Do professionals’ inflation forecasts incorporate the beliefs of others? A functional data approach

Abstract:

We apply functional data analysis to survey expectations data, and show that functional principal component analysis combined with functional regression analysis is a fruitful way of capturing the effects of others’ forecasts on a respondent’s inflation forecasts. We estimate forward-looking Phillips curves on each respondent’s inflation and unemployment rate forecasts, and show that for nearly half of the respondents, the forecasts of others are important. The functional principal components of the cross-sectional distributions of forecasts are shown to capture characteristics other than the mean or consensus forecast, and include forecaster disagreement.