Comparison of Forecasting Performance in Multivariate Nonstationary Seasonal Time Series Models Seong, Byeong-Chan;
This paper studies the analysis of multivariate nonstationary time series with seasonality. Three types of multivariate time series models are considered: seasonal cointegration model, nonseasonal cointegration model with seasonal dummies, and vector autoregressive model in seasonal differences that are compared for forecasting performances using Korean macro-economic time series data. The cointegration models produce smaller forecast errors in short horizons; however, when longer forecasting periods are considered the vector autoregressive model appears preferable.
Seasonal time series;seasonal cointegration;vector autoregression;seasonal dummies;
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