The Wall Street Journal notes that the Federal Reserve says it makes its determinations based on what the data tell it, and then the WSJ notes that the Fed has been wildly wrong lately and lays that off to data volatility. The failures, it seems, are in the Fed’s data dependency.
The Fed says it sets policy based on incoming data, especially on inflation and jobs. And those data have been both unreliable and far more volatile than usual….
The WSJ then provides its definition of data dependency:
“[D]ata dependency” has come to mean looking only at recent data, ignoring projections for the effects of interest rates on the economy in future.
The problems with this definition are two. In the first place, projections of the future are just guesses, even if somewhat informed by current data. As a great 20th century American philosopher understood, it’s tough to make projections, especially into the future.
The other problem is that this definition of data dependency wholly ignores realized, empirical data: those that have occurred before “recent.” Decent data reliance requires those past data be included, even if as estimates of the underlying trend through that empirical past into “today” (and some little way into the future).