Forecasting Austrian inflation

In this paper we apply factor models proposed by Stock and Watson [Stock, J.H., Watson, M.W., 1999. Forecasting inflation. Journal of Monetary Economics 44 (2), 293-335.] as well as VAR and ARIMA models to generate 12-month out-of-sample forecasts of Austrian HICP inflation and its subindices. We apply a sequential forecast model selection procedure tailored to this specific task. It turns out that factor models possess the highest predictive accuracy for several subindices and that predictive accuracy can be further improved by combining the information contained in factor and VAR models for some indices. With respect to forecasting headline HICP inflation, our analysis suggests to favor the aggregation of subindices forecasts over a forecast of headline inflation itself.