• Title/Summary/Keyword: 차분벡터자기회귀

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Causal Analysis between the Korean and the U.S. Monthly Business Conditions (한미 월간 경기동향의 선행성 분석)

  • Kim, Tae-Ho
    • The Korean Journal of Applied Statistics
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    • v.22 no.1
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    • pp.17-28
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    • 2009
  • This study attempts to perform the statistical test for the causality between the Korean and the U.S. business conditions in association with the lead-lag relationship between the domestic stock price and the business condition. Their causal relationships are clearly identified after the outbreak of the IMF financial crisis. The vector autoregression for the corresponding period appears to reflect the strong interrelationships between the market variables and the dependency of the domestic business conditions on the U.S. market. The estimation results validate the leading effect of the stock price and the U.S. business behavior.

Comparison of Forecasting Performance in Multivariate Nonstationary Seasonal Time Series Models (다변량 비정상 계절형 시계열모형의 예측력 비교)

  • Seong, Byeong-Chan
    • Communications for Statistical Applications and Methods
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    • v.18 no.1
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    • pp.13-21
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    • 2011
  • 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.