Tyler Cowan asks, "Why does anyone support private macroeconomic forecasts?"
I've long found the market for such forecasts to be a puzzling practice…. Even if some forecasts are quite useful, what's the value of supporting a marginal or additional forecast? Is the next forecast to come along so much better? Forecasts would seem to be the classic example of a public good.
Given my interest in turning scanning from a private resource into a public good, Tyler's question caught my eye. He suggests that it's not about getting better knowledge at all, but about something more like social status: perhaps
outsiders pay for the forecast to join a more exclusive club of clients with other privileges. It's a bit like how art galleries won't sell their best pictures to complete outsiders but instead ask that you "pay your dues" by being a loyal customer for years. In other words, it's an arbitrary fee to enforce price discrimination, backed by some plausible pretext.
Under a related model, the firm pays for the forecast as a means of generating publicity, signaling its size, seriousness, and audience, and in general marketing itself to outside clients. It is unclear who bears the final incidence of these expenditures, the firm or the clients, but still "forecasting isn't about knowledge," as Robin Hanson would have said to the oracle at Delphi.
In other words, the "utility" of macroeconomic forecasts doesn't come from the actual information you get by buying them, but from the signal buying the forecasts sends to competitors about your seriousness. I've heard similar kinds of arguments about futures and scenario work– that Hermann Kahn's work on nuclear scenarios in the 1960s was intended not just to improve the Joint Chiefs' or SAC's thinking, but to make the Soviets worry about what we going to do in the future– and I think there are almost always local reasons for engaging futurists that don't have much to do with the official reasons you hire futurists. (Indeed, the really good consultants are able to figure out these reasons, and to adjust their engagements accordingly.)
Bruce Bartlett proposes another answer:
Why Tyler may not realize is that forecasting companies do far more than generate aggregate data; they also produce a vast amount of industry specific data that is enormously useful for investors, managers and others that need to know how a particular industry is expected to perform given the forecast for GDP, inflation etc.
In some cases, the industry data may even contribute to price collusion.
I should note that there's an excellent study of futures orientation, forecasts and uncertainty in forestry— a profession that sees itself as managing processes that play out over centuries– but we could use many more studies of how our work is really used.