CW 1042 - Rising Inflation, the Future of AVMs & Impact of Short-Term Rentals with Dr Andy Krause, Part 2
14 Aug 2018 · 25 min
Jason Hartman and Dr. Andy Krause discuss inflation's role in real estate, how automated valuation models work by aggregating data to spot price trends, and why they're backward-looking. AVMs are improving with drone imagery and curb-appeal grading, but incorporating short-term rentals remains difficult due to zoning volatility and limited public rental data.
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From the initial market recommendation from yourselves and the choosing of the property right through to the leasing process of the property manager. Everyone has been just totally professional and the communication is excellent, especially with being such a long distance away.
Welcome to the Creating wealth show with Jason Hartman. You're about to learn a new slant on investing, some exciting techniques and fresh new approaches to the world's most historically proven asset class that will enable you to create more wealth and freedom than you ever thought possible. Jason is a genuine, self made multimillionaire who's actually been there and done it. He's a successful investor, lender, developer and entrepreneur who's owned properties in 11 states, had hundreds of tenants, and been involved in thousands of real estate transactions. This program will help you follow in Jason's footsteps on the road to your financial Independence Day. You really can do it. And now here's your host, Jason Hartman with the complete solution for real estate investors.
Welcome real estate investors and financial independence seekers. This is your host, Jason hartman with episode 1042. 1042. And I am once again today in the car because we just stayed at the iconic Ojai Valley Inn and Spa. We're leaving there to go to Santa Barbara right now. I tell you, this Ojai Valley Inn and SPA, it's on 220 acres. The grounds are absolutely gorgeous. You know, this little town of Ojai, Ojai, if you haven't heard of it, is kind of inland of Santa Barbara here in California. It's so nice to be able to visit California without paying the taxes in California. Although you do pay them as a, as a now tourist. I've spent the vast majority of my life here and always wanted to just move around and live in some different places. And so that's what I'm doing. You know, in 2011, I moved to Arizona and then I lived in Las Vegas for a year and a half. Definitely do not like Las Vegas. Not a fan, Not a fan. But hey, another no income tax state. And now we're trying Florida, another no income tax state. The there's only. Well, it depends how you look at it because the income tax issue in various states is kind of this. It's not as simple as it might sound. It's kind of hybridized, if you will, and it varies a little bit. You know, there are 7, 9 or 11 no income tax states in the country, depending on how you look at it. And as you know, my financial advice has long been get yourself to a lower tax nexus if possible. If at all possible, do that. Today we will be continuing our discussion from yesterday of automated valuation models, avm. So we'll learn more about Zestimates and various computerized algorithms and how they they estimate the value of a property. So we'll get more into that here in just a few minutes. Before we get to a couple of news, I want to talk about inflation and I want to about the parts shortages in factories dovetails on what I talked about yesterday. But before we do that, I'll just tell you a little bit about the Ojai Valley Inn and Spa. This is this iconic place where all the celebrities go. You know, it's reasonably close to LA, about 70 miles north of Los Angeles. And so all the celebrities go there and you know, they get their spa treatments and live very well. It's a very high priced place. It was not cheap at all. We got a pretty good hotel deal. Did we get a good hotel deal, Carmen? I don't know. I don't know. Right now she's not so hot on our hotel deal. Hey, we just entered Montecito, population 10,000, on our way here into Santa Barbara. We got a pretty good hotel deal on one of the hotel websites. And it wasn't as outrageous as it normally would have been, but it was still pretty expensive. Going out to dinner and having a very light dinner was very expensive as well. But you know what you see when you go to these places is you basically see the future. It's a look into the future. When we did our Venture alliance event in New York City, what about two months ago or so, and I talked to you from there. You know what you see when you go to a place like New York City? If you don't live there already, then you already know what I mean. And of course we have lots of New York City listeners. But you see the future. You see the inflationary future. That's how it will feel in little cities, little places that aren't these expensive areas like Ojai or Santa Barbara or New York City. That's how it will feel everywhere in the near future as inflation starts to take its toll. So Wall Street Journal article over the weekend entitled Stronger Inflation Eats into Paychecks. A humming US Economy is pushing inflation up to levels that the considers healthy. Now, compared to what? Right, the Jason Hartman question compared to what? Why is it that we should have any inflation at all? And you know, if you want to study this a little bit, don't just study it. From a Federal Reserve creature from Jekyll Island, G. Edward Griffin. He's been on the show many times. And he spoke at our Meet the Masters event two years ago in Irvine, California. Don't just consider it from that angle, but I want you to also consider the inflation concept from a more. Well, a more sociological angle. Okay? And what I mean by that is I want you to go to Wikipedia and look up a man by the name of Edward Bernays. Edward Bernays. And Bernays was very famous because he, by many, he considered to be the founder of the modern consumer society and the founder of public relations, pr, you know, that whole field of PR and public relations, Edward Bernays. And he orchestrated this stunt and maybe it was the also the first. Well, he gave a lot of people cancer, I can tell you that for sure. But it was the first real. Well, it wasn't the first wave of it, but he helped the first wave of feminism. How did he do that? Well, there was a parade and I can't remember the exact year, so forgive me for that, but you know, what are we talking 70, 80 years ago? Maybe something like that. Edward Bernays told the women in the parade, he set this up, that they were going to. As they were, you know, walking along, marching in the parade. They were. Or maybe they were on a float, I can't remember. I think they were marching. He told them that all at the same time, you're going to pull out cigarettes. Now, in that day, it was not really considered socially appropriate for women to smoke cigarettes. Men smoked them. So the men got all the cancer and had that disgusting, terrible habit. Folks, if you're a smoker, the most important thing you can do is stop listening to my podcast. Don't worry about investing in real estate. Worry about quitting smoking, okay? Because that is more important. And after you're done with that, sign a petition to ban leaf blowers. Because leaf blowers are super, super annoying. Hey, smoking ain't great either. But anyway, so I think we're on a tangent. Tangent alert. So Edward Bernays, you laughing over there?
Yes, there's always a tangent, okay?
There's always a tangent. So Edward Bernays had all the women pull out the cigarettes and light them up. And he said, we're going to call them torches of freedom. Torches of freedom. And this was to coincide with the suffrage movement and feminism and women's rights and, you know, first and second wave feminism are totally fine. The third wave is a little crazy radical. But that's a whole different tangent that we can talk about later. So study Edward Bernays. Because the other thing that Edward Bernays did, now, you know, look it, if you look at the s and P500, the 500, you know, stocks in the S and p index, about 72% of that entire S and P index is made up of consumer spending, right? Consumer discretionary spending. Wants more than needs, okay? Wants more than needs. And Edward Bernays was the guy that really created that. For better or worse. And I would say for worse. For worse. This was something, you know, before, before Bernays came along, Americans were quite content with just having a decent life and having the basics of life. And you know, then after Bernays came Madison Avenue. And certainly most of you have seen the series Mad Men and you know, you know about Madison Avenue and the advertising culture and all of that stuff, right? And so this was a big change and this created inflation. Now there's another sort of conspiratorial part to this, and this is the promotion of divorce. Yes, you heard me right, the promotion by the media of divorce. And think about it. And I've talked about this before, folks. If you are part of the corporatocracy and you supply consumer goods and you make up 72% of the S&P 500 index and you want to make more money and you want to increase the size of your market, well, married people aren't going to help you do that. You can double the size of your market if everybody gets divorced. They're going to need two coffee makers, they're going to need two toasters, they're certainly going to need two cars, they're going to need double everything. So a great way to increase the divorce size of your market is to discourage marriage, to discourage the traditional nuclear family. And boy, has this ever worked. Sadly. Sadly. I mean, speaking to you as a person who would like to get married and thought he would be married a lot of years ago in his 20s, just kind of never happened for me. And there are a lot of reasons, but you know, this is the cultural zeitgeist of society, is to promote singledom, to promote divorce, to promote discontent, to promote the consumer society, to promote distractions from arguably what is really important in life. Just food for thought. But anyway, back to the article on stronger inflation. There you go. Okay, so inflation is here, right? For many years I really couldn't say it's here. And of course a big part of my strategy is based on my trademark phrase, inflation induced debt destruction. So that's a big part of investing. Now another article in the Wall Street Journal, same front page, Parts Makers Shortages Tap Breaks on Industrial Boom. Remember yesterday when I was talking to you about the, give or take $2 million of my own money. Well, not my own, I guess, because it's through various business entities I have. But essentially, you know, at the end of the day, my money created all that. It is loaned out on various loans, mostly to our local market specialists who are rehabbing properties for you. And I talked about two ways to look at it and how the paybacks are coming in slowly. In fact, I just got a partial payback today, which is something I've never had before. I always get the full loan paid off. Well, this borrower paid part of my loan back just today. The money was wired into my company's account. It concerns me that these loans are paying back slowly. But again, I'm not exactly sure why. Not sure why yet. And I'm going to do a deeper analysis into that. Does it mean that things are turning and things are getting bad or does it mean that it is just too hard to find parts? Because look at this. Okay, so the article says American factories are running short on parts. Suppliers of everything from engines to electronic components are lagging behind the boom in the US Manufacturing sector which has lifted demand in markets such as energy, mining, construction. As a result, some manufacturers are idling production and digesting higher costs. So this is certainly an inflationary sign. And it's also the same thing that is true if you're rehabbing a house. It's the same exact concept. Supplies are scarce, including supplies of labor. So very important to consider that as we watch things happen. Okay, couple more things just to remind you before we get to our guest today and talk about automated valuation models of real estate. Number one, join us in Hawaii first week of November. Go to jasonhartman.com to register for our two day conference there. Number two, if you use Alexa then be sure to add our Alexa skill and hear the Jason Hartman Real Estate Update every day for free on Alexa. And that'll be part of your news briefing or your Flash briefing on your Alexa device or on your Alexa app on your phone. And number three, be sure to subscribe to the new PropertyCast where you can get properties your delivered to your RSS feed as they become available. So if you want to be on the hot list there and get the hot sheet, if you will, of properties, be sure you subscribe to the Property Cast and remind me on an episode I got to tell you about this refinance I'm doing on this apartment building I own. Boy oh boy, that thing is, you know I've talked to you before about commercial Real estate and how commercial real estate is not for time. The first faint of heart. You would not believe the loan docs I had to sign to refinance this property. It's like, okay, we are going to take your firstborn and an arm and a leg again. It goes back to what I told you about the perils I had with various office properties that I've leased over the years. And man, there is nobody watching out for you when it comes to commercial real estate. It is not for the faint of heart. So if you're considering commercial real estate investments, just know that the protection mechanisms that exist in the single family home business are completely absent in the commercial real estate world. And we'll talk more about that later. Don't have time today. Okay, let's get to our guest and talk about automated valuation modeling. Here we go.
So I can see how the software could do a much better job than a huge human at weighting and determining valuation from different data sets and so forth. So, so that's really good. That's where the AVM thing might be better, but what else does it do? What else do these algorithms do?
So one thing that you can also pull out of the algorithm is you can get some pretty good local measurements of price movements. So that's often a real help in this, where sometimes appraisers, depending on how well they know an area, may often make some pretty rough assumptions on how quickly the market's moving in a certain neighborhood or a certain county or city. And within the avm, because of the volume of data you have, you can really test those assumptions and come up with some really localized price movements and price trends, which is something that in the avm, we developed the atomized avm, we really tried to focus on the locality of price trends to say we understand, you know, we're based here in Seattle and we know that, you know, one neighborhood over from another neighborhood, price moments can be considerably different. So really, a well constructed AVM will give you an opportunity to understand how different neighborhoods are changing and in what direction.
Good.
So, Mel, you work with Atom Data and we've had Darren Bloomquest on the show many times and he's spoken at a couple of our conferences.
Is there anything you, you know, thoughts.
That you have, and I don't know.
If this is your area or not.
On, you know, where the market is.
Going or, or where certain markets are.
Going because you just spoke to that sort of momentum aspect of the data. Yes.
So I think one thing that's important to know is that most AVMs are not in the business of making predictions. They're inherently sort of backward looking. There are a lot of AVMs out there that actually kind of specialize in doing what we call retro AVMs where they will do a value in the 10 years in the past, if you need that for some particular reason. But making forward predictions is, you know, there's much more goes into what a house is going to be worth a year from now is certainly dependent on what it's worth now. But there are a lot of macro and microeconomic factors that get into that. So that isn't something that we here at AVM analytics have generally been doing. You know, we, we like to think that our atomized AVM will be very quick to pick up changes because of the locality at which we run that and the fact that we're using very, very localized models to pick up on price changes. But, but we're not in the business of trying to guess what it's going to do a year from now because there are just too many things that go into that.
There are. And this is why predictions are usually.
Worth the napkin they're written on very often. Yeah, yeah, absolutely. Well, what do you see as things.
Coming up in the industry in terms of the future of all of this or just the industry in general?
Well, I think there's a couple of things that seem to be happening in the industry. I think the continued use of image data and as this consolidation happens in the industry, the bigger players are going to come up with a larger and larger sort of time series of photos. So as time goes on, suddenly they're going to have photos on 20% of homes and then 40% of homes and then 60% of homes. Right to the point where that stock of image data is going to become a lot more useful for the model. So that's one thing, I think, another.
Before you move on from that one that's interesting. The computer will be able to tell how attractive the house looks.
Why wouldn't they?
Dating sites can tell how attractive people look. And you know, there are certain, by the way, sort of universals in that. I mean, everyone has their own taste, of course, but there are some principles, some broad principles of, you know, what.
Our eye likes to see.
You know, there's the golden ratio.
I mean, we know, we've all heard.
Of that stuff, right? So some of this stuff is not really subject to opinion. It is just the way most people view the world. And so the image data on housing will, someday the computer will give a grade It'll give a comp extra points for having good curb appeal or being.
Neat and clean versus sloppy or decorated well or whatever. Right?
Absolutely. I mean, that's sort of where it's headed. And I think you can also then start to say maybe we don't know if people like pink or white better, but what we notice in the model is that pink paint actually has a 5% price premium once we control for all these other things. So there may be some kind of latent human activity that at some point we can also try to understand do that in the future. So I think that's really one of the big avenues that people are going after. I think a number of the firms are using drones to try to get a better sense of some of the very micro spatial factors that contribute to housing. Is it next to a non residential use? What does the view actually look like from the top floor? So there are some of these things that maybe the photos don't show you, but a real thorough remote sensing analysis of the property could as well. Those two are kind of in a similar vein, but expect a lot of innovation in that front. And then I think there's probably some movement headed short term rentals. Airbnb is becoming such a big deal in cities here in Seattle, it's definitely a big deal. So I think some people are starting to talk about how that might contribute to value in trying to understand how those entitlements in general, zoning changes, ability to sublet a part of your home on Airbnb. How do we start to think about that in an avm? And I think we're in the very, very early stages of that. But as I'm sure you know and your listeners know, that can contribute a lot to value.
Oh, sure.
And how do you properly capture that? And that's always been a big question in the AVM space. And you know, we might finally begin to a point where again, the data is there to start to answer those questions.
Yeah, you know, I have seen many articles on the short term rental effect on markets and some say that it's hogging up inventory. Too much inventory has come out of the housing stock that's being used as short term rentals and it's not really part of the market anymore, the traditional market. So when a home buyer wants to buy a home, there are fewer homes available because some of that stock has been sucked up. There are some interesting effects there, no question about it.
Yeah, absolutely. About a year ago, I was living in Australia for a while, and particularly in Sydney and Melbourne. It's a very big problem in some of the better neighborhoods near the beaches and things where there are some neighborhoods that are approaching 20% Airbnb own unit or utilize units in terms of apartments and condominiums. So. Absolutely.
Yeah. Yeah. That's crazy. I would, you know, that's something to definitely watch for. And it's something like you said, we don't really even understand it yet. We don't even understand the impact. And also that use, that zoning can change virtually overnight. So you got to be really careful of what you price into the market because of that, because there's a lot of. A lot of controversy over that and a lot of fights, a lot of wars going on at various city councils and in various neighborhoods. So we'll see how that all works out.
Are there any questions I didn't ask you anything you wanted to share with.
Our listeners in general, I think.
Good question that you've asked, certainly. I think one thing that I'd like to stress to at least clients of ours and people who interact with our AVM is that while the value is important, always look at the number value that an AVM gives you, but look at the confidence interval or the range as well. That's equally important or maybe more important when you're evaluating an avm, if that range is really wide, that gives you an insight into the model, and that gives you an insight into how good the modelers think they're doing in that area. So if you see a really wide range, a really wide confidence interval, your takeaway should be, well, yeah, they gave me a value, but they're not even that confident in it. So that can really be a good place to start understanding, at least at a very simple level, how good the producer of an AVM thinks they are in an area. So I would urge your, your listeners or anyone interacting with AVMs to, if it's not provided to you, to ask for that confidence interval and then use that as a gauge kind of to how much trust you should put into avm.
Right?
Absolutely.
You know, one question I do want.
To ask you before you go is when we have been talking this whole context of this conversation, I assume, is really about the value of properties, but our listeners are investors. What about rental prices?
Do you work on that side of the AVM world at all, or are.
You strictly working on sales prices?
At the moment, we're strictly working on sales prices. Rents, I think, are certainly an interesting place to be as the investor class grows, as people start to understand the fundamentals of the market more, they start to understand that their home is not just a place to live, it's an income generating asset. The biggest issue with the rental market is data. You know, rental transactions are not public record anywhere. And what you do get, you know, if you look at Craigslist or even one of the larger sites, all you get is list price. You never really find out the contract price.
Right.
Nor do you know the duration, nor do you know what's happening when there's renewals. So the data is just a lot cloudier in the rental space. I think that's why those type AVMs have been very slow to develop.
Yeah, I agree with you. And there are some websites out there that pretend to do it, but it's just the data's all over the board.
Very true, very true.
Yeah, no question about it.
Give out your website, Andy, and tell.
People where they can find you.
Yeah, so they can find us@greenfieldadvisors.com and then our subsidiary, avmanalytics.com is where we do all of our kind of real estate data science work. Any of those two websites will get you to the interesting work we're doing. And then obviously, Adam, Data Solutions as well, they're our data partner and they've got a number of different interesting products for investors, owners, anybody interested in the market. So, yeah, please do check us out.
Fantastic. Dr. Andy Kraus, thank you for joining us.
Oh, thank you, Jason, for having it. It was wonderful.
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