New York Fed: "Forecasting Inflation with Fundamentals . . . It’s Hard!"

From the Federal Reserve Bank Of New York's Liberty Street Economics blog:

 Controlling inflation is at the core of monetary policymaking, and central bankers would like to have access to reliable inflation forecasts to assess their progress in achieving this goal. Producing accurate inflation forecasts, however, turns out not to be a trivial exercise. This posts reviews the key challenges in inflation forecasting and discusses some recent developments that attempt to deal with these challenges.

        The behavior of U.S. inflation measures has changed substantially over time. The chart below plots the inflation rates measured by the deflators for personal consumption expenditure with and without food and energy expenditures—or PCE and core PCE, respectively. Inflation rates have varied over the past five or so decades, averaging about 3 percent in the 1960s, 8 percent in the 1970s, 4 percent in the 1980s, and 2 percent since the 1990s. Essentially, the long-run trend in inflation increased during the 1970s, reaching peaks around 1974-1975 and 1980; decreased after 1982-1983; and stabilized at about 2 percent in the early 1990s, where it has remained. (See Cogley and Sargent [2005] and Cogley, Primiceri, and Sargent [2010] for reviews of past inflation behavior.)




        A time-varying underlying inflation rate complicates inflation forecasting tremendously. To illustrate this, suppose a forecaster attempts to forecast inflation with a model that relies on lags of inflation—that is, past inflation—under the assumption that long-run inflation remains unchanged (an autoregressive model ). The resulting forecasts for future inflation rates will be anchored by the assumed unchanged long-run inflation rate. Now, if in reality the long-run rate changes, then the inflation forecasts from the autoregressive model will be biased because the model assumes that there is a tendency for inflation to converge back to the “old” long-run inflation rate. Indeed, in this case one would do better by using the current inflation rate as a predictor for future inflation (a random walk model) because this would not build this false anchoring into the forecast. Stock and Watson (2007) show that inflation is well described by an agnostic model in which a slowly evolving trend is extracted from inflation itself and shocks to this estimated inflation trend are allowed to be larger or smaller from period to period. When the most recent estimate of this inflation trend is used as a predictor for all future inflation rates, it outperforms a range of alternative models, suggesting that adding some form of structural change to predictive models helps improve inflation forecasting.....MORE