In this episode of the REconomy podcast from First American, Chief Economist Mark Fleming and Deputy Chief Economist Odeta Kushi discuss how technology and innovation played a role in the recent GameStop stock market frenzy and what that phenomenon has in common with innovation in mortgage finance and the housing market.
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“Rather than having to fax your bank statement and submit copies of your last three years of tax returns, give me permission to connect directly to your bank and to the IRS and pull down that data on your behalf. This is good for the consumer because it's easier, it reduces your transaction costs, the time and energy you have to spend gathering that information and making the loan application, and it improves the accuracy of the data for the lender to make the decision. So better transaction, lower transaction costs for the consumer, better customer experience for the consumer, more accurate decisioning processes on the part of the lender.” – Mark Fleming, chief economist at First American
Odeta: Hello, and welcome back to another episode of the economy podcast where we discuss economic issues that impact real estate, housing and affordability. I'm Odeta Kushi, deputy chief economist at First American. And here with me is Mark Fleming, chief economist at First American.
Mark: Hey Odeta.
Odeta: Hello. So you've probably heard a little bit about a video game retailer called GameStop. And today, we're going to use GameStop as a starting point for a broader discussion on markets and the matching problem. With a focus, of course, on the housing market. Just a little bit of context on GameStop. In case you're one of the few that hasn't heard GameStop shares, traded wildly in January of this year, GameStop, shares went from a few dollars in 2020, to just above $480 by the end of January before falling once more. I just checked this morning, they're at about $46 a share right now. And this was a result of a short squeeze of the stock from retail investors using apps like Robinhood. So I guess the question is, what is it about the stock market that allowed for this to happen? And how does technology play a role in that?
Mark: This is really going to be fun. I mean, today, we're going to talk about cartels, dating apps, ride sharing, and somehow connect that to the property market. But let's go back, you know how much I love history and the history of the stock market. Do you remember back in the day, in fact, for most of the stock market's history, up until only the latter part of the 20th century, when you wanted to buy or buy stocks, or someone wanted to sell stocks? Remember all the videos from my favorite decade, the 80s, when people would be standing on the stock market floor, waving hands and crazy gestures at each other?
Odeta: Well, I'm not familiar with the 80s. But sure, continue, I'm with you.
Mark: That's how it works. That was the market. That was the challenge to match a buyer to a seller. For most of the history of the stock market meant somehow you had to communicate with someone that you wanted to sell your shares of a certain stock. And somehow, someone else was communicating likely to somebody else about their desire to buy those shares of stocks. And so the matching of buyers to sellers in the market was this extremely cumbersome and complex process that sort of played out on the proverbial stock market floor.
Odeta: And that must cost some money, right?
Mark: That costs a lot of money, the fees were very large to make that happen. And then the 1980s rolled around, and the NASDAQ came along, and they automated the floor. But it was still pretty hard to find the people to match even though the computer was doing the matching instead of humans waving their hands. But that put a lot of pressure on the fees. Fast forward to then the internet comes along. And more people have more information and communicate more efficiently and the cost of information goes down. And that further accelerate accelerates the efficiency of the matching program. The net end result that Robinhood represents is we are so fast and efficient at the matching process in the market for stocks, that the transaction costs are nigh free. And the other aspect of the market is it's also very liquid because what's being traded in the market is what we refer to as -- hold on now, I'm gonna throw out an economics term -- an extremely homogeneous good. That good, a stock an ATT share or a GameStop share, they're all the same, I don't really care which share I buy. Now, we've talked about this concept of homogeneous versus heterogeneous goods in a prior podcast and on our blog, but what we're gonna hold that thought, and we'll come back to that later. But that's what's driven down the fees and gotten us to this point where it's so fast, efficient, liquid and low cost, because the matching process in the market is so effective today.
Odeta: And that's really allowed for a lot of these, what we call retail investors, you and me, for example, to enter the market. And I read a very interesting stat that showed that retail investors made up a 10th of trading volumes in America in 2019. That rose to about a quarter in January of this year. Now that really speaks to this whole GameStop phenomenon. But nevertheless, this kind of technology allows a lot more people to enter and to start playing around in the stock market. But this isn't the only area where technology is changing things up a little bit and we promised you a show and so We will deliver. There's a lot of different platforms on there. Think eBay. eBay has revolutionized what you would see as the traditional lawn sale today, right? You can buy and sell things on eBay. Uber and Lyft are solving the matching problem of getting you to where you need to go. Match.com and Tinder, solving the love matching process. You're swiping left or swiping right and you're finding your ideal partner on an app. But what about other markets? Maybe even less exciting markets? How does the market for bonds or maybe a little bit closer to our wheelhouse property differ from the stock market? And I think it has a little bit something to do with that economics term homogeneous?
Mark: Yeah, I would probably argue that the the dating scene and Match.com or Tinder represent relatively, shall we say, heterogeneous goods. Whether you're a buyer or the seller...let's let's move on. But yes, the concept of the, it's much easier to buy a good to find a match on your proverbial Match.com for your marketplace, when the good is more homogeneous, because it doesn't matter which one. You know, you mentioned Match.com, Uber and Lyft. Like, you could argue that, you know, getting a ride is a quite heterogeneous good, because where I'm standing, trying to flag down a taxi and where I need to go and where the taxi driver is, creates this complex problem. But if we stick to the argument of moving from stocks to the next level up, we can consider bonds. Now, any given company might have one stock, but it might have many different bonds with different maturity dates and coupons. You know, without getting into too much detail about maturity dates and coupons on a bonds, basically, different kinds of bonds for the same market, a more heterogeneous, good, and so a little less liquidity, a little less trading, a little less price discovery. But that said, you could look at things like treasuries, those are bonds issued by the US government, there's a lot of different ones. But those are heavily traded. And there's lots of price discovery and loss of efficiency in those matching markets, that helps them to drive down the prices and create efficient markets there. The more heterogeneous though the goods become, the harder it is for that market to work.
Odeta: And if you think bonds are heterogeneous and thinly traded, let's look to housing. There are 140 million unique properties in the United States. And on any given year, they change change hands at about 5%. So housing, and we've said this before, is a thinly traded heterogeneous good. So would you say there's a matching inefficiency in the housing market matching a buyer with a seller? I know the answer to this question, because I'm in the process of finding a home right now. So I feel that pain, but I would say there's an issue here.
Mark: Odeta, you're dating the housing market right now. Oh, by the way, there's not that many eligible bachelor houses out there right now. Don't I know it. You're preaching the choir. And you know, you're pretty picky. Not any ol' bachelors gonna do. You want a very specific one. But when you have such a heterogeneous, good, the challenge of actually being able to find that one, and then add to that what we have in the housing market today, not that many, makes for a very, very big and challenging task. And that's fundamentally been the case. If stocks are the most liquid most homogeneous example of a goods market or a matching market that we can find, then you could arguably say that the housing market is the antithesis to that because housing is probably the most classically heterogeneous good. No house is the same. I mean, the closest you could possibly come with a maybe be two condos on top of each other, but other than that, extremely heterogeneous good. And so not only are, as you point out, it's thinly traded, not that many homes turnover, but the process of that matching market is extremely challenging. And that's something that, you know, we've relied on humans to help with for the longest time basically, most of our market history has been, you know, that's the real estate agent facilitates, much like the New York Stock Exchange and people waving hands on the stock market for facilitated real estate agents helped us find each other to buy the homes And the question becomes, what can we do to make this market also more efficient?
Odeta: You're right. And I mean, can a girl just get some closet space? That's all I ask. My list isn't that long. Well, tech is evolving in the housing sector as well. We're not staying in time, right. So one of those changes comes in the ibuyer. And for those that don't know, an ibuyer is yes, instant buyer. And I would probably refer to them more as a middleman than a matchmaker, right ibuyers use home value assessment tools, data-driven machine-learning algorithms, to determine what your house is worth. And then will make an instant cash offer to buy your house. So they kind of offer more of a certainty in home selling. But are there any other technologies that might be making the home buying process a little bit more efficient? I mean, you mentioned that that Realtors obviously facilitate in this matching process. What else is out there?
Mark: Well, so the real estate community actually created its own platforms to facilitate communication with each other. That's what the MLS is represent, right? you list your home for sale on an MLS and that allows selling agents of sellers to show what the inventory of you know, eligible bachelors are out there. And then buyer agents can go on and as the representatives of of the daters to find their, their respective bachelors. So those MLS systems have been around for a number of years and as digitization and automation and the internet and all of those things have helped to facilitate more efficient platforms for that, for that information. It's also now become more directly available to the consumer. That's what Zillow and Redfin and all of these other platforms allow not just the real estate agents to see what's in the market to sort of facilitate the matching problem, but the consumers more directly are able to participate in finding the potential matches. So that's a huge leap forward. But also, more importantly, to just facilitate the efficiency of the match of you Odeta dating the housing market, and eligible bachelor home with big closets, finding you.
Odeta: Right. They're right at my fingertips. Now I can do a web search and look at all of my eligible bachelors all at once and make some decisions. And obviously, the Realtor will help in facilitating that transaction. When that day, lucky day comes for me. But there are also a number of other technologies that are helping to address other issues. So let's talk data. Let's talk executing a transaction. There is Day 1 Certainty, for example, you and I talked about this quite a bit, how is that technology helping to make for a more efficient home buying process?
Mark: So here we distinguished from the market to find the home to the process of buying the home, particularly if you need to get a loan. And when it comes to getting loans, you've got a variety of platforms that are now becoming available to more efficiently, particularly gather the data necessary for the loan decisioning process and the underwriting process for the loans to happen. And in the housing finance space, there's been a lot of financial innovation much akin to what's happened actually with the stock market and Robinhood and creating liquidity and information transfer. In this marketplace, the most important thing is the information, not necessarily the price. There's been a lot of work to develop the tools to gather the information more efficiently from the consumer to make the loan underwriting decisions. So you know, rather than having to fax your bank statement and submit copies of your last three years of tax returns, give me permission to connect directly to your bank and to the IRS and pull down that data on your behalf. This is good for the consumer because it's easier, it reduces your transaction costs, the time and energy have to spend gathering that information and making the application and it improves the accuracy of the data for the lender to make the decision. So better transaction, lower transaction costs for the consumer, better customer experience for the consumer, more accurate decisioning processes on the part of the lender. So here again, you know, information and technology to facilitate the transfer of information makes for a better functioning in this case, not necessarily changing liquidity, but a better functioning market for getting a loan in order to buy that home that you can't find right now.
Odeta: A win-win it seems. So technology, the lesson here we started out with GameStop and ended with housing but I think that the broad lesson is that technology makes it possible for us to have greater price transparency, more liquidity in markets, and overall a more efficient market, whatever that market may be. And I think we'll stop there. That's it for us. Thank you for joining us on this episode of the REeconomy podcast. Be sure to subscribe on Apple, Google, Spotify, or your favorite podcast platform. You can also sign up for our blog at www.FirstAm.com/economics. And if you can't wait for the next episode, please follow us on Twitter. It's @OdetaKushi for me and @MFlemingEcon for Mark. Thanks and until next time.