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by klochner 3481 days ago
Any concerns about adverse selection?

I'd want to use OpenDoor if their pricing model came in above what I could reasonably get in the market, and would be more likely to wait it out if they came in low.

3 comments

I think that most would say that about any kind of offer. In practice, most people want to sell their homes quickly and are nervous about turning away fair offers because they might not see a better one. You might as well be saying that you overvalue your home and never plan to sell, which is unlikely. :)

I don't know if OpenDoor is "the answer," but it bothers me that homeowners are often punished by having to work locally, where their skills are unlikely to remain ideal for the area over many years, or work remotely, which not every career allows and not every personality is suited. Being able to sell a home so quickly is even better than having a month-to-month lease. Presumably OpenDoor's higher fees are something employers could start to pay for as part of relocation (and large employers might negotiate volume rates.)

I'm an economist at Opendoor — yes, adverse selection is a big concern! A few things to note:

1. Every time we improve our valuation model, we limit the scope of adverse selection. A more accurate model means there is less tail in the error distribution, which means we are less like to acquire a home we have mistakenly overvalued. As we improve our model accuracy over time through feature modifications and training on more data, the adverse selection problem will partially self-correct.

2. Every time we reduce our fees, we limit the scope of adverse selection. Improvements to our operational efficiency mean we face lower costs, which over time will allow us to offer fees more on par with or below current market norms. When we offer high fees we run the risk that the only ones accepting those offers are those where we've missed something important about the home. Fee reductions help us limit the scope of this problem, and buy more typical homes.

3. Adverse selection is only possible in the context of asymmetric information. Anything we can do to reduce information asymmetries (i.e. better data collection and vetting up front) will reduce the possibility of adverse selection. We're working on this.

4. Adverse selection isn't a problem limited to institutional buyers like ourselves. Any time someone makes an offer on a home, and that offer is accepted, the buyer risks adverse selection. See for instance the "winner's curse." We can do better than the average buyer at solving this problem so long as we are better at information collection and valuation.

5. Lastly, the main economic prediction of adverse selection is that buyers will take adverse selection risk into account by bidding low, which means that a certain amount of otherwise mutually beneficial trade will fail to occur because buyers bid below their true valuations. To the extent we can reduce information asymmetries and help solve adverse selection, we can truly be a market maker by enabling additional mutual beneficial trade than would happen without us.

Across thousands of homes, we have a pretty good sense of the costs here. Since we do the full home inspection before close, it's not as bad as you might think. We've learned to ask about and look for the obvious things (airplane noise, busy streets, recent crime, terrible new neighbors)
How can you know a seller is telling the truth RE: matters that are hard to validate in an inspection, e.g. terrible neighbors?
The sellers are required to disclose any issues like this, ex. if the police were forced to be called to their neighbors, etc. Other neighbors in the area would know about "terrible neighbors" so if this came out, they could sue the sellers and more importantly the selling real estate broker.
Is there a set of public domain resources for police calls by neighborhood and type?
Trulia seems to be using such info to create color-coded crime maps.
So ironically that's a feature my cofounder/CEO at Opendoor Eric Wu launched while he was at Trulia after they acquired his last company.