Editorial
In this paper Friedrich Fritzer, Gabriel Moser and Johann Scharler evaluate the performance of VAR and ARIMA models to forecast Austrian HICP inflation. Additionally, they investigate whether disaggregate modelling of five subcomponents of inflation is superior to specifications of headline HICP inflation. The modelling procedure is to find adequate VAR and ARIMA specifications that minimise the 12 months out-of-sample forecasting error. The main findings are twofold. First, VAR models outperform the ARIMA models in terms of forecasting accuracy over the longer projection horizon (8 to 12 months ahead). Second, a disaggregated approach improves forecasting accuracy substantially for ARIMA models. In case of the VAR approach the superiority of modelling the five subcomponents instead of just considering headline HICP ination is demonstrated only over the longer period (10 to 12 months ahead).