Data-Driven Housing Policy with AEI’s Ed Pinto

Mike Simonson here. Thanks for joining me today. Welcome to the Top of Mind podcast. If you follow along with Altos Research, you're familiar with our weekly market data video series with the top of Mind podcast. We like to add context to the discussion about what's happening from leaders in the industry. Each week, Altos research tracks every home for sale in the country. We see all the pricing, all the supply and demand, all the sales, all the changes in that data, and we make it available to you before you see it in the traditional channels. People desperately need to know what's happening in the housing market right now. It's been changing so quickly and surprising in so many ways. So if you need to communicate about this housing market to your clients, to buyers and sellers, go to altos research.com and just book a free consult with our team.

(01:00)
We'll review your local market and teach you how to talk about the housing market and use the data in your business. Alright, let's get to the show. My guest today is Ed Pinto. He's the senior fellow and co-director of the A EI Housing Center at the American Enterprise Institute. Ed is someone who's seen it all in this industry. He is been working in housing and mortgage for decades and is one of the most respected voices in the American housing policy today at a EI as research covers, housing, finance and construction and affordability. If you're a regular listener to the podcast, you'll know that I try to learn the best thinking about how to solve America's many housing challenges and Ed is really a perfect guest to talk about the data, the trends, the policy things, and so I'm really excited to tap into his expertise today. So Ed, welcome to the show.

Thanks, Mike. Pleasure to be here. Looking forward to it.

Alright, let's get started with just a background on the American Enterprise Institute, the housing center that you founded and your background. Give folks who aren't familiar with your work, let's give 'em a little bit of what you know.

Sure. So the American Enterprise Institute was founded in 1938 and it was founded literally to focus on American enterprise. Its full name is the American Enterprise Institute for Public Policy Research. And so we have 150 or so scholars that focus on all facets of the American policy landscape. And I focus along with Tobias Peter, who's the co-director on the housing market. The American Enterprise Institute is a little different than I think virtually any other think tank and there are quite a few think tanks. First of all, we don't take any money from the government, never have, never is a very long time, but as I understand it never will. That's state government, local government, federal government, international governments, full stop, no money from the government. If you're going to focus on enterprise, you have to be focused on enterprise, not on government. Our middle name is not government.

(03:18)
And secondly, when we say the American Enterprise Institute is nonpartisan, it also means that it has absolutely no positions on anything. The only people have positions are the scholars. So I have positions, Tobias has positions, the other scholarship positions, we have people on both sides of various positions. There is no party line at a EI, our research that Tobias and I work on, we put together that research. We don't ask permission. We don't get any of the things we publish and don't have to be reviewed by anyone. There's no editorial control. It is, we have academic freedom. The third thing is we don't have to hunt what we eat, meaning we don't have to go out and raise money to fund the housing center. Now obviously we need to be doing good work in order to get the resources that we get, which have expanded substantially over time.

(04:13)
I'll talk about that in a minute. But we have to basically be doing good work and if we do good work, then we get support, but we don't have to go out and find that support. We're always looking for donations though, but we don't have to go raise those ourselves. And that really, as I said, distinguishes us from pretty much all the other think tanks. The housing center, I founded it back in 2013. I got involved with a EI back in 2008 during the financial crisis. And Mike, as you said, I've been involved in this industry. It's now my 50th year, 1974 is when I started as an attorney at Michigan State Housing Development Authority, which was affordable housing. So I've been in affordable housing. I've worked for two mortgage insurance companies, both MGIC and what was known as GE Capital. I actually don't remember the name they go under today because it's changed a couple times, but it was GE Capital back 30 years ago.

(05:15)
In between those two stints, I worked at Fannie Mae for five years. My last position there was as executive vice president, chief credit officer, I like to say I was there before they went over to the dark side. We'll talk a little bit more about that. And then started my own business in 1989 and started consulting including with GE Capital and a number of other companies and banks and mortgage originators, et cetera. And did that for many years until about 2008. And I continued after that. But in 2008, that was the height of the mortgage crisis. That was just beginning to, and I thought that people needed to understand what actually had happened. And since I had seen this from a very high level, at least through the late eighties and had been staying in touch with the mortgage industry through the nineties and the early odd years that I had something to add.

(06:15)
And that's how I ended up at a I with the housing center. Basically, we decided that we didn't want what happened in 2008 where everyone all of a sudden is surprised that the loans that were being originated were just really poor quality, extraordinarily poor quality. And I was able to explain what happened. And a lot of research has been done to explain that, but we decided we didn't want that happening again. So we needed to set up the housing center to track what was going on. And so that's what we've done. Our motto is data, turning data into information, information into knowledge, knowledge into policy. And that's what we do. What we think is one of the largest, if not the largest data set just for housing, mostly single family. We do focus a little bit on multifamily, but it's mostly single family housing from all facets. And we organize that information and we do our research and we basically create new knowledge.

Okay. That's the whirlwind tour. There's a lot actually that I'm looking forward to chatting about in there. The data to information, information into knowledge and knowledge and policy. I actually want to talk to you about all four of those elements today. What do we need to know along the way? And maybe there's another element in there that I'm going to ask about. We're going to come back to later, which is you said you started the housing policy center to prevent surprises that we had in 2008. And so I'm interested in asking about

Are there

Surprises? What do you think that some people might be surprised about? But let's start with the big four framework that you say of your motto, which is turning data into information, information and knowledge and knowledge and a policy. Let's start with the data. What do you like to look at when you're understanding the housing market?

So first of all, we like what we call census data. Small C has nothing to do with the Census Bureau. It could be census bureau data. Most of the time, 95% of the time it is not, but it's census type data, meaning it covers the waterfront, which is what a census is supposed to do. So for example, when first, even before the housing center was created, we were looking at the financial crisis and what led up to it. And we were particularly interested in focusing on land prices and the relationship between land prices, land shares, house prices and foreclosures and the change in house prices and foreclosures that resulted. And in order to do that, we found that up to that point, that was in 2011. So the financial crisis was well on its way still unfolding, but well on its way. And we had looked in the largest study that had ever been done of properties in terms of land prices trying to come up with what the value of a lot is was 10,000 properties.

(09:24)
We did 10 million properties, so we were doing it two, was it 10,000 a hundred? That was what, three orders of magnitude larger. And we had to get the data. And because of the long time relationships I've had, some of which are old, some of which are new, I knew a lot of people and I'd go to the mortgage banking conventions and all of these different things. And we ran into two people that I knew that happened to have the data that we needed. And these were massive amounts of data. And we were fortunate that both companies gave us the data for absolutely free. One set of data was all the public records data, which had all the sales prices. The automated valuation model for all of those properties we're talking 10 million properties across 10 metros and including some very large metros like Chicago and Los Angeles.

(10:24)
And then we needed data on construction costs. And so we got 10 million construction cost estimates, which literally dim the lights at the company that was doing it. They had never done 10 million of these, much less, and they were doing 'em on weekends and on holidays because they didn't want to slow down their production. But they eventually got us all 10 million. And so we were able to do this study and what we found was that what had really happened in Phoenix is a perfect example at the low price end in 2000, a home might sell and we're talking constant quality homes, the same homes over time, the price changes, but it's the same home. In 2000, a low priced home might've sold for let's say a hundred thousand dollars. In Phoenix, the land portion at that time, roundabout was $20,000 and the structured portion roundabout was $80,000.

(11:19)
You flashed forward to 2007 and that house is now selling for $400,000. Same house. What drove it of course, was all of the leverage and lower interest rates and everything else, but primarily leverage without any commensurate increase, relatively speaking in demand or not enough increase in, excuse me, in supply without enough increase in supply, demand was going gangbusters, but supply, which was going rapidly, not rapidly enough to keep up with demand. And so prices were now 400,000. But if you think about it, the structure, let's be generous. Let's say it's now worth with inflated dollars after seven years, it's now worth a hundred thousand dollars. Pick a number. Well that meant it went up 25%, but the house went up to 400,000, meaning there was $300,000 of increase. Well, if the house went up 20, that meant 280,000 of that increase was land. So the land went from 20,000 to 280,000, which was an increase of 14 times.

(12:19)
We actually found, when we got the numbers crunched, it went up 16 times and then it went right back down to roughly where it had started. Now the price was a little bit more. By 2013, the value might've been a little bit more. It went from 400 down to maybe 1 25. But the land actually absorbed all of that decline because again, the property, the structure's not increasing. So that was the beginning of we need census type data, we need all of the data. No one had done that before because the cost of doing that, when we talked to researchers and they said, look, ed, nobody's ever done that, that would be a prohibitive for cost. And so what researchers do is they find free data, but to them free data is literally what they find Googling for data, not the right data. They find free data and then if it's not the right data, they say, well, it's the best we can get for free.

(13:21)
And then they go do their research. We never accept that. We start with, we want the best data and then we find out who the best is and then we go try to get those data and use them. And that's been successful for us. We have about 20 or 25 data suppliers that we've worked with that provide us data and we take that data and then build it into a large database that's connected, which allows us to move from data to information. One of the things that we also learned is we were creating a data utility that most, again, researchers start with, I have a project that I want to know the answer to research project. Now lemme go get the data. When we start a project, we start with, we probably have 80% or 90% or a hundred percent of the data. The question's new, but the data is in the utility. And if we need more data, we then go get the additional data and we add it to our utility, which then makes our utility bigger and better.

So in that grand database, the work and the American housing work, you said as the question is new. So what are the new questions now that are what are on top of us right now? Let's see, what information do people need to know right now?

One of the one that I've really been interested in, it's probably not top of people's minds, but you're probably going to be asking what have been some of the big things that have happened in the last 20 years or 30 years. And one of the big things that happened was the interest rate repression and the quantitative easing by the Fed since 2008. That created a lot of house price appreciation starting in 2012 through 2000, beginning of 2020, house prices were going up pretty smartly on a constant quality basis. And then we got to the pandemic and the Fed really put the pedal to the metal, fortuitously the leverage. I like to think in punch bowls, the leverage punch bowl, the light just went off. Yeah, there we go. The leverage punch bowl did not get further juiced with 200 proof, but the monetary punch bowl was put, pure grain alcohol at 200 proof and interest rates went down to below 3%.

(15:57)
House prices soared at unsustainable levels, but they've stayed very high and it's created all kinds of knockoff effects. And so one of that in those knockoff effects is we do a lot of research on zoning and supply. And what we've concluded is that zoning basically defines what can legally be built on a parcel. And when we talk about single family detached, which something like 75% of all of the residential acreage in the United States is legally restricted to or effectively restricted to single family detached units. And so if you have the house prices went up the way they did during the pandemic, again, you have to think about it, it was really land share and land price that went up. The structure didn't change much. People talk about the inflation and this and that, but we track building cost inflation. It has not been astronomical. It is nowhere near what the house prices have done.

(17:02)
It's mostly just been land prices going up. So what happens is if the highest and best use, which is what drives the use of land, you will put land to its highest and best use. That's legal. That is the basic premise of owning a piece of land. You want it to be its highest and use. And if the land shares go up to a certain level and you're limited to single family detached, the highest and best use is a McMansion. You tear down a 50 or 60-year-old property, and that may be 14 or 1500 square feet. It may be selling in California for 800 or $900,000 because there's so little supply. That land gets to be incredibly expensive even though the structure is basically 70 years old and it was a starter home 70 years ago, but now it's an 800 or a million dollars home.

(17:53)
But the reality is tearing down that home and building McMansion of 4,000 square feet or 5,000 square feet is the highest and best use. And so our research has turned to looking at the data to actually identify the McMansion building. We call it infill McMansion because you have McMansions that get built on greenfield or virgin territory, new subdivisions, but we're talking infill McMansion and something like 40, 55% of all of the single family detached homes that get built in LA City, Los Angeles, they don't build a lot, but 54% of them are in Phil McMansions, which really I call, you're eating your arm, you're taking million dollar homes in la, you're tearing them down, you're building one unit on it for three and a half to $4 million and you're building a 4,000 square foot house to replace a 1500 square foot. One, you've added zero to the supply zero and you've made the housing market. Then the broad picture of affordability worse. But we like to say if the single family detached zoning, the highest and best use is single family detached and land prices are high enough. Effectively the zoning is McMansion zoning. That's the only thing that any developer will build on that lot will be a McMansion, not because they want to, but because it's the only legal use.

Alright, there's a ton there. So at first I thought you were advocating for McMansions, but

I'm agnostic when it comes to McMansions, except I don't understand why someone who owns a piece of property shouldn't have the option. If the McMansion is 4,800 square feet, why can't they build four town homes of 1200 square feet? Because I think they're the same in terms of size. The envelope is identical. Why can't they? That seems to be a property that people should have.

Okay, so what you're really saying is that one of the effects of the long-term low rates is that we were able to finance development, but the zoning laws didn't keep up, and therefore we really only financed bigger houses McMansions as a result of long-term cheap money. But that pressed up against maybe a slow moving local bureaucracy is that

That's roughly true, although the overall size of homes during the last five years or so has been coming down. But in places like California, in la, they're still building. We're talking infill McMansions, not necessarily Greenfield, but infill McMansions of which we've tracked hundreds of thousands of them built over the last 10 or 12 years. We now can identify that because we have data turned into information, information turned into knowledge. So here's a piece of knowledge that we were able to glean from being able to track hundreds of thousands of McMansions. We believe the market in general is pretty efficient. Again, our middle name is enterprise, and so we believe enterprises are pretty efficient. And so when we look at the land share, which is very simple, if a property sells for $500,000 and the structure is worth a hundred thousand, then the land is worth 400,000.

(21:33)
It's an 80% land share. The normal land share. What you'd want to have normally, unless you're in an area with really tremendous amenities, water, it's on water, that's an amenity that adds value to the land. But normally 20 or 30% land share would be normal. In California, the average land share is probably 80%, which means that the propensity to McMansion is very high. So we've actually looked at what happens at 50 to 60, and if you say 50 to 60% land share, you have a conversion rate for every a hundred homes. How many converted? Well that we'll call that one. And then we go to 60 to 70, well that turns out to be two twice as much, and then we'll go to 70 to 80, well that turns out to be four, and then we'll go to 80 to 90. Well, that turns out to be eight. So you actually have, as the land share increases, this is a general rule across the country, you have an exponential growth in the propensity for the land share. Why? Because when a developer has a property or anybody buys a property, one of the things they have to ask themselves is what is the highest and best use of this property? And if the higher the land share, the more it screams, tear me down.

(23:00)
So the Fed has as usual with unintended consequences, have really fueled this in California, but I was just in Raleigh, North Carolina, which in general, Raleigh doesn't have a huge propensity towards McMansion, but there are certain areas where they have zoned commercial areas to be urban mixed use amenity zones, think hotels and office buildings and restaurants and shops and supermarket and all of those things along with some housing, but they leave the residential single family zone around it. Well, that residential family zone now has a new set of amenities that adds to the value of the land. Now people think of it as the price of the house went up, but it's the same old house. It's the land that went up. Well, now you have a developer comes in, and I was just in this neighborhood in Raleigh yesterday. I just was there yesterday. And so houses that are 1500 square feet on a half acre, I mean these are large lots on a half acre, that those houses are being replaced by four and 5,000 square foot houses selling for $3 million.

(24:22)
Why? Because they're easy walk to this great amenity called the North Hills Urban Amenity area, and that's what happens. But the planners don't seem to understand these basics of what I call urban land economics. But Mike, I have to tell you, this zoning issue goes back to the federal government, which most people are very surprised to hear because if you're in real estate, you tend to know that the federal government doesn't have any zoning power under our constitution. Those powers are reserved to the states and the states can delegate it to the cities, which is what they've largely done. However, the federal government got involved in this in 1922. And in 1922, the Commerce Department organized a zoning commission to put together a model. State zoning statute had no force of law, Congress didn't pass anything about it. It was just the bully pulpit of the Commerce Department.

(25:29)
Herbert Hoover happened to be the Secretary of Commerce at that point. And so he came up with this. He appointed a lot of planners. They were all planners on the committee. And of course, when you ask planners what the answer is, they're going to say zoning. So of course they came back with zoning, but there was a nefarious under belly to this In 1916, the Supreme Court had said that you couldn't have zoning provisions that were race-based under the 14th Amendment. And so cities and states and the federal government got interested in, well, how do we stop blacks and other nationalities, ethnic groups, particularly southern Europeans, Eastern Europeans, from moving into the neighborhoods during the roaring twenties, what became known as the Roaring twenties? And the answer was economic segregation and economic segregation worked as effectively as race and nationality segregation. It did work hand in hand with private covenants, which were still legal.

(26:42)
And they knew, and this is why it comes full circle to the solution that we'll talk about. They knew back in 1922 from research done by a planner in 1917 that if you allowed a mix of housing structure types in a neighborhood, single family detached duplexes, triplexes townhouses, you'd have a mix of price points and rent points. And therefore you would have what I would call today naturally inclusive zoning or inclusionary zoning as the term originally was meant back a hundred years ago. We bastardized it today to mean something completely different. But back then, the neighborhoods were naturally inclusionary. And if you think back to any trolley, car suburb in any place in the United States, you will see a commercial area, a little strip of, it could be six blocks or 12 blocks, a little area. It might be a block or two wide, and then you will see all kinds of housing types around it, and that was normal. And then you'll see a lot of townhouses and a lot of single family, and nobody thought twice about all of that mix. All of that was made effectively illegal with the federal government's approach.

Fascinating. It's amazing how much of the economic issues we deal with today have the roots in the racism of the early 20th century or the 19th century. A fascinating insight. It leads to a bunch of questions, and I'm just going to go super geeky right away, which is it sounds like you'd be in favor of Georgia's land value tax in terms of a way to help solve some of the affordability and some of the land value price challenges that drive our market. Is that true? Are you a Georgias

No. First of all, this is why, let me step back a second. One of the things I've learned in my 50 years in the housing finance industry is the federal government screws it up virtually every time. And the reason they screw it up, well, there are two reasons. One is that it's a one size fits all approach in order to get the votes in Congress. I mean, that's how we got our constitution. The small states and large states had a compromise. Well, how do you come up with a solution that works in Montana and works in California? They both have similar problems, but the solutions are very vastly different. And just take the low-income housing tax credit. There are parts of the country that have ample housing supply. Yet the way the low-income housing tax credit is doled out. It's on a per capita basis.

(29:43)
Every person that lives in a state gets, there's a certain formula. Some small states get a hold harmless, but put those relatively small number of states to the side. The rest of the states, California and whatever, the Mississippi get the same per capita dollars. Well, again, that's because the federal government is operating through senators and representatives, and that's what they come up with. And so that's a problem. The second problem is that I've studied what the federal government has done over the last literally 90 years starting in the Great Depression. It's very good at stimulating demand. It is very poor at stimulating supply. Yes.

And when we think about affordability, like what happens, we create programs to give people money, it helps them be affordable, but that stimulates demand. I see that all the time.

And so one of my favorite economists, I like housing economists, particularly from the first half of the 20th century, but Ernest Fisher was one. He was the first chief underwriter, no, he was the chief economist at FHA back in the thirties, and he became a professor after that, I think Columbia. And he did an analysis in 1951 on housing finance. And Mike, you like this months inventory. And back then it was just called is a seller's market or a buyer's market. And they talked about seller's markets and buyer's market quite a bit. And he had data, he had access to FHA data and he had access to VA data and he created a series of natural experiments, meaning there were certain things done on FHA with this program versus that that created two different results. And then on FHA, there was new construction and existing and he was able to measure the difference in the reaction based on what was allowed for new construction.

(31:49)
And what he was tracking was the increase in leverage loan terms were being increased down, payments were being decreased. And he basically came up with a basic observation in a seller's market, if you ease credit, most of that credit easing will get capitalized into higher prices and will not actually expand the quality of housing that's available to individuals at the same income. The reverse was if you do the same thing in a buyer's market, then you will expand access, you will expand quality to people of the same income, and therefore you have to know whether it is a buyer's market or a seller's market. And so what happened during both the time of the runup in financial crisis, we were bouncing around on the cusp of a buyer's and seller's market through much of the early to mid nineties. But by the latter part of the nineties, let's call it 97 or 98, we started entering into a buyer's market, excuse me, I'm sorry, a seller's market.

(32:58)
And that seller's market continued until the beginning of 2007 unabated and got stronger and stronger even though there was massive construction going on in 2005, I believe we got down to something like 3.4 months of inventory. 3.4 months was the lowest level that the NAR, which reports that had been at since the 1980s when they started tracking it. So that was the strongest in 2005 roundabout we had the strongest sellers market since the 1980s, yet we kept pouring on more and more credit easing. And that led to all this time the runup in house prices. Well, now let's flash forward to 2019. 2019. We've had interest rate repression for the large period from 2008 through 2019. It ebbed and flowed, but we were actually entering some more interest rate repression in 2019. I believe that the Fed started buying treasuries again late in 2019, and then the pandemic hits.

(34:11)
So pre pandemic in February of, don't the exact number, but in February, 2020, we were at a level where the month's inventory was lower than 3.4 months. The point it had been in 2005. And so the fed in the face of having at that point, the lowest inventory in what, 30, 35 years? No, 45 years, 40 years, ended up putting pedal of the metal driving interest rates down to under three and accumulating a $9 trillion portfolio of treasuries and mortgage backed securities. Well, that drove the month's inventory to unheard of debts. I think it got down to like 2.2 months. Don't hold me the number, but something like that, we'd never come anywhere close to that. And what happens, what we find out is as you move from seven months, which is the point where you're between a buyer's market and a seller's market, as you move down from that, you move from seven to six, there's a reaction.

(35:20)
You move from six to five to four, as you're moving down the pace of increase of prices, the pressure for higher prices starts growing faster and faster because you're actually, when you go from three to two months, that's a huge, that's a one third reduction. And what happens is you can track, Mike, you probably have done this, you start seeing what the bid versus ask is. So the listing price is $200,000, but people are offering 210,000. Well, the percentage of overbid starts going up and up and up. Well, that's because as that supply, well in some places the supply got down under one month

And

Going up close to 30% a year.

So that is really insightful. So I think about how the government's, everybody's interested in affordability. We want a World War affordability, and the hammer that the government has is incentives. It's financing, help, it's money. So that's on the demand side. And I've never heard the insight before that in a seller's market, you add that, then you don't actually don't help affordability. You heard it in a buyer's market, that's when you can increase accessibility and therefore affordability for people. That's a really insight. And then of course the corollary is we haven't been in a buyer's market for 14 years.

Exactly. So

All of the incentives have pushed prices higher. So okay, that's a terrific insight. The question for you then is, so does that mean there are two questions? I'll phrase it two ways. One is, does that mean that there is inevitably a price correction that's going to happen? And the other side of that coin is, if not, is affordability a solvable problem in the us?

Two great questions, Mike. So to the first question goes back to what I said. We decided in 2013 we would track the market. We started out with leverage as a result of the financial crisis, and we pushed and pushed the federal agencies, Fannie Mae, Freddie Mac, FHA, va, and rural housing. The last three are done under Ginnie Mae. So Ginnie Mae started publishing loan level anonymized, but loan level details about the characteristics of the loan, including FICO scores and debt income ratios and down payments and rate and turn, refinances, cash out, refinances, loan types, loan terms, loan tenure, you name it. All of those facts, first time buyer, all of those facts started being published by the three big agencies, Fannie Mae, Freddie Mac, Jeannie Mae. That's why a lot of our data goes back to 2012 because it starts in about 2012, late in 2012.

(38:33)
And that's where we could get all three to come together. And so I think it's September, 2012. So we started in 2013. We were able to go scrape up and find all of the data back to September, 2012, and that's where we start. And we've been tracking those every month ever since. And we have a monthly briefing call where we go over, that's one of the things we go over, what is the stressed mortgage default rate? Because one of the things we could do from other data that was published is we could figure out for the year 2007, 2008, excuse me, 2006, 2007, that was the peak year in leverage. We can figure that out from data that has been published by Fannie Mae and Freddie Mac going back. And we've put together all the other pieces, FHA VA and the private sector and the mortgage backed securities from all the different data suppliers we have, including the federal government.

(39:35)
We were able to take that back to about 1994. And there's actually a paper by a colleague, Steve Ulner entitled 25 Years of Mortgage Risk. And that paper was co-authored with a researcher at FHFA. And that really is the definitive paper on what happened because it starts in about 2000, excuse me, 1993 or 1994 runs through 2018, but the key years are through 2007. And so we, given all the data that we had, we were actually able to figure out based on loan characteristics, and we created 320 buckets for single family, excuse me, for fixed rate purchase loans, fully amortizing, fully documented, the plain vanilla loan. And then we have all the other buckets for refi, cash out rate and term for low dock for arms, all the things. But the core bucket is the fixed rate, fully amortizing 30 year, fully documented owner occupied purchase loan.

(40:40)
We were able to figure out what the default propensity was of what is the equivalent of a category five hurricane, which is what we had. It was the biggest price decline in our history, even exceeded slightly what happened during the runup to the Great Depression because actually most of the price decline wasn't during the Great Depression. It started, that incident started in 1927, and so it already had proceeded a couple years when the stock market crash and the Great Depression starts. And so we were able to figure that out and we were able to come up with what we literally called a periodic table of risk. And we could say, look, there are three big variables that we track because again, it was all purchase money, 30 year fixed rate, fully amortizing, fully documented. So we got rid of all the risk factors that aren't in that definition we're left with three big risk factors. Risk factor one is combined loan to value if it's a purchase. The flip side is down payment, the reciprocal number two is FICO score. And number three is debt to income ratio. Of the three, the two that are roughly equally important are the combined loan to value and the FICO score. However, under stress, which is when unemployment goes up, is when the debt income ratio kicks in as an important factor.

(42:13)
So we end up with these three 20 buckets and the bucket at the lowest risk point. And they're all very well populated, although there's tons and tons of loans at the high risk buckets. But again, there are these three 20 buckets. The lowest bucket might be a propensity one in 400 loans goes bad, one in 400. This isn't loans originated in oh 6, 0 7 1 in 400, you get to the highest risk bucket and it's 50 out of a hundred. So you're looking at a massive difference just from one corner of the periodic table to the other. And then we said, look, we're now able to risk rate new originations. Now we don't have the same things going on in the overall mortgage ecosystem, but the way we described it is if we had another event, like the event we had, this is what the default level would expect it to be.

(43:15)
And therefore if we had a substantial price decline, but not the 28 to 30% decline we had in starting in oh seven, but let's say we had a 10% decline, we would think that the relationship between the various buckets would still hold. We actually had an opportunity to test that during the pandemic. So during the pandemic, there was a lot of forbearance, but the loans were still delinquent. They just weren't reported to the credit bureaus, but they were still reported to Fannie, Freddie and Ginny as delinquent. And so we ignored the forbearance and we just tracked the performance of loans based on how they actually performed and did a curve that had the performance level that actually took place as a result of the pandemic event. That was the Y axis. And the X axis was our stress mortgage default rate, and we got a curve and then we overlaid the curve from oh 6 0 7 on top of it, and we had like this Mike, a 99.9 car R squared.

Okay, so

It's real insight into how likely are we to see default rates happen. We think it's

Low because the biggest risk part of the mortgage ecosystem today is FHA, but FHA is maybe 20% of the purchase market. It's less of the refi market, and you need to have a lot of concentration in a given neighborhood. FHA is relatively concentrated, but it's nothing like the way it was back in the peak at oh 6, 0 7. And in fact the stress mortgage default rate peaked at something like 39 out of a hundred in oh 6, 0 7, that was the average. And it's about 13 today, so that's about a third. So just on that basis alone, the default level based on this stress mortgage default rate is only a third and it's much more widely dispersed. The risk pockets are much less concentrated. And so we believe that unless there was a very strong economic event or international event that the market, so we basically have a projection on this. We say, look it unemployment is, I think three and a half, whatever it is, still very low. It would have to go to five and a half to even start moving the needle

On defaults.

On defaults and foreclosures. Why? Well, the first couple of points from three and a half to five and a half is not actually going to be impacting the people who have mortgages. By and large, it's going to be impacting renters more and they have lower incomes, et cetera, and lower FICO scores. And you need to get to an unemployment rate of about five and a half in order to start really impacting FHA. And then that's just to start moving the needle. And so you'd have to get to something like seven or 8%. And again, remember we were at 10 point a half percent during the great financial crisis, and that was with a 39 or 38 stress mortgage default rate. So again, even if we got to 10 and a half, you wouldn't have the same impact that we had in oh 6 0 7. So I view that as all good news. I view it as part of we've done our job. Remember I said our goal was we didn't want this to happen again, never was a long time, but since if you don't measure something, I mean you know this, but if you don't measure something, then you can't figure out what's going on. We've been measuring it every month since December, 2013.

So this, I need to recap this for people in order for us to, so right now unemployment is in the threes. In times past, if unemployment got the five a half that we might start seeing moving the needle on defaults. But really we're looking at, because we have high LTVs and better FICO scores really right now,

Low ltv, higher equity,

Higher equity, lower ltv. That's right, thank you. Higher equity, that really means that we need to see, we would need to see unemployment hit seven or 8% before we really start seeing defaults happen and foreclosures happen. And to get a real crisis, we'd need to see unemployment would have to get up over 10% in order to fit in based on all the variables we can look at. That's really useful because there's a lot of people who listen to this podcast who follow the data, who assume that as soon as the economy turns, we're going to finally see the foreclosures happen, defaults happen, and therefore home prices crash. But it's got to be a big turn, is what you're saying.

It's got to be a big turn. And they also saying, oh, that'll bring supply. Supply comes from basically three sources. New construction, obviously the more new construction you get, the more supply you get with one exception, which is the McMansions. That new construction doesn't add supply as we know from la. Secondly, you have the supply that comes from move up buyers. Now the move up buyers have to move somewhere in general, and that's where the new construction many times comes into play. But you also have people moving into retirement homes and people dying and things like that. There is a turnover that comes from existing homeowners moving right now that is very, very sluggish because of the lock-in effect from the same fed interest rate repression and quantitative easing policies that have now with the reversal of interest rates. Now with the 30 year rate above seven people are locked in because they don't want to give up that two and three quarters to three and a half percent rate, which is where most people are and they have lots of other options.

(49:48)
One option is you can remodel, one option is just stay put. One option is to buy another house but then rent the house, which again doesn't put it on the supply market as an owner occupied property. And then there's a third way that historically has been a pretty big source, particularly during recessions, and that was foreclosures. Foreclosures move people from home ownership into rental. And when that happens, that home, which tends to be a lower priced home, ends up being put on the market and is available for lower income buyers to buy. Well, that's also broken for the reasons that we just went through. I mean, broken is the wrong word, but that also isn't providing any uplift to the supply and isn't likely to for the foreseeable future.

So in that sense, maybe some new construction happening, but we have restricted move up buyers and we have obviously very restricted on the foreclosure side. So does that mean, back to my two questions, does that mean home prices can't fall, aren't going to fall? How do we think about

That? I say never, never get

Very long.

However, as far as my crystal ball, and I'm looking at five of them here that I've gotten from omics as far as my crystal ball, it gets cloudier as you move further out. But house prices are moving up pretty smartly right now. Again, constant quality. They're going up roughly 6% year over year by the end of the year give or take. And we foresee that or see that continuing until some other event happens. And I can't remember it was chip case or Robert Schiller that said, if you want to know what prices are going to do tomorrow, look at what they did yesterday or today, because house prices don't change direction very often. So actually if you go back to 1992, house prices pretty much they were moving sideways. Sideways. They started going up, nominal house prices started going up in 97 and they continued up until 2007.

(52:10)
Then they plummeted from 2007 to 2011. They started going up in 2012 in the beginning of 2012. And then they continued up with a little bit of on the higher end because of some tax law changes and other stuff. But the overall numbers kept going up until the pandemic and then they dropped so little and for so short a time that it almost ended up disappearing. And so there wasn't enough to actually measure much. And then we get to the point where the Fed starts raising interest rates a year and a half ago. That led to a big slowdown in the rate of inflation, but it never on a national level got to below zero, but it went from 18% down to a couple of percent. That was a big disinflation drop, but it never got to negative, but it did have a big drop and in some areas it did go negative and in some price points it did go negative because again, if you get nationally pretty close to zero, you're going to have a lot of movement around that.

(53:13)
And so that gives us a point that we can actually measure to start comparing things that are going on because we actually had a correction of some type. It was very minor, relatively speaking and relatively short. And then after a relatively short period of time, prices started going up again and which is where we are today. Now there's some seasonality to those prices, which we'll just ignore because prices do have seasonality based on the time of year and schools and stuff like that, school year and things like that. But in general, we had a downturn that happened in 23 and extended in early 24, and then we had an uptick that happened in early 24 that we're still in. So that allows us to sort of analyze to some extent what's going on here. But again, I don't see anything on the supply side that is going to lead to what effectively becomes the months inventory goes from 3.4 or wherever it is today to something not seven is the equilibrium point. It would need to go to eight or nine to actually start having a nominal price decline and it really need to go to 11 to have a significant decline. And so that's a long way from 3.4.

Yes, it is. And by the way, we measured during the pandemic, the onset of the pandemic, three weeks of housing price declines, and then on week four it ticked up, but we were like, oh guys.

So what happened during that time period, we realized, as you know Mike and you had the same epiphany. Wait a minute, our data needs to be much less latency to the data. And so at that point we were looking at monthly HPA calculations with, if it were March 20th, we'd be publishing February for the month of February, which really means the middle of February. So it was already five weeks old at that point. If we were doing mortgage risk data and we were publishing in early in April when the pandemic is in full bore, we were looking at data from December because of all the lags that were going on and fortuitously, we had a few months before the pandemic, better be lucky than smart. We had gotten access to optimal blue data, which is rate lock data. And so we started looking at the rate lock data.

(56:02)
Oh, we can now do now cast, because the rate lock data was coming out daily, we aggregated to weekly. And so we started coming out with a weekly now cast. So on Monday we would have the data through the following Friday, we were able to come up with not only volume data from the rate locks, we were able to come up with mortgage risk data because we had the FICO scores and the this and the that. We had all the factors we needed and we could see what that was doing. And we were able to create a replacement. We were able to determine a way to replace our constant quality approach on a national level with a weekly constant quality estimate. That tracked very well. We couldn't get below the national level and we couldn't divide it into price tiers. And it tracked extremely well with the actual results that we got from our national full data that had a month. So we've gained five weeks there and we gained like three or four months on the other side, and that was invaluable. So by the time August rolled around, we were basically writing and were hoping the Fed was listening, but they weren't that, wait a minute, guys, this market is fine. It's already back and it's getting ready. The month's inventory is plummeted and it was already at a record low level and it's plummeting, house prices are going up. What in the world are you doing?

Yeah, yeah, yeah, for sure. And of course you just described the entire reason for being for Altos Research, right? We're tracking the entire country every week so that we know exactly what's happening and we could spend an hour on that. We're getting close to an hour already here. We've so much to go. I've got a dozen questions I haven't even hit yet, but here's one that I'm interested in. We've talked about the government and as almost a villain in the role in our housing market. Are there other villains, and I'm thinking about people like to blame the Wall Street funds that are buying single family homes or they like to blame Airbnb. Are there other villains in this market that are preventing affordability or driving prices up or supply? Are there villains we should pay attention to?

I think generally not. I like to use the car industry, which was doing great up until the pandemic hit and the supply chain problems and the used cars went crazy and all of that. But up until that point, the median car price to median income was running, give or take 50%. So basically you earned enough in a year if you used all your income to buy a car in six months, basically six months of income could buy a new car, the average new car, a median new car. And that had been that case for 50 years, and the housing market hasn't operated that way. It used to be back in 1970 that it was 2.8 times income nationally in California was like three. And California I call it was normal back then, but it's not normal now. San Francisco is a 10 to one median house price to median income.

(59:30)
And so that would be like saying that, oh, building convertibles is somehow screwing up the car manufacturing process because it's pulling off whatever, or building whatever or having antique cars or markets. Those are markets. The real problem is we have hamstrung the private sector free enterprise from building housing, and we've done it through zoning and land use restrictions that are onerous. And in the process we've driven up the cost of the land. And then politicians say it was a market failure. Well wait a minute. It's not a market failure, it's a policy failure. If you'd let the market operate the market like it does with virtually everything else would provide abundance, there's a way to tell Mike how much it's due to government versus not. How many conferences a year are there on the price of computers? How many conferences a year are there on the price of cell phones, the price of clothing, you name it zero. How many conferences are there on housing affordability, on higher education affordability, on healthcare affordability, thousands. So there's a direct relationship between the government's role in creating higher prices and the number of conferences. And why are there so many conferences? Because the government gives money to all these groups, and what do they do? They hold conferences.

I love it. The conference indicator we have have a direct correlation. I'm not

Talking about your conference, Mike.

No, that's right. That's terrific. That's really fascinating. Look, we're actually at the top of the hour already. I can't believe it. But let me shift it to one question I like to ask a lot of my guests, which is talk to me about the next decade. What do you see risks and likely trends? What should we pay attention to for the next decade in housing?

So I think we put out a piece earlier, I guess it was in January that was an optimistic piece saying we have the tailwinds are at our back on adding supply, and we basically recounted that Washington state, Montana, Vermont, all past what we call light touch density. Others call the missing middle or middle housing laws that allowed, they don't outlaw single family detach. They just allow the kinds of things that were perfectly normal back in 1922 to be built again today, including ADUs and including townhouses, et cetera. Those types of houses are naturally affordable. We've put together a whole data set. So the flip side of McMansion is if you are allowed to build a light touch density, and we have all kinds of case studies we've done of this, builders will choose to build the light touch density over the McMansion. They don't want to build the McMansions if the only thing you'll let them build is a McMansion.

(01:02:55)
Of course they'll build that. But if you allow them to build townhouses, they will take a half acre plot and build six townhouses on it or 10 townhouses. I mean, half acre plot is 22,000 square feet in Houston. You can build a townhouse on 1200 square feet. That's what, 10 townhouses, excuse me, that's 15 townhouses in Philadelphia. The existing lots, which date from 150 years ago, it's a townhouse city. They have vacant lots, thousands and tens of thousands of them that have eight, 900,000 square feet. You can build a townhouse on 800 square feet in Houston, excuse me, in Philadelphia. And they are. So we think that the opportunity is light touch density, but we follow a three-step process. Step one is buy right light touch density, meaning there can't be discretion. As soon as you give an administrator discretion, they will exercise it. And as soon as you give 'em discretion, the NIMBYs will take control the not in my backyard group, because then you have to have a hearing.

(01:04:10)
We're talking about property rights. You should have the right, as I mentioned before, instead of building a 4,000 square foot McMansion of building four townhouses on that same property, you should have that right. That comes with owning land, in my opinion. And so it is a property right issue. So by right light touch density. Two, keep it simple. Stupid regulations, you can't put poison pills. They will pass BuyRight density like Minnesota did, excuse me, five or six years ago to great fanfare, but nothing virtually has happened from it. Why? They didn't change the other rules around it. So it isn't economical to build a triplex on a single family lot because the floor area ratio inside baseball, technical term, how much floor area can you have on that lot? They didn't change. And so you can't build a triplex that's economically viable at that flurry ratio.

(01:05:12)
So they don't get any, and then they blame the developers. See, they weren't interested anyway, but where they don't put poison pills, they get tens and tens of thousands. And the last thing is, if you put BuyRight light touch density combined with keep it simple stupid, you will unleash the swarm. And you know this Mike, the swarm is American ingenuity. You will have people coming out of the ground, not the big builders necessarily. There's nothing wrong with big builders, but this does not fit their business model. The big builders are looking at greenfield subdivisions large. Can they build a thousand homes or 500 homes? We're talking about building one at a time, but you can build one at a time. We've tracked, there were 20,000 of them built in Seattle. There were 20,000 of them built in Houston, Palisades Park, New Jersey, converted half of its housing stock to duplexes over 30 years, one at a time.

(01:06:10)
And Philadelphia built tens of thousands of townhouses one at a time. And then people say, well, what about the financing? Well, amazingly enough, American ingenuity works there too. All of these places got financing. They didn't need Fannie Mae and Freddie Mac. I know that's hard to believe, but they didn't need them. What happened was specialty lenders popped up and the reality is these town homes are financeable. They're single family attached homes you can get a mortgage on easily. People get mortgages on townhouses every day of the week. The construction lending people figured it out. So that's the positive. And we think, as I say, we have the wind at our back. The negative is the federal government. If the federal government gets in here and puts in some type of, again, they're loathed to get directly into zoning, although I've already given the history of how they screwed this up a hundred years ago.

(01:07:10)
But they want to get into some carrot and stick and they keep talking about that. And if they do that and they start putting a lot of restrictions on funding and say, you have to do this or you have to do that, and then we'll give you money. But what they ask them to do basically violates the keep it simple stupid rule. And so we see that the federal government, HUD has a very hard time analyzing things from a market perspective. HUD is not market oriented. And so they looked at Seattle, which had a program that led to tens of thousands of town homes being built. The city of Seattle four or five years ago decided that they could do better. You got to hold onto your wallet when they say that we could do better. And they basically put in what they call it, a mandatory affordable housing tax.

(01:08:01)
And they started taxing each developer that was building. So if you're building 50 units, well maybe there's even the money to do that. But if you're building three and you say one in five needs meet a requirement and you round up all of a sudden one in three, well wait a minute. And then you get to avoid it by paying $35,000 per unit upfront. Well, you just added $105,000 to the front end and it has to be paid even before you pull a permit as we paid on day zero. And so that basically put a kibosh on the development of these townhouses. So when HUD looks at it, they talk about, oh, look at all the money they collected from what did get built. They never looked at what didn't get built and what didn't get built. Swamped, what did get built. So Seattle actually lost housing, not gained it.

It's fascinating. Okay, so to sum up the next decade, you do have some supply optimism because I think, and I think we've talked about that on this podcast in other times, is there are some policy folks who are, they're understanding density and they're moving out of the seventies mentality, suburbia mentality and starting to understand light touch density. So you have supply optimism over in the coming decade, but you're still worried about the heavy hand of government getting in the way and actually preventing that supply from happening.

Yes, I'd much rather rely on the laboratory of the states, the states or the laboratories of progress. And I'd much rather rely on them than the federal government.

Ed Pinto, it's been a real pleasure hearing all your data and your history and your perspective. You do a lot of publishing at the American Enterprise Institute. Where's the best place for people to find it and follow? The

Easiest thing if you just Google AI Housing Center, that will take you to our webpages. We have all kinds of what we call housing market indicators there, HMI. You can also, if you Google a EI heat, which heat stands for Housing and Economic Analysis toolkit, and you can also Google a EI, good neighbor. And that is a second toolkit that we have that I know we didn't have a chance to talk about it, but really provides a lot of insight into why the homeless problem is fundamentally a supply problem and it's fundamentally a supply problem of the owner occupied market. And so we looked at a total of 54 different variables that could correlate to homelessness across the country. We looked at 360 different, the HUD tracks 360 different geographies. They're called communities of care across the country, every spot in the country in one of these communities of care.

(01:11:14)
And so we looked at all 360 and we looked at the relationship in 2019 between what we call displacement pressure, which is very simple median house price divided by median income, a very simple metric. And it's for housing, not rental, it's just for sale housing across median income, whatever the median income is. Doesn't mean it's not home buyers, it's just the entire median income. That's the x axis. Your Y axis is displacement rate, which is very simply the point in time January number done every year on one day, that rate divided by a thousand divided, excuse me, over the population divided by a thousand to get you a number. The national number on that is something like 0.5.

(01:12:09)
But there are places that are at, in fact, there's a place in California that is at 11 per thousand, which means one in every 100 people are homeless on that one night. But the evidence, there's lots of evidence. And we found that of all those 54 variables, the one that had the most predictive power was median house price to median income. And that's the only way you can explain why Los Angeles on a per capita basis, has 11 times. Though the homeless rate of Houston, the mental illness rate in LA and Houston are about the same. The alcoholism rates are about the same. The criminal rates are the same. The drug usage rates are the same. The difference is housing supply, but it's really the whole housing supply starting with home homes that people buy.

That's a really important point. I'm glad we got to get it in. I talk about it a little bit, but it's really, homelessness is a housing problem. Homelessness is a housing affordability problem. And so we maybe need to come back and do another hour and just talk about that aspect of the American housing scenario like that crisis, a homelessness crisis in particular. And it's a function. We talked about it as a function like the decade of low rates in a seller's market that actually only drives home prices up and didn't improve accessibility. And so this is one of the aspects of that challenge. And so that's some really good, so that's the good neighbor work that you did.

So a EI neighbor that'll take you to that toolkit.

That's really great. I'm really glad we got that in, and thank you for sharing that. So Ed Pinto, thank you so much and everybody, this is the top of mind podcast. Thanks again for listening. We'll be back in next week with another guest. And if you enjoyed the show as much as I did, I appreciate leaving a recommendation for us in your favorite podcast channel that helps other people find us and helps us reach more people with the important messages like what we had here with Ed today. So thanks everybody. Thanks, ed. Thank you, Mike.