On the Accuracy of Time-Series, Interest Rate, and Survey Forecasts of Inflation

Abstract

There has been much work examining and evaluating different methodologies in forecasting inflation. For example, Fama (1975, 1977) develops an interest rate model to predict the 1-monthahead rate of inflation using the CPI. Fama and Gibbons (1982, 1984) modify the interest rate model to account for a nonconstant real rate of interest and compare it to a univariate timeseries forecasting model and to the Livingston forecasts. Carlson (1977a, 1977b) and others also analyze the consensus forecasts from the Livingston survey pertaining to multiperiod forecasts of inflation. Pearce (1979) considered the Livingston survey and time-series forecasts. Our purpose in this paper is to investigate further the relative forecasting ability of three different methodologies. In contrast to previous studies that have generally used the CPI to measure inflation, our analysis uses the implicit GNP deflator. This modification is motivated largely by the fact that calculations of the CPI inflat'n rate often are distorted greatly by changes in relative prices (e.g., Blinder 1980; Fischer 1981). This paper compares the accuracy of three different inflation forecasting procedures. These include a univariate time-series model, an interest rate model based on the methodology of Fama and Gibbons, and the median forecasts derived from the American Statistical Association-National Bureau of Economic Research survey. The evidence presented is based on ex ante forecasts of quarterly inflation rates using the GNP deflator for the period 1970:11984:11. Based on the evidence presented, the general conclusion is that the survey forecasts provide the most accurate inflation forecasts.