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Jonathan Levin

Jonathan Levin

President of Stanford University

Oct 16, 2026

4:33
Cuéntanos un poco más sobre eso.
4:35
En los años 2000, principios de 2000, la Fed tuvo un problema.
4:41
Las tasas ya estaban muy bajas después de los choques del 11 de septiembre y todo, y el banco central realmente no podría bajar mucho más la tasa de interés, pero los bonos no estaban respondiendo.
4:55
Así que la Reserva Federal empieza a caer bajo la influencia de Michael Woodford y empieza a explorar cómo pueden manipular las expectativas de los mercados y de los hogares para conseguir sus objetivos.
5:11
Y fue en ese entonces que Alan Greenspan, apenas meses después de un documento, una publicación muy importante de Michael Woodford, Greenspan sale con un comunicado revolucionario diciendo básicamente: las tasas de interés se van a quedar donde están por un buen rato.
5:31
Y eso sí ayudó, aunque sea brevemente, a bajar las tasas de interés, los yields de los bonos a diez años, por ejemplo, que son tan fundamentales para las hipotecas en Estados Unidos y muchos otros tipos de bonos.
5:47
Y con la Fed de ahora, ¿cuál es la justificación de Kevin Warsh para comunicar menos? ¿Y hay algo que se pueda rescatar de esa estrategia?
5:54
estrategia?Lo que pasa con Warsh es que él está respondiendo de la experiencia de 2021 y la Fed de Jerome Powell en ese entonces estaba usando bastante forward guidance, como le llaman, para efectivamente bajar los yields de los bonos durante la pandemia.
24:47
intelligenceW- w- w- the Microsoft part of this, why, why is it that Napster needs to go through Microsoft and Azure to do this? Explain the deal essentially.
24:58
Well, I mean, in essence, uh, there are many companies that are partners obviously with, uh, Microsoft.
25:04
And, uh, we saw an opportunity to sort of continue to sit and work with all the large language models with our, uh, with our agent.
25:13
And, uh, quite frankly, Microsoft was the best partner, uh, for us at this point to really make sure that our customers own the data, own th- own their own customers, own their experience, um, uh, and really own their models, and I think that's the path that we saw Microsoft on.
29:54
So you don't have any serious outlay on your own compute capacity, essentially.
30:00
Well, exactly.
30:01
Our agents, uh, uh, uh, sit on top of all models, so we're really, uh, quite frankly, um, um, the interface, um, what, what c- our customers would use to have an interface with a customer.
30:17
Um, and so it, it's super important, uh, that we keep our, our focus on how our customers can have the best interaction with their customers, uh, and really pivot the discussion away from cutting costs and how AI displaces folks and really sort of pivoting the conversation to how we can learn through these online interactions, for example, why 90% of people aren't buying from your website, and start to figure out how AI can be a tool to the blue sky side of the equation.
24:36
The modern theory of utility makes no attempt to explain choice behavior." So John, what exactly is utility and why does it matter? [chuckles]
24:46
You're asking, Rae, that you're, you're getting into a very deep problem in, in economics, which is why do people make certain choices? That's the foundation of, you know, really all of economics and the foundation of game theory, 'cause game theory you're in a strategic setting, you gotta decide, uh, what to do and, um, what are your motivations.
25:02
And economics is not the only discipline that looks at that.
25:05
Psychology and philosophy look at those questions as well.
25:09
I always taught ...
25:09
When I taught first year economics, I, you know, I always would, would try to talk to people about the sort of caricature version of economics where you sort of specify a, a, a preference as utility function that's very material.
25:24
People are trying to achieve material ends.

10 MINS LATER

35:46
Do you think that's accurate?
39:02
Can he follow the same playbook?
39:05
Yeah, uh, the point of my column, uh, on Greenspan is, is like, look, it's obviously very tempting to draw parallels between AI and the internet era.
39:14
And of course, Greenspan's famous call in the late '90s was, uh, letting the economy sort of, sort of run because, uh, he thought, you know, incipient productivity was so strong, we, you know, we didn't have to worry too much about inflation.
39:28
My argument is, is that beyond those ostensible similarities, there are a lot of differences.
39:34
So, uh, you know, take for instance, the fact that, uh, you know, Greenspan had demographics on, on his side, the great moderation.
39:44
Uh, he, uh, you know, enjoyed a long period of relatively low and stable energy prices.
39:50
Obviously, that's not at all similar [laughs] uh, to the world we're living in today.
40:24
Is Chairman Warsh, is he gonna get a victory lap on productivity?
Paola Vega Torre
Paola Vega TorreCORRESPONDENT
4:00
Jon, después de tanto entusiasmo, ¿cómo interpretamos la volatilidad de las acciones de SpaceX?
4:06
Parte de esto ya se veía venir.
4:09
Lo que pasó en los últimos quince años deja claro que los mega IPO no suelen ser tan buena inversión.
4:16
Generan tanto entusiasmo y salen a bolsa con valuaciones tan disparatadas que muchas veces ni siquiera le ganan al S&P 500 en los primeros uno a tres años.
4:26
En el fondo, nada ha cambiado para SpaceX, salvo dos cosas.
4:31
Primero, ya le estás agregando un montón de deuda a la estructura de capital.
4:36
Y dos, al resto del mercado le ha ido mal.
Paola Vega Torre
Paola Vega TorreCORRESPONDENT
4:57
¿Por qué está pasando eso?
2:54
Thanks, everyone, for coming.
2:56
Really appreciate you doing this.
2:58
Um, so we're gonna-- I'm gonna ask you some questions.
3:00
We'll have some questions from, uh, from students, and, uh, l- looking forward to, to hearing your thoughts.
3:07
Um, maybe we would-- You've been chronicled a lot recently, a movie, a, a, a book.
3:14
So some-- many people have, have heard about your, your trajectory.
3:19
It is quite remarkable.

14 MINS LATER

17:32
Mm-hmm.
45:31
Is that right? Yeah.
45:32
I would say so.
45:33
I mean, you look at the investors that are coming to our event.
45:37
They're the institutional investors.
45:39
So the equivalent of the superannuation funds who invest in the sector.
45:43
But now look at those pension funds, institutional wealth managers, the institutional financial endowments and funds that exist throughout the world, as well as family offices and high net worth individuals.
46:00
These are folks that are investing generationally in the land and have seen it produce over time.
PhilAUDIENCE
49:37
Yeah.
1:40
Is that right? Yeah.
1:41
I would say so.
1:42
I mean, you look at the investors that are coming to our event.
1:46
They're the institutional investors.
1:47
So the equivalent of the superannuation funds who invest in the sector.
1:52
But now look at those pension funds, institutional wealth managers, the investors.
1:59
the institutional financial endowments and funds that exist throughout the world, as well as family offices and high net worth individuals.
5:45
Yeah.
3:27
Acá nos explica por qué valdría la pena esperar un poco.
3:33
Lo que digo en mi columna de esta semana es que obviamente es una empresa impresionante.
3:39
O sea, la tecnología que tienen en términos de lanzar satélites y llegar a nuevos planetas.
3:46
O sea, no existe otra compañía como esta.
3:50
Y yo digo que eventualmente vas a querer tener esta compañía en tu portafolio.
3:55
Pero las valuaciones son francamente un poco ridículas.
4:00
O sea...
5:42
¿Qué opinas al respecto?
17:40
Why don't you quickly just share your story? How, how did you, uh, co-found Chainalysis?
17:45
Yeah, I, I really fell into crypto, and actually, you know, I'm maybe a couple of hundred meters from when I first really got my break in cryptocurrency.
17:56
I was, uh, sitting at the Yerba Buena Center right next door to Moscone, and I was speaking about cryptocurrency in 2014 at the first CoinSummit conference.
18:07
And, uh, at that stage, I was doing the economics of cryptocurrency.
18:14
I was researching, I was writing the early game theory work and empirical work on how does-... blockchain work as a payment system? How can it be that we can have this decentralized money system that's a public good? And from there, I realized as I was looking at that data, there needed to be someone who actually understands how and why people are using cryptocurrency if this is ever gonna be a big market.
18:41
And I met my co-founders at Chainalysis, who were just starting to actually investigate the same type of problem.
18:48
And the three of us got together and we said, "You know, we need to be the people that create this map between the real world and the blockchain transactions." And it just happened to be that the first use case for that was criminal investigations that involved cryptocurrency that was stolen from other people, or being used on the dark web to facilitate, you know, drug trafficking or, or child exploitation.
19:25
So where does it go from here? Uh, particularly with quantum computing on the horizon and-
3:08
And then the second part is we actually had some, uh, local families who, uh, some of whose kids, all of who had been counseled on tracheostomy, some of whose kids ended up with a tracheostomy tube, and then, uh, another one who, who did not ex- uh, go through their experience as well.
3:22
It was really cool because the audience was like a focus group, so we asked them about cases, and there was a lot of variability in their opinions on whether they would recommend, how likely they were to recommend tracheostomy at different time points.
3:35
And so we wanted to get a, a sense of, you know, with this baseline information, what is the current state across the nation for, um, counseling.
3:46
And then when you add on different comorbidities, like if you have pulmonary hypertension, how does that change your conversation? How does that change your counseling?
speaker_0ADVERTISER
4:56
Mm-hmm
4:56
... post-menstrual age side.
4:57
But if you are in a place that doesn't have those, it was gonna require ongoing hospitalization, then you may give the patient more time.
5:04
But what came up over and over again was the family being a huge partner in all of this.
3:36
¿Pero son realmente oportunidades únicas o una señal de advertencia? Hoy conversamos con Jonathan Levin, columnista de Bloomberg Opinion, sobre qué dice la historia y los datos acerca de estos momentos de euforia financiera.
3:51
Efectivamente, los datos son muy claros.
3:54
Los retornos más extraordinarios ya se ganaron antes del primer día de cotización en muchos de estos gran IPOs de la última década.
4:04
Así que la historia aconseja precaución, no euforia.
4:09
Todo el mundo está muy emocionado por estas tres ofertas públicas que vienen tal vez este año.
4:15
Anthropic, OpenAI, de ChatGPT y SpaceX.
4:20
Y la verdad es que las valuaciones ya han subido bastante en los mercados privados.
6:24
Explícanos un poco más.
3:19
Acá nos dice por qué nunca estuvo del todo convencido de que el Sell America duraría.
3:26
Hay que empezar con qué es la narrativa de que los inversionistas estaban vendiendo a Estados Unidos.
3:33
Y esta narrativa surge como una manera de explicar la caída coordinada de los activos estadounidenses al principio del gobierno de Trump.
3:42
Y desde entonces nadie ha dejado de hablar de esta narrativa que le llaman el Sell America Trade en inglés.
3:51
Pero al final de cuentas era una narrativa falsa desde mi punto de vista.
3:55
Demasiado simplista, algo que suena bien, pero no tiene fundamento.
4:00
¿Por qué? Bueno, para empezar, en las últimas dos semanas, el mundo ha sufrido un shock en forma de la guerra en Irán.
4:56
Explícanos un poco más.
Paola Vega Torre
Paola Vega TorreCORRESPONDENT
5:28
¿En realidad han ayudado a bajar los precios y reducir el déficit comercial o han generado nuevos problemas?
5:35
Es complicado.
5:36
Yo diría nuevos problemas.
5:38
Técnicamente la inflación es más lenta.
5:42
Tal vez eso no es lo que uno pensaría.
5:45
La inflación está en 2.4% y cuando Trump entró estaba en 3%.
5:51
Así que técnicamente eso parece ser un poco mejor, pero hay que considerar el contrafactual.
Paola Vega Torre
Paola Vega TorreCORRESPONDENT
6:22
estrategia económica actual de Trump?
4:49
¿Por qué Walsh es visto como hawkish con este tema en particular?
4:54
Walsh empezó su carrera en la política monetaria en 2006 y estaba en la Reserva Federal cuando se desató la crisis financiera.
5:05
Y bajo Ben Bernanke, la Reserva Federal empezó una política de comprar bonos en el mercado abierto para tener influencia sobre toda la curva.
5:20
de renta fija aquí en Estados Unidos.
5:23
Y en ese tiempo, Bush estaba constantemente preocupado que íbamos a desatar una nueva ronda de inflación.
5:33
Nunca pasó en ese tiempo.
5:35
Y en ese sentido nunca ha cambiado su mensaje.
6:16
¿Cuál es la lectura que haces de los últimos datos y el rumbo de tasas de interés?
3:09
Y acá nos explica más.
3:12
Este año los estrategas de Wall Street están más o menos optimistas en comparación con años pasados.
3:18
Están esperando una ganancia de alrededor de 11% en el S&P 500.
3:23
Pero...
3:27
El problema es que la historia demuestra que estas predicciones no son nada fiables, lamentablemente.
3:35
O sea, en ocho de los últimos nueve años, estas predicciones han tenido un margen de error de doble dígitos.
3:46
O sea, estas predicciones son peor que malas, digamos.
4:14
¿Por qué?
11:05
I don't know if you can share details some you know, but as much as you can, what are some of the common scams that you're seeing that people are trying to do?
11:14
Oh, we love this.
11:16
So we love a good scam at Chain Analysis.
11:21
So there's lots of different scams that happen.
11:23
I mean, we obviously track the different types.
11:27
I would say that one that we're very familiar with is the investment scams that are popping up.
11:34
We screen really every single website that is created in the world every day.

17 MINS LATER

speaker_1ADVERTISER
29:02
Varies by state.
4:49
How are these policies affecting the labour market right now? Or what's the concern for local employers?
4:56
Yeah, well, a labor market, it's not exactly clear just yet, but I think we're seeing indications of this in the housing market.
5:04
For instance, people are more apprehensive about making long term decisions because they don't know what their status is going to be in the medium term.
5:13
Over the next few months, you have to start feeling the impacts because estimates from the likes of Morgan Stanley suggest that the net flows of immigrants, this is both documented and undocumented, are going to step down in just a huge way from 2024 to 2025.
5:31
The estimate is that we'll go from something on the order of a net 3 million all the way down to something on the order of a 0.3, 0.4 million.
5:41
So just from a flows standpoint, that's a massive change.
5:46
And it's something that's going to feel even more massive in immigrant heavy cities like the one that I live in.
10:34
I mean, there's just a lot of uncertainty about the policy.

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