Hassani, H., Heravi, S. and Zhigljavsky, A., 2012. Forecasting UK Industrial Production with Multivariate Singular Spectrum Analysis. Journal Of Forecasting.
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In recent years the singular spectrum analysis (SSA) technique has been further developed and applied to many practical problems. The aim of this research is to extend and apply the SSA method, using the UK Industrial Production series. The performance of the SSA and multivariate SSA (MSSA) techniques was assessed by applying it to eight series measuring the monthly seasonally unadjusted industrial production for the main sectors of the UK economy. The results are compared with those obtained using the autoregressive integrated moving average and vector autoregressive models. We also develop the concept of causal relationship between two time series based on the SSA techniques. We introduce several criteria which characterize this causality. The criteria and tests are based on the forecasting accuracy and predictability of the direction of change. The proposed tests are then applied and examined using the UK industrial production series.
|Uncontrolled Keywords:||singular spectrum analysis; forecasting; causality; industrial production series|
|Subjects:||Social Sciences > Economics|
Science > Mathematics
|Deposited By:||Dr Hossein Hassani|
|Deposited On:||02 May 2012 09:23|
|Last Modified:||07 Mar 2013 15:55|
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- Forecasting UK Industrial Production with Multivariate Singular Spectrum Analysis. (deposited 03 Apr 2012 15:59)
- Forecasting UK Industrial Production with Multivariate Singular Spectrum Analysis. (deposited 02 May 2012 09:23) [Currently Displayed]
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