Episode 233

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Published on:

28th Jun 2023

Exploring the US Economy with Michael Brown

This week on the podcast Matt sits down with Michael Brown, Principal US Economist for Visa and member of the Walton College’s Dean’s Executive Advisory Board. They begin the conversation with Michael sharing how he got interested in economics during his undergraduate studies at the University of Arkansas, what he does in his role at Visa in the macroeconomic space and how he synthesizes so much data down to communicate it to their clients. They go on to discuss the methods of forecasting the US economy and also the challenges and trade offs associated with short term versus medium term versus long term predictions. They also touch on the most challenging pieces to forecast. They end the discussion with a focus on supply chain and the macro picture of the economy as well as some medium to long run trends on the consumer side of the economy that Michael sees coming up.

Transcript
Michael Brown:

Whether it is the invasion of Ukraine, whether it

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is COVID restrictions in China, every single one of those policy

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actions, physical actions has global ramifications, not just

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for the global economy, but for on the ground, individual

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business owners who are trying to manage through that lack of

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clarity.

Matt Waller:

Excellence, professionalism, innovation, and

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collegiality. These are the values the Sam M. Walton College

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of Business explores in education, business and the

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lives of people we meet every day, I'm Matt Waller, Dean of

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the Walton College, and welcome to the be epic podcast. I have

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with me today, Michael Brown, who's principal US Economist at

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Visa. And Michael received his undergraduate degree from the

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Walton College and his Master's of Arts degree in economics from

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the Walton College. And he is currently on my Executive

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Advisory Board. Michael, thank you so much for joining me

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today.

Michael Brown:

Great to be here, Matt.

Matt Waller:

So, Michael, you've really been in economics your

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whole career and you studied economics as a student. Would

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you mind just sharing a little bit about how you got interested

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in economics?

Michael Brown:

Sure. Yeah, I guess it all started as an

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undergraduate at the Walton College, you know, I was taking,

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I believe the intermediate level courses. And it was really micro

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that was fascinating to me. So the application of mathematics

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to business problems, was intriguing to me. And I kind of

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stayed down that path for a while, partnered with a

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professor at the time by the name of Cary Deck, who was a

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very inspirational person in my career track. And Cary was

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adamant that the research really helped us understand business

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problems in an applied sense. And Cary was an experimental and

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behavioral economist. And that was also quite fascinating. I

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have a minor in Psychology also, from the University of Arkansas

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there and blending those two passions, I thought was a

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natural intersection to do micro.

Matt Waller:

Michael, of course, I've heard your presentations,

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and I followed, I followed your career. And it's really

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impressive, the knowledge you've gained, of course, you've been

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with Visa for almost five years. And prior to that you were vice

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president and economist at Wells Fargo for over eight years, and

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you've had other experiences as well. But would you mind telling

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us a little bit about what you do as principal US economist for

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Visa?

Michael Brown:

Sure. Well, it's a far cry from that micro

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undergrad student that I described to you just a moment

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ago. You know, the reality is I spend a lot of my time focused

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on developments in the macro economy, there is some

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behavioral aspects of what we do in terms of understanding shifts

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in consumer confidence and psychology, and how that may

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impact consumption patterns. But more broadly, if I had to divide

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up kind of my time into a pie chart, if you will, I'm an

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economist, I love charts, right? So, you know, you divide the

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time up, I'd say about 70% of my time, is focused on interfacing

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with our clients and communicating the work that's

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done here in the office by our incredibly talented team of

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analysts, economists and data scientists distilling that down

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into an easily digestible format for CEOs CFOs, and senior

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leaders across our clients, which include banks, large

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merchants, you know, there's fintechs are kind of in the

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fold, and big tech companies today, as they're starting to

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wade into the payments ecosystem. So a lot of what I do

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is information, distilling, and presentation. Still have the

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hard skills, though, you know, just this morning, we were

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designing a new round of forecast models. So still

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heavily involved in econometric design as well, as you know, we

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do some academic work here as well to keep us fresh on some of

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the new and innovative techniques out there in both

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economic forecasting, but also sort of pushing the envelope

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with broader economic research topics.

Matt Waller:

Well, I could imagine that it's probably hard

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to find people that fit into your profile, because a lot of

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times people that are real strong in econometrics tend to

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be you know, focused on math and maybe more introverted. Clearly

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one of yours strengths is communication, but also that

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synthesis skill. Anytime you've got a lot of different analyses,

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especially when they may be pointing in different

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directions, trying to synthesize it in a way that people can

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understand and relate to and then make decisions upon isn't

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easy. How did you learn to do the synthesis and communication

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pieces?

Michael Brown:

That just came with, with experience, you know,

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my first job out of graduate school, is actually at the

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Arkansas Federal Assembly. And I served as kind of a policy

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analyst and, you know, very research focused from the

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beginning. But then, you know, you complete a research project,

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and then you're often called upon to testify in a committee,

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or, you know, in front of, you know, other members of the

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legislature. And that was when I learned fairly quickly that, you

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know, distilling things down to their constituent components,

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and then trying to communicate, just the essentials, was sort of

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core to it. So that was really an enlightening experience,

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having to take a often 40, 50 page research document, distill

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it down into 10, 15 minutes of testimony, just going through

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that process was very challenging at first, I'll

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admit. When I moved to Wells Fargo, the story changed, right,

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it was all about, we have a literally like telling a story

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of the economy, and its facets and its developments and its

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nuances and turning points, and then trying to convey that in

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not just an informative way. But frankly, in a way that's going

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to connect with the audience that you're in front of. So for

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example, you know, if you're talking to a hedge fund, you can

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be a little more technical and a little more rigorous. If you're

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talking to CFOs of middle market clients or midsize companies,

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that takes a different approach. So that's when the skill set of

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adapting communication styles came into it. And now it's more

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a function of okay, now we're speaking mostly to CEOs and

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CFOs, you kind of have a boilerplate that you can

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navigate.

Matt Waller:

Well, I know you've done a lot of forecasting of the

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US economy. And that's so hard to do. Would you talk a little

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bit about methods of forecasting the US economy and also the

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challenges and trade offs associated with short term

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versus medium term versus long term?

Michael Brown:

All phenomenal questions. So the first comment

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I would say is you need to be as humble as you possibly can be to

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be an economic forecast, a particularly in today's

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environment of if you think you're going to be right, the

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majority of the time you are you were mistaken yourself. And I

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learned this long ago, right. I mean, when I first started

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forecasting, at my time, at Wells Fargo, the most important

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aspect of doing it is coming up with a consistent storyline

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around what the data supports. And you know, the numbers that

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we come out of our models were often kind of ad factoring to

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make sure that that consistency is there in the message. And in

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the storyline, a macro forecast ranges anywhere between five to

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32 line items, we're forecasting about 32, here at Visa

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acurately. And those line items should all move consistent with

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that fabric of the story that you're telling. And sometimes

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the models aren't great at doing that as hard as you try as a as

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an a good econometrician. They're not always consistent,

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and particularly in a post COVID environment as we're in and

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trying to navigate now. So one be humble, two grounded in the

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macro theory, if you're not driven by the known principles

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and relationships, that, frankly, are our guiding

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principles. It's the reason we're economists and not data

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scientist, is we're using that framework of macro theory to

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guide our thinking around that storyline development. And then

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finally communicating it in a clear and concise manner that,

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you know, has its footnotes attached, as I like to say, but

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you're still, you know, accentuating it with with just

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the,

Matt Waller:

Well, you know, when you talk about all these

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different items you're forecasting, what are what are

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some of them, you're you're forecasting and which ones are

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the most challenging?

Michael Brown:

Well, so the top line, I mean, the biggest thing

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everyone looks at is US GDP growth, right? So we, we don't

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even refer to it as GDP when we're talking to clients. We

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just say economic growth, you know, again, we're trying to get

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out of the realm of, you know, teaching undergrad econ as part

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of our updates to our executives, certainly inflation.

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Here at Visa a big part of our business is obviously consumer

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spending. So for example, we look at both real spending,

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which tells us how much foot traffic, they go through our

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merchants. But we also look at nominal spending, which is going

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to correspond with revenues. So again, taking, you know, the the

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inflation piece, adding it to the real or inflation adjusted

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variables. All of these are kind of key inputs into not just our

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business, but our clients business as well. The great

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thing about our business model here at Visa is when our clients

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do well, we do well, it's also so you know, it's it's kind of

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interesting to come in and provide these additional

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perspectives. Now, the hard part, I would say, you know,

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interest rates are up there with some of the more difficult line

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items to kind of forecast oil prices. Oftentimes, I will

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consult a ouija board rather than a forecast model. I mean,

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it is really difficult to kind of forecast it. And in the third

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bucket, I would say is anything that would involve political

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calculations versus economic fundamentals. So for example,

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you know, the the hot topic these days is the federal budget

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and of course, debt ceiling debates, that is inherently a

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political decision. And I learned a long time ago, let's

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stick to the economics, we'll let the political forecasting to

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the political scientists because it gets really tricky, very

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quickly to try to figure out the direction of those kinds of

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variables.

Matt Waller:

Your point about, you know, trying to come up with

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the story that weaves everything together, where the forecasts of

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each of the lines makes sense together. Because you would

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expect certain things to react in certain ways, under certain

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circumstances, based on theory, but that gets into something

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really interesting, which is the short run versus the long run.

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Because even if your story's right, because of the stochastic

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nature of the variables, the short term forecasts could just

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have some noise in them that make the make it inconsistent

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with the story.

Michael Brown:

You're absolutely right, I mean, you know, we

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actually divide our time up. Usually, the mornings of our

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day, are really focused on the short term, macro fluctuations.

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And for better or worse, the bulk of our client base is

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really keyed in and dialed in to that short run view. That said,

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your eye isn't on the long run ball, some, you're gonna miss a

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lot. And so the afternoons here, are really us jumping into our

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huddle rooms, or our little side chat rooms. And kicking around

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these longer run themes. We spend a lot of time talking

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about the implications of Gen Z, on productivity, growth, and

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technological adoption, you know, the trends that are going

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to shift across demographic groups, but also what a large

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and growing retirement base means for the potential GDP

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growth of the US. And all of these things, if you're doing

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any kind of medium to long run planning are essential to kind

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of inform clients of as well. So it's not just demographics. I

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mean, we go back again, to macro principles, right? We're talking

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about productivity growth technology, or, you know, labor

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augmenting technology in that production function. And then

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capital flows globally. And all of that feeds into kind of our

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medium to long run perspective. But it's all grounded in those

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simple production functions that we all learned, you know, as

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undergrad and grad students.

Matt Waller:

Michael, there's economists in a lot of different

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industries, I would think you have a little bit of an

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advantage, because any economist has access to archival data, you

Matt Waller:

also have access to payment, and data.

Michael Brown:

We do I mean, you know, in terms of our payment

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volumes, we roughly see close to 25 cents of every dollar spent

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here in the United States. And that's about, you know,

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somewhere around 21 to 22 cents globally. So it's, it's a fairly

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large penetration rate. And it does allow us to get a pretty

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high degree of visibility into the consumer side. But you know,

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we also have small business cards and commercial cards as

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well. So we are able to gather intelligence on multiple facets

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of the US economy through the lens of of our card payment

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data. But I would say that there's also challenges with

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that, you know, I mean, I'm sure your students are learning about

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big data there at the Walton College in excruciating detail.

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It has a tremendous amount of noise associated with it. And as

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an economist, you know, it's a little funny to say working for

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a business. But there's a lot of what I call business noise in

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our big data. So I'll give you an example. Let's say we have a

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bank that was issuing a competitor's product and they

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convert to issuing Visa. Well, that was economic activity that

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was going on before we could see that in our big data set. And

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we've got to figure out ways, creative ways, that control for

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that. And we've got folks migrating in and out of our

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ecosystem daily, right. So it would be impossible to trace

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down every single, inbound and outbound kind of transaction,

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when we're talking, you know, millions and millions a day. So

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we've come up with clever ways, thanks to our talented data

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scientists to kind of scrub the big data and extract what I call

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the economic signal from from the big data and make it a

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useful economic measure. So yes, there are a lot of advantages,

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but there's also a tremendous amount of sort of data cleaning,

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and then it, then there's, then there's the sort of balance

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issue that we're always struggling with as particularly

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in our profession, as Applied Business economists, because

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you're right, we have a lot of insider information. And as a

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publicly traded company, we have to protect a lot of that

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information. I would love nothing more than to start

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publishing forecasts based off of what I saw two days ago in

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our transactions data. But that would end up front running our

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forward guidance, our executive team, our financials. So there's

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a business ethics angle to this as well, that we have to be

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very, very cognizant of. With that big data, we also have a

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big level of responsibility to protect the confidentiality of

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some of that data as well.

Matt Waller:

I know that, under your leadership, Bloomberg News

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ranked Visa's US economics team as among the top forecasters of

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the US economy. How how did you lead your team to that

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achievement? What what did you have to do?

Michael Brown:

First, you know, I'll just kind of walk you

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through how we onboard our our economist here. And phase one is

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really the indoctrination of our approach to econometrics. And

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basically, systems thinking, for me to think about the economy as

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a system? And what are what are the things that could break the

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system? What are the things that can make the system run faster?

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What are the levers we could pull to, to perhaps make the

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system run more efficiently, so you start thinking of it as a

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system. And we basically, to divert it a little bit, as I

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like to say, we basically apply that thought process to our

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econometric structures and models. So we have, we use

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machine learning techniques, such as Bayesian vector auto

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regressions, and other types of applied techniques as well, that

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will take both public and proprietary economic data that

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we subscribe to feed that through our systems of

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equations. And that helps us understand the co-movements

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between things. But again, we also have a lot of experience

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here. I mean, get off get to a team with close to 90 years of

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combined experience, you know, forecasting and understanding

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the economy. And that's invaluable, having folks that

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have lived through different types of recessions have seen

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data develop in different ways. And probably the death kill of

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an economist is have seen the magnitudes of the revisions that

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can come with some of the data that we rely on heavily to find

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turning points in the economy. And all of that just kind of

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gels. I think probably the most rewarding moment of my months,

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is sitting in a forecast, which we have the first Friday of

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every month after the Non Farm Payroll report comes out. And we

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sit there and everybody goes around the room. And they they

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talk about what what they think is right what they think is

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wrong, and there is no hierarchy in that room. Everyone's idea

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matters. Everyone's thought matters. Everyone's research

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matters when it comes to that. And creating that flat

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structure. In that one meeting that sets the tone for what

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we're going to say, for the next 30 to 60 days is is incredibly

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important as a leader to make sure that you're creating that

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inclusive environment, a free flow of ideas, particularly in a

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research function like we serve. So just setting up the

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environment and setting the team up for success in their

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endeavors as an applied econometrician as well.

Matt Waller:

So you must have had to build a lot of trust to

Matt Waller:

get that to happen. Because it's easy to say. But when you get

Matt Waller:

that many people into a room, it's there's a lot of

Matt Waller:

complicated sociological and political issues that go into

Matt Waller:

it. So how did you build the trust?

Michael Brown:

Well, so one of the sort of foundations of my

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management style is I really am important, I really place a lot

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of emphasis on one on one conversations. So every single

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week, whether I'm traveling or not, it may be 15 minutes that

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week, or sometimes it's an hour, and I'm sitting down with each

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member of the team, and understanding what's working,

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what's not working, helping them set priorities, and knowing that

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I have their back when they can't get to priority number

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five on that list, is also an important aspect of kind of

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managing workflow. And I think probably another dimension to it

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is really listening more than you're talking, you know, those

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one on one conversations, if I leave the room, feeling like I

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spoke more than 30% of the time, I think I walk away saying I

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probably did something wrong. And I need to kind of reassess

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and reevaluate my approach the next time.

Matt Waller:

Well, congratulations on your terrific

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achievement there. One shifting gears just a little bit. You

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know, throughout history, there are these shocks that occur to

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economies I, the biggest one, of course, COVID, that's the most

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memorable, had an incredible impact in so many different

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ways. It's hard to even conceive of all these changes. And you

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know, you could think and we would be, we have to bring up

Matt Waller:

generative AI. But I wonder, is generative AI, a shock? That, I

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mean, maybe we're not seeing it yet, but I know, I know, so many

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alumni in various industries that are telling me really

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innovative ways that they're using it. But even in the

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university, we're finding ways of using it that are quite

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remarkable, that truly make us more efficient. But what are

Matt Waller:

your thoughts? Do you think? Do you think this is going to be a

Matt Waller:

shock?

Michael Brown:

Shock might be a little strong of a word. I, as

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an economist, I go back to first principles. And I think the

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power of what you described is really the augmentation of

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labor. And if you think about the long run trends here in the

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US, we're in a country with an aging population, slow net in

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migration, slow year on year population growth. The key story

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in macro economics today is the high rates of inflation. So how

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do you bring that down? Well, in light of not being able to grow

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your labor force, you bring that down through enhancing your

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existing labor force. And so I'm kind of a glass half full kind

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of guy on this, because I think the power to enhance the

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abilities of the human capital that we have in this country and

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others around the world, I think it's going to be an unlock of

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potentially higher GDP growth than we otherwise would have had

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in the absence of this kind of innovation and technology. Now,

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that said, I don't think we're ready to just run full steam

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ahead. I'll just give you the example here at Visa, it is

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prohibited on our systems to use chat GPT or other generative AI

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tools. And the reason is that the fear of putting in something

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that is company proprietary into that ecosystem and having it

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uploaded into a public database for other future consumption,

Michael Brown:

maybe to answer other questions out there. That risk of

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intellectual property CPG or loss is really high.

Matt Waller:

Yeah, that's a really good point. The World

Matt Waller:

Wide Web was similar. When it was created, many companies

Matt Waller:

banned it because it was so easy for information to flow outside

Matt Waller:

through the World Wide Web. So Michael, it's funny prior to the

Matt Waller:

pandemic, no one very few people knew what Supply Chain

Matt Waller:

Management was and Logistics was a term they didn't really use

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much. And during the pandemic, it was on the front page every

Matt Waller:

day and now people know about it. It's amazing. And of course,

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as you know, our undergraduate program in supply chain is now

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ranked number one in North America by Gartner. And the

Matt Waller:

Masters program is ranked number two in North America by Gartner

Matt Waller:

which we're very grateful for. But would you mind speaking

Matt Waller:

little bit to supply chain the macro picture of the economy?

Michael Brown:

Well, it's interesting, I'll take you back

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to one of my trips to Southern California, I was flying from

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San Diego back here to the San Francisco Bay Area. And this was

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early in 2021. So February, March kind of timeframe. And I

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remember flying over the Port of Long Beach, looking at all the

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vessels lined up. And that was the clearest visual

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representation of the public economic data. And what I would

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say is, it was incredible the amount of tug and pull on US GDP

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growth that we saw from the collapse of inventory, the

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rebuilding of inventory. You know, I rarely talk about an

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esoteric concept we call real final sales to private domestic

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purchasers, essentially, its core GDP growth, right? How are

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consumers, businesses and government spending and

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investing? But I had to talk about that measure, because the

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inventory cycle was so inconsistent with core demand in

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the economy, they were so out of sync for so long, that you, it

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was sending false signals about the strength or weakness of the

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economy, depending on the quarter. So that was an

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incredible time, where one we learned just how globally

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interconnected the world is, and how, when we're doing better,

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and everybody else is doing better, it uplifts us all.

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Because, whether it is the invasion of Ukraine, whether it

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is COVID restrictions in China, every single one of those policy

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actions, physical actions has global ramifications, not just

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for the global economy, but for on the ground individual

Michael Brown:

business owners who are trying to manage through that lack of

Michael Brown:

clarity. So I think the scarring of what we went through with

Michael Brown:

supply chain is going to be with us for a while, and it's gonna

Michael Brown:

have some very important implications for business

Michael Brown:

management going forward.

Matt Waller:

Michael, I know you've done extensive research

Matt Waller:

on the consumer side of the economy. Would you mind talking

Matt Waller:

a little bit about some of the medium to long run trends that

Matt Waller:

you're seeing on the consumer side?

Michael Brown:

Well, I think there's probably two broad

Michael Brown:

buckets. One is kind of the demographic shifts. And right

Michael Brown:

now we're in this phase where a boomers are kind of moving into

Michael Brown:

their retirement years, they're leaving the labor force,

Michael Brown:

frankly, post pandemic a little bit earlier than we had

Michael Brown:

anticipated. And that starts having some profound impacts on

Michael Brown:

aggregate consumption. And I'll give you one example. In

Michael Brown:

economics and macro, we talked a little bit about this concept of

Michael Brown:

the wealth effect. So as one's value of its of their home, or

Michael Brown:

their stock portfolio rises, there is some knock on effect on

Michael Brown:

aggregate consumption. And historically, you know, if you

Michael Brown:

look at the economic literature, it's been range bound. I mean,

Michael Brown:

depending on the studies you look at, it's between five cents

Michael Brown:

and 10 cents, meaning that for every dollar of wealth, that

Michael Brown:

increases, you tend to spend about five cents or 10 cents.

Michael Brown:

Now some of this is psychological, right, I feel

Michael Brown:

better about my financial situation. And therefore, I can

Michael Brown:

go out and spend a little bit more. But what we're seeing is

Michael Brown:

this wealth effect, as we measure it, has now grown to

Michael Brown:

roughly around 34 cents. So it's a profound shift in the

Michael Brown:

deviation from what we've seen over the last decade and a half.

Michael Brown:

And the reason that's so important is because you start

Michael Brown:

putting the pieces together, we accumulated a tremendous amount

Michael Brown:

of housing and financial wealth over the last five years as an

Michael Brown:

economy. The second key aspect is we are much more sensitive to

Michael Brown:

changes in stock markets today than we were, say, 20 years ago.

Michael Brown:

The third piece, as I mentioned, is you look at the share of the

Michael Brown:

population over the age of 55, who has retired early, it's

Michael Brown:

incredible post pandemic. And so it makes some sense that this

Michael Brown:

wealth effect and wealth accumulation is having some

Michael Brown:

impact as well. So that's a big trend that we're looking at for

Michael Brown:

the next five years as the retirements continue to

Michael Brown:

accelerate in the coming years. And so I think what we're about

Michael Brown:

to see over the next 10 years is the evolution of working at just

Michael Brown:

a tech company to that permeating multiple other

Michael Brown:

sectors of the economy. And you're already seeing this in

Michael Brown:

financial services with automated trading and trying to

Michael Brown:

enhance productivity, and that's that sector. And I think, you

Michael Brown:

know, we're just now seeing the tip of the iceberg as this tech

Michael Brown:

stack moves from Silicon Valley, as I like to say out to the rest

Michael Brown:

of the country, to kind of permeate some of these

Michael Brown:

industries and that enables purchasing power of consumers in

Michael Brown:

a whole new way. Any new markets that I think we're just now

Michael Brown:

starting to get a handle?

Matt Waller:

Well, Michael, this has been really interesting.

Matt Waller:

Congratulations on your tremendous success in your

Matt Waller:

career and for taking time to visit with me about this. I

Matt Waller:

really appreciate it.

Michael Brown:

It's been fun Matt, always great chatting with

Michael Brown:

you and very, very pleased to always support the Walton

Michael Brown:

College here as well.

Matt Waller:

On behalf of the Sam M Walton College of

Matt Waller:

Business, I want to thank everyone for spending time with

Matt Waller:

us for another engaging conversation. You can subscribe

Matt Waller:

by going to your favorite podcast service and searching.

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About the Podcast

Be EPIC Podcast
Welcome to the Be Epic Podcast featuring Brent Williams, interim dean of the Sam M. Walton College of Business at the University of Arkansas. In each episode, you will hear from guests that will inspire you to be epic. As experts in their field, they will emphasize strategy, leadership, and entrepreneurship. This programming will highlight innovation and cutting-edge information that will leave you wanting more. Be sure to connect with Brent Williams on LinkedIn to join the conversation, access show notes and discover fantastic bonus content.