다변량 비정상 계절형 시계열모형의 예측력 비교

Comparison of Forecasting Performance in Multivariate Nonstationary Seasonal Time Series Models

초록

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.

키워드

Seasonal time series; seasonal cointegration; vector autoregression; seasonal dummies; 계절형시계열; 계절형공적분; 벡터자기회귀; 계절형가변수
제목
다변량 비정상 계절형 시계열모형의 예측력 비교
제목 (타언어)
Comparison of Forecasting Performance in Multivariate Nonstationary Seasonal Time Series Models
저자
성병찬
DOI
10.5351/CKSS.2011.18.1.013
발행일
2011-01
저널명
Communications for Statistical Applications and Methods
권
18
호
1
페이지
13 ~ 21