標題: Production forecasting of Taiwan's technology industrial cluster: A Bayesian autoregression approach
作者: Lee, JC
Hsu, PH
Wang, CH
Lai, HC
統計學研究所
Institute of Statistics
關鍵字: industrial clusters;vector autoregression;Bayesian vector autoregression;forecasting;Taiwan
公開日期: 1-六月-2005
摘要: This study proposes a forecasting method that combines the clustering effect and non-informative diffiuse-prior Bayesian vector autoregression (NDBVAR) model to forecast the productions of technology industries. Two empirical cases are examined to verify the proposed method: the semiconductor industry and computer manufacturing industry in Taiwan. It is found that the NDBVAR model outperforms the other three conventional time series models including the autoregression (AR), vector autoregression (VAR), and Litterman Bayesian VAR (LBVAR) models. Moreover the NDBVAR model also outperforms the forecast reports from leading market information providers over the past several years. The forecasting method proposed is therefore concluded to be a feasible approach for production prediction, especially for technology, industries in volatile environments.
URI: http://hdl.handle.net/11536/14407
ISSN: 0825-0383
期刊: CANADIAN JOURNAL OF ADMINISTRATIVE SCIENCES-REVUE CANADIENNE DES SCIENCES DE L ADMINISTRATION
Volume: 22
Issue: 2
起始頁: 168
結束頁: 183
顯示於類別:期刊論文


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  1. 000231890500005.pdf