 00:16:29,920 --> 00:16:33,200 Speaker 1: or delayed admission while these trade tensions were building with US. 259 00:16:33,440 --> 00:16:38,680 Speaker 1: Have we seen any impact from that activity already on prices? Well, 260 00:16:38,720 --> 00:16:41,040 Speaker 1: that was what was pushing things down. Um. You know, 261 00:16:41,400 --> 00:16:43,880 Speaker 1: it's not even so much the lack of sales. Because 262 00:16:44,040 --> 00:16:46,200 Speaker 1: markets are fungible, they have a way to to react. 263 00:16:46,240 --> 00:16:48,480 Speaker 1: You know, if Brazil starts selling all their soybeans to China, 264 00:16:48,480 --> 00:16:51,080 Speaker 1: the US soybeans will go someplace. But as you note it, 265 00:16:51,120 --> 00:16:54,080 Speaker 1: in the meantime, while the confusion reigns, they can actually 266 00:16:54,120 --> 00:16:56,800 Speaker 1: sit in a port and lose value. Um. And that 267 00:16:56,880 --> 00:17:00,400 Speaker 1: indeed has been going on. How much of that is versable. 268 00:17:00,400 --> 00:17:01,720 Speaker 1: It's going to kind of depend on some of the 269 00:17:01,720 --> 00:17:04,439 Speaker 1: logistics of the shipment itself. But we have seen a 270 00:17:04,480 --> 00:17:06,640 Speaker 1: little bit of a glimpse of what could happen when 271 00:17:06,720 --> 00:17:10,040 Speaker 1: China stops buying, which is going to give markets a 272 00:17:10,040 --> 00:17:12,920 Speaker 1: lot of relief if they get a signal like today 273 00:17:12,960 --> 00:17:15,680 Speaker 1: that they might be buying again. Alan, if we were 274 00:17:15,720 --> 00:17:18,960 Speaker 1: to tour the winter wheat belt, what would we find 275 00:17:19,080 --> 00:17:22,399 Speaker 1: right now? Uh, Well, you know, the Midwest got pummeled 276 00:17:22,400 --> 00:17:24,439 Speaker 1: with a lot of rain. The question is is it 277 00:17:24,520 --> 00:17:27,119 Speaker 1: too late for the harvest. You know, especially in Kansas 278 00:17:27,200 --> 00:17:29,320 Speaker 1: more your southern plains, they're starting to look at preparing 279 00:17:29,400 --> 00:17:32,399 Speaker 1: fields and doing some harvesting in the next few weeks. Um. 280 00:17:32,400 --> 00:17:33,800 Speaker 1: I'm sure they're gonna be taking a look at the 281 00:17:33,840 --> 00:17:36,200 Speaker 1: quality of the crops right now and figuring out whether 282 00:17:36,240 --> 00:17:37,919 Speaker 1: some of the moisture that they've gotten will actually help 283 00:17:37,960 --> 00:17:40,240 Speaker 1: them out. So where are we going to see any 284 00:17:40,359 --> 00:17:43,439 Speaker 1: kind of big changes in agriculture? Is it going to 285 00:17:43,480 --> 00:17:45,840 Speaker 1: be weather related or is it going to be purely 286 00:17:45,880 --> 00:17:49,040 Speaker 1: because of the confrontation with We're not we're not quite 287 00:17:49,080 --> 00:17:51,879 Speaker 1: into the weather market yet, although we're getting there. You know, 288 00:17:51,960 --> 00:17:54,680 Speaker 1: planting is now pretty fully underway. Um. In a lot 289 00:17:54,680 --> 00:17:56,840 Speaker 1: of more southern parts of the country, your spring planting 290 00:17:56,920 --> 00:17:59,760 Speaker 1: is has been done. If you're my parents up in Minnesota, 291 00:17:59,800 --> 00:18:01,720 Speaker 1: you're just getting to your fields right now because you 292 00:18:01,720 --> 00:18:05,840 Speaker 1: have those late season snowstorms. But um, at this point, 293 00:18:05,960 --> 00:18:08,640 Speaker 1: it is unusual some of these macro trade moves are 294 00:18:08,640 --> 00:18:11,560 Speaker 1: actually moving markets in a way that weather won't. I 295 00:18:11,640 --> 00:18:14,879 Speaker 1: guarantee you come July and August. It's not gonna matter 296 00:18:14,920 --> 00:18:17,400 Speaker 1: what President Trump is saying about trade. Farmers are gonna 297 00:18:17,400 --> 00:18:19,560 Speaker 1: wonder if there's rain, and that's what's gonna move commodity 298 00:18:19,560 --> 00:18:22,200 Speaker 1: markets in Chicago. Alan, what's the one thing we should 299 00:18:22,200 --> 00:18:24,320 Speaker 1: be looking forward to see whether the thoughting of the 300 00:18:24,320 --> 00:18:26,879 Speaker 1: trade talks is real. You've got to be looking at 301 00:18:26,920 --> 00:18:29,600 Speaker 1: weekly export sales at the USDA puts out reports on 302 00:18:29,600 --> 00:18:32,160 Speaker 1: Thursday about how much got bought of where um. If 303 00:18:32,200 --> 00:18:35,760 Speaker 1: you start seeing tangible changes in these volumes, then indeed, 304 00:18:35,760 --> 00:18:38,000 Speaker 1: this this is real and this is a bowl market. 305 00:18:38,720 --> 00:18:43,119 Speaker 1: Give you twenty seconds, NAFTA, Where are we there? NAFTA Again, 306 00:18:43,200 --> 00:18:45,480 Speaker 1: just uncertainty, things sort of muddling along. And that's a 307 00:18:45,520 --> 00:18:48,400 Speaker 1: case where the farm constituency has sort of become comfortable 308 00:18:48,440 --> 00:18:50,960 Speaker 1: with US uncertainty. You don't see NAFTA being the driver 309 00:18:51,040 --> 00:18:52,760 Speaker 1: the way it was a few months ago. All Right, 310 00:18:52,800 --> 00:18:54,640 Speaker 1: I want to thank you very much for being with us. 311 00:18:54,880 --> 00:18:58,679 Speaker 1: Alan Bjorka is our expert for all things agriculture. Are 312 00:18:58,800 --> 00:19:02,800 Speaker 1: agriculture reporter from Bloomberg joining us from our one studios 313 00:19:02,840 --> 00:19:06,440 Speaker 1: in Washington, d c Yes, Lisa, I just I love 314 00:19:06,600 --> 00:19:09,880 Speaker 1: I love looking at the futures of corn and of sorghum, 315 00:19:10,080 --> 00:19:12,400 Speaker 1: and so I think this is super important. I think 316 00:19:12,400 --> 00:19:14,520 Speaker 1: that this is a lot of where the trade deal 317 00:19:14,560 --> 00:19:18,320 Speaker 1: and the trade negotiations will live, and that there is 318 00:19:18,359 --> 00:19:20,680 Speaker 1: definitely some skepticism because there isn't the same kind of 319 00:19:20,760 --> 00:19:23,400 Speaker 1: runaway rally you've seen. I was gonna say, you've seen 320 00:19:23,400 --> 00:19:26,639 Speaker 1: a fifty cent per bushel increase in the price of 321 00:19:26,720 --> 00:19:29,760 Speaker 1: corn since the beginning of the year. So, but that's 322 00:19:29,840 --> 00:19:31,399 Speaker 1: due to a lot of things, right, there are a 323 00:19:31,440 --> 00:19:34,040 Speaker 1: bunch of different factors, with people planting less of them, 324 00:19:34,560 --> 00:19:37,360 Speaker 1: less less of corn plants, and more so by being 325 00:19:37,480 --> 00:19:38,840 Speaker 1: so I mean, there are a bunch of different factors. 326 00:19:38,880 --> 00:19:40,760 Speaker 1: But yes, there's been a market increase, and we're going 327 00:19:40,800 --> 00:19:42,200 Speaker 1: to watch and see if they can get a farm 328 00:19:42,240 --> 00:19:44,440 Speaker 1: bill together. I know that the Senate has their own 329 00:19:44,520 --> 00:19:46,280 Speaker 1: version of a farm bill that they are trying to 330 00:19:46,640 --> 00:20:03,879 Speaker 1: put together. Bloomberg Markets brought to you by b and 331 00:20:04,000 --> 00:20:10,119 Speaker 1: Y Melons Insight Conference. It must attend for advisors June 332 00:20:10,119 --> 00:20:13,159 Speaker 1: six through the eighth in Orlando, Florida. Registered at b 333 00:20:13,240 --> 00:20:20,000 Speaker 1: and Y melon Insight dot com. Pam let's talk about robotics, please, 334 00:20:20,280 --> 00:20:23,639 Speaker 1: artificial and artificial intelligence and artificial intelligence and all that 335 00:20:23,680 --> 00:20:27,320 Speaker 1: great stuff. We're looking at the robo et F. It's 336 00:20:27,320 --> 00:20:29,520 Speaker 1: a two point three billion dollar e t F and 337 00:20:29,640 --> 00:20:33,000 Speaker 1: last year returned more than forty four I want to 338 00:20:33,000 --> 00:20:36,520 Speaker 1: bring in the CEO and partner of robo Global LLC, 339 00:20:37,080 --> 00:20:40,160 Speaker 1: Travis Briggs, who comes to us from Dallas, Texas. Travis, 340 00:20:40,160 --> 00:20:42,919 Speaker 1: thank you so much for joining us. I want to 341 00:20:42,960 --> 00:20:48,560 Speaker 1: start with what makes a company a robotics company? Well, 342 00:20:48,600 --> 00:20:52,720 Speaker 1: thank you for having me. Um. You know, we the 343 00:20:52,760 --> 00:20:56,160 Speaker 1: way that the lens that we look at robotics, automation 344 00:20:56,200 --> 00:21:00,920 Speaker 1: and AI is really from a percentage of revenue directly 345 00:21:01,200 --> 00:21:05,560 Speaker 1: or indirectly attributed to robots automation. So when you look 346 00:21:05,600 --> 00:21:09,440 Speaker 1: at the index, you'd be surprised to know there's over 347 00:21:09,520 --> 00:21:13,399 Speaker 1: eighty companies and and they they all focus on different 348 00:21:13,400 --> 00:21:16,680 Speaker 1: parts of the value chain of robotics and automation. So 349 00:21:16,760 --> 00:21:19,719 Speaker 1: half half of the half of the index is focused 350 00:21:19,760 --> 00:21:24,840 Speaker 1: on the technologies that enable the enabling technologies that allow 351 00:21:25,680 --> 00:21:28,639 Speaker 1: robotics actually sense, process and act. The other half is 352 00:21:28,680 --> 00:21:33,680 Speaker 1: the applications like drones or industrial manufacturing robots or logistics 353 00:21:33,680 --> 00:21:39,480 Speaker 1: automation or healthcare robots, things that you would immediately recognize, Travis. 354 00:21:39,560 --> 00:21:41,840 Speaker 1: Maybe let's talk about some examples if we can, that 355 00:21:41,880 --> 00:21:45,719 Speaker 1: way people can get a better idea. For example, ocean 356 00:21:45,760 --> 00:21:50,960 Speaker 1: Eering International, they use robotic and remote sensing technology in 357 00:21:51,080 --> 00:21:56,120 Speaker 1: order to become more efficient in the oil industry. That's right. 358 00:21:56,480 --> 00:22:00,960 Speaker 1: So that's one of the components of our energy sector. Oceaneering, 359 00:22:01,240 --> 00:22:03,639 Speaker 1: which is a bell weather meaning it has a high 360 00:22:03,720 --> 00:22:10,080 Speaker 1: revenue attribution to robotics UM uses what's called remote operated vehicles, 361 00:22:10,160 --> 00:22:14,360 Speaker 1: and those are simply robots that can go very deep 362 00:22:14,400 --> 00:22:18,520 Speaker 1: into the sea to monitor, to perform maintenance, to perform drilling. 363 00:22:18,880 --> 00:22:22,479 Speaker 1: It essentially allows companies, energy companies to drill where they 364 00:22:22,480 --> 00:22:25,160 Speaker 1: hadn't been able to drill before. And also you've got 365 00:22:25,200 --> 00:22:28,960 Speaker 1: Intuitive Surgical, so that's another health gets a health care application. 366 00:22:29,000 --> 00:22:32,399 Speaker 1: That's another example of a company in the index. Right, 367 00:22:32,440 --> 00:22:38,320 Speaker 1: they have the Da Vinci surgical system. That's that's absolutely right. Um, 368 00:22:38,480 --> 00:22:40,639 Speaker 1: we're seeing that's one of the biggest growth areas is 369 00:22:40,640 --> 00:22:45,720 Speaker 1: in surgical robotics, with not only uh Intuitive Surgical, but 370 00:22:45,920 --> 00:22:49,440 Speaker 1: also mas or robotics and others that are in the index. 371 00:22:49,520 --> 00:22:52,160 Speaker 1: So do you've you've touched on a couple of companies 372 00:22:52,200 --> 00:22:54,840 Speaker 1: on the application side. Let me give you an example 373 00:22:55,760 --> 00:22:58,040 Speaker 1: of a company that maybe your listeners haven't heard of 374 00:22:58,240 --> 00:23:01,720 Speaker 1: on the technology side, and that's cod Next, that's a 375 00:23:01,840 --> 00:23:07,159 Speaker 1: US based company, world leading machine vision company. You think, okay, well, 376 00:23:07,320 --> 00:23:10,320 Speaker 1: what does machine vision have to do with robotics. Turns 377 00:23:10,359 --> 00:23:13,680 Speaker 1: out it's a critical enabling technology of robotics. When you 378 00:23:13,760 --> 00:23:17,920 Speaker 1: think about surgical robots, you think about industrial manufacturing robots, 379 00:23:18,080 --> 00:23:21,800 Speaker 1: or even drones, a key component is their ability to 380 00:23:21,880 --> 00:23:25,800 Speaker 1: see right, is to sense their surroundings. So the machine vision, 381 00:23:25,840 --> 00:23:30,719 Speaker 1: the technology component, actually applies across multiple applications. We'll just 382 00:23:30,760 --> 00:23:33,040 Speaker 1: say that we do know about Cognis because it's based 383 00:23:33,040 --> 00:23:37,040 Speaker 1: in nati uh and of course Natick and Boston area 384 00:23:37,160 --> 00:23:43,560 Speaker 1: home Boston a Newburyport. But the stocks down this year, 385 00:23:43,720 --> 00:23:48,119 Speaker 1: Why is that? Well, I'll say this, Uh, you know, 386 00:23:48,200 --> 00:23:50,400 Speaker 1: stocks will go up and down in the short term, 387 00:23:50,440 --> 00:23:53,359 Speaker 1: but if you if you increase that lens to look 388 00:23:53,400 --> 00:23:56,399 Speaker 1: back two and a half years ago, I think the 389 00:23:56,440 --> 00:24:01,960 Speaker 1: stocks probably up over so short term pullback, but the 390 00:24:01,960 --> 00:24:04,560 Speaker 1: previous two years have been outstanding for the company, and 391 00:24:04,840 --> 00:24:08,560 Speaker 1: we think the future continues to look bright. So Travis 392 00:24:08,600 --> 00:24:10,600 Speaker 1: I want to assume out a little bit because we 393 00:24:10,600 --> 00:24:12,920 Speaker 1: hear a lot about how artificial intelligence is going to 394 00:24:13,000 --> 00:24:16,960 Speaker 1: transform every industry out there. Are you noticing that an 395 00:24:16,960 --> 00:24:21,080 Speaker 1: increasing number of companies are deriving a greater proportion of 396 00:24:21,119 --> 00:24:26,400 Speaker 1: the revenues from robotics and artificial intelligence and automation. Yeah, 397 00:24:26,480 --> 00:24:29,760 Speaker 1: the question on artificial intelligence is is a really good 398 00:24:29,760 --> 00:24:33,960 Speaker 1: one because it's it's it highlights how quickly this area 399 00:24:34,000 --> 00:24:36,840 Speaker 1: is changing. You know, we we launched that index will 400 00:24:36,880 --> 00:24:39,960 Speaker 1: be five years ago in August, and the reality is 401 00:24:40,040 --> 00:24:43,639 Speaker 1: a I was was a footnote um and within the 402 00:24:43,720 --> 00:24:48,679 Speaker 1: last two years, I'd say um AI has become at 403 00:24:48,720 --> 00:24:53,280 Speaker 1: the forefront of all conversations around automation. And the reason 404 00:24:53,400 --> 00:24:56,920 Speaker 1: that is is, you know, we now have extremely powerful 405 00:24:56,960 --> 00:25:02,040 Speaker 1: sensors and processing chips that the price reasonably. You have 406 00:25:02,119 --> 00:25:06,080 Speaker 1: these massive data centers that can process enormous amounts of 407 00:25:06,119 --> 00:25:11,240 Speaker 1: data and essentially, when you think about AI, it's algorithms, 408 00:25:11,240 --> 00:25:16,639 Speaker 1: processing power and then data. And of all the digital 409 00:25:16,720 --> 00:25:21,240 Speaker 1: data that's been captured through through history was captured in 410 00:25:21,280 --> 00:25:24,760 Speaker 1: the last two years. Now you created the index? Correct? 411 00:25:25,520 --> 00:25:29,879 Speaker 1: That is correct? And what motivates the index? In other words, 412 00:25:29,920 --> 00:25:32,600 Speaker 1: is there a person that decides what goes in what 413 00:25:32,680 --> 00:25:38,159 Speaker 1: goes out. Yeah, So the primary objective when we created 414 00:25:38,200 --> 00:25:42,800 Speaker 1: the index was to capture the entire ecosystem, or think 415 00:25:42,800 --> 00:25:45,879 Speaker 1: of it as the value chain. We we wanted to 416 00:25:46,000 --> 00:25:49,840 Speaker 1: make sure that when this theme of robotics and automation 417 00:25:49,880 --> 00:25:53,640 Speaker 1: continued to grow and expand as quickly as it has, 418 00:25:53,840 --> 00:25:57,280 Speaker 1: that we had identified the companies that would benefit from that. 419 00:25:57,640 --> 00:26:00,480 Speaker 1: And we realized earlier on the best coach was a 420 00:26:00,480 --> 00:26:04,480 Speaker 1: diversified one, and so, as I mentioned earlier, we chose 421 00:26:04,520 --> 00:26:07,400 Speaker 1: to capture the entire value chain, everything from the sensors, 422 00:26:07,480 --> 00:26:11,560 Speaker 1: the processing, the computing, you know, to the end use applications. 423 00:26:11,840 --> 00:26:16,440 Speaker 1: Hell as you mentioned oceaneering, surgical robots, industrial manufacturing robots 424 00:26:16,440 --> 00:26:21,040 Speaker 1: and such. So, as I mentioned earlier, the robo et 425 00:26:21,280 --> 00:26:24,120 Speaker 1: F was up more than forty four percent last year. 426 00:26:24,480 --> 00:26:28,639 Speaker 1: This year it's underperforming some of the broader US stock indusseries. 427 00:26:28,840 --> 00:26:30,200 Speaker 1: What do you expect, I mean, what do you what 428 00:26:30,240 --> 00:26:32,080 Speaker 1: do you attribute to sort of the underperformance and what 429 00:26:32,119 --> 00:26:36,800 Speaker 1: do you see the potential performance later? Sure? I think, um, 430 00:26:36,840 --> 00:26:38,679 Speaker 1: if you look at the index and the performance of 431 00:26:38,680 --> 00:26:43,160 Speaker 1: the index since inception, which has booked over a four 432 00:26:43,240 --> 00:26:48,240 Speaker 1: year track record, UM on average, it has outperformed the 433 00:26:48,240 --> 00:26:52,359 Speaker 1: broad market indusseries. And I think when you have a 434 00:26:52,520 --> 00:26:57,280 Speaker 1: focus on companies that are growing as quickly as these 435 00:26:57,560 --> 00:27:01,320 Speaker 1: as this robotics and automation sector is, is that you 436 00:27:01,359 --> 00:27:04,960 Speaker 1: would hope right. The obvious objective is to outperform broad 437 00:27:05,000 --> 00:27:11,199 Speaker 1: market indices over traditional market cycles just quickly. When you 438 00:27:11,280 --> 00:27:16,960 Speaker 1: talk about robotics, does that also include um uh sort 439 00:27:16,960 --> 00:27:22,040 Speaker 1: of systems in the aerospace and defense industry. So we 440 00:27:22,160 --> 00:27:27,320 Speaker 1: do have a subsector. There are twelve subsectors in the index, 441 00:27:28,000 --> 00:27:33,360 Speaker 1: one of which is surveillance, and it does include companies 442 00:27:33,640 --> 00:27:39,720 Speaker 1: that are UH focused on researching and development for the 443 00:27:40,160 --> 00:27:46,119 Speaker 1: unmanned aeral vehicle UH applications or overdrones. YEP, that's right, 444 00:27:46,320 --> 00:27:48,600 Speaker 1: Thanks very much for being with us. Travis Briggs is 445 00:27:48,600 --> 00:27:52,040 Speaker 1: the chief executive and the partner of robo a Global 446 00:27:52,080 --> 00:27:54,640 Speaker 1: based in Dallas, Texas, helping to manage more than two 447 00:27:54,680 --> 00:28:13,080 Speaker 1: point four billion dollars. Shares of General Electric they're higher 448 00:28:13,119 --> 00:28:15,840 Speaker 1: by three and a half percent. The shares of web 449 00:28:15,880 --> 00:28:18,320 Speaker 1: Tech they are up more than four and a quarter percent. 450 00:28:18,359 --> 00:28:21,159 Speaker 1: Here to tell us more, Brooks Sutherland Industrials and Deal's 451 00:28:21,240 --> 00:28:25,560 Speaker 1: columnists for Bloomberg opinion brook always a pleasure. Maybe you 452 00:28:25,560 --> 00:28:29,040 Speaker 1: could just explain what exactly is General Electric doing with 453 00:28:29,200 --> 00:28:34,159 Speaker 1: its locomotive business A little bit complicated. Um So, what 454 00:28:34,200 --> 00:28:36,720 Speaker 1: they're going to do is they're going to actually sell 455 00:28:36,920 --> 00:28:40,160 Speaker 1: a portion of the locomotive business to wob Tech. Then 456 00:28:40,200 --> 00:28:43,200 Speaker 1: they're going to spin off what's left of the transportation 457 00:28:43,200 --> 00:28:46,880 Speaker 1: division to its own shareholders, and then they'll merge that 458 00:28:47,000 --> 00:28:50,480 Speaker 1: spun off portion with wob Tech. Um So, sort of 459 00:28:50,520 --> 00:28:52,520 Speaker 1: a roundabout way. And the reason why they're doing that 460 00:28:52,600 --> 00:28:55,840 Speaker 1: is that this all ends up being tax free to shareholders, 461 00:28:56,160 --> 00:28:58,640 Speaker 1: which is what investors like to see. Um g E 462 00:28:58,720 --> 00:29:01,480 Speaker 1: will get a two point nine billion dollar cash payment 463 00:29:01,640 --> 00:29:05,160 Speaker 1: up front, and then between it and its shareholders that 464 00:29:05,200 --> 00:29:08,640 Speaker 1: will own about fifty point one percent of the combined entity. 465 00:29:09,120 --> 00:29:11,640 Speaker 1: So let's let's take a step back. Yes, shares are 466 00:29:11,760 --> 00:29:14,680 Speaker 1: up today, but they are still down nearly so far. 467 00:29:14,800 --> 00:29:18,680 Speaker 1: You're to date, General Electric is whild widely expected to 468 00:29:18,720 --> 00:29:22,520 Speaker 1: have to restructure its entire operations, possibly sell off traumatic 469 00:29:22,560 --> 00:29:26,080 Speaker 1: parts of its business. So do we get any insight 470 00:29:26,360 --> 00:29:29,120 Speaker 1: into what the leadership is thinking with respect to that 471 00:29:29,160 --> 00:29:33,200 Speaker 1: restructuring based on the deal announced today? Sure? So, Transportation 472 00:29:33,240 --> 00:29:35,760 Speaker 1: is a division that they have flagged for divested sure 473 00:29:35,840 --> 00:29:38,120 Speaker 1: since about November, so they said, you know, we're looking 474 00:29:38,200 --> 00:29:41,600 Speaker 1: at options for this. So it's definitely good to see 475 00:29:41,640 --> 00:29:44,360 Speaker 1: a deal actually happening here. I think investors were starting 476 00:29:44,400 --> 00:29:46,440 Speaker 1: to get a little bit restless that we hadn't really 477 00:29:46,480 --> 00:29:50,000 Speaker 1: seen any sort of major portfolio action. They did an 478 00:29:50,080 --> 00:29:52,280 Speaker 1: asset sale a little while ago with a healthcare I 479 00:29:52,320 --> 00:29:55,000 Speaker 1: T business, but that was fairly small, and so this 480 00:29:55,080 --> 00:29:57,640 Speaker 1: is the most significant thing we've seen to date. But 481 00:29:58,040 --> 00:30:00,560 Speaker 1: you know, I do think sort of the devil is 482 00:30:00,600 --> 00:30:03,240 Speaker 1: in the details here, and you know, they've done asset 483 00:30:03,280 --> 00:30:06,840 Speaker 1: divestitures before, and the purchase price has wound up not 484 00:30:06,960 --> 00:30:09,360 Speaker 1: being as great as it looks, just because you know, 485 00:30:09,400 --> 00:30:11,480 Speaker 1: you have to use some of that cash in the 486 00:30:11,520 --> 00:30:14,200 Speaker 1: case of the industrial solutions business that they sold to 487 00:30:14,280 --> 00:30:16,520 Speaker 1: a b B last year, use some of that cash 488 00:30:16,560 --> 00:30:19,400 Speaker 1: to pay back g capital for accounts receivable as you 489 00:30:19,440 --> 00:30:22,640 Speaker 1: have deal taxes. And then there's the pension liabilities that 490 00:30:22,680 --> 00:30:26,080 Speaker 1: are associated with a lot of these businesses. Oftentimes g 491 00:30:26,280 --> 00:30:29,280 Speaker 1: E retains those liabilities and does not pass those on 492 00:30:29,400 --> 00:30:31,920 Speaker 1: to the buyer, which creates sort of an obvious problem 493 00:30:31,960 --> 00:30:35,120 Speaker 1: as you look down the line in terms of more divestitures, 494 00:30:35,120 --> 00:30:37,680 Speaker 1: possible breakups. You know, how does GE find a home 495 00:30:37,720 --> 00:30:40,160 Speaker 1: for all of these assets and yet still get stuck 496 00:30:40,200 --> 00:30:44,880 Speaker 1: with a very big pension liability. Is there any information 497 00:30:44,920 --> 00:30:48,840 Speaker 1: as to why they believe that combining their locomotive business 498 00:30:48,880 --> 00:30:51,240 Speaker 1: with web tech is good for them? Sure, you know, 499 00:30:51,280 --> 00:30:53,520 Speaker 1: I do think this is a good deal on the 500 00:30:53,560 --> 00:30:55,640 Speaker 1: face of it. Um. You know, I think for wab 501 00:30:55,680 --> 00:31:00,440 Speaker 1: Tech it's clearly very transformational, significantly increases its business. UM. 502 00:31:00,480 --> 00:31:02,720 Speaker 1: You know, the locomotive business is a sort of a 503 00:31:02,800 --> 00:31:05,920 Speaker 1: cyclical low point um demand has been weak, but we're 504 00:31:06,000 --> 00:31:09,360 Speaker 1: just starting to see that pick up. This combined entity 505 00:31:09,400 --> 00:31:12,200 Speaker 1: will be able to take advantage of that. UM. It'll 506 00:31:12,240 --> 00:31:16,160 Speaker 1: have opportunities for cost savings, higher profitability. You know, I 507 00:31:16,600 --> 00:31:18,480 Speaker 1: think on the face of it it makes sense. It's 508 00:31:18,520 --> 00:31:20,160 Speaker 1: just as you sort of take a step back and 509 00:31:20,160 --> 00:31:23,640 Speaker 1: look at what this means bigger picture for GE. I 510 00:31:23,680 --> 00:31:26,200 Speaker 1: think that's where really sort of the interesting element is. 511 00:31:26,240 --> 00:31:28,360 Speaker 1: And you know, it's been sort of talked about could 512 00:31:28,440 --> 00:31:30,920 Speaker 1: you do a full blown breakup of G And I 513 00:31:30,920 --> 00:31:34,760 Speaker 1: think this structure with loob Tech, where you have, you know, 514 00:31:34,840 --> 00:31:37,800 Speaker 1: sort of a convoluted way of holding onto a stake 515 00:31:37,840 --> 00:31:40,280 Speaker 1: in the combined business and still getting some cash out 516 00:31:40,320 --> 00:31:42,640 Speaker 1: of it is something that g could explore for other 517 00:31:42,680 --> 00:31:44,880 Speaker 1: pieces of its business. But just to go back to 518 00:31:44,920 --> 00:31:47,320 Speaker 1: what I was talking to do do before, the real question 519 00:31:47,360 --> 00:31:49,120 Speaker 1: is you know what you do with sort of the 520 00:31:49,600 --> 00:31:52,720 Speaker 1: liabilities they're attached to these businesses. We don't have details 521 00:31:52,720 --> 00:31:55,400 Speaker 1: on that yet. I expect that will come in regulatory filings, 522 00:31:55,400 --> 00:31:57,040 Speaker 1: and that's going to be something investors are going to 523 00:31:57,080 --> 00:31:59,200 Speaker 1: want to pay close attention to. How do you have 524 00:31:59,240 --> 00:32:03,320 Speaker 1: a sense of the volume of pension liabilities that could 525 00:32:03,400 --> 00:32:07,640 Speaker 1: get sort of shunted back to GE if that's part 526 00:32:07,640 --> 00:32:11,360 Speaker 1: of this deal. Sure, So the underfunded pension was about 527 00:32:11,400 --> 00:32:14,920 Speaker 1: twenty eight point seven billion at the end of overall 528 00:32:15,000 --> 00:32:17,400 Speaker 1: for all of G for all of g e UM. 529 00:32:17,440 --> 00:32:20,120 Speaker 1: You know, JP Morgan Chase and co analyst Steve two 530 00:32:20,200 --> 00:32:23,320 Speaker 1: Sad did some interesting work on the Industrial Solutions business 531 00:32:23,800 --> 00:32:27,480 Speaker 1: UM and pointed out that, you know, the pension associated 532 00:32:27,480 --> 00:32:30,480 Speaker 1: with assets held for sale was about forty two million, 533 00:32:30,600 --> 00:32:34,040 Speaker 1: even though Industrial Solutions has I think it's about thirteen 534 00:32:34,080 --> 00:32:37,920 Speaker 1: thousand employees, so obviously it should be a much bigger percentage. 535 00:32:38,000 --> 00:32:41,760 Speaker 1: Transportation I believe has about eight thousand employees, so I mean, 536 00:32:42,280 --> 00:32:44,720 Speaker 1: if you sort of extrapolate what we saw with industrial 537 00:32:44,760 --> 00:32:48,840 Speaker 1: solutions and apply that to maybe a potential outcome for transportation. Again, 538 00:32:48,880 --> 00:32:50,640 Speaker 1: we don't have any details on this yet, so it's 539 00:32:50,640 --> 00:32:52,720 Speaker 1: sort of hard to say, but you know, if if 540 00:32:52,720 --> 00:32:55,000 Speaker 1: you have sort of a similar percentage, you can easily 541 00:32:55,040 --> 00:32:57,360 Speaker 1: see how ge gets stuck with sort of these billions 542 00:32:57,360 --> 00:33:01,840 Speaker 1: of liabilities without assets underneath to with that. Well, I 543 00:33:01,840 --> 00:33:04,080 Speaker 1: know that Lisa is eager to get her hands on 544 00:33:04,120 --> 00:33:09,200 Speaker 1: an HSP forty six high horsepower passenger locomotive that Correct 545 00:33:09,400 --> 00:33:14,280 Speaker 1: and web Tech actually builds already with partnership with General. Honestly, 546 00:33:14,680 --> 00:33:17,960 Speaker 1: Pim knows my innermost dreams and thoughts when it comes 547 00:33:18,000 --> 00:33:21,520 Speaker 1: to locomotives, and uh, you know, then I'll just let 548 00:33:21,600 --> 00:33:24,520 Speaker 1: you know the launch customer for the one version of 549 00:33:24,920 --> 00:33:30,160 Speaker 1: this the A is the Massachusetts Bay Transportation Authority. And 550 00:33:30,280 --> 00:33:35,120 Speaker 1: Lisa Abramowitz, thank you so much million apiece and you'll 551 00:33:35,160 --> 00:33:37,920 Speaker 1: front me the money, okay, A brook Sutherland, thank you 552 00:33:37,960 --> 00:33:40,840 Speaker 1: so much for being with us. Really fascinating, really good 553 00:33:40,880 --> 00:33:43,480 Speaker 1: insights on the idea of these pension liabilities, which could 554 00:33:43,480 --> 00:33:48,720 Speaker 1: potentially make investors a little less enthusiastic about this cash infusion. 555 00:33:48,800 --> 00:33:53,160 Speaker 1: Brick Sutherland is an industrials and deals columnist for Bloomberg Opinion. 556 00:33:55,600 --> 00:33:58,160 Speaker 1: Thanks for listening to the Bloomberg p m L podcast. 557 00:33:58,480 --> 00:34:02,400 Speaker 1: You can subscribe and listen to views at Apple Podcasts, SoundCloud, 558 00:34:02,520 --> 00:34:06,000 Speaker 1: or whatever podcast platform you prefer. I'm pim Fox. I'm 559 00:34:06,000 --> 00:34:10,040 Speaker 1: on Twitter at pim Fox. I'm on Twitter at Lisa Abramo. 560 00:34:10,160 --> 00:34:12,759 Speaker 1: It's one before the podcast. You can always catch us 561 00:34:12,760 --> 00:34:14,360 Speaker 1: worldwide on Blueberg Radio.