Terrible news arrived today in our small community of economists: the bright young Portuguese economist and an old friend from my Northwestern days, Tiago Pires, passed away suddenly over the weekend. Tiago is a structural IO economist at the University of North Carolina-Chapel Hill who has written on demand estimation particularly in the face of search costs. Everyone who has met him can tell you that he was always in good spirits, and that he has been a true friend and useful sounding board for many of us. Friends tell me that Tiago had been making the rounds at the industrial organization conference IIOC just this week, and seemed to be in perfect health. To honor Tiago, let’s discuss Tiago’s job market paper from a couple years ago.
The basic idea, which runs through much of Tiago’s work, is that properly evaluating demand for products, and hence the effects of mergers or other IO policies, depends fundamentally on costly search. The basic idea is not new – it can be seen as far back as the great George Stigler’s 1961 paper on the economics of information – but the implications are still not fully drawn out.
Consider shopping for laundry detergent. Rare is the shopper who, like Honey Boo Boo’s family, searches for coupons and compares relative prices every week. Rather, most weeks you likely just show up at your usual store, perhaps glancing at the price of your usual detergent as you pass the aisle; there could be a great sale on some other detergent, but you’d never know it. As you start to run low on detergent at home, you’re more likely to actually stroll down the whole detergent aisle, perhaps checking the price of few more options. On occasion, the detergent makers sponsor an ad or a promotion at the end of the aisle, and you learn the price of that particular product cheaply. If the price is good and you know the price, you might buy some detergent, though not too much since the cost of searching in the future must be traded off against the cost of storing a bunch of detergent in your closet.
Tiago models shoppers who proceed exactly in that fashion: on the basis of how much detergent you have left, you search a handful of detergent prices, and you buy if the price is right. When you are almost out of detergent, you might search a bunch of prices. When you have quite a bit of detergent, you rationally only buy if you happen to see your usual favorite on sale. The data match the basics of the model: in particular, you are more likely to buy your “usual” brand when you have a lot of detergent left than when you are almost out, since it’s not worth bothering to search prices in the former case. This combination of costly search plus changing household “inventory” means that standard static analysis gives a very misleading portrait of what consumers do. First, elasticity estimates will be screwed up: if rivals shift their price up and down, and I don’t even notice the changes, you may think my demand is very inelastic, but really it’s just that I am not searching. Second, price promotions in conjunction with ads that lower search costs aren’t actually that useful for revenue or profit: the shopper would have eventually checked prices when their detergent stock ran low, and the ad just causes them to check prices early and buy if there is a good enough sale, stealing sales away from future shopping trips. Third, popular brands should do what they can to keep consumers from running low in their stock, such as making it obvious via packaging how much detergent is left, or trying to sell bigger packages. The reason is that only the consumer who is low on stock will bother to search the prices of competitors.
Tiago has used search costs is a number of other papers. With Guillermo Marshall, he studied how stores trade off convenience (being located near consumers, roughly) with quality (being a nice supermarket rather than a convenience store, roughly): as travel costs increase because of traffic or bad weather, you see more stores invest in increasing convenience rather than quality, in surprisingly big economic magnitudes. Terrible convenience stores in the ‘hood are partially driven by market frictions due to high transportation costs, not just differences in products demanded or in income! With Fernando Luco and Mahraz Parsanasab, he studies how the Internet has affected the film industry by changing both search costs for learning about what movies might be worth seeing, as well as changing the market structure of the film industry via Netflix, piracy and similar. Looking across countries, internet access improves film industry revenue and decreases market concentration as the internet becomes common, but broadband access has no such revenue effect, and actually makes market concentration worse as it becomes common. Here’s to Tiago’s memory, and to the continued study of markets using our most powerful tool: theoretically-sound models of structural choice combined with data about the operation of real markets!
The costly search paper described above can be found in its most recent working paper version here: November 2015 working paper (No RePEc IDEAS version).