Interview with Preston McAfee on market design in tech firms

Econ focus, from the Richmond Fed, has an interview with Preston McAfee:

Fourth Quarter 2018, INTERVIEW
R. Preston McAfee
Article by: David A. Price

Here are two questions and answers, the first about market design, and the second about when it might be wise to avoid getting involved in it...

EF: In both your academic work and in your published work as a corporate economist, you've done a lot of research on market design, including auction design. And of course, you collaborated on the design of the FCC wireless spectrum auctions. What are some of the main things you've learned about designing markets?

McAfee: First, let's talk about just what market design is. It's a set of techniques for improving the functioning of markets. Specifically, it uses game theory, economic theory, experimental research, behavioral economics, and psychology, all of those disciplines, to make markets work better.

In politics, you have people who don't want to use markets, and then you have people who say just let the market do it — as if that didn't have any choices attached to it. But in fact, often how you make a market work determines whether it works well or poorly. Setting the rules of the game to make markets more efficient is what market design is all about. Thus, whether to hold an auction, whether to sell or lease, who bears responsibility for problems, and what information is communicated to whom are all questions answered by market design. At least four Nobel Prizes have gone for developments in this area.

One thing we learned is to design for mistakes by participants. People will make mistakes, and to encourage participation and efficient outcomes, it is desirable that those mistakes not be catastrophic.

Moreover, there is a trade-off between the potential efficiency of a market and the generation of mistakes. Give people the ability to express complex demands, for example, and the potential efficiency rises, because people can express exactly what they want. But the number of mistakes will rise as well, and the actual performance can decline. I often find myself supporting a simpler design for this reason; I push back on complexity unless that complexity buys a lot of efficiency.

When we designed the PCS [personal communications services] auctions, the spectrum auctions, we were aware that if you made them complicated, people weren't likely to function that well. We had empirical evidence of that.

Take a situation where you have seven properties up for auction. One regime is that I bid independently on each of the properties, and if I am the winning bidder on all seven, I get the seven. Another is to allow the bidder to submit a contingent bid — to say I only want all seven. That's called package bidding or combinatorial bidding. We were aware that in practice those don't work so well, because it winds up taking a long time to figure out who should win what.

But there is some potential loss from not having a package. Because if, let's say, I'm selling shoes, most people don't have much use for a single shoe. So you would not want to sell the shoes individually, even though there are a few people who want only the left shoe or the right shoe. And in fact, I am a person who would like to get different sizes in a left shoe and a right shoe. So there's this trade-off between simplicity, which makes it easier for most, and expressiveness. There is value in that simplicity not only in terms of getting to an answer more quickly, but also in helping bidders avoid mistakes.

Another example is a second-price auction, where you don't pay what you bid; if you're the highest bidder, you pay the second-highest bid, as opposed to paying your own bid. It has a certain resilience to it. There was a guy who actually submitted a bid that was 1,000 times higher than he intended. Just added three zeroes by accident. But in that auction, if you're paying not your bid but the next highest bid, it takes two to make the mistake in order for that to actually cause him to go broke. He wouldn't have gone broke under the second-price auction, whereas he would under the first-price auction. In that specific instance, we had put in a withdrawal rule that allowed him, at some penalty but not a ruinous penalty, to withdraw.

EF: Much of the economic research that has been publicly discussed by technology companies has focused on outward-facing decisions such as pricing and, as we discussed, market design. Are tech companies also using research to structure the incentives of their employees, and is there more they can be doing?

McAfee: I've hired a lot of people over the years, more than 50 anyway, probably more than 60. And among those have been several people, some quite distinguished economists, who decided that the first thing they wanted to do was get involved in compensation.

Your leverage regarding compensation is greatest in the sales force. If you've got a salaried engineer, let's say, there's not as much you can do. But in sales, the financial incentives are large and strong. I try to prevent economists on my teams from ever messing with sales force compensation, because there's no quicker way to be fired. The sales force is very persuasive. That's their job; they're supposed to be persuasive.

There was a case where we had an executive vice president come to us and say, "We really want to run some experiments and learn about the sales force." As I said, I did my best to keep my team out of such matters, but when management comes to me and asks for help, I feel I have to oblige. Not only that, I had people chomping at the bit wanting to get involved. We designed some incentives and then what happened next was fully predictable, which is that the EVP got fired. Fortunately, my team was safe because it hadn't come from them.

My teams have worked with HR on other issues. There's always some ongoing work with HR. It can be on promotion, recruiting, collaborating — anything but compensation.