Uncertainty over models and data: the rise and fall of American inflation

An economic agent who is uncertain of her model updates her beliefs in response to the data. The updating is sensitive to measurement error which, in many cases of macroeconomic interest, is apparent from the process of data revision. I make this point through simple illustrations and then analyze a recent model of the Federal Reserve's role in U.S. inflation. The existing model succeeds at fitting inflation to optimal policy, but fails to link inflation to the economic trade-off at the heart of the story. I modify the model to account for data uncertainty and find that doing so ameliorates the existing problems. This suggests that the Fed's model uncertainty is largely overestimated by ignoring data uncertainty. Consequently, now there is an explanation for the rise and fall in inflation: the concurrent rise and fall in the perceived Philips curve trade-off.