The discourse presented by J Scott elucidates a critical examination of the prevailing economic landscape, particularly as it pertains to the intricacies of a "fracturing of our epistemic reality" within the 2026 economy. At the forefront of this analysis is Scott's contentious "Flat Housing" thesis, which posits that single-family home values are likely to experience stagnation rather than a catastrophic decline, remaining static until 2031 as inflation aligns with the historical trend line. This episode delves into the juxtaposition of headline indicators, such as GDP and unemployment rates, which suggest a flourishing economy, against the underlying data that reveals a more precarious situation for investors. Scott further expounds on the deflationary pressures exerted by artificial intelligence on the labor market, and he emphasizes the unique acquisition opportunities present in the multifamily apartment sector amid current market turbulence. Through rigorous examination, this dialogue equips listeners with the analytical frameworks necessary to navigate a complex and often misleading economic narrative.

Takeaways:

1. The economic landscape is complex, and relying solely on headline data can obscure underlying risks.
2. Jay Scott predicts a stagnation of single-family home values until 2031, contrary to expectations of a crash.
3. The rise of AI is creating deflationary pressures on labor, impacting economic stability and investment strategies.
4. Investors must consider a K-shaped economy, where asset owners thrive while wage earners struggle with increasing costs.
5. The podcast emphasizes the importance of analyzing multiple data points rather than trusting singular headlines for economic insights.
6. Current multifamily investment opportunities may present a rare acquisition window due to significant market corrections.

Links referenced in this episode:

1. jscott.com

I think a lot of people don't realize that there is so much data besides what we see in the headlines.

I think of economics and the economic landscape like a puzzle.

If I handed you a 5,000 piece puzzle and I gave you five pieces, you'd have no idea what that puzzle was, what the picture on the puzzle was.

If I handed you 100 pieces, you might start to get an idea of what the picture is.

If I gave you 1,000 pieces, you'd get a lot better.

Ideal.

I gave you all 5,000 pieces, you know exactly what that picture was.

And economics and economic data is the same thing.

If you look at two or three or four data points and there are some big ones, I mean things like inflation, gdp, unemployment, the things that consume the headlines, it may make you feel like you know, the bigger picture.

But the reality is it's only once you start looking at dozens or hundreds of pieces of data do you really get a good idea of the picture that's forming and foreign.

Welcome to Truly Passive Income.

I'm Neal Henderson.

And I'm Clint Harris.

And today's guest is Jay Scott.

Jay's a partner at Bar Down Investments where he and his team have acquired over a thousand multifamily units totaling more than 110 million in assets.

Over his 15 year real estate career, Jay has bought, built, rehab and held over 150 million in property across the country.

And also the author of five bigger Pockets book, including the bestselling the book on estimating rehab costs.

And co host the award winning Drunk real Estate podcast.

I have listened and watched both of those and they're both fantastic.

Jay has invested through multiple real estate cycles, built a reputation for helping investors think clearly when the economic noise is at its loudest.

He focuses less on predictions and more on reading the data that drives long term outcomes.

Jay, super excited to have you here today.

Thank you for your time.

We appreciate it.

How are you, sir?

I'm doing well.

I appreciate you, you guys having me.

This is going to be fun.

Absolutely.

Longtime listener, first time caller.

Jay, you're one of the guys that I, you know, you post a lot of stuff and I look at all of it and a lot of times it's very humorous but it's oftentimes also very insightful and you're a little bit of a, I consider you to be a self taught economic guru.

Tell me a little bit about your background and how you lean into a very data driven approach to everything you do.

So tell us a little bit about your mentality and then how you got to where you are.

Yeah, so I am a reformed engineer.

So my education is engineering.

I spent the first half of my career in Silicon Valley doing the tech thing.

Spent most of my career at Microsoft while I was in the business world.

In the tech world, I got my mba.

So that's kind of where a lot of my formal economic knowledge comes from.

How can I help lower risk, reduce variance, and kind of focus on being able to use those skills to help me specifically grow wealth?

Do you remember an inflection point that made you decide to make that switch?

Yeah, very simply, my wife and I decided to get married and we were both in our mid-30s.

We were, she was working, I mean, she was traveling three and a half weeks a month.

She was Meg Whitman's right hand woman at ebay.

So she was flying the corporate jet around the world for, for most of the time.

I was traveling a couple weeks a month between California and headquarters in Washington.

And so we never saw each other and we were getting older, we wanted to start a family and we just knew that the tech lifestyle wasn't going to allow us to do that.

So we said, okay, at least one of us has to quit our jobs.

But instead of trying to decide which one that was going to be, we decided we'd both quit.

We'd move back closer to family on the east coast and we'd figure out something else.

And that something else ended up being real estate.

And we'd been in real estate or I've been, she was my partner in real estate for a decade.

Then she decided to focus on the family and I continued to do it.

So I've been in the business for going on 20 years now.

Let me ask you this.

With the way that you 10, you have a tendency that I've seen to kind of look through or past the headlines and just look at the economic data points.

Right?

Don't get lost in the noise or the hype and everything else.

Like look past what's, what's happening that everybody's talking about in the tabloids and what's the, the brass tax that we can navigate on?

How has that served you over the past few years?

Like, do you feel like that gives you A strategic advantage are you put in a position where you feel like you can skate to where the puck is going because you feel like you have a better vision of where things are headed.

Yeah, I think a lot of people don't realize that there is so much data besides what we see in the headlines.

I think of economics and the economic landscape like a puzzle.

If I handed you a 5,000 piece puzzle and I gave you five pieces, you'd have no idea what that puzzle was, what the picture on the puzzle was.

If I handed you 100 pieces, you might start to get an idea of what the picture is.

If I gave you a thousand pieces, you'd get a lot better.

Ideal.

I gave you all 5,000 pieces.

You know exactly what that picture was.

And economics and economic data is the same at two or three or four data points.

And there are some big ones.

I mean, things like inflation, gdp, unemployment, the things that consume the headlines.

It may make you feel like you know, the bigger picture, but the reality is it's only once you start looking at dozens or hundreds of pieces of data do you really get a good idea of the picture that's forming.

And so on top of that, basically media is looking for clicks.

Media is going to put out whatever is going to get, get the most attention.

And a lot of times the headline data is the thing that gets the attention.

Unemployment rates going up, inflation's going up or down, GDP is going up or down.

But when you start to dig into the data, what you often find is the nuance changes the message.

And the media doesn't know enough about economics.

They don't care enough frankly to dig into the data, to get to the details.

Again, they're just looking for clicks.

I don't care about the clicks.

I dig into the details because I want to really know where things are headed.

As you said, be able to skate to where the puck is headed, not to where it is.

Follow up question on that.

Like, it seems to me these days that you're, there's more noise than there ever has been.

And I love your analogy of the puzzle pieces, but the reality is the pieces of this puzzle are not all the same size.

Some of these pieces are a lot bigger.

Right.

If you get five of those pieces, but if they're the big chunky ones, you can be like, okay, this is a, this is a landscape or whatever, but versus some of these pieces are just minutia and you got to kind of paint in some of the broad strokes.

However, I feel like we're getting to the point where some of the data can't be trusted.

Right.

There is definite political manipulation on both sides that's happening.

For whatever people are trying to accomplish this, their goal, it's going to give them power, keep them in office or help them make money or reduce losses, whatever it may be.

Like, how does that come into play?

Everybody's got an agenda these days.

So when you're talking about the data points that you're looking at, like, what are those data points and how do you know that you can trust the data to make sure that it's real and actionable?

Yeah.

So let me start with.

I try and be really careful about this.

I don't like to accuse any administrator of flat out manipulating the data.

So I'm not going to come on and say I think the current administration is lying to us and manipulating or the last administration or the one before that, or the one before that.

But I will say that while that is possible, I mean, I'm not going to rule out that there is actual manipulation going on.

Even barring the idea of actual manipulation, there are things that administrations can do and these reporting agencies can do to skew data in a way that they want.

The biggest way is simply changing the way we calculate.

And by changing the calculations, by changing the formulas, by changing the data that you're looking at, you can skew the data to a direction that you want.

Additionally, I'll use inflation because this is the best example today.

There's kind of two types of inflation data that we use to build.

And when I say we, not me, but the, the agencies that do this, the bls, there's two types of data they use to kind of build the inflation report.

Number one, they use direct data where they actually go out and they look at products and they say, how much does that product cost today?

Second, they use what's called imputed data.

And imputed data means they didn't go out and look at the product.

Maybe the product wasn't available on the shelves, they wanted to go look at some particular brand of turkey that's sold out that day so they don't find it.

Or maybe what we're seeing is there's a lot of budget cuts at these agencies, so there's not as many people to go out and collect data.

So they say, okay, we're not collecting data in North Carolina because we don't have enough People.

So what we're going to do is we're going to impute the data, which means we're going to take data from other cells, we're going to take other data that we have.

Maybe we're going to take Turkey data from South Carolina, or maybe we're going to take last month's Turkey data, or maybe we're going to take a different brand of Turkey and we're going to say that's good enough.

And we're going to replace what would be a direct piece of data, looking at the price of this thing that we've always looked at, and replace it with something else that we think is good enough.

And the problem with imputed data is one, there can be biases.

If you want to make things look lower and you're imputing data, basically you're going to take something that you say this is, this is comparable.

When it's not really comparable, it's cheaper.

If you want to make it look higher, well, it's not really comparable, it's higher.

And one of the things we've seen, especially over the last eight to 10 months, is that the amount of imputed data in the inflation report has gone from 10 to 12%, which is where it's been for much of the last 30 years, to nearly 36, 37%, close to 40% in some cases.

And so what we're seeing is a lot of that inflation data is no longer direct data.

It's data that some economists at the BLS are saying this data is good enough.

We don't have the real data.

So I'm just going to assume this is good enough.

And they're using their own judgment to kind of substitute.

And maybe their judgment is good, maybe they're biased.

We don't know.

But the fact that, that 40% or nearly 40% of the data is kind of at risk of, of bias is really scary.

That is really scary.

And you basically go from having to discount 10 to 15% margin of error.

That's just, you know, that's baked in to 30, 35%.

Yeah, that's a very, very large standard deviation.

It is.

Navigate around it is, you know, what

we're, what we're talking is something I'm very passionate about, which is there.

The, the problem that we're faced with right now in society so much is our fracturing of our epistemic reality.

And let me explain what I mean by that big word is that, you know, reality.

The best example I can use is reality is I have a six Sided dice.

You got two people sitting across the table.

I, I roll that dice and it comes up a four.

You can see it's a four.

I can see it's a four.

The reality is it's a four.

But if we put up a blind between each other and now you, the other person asks what the number is, and I say, it's a four, and I'm telling the truth.

But if the other person on the other side of the table had a really vested interest in it becoming, being a five, and they've started to view me as an unreliable narrator, now suddenly we start to really have a problem with people believing what they see.

And we're where social media is starting to drive us into these information silos and these media silos.

And the incentive, like you said, is not, you know, by the media.

It's not to present reality, it's to present sensational data that drives clicks.

And, and it's this, it's this vicious feedback loop.

And now with AI and I, I'm a victim of this right now.

I'm notorious for showing my son acute animal video of a, of an animal jumping on a trampoline.

My son is usually the one who goes, dad, that's AI and I'm not.

And that, that's what's like, so it's not going to get better is what I'm saying.

And so it's very interesting to me, like the way that you're solving that is you're having to sort of go back and look at the way, all right, how did we track data over the last hundred years and how has it changed?

Is that, yeah, I think one of the big problems that we're facing is there's a couple of ways of looking at data.

Number one is the scientific method.

I mean, any scientist will tell you, you start with the hypothesis, I think this is what's happening.

Then you go test it.

You say, if I, if I run these experiments, am I confirming what I'm seeing or am I not confirming what I'm seeing?

But you don't really decide in your mind this is what I think is going to happen.

You come up with a hypothesis, but it might be a hypothesis that you're like, I don't really think this is what's happening, but I want to prove that it's not happening.

So you go in kind of without any expectation that what you're trying to prove is going to be proved or disproven.

And so you let the science kind of decide.

Unfortunately, there's the other side of this coin, that's called confirmation bias.

And that's where you start with a conclusion in your head.

You say, I believe this to be true.

And instead of going and testing and saying is it true, is it not true?

What you do is you go out and you start to look for data that supports that thing that you already expect to be true.

You discount anything that doesn't support or prove the thing that you expect to be true, and then you just reinforce your beliefs.

0000001% that says it's a five.

The guy on Twitter who says it's a five.

The media that, that you, that you consume, that's not reliable, that says it's a five.

The, the guy that takes a picture and manipulates it with AI to make it look like a 5.

Basically you're going to look for all those edge cases that confirm your belief, your original belief, without analyzing the data in a clear, coherent, coherent way.

And so that, that's the problem that I'm seeing today is that we have a lot of confirmation bias.

People start with the conclusion and then build evidence to support that conclusion.

As opp.

All the evidence.

It's, it's never been easier to either find evidence, this quote unquote evidence that supports what you believe, or to be able to manufacture it.

And it's never let the facts get in the way of a good conclusion is basically where it feels like we're headed with a lot of it.

I grew, I grew up in the 80s and when I was growing up we didn't have the Internet.

And so if I wanted to learn something, if I had a question about something, I go to an encyclopedia, I go to go to the library, and you're not going to find a lot of really bad information there, at least not purposefully bad information.

Because there's just.

There was no incentive to create bad information that takes years to write and publish and whatever.

When you can go out on the Internet, when you go on Twitter, social media, Facebook, whatever it is, and in three seconds you can put out bad information, the incentive to do so increases.

If somebody has to write a book to put out bad information, it's just not worth the time or energy.

And so yeah, the ability to disseminate information so quickly today is really the problem.

So we're kind of talking about two different things that are very interesting here.

And it's, it's pre and post prognostication here.

Basically it's like, okay, let's look at the data that's helping us understand what's the actual condition of the economy.

From the jobs data that you know, what income data, everything that you're looking at, it's gotten squishy.

Right?

Okay, there used to be a certain amount of this was squishy and you have to look through the noise at the real indicators and that seems like it's gotten more challenging and it's only going to continue to get more challenging.

Hopefully.

You think that as the noise builds up, our ability to see through the noise is improved as well.

Tragically, that's probably just going to become, come from us being more skeptical of everyone and not trusting people.

But then you've got, okay, let's say that we've got the data to the best of our ability.

This is what we think is happening.

Looking at all the indicators and eliminating the fluff.

Now how do we use that to look at what we think is coming in the future?

Where's the opportunity, where's the risk?

How do we skate to where the puck is going?

And I'm not going to ask you to make any predictions, but I know that you do that from time to time.

So like, given the general sense of the data that you do look at, that you do think is actionable, give us an overall idea of if you've got your head wrapped around that correctly, what is likely that the next few years may look like.

And give us an example of how you as an investor are using that to shape your mentality on the, the low hanging fruit, the places you want to avoid, the places you may want to lean into and how do you actually apply that in a meaningful way to create value for your family.

Yeah.

So let's start with the hypothesis or the belief that all the data that we have is accurate, whether it's true or not.

Let's start from that place that we assume all the data is real.

I'm seeing something over the last, and I don't want to say the last year because it's the new administration.

This isn't a presidential thing.

It happens to be the last year, but I don't think this has happened ever.

Anything to do with, with Trump being in office or Biden leaving office or anything like that.

But over the last year, what I've seen is that the headline data is starting to deviate from what the underlying data is actually indicating.

And so, to use some concrete examples, let's start with.

Let's start with gdp.

So GDP is the total output of the economy.

We want that number to be high.

Typically, anything over three and a half, 4% growth in the economy per year is really, really high.

Good.

Q2 of this year, Q1 was really bad.

Q2 was strong at 3.8%.

Q3 was really strong at 4.4%.

Again, let's assume we believe the numbers.

You look at GDP as kind of the holistic health of the economy, and you say, wow, the economy is doing absolutely great.

Just going gangbusters and things are growing fast and we've got nothing to worry about.

Now, even if you assume that's true, once you start digging into the data, what you realize is you can look at different components of the economy and you can see that maybe one part of the economy, manufacturing might be doing well or doing poorly, technology might be doing well or doing poorly, hospitality might be doing well or doing poorly.

When we dig into the data, what we find is basically every component of the economy is doing poorly except for tech and specifically AI.

And so not saying that that discounts the fact that the economy is growing.

It is.

It might be growing at 3, 4, 5%.

But even if you believe that, you have to acknowledge that all the growth is in one very specific part of the economy, AI.

In fact, some data says that if you take AI out, what you see is growth of less than 1%, maybe close to 0%.

So basically, all of the growth in the economy is coming from now.

Again, not necessarily a bad thing, but it adds risk.

If that one sector of the economy were to soften or implode or the bubble bursts, GDP could go from 5% to 0% overnight.

And so when you dig into the data, what you see is that the headline may still be true, but it's not necessarily telling us what the underlying data is telling us.

And so digging into the data gives us a lot more information.

Yeah, the economy might be strong right now, but it has a lot of potential weakness.

There's a lot of risk in the economy.

And then we could do the same thing for unemployment.

Employment number.

Yeah, it's gone up a half percent over the last year to about 4.5%.

Still, historically, by historical measures, 4.5% isn't too bad.

I mean, the 3.5% we saw a year, year and a half ago was just absolutely unbelievable.

4.5% is not that bad.

Again, you look at the data and what you find is that the important sectors, manufacturing, technology.

I don't want to say government's important, but to a large degree, government workers are important.

Those parts of the employment base are shrinking.

Where we're seeing increase in the employment base are things like health care and education, which isn't bad, but those aren't the things that support the economy and grow the economy longer term.

We want to see growth in economy, the in manufacturing, we want to see growth in technology.

So you look at the headline number, 4.5% unemployment, not too bad.

You dig in and you realize the sectors that we really care about are losing jobs.

The sectors we care less about are the ones that are gaining jobs and allowing the unemployment rate not to go up too high.

Then we can do the same thing for inflation.

You look at inflation, again, if you believe the numbers, inflation's coming down, it's not too bad, 2.7%, 2.8%.

But if you look at the, if you dig into the data, you realize the areas where we see high inflation are the things that most people care about, things like groceries.

People really care about groceries because everybody in this country needs to buy groceries.

They need to eat food, they need to pay their rent.

And so those things are going up very quickly.

But it's being offset by other categories of inflation that I would say are less important.

Automobiles.

We saw a lot of deflation, which means price decreases in automobiles over the last few months.

That's been a large part of why inflation has come down or hasn't gone up.

But how many people really care about automobiles?

It's an important part of the economy, but it's not as important to more people.

Gasoline.

Great that gas prices are going down, but the reality is that there's been 15% less demand for gasoline over the last three months.

And so the prices going down isn't necessarily saying that the economy is good.

It's saying there's less demand.

Why is there less demand for gasoline?

When do we have less demand for gasoline?

When people aren't going to work, when people aren't traveling on airplanes, when people aren't traveling, shipping things and buying things that have to be trucked across the country.

So the fact that we see deflation in gasoline, gasoline prices going down, it's great for us who drive wherever we drive, but for the broader economy, it's not necessarily a good thing.

And so again, you look at the high level numbers, gdp, unemployment, inflation, we can do this for other categories as well.

Everything looks great.

You dig in and what you see is a lot more weakness than people talk about, a lot more risk than people talk about.

And I think that that weakness and that risk that's not being reported in the headlines is what is going to hurt us over the next year or two.

So essentially the, the headlines saying it's a five, but when you dig behind the, behind the headline, it's more like a four.

Well, it's still, it might still be a five, but that five is all in one place.

That could go away tomorrow and make it a zero.

Yeah.

You and I have had this discussion offline before about people's underlying perception of the economy can often be colored by politics.

And I don't want to, you know, and I really don't want to dig in to like turn this into a political discussion.

But like, I've seen it.

There's, there's like this great graph that shows the polling data of people's perception of the economy is colored by, is great when their preferred political party is in power.

And then literally within two weeks of their political party or not, political preferred political party changes power.

Suddenly their perception completely changes.

Yeah, we see this every election cycle.

October, October, if Democrats are in power and you ask people, how's the economy?

Democrats are up here and Republicans are down here.

Republicans win the election two weeks later and how's the economy?

It's horrible.

The people that said it was great and vice versa.

It's frustrating and, but I think what you're talking about also is there, you know, we're entering kind of, we've got this kind of K shaped economy where you have, you know, the people who don't own assets, who work W2 jobs right now are getting crushed.

They care about the price of groceries, the price of gas, the price of energy, the price of housing.

The, those of us who own assets are going, what are you talking about?

The economy's great.

My, my, my stock portfolio is doing fantastic.

My properties are worth more.

All my properties are worth more.

What are you talking about?

And that was, you know, one of the things that I remember seeing in the last year of the Biden administration is they kept on going, what are you talking about?

The economy's doing great.

What are you like, what are you guys complaining about?

The stock market's at record highs.

And, and it's, and it's, you know, I'm seeing the exact same thing right now, which is, hey, now we're in power.

The economy's great.

And Then.

But you interview people on the street and they're going, no, like, like, I'm still paying too much for eggs, I'm paying too much for gas.

Like, there's every month it's getting harder and harder to live.

And I want to kind of wrap up this discussion and get your feedback on what I just said, because I want to move on to.

All right, great.

How does this affect real estate investors?

But I'll get off my soapbox for a second, let you get on yours.

Yeah, no, no, I mean, you've hit the nail on the head.

And I mean, that brings up another example of headline data versus underlying data.

You look at the headlines and there's this one piece of data that's probably GDP is probably the most important overall piece of data to tell us the health of the economy.

The best piece of data that I found to kind of prognosticate where the economy's headed is this thing called retail spending.

How much are people spending?

And we want to see that grow every month.

We want to see people spending more money than the previous month.

And what we've seen is retail spending growth over the last six months is good.

We're seeing strong growth, 0.6% per month, which is like 7% growth per year, 0.5%, 0.4%, 0.3%.

We're consistently seeing strong growth.

You dig in again, you go, you move away from the headline number, you dig in and what you find is nearly all of that growth in retail spending is coming from the top 10%.

The people that you mentioned, the people that have assets, the people that have stocks, that have bonds, that have real estate, that have crypto, that are basically printing money these days, they're the ones that are spending.

The other 90% have basically stopped spending and they are only spending money on the absolute essentials.

And so the headline looks great.

Retail spending's up.

People are spending lots of money.

But the reality is that K shaped economy that you mentioned, where it's 10% of people spending money, 90% of people hunkering down because they're struggling.

And depending on which group you're in or which group you talk to or which group is reporting the news, you're going to have a very different perspective on what's going on in the economy.

Yeah.

And to your point, like, if you have that K shaped economy and then that that upper echelon gets squeezed, they can stop that spending a lot faster than if it's the entire economy and you can have a big fall from grace Very rapidly.

And we've all seen the dot com bubble burst.

What if something happens with AI?

What if it doesn't turn out to be what we thought or everybody lay them on the brakes for regulation because something scary happens with Grok 5.

There's so many different unknowns there.

The world is changing very rapidly.

Yeah.

The high level takeaway is the data looks strong right now, but the underlying data makes it look like there's a lot of risk because everything's kind of concentrated in small areas that if those areas take a hit, the whole economy is likely to go down.

Great insight, Jay.

Thank you.

What do you.

Jay Scott, $100 million worth of assets traded under your belt.

What are you doing with this information?

Yeah, so a couple things and it's hard to have this discussion in a general sense because people invest in different things, they invest in different ways.

If you told me that you're flipping houses, I'm going to give you a different perspective than if you told me that you're buying and holding rentals long told me you're buying and holding rentals long term.

I'm going to give you a different perspective on whether it's single family houses or whether it's multi family apartments or whether it's commercial.

And so it's hard to speak in generalities.

What I will say though, let me, let me start because I think the single family housing market is kind of the barometer that a lot of people use for real estate.

We say, how's the real estate industry?

You look at single family housing and the interesting thing is I'm in multifamily now.

We build and buy large 150 unit plus apartment complex.

And if you were to ask the average person how's real estate been over the last five years, four years, people would say absolutely fantastic.

You asked me how real estate's been over the last four years.

Well, in multifamily and a lot of people don't realize this if you're not in this part of the industry.

Probably the worst multifamily recession in history.

But you'd have no idea if you're not in this, this segment of the of of the real estate economy, you'd be thinking real estate's doing great.

And so it's important to realize that when I talk about, let's say real estate, that every sector is going to be different.

And so I need to be very careful about when I say where I think things are headed.

It's going to be for one specific sector and it doesn't necessarily translate to any other sector.

Again, self storage is doing horribly over the last couple years, but warehouses feel attacked.

But it's true.

I mean think about it, what drives.

And this was interesting.

So my co host on my podcast is a self storage guy, owns a half billion dollars in self storage.

And I always used to think self storage was, was a recession resistant or at least recession resilient.

I call it resilient asset class.

What he explained to me, and this makes perfect sense, is self storage does really well when there are a lot of transactions, when there are a lot of single family housing transactions.

When people are moving, self storage does well because they need a place to put their stuff when they're moving.

And typically once they put it there, they're not going to take it out for a while.

And so during a recession we typically have a lot of people moving because people are getting foreclosed on, people are sizing, people are moving houses to apartments.

And so we, we think about generally like in, in tough times, but over the last couple years we've kind of had this housing recession in the sense that, that, that like we're in a bubble and prices are too high, but nobody's moving.

And when nobody moves, self storage doesn't do well.

And so it, it's kind of a mind shift there.

And so certain asset classes in real estate have been doing really well, certain have been doing poorly.

And so I, I like to be very careful when I talk about this.

So, but let's start talk about single family housing values because that's kind of the barometer that we use to measure real estate overall.

I've been saying this for the last three or four years and I will, I've been right so far.

It doesn't mean I'm going to continue to be right, but I've been right so far and so I'm going to stick with it.

I mean, we were directing, we were directly putting money into the veins of the economy.

We're giving it to people.

It was pretty clear that we were going to see inflation.

And we did.

And with inflation, typically housing prices go up.

Additionally, interest rates were near zero.

Basically the loan was the asset there.

The houses were great, but a 323 4% mortgage was like just as good of an asset as the house itself.

22, we started to see a lot of inflation.

And basically what I said was, okay, stop buying.

Not necessarily stop buying, but, but don't just go out and buy everything.

And everybody said, okay, is this where the housing crash comes?

Like we're starting to see a lot of inflation.

Real single family real estate's in a bubble.

The crash has got to be coming, right?

If you look at, and just a step back, and I'm sorry being long winded here, but this is kind of an important point.

If over history, over the last 120 years, what you see is the inflation line kind of goes up and to the right, the real estate housing values line goes up and to the right, basically tracks it Exactly.

2004, housing went up a lot more than inflation.

We saw this bubble in housing.

2008, it all came crashing back down.

Crash back.

Housing values crash back down to the inflation Trend line.

So housing values right now are well above the inflation trend line.

And so a lot of people say housing and inflation should kind of travel together long term.

But what I've been telling people is there's a second option.

We don't have to have housing values come crashing down to meet that, that inflation trend line.

If housing values stay flat for the next 5, 6, 7, 8 years while inflation catches up, those lines are going to intersect again.

So now the question is, is it more likely that values are going to come crashing down to hit that trend line or are they going to flatten out for five, six, seven, eight years to meet the trend line.

They don't necessarily have to go up.

But if you look at supply and demand characteristics, there is not a lot of supply coming online when you don't have a lot of new supply coming online.

Obviously we're seeing a lot more now than we were seeing a year ago.

But when you don't have a ton of supply coming online, values don't drop.

Demand.

There is $300 billion sitting on the sidelines looking for a home.

A lot of that's looking for a home in real estate.

So if housing values do start to drop, there's a lot of money that's going to get pumped into the market that's going to push them back up.

As of a few months ago, depending on the data you look at, there's somewhere between 3 and 6 million of underserved units, basically demand for housing units that aren't being served.

There's between 3 and 6 million Americans that are looking to a single family home and they might not buy it right now because they can't afford it, but if prices start to drop, they're going to go out and they're going to buy.

If interest rates come down, they're going to go out and buy.

So there's a lot of demand out there to kind of force things up.

And then the second piece, which I think is even more important, is I think we're going to see inflation relatively high for the rest of this decade.

There are a lot of inflationary pressures, deficit spending, tariffs which may or may not stick around, immigration policy which may or may not stick around, supply chain constraints that we're still seeing through from COVID lots of inflationary pressure.

When you have high inflation, again, that drives real estate prices up.

And so I think there's more reason to believe that real estate prices are going to stay elevated, they're going to stay propped up for the next five or six years as opposed to them coming crashing back down.

And I think those trend lines will meet again.

But my back of the napkin calculations tell me that those trend lines will meet Again in four or five, six years.

Which means that I think my prediction is that we're going to see flat housing for the next four or five, six years.

I really think it's going to be true for the next three or four or five or six years.

But I also don't think we're going to see that crash that people are talking about.

Well, I'm curious if we are.

We're real estate guys here.

If we're having, if this is a little bit of confirmation bias, because you talk to somebody who does not own an asset right now, who doesn't own a home, and they're like, prices have to come down.

They have to come down because people can't afford housing.

And I agree with you, as much as I'm cheering for, at the very least for housing prices to stay flat and not drop.

And I do agree with you, I think the underlying demand is just there and there's just no way, unless there's some, you know, unless there's some massive thing that happens.

The only thing I can think of that might affect it is all of a sudden we have a mass die off of baby boomers and they just like unload all of their homes and.

But even then, I don't think even that will have the effect of dropping home prices.

Yeah.

So let me, let me say two things.

First to the houses are unaffordable.

Yes, houses are unaffordable.

The good thing is because of inflation and the higher the inflation, the higher this is, is wage growth.

Every year people should be making more money.

Obviously it doesn't always happen, but in real terms, people should be making more money every year.

And the higher inflation, typically, the higher real wage growth.

And so, yeah, people can't afford houses today, but if value, if housing values don't go up in the next year, but wages do, housing can be a little bit more affordable in two years, they're going to be a little bit.

In three years, four years, in six years, hopefully we get to the point where people are making more money in six years than they are today.

If housing values haven't gone up, houses have now become a lot more affordable.

So that's number one.

Here's the kind of the counter view and to your point about this could be confirmation bias.

It really could simply because I've been saying this for four years, I've been right for four years.

It's hard for me to kind of change and say, oh, I've been right for four years.

Nobody else was saying this.

I'm going to look like a genius if it's true.

So there is some confirmation bias.

I don't want to change that.

Here's the one situation I think that could change my prediction.

Again, I said the reason I think housing values are going to stay propped up is because of supply, demand and inflation.

If any of those, or all three of those change significantly, that's what could push housing values down tremendously.

So what could change?

Supply, demand and inflation.

On the supply side, if we see interest rates drop considerably, we could see a whole lot more supply.

There are a lot of people who aren't going to sell their houses right now because they have a 4% mortgage, a 3% mortgage.

I have a 2.75% mortgage.

I'd love to pay my house off, but I can't justify that with a 2.75% mortgage.

If interest rates come down considerably, we could see a whole lot more supply demand.

If people start losing their jobs, if people.

If the stock market starts to do really poorly, if crypto starts to do really poorly, if gold and silver start to drop precipitously, people are going to have a lot less money to spend and there's going to be a lot less demand.

And then if inflation goes down tremendously, well, inflation again is a big driver of real estate values.

If inflation goes down, that could drop real estate values.

So less supply could hurt real estate.

I'm sorry, More supply could hurt real estate, less demand could hurt real estate, and lower inflation could hurt real estate.

What's the one thing that could cause all three of those things to happen?

It's a big recession.

A big recession would drive interest rates down, which would drive supply.

A big recession would drive people out of their jobs.

They're going to lower their credit scores.

They're not going to be able to qualify for mortgages, which would lower demand, and then a big recession.

The primary impact that a big recession has is it reduces inflation.

So if we see a big recession, that's the one thing that could reverse all three of those factors and could cause real estate prices to come down or even crash.

So the question we have to be asking ourselves is what's the likelihood of a big recession?

Because that's going to kind of inform our belief of whether we're going to see a crash in real estate values or we're going to see what I kind of expect that we're going to see.

That could go a couple different ways here.

Let me throw a couple more wrinkles in here that we haven't talked about.

So you've I agree with you.

The fundamentals of supply and demand stay that the housing prices should stay proper up.

Again.

My wife is a full time real estate professional.

Like I understand that we're 9 million something homes behind where we should be based upon the current demand.

There's a lot happening in the world right now.

So let's look forward over the next three to five years and this is going to start expose how much late night YouTube I'm watching you've got so two weeks ago my health insurance costs, I'm married 14 years, two little boys, six year old and about to turn three.

And our health insurance costs jumped up from $800 a month to $2,200 a month.

Ours too.

Okay, so that's a lot of that is because the subsidies for Obamacare went away.

There was some major problems with that.

I come from the healthcare industry.

I'm not trying to have that conversation right now.

But the point is that fixed overhead cost just significantly jumped for a lot of people.

The cutoff for what subsidies you can get at different levels changed if you're a dollar over, you know, from I, you know, I have to claim how much income I think we're going to make this year.

If I was $1 over that amount is a $15,000 penalty plus, plus the, the interest on top of that that I would have to pay back.

So it's a pretty big carrot or a stick situation that we've got going on with healthcare.

Okay.

On top of that you've got AI right now.

And the, the best guess right now is that of everything that you have operating inside your businesses, 92% of decisions made or positions can either be done by AI or significantly helped by AI whether it's marketing, pa, whatever it may be.

8% of things are still purely relationship to relationship, person to person.

Everything else maybe can't be replaced but certainly can be augmented.

Who's not using AI to help write an email?

Right.

And then also you have the Optimus Robot Gen 3.

That is at some point we all know Elon and his timelines, but some point in the next, between the next one and 27 years from now, he will come out with this.

And it's his belief is that it's drastically changing the world because you have this goods and services and labor and now you've got labor like basically unlimited, quote unquote, unlimited cheap or free labor.

The last time you saw that at magnitude was when the Egyptians built the pyramids.

Right.

This is a significant situation that could maybe cause a massive shift.

If you have this potential for unlimited cheap labor data centers in the future, maybe they get solved in space with SpaceX, maybe they don't.

But you've got this unbelievable amount of compute, this unbelievable amount of energy.

A lot of people probably losing their jobs because of AI.

Warehouse positions are likely going robotic, A lot of fast food likely going robotic.

A lot of those entry level jobs that were never supposed to be careers that turned out to be that way are going to disappear.

So how do we factor all that in?

Even if we get the data as good as we possibly can, the stuff that we know is coming down the pipeline over the next 1, 3, 5, 7 years are disruptors that we've never seen before.

So how are we looking at all that?

How do we factor that in?

All of a sudden this turned into a confetti filled pinata instead of a couple things that we're looking at.

So what are your thoughts on all that?

Now we're gonna, now we're really going down the rabbit hole?

No, and it's not even a rabbit hole.

It's, it's a really important discussion.

And, and we've talked about it on our podcast before.

I've done presentations on this before.

And so I'm gonna, I'm gonna kind of, unless we have another three hours, we can't go too deep on this.

We could easily talk.

Yeah, I'm happy to.

Let me start with, I agree with everything you just said.

I think AI is going to be hugely deflationary.

And when I say deflationary, I mean it's going to force prices down because labor costs are going to come down so significantly over the next however many years.

And I think that's going to be a shift in our economy.

It's probably going to be a shift in the global economy and it's going to be something that is going to, to change the world.

Anytime you see deflation, typically deflation's a bad thing for the status quo.

And I think we're going to have to shift a lot of our thinking around labor, around employment, around universal basic income, et cetera, et cetera, et cetera.

I think it could have a massive impact on real estate values.

I've said that the biggest risk to real estate over the next however many years is AI simply because the deflation, basically wages coming down.

We talked about this a few minutes ago.

As wages are going up, that's good.

People are making more money.

Housing values are going to go up because people can afford more house.

As we see deflation in labor costs and pricing, we're going to see wages go down.

And so when wages go down, people can't afford as much house and housing prices go down.

So I think this is a huge risk.

I think everything you said is absolutely true.

Here's the place where I don't quite agree is the timeline.

I know a lot of people think this is a one year, three year, five year problem.

I think this is a 10 to 20 year problem.

And I think as a real estate investor, if we're thinking out 10 to 20 years, this absolutely has to figure into our thinking.

Even 7, 8, 9, 10 years.

I just don't believe, and I'm a technology guy, doesn't make me any more right than anybody else.

But just my perspective is that we anticipate that there are going to be impacts from technology generally a lot faster than those impacts actually take place.

I know what it takes to build and produce and sell and productize technology.

And it's generally a lot more than people expect.

Yeah, V1 Alpha beta versions of technology can roll out quickly, but by the time they become to the point where they're productizable and built in mass quantity, especially hardware, is a lot longer than people expect.

So I think this is a 10 year problem, a 15 year problem, a 20 year problem.

I could be wrong, but I don't think this is a 1, 2, 3, 4, 5 year problem.

As long as I accomplished my goal of scratching the surface just enough that we have to have you come back and talk about this more in depth future.

Our work here is done.

So I know for the sake of time, especially yours and our listeners, we got to start wrapping it up.

Anything you need to ask, Neil?

Yeah, I'm curious about.

That was exactly what we need to start wrapping this up.

And I but I wanted to tie this into a Little bow and ask you, you know, you're looking at all this data, you're talking about all this data, ultimately what it comes down to, you've got skin in the game when it comes to multifamily investing.

And it has been, it's been a hard five years.

But at Bardown Investments, you are still investing in multifamily.

Yeah, we've avoided any big or risky investments over the last three years.

As soon as interest rates started to go up, we kind of saw the writing on the wall.

That said, while there are a lot of people in multifamily right now that are licking their wounds and that are feeling really dejected, especially passive investors who have been in deals that aren't paying or they've done capital calls or in some cases not with us, but there are plenty of deals out there that are getting taken back.

And so there are a lot of investors out there that are really not happy with multifamily right now.

But the reality is that it's, to use a Buffet quote, there's blood in the streets in multifamily and we are at a low.

I mean, if the stock market were to drop 30 or 40%, everybody realizes that's probably the time to buy, especially if the long term fundamentals are good in multifamily.

That's what's happened.

We've dropped 30, 35% and we believe now is probably a great time to get in.

It's not going to be a pretty next year or two years or even three years, but we've likely hit the bottom.

We're likely on the upswing.

And if you buy something now, in a few years, you're going to be happy even more.

So our thesis is that buying an existing property right now is probably not the best thing to do.

We're not going to see nearly as much, much supply coming on as we're going to have demand.

And so we see an opportunity to start doing development.

So for anybody out there, I think development is good timing right now.

If you're in the multifamily space, you're probably not happy.

But think about the fact that we're probably at a lower.

And so if you buy now or you start building now, in a couple years, when you're ready to sell, it's probably going to be a much, much better market.

So I think timing right now for multifamily is actually better than it's been in a decade.

And that, ladies and gentlemen, is called skating to where the puck is going.

Well done.

Thank you for helping us land the plane on how you're taking that data and extrapolating that in a way to create value for yourselves and your investors.

I love that.

I'm going to get to our last question because we are over time here.

Here you've got five of them on the wall behind you.

So I'm going to ask that the answer to this question not be one of the books that you have written mostly on the bigger pockets format of which that I have read and they're all fantastic and everyone should read them.

But the question that I have for you, of everything that you push and everything you put out there and everybody that comes to you with these different economic questions, is there one book or resource that you find yourself recommending to people more than any other where they can go and educate, educate themselves.

It's not a real estate or an investing book, but I'll tell you my favorite book of all time.

It's a book called Thinking Fast and Slow by a guy named, he's a, I think Nobel prize winning psychologist, maybe even economist Daniel Kahneman.

But Thinking Fast and Slow, and it's a book all about how our brains work, how we take in information and either correctly or incorrectly process that information to kind of draw conclusions and make decisions.

And it's it that book, I try and read it every couple years because it's just so insightful.

And so for anybody that's interested in how we think and how that thinking impacts the way we act and the decisions we make, which is tremendously important in any business that you might be in.

I highly recommend it.

So Thinking Fast and Slow by Daniel

Kahneman I don't think we've had that recommendation before.

We've had 130 to 140 different recommendations.

Probably a lot of purple Bible rich dad, poor dad and a lot of who, not how, but never that that one.

So thank you for that.

Hey Scott, I can't tell you how much I appreciate you coming on.

Thank you for being so generous with your time.

If any of our listeners want to find out more about you or bar down investments, anything else that you've got going on right now, what would be the best way for people to connect and do that?

Yeah.

Jscott.com letter j s c o t t.com and that'll link you out to to to everything we have going on.

My email address is there if anybody wants to reach out.

I love it.

I also will.

I'll throw in a plug for Jay's newsletter letter which I'm subscribing to.

I think it's Thoughts Thoughts with J. Scott and thoughts with Jay and and that comes through.

And a lot of the data that we've been talking about comes through on that.

So I recommend it.

Little creepy how often your name comes up in this office.

Yeah.

Your ears are ever burning.

Just know it's probably coming from Wilmington, North Carolina.

But we appreciate you, we appreciate your time today.

Thank you so much for being here and we look forward to having you back hopefully in six months or so and prove everything right that you said.

Said today would love it.

Thanks guys.

Thanks.

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