1
00:00:02,520 --> 00:00:13,760
Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg

2
00:00:13,840 --> 00:00:17,920
Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern

3
00:00:18,200 --> 00:00:21,240
Speaker 1: on Apple car Play or Android Auto with the Bloomberg

4
00:00:21,320 --> 00:00:24,840
Speaker 1: Business app. Listen on demand wherever you get your podcasts,

5
00:00:25,280 --> 00:00:27,120
Speaker 1: or watch us live on YouTube.

6
00:00:27,320 --> 00:00:30,000
Speaker 2: Joining us now, wasting too much time, I'm sorry, folks.

7
00:00:30,480 --> 00:00:35,560
Speaker 2: Richard Clarida of Columbia University, of PIMCO and of course

8
00:00:35,600 --> 00:00:38,919
Speaker 2: the former vice chairman of the FED, Professor CLARDA. Were

9
00:00:39,000 --> 00:00:41,120
Speaker 2: thrilled to have you in today. Can I go nerd

10
00:00:41,159 --> 00:00:43,479
Speaker 2: for a moment? Sure? Okay. I never talk about the

11
00:00:43,520 --> 00:00:46,639
Speaker 2: Nobel Prize in economics. It's like bad luck, and I'm

12
00:00:46,640 --> 00:00:49,800
Speaker 2: not doing that with somebody qualified to get the call

13
00:00:49,880 --> 00:00:52,600
Speaker 2: from Scandinavia. But I want to go back. This is

14
00:00:52,640 --> 00:00:56,440
Speaker 2: really important, Richard Clarida. There can be like in nineteen eighty,

15
00:00:56,480 --> 00:00:59,520
Speaker 2: I've had the honor of talking to Joe Stiglitz about

16
00:00:59,560 --> 00:01:03,880
Speaker 2: Gross and Stiglitz, which in nineteen eighty I'm not kidding, folks,

17
00:01:04,160 --> 00:01:08,280
Speaker 2: it was like a four page paper. It was small,

18
00:01:08,680 --> 00:01:11,800
Speaker 2: it was focused. And then with you and you know,

19
00:01:12,000 --> 00:01:13,640
Speaker 2: I don't want to get into you know this or

20
00:01:13,680 --> 00:01:20,400
Speaker 2: that there's Clarita Girtler and A Gali okay, up at

21
00:01:20,400 --> 00:01:24,040
Speaker 2: Brown University. When you make a paper like that that

22
00:01:24,240 --> 00:01:28,000
Speaker 2: is treasured by this is on DSGE folks, it's treasured

23
00:01:28,040 --> 00:01:32,120
Speaker 2: by all of economics, how do you get that paper done?

24
00:01:32,680 --> 00:01:35,120
Speaker 2: That ends up being like, hey, should they win a

25
00:01:35,160 --> 00:01:38,880
Speaker 2: Nobel Prize? What was the process of doing? You know,

26
00:01:39,080 --> 00:01:42,760
Speaker 2: name the paper, but I'll go to Girtler The Science

27
00:01:42,800 --> 00:01:45,240
Speaker 2: of Monetary Policies just one example.

28
00:01:46,360 --> 00:01:50,040
Speaker 3: Well, it was an interesting time because the authors Mark Gertler,

29
00:01:50,120 --> 00:01:54,040
Speaker 3: Jerdi Galli and I were sort of either early or late.

30
00:01:54,160 --> 00:01:57,360
Speaker 3: But we felt there was a vacuum in academic economics

31
00:01:57,560 --> 00:02:00,360
Speaker 3: in that it treated monetary policy as a black box,

32
00:02:00,440 --> 00:02:03,280
Speaker 3: and we thought these guys are trying to do something sensible.

33
00:02:03,320 --> 00:02:07,000
Speaker 3: So we actually worked out essentially a forward looking tailor

34
00:02:07,080 --> 00:02:09,880
Speaker 3: rule to describe actual monetary policy. And it turned out

35
00:02:09,919 --> 00:02:11,560
Speaker 3: that it actually did a good job and it made

36
00:02:11,560 --> 00:02:14,160
Speaker 3: a lot more sense than the black box. But when

37
00:02:14,200 --> 00:02:16,239
Speaker 3: we wrote that paper, I don't think we had any

38
00:02:16,240 --> 00:02:18,080
Speaker 3: idea that it would have the impact.

39
00:02:17,760 --> 00:02:20,000
Speaker 2: That it did. We thought it could get ignored, okay,

40
00:02:20,120 --> 00:02:24,040
Speaker 2: away from you. In modern economics, there's a nineteenth century

41
00:02:24,040 --> 00:02:27,240
Speaker 2: what's called plug and chug which you have an equation, folks,

42
00:02:27,520 --> 00:02:30,120
Speaker 2: and you fill in the little blanks of the algebraic

43
00:02:30,200 --> 00:02:33,880
Speaker 2: equation the tailor rule. You can't do that because you

44
00:02:33,919 --> 00:02:36,240
Speaker 2: don't know where the output gap is right right out? Yeah,

45
00:02:36,400 --> 00:02:38,680
Speaker 2: is Jerome Powell flying blind?

46
00:02:40,040 --> 00:02:45,240
Speaker 3: Well, he's certainly flying with an obscured vision out the cockpit,

47
00:02:45,840 --> 00:02:48,480
Speaker 3: for sure. And I think there's always some uncertainty about

48
00:02:48,560 --> 00:02:51,320
Speaker 3: things like what is our star? What's the full natural

49
00:02:51,360 --> 00:02:55,239
Speaker 3: rate of unemployment? But it's probably elevated now. And the stakes,

50
00:02:55,320 --> 00:02:57,440
Speaker 3: let's be honest, I guess, let me cut to the punchline.

51
00:02:57,680 --> 00:03:00,640
Speaker 3: The stakes are higher now because of the fact that

52
00:03:00,680 --> 00:03:03,400
Speaker 3: for the last four years inflation has been above target,

53
00:03:03,400 --> 00:03:05,520
Speaker 3: and of course in twenty twenty one and twenty twenty

54
00:03:05,520 --> 00:03:08,280
Speaker 3: two it served and was not transitory. And so I

55
00:03:08,320 --> 00:03:10,440
Speaker 3: would argue that the stakes are higher now for the

56
00:03:10,480 --> 00:03:11,359
Speaker 3: FED than they have been.

57
00:03:11,360 --> 00:03:14,239
Speaker 2: Really, going back to Paul Volker forty years.

58
00:03:14,040 --> 00:03:18,000
Speaker 4: Ago, does the government shutdown impact the Fed's ability to

59
00:03:18,080 --> 00:03:22,480
Speaker 4: manage its mandate here in terms of managing interest rates?

60
00:03:23,160 --> 00:03:26,560
Speaker 3: The longer it goes on, the more that becomes a factor.

61
00:03:27,440 --> 00:03:30,320
Speaker 3: In particular, because a lot of the data comes from

62
00:03:30,400 --> 00:03:33,480
Speaker 3: the government, including you know, inflation data and the labor

63
00:03:33,520 --> 00:03:37,840
Speaker 3: market data. Now, the FED, like many other organizations and

64
00:03:38,320 --> 00:03:40,960
Speaker 3: in the private sector, looks at a wide range of

65
00:03:41,040 --> 00:03:44,280
Speaker 3: high frequency data. You get ADP, you get a lot

66
00:03:44,320 --> 00:03:47,640
Speaker 3: of different indicators of the labor market. But yes, the

67
00:03:47,720 --> 00:03:51,280
Speaker 3: longer this goes on, the more challenging it is to

68
00:03:51,360 --> 00:03:53,320
Speaker 3: determine exactly where the economy is.

69
00:03:53,840 --> 00:03:56,840
Speaker 4: What do you think is the bigger risk for this economy?

70
00:03:56,880 --> 00:03:59,040
Speaker 4: Is it from the Fed's perspective, is it the labor market?

71
00:03:59,080 --> 00:04:01,320
Speaker 4: Is this inflation? Are they evenly balanced here? What do

72
00:04:01,320 --> 00:04:02,680
Speaker 4: you think the bigger risk?

73
00:04:02,720 --> 00:04:05,120
Speaker 3: Well that was what was important about the September meeting

74
00:04:05,120 --> 00:04:08,720
Speaker 3: because up until September, Jay Powell and many on the

75
00:04:08,760 --> 00:04:12,680
Speaker 3: committee had said, look, we have dual mandate employment and inflation,

76
00:04:12,840 --> 00:04:15,640
Speaker 3: and they seem to be roughly in balance. And at

77
00:04:15,640 --> 00:04:18,240
Speaker 3: the September meeting they said, we're now more concerned about

78
00:04:18,279 --> 00:04:21,800
Speaker 3: the balance of risk in the labor market. And I

79
00:04:21,880 --> 00:04:25,279
Speaker 3: respect that, But the reality is inflation now using the

80
00:04:25,320 --> 00:04:28,280
Speaker 3: FEDS preferred measures two point nine percent, that's where it

81
00:04:28,360 --> 00:04:32,280
Speaker 3: was eighteen months ago. It's well above two and so

82
00:04:32,440 --> 00:04:34,800
Speaker 3: there is a risk to both sides. There's a risk

83
00:04:34,839 --> 00:04:37,400
Speaker 3: if you don't cut rates the unemployment rate goes up

84
00:04:37,400 --> 00:04:38,919
Speaker 3: a lot. There is a risk that if you do

85
00:04:39,040 --> 00:04:42,040
Speaker 3: cut rates a year from now, inflation stuck in the threes.

86
00:04:42,600 --> 00:04:44,719
Speaker 2: Richard Claiter, with this talk, is a former vice chairman

87
00:04:44,760 --> 00:04:47,880
Speaker 2: of the FED. For an extensive conversation. When we invented this, Paul,

88
00:04:47,960 --> 00:04:50,560
Speaker 2: I mean to go from Man Deep Singh with his

89
00:04:50,680 --> 00:04:53,279
Speaker 2: brilliance on AI to Professor Claiter, I mean, this is

90
00:04:53,279 --> 00:04:54,720
Speaker 2: the way you roll, That's how you do it. This

91
00:04:54,760 --> 00:04:56,159
Speaker 2: is how you do it. We said good morning to

92
00:04:56,200 --> 00:05:00,200
Speaker 2: all of you across America worldwide as well. Okay, I'm

93
00:05:00,200 --> 00:05:02,880
Speaker 2: in the basement of the of our building in London

94
00:05:03,160 --> 00:05:06,520
Speaker 2: with a guy named Jean Claude Trichet, the engineer from Leon.

95
00:05:07,160 --> 00:05:10,680
Speaker 2: He's brilliant. He goes Tom, I think you call me Tom.

96
00:05:10,760 --> 00:05:14,560
Speaker 2: I can't remember, and he says it is about diffusion,

97
00:05:14,760 --> 00:05:18,720
Speaker 2: and we're talking about productivity. I hate the phrase K

98
00:05:18,960 --> 00:05:24,520
Speaker 2: shaped economy because it implies a symmetric distribution baloney. The

99
00:05:24,560 --> 00:05:28,119
Speaker 2: productivity that we're all witnessing right now. Maybe Jeff Sachs

100
00:05:28,160 --> 00:05:31,480
Speaker 2: would be good at this. Yeah, the productivity that we're witnessing.

101
00:05:31,800 --> 00:05:35,039
Speaker 2: You can't tell me it's evenly diffused. Across some mirror.

102
00:05:36,000 --> 00:05:40,920
Speaker 2: How asymmetric are we in this productivity? Boom?

103
00:05:41,520 --> 00:05:44,599
Speaker 3: Well, I think you're one hundred percent right. You know

104
00:05:44,680 --> 00:05:47,800
Speaker 3: the term in economics, you know, is is it labor

105
00:05:47,839 --> 00:05:49,280
Speaker 3: augmenting technical change?

106
00:05:49,320 --> 00:05:50,640
Speaker 2: And I think the answer is yes.

107
00:05:50,720 --> 00:05:53,960
Speaker 3: But more labor is augmented, another lager over time may

108
00:05:53,960 --> 00:05:56,920
Speaker 3: be substituted for. And I think that is really the

109
00:05:56,920 --> 00:05:59,720
Speaker 3: potential disruption from AI is not only does it lift

110
00:05:59,720 --> 00:06:02,039
Speaker 3: out at per hour, but it also could result in

111
00:06:02,279 --> 00:06:05,400
Speaker 3: at some point in some displacement as well. So I

112
00:06:05,400 --> 00:06:07,480
Speaker 3: think it's too soon to tell, but the minimum we

113
00:06:07,520 --> 00:06:09,120
Speaker 3: know it's not evenly distributed.

114
00:06:09,200 --> 00:06:12,200
Speaker 2: Dominic Constume over at Missou and now Brilliant out of Oxford,

115
00:06:12,279 --> 00:06:16,479
Speaker 2: Doctor Constum would say, there's a capital deepening issue here.

116
00:06:16,600 --> 00:06:20,880
Speaker 2: Explain to our audience this wall of AI money and

117
00:06:20,920 --> 00:06:24,200
Speaker 2: what that does to the capital dynamics of America.

118
00:06:24,440 --> 00:06:27,320
Speaker 3: Well, the interesting point is, you remember a couple decades ago,

119
00:06:27,800 --> 00:06:30,320
Speaker 3: the talk in the US was about the witless economy,

120
00:06:30,360 --> 00:06:33,320
Speaker 3: that we could get all this GDP without bricks and mortar.

121
00:06:33,680 --> 00:06:35,560
Speaker 3: And it turns out that at least for this part

122
00:06:35,560 --> 00:06:37,560
Speaker 3: of the new economy, you need a lot of bricks,

123
00:06:37,600 --> 00:06:39,400
Speaker 3: a lot of mortar, a lot of servers, and a

124
00:06:39,400 --> 00:06:42,520
Speaker 3: lot of power generation. So in some ways to get

125
00:06:42,560 --> 00:06:46,839
Speaker 3: to the very new economy, you need old economy capital spending.

126
00:06:46,920 --> 00:06:49,560
Speaker 3: And that's a pretty interesting period to be in. We

127
00:06:49,560 --> 00:06:51,880
Speaker 3: think it's going to go on for five to ten years,

128
00:06:51,880 --> 00:06:54,520
Speaker 3: but it's a different economy than we were used to

129
00:06:54,520 --> 00:06:56,400
Speaker 3: thinking about in the last twenty years.

130
00:06:56,880 --> 00:06:59,120
Speaker 4: You strip out the AI spend, a lot of folks

131
00:06:59,120 --> 00:07:01,640
Speaker 4: will tell you this economy not that strong. Capital spending

132
00:07:01,720 --> 00:07:03,200
Speaker 4: is not that good.

133
00:07:03,240 --> 00:07:06,320
Speaker 2: How do you think about that arithmetically? That's correct.

134
00:07:06,360 --> 00:07:08,160
Speaker 3: You know, in the first half of the year GDP

135
00:07:08,320 --> 00:07:11,920
Speaker 3: growth was about one point six one point seven. If

136
00:07:12,000 --> 00:07:15,320
Speaker 3: you strip out tech investment then it was somewhere between

137
00:07:15,440 --> 00:07:17,679
Speaker 3: zero and half of that, and you have to adjust

138
00:07:17,720 --> 00:07:20,520
Speaker 3: for imports. But clearly in the first half of the

139
00:07:20,560 --> 00:07:25,720
Speaker 3: year it's really been an AI driven capex economy.

140
00:07:25,840 --> 00:07:28,880
Speaker 4: So one of the issues out there that I guess

141
00:07:28,880 --> 00:07:31,120
Speaker 4: it's got to push the background a little bit, maybe

142
00:07:31,200 --> 00:07:34,960
Speaker 4: just because fatigue is tariffs and the impact on the economy.

143
00:07:35,320 --> 00:07:40,520
Speaker 4: We have not necessarily seen meaningful inflation resulting from the tariffs.

144
00:07:42,160 --> 00:07:44,760
Speaker 4: Growth seems to be kind of hanging in everything. Strong

145
00:07:44,800 --> 00:07:47,560
Speaker 4: gd for in a few weeks ago. How do you

146
00:07:47,560 --> 00:07:50,040
Speaker 4: think tariffs will impact the economy if at all.

147
00:07:51,160 --> 00:07:58,120
Speaker 3: The economy has been refreshingly and surprisingly resilient. I don't

148
00:07:58,120 --> 00:08:01,040
Speaker 3: think there's any doubt about that. So at PIMCO, we've

149
00:08:01,200 --> 00:08:04,480
Speaker 3: revised up our outlook. You know, Atlanta Fed is now

150
00:08:04,520 --> 00:08:08,480
Speaker 3: saying Q three could come in north of three percent.

151
00:08:09,320 --> 00:08:11,600
Speaker 2: So I actually think it actually in part.

152
00:08:11,400 --> 00:08:13,600
Speaker 3: Is because of at the same time we've had the

153
00:08:13,640 --> 00:08:17,960
Speaker 3: tariff hit to the economy, we've also had a justifiable

154
00:08:18,000 --> 00:08:22,680
Speaker 3: optimism about tech and capital spending, so that that's been

155
00:08:22,720 --> 00:08:26,680
Speaker 3: an important feature. I think the other important feature is that,

156
00:08:27,360 --> 00:08:29,760
Speaker 3: you know, some of the tariffs have been absorbed either

157
00:08:29,800 --> 00:08:32,000
Speaker 3: by the profits of US companies that had a lot

158
00:08:32,000 --> 00:08:35,240
Speaker 3: of profits to absorb or foreign exporters. And then the

159
00:08:35,280 --> 00:08:38,920
Speaker 3: third piece is we're probably not yet at the at

160
00:08:38,960 --> 00:08:41,600
Speaker 3: the endpoint of teriffs. They will continue to show up

161
00:08:41,600 --> 00:08:44,760
Speaker 3: in the inflation data at least for a while, but

162
00:08:44,800 --> 00:08:46,920
Speaker 3: I think increasingly I and the Federal of the view,

163
00:08:46,920 --> 00:08:49,760
Speaker 3: and that the FEDS what's important that this is really

164
00:08:49,800 --> 00:08:52,400
Speaker 3: not going to be an inflationary story. It's a price

165
00:08:52,520 --> 00:08:55,200
Speaker 3: level adjustment that we're sort of in the middle innings

166
00:08:55,240 --> 00:08:56,160
Speaker 3: of getting through.

167
00:08:56,160 --> 00:08:59,240
Speaker 2: Against some nerd knowledge here, folks, Good morning Global Wall Street.

168
00:08:59,600 --> 00:09:02,440
Speaker 2: Richard Clara with this with PIMCO, and of course forever

169
00:09:02,520 --> 00:09:07,480
Speaker 2: with his Columbia University. Okay, my path in foreign exchange

170
00:09:07,520 --> 00:09:11,880
Speaker 2: is Mundel, Mundel, Fleming, Jacob Frankel. Out of Chicago, a

171
00:09:11,880 --> 00:09:15,000
Speaker 2: guy named Rogoff shows up, No excuse me than Rudy

172
00:09:15,040 --> 00:09:19,680
Speaker 2: Dornbush up at Amputeen this upstart Rogoff and so getting

173
00:09:19,760 --> 00:09:22,440
Speaker 2: ops felt out at Berkeley. They show up and it

174
00:09:22,480 --> 00:09:24,880
Speaker 2: goes on and on and on. Let's take it back

175
00:09:24,880 --> 00:09:28,880
Speaker 2: to Colombia, where you have this incredible that you helped build,

176
00:09:29,440 --> 00:09:35,319
Speaker 2: this incredible synthesis of international economics. Explain to America with

177
00:09:35,559 --> 00:09:39,640
Speaker 2: Xavier Salah, m Lartin or Robert Mundel the Giant would

178
00:09:39,679 --> 00:09:44,160
Speaker 2: say about how screwed up, messed up Japan is. With

179
00:09:44,400 --> 00:09:50,800
Speaker 2: weekend log convex interest rates moving higher, the real rage

180
00:09:50,920 --> 00:09:54,440
Speaker 2: chart published out of Tokyo today by Bloomberg is grim.

181
00:09:54,920 --> 00:09:58,800
Speaker 2: Explain why our listeners and viewers should care about the

182
00:09:58,800 --> 00:09:59,920
Speaker 2: fragility of Japan.

183
00:10:01,240 --> 00:10:04,800
Speaker 3: Well, because Japan is obviously a major economy, but it's

184
00:10:04,840 --> 00:10:08,880
Speaker 3: also an even bigger part of you know, international financial system.

185
00:10:09,000 --> 00:10:12,360
Speaker 3: With the yen an important currency, especially in risk off episodes.

186
00:10:12,960 --> 00:10:16,000
Speaker 2: Somebody has to hold all the jgbs.

187
00:10:15,320 --> 00:10:18,320
Speaker 3: That the government has been issuing, and so what happens

188
00:10:18,320 --> 00:10:22,960
Speaker 3: in Japan also spills over into US capital markets and

189
00:10:23,000 --> 00:10:26,800
Speaker 3: the global economy. And I think what's important for the

190
00:10:26,920 --> 00:10:30,160
Speaker 3: listeners to understand now is that markets and investors have

191
00:10:30,240 --> 00:10:32,640
Speaker 3: had sort of a rule of thumb about Japan, which

192
00:10:32,679 --> 00:10:34,559
Speaker 3: is it sort of goes off in its own it's

193
00:10:34,600 --> 00:10:38,240
Speaker 3: got deflation. Eventually they'll figure out their fiscal situation. And

194
00:10:38,280 --> 00:10:41,320
Speaker 3: now Japan has broken out of deflation. They now have inflation,

195
00:10:41,679 --> 00:10:44,480
Speaker 3: they have positive interest rates, and they're now very much

196
00:10:44,480 --> 00:10:46,920
Speaker 3: a player in the global financial system.

197
00:10:47,200 --> 00:10:48,439
Speaker 5: Is there is there.

198
00:10:48,360 --> 00:10:53,520
Speaker 2: Any precedent for a successful reflation. I don't see it

199
00:10:53,559 --> 00:10:56,760
Speaker 2: in the literature. It's original to Japan, isn't it.

200
00:10:58,080 --> 00:11:01,439
Speaker 3: Well, Japan was went through about a two decade period

201
00:11:01,440 --> 00:11:04,360
Speaker 3: where they had deflation. It wasn't a spiral, but prices

202
00:11:04,360 --> 00:11:06,280
Speaker 3: were negative. I think to me, Tom, one of the

203
00:11:06,320 --> 00:11:10,280
Speaker 3: interesting things about Japan is although the boj was trying

204
00:11:10,280 --> 00:11:13,839
Speaker 3: to reflate the economy, the politicians in the public actually

205
00:11:13,880 --> 00:11:16,720
Speaker 3: didn't get a vote. They actually liked deflation. You know,

206
00:11:16,760 --> 00:11:19,400
Speaker 3: if you've got you've got your savings in yen under

207
00:11:19,400 --> 00:11:21,840
Speaker 3: the mattress. You know, deflation is good for you. So

208
00:11:21,840 --> 00:11:24,640
Speaker 3: I think a challenge right now in Japan is they finally,

209
00:11:24,679 --> 00:11:27,640
Speaker 3: after twenty five years, achieved the positive two or three

210
00:11:27,679 --> 00:11:31,640
Speaker 3: percent inflation. But it's creating substantial political tension as well.

211
00:11:31,679 --> 00:11:34,400
Speaker 2: Well, I can't emphasize that that was brilliant. We'll try

212
00:11:34,440 --> 00:11:36,440
Speaker 2: to do that single best idea. We'll see if the

213
00:11:36,480 --> 00:11:41,520
Speaker 2: interns get the cut today. Well, the societal change. I

214
00:11:41,640 --> 00:11:44,199
Speaker 2: was at the White House correspondence dinner and you got

215
00:11:44,200 --> 00:11:47,960
Speaker 2: this whole security idiocy because the President's there and Martin

216
00:11:48,000 --> 00:11:50,480
Speaker 2: Feldstein's standing in front of me. I think rogue off

217
00:11:50,600 --> 00:11:53,320
Speaker 2: was my guest. Martin Feldstein's standing in front of me.

218
00:11:53,679 --> 00:11:56,720
Speaker 2: We'd all had six martinis. And he turns around and

219
00:11:56,760 --> 00:12:01,120
Speaker 2: he says, Tom, Japan has been lost for two decades. Yep,

220
00:12:01,240 --> 00:12:03,000
Speaker 2: that was a societal struggle.

221
00:12:03,320 --> 00:12:04,600
Speaker 5: Is Japan now found?

222
00:12:05,040 --> 00:12:07,360
Speaker 4: Is it out of the wilderness at this point?

223
00:12:07,400 --> 00:12:07,840
Speaker 6: Do you think?

224
00:12:08,120 --> 00:12:10,720
Speaker 3: Well, as I mentioned, you know, narrowly, it certainly is

225
00:12:10,800 --> 00:12:12,400
Speaker 3: no longer in deflation.

226
00:12:12,600 --> 00:12:14,960
Speaker 2: It has positive interests.

227
00:12:15,080 --> 00:12:17,920
Speaker 3: I will say, just an anecdote, if I'm allowed an anecdote,

228
00:12:17,920 --> 00:12:21,160
Speaker 3: I visit Japan almost every year for the last thirty years.

229
00:12:21,480 --> 00:12:22,840
Speaker 2: And most recently this summer.

230
00:12:22,880 --> 00:12:26,440
Speaker 3: I was struck by not only the boom in the economy,

231
00:12:26,720 --> 00:12:29,000
Speaker 3: but it is a real tourist magnet now. In fact,

232
00:12:29,040 --> 00:12:31,679
Speaker 3: if anything, in Japan, the politics is such that there

233
00:12:31,679 --> 00:12:33,800
Speaker 3: are too many tour right, which is a problem they

234
00:12:33,800 --> 00:12:35,400
Speaker 3: did not have for twenty five years.

235
00:12:35,440 --> 00:12:37,000
Speaker 2: Professor, I got to ask you, or I should say

236
00:12:37,080 --> 00:12:39,880
Speaker 2: Vice Chairman, I've got to ask you. Lisa Cook gets

237
00:12:39,880 --> 00:12:43,000
Speaker 2: an extended stay at the Fed. What is the significance

238
00:12:43,240 --> 00:12:46,560
Speaker 2: of Lisa Cook remaining at the Federal Reserved table.

239
00:12:47,120 --> 00:12:49,600
Speaker 3: Well, obviously the case is at the Supreme Court, and

240
00:12:49,640 --> 00:12:52,800
Speaker 3: so we'll know next year where they end up. But

241
00:12:52,880 --> 00:12:55,719
Speaker 3: what's important is, you know, she continues to serve as

242
00:12:55,720 --> 00:12:59,760
Speaker 3: a governor and continues to vote on monetary policy.

243
00:13:00,480 --> 00:13:03,479
Speaker 2: And I think that that is right. I think that's appropriate.

244
00:13:03,840 --> 00:13:07,559
Speaker 2: Did Columbia pay for Sala E. Martin's bright colored jackets?

245
00:13:08,280 --> 00:13:09,360
Speaker 2: Is that part of his deal?

246
00:13:09,720 --> 00:13:12,400
Speaker 3: During my time as chair, we did not subsidize the

247
00:13:12,920 --> 00:13:16,280
Speaker 3: jackets or the m and ms that he distributes to class.

248
00:13:17,080 --> 00:13:19,600
Speaker 2: But I'm not sure about the current practice. This is

249
00:13:19,720 --> 00:13:23,280
Speaker 2: your dovo. Sally Martin's like three quarters of a mile away,

250
00:13:23,559 --> 00:13:25,800
Speaker 2: and he's there in bright orange, just like there's the

251
00:13:25,840 --> 00:13:29,480
Speaker 2: growth guy from Columbia, Richie Claire brilliant. Thank you so much, really,

252
00:13:29,520 --> 00:13:32,240
Speaker 2: treasure of the comments there. Maybe we'll get him back

253
00:13:32,280 --> 00:13:37,280
Speaker 2: once we figure out who Scandinavia annoints this week as well.

254
00:13:37,480 --> 00:13:41,400
Speaker 2: Clarida is with Pimco. Stay with us. More from Bloomberg

255
00:13:41,559 --> 00:13:43,600
Speaker 2: Surveillance coming up after this.

256
00:13:50,840 --> 00:13:54,439
Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live

257
00:13:54,480 --> 00:13:58,000
Speaker 1: weekday afternoons from seven to ten am Eastern Listen on Apple,

258
00:13:58,040 --> 00:14:01,400
Speaker 1: Karplay and Android Otto with the Work Business up or

259
00:14:01,520 --> 00:14:03,000
Speaker 1: what Us Live on YouTube.

260
00:14:03,120 --> 00:14:06,119
Speaker 2: Joining us now. Finally, Jane Foley out of FX strategy

261
00:14:06,600 --> 00:14:09,360
Speaker 2: at Robbo Bank in London. I can't say enough, folks

262
00:14:09,360 --> 00:14:13,280
Speaker 2: about the difference here in the Rabobank of the Netherlands.

263
00:14:13,320 --> 00:14:19,840
Speaker 2: They go back to commercial hedging utilizing foreign exchange back centuries.

264
00:14:20,320 --> 00:14:24,240
Speaker 2: It's a whole different twist here on the dynamics. Jane Fowley,

265
00:14:24,360 --> 00:14:28,359
Speaker 2: I want you to explain the sowhat to our American

266
00:14:28,440 --> 00:14:31,320
Speaker 2: listeners and viewers and those in London frankly as well

267
00:14:31,960 --> 00:14:36,640
Speaker 2: of a week Japanese yen our two point nine standard deviations,

268
00:14:36,960 --> 00:14:40,400
Speaker 2: What why do I care that dollar yen could go

269
00:14:40,440 --> 00:14:43,440
Speaker 2: to one fifty five shockingly week Japan?

270
00:14:45,160 --> 00:14:47,360
Speaker 7: Well, I mean, gently excuse me. That's the talk this

271
00:14:47,400 --> 00:14:49,160
Speaker 7: morning that we could see a move back to one

272
00:14:49,320 --> 00:14:52,880
Speaker 7: fifty five. And it is all because the market thinks, well,

273
00:14:52,960 --> 00:14:55,200
Speaker 7: you know, the end characterve is back on. You know,

274
00:14:55,240 --> 00:14:57,200
Speaker 7: we're going to not get the Bank of the Bank

275
00:14:57,280 --> 00:15:00,800
Speaker 7: of Japan interest rate hiking October after But I would

276
00:15:00,920 --> 00:15:04,480
Speaker 7: warn but I think this is a really dangerous strategy

277
00:15:04,480 --> 00:15:08,040
Speaker 7: in it. Why is it dangerous because if you think

278
00:15:08,080 --> 00:15:11,600
Speaker 7: about the position of the LDP leader now, and she

279
00:15:11,760 --> 00:15:14,280
Speaker 7: is of course quite likely to be voted in as

280
00:15:14,400 --> 00:15:17,440
Speaker 7: the Prime minister maybe next week, although there's some issues

281
00:15:17,480 --> 00:15:20,840
Speaker 7: there with her coalition, But assuming she is the prime minister,

282
00:15:20,880 --> 00:15:24,640
Speaker 7: you've got to wonder does she actually want a weaker yen?

283
00:15:24,920 --> 00:15:27,560
Speaker 7: Now the market is assuming that she is going to

284
00:15:27,560 --> 00:15:31,640
Speaker 7: follow the policies of her mental Aarby. But of course

285
00:15:31,680 --> 00:15:35,000
Speaker 7: when Abe was the prime minister, things were very different

286
00:15:35,000 --> 00:15:38,440
Speaker 7: in Japan. They were still trying to fight deflation. Now

287
00:15:38,640 --> 00:15:42,760
Speaker 7: Japan has got inflation, and she is very concerned that

288
00:15:42,840 --> 00:15:47,160
Speaker 7: a lot of this inflation is because of important inflation.

289
00:15:47,400 --> 00:15:50,080
Speaker 7: And of course, if you are worried about important inflation.

290
00:15:50,800 --> 00:15:54,720
Speaker 7: Why would you want a weaker currency, particularly when you

291
00:15:54,760 --> 00:15:57,400
Speaker 7: want to build a strong relationship with President Trump, who,

292
00:15:57,440 --> 00:16:01,400
Speaker 7: according to the Japanese prayers, may start Japan in his

293
00:16:01,600 --> 00:16:04,080
Speaker 7: visits to Asia and perhaps at the end of this time.

294
00:16:04,120 --> 00:16:07,400
Speaker 7: So I think this could be quite a dangerous strategy.

295
00:16:07,440 --> 00:16:09,600
Speaker 7: I'm not quite so certain that beat the carriage trade

296
00:16:09,600 --> 00:16:10,400
Speaker 7: will be on so long.

297
00:16:10,560 --> 00:16:13,760
Speaker 2: In Paul Toro Fujioko off for Tokyo Desk has a

298
00:16:13,760 --> 00:16:17,960
Speaker 2: brilliant story today showing the in the new inflation, the

299
00:16:18,000 --> 00:16:22,960
Speaker 2: inflation justed wages. The japan people are flat on If

300
00:16:23,000 --> 00:16:27,160
Speaker 2: that happened in America, they'll literally be revolt. They're flat

301
00:16:27,240 --> 00:16:30,120
Speaker 2: on their back with a negative real wage growth.

302
00:16:30,240 --> 00:16:33,320
Speaker 4: Absolutely, Jane, we've got I think the story maybe this

303
00:16:33,360 --> 00:16:36,320
Speaker 4: week over it. Certainly this year has been gold. We've

304
00:16:36,320 --> 00:16:39,240
Speaker 4: got gold north of four thousand dollars per ounce. A

305
00:16:39,240 --> 00:16:42,120
Speaker 4: lot of folks are saying, hey, this is a safe haven,

306
00:16:42,360 --> 00:16:44,720
Speaker 4: maybe more so than the US dollar. What are folks

307
00:16:44,760 --> 00:16:47,440
Speaker 4: in your world thinking about the relationship between the US

308
00:16:47,480 --> 00:16:48,120
Speaker 4: dollar and gold.

309
00:16:49,320 --> 00:16:51,320
Speaker 7: Well, certainly that seems to be you know, the fashion

310
00:16:51,360 --> 00:16:53,720
Speaker 7: trade right now. But I do think that there is

311
00:16:53,880 --> 00:16:56,240
Speaker 7: room for both and I do think that if we

312
00:16:56,280 --> 00:17:00,320
Speaker 7: did have, say a sudden step up of geopolitician, I

313
00:17:00,320 --> 00:17:02,960
Speaker 7: think we'd see the dollar and we'd see gold gold rallying,

314
00:17:02,960 --> 00:17:05,200
Speaker 7: although over time the dollar, you know, if the dollar

315
00:17:05,240 --> 00:17:07,560
Speaker 7: were to recover significantly, of course, I think there would

316
00:17:07,560 --> 00:17:08,680
Speaker 7: be forfit taking first of.

317
00:17:08,600 --> 00:17:09,760
Speaker 2: All in gold.

318
00:17:10,119 --> 00:17:14,160
Speaker 7: Now, gold I think is a real true diversification trade

319
00:17:14,200 --> 00:17:16,320
Speaker 7: this year, and I think this is where a lot

320
00:17:16,320 --> 00:17:18,280
Speaker 7: of the buying has come from. You know, if we

321
00:17:18,400 --> 00:17:20,280
Speaker 7: go back to the first five months of this year,

322
00:17:20,320 --> 00:17:23,240
Speaker 7: that there was this rotation trade away from the US

323
00:17:23,240 --> 00:17:26,160
Speaker 7: assets and maybe that's stop now bores turned around because

324
00:17:26,160 --> 00:17:28,240
Speaker 7: we do see you know, the AI trade, the S

325
00:17:28,280 --> 00:17:32,200
Speaker 7: and P making you such strong gains really since since June.

326
00:17:32,240 --> 00:17:36,040
Speaker 7: But I think there is diversification still amongst that. We've

327
00:17:36,040 --> 00:17:39,240
Speaker 7: seen various different stock markets, including the perform quite well

328
00:17:39,800 --> 00:17:42,200
Speaker 7: this year, and we've seen silver do well, We've seen

329
00:17:42,240 --> 00:17:44,920
Speaker 7: bitcoin do well, and I think there is a want

330
00:17:44,920 --> 00:17:48,960
Speaker 7: by many investors really to diversify their portfolios, and I

331
00:17:48,960 --> 00:17:51,200
Speaker 7: think that's where the strength in gold is coming from.

332
00:17:51,760 --> 00:17:54,520
Speaker 4: Jane, We've we've seen the Bloomberg dollar index, you know,

333
00:17:54,600 --> 00:17:57,200
Speaker 4: kind of stabilize here over the last month, or two

334
00:17:57,280 --> 00:18:00,199
Speaker 4: here the dollars stabilized. Is this kind of a a

335
00:18:00,240 --> 00:18:03,439
Speaker 4: new level you think for the dollar?

336
00:18:03,640 --> 00:18:05,800
Speaker 7: Yeah, you know, the dollar is the best performing G

337
00:18:05,920 --> 00:18:08,520
Speaker 7: ten currency on the one month view, despite the fact

338
00:18:08,520 --> 00:18:10,880
Speaker 7: that it's still the worst performing on the year to date.

339
00:18:11,440 --> 00:18:14,240
Speaker 7: And we have seen a lot of stability really over

340
00:18:14,280 --> 00:18:17,359
Speaker 7: the summer months. Really sort of July is and you know,

341
00:18:17,400 --> 00:18:19,399
Speaker 7: a lot has been said over the spring about the

342
00:18:19,920 --> 00:18:24,200
Speaker 7: hedging strategies or the change in hedging strategies by non

343
00:18:24,840 --> 00:18:29,320
Speaker 7: US dollar based fund managers, and that probably accelerated the

344
00:18:29,400 --> 00:18:32,440
Speaker 7: downside of the donor certainly through the spring. But if

345
00:18:32,440 --> 00:18:35,080
Speaker 7: we assume that for now, you know, that's done, maybe

346
00:18:35,080 --> 00:18:37,440
Speaker 7: it could start again. But if we assume it's done,

347
00:18:37,600 --> 00:18:39,200
Speaker 7: you know, I think what we've got now is short

348
00:18:39,240 --> 00:18:42,399
Speaker 7: covering in the dollar because there's an awful lot of

349
00:18:42,520 --> 00:18:47,280
Speaker 7: fed easine in the price. The market's still whether or

350
00:18:47,280 --> 00:18:48,640
Speaker 7: not inflation will come through.

351
00:18:48,560 --> 00:18:51,600
Speaker 2: Tours jargon here, let's let's translate this. Jane. You're saying,

352
00:18:51,640 --> 00:18:54,640
Speaker 2: everybody bet the bank, bet the farm that there would

353
00:18:54,640 --> 00:18:57,480
Speaker 2: be strong dollar, and now they're turning that trade around

354
00:18:57,480 --> 00:18:58,400
Speaker 2: and going the other way.

355
00:18:59,560 --> 00:19:01,360
Speaker 7: It seems that's what happened in the spring. So if

356
00:19:01,359 --> 00:19:04,440
Speaker 7: we go back to the global financial crisis, we've seen

357
00:19:04,720 --> 00:19:07,720
Speaker 7: you since then, a massive rally out performance of the

358
00:19:07,800 --> 00:19:10,280
Speaker 7: S and P five foundred and really a massive rally

359
00:19:10,280 --> 00:19:12,320
Speaker 7: in the value of the US dollars. So everyone was

360
00:19:12,359 --> 00:19:17,960
Speaker 7: buying American assets and during that period non dollar based assets,

361
00:19:18,000 --> 00:19:21,760
Speaker 7: so really Asian European fund managers, they were investing in

362
00:19:21,760 --> 00:19:23,399
Speaker 7: a lot more money. There was a lot more money

363
00:19:23,600 --> 00:19:26,240
Speaker 7: to be invested, and a lot of that was finding

364
00:19:26,280 --> 00:19:28,639
Speaker 7: its way into the US. And I think come the

365
00:19:28,680 --> 00:19:32,480
Speaker 7: beginning of this year, the market, okay, the dollar's done

366
00:19:32,560 --> 00:19:35,040
Speaker 7: so well in recent years, we weren't that hedged, and

367
00:19:35,160 --> 00:19:37,200
Speaker 7: at the start of this year they started to hedge

368
00:19:37,240 --> 00:19:37,719
Speaker 7: the dollars.

369
00:19:37,800 --> 00:19:39,679
Speaker 2: Jane, we're running out of time. First of all, we

370
00:19:39,720 --> 00:19:41,080
Speaker 2: got to get you in the studio in New York

371
00:19:41,080 --> 00:19:42,840
Speaker 2: to do like a double barrel, like a whole hair

372
00:19:42,880 --> 00:19:46,080
Speaker 2: four with Jane Folly, a raval bank. Jane. People think

373
00:19:46,119 --> 00:19:48,200
Speaker 2: I got hired at Bloomberg because I'm like bow tie.

374
00:19:48,200 --> 00:19:51,160
Speaker 2: It's not true, folks. I mean meetings with like Matt Winkler,

375
00:19:51,200 --> 00:19:54,520
Speaker 2: Peter Grauer retiring chairman, and they're going dance all our

376
00:19:54,600 --> 00:19:56,960
Speaker 2: rods and cones. Where do you do that, You do

377
00:19:57,040 --> 00:20:00,560
Speaker 2: that in Jane Foley space. Foreign exchange, Jane, I'm seeing

378
00:20:00,680 --> 00:20:06,200
Speaker 2: huge tension. If I look at something obscure like sterling swissy,

379
00:20:07,160 --> 00:20:12,040
Speaker 2: I'm out strong, Swiss franc to new territory, new points

380
00:20:12,440 --> 00:20:16,040
Speaker 2: of tension. If I look at euro yen back up

381
00:20:16,040 --> 00:20:20,400
Speaker 2: to a one seventy seven week en, points of tension

382
00:20:20,800 --> 00:20:25,240
Speaker 2: in your world, What do those tensions mean in foreign exchange,

383
00:20:25,600 --> 00:20:29,080
Speaker 2: for the stock market, for the bond market.

384
00:20:29,240 --> 00:20:31,040
Speaker 7: Well, I mean the Nikai T two five has perform

385
00:20:31,119 --> 00:20:33,920
Speaker 7: really quite well this year. But if you're an overseas

386
00:20:33,960 --> 00:20:36,800
Speaker 7: investor investing in Japanese assets, well, you're not going to

387
00:20:36,840 --> 00:20:39,880
Speaker 7: really like the en going lower. Now.

388
00:20:40,000 --> 00:20:41,040
Speaker 2: The yen again.

389
00:20:40,920 --> 00:20:43,280
Speaker 7: Seems out of place here because what we've seen is

390
00:20:43,520 --> 00:20:46,800
Speaker 7: some Safeyvin Ausset's doing quite well, the dollar stabilizing, the

391
00:20:46,800 --> 00:20:49,480
Speaker 7: Swiss frank doing well, goal doing well, but the yen

392
00:20:49,520 --> 00:20:51,800
Speaker 7: again on the back foot, and that to me is

393
00:20:51,840 --> 00:20:56,480
Speaker 7: another reason why this yen selloff is probably overdone.

394
00:20:56,800 --> 00:20:59,880
Speaker 2: Okay, Jane Foley, thank you, thank you so much. Stay

395
00:21:00,119 --> 00:21:10,960
Speaker 2: with us. More from Bloomberg Surveillance coming up after this.

396
00:21:10,960 --> 00:21:14,880
Speaker 1: This is the Bloomberg Surveillance podcast. Listen live each weekday

397
00:21:14,920 --> 00:21:18,240
Speaker 1: starting at seven am Eastern on Applecarplay and Android Auto

398
00:21:18,359 --> 00:21:21,280
Speaker 1: with the Bloomberg Business app. You can also listen live

399
00:21:21,400 --> 00:21:24,960
Speaker 1: on Amazon Alexa from our flagship New York station, Just

400
00:21:25,000 --> 00:21:27,560
Speaker 1: say Alexa play Bloomberg eleven thirty.

401
00:21:27,800 --> 00:21:33,359
Speaker 2: Here's the way it rolls, folks, Economics, finance, investment, international relations.

402
00:21:33,800 --> 00:21:38,280
Speaker 2: It's no different than sports entertainment. Taylor Swift, did you

403
00:21:38,320 --> 00:21:39,440
Speaker 2: know she has a new album out?

404
00:21:39,480 --> 00:21:39,960
Speaker 6: I heard that.

405
00:21:40,280 --> 00:21:43,280
Speaker 2: I think we're efforting her right now, Miss Swift. If

406
00:21:43,320 --> 00:21:47,160
Speaker 2: you're listening, bring Jack with you as well. Taylor. Anyways,

407
00:21:47,160 --> 00:21:49,720
Speaker 2: people keep score and as a young kid that came

408
00:21:49,760 --> 00:21:52,920
Speaker 2: out of York University of York in England and all

409
00:21:52,960 --> 00:21:56,120
Speaker 2: of a sudden things are working. He's with Capital Economics,

410
00:21:56,400 --> 00:22:00,800
Speaker 2: which is a really wonderful firm writing clear stuff. He's

411
00:22:00,840 --> 00:22:05,399
Speaker 2: global group, such a group Chief Economistic Capital Economics, but

412
00:22:05,600 --> 00:22:09,600
Speaker 2: really made us a splash, like with the ft and

413
00:22:09,640 --> 00:22:14,000
Speaker 2: the thinking within England of what in God's name is

414
00:22:14,080 --> 00:22:17,520
Speaker 2: going on? The summary of it is a wonderful two

415
00:22:17,600 --> 00:22:21,640
Speaker 2: hundred and fifty pages. The Fractured Age Martin Wolf warbles

416
00:22:21,680 --> 00:22:25,280
Speaker 2: gaily on the cover. A guy named Robert Nibleta Chathamhouse

417
00:22:25,280 --> 00:22:27,960
Speaker 2: shows up so does bread sets her Neil shearing with

418
00:22:28,040 --> 00:22:31,800
Speaker 2: us in celebration of the fractured age? Did you time

419
00:22:31,920 --> 00:22:34,439
Speaker 2: the book release for the world falling apart?

420
00:22:36,440 --> 00:22:38,679
Speaker 6: Some things with the book that you need an idea,

421
00:22:39,160 --> 00:22:41,480
Speaker 6: you need the support of your friends and family, and

422
00:22:41,520 --> 00:22:44,399
Speaker 6: you need a bit of luck. I'm luck in space.

423
00:22:45,240 --> 00:22:49,119
Speaker 2: What is the distinction of this fractured age that's not

424
00:22:49,240 --> 00:22:53,119
Speaker 2: in the zeitgeist? Now, all the blood, the eighteen newspapers,

425
00:22:53,520 --> 00:22:57,199
Speaker 2: the media, people like us, what are we missing of

426
00:22:57,240 --> 00:22:57,840
Speaker 2: this fracture?

427
00:22:58,480 --> 00:23:00,720
Speaker 6: So I think that the genesis the book was that

428
00:23:00,800 --> 00:23:04,320
Speaker 6: the rhetoric of deglobalization was everywhere right. Tariff's going up,

429
00:23:04,400 --> 00:23:07,280
Speaker 6: trade barriers going up, this idea that we're returning to

430
00:23:07,280 --> 00:23:10,719
Speaker 6: the nineteen thirties, countries are turning inwards. And when we

431
00:23:10,760 --> 00:23:13,520
Speaker 6: at capst Economics looked at the data, we saw global

432
00:23:13,520 --> 00:23:16,520
Speaker 6: trade volumes going up year on year on year. So

433
00:23:16,640 --> 00:23:19,000
Speaker 6: this idea, the thing that everyone's missing is the idea

434
00:23:19,000 --> 00:23:22,920
Speaker 6: that the world isn't deglobalizing. But clearly something is changing.

435
00:23:23,440 --> 00:23:25,000
Speaker 6: And as I argue in the Burke, and as we've

436
00:23:25,000 --> 00:23:27,119
Speaker 6: written about a cap of Economics, the thing that has

437
00:23:27,160 --> 00:23:30,960
Speaker 6: shifted is the relationship between the world's two major economies,

438
00:23:30,960 --> 00:23:34,760
Speaker 6: the US and China, they've become superpower rivals, and that's

439
00:23:34,920 --> 00:23:37,960
Speaker 6: causing those economies to both put apart or fracture, and

440
00:23:38,000 --> 00:23:40,320
Speaker 6: then other economies to have to pick aside.

441
00:23:40,400 --> 00:23:44,200
Speaker 4: Essentially, So again, we all grew up in a world

442
00:23:44,200 --> 00:23:48,159
Speaker 4: of globalization. That's just that's several generations have grown up

443
00:23:48,160 --> 00:23:51,080
Speaker 4: in that world. Is that still the world we're in

444
00:23:51,080 --> 00:23:54,240
Speaker 4: in terms of globalization, because it again it doesn't feel

445
00:23:54,240 --> 00:23:54,560
Speaker 4: that way.

446
00:23:54,840 --> 00:23:57,280
Speaker 6: Well, globalization has certainly shifted, and if you look at

447
00:23:57,359 --> 00:24:00,159
Speaker 6: trade flows you can see them see the evidence that

448
00:24:00,320 --> 00:24:05,679
Speaker 6: shifting globalization. So up to about four years ago, about

449
00:24:05,720 --> 00:24:09,040
Speaker 6: three quarters of US cell phones came from China. Less

450
00:24:09,040 --> 00:24:10,840
Speaker 6: than one in four cell phones are going to be

451
00:24:10,880 --> 00:24:13,200
Speaker 6: produced in China that are consumed in the US this year,

452
00:24:13,440 --> 00:24:16,320
Speaker 6: with more coming from Vietnam and India. So we're still

453
00:24:16,359 --> 00:24:19,679
Speaker 6: consuming vast amounts of cell phones and imported vast amounts

454
00:24:19,680 --> 00:24:22,600
Speaker 6: of cell phones, but the location of the production is shifting,

455
00:24:22,840 --> 00:24:24,680
Speaker 6: and it's shifting for these security reasons.

456
00:24:25,359 --> 00:24:28,280
Speaker 4: Can the global economy truly be global if there is

457
00:24:28,320 --> 00:24:35,000
Speaker 4: this seemingly broadening divide between China and the West.

458
00:24:35,320 --> 00:24:38,080
Speaker 6: Well, there's going to be greater frictions within global trade

459
00:24:38,119 --> 00:24:41,560
Speaker 6: and capital flows and technology flows, maybe people flows too.

460
00:24:42,280 --> 00:24:45,440
Speaker 6: As I argue in the book, the key economic, key

461
00:24:45,520 --> 00:24:47,919
Speaker 6: driver of the economic consequences of this fracturing it's going

462
00:24:47,960 --> 00:24:50,720
Speaker 6: to be twofold. One is how do other countries align?

463
00:24:51,640 --> 00:24:53,720
Speaker 6: Can the US block, which is enormous, kind of hold

464
00:24:53,720 --> 00:24:55,760
Speaker 6: together or does Trump push everyone apart?

465
00:24:56,400 --> 00:24:58,280
Speaker 5: And then the second, as you allude.

466
00:24:58,000 --> 00:25:00,840
Speaker 6: To Poored, is the contours of the fracturing. If it's

467
00:25:00,880 --> 00:25:04,240
Speaker 6: contained to things like cell phones and batteries and chips

468
00:25:04,280 --> 00:25:08,280
Speaker 6: and semiconductors and pharmaceutical products, then I think the economic

469
00:25:08,520 --> 00:25:11,320
Speaker 6: costs are going to be quite limited to be manageable.

470
00:25:11,720 --> 00:25:14,480
Speaker 6: If we get a much wider fracturing that encompasses many

471
00:25:14,520 --> 00:25:16,920
Speaker 6: more areas than the economic costs will be much larger.

472
00:25:17,960 --> 00:25:20,480
Speaker 6: And if the two sides ever come to conflict, then

473
00:25:20,720 --> 00:25:23,000
Speaker 6: all bets are off. We shouldn't worry about the economic costs.

474
00:25:22,920 --> 00:25:25,680
Speaker 2: We're sharing with us. The fractured age is the book

475
00:25:25,680 --> 00:25:29,040
Speaker 2: two hundred and fifty pages. Mister wolf Over at Financial

476
00:25:29,080 --> 00:25:33,760
Speaker 2: Time says an exceptionally sensible, clear headed, and original thinker.

477
00:25:33,760 --> 00:25:36,320
Speaker 2: I'll vote for that is well. One of your Catholic

478
00:25:36,320 --> 00:25:39,840
Speaker 2: economics essays Europe flat and is back. We see that

479
00:25:39,960 --> 00:25:43,240
Speaker 2: with the politics of France and I looked at it's

480
00:25:43,359 --> 00:25:46,800
Speaker 2: sterling swissy today and my word, it looks like Britain

481
00:25:46,840 --> 00:25:51,800
Speaker 2: after World War Two. How fragile is the continental and

482
00:25:52,000 --> 00:25:53,800
Speaker 2: United Kingdom economy right now?

483
00:25:54,440 --> 00:25:56,800
Speaker 6: I think about the UK to one side. The UK

484
00:25:56,920 --> 00:25:58,920
Speaker 6: we have our own fiscal challenges, but actually I don't

485
00:25:58,920 --> 00:26:01,600
Speaker 6: think they're quite as a cut as say France. Yeah,

486
00:26:01,600 --> 00:26:03,680
Speaker 6: there's plans on the way to reduce the deficit in

487
00:26:03,720 --> 00:26:06,160
Speaker 6: the UK. The question is, really you're optimistic the UK

488
00:26:06,240 --> 00:26:07,639
Speaker 6: can get it det I think we can get to

489
00:26:07,720 --> 00:26:10,240
Speaker 6: kind of muddle our way through. There's enough fiscal fudge

490
00:26:10,320 --> 00:26:12,280
Speaker 6: going around that we can kind of muddle our way.

491
00:26:12,119 --> 00:26:12,960
Speaker 2: Through this one.

492
00:26:13,200 --> 00:26:15,600
Speaker 6: France, it seems to me, is a bit more intractable.

493
00:26:15,760 --> 00:26:19,520
Speaker 6: They've had four governments now of four on the back

494
00:26:19,560 --> 00:26:22,040
Speaker 6: of efforts to try to reduce the budget deficit. The

495
00:26:22,240 --> 00:26:25,040
Speaker 6: parliament is fractured, there's a presidential election due in twenty

496
00:26:25,119 --> 00:26:28,679
Speaker 6: twenty seven. All of this political dysfunction is fodder for

497
00:26:29,160 --> 00:26:31,280
Speaker 6: nationalists populist and let's see what happens in the twenty

498
00:26:31,320 --> 00:26:33,920
Speaker 6: twenty seven election. I don't think that we're going to

499
00:26:33,960 --> 00:26:36,119
Speaker 6: have a repeat of the Eurozone crisis. I don't think

500
00:26:36,119 --> 00:26:38,600
Speaker 6: we're going to get big debt to faults in banking crises.

501
00:26:38,640 --> 00:26:41,200
Speaker 6: The banks in France look pretty well capitalized. They don't

502
00:26:41,240 --> 00:26:44,119
Speaker 6: hold much government debt, but it's a fiscal crisis that

503
00:26:44,240 --> 00:26:44,600
Speaker 6: is brewing.

504
00:26:44,920 --> 00:26:47,560
Speaker 2: Albums. If the right takes over in France, I mean

505
00:26:47,560 --> 00:26:51,920
Speaker 2: within the five party parliamentary system, the right in Hungry,

506
00:26:52,320 --> 00:26:54,919
Speaker 2: the right in Poland, the right, I mean there's a

507
00:26:55,040 --> 00:26:58,760
Speaker 2: huge fear almost of it. I'll call it a Trumpian

508
00:26:58,880 --> 00:26:59,440
Speaker 2: right in.

509
00:26:59,440 --> 00:27:01,880
Speaker 6: Europe, absolutely, and we're seeing it happen. That's what we're

510
00:27:01,880 --> 00:27:03,840
Speaker 6: seeing this play out in real life. That I think

511
00:27:03,880 --> 00:27:07,159
Speaker 6: the question is what type of rights that might might

512
00:27:08,040 --> 00:27:12,359
Speaker 6: govern Italy is an interesting example here. We've had a

513
00:27:12,440 --> 00:27:15,320
Speaker 6: kind of populist right wing government for the last couple

514
00:27:15,320 --> 00:27:18,880
Speaker 6: of years under Georgia Maloney. Actually they've governed in economic

515
00:27:19,000 --> 00:27:21,840
Speaker 6: matters in their relatively orthodox way. So I think it

516
00:27:21,880 --> 00:27:25,560
Speaker 6: depends as much upon how they govern in if they

517
00:27:25,600 --> 00:27:28,480
Speaker 6: win power as to what the rhetoric do.

518
00:27:28,400 --> 00:27:31,960
Speaker 4: You think This is a seminal point for France right

519
00:27:32,000 --> 00:27:35,640
Speaker 4: now to either stay the course and hope for the best,

520
00:27:35,720 --> 00:27:40,359
Speaker 4: or make it some significant changes. Is this a pivot moment.

521
00:27:40,800 --> 00:27:42,440
Speaker 6: I think we are kind of we're approaching one of

522
00:27:42,480 --> 00:27:45,240
Speaker 6: those pivot moments, certainly when it comes to the political

523
00:27:45,280 --> 00:27:48,119
Speaker 6: structure of France. If you look at the rise of

524
00:27:48,160 --> 00:27:49,240
Speaker 6: the right, and you look at the rise of the

525
00:27:49,320 --> 00:27:51,840
Speaker 6: right across Europe, I mean, the center is kind of

526
00:27:51,880 --> 00:27:54,199
Speaker 6: holding so far. The center health in the German elections

527
00:27:54,280 --> 00:27:57,240
Speaker 6: last year. The center's held so far in France. The

528
00:27:57,359 --> 00:28:00,159
Speaker 6: question is would it continue to hold through to twenty

529
00:28:00,240 --> 00:28:02,639
Speaker 6: twenty seven in those elections you're sharing.

530
00:28:02,720 --> 00:28:05,600
Speaker 2: And the government shutdown of the United States.

531
00:28:05,280 --> 00:28:08,040
Speaker 5: Of America, well, I've just spent two hours.

532
00:28:08,080 --> 00:28:11,480
Speaker 6: I came. I flew into Dallas on Monday evening. I

533
00:28:11,520 --> 00:28:13,119
Speaker 6: spent two and a half hours at immigration.

534
00:28:14,680 --> 00:28:16,520
Speaker 2: Yeah, did you say hello to Lisamated?

535
00:28:17,080 --> 00:28:20,960
Speaker 6: Exactly. So it's so it's having a real world consequence

536
00:28:21,000 --> 00:28:23,640
Speaker 6: now in terms of the impact on the economy. When

537
00:28:23,680 --> 00:28:26,000
Speaker 6: we look through the history of government shutdowns, we can't

538
00:28:26,000 --> 00:28:27,840
Speaker 6: really see them in the economic data. It tends to

539
00:28:27,840 --> 00:28:29,760
Speaker 6: be a bit of dislocation that gets made up in

540
00:28:29,800 --> 00:28:32,439
Speaker 6: subsequent months. But again, a bit like France, this speaks

541
00:28:32,480 --> 00:28:35,359
Speaker 6: to political dysfunction, and it is as acute here in

542
00:28:35,440 --> 00:28:37,600
Speaker 6: the US as it is in Europe.

543
00:28:37,840 --> 00:28:42,280
Speaker 2: Congratulations, you're sharing the fractured age. Can't say enough about it.

544
00:28:42,400 --> 00:28:47,640
Speaker 2: Really an abrupt read in well timed to say the least.

545
00:28:48,080 --> 00:28:59,680
Speaker 2: Stay with us. More from Bloomberg Surveillance coming up after this.

546
00:28:59,680 --> 00:29:03,600
Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday

547
00:29:03,640 --> 00:29:07,040
Speaker 1: starting at seven am Eastern on Applecarplay and Android Auto

548
00:29:07,080 --> 00:29:09,920
Speaker 1: with the Bloomberg Business app. You can also watch us

549
00:29:09,960 --> 00:29:13,680
Speaker 1: live every weekday on YouTube and always on the Bloomberg Terminal.

550
00:29:13,920 --> 00:29:16,920
Speaker 2: That special moment here for Bloomberg Surveillance this morning, our

551
00:29:17,160 --> 00:29:19,800
Speaker 2: essay of the year I'm thrilled to announces, will do

552
00:29:19,880 --> 00:29:22,680
Speaker 2: that here in a moment. Stay with us across America

553
00:29:22,760 --> 00:29:26,320
Speaker 2: around the work. Can I just suggest this hour of

554
00:29:26,320 --> 00:29:29,480
Speaker 2: Bloomberg Surveillance sponsored by generous.

555
00:29:29,120 --> 00:29:30,920
Speaker 5: Electric Shorts Finances Chins.

556
00:29:30,960 --> 00:29:33,560
Speaker 2: We'll do that maybe as well. Futures up, ten down,

557
00:29:33,560 --> 00:29:36,480
Speaker 2: Futures up, one hundred and thirty eight. Bloomberg Surveillance this

558
00:29:36,560 --> 00:29:40,400
Speaker 2: Morning brought you by IBKR. Well the US Consumer Sentiment

559
00:29:40,440 --> 00:29:45,360
Speaker 2: Index it seeds sixty in October twenty twenty five at

560
00:29:45,400 --> 00:29:50,320
Speaker 2: IBKR Forecast Trader. The yes was recently at thirty three percent.

561
00:29:50,600 --> 00:29:56,040
Speaker 2: Start predicting today at ibkr dot com slash forecast. Last

562
00:29:56,080 --> 00:30:00,520
Speaker 2: training day for this contract is October twenty five, So

563
00:30:00,920 --> 00:30:04,000
Speaker 2: over a decade ago. David Brooks did an essay in

564
00:30:04,040 --> 00:30:05,600
Speaker 2: the New York Times. It was my essay of the

565
00:30:05,680 --> 00:30:10,960
Speaker 2: year on the nerds in the smooth Guys on Wall Street.

566
00:30:11,040 --> 00:30:15,400
Speaker 2: It was brilliant on the cultural divide on Wall Street.

567
00:30:15,440 --> 00:30:19,000
Speaker 2: I still quote it in speeches all the time. Brilliant essay.

568
00:30:19,800 --> 00:30:23,160
Speaker 2: This year, My essay of the year is on the

569
00:30:23,280 --> 00:30:27,960
Speaker 2: generational divide that we live every single day. Paul's limited,

570
00:30:28,080 --> 00:30:30,040
Speaker 2: I'm limited, Tucker. Do you have offspring?

571
00:30:31,000 --> 00:30:31,120
Speaker 6: Ah?

572
00:30:31,320 --> 00:30:35,840
Speaker 2: Yeah, okay, altering as well, joining us now with my

573
00:30:36,080 --> 00:30:37,720
Speaker 2: essay of the year. This was out of the Wall

574
00:30:37,720 --> 00:30:41,280
Speaker 2: Street Journal a number of days ago, and she's made

575
00:30:41,280 --> 00:30:44,440
Speaker 2: a huge splash with it. Is Professor Susie Welch of

576
00:30:44,600 --> 00:30:50,080
Speaker 2: NYU is gen z unemployable. It has created a firestorm

577
00:30:50,480 --> 00:30:52,600
Speaker 2: of comment. And I have to go to this because

578
00:30:52,600 --> 00:30:55,000
Speaker 2: the last time Susie, I think I saw you was

579
00:30:55,040 --> 00:30:58,240
Speaker 2: with a guy named Jack Welch. When did you decide

580
00:30:58,400 --> 00:31:02,040
Speaker 2: to go into the dark caver and of academics at NYU?

581
00:31:02,120 --> 00:31:04,200
Speaker 2: What was the pat You didn't have to do this?

582
00:31:04,280 --> 00:31:07,400
Speaker 8: I did not I had been in broadcast journalism for

583
00:31:07,440 --> 00:31:09,920
Speaker 8: a bunch of years, and then I was running a

584
00:31:09,960 --> 00:31:14,200
Speaker 8: small tech music tech company, and the pandemic brought it

585
00:31:14,240 --> 00:31:17,160
Speaker 8: to its knees. And then Jack passed away, and I

586
00:31:17,200 --> 00:31:19,360
Speaker 8: went up to the woods of upstate New York with

587
00:31:19,400 --> 00:31:21,200
Speaker 8: all my kids and all their spouses and all of

588
00:31:21,200 --> 00:31:24,160
Speaker 8: our dogs. And then the pandemic ended and everybody went

589
00:31:24,240 --> 00:31:27,040
Speaker 8: back to life. I had been cooking up in my

590
00:31:27,120 --> 00:31:29,760
Speaker 8: mind a class called Becoming You, which was going to

591
00:31:29,760 --> 00:31:31,240
Speaker 8: help people figure out what to do with their lives,

592
00:31:31,320 --> 00:31:32,840
Speaker 8: which was what I was trying to figure out what

593
00:31:32,880 --> 00:31:33,920
Speaker 8: to do with my life.

594
00:31:34,240 --> 00:31:36,120
Speaker 5: And I brought it to n Yu Stern and to.

595
00:31:36,120 --> 00:31:37,800
Speaker 8: The dean there, who I knew from my previous life,

596
00:31:37,800 --> 00:31:39,240
Speaker 8: and I said, I've got this class I wish I

597
00:31:39,240 --> 00:31:41,800
Speaker 8: had taken in business school that has a methodology that

598
00:31:41,880 --> 00:31:43,680
Speaker 8: helps you figure out what to do with your life.

599
00:31:43,800 --> 00:31:46,640
Speaker 8: And he said, well, let's try it as an experiment.

600
00:31:46,760 --> 00:31:50,400
Speaker 2: Before we get to the essay. Yes, what reeks in

601
00:31:50,480 --> 00:31:55,760
Speaker 2: this essay is academic rigidity. This is not some fancy

602
00:31:55,840 --> 00:31:59,920
Speaker 2: person like Susie Welch who decided to get some cushy thing.

603
00:32:00,560 --> 00:32:03,160
Speaker 2: There are some real work of often here. This is

604
00:32:03,200 --> 00:32:06,840
Speaker 2: like legit, accountable academic research, isn't it.

605
00:32:06,920 --> 00:32:08,480
Speaker 5: Yes, I'm proud to say that it is.

606
00:32:08,560 --> 00:32:10,560
Speaker 8: I mean it was conducted by myself and my team,

607
00:32:10,600 --> 00:32:13,600
Speaker 8: which includes all of the usual suspects of psychometricians and

608
00:32:13,680 --> 00:32:16,960
Speaker 8: data analysts and so forth. So we the research, I

609
00:32:17,000 --> 00:32:18,840
Speaker 8: think is I'm really proud of it.

610
00:32:18,840 --> 00:32:19,760
Speaker 5: It's rock solid.

611
00:32:19,880 --> 00:32:24,160
Speaker 2: Forty thousand people, seven thousand plus gen Z types. Yeah,

612
00:32:24,240 --> 00:32:27,600
Speaker 2: when did the shock set in over your outcome? And

613
00:32:27,640 --> 00:32:28,200
Speaker 2: describe there?

614
00:32:28,360 --> 00:32:31,320
Speaker 8: Well, there's a bunch of you know, Look, I teach

615
00:32:31,880 --> 00:32:35,400
Speaker 8: gen Z every single day, I mean every semester. Are

616
00:32:35,560 --> 00:32:38,560
Speaker 8: hundreds of students, So my shock was perhaps less than

617
00:32:38,600 --> 00:32:40,080
Speaker 8: the rest of the team because I'm in the room

618
00:32:40,240 --> 00:32:44,880
Speaker 8: with them. Now, NYU students are not quite as representative

619
00:32:44,920 --> 00:32:47,680
Speaker 8: of gen Z as outside of NYU. These are MBAs,

620
00:32:47,680 --> 00:32:49,400
Speaker 8: so they tend to have a little bit more ger

621
00:32:49,560 --> 00:32:52,200
Speaker 8: going on. I think that when we saw the two

622
00:32:52,280 --> 00:32:55,560
Speaker 8: percent number which we can get to, we were all like,

623
00:32:55,760 --> 00:32:58,000
Speaker 8: we checked it about thirty five timesoose.

624
00:32:58,040 --> 00:32:59,560
Speaker 5: We thought that is too much in that number.

625
00:33:00,240 --> 00:33:01,720
Speaker 8: So what we did is we have a tool called

626
00:33:01,760 --> 00:33:04,920
Speaker 8: the Values Bridge, which we developed in our labs, and

627
00:33:05,000 --> 00:33:07,000
Speaker 8: what it does is it ranks your values from one

628
00:33:07,040 --> 00:33:10,000
Speaker 8: to sixteen, your personal values from one to sixteen. And

629
00:33:10,080 --> 00:33:13,040
Speaker 8: so we now seventy five thousand people have taken this test,

630
00:33:13,040 --> 00:33:14,360
Speaker 8: but at the time we did the research, it was

631
00:33:14,400 --> 00:33:16,479
Speaker 8: forty five thousand people. And we were able to cut

632
00:33:16,560 --> 00:33:18,719
Speaker 8: it by generation and we were able to see gen

633
00:33:18,840 --> 00:33:21,800
Speaker 8: Z's values ranked from one to sixteen. And their number

634
00:33:21,800 --> 00:33:25,440
Speaker 8: one value is something we call you ammonia, which encompasses

635
00:33:25,480 --> 00:33:29,320
Speaker 8: self care, recreation, leisure, fun employment. You know, just so

636
00:33:29,480 --> 00:33:32,239
Speaker 8: John Tucker, But I think we all know somebody who

637
00:33:32,280 --> 00:33:34,560
Speaker 8: was in eutamonia is their number one value. Number two

638
00:33:34,600 --> 00:33:37,240
Speaker 8: was authentic self expression voice as we call it, and

639
00:33:37,320 --> 00:33:40,320
Speaker 8: number three was the desire to organize their life around

640
00:33:40,360 --> 00:33:42,560
Speaker 8: helping other people, which is very admirable, I would say.

641
00:33:42,960 --> 00:33:45,000
Speaker 8: But after I saw those top three values, I thought,

642
00:33:45,680 --> 00:33:48,120
Speaker 8: I wonder what hiring managers are looking for, because my

643
00:33:48,160 --> 00:33:49,800
Speaker 8: students are going out into the world to get hired.

644
00:33:49,800 --> 00:33:52,480
Speaker 8: I have four adult children who are fighting out there

645
00:33:52,480 --> 00:33:54,360
Speaker 8: in the world every day. So we did a separate

646
00:33:54,640 --> 00:33:59,400
Speaker 8: study and we replicated it twice after that to say, okay,

647
00:33:59,640 --> 00:34:02,160
Speaker 8: here the definitions of all the values hiring managers in

648
00:34:02,280 --> 00:34:07,520
Speaker 8: knowledge industries mainly business, It was tech, it was accounting, finance,

649
00:34:07,560 --> 00:34:10,319
Speaker 8: and so forth. The consulting what values are you looking for?

650
00:34:10,360 --> 00:34:11,240
Speaker 5: And lo and behold.

651
00:34:11,239 --> 00:34:13,400
Speaker 8: They were looking for the number one value of achievement,

652
00:34:13,600 --> 00:34:15,960
Speaker 8: the desire to have success that other people can see.

653
00:34:16,200 --> 00:34:19,160
Speaker 8: Number two was a desire for learning, stimulation and growth.

654
00:34:19,160 --> 00:34:21,920
Speaker 8: And the third value was work centrism, the desire to

655
00:34:22,000 --> 00:34:26,560
Speaker 8: work hard. And when you cross reference those two data sets,

656
00:34:26,719 --> 00:34:29,440
Speaker 8: it ends up that it's just two percent of gen

657
00:34:29,560 --> 00:34:32,359
Speaker 8: Z that have the values that hiring managers are looking for.

658
00:34:32,800 --> 00:34:33,320
Speaker 5: It's interesting.

659
00:34:33,400 --> 00:34:38,160
Speaker 4: I've for gen Z adjacent kind of offspring. They're all employed,

660
00:34:39,160 --> 00:34:42,640
Speaker 4: but they tell me their first memories of my oldest

661
00:34:42,680 --> 00:34:45,640
Speaker 4: were nine to eleven. That's their first memory. Yeah, and

662
00:34:45,680 --> 00:34:49,680
Speaker 4: then they had, you know, the great financial crisis, right,

663
00:34:50,000 --> 00:34:52,120
Speaker 4: their parents are impact that everybody's parents are impact. And

664
00:34:52,120 --> 00:34:54,400
Speaker 4: then they had the pandemic. So they've had some stuff,

665
00:34:54,640 --> 00:34:57,319
Speaker 4: you know, and I wonder have that influence is kind

666
00:34:57,360 --> 00:34:58,839
Speaker 4: of how they look the view of the world.

667
00:34:58,960 --> 00:35:00,960
Speaker 8: Yeah, I think they don't want to buy into a

668
00:35:01,000 --> 00:35:03,080
Speaker 8: deal that their parents bought into that didn't work out

669
00:35:03,120 --> 00:35:03,960
Speaker 8: for a lot of their parents.

670
00:35:04,080 --> 00:35:06,160
Speaker 5: I mean, you can you can come up with.

671
00:35:06,080 --> 00:35:08,279
Speaker 8: A hundred reasons why they have these values and they're

672
00:35:08,400 --> 00:35:10,920
Speaker 8: entitled to them. I think that the problem is values

673
00:35:10,960 --> 00:35:13,960
Speaker 8: have consequences, and so some of them also have affluence

674
00:35:14,000 --> 00:35:16,360
Speaker 8: as a top value, and then they are very frustrated

675
00:35:16,600 --> 00:35:19,120
Speaker 8: and frustrated to the point of kind of anger that

676
00:35:19,160 --> 00:35:22,240
Speaker 8: they don't get the they don't get to have affluence

677
00:35:22,280 --> 00:35:23,840
Speaker 8: also as an output. If you have the value of

678
00:35:23,840 --> 00:35:25,960
Speaker 8: self care number one, so they can have their value.

679
00:35:26,000 --> 00:35:27,640
Speaker 8: I don't you know how they can buy their values.

680
00:35:27,760 --> 00:35:29,440
Speaker 8: I get it, there's a million reasons. I mean, their

681
00:35:29,480 --> 00:35:31,840
Speaker 8: parents might be to blame. I mean, with the torrent

682
00:35:31,880 --> 00:35:34,200
Speaker 8: of letters that came to the letters to the editor

683
00:35:34,239 --> 00:35:36,120
Speaker 8: after the article ran, a lot of people had a

684
00:35:36,160 --> 00:35:38,600
Speaker 8: lot of people they wanted to blame for this phenomenon.

685
00:35:39,480 --> 00:35:43,120
Speaker 4: What does corporate America do here? Is corporate America adjust?

686
00:35:43,239 --> 00:35:43,600
Speaker 7: You think that?

687
00:35:43,840 --> 00:35:45,960
Speaker 2: Or do the students adjust or do they.

688
00:35:46,239 --> 00:35:48,000
Speaker 4: Just find to find some common ground?

689
00:35:48,080 --> 00:35:49,800
Speaker 5: Maybe this is a million dollar questions.

690
00:35:49,800 --> 00:35:51,480
Speaker 8: So I've talked to a lot of business leaders since

691
00:35:51,520 --> 00:35:55,240
Speaker 8: the piece came out, and so the companies with brand

692
00:35:55,360 --> 00:35:58,719
Speaker 8: equity who can go higher the two percent are out

693
00:35:58,719 --> 00:36:01,200
Speaker 8: looking for them earlier, and they one executive said to me,

694
00:36:01,440 --> 00:36:03,960
Speaker 8: this is a cage match. We're willing to fight all right,

695
00:36:03,960 --> 00:36:05,600
Speaker 8: they're going to go find that two percent. They're going

696
00:36:05,640 --> 00:36:07,120
Speaker 8: to they know where they are, they're going to go

697
00:36:07,160 --> 00:36:09,480
Speaker 8: get them earlier, and they're going to lock them down.

698
00:36:09,880 --> 00:36:11,880
Speaker 8: And then other companies are going to have to figure

699
00:36:11,880 --> 00:36:14,359
Speaker 8: out what to do about the fact that they're not

700
00:36:14,400 --> 00:36:18,440
Speaker 8: going to be hiring young people who share their company values.

701
00:36:18,800 --> 00:36:21,560
Speaker 8: And do they accommodate them or do they try to

702
00:36:21,680 --> 00:36:24,320
Speaker 8: slowly move them over to a different.

703
00:36:24,040 --> 00:36:26,040
Speaker 5: Way of thinking. It's very hard to talk people out

704
00:36:26,080 --> 00:36:26,600
Speaker 5: of their values.

705
00:36:26,640 --> 00:36:28,560
Speaker 4: However, Yeah, what do you find in the NBA program,

706
00:36:28,640 --> 00:36:31,600
Speaker 4: Because you said those people kind of self select, they

707
00:36:32,680 --> 00:36:35,920
Speaker 4: want to achieve, presumably, but again I would suspect you

708
00:36:35,960 --> 00:36:36,879
Speaker 4: see some of that in your class.

709
00:36:37,000 --> 00:36:40,279
Speaker 8: I mean, I see a preponderance of pneumonia, self care

710
00:36:40,320 --> 00:36:43,040
Speaker 8: being a top value. I do have MBAs, okay and so,

711
00:36:43,600 --> 00:36:46,520
Speaker 8: and in particular the nbas we're majoring in finance. Those

712
00:36:46,719 --> 00:36:49,040
Speaker 8: they have a lot of the values that companies are

713
00:36:49,040 --> 00:36:50,880
Speaker 8: looking for, and they're picked off pretty early.

714
00:36:52,080 --> 00:36:52,879
Speaker 5: But I don't think this.

715
00:36:52,880 --> 00:36:55,520
Speaker 8: Is true in colleges in general, and I think there's

716
00:36:55,520 --> 00:36:56,800
Speaker 8: a few And this is what I mean is that

717
00:36:56,840 --> 00:36:58,520
Speaker 8: companies are going to figure out where the two percent

718
00:36:58,520 --> 00:36:59,759
Speaker 8: are and they're going to come get them and they're

719
00:36:59,760 --> 00:37:00,640
Speaker 8: going to at them early.

720
00:37:01,440 --> 00:37:04,600
Speaker 4: So how about for these these kids, though, I mean,

721
00:37:05,000 --> 00:37:08,800
Speaker 4: do they recognize that maybe they are in fact different

722
00:37:09,000 --> 00:37:12,480
Speaker 4: from certainly maybe their parents and maybe their grandparents and others,

723
00:37:12,520 --> 00:37:14,560
Speaker 4: and they they're defiant and they're okay with them.

724
00:37:14,600 --> 00:37:17,560
Speaker 8: No, they're defiant. I mean they're not just okay. They're

725
00:37:17,680 --> 00:37:20,600
Speaker 8: they're they're defiant. They're like you, I mean what the

726
00:37:20,719 --> 00:37:23,439
Speaker 8: letters from gen Z that I got, the emails were like, hey,

727
00:37:24,080 --> 00:37:27,080
Speaker 8: shut up over there, lady, because you ruined the world.

728
00:37:27,120 --> 00:37:30,359
Speaker 8: You boomer people ruined the world. And our response is this,

729
00:37:30,719 --> 00:37:32,879
Speaker 8: and why would we want your values? Look what you

730
00:37:32,920 --> 00:37:37,840
Speaker 8: did to us with climate change and terrorism and school shootings.

731
00:37:38,000 --> 00:37:41,560
Speaker 5: You created this world? Why would we buy your version

732
00:37:41,600 --> 00:37:42,080
Speaker 5: of events?

733
00:37:42,280 --> 00:37:45,440
Speaker 2: Welcome all of you across America. It is my essay

734
00:37:45,520 --> 00:37:48,680
Speaker 2: of the year. Susie Welch, professor at New York University.

735
00:37:48,719 --> 00:37:51,000
Speaker 2: Where that's it's in the Wall Street journals. Created a

736
00:37:51,040 --> 00:37:55,640
Speaker 2: firestorm of comment, including from the kids in my family

737
00:37:55,719 --> 00:37:57,960
Speaker 2: as well. Susie, I had the honor of talking to

738
00:37:58,000 --> 00:38:00,560
Speaker 2: a guy named Jack Welch and frankly on it fmled

739
00:38:00,600 --> 00:38:04,840
Speaker 2: as well. Is the magic of the corridor from Pittsfield, Massachusetts,

740
00:38:05,120 --> 00:38:10,080
Speaker 2: through Albany out the Mohawk River Valley every single nineteenth

741
00:38:10,239 --> 00:38:14,439
Speaker 2: early twentieth century industrial X exercise out to the Great

742
00:38:14,480 --> 00:38:19,280
Speaker 2: Eastman Kodec Company GE nineteen twelve invented a fine benefit

743
00:38:19,320 --> 00:38:24,040
Speaker 2: pension plan. Those companies Carrier in Syracuse, Coodek, and Rochester.

744
00:38:24,400 --> 00:38:27,080
Speaker 2: They took care of their employees. What you're going to

745
00:38:27,160 --> 00:38:29,839
Speaker 2: hear in your classroom, what I hear every day is

746
00:38:29,880 --> 00:38:34,399
Speaker 2: the loyalty has been broken because of the employers. What

747
00:38:34,440 --> 00:38:38,000
Speaker 2: do employers need to do to increase that two percent

748
00:38:38,360 --> 00:38:39,920
Speaker 2: to a much larger number.

749
00:38:41,040 --> 00:38:43,920
Speaker 8: I think that they can't do what they would need

750
00:38:43,920 --> 00:38:47,279
Speaker 8: to do, which is promise a long term employment. I mean,

751
00:38:47,320 --> 00:38:49,520
Speaker 8: people feel loyal when they feel like, Okay, I'm investing

752
00:38:49,520 --> 00:38:51,200
Speaker 8: my time in a company, and I'm going to be

753
00:38:51,239 --> 00:38:53,000
Speaker 8: here in two or three years and my boss is

754
00:38:53,000 --> 00:38:53,480
Speaker 8: going to be here.

755
00:38:53,600 --> 00:38:56,440
Speaker 2: Disclosure Bloomberg LP every day. It's a privilege. I mean,

756
00:38:56,440 --> 00:38:58,440
Speaker 2: that's where we come from, right, the three of us

757
00:38:58,520 --> 00:38:59,319
Speaker 2: in this were right.

758
00:38:59,440 --> 00:39:01,920
Speaker 8: Well, you probably a sense that, look, this company is

759
00:39:01,960 --> 00:39:04,319
Speaker 8: healthy and it's thriving, and we're all going to be here,

760
00:39:04,360 --> 00:39:06,960
Speaker 8: and I'm willing to give myself to this organization and

761
00:39:07,000 --> 00:39:09,000
Speaker 8: to work the extra hours because we're all going to

762
00:39:09,040 --> 00:39:11,920
Speaker 8: be here together. And but for most people going into organizations,

763
00:39:11,920 --> 00:39:14,560
Speaker 8: there's this constant sense of fragility and we may not

764
00:39:14,680 --> 00:39:15,000
Speaker 8: be here.

765
00:39:15,080 --> 00:39:16,200
Speaker 5: I could be gone tomorrow.

766
00:39:16,360 --> 00:39:19,680
Speaker 8: Why would you invest in yourself in that? And so

767
00:39:20,239 --> 00:39:23,680
Speaker 8: that contract is pretty much over now. There are places

768
00:39:23,719 --> 00:39:25,960
Speaker 8: I think JP Morgan, Goldman Zachs you can go and

769
00:39:25,960 --> 00:39:28,280
Speaker 8: think I could try to build my whole career here.

770
00:39:28,280 --> 00:39:30,160
Speaker 5: But there's not a lot of companies like that anymore.

771
00:39:30,480 --> 00:39:33,480
Speaker 4: A lot of it is technology. There's so much technology

772
00:39:33,480 --> 00:39:35,560
Speaker 4: out there, there's so much. Is that a net positive?

773
00:39:35,600 --> 00:39:37,040
Speaker 4: Like do the kids in your class like that's a

774
00:39:37,080 --> 00:39:42,080
Speaker 4: net positive? AI is probably all over your daily issues

775
00:39:42,200 --> 00:39:46,440
Speaker 4: with your dealings with your students. Is that is technology

776
00:39:46,440 --> 00:39:48,360
Speaker 4: with the hindsight a net positive or net negative?

777
00:39:48,960 --> 00:39:51,000
Speaker 8: This is I don't know the answer. Sometimes I think

778
00:39:51,040 --> 00:39:53,000
Speaker 8: it's a real net negative and what it's done to

779
00:39:53,120 --> 00:39:54,920
Speaker 8: how much we talk to each other. But I will

780
00:39:54,960 --> 00:39:59,000
Speaker 8: say that my students are terrified because of AI. Like right,

781
00:39:59,040 --> 00:40:02,279
Speaker 8: AI is taking the job they would do AI. You know,

782
00:40:02,440 --> 00:40:05,440
Speaker 8: a first year consultant or a first year analyst, they're

783
00:40:05,440 --> 00:40:08,520
Speaker 8: like deer in headlights, like what jobs are left for us?

784
00:40:09,000 --> 00:40:13,080
Speaker 8: How where are our entry points? That's why technology is scary.

785
00:40:13,200 --> 00:40:15,719
Speaker 8: Now when it comes to using AI for.

786
00:40:15,680 --> 00:40:18,880
Speaker 5: Homework, that's a totally what is your experience? What do

787
00:40:18,880 --> 00:40:19,120
Speaker 5: you say?

788
00:40:19,400 --> 00:40:21,120
Speaker 8: When it first came out, they were using it a lot,

789
00:40:21,239 --> 00:40:23,319
Speaker 8: and then as teachers we got very savvy about how

790
00:40:23,360 --> 00:40:26,120
Speaker 8: to phrase the homework, you know, from your personal experience.

791
00:40:26,640 --> 00:40:28,000
Speaker 8: And then I look at my students, I say, you know,

792
00:40:28,000 --> 00:40:29,600
Speaker 8: it's against the rules to use this on exams, and

793
00:40:29,640 --> 00:40:32,759
Speaker 8: I'm asking you personally, for reasons of integrity, do not

794
00:40:32,840 --> 00:40:33,279
Speaker 8: use AI.

795
00:40:33,320 --> 00:40:34,200
Speaker 5: And generally they.

796
00:40:34,120 --> 00:40:39,080
Speaker 2: Comb aerospace engineering At Boulder, I got through the Great

797
00:40:39,080 --> 00:40:42,520
Speaker 2: Books English course off the cliff notes. Did you mean

798
00:40:42,600 --> 00:40:45,560
Speaker 2: is there any difference between the cliff notes and AI?

799
00:40:47,520 --> 00:40:49,880
Speaker 8: That's a good point. I think that AI does the

800
00:40:49,920 --> 00:40:52,200
Speaker 8: thinking for them. With the cliff notes, usually you would

801
00:40:52,200 --> 00:40:54,480
Speaker 8: then go into a classroom and you'd be forced to

802
00:40:54,480 --> 00:40:57,959
Speaker 8: discuss issues. But AI, right, you know, does the thinking

803
00:40:58,000 --> 00:40:58,799
Speaker 8: and the talking.

804
00:40:58,840 --> 00:41:01,520
Speaker 2: Explain to me what I I also see, particularly what

805
00:41:01,640 --> 00:41:06,920
Speaker 2: I'm giving speeches between the American gen z yeah and

806
00:41:06,960 --> 00:41:11,160
Speaker 2: the hungry four is a stereotype the hungry for in

807
00:41:11,239 --> 00:41:15,200
Speaker 2: a kid's recent immigrants. Second they're not buying the gen

808
00:41:15,320 --> 00:41:19,560
Speaker 2: Z thing. They're focused and they're killing it in differential equations.

809
00:41:19,760 --> 00:41:20,640
Speaker 2: It's stern, all right.

810
00:41:20,680 --> 00:41:22,640
Speaker 8: So this is what I want to say to that,

811
00:41:23,400 --> 00:41:24,799
Speaker 8: and I want to wait to the data comes in.

812
00:41:24,840 --> 00:41:27,120
Speaker 8: But we are currently running the exact same study in

813
00:41:27,160 --> 00:41:31,200
Speaker 8: three different places, one with first generation immigrants as part

814
00:41:31,200 --> 00:41:33,880
Speaker 8: of the gen Z and then we are attempting in

815
00:41:33,960 --> 00:41:37,399
Speaker 8: a collaboration with a different school to do it for

816
00:41:37,440 --> 00:41:39,759
Speaker 8: this exact study in India, and I don't know if

817
00:41:39,760 --> 00:41:41,560
Speaker 8: we'll be able to do it, but in China. And

818
00:41:41,600 --> 00:41:45,160
Speaker 8: I think that has implications for American competitiveness because if

819
00:41:45,160 --> 00:41:48,920
Speaker 8: it comes back, then in India eighty two percent of

820
00:41:48,960 --> 00:41:53,280
Speaker 8: gen Z has hiring managers values.

821
00:41:53,640 --> 00:41:55,239
Speaker 5: Right, that's worriesome that.

822
00:41:55,320 --> 00:41:57,239
Speaker 2: Susie Welcher is my essay of the year. It's in

823
00:41:57,280 --> 00:42:00,400
Speaker 2: the Wall Street Journal on gen Z. Thrilled could come

824
00:42:00,440 --> 00:42:05,080
Speaker 2: in to celebrate the research of it at New York University,

825
00:42:05,080 --> 00:42:06,360
Speaker 2: Paul finished it up. Please.

826
00:42:06,440 --> 00:42:08,839
Speaker 4: I wonder if gen Z, because I live with them

827
00:42:08,840 --> 00:42:13,879
Speaker 4: every day, will be if their values will change as

828
00:42:13,880 --> 00:42:18,280
Speaker 4: they age and they say, ooh, I got a mortgage now, Okay, So.

829
00:42:18,520 --> 00:42:22,279
Speaker 8: Values generally don't change, Okay, right, values are generally set

830
00:42:22,320 --> 00:42:24,040
Speaker 8: by time we're twenty five years old, because a lot

831
00:42:24,080 --> 00:42:26,160
Speaker 8: of things go into that too. What changes is how

832
00:42:26,200 --> 00:42:28,520
Speaker 8: much we express them or repress them. So I think

833
00:42:28,520 --> 00:42:30,480
Speaker 8: what will happen is gen Z will keep these values

834
00:42:30,480 --> 00:42:32,920
Speaker 8: because unless you have a seismic event, your values generally

835
00:42:32,920 --> 00:42:36,000
Speaker 8: stay the same your whole life. The seismic event may

836
00:42:36,040 --> 00:42:38,920
Speaker 8: be not getting a job, and then therefore they'll repress

837
00:42:39,000 --> 00:42:42,080
Speaker 8: certain values or they'll suppress them not happily.

838
00:42:43,440 --> 00:42:46,480
Speaker 4: Do you see that as again, you're the one of

839
00:42:46,520 --> 00:42:48,760
Speaker 4: the top NBA programs in the world.

840
00:42:48,800 --> 00:42:53,960
Speaker 2: Here my first sponsor, first people to step up.

841
00:42:54,320 --> 00:42:56,480
Speaker 4: My point is half of Global Wall Street came out

842
00:42:56,480 --> 00:42:57,240
Speaker 4: of the Stern program.

843
00:42:57,480 --> 00:42:57,920
Speaker 2: Everywhere.

844
00:42:57,960 --> 00:43:02,240
Speaker 5: Absolutely, that's ever really true. I mean, as a student

845
00:43:02,239 --> 00:43:05,799
Speaker 5: body changed there? Do you think my students who I.

846
00:43:05,760 --> 00:43:07,480
Speaker 8: Don't want to make generalizations, but my students who are

847
00:43:07,600 --> 00:43:10,960
Speaker 8: first generation generally are in that two percent, so they're

848
00:43:10,960 --> 00:43:13,400
Speaker 8: not changing anything. They're like, they've got their parents' values

849
00:43:13,400 --> 00:43:17,239
Speaker 8: and they're there to win, and they are clearly already there.

850
00:43:17,680 --> 00:43:20,440
Speaker 8: I don't see the change yet right now, I just

851
00:43:20,560 --> 00:43:25,800
Speaker 8: see a shock, you know, Okay, nobody doubts the research, right,

852
00:43:25,920 --> 00:43:27,080
Speaker 8: they don't know what they're going to do.

853
00:43:27,080 --> 00:43:29,360
Speaker 2: Do you give out c's? Okay, I just you know,

854
00:43:29,520 --> 00:43:32,520
Speaker 2: just a vignette, folks. I had a privilege of Ruth

855
00:43:32,560 --> 00:43:37,640
Speaker 2: Rebecca Stroic in mathematics one hundred million years ago. It

856
00:43:37,680 --> 00:43:41,040
Speaker 2: was a curved grade, right like in England where it's

857
00:43:41,160 --> 00:43:45,319
Speaker 2: much tougher. Could you give Professor Walch a Tito's and

858
00:43:45,400 --> 00:43:50,879
Speaker 2: tang that's good morning? Drink here, Susie, Susie, I look

859
00:43:50,920 --> 00:43:54,600
Speaker 2: at the great inflation and it's a joke. I mean,

860
00:43:54,960 --> 00:43:58,719
Speaker 2: I killed myself for quality C in organic chemistry.

861
00:43:58,840 --> 00:44:01,080
Speaker 5: Yes, I did too. I have I want you to

862
00:44:01,120 --> 00:44:03,160
Speaker 5: know something. I have given a C.

863
00:44:04,200 --> 00:44:06,840
Speaker 8: It's not a very common thing, but what the student

864
00:44:06,840 --> 00:44:09,440
Speaker 8: maybe should have gotten was different than a C. But

865
00:44:09,520 --> 00:44:11,360
Speaker 8: I gave a CE. It felt like a very brave

866
00:44:11,480 --> 00:44:14,400
Speaker 8: and daring thing to do. I spoke to the academic

867
00:44:14,400 --> 00:44:16,560
Speaker 8: dean beforehand, setting I'm giving a CI.

868
00:44:17,080 --> 00:44:17,719
Speaker 2: No kidding me?

869
00:44:17,800 --> 00:44:21,600
Speaker 8: Yeah, because look there's a there's great devlation everywhere. You know,

870
00:44:21,719 --> 00:44:24,920
Speaker 8: I'd be lying to say there wasn't. Should we be

871
00:44:24,960 --> 00:44:26,719
Speaker 8: giving c's the students to say, no, no, no, we

872
00:44:26,760 --> 00:44:27,480
Speaker 8: got to get jobs.

873
00:44:27,480 --> 00:44:30,640
Speaker 5: Please don't do that to us. But lawyers are not

874
00:44:30,719 --> 00:44:31,680
Speaker 5: allowed to ask your.

875
00:44:31,520 --> 00:44:34,960
Speaker 2: Gpsh no one in the control room has ever gotten

876
00:44:35,000 --> 00:44:37,239
Speaker 2: a C. That's what. No, Let's go around the room.

877
00:44:37,600 --> 00:44:40,160
Speaker 4: Business School back in the early nineties, you had twenty

878
00:44:40,239 --> 00:44:42,319
Speaker 4: classes and if you passed all twenty, they stamped your

879
00:44:42,320 --> 00:44:43,799
Speaker 4: passport and I could go back to a Wall Street

880
00:44:43,800 --> 00:44:46,480
Speaker 4: at twice the pay. So though, saying was twenty p's

881
00:44:46,640 --> 00:44:47,440
Speaker 4: equals sixty G.

882
00:44:47,840 --> 00:44:48,680
Speaker 5: My grades mattered.

883
00:44:48,719 --> 00:44:50,759
Speaker 8: My grades at Harvard Busines School, my grades at Harvard,

884
00:44:50,760 --> 00:44:54,160
Speaker 8: they both mattered a lot. And I worked so hard,

885
00:44:54,480 --> 00:44:56,279
Speaker 8: and I did ask do they work the.

886
00:44:56,280 --> 00:44:59,239
Speaker 2: Same hard today that you lived at HBS.

887
00:44:59,320 --> 00:45:01,040
Speaker 5: I don't know. I don't know because I'm not.

888
00:45:02,000 --> 00:45:04,239
Speaker 2: I've asked these kids get through Michael.

889
00:45:03,960 --> 00:45:07,960
Speaker 8: Porter at HBS right now. I got to believe it

890
00:45:08,040 --> 00:45:10,360
Speaker 8: they can. I mean, I don't know because I'm not

891
00:45:10,400 --> 00:45:12,439
Speaker 8: in that classroom. I ask my friends there.

892
00:45:12,440 --> 00:45:16,319
Speaker 4: Here's what my friend, this Bloomberg LP is managed by

893
00:45:16,320 --> 00:45:18,799
Speaker 4: twenty and thirty somethings, So we're the outliers.

894
00:45:18,880 --> 00:45:19,879
Speaker 7: Yeah, and the.

895
00:45:19,920 --> 00:45:23,279
Speaker 4: Smartest people running these businesses are to me kids. But

896
00:45:23,360 --> 00:45:26,880
Speaker 4: they're so smart, they're so driven, they're so creative. I

897
00:45:26,960 --> 00:45:29,520
Speaker 4: hired a bunch of them from boom Bloombir Intelligence.

898
00:45:29,560 --> 00:45:31,239
Speaker 2: Yes, yeah, I'm not.

899
00:45:31,360 --> 00:45:33,400
Speaker 4: I'm fine. I'm comfortable with this.

900
00:45:33,520 --> 00:45:34,319
Speaker 5: The kids are all right.

901
00:45:34,360 --> 00:45:37,080
Speaker 2: The kids are all right. One final question of twenty seconds,

902
00:45:37,160 --> 00:45:38,520
Speaker 2: how much hate mail have you gotten?

903
00:45:40,440 --> 00:45:43,560
Speaker 5: It's a good portion of it. I have to say.

904
00:45:43,600 --> 00:45:45,360
Speaker 5: You know, people always like to kill the messenger.

905
00:45:45,480 --> 00:45:47,360
Speaker 8: And you know, it's as if I stood up and

906
00:45:47,400 --> 00:45:50,719
Speaker 8: said gen Z is unemployable at me and they did.

907
00:45:52,040 --> 00:45:56,319
Speaker 2: What you've done is phenomenal. Susie Welch, thank you so much.

908
00:45:56,400 --> 00:45:59,960
Speaker 2: My essay of the year is gen Z Unemployed.

909
00:46:01,080 --> 00:46:05,920
Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify,

910
00:46:06,040 --> 00:46:09,839
Speaker 1: and anywhere else you get your podcasts. Listen live each

911
00:46:09,880 --> 00:46:13,719
Speaker 1: weekday seven to ten am Eastern on Bloomberg dot com,

912
00:46:13,840 --> 00:46:17,640
Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app.

913
00:46:17,960 --> 00:46:21,080
Speaker 1: You can also watch us live every weekday on YouTube

914
00:46:21,360 --> 00:46:23,360
Speaker 1: and always on the Bloomberg terminal.