How did you become interested in the impact of loss aversion on seller behavior?
My first job after I left graduate school was working at the Federal Reserve Bank of Boston. It was right after a downturn in the housing market in the late 1980s in Boston. One of the things that became clear if you looked at the housing market was that it just didn’t function well in a downturn. In particular, you saw lots of houses on the market and very few transactions taking place.
I had just come from graduate school, where you learn about Walrasian auctions: if there are a lot of things on the market and not very many bidders, prices should fall. This is just what would happen on the New York Stock Exchange — a lot of stocks for sale, a lot of asks, no bids, that pushes prices down until there’s a point at which supply equals demand. But that doesn’t happen in the housing market. So people can sit with their houses on the market for a long time, not lower their price appreciably and eventually just decide not to sell.
What was your hypothesis?
Initially we went after kind of the standard economists’ view of the housing market, which is liquidity constraints or mortgage constraints. Let’s say you have a $150,000 loan on a house that’s worth $180,000. If the value of the house falls to $130,000, people are going to be reluctant to sell, because they don’t have the cash to cover the mortgage. That’s the standard view of what’s going on. Our first paper on the subject discovered that, in fact, that was true, but it didn’t explain most of what was going on. Most people who had their houses on the market actually had a loan amount that was well below the expected selling price of the property, so they couldn’t be sitting with their house on the market purely because of liquidity constraints.
That led us to the second paper, and this sort of plays off of an idea of behavioral finance, which is something called prospect theory or the disposition effect. It’s the idea that people don’t like transacting at prices below what they paid for an asset, whether it’s a house or a coffee mug or shares of stock. This is just an aversion that people have to selling an asset that they purchased for a loss, which to most people seems like a reasonable thing. But as an economist, I would separate the desire not to lose money — which of course everybody has when they make an investment — from the observation that once you’ve made the investment and you’ve lost money, you might as well do the best you can given the circumstances.
The interesting thing about loss aversion in the housing market is that people give up real things in the process. They decide not to take a job in another place. They decide to leave their family in cramped quarters. They suffer real problems as a result of not selling a house for a loss. That’s what makes loss aversion in the housing market so interesting. That was how we got into the project — recognizing that the standard economic theory didn’t apply in the housing market.
Can you talk briefly about your research methodology?
I think this has been the most challenging project, from a data perspective, that I’ve ever had, because we had to get information on houses that were on the market, and that isn’t in any standard database. You can go to the county assessor’s office and find out what a house sold for, but you don’t know when that house was put on the market. So we worked with a woman in Boston who runs a private listing service and collected all of her data. We did some computer matching and eventually hand-matched all of the remaining data to sales from the deeds records. At one time we actually had two full-time research assistants working, and all they were doing was just hand-matching properties.
So we ended up with this database that matched properties coming on the market with sales and attributes of the properties. It’s the first database — and still the only database — that I know of that gives a comprehensive snapshot of the market. The key thing is, most databases that people have are based on transactions — properties that sell. What’s unique about this database is that it also includes information on properties that don’t sell.
One of the things we discovered immediately was that when things started falling in 1990 — actually, the market bottomed in 1992 — two-thirds of the properties that came on the market were eventually withdrawn without sale. So to study what we were studying, it was really important to have a database of not only things that sold but also things that didn’t. That was really the innovation we had in putting together this database: it allowed us to study things that didn’t sell, which is not what most people study in economics or finance.
Was there anything about the results that surprised you?
I was really surprised at the extent to which loss aversion mattered relative to standard economic theories. This clearly has a big effect on behavior and a big effect on markets in ways that we’re just starting to understand now. There’s a really growing branch of economics and finance that focuses on psychology and human behavior. Partly, what I learned from this project is that those areas shouldn’t be underestimated for their potential to help us understand how consumer markets work. The evidence in our paper shows that the loss aversion effect applies less well to investors in these markets. The psychological effect still matters to investors, but just not as much as it matters to owner-occupants.
What are the practical implications of this research?
There are a couple of things. The first is that for people who are buying and selling houses, this can help them understand strategies that you can pursue in markets. There may be times when buyers have to recognize that there may be a lot on the market, but as I’ve sometimes facetiously commented, there are a lot of houses on the market but not very many houses for sale, because the ones that are on the market are essentially overpriced and in many cases the owners are unwilling to reduce those prices. So I think in down markets, the practical implications are that housing markets don’t function well. I think participants in the market need to understand that and adjust their behavior accordingly. It may that mean buyers, if they really need to buy, are going to have to pay more than they think the market price is for houses.
And I think sellers should really try to understand what’s driving their decisions. In particular, I think sellers probably should recognize that although they don’t want to sell for a loss, the loss is sunk, and that if they’re giving up real things to live in their house, they may be better off selling their house at a lower price. But the trade-off is that the next house they buy they’re also buying at the same lower price level. On the one hand, they’re selling for less money as a seller, but they’re also buying for less money as a buyer. So I think sellers need to reexamine their own thinking about what happens in a down market. At the moment that seems pretty far away given how hot the housing market is, but if house prices start to fall, this kind of evidence may come back into vogue again.
Are you doing any follow-up research?
What we’re doing now is looking directly at the question of housing bubbles and really trying to understand what happens in good markets. Our previous research and most research in the housing area is all about focusing on downturns. The research that we’re doing now is looking at very strong markets, like we’re seeing today, and trying to understand to what extent psychology plays a role in booms in the housing market. We’re also contrasting that with commercial real estate and trying to understand how housing reacts similarly to and differently from sales of commercial properties.
Chris Mayer is the Paul Milstein Professor of Real Estate and director of the Paul Milstein Center for Real Estate at Columbia Business School.