摘要：The study aims to explore the feasibility of adopting for inflation forecasting a sophisticatedexpert system normally used in routine outlier detection and deseasonalization of time series.Known as TRAMO/SEATS expert system, this twin program is a fully automatic procedurethat extracts the trend-cycle, seasonal, irregular and certain transitory components of highfrequency time series via the so-called ARIMA-model-based method. The results of the studyreveal the feasibility of the use of the technique for routine inflation forecasting. The automaticmodel building capability of TRAMO/SEATS is exploited to arrive at an ex-ante model that hasthe ability to generate optimal forecasts. The results show the ability of the final model toforecast inflation with remarkable accuracy.Keywords: Inflation; inflation rates; economic forecasts; economic forecasting; forecastingtechniquesDOI: 10.3860/ber.v20i1.1665DLSU Business & Economics Review 20.1 (2010), pp. 1-11
