On predicting the semiconductor industry cycle: a Bayesian model averaging approach
Wen-Hsien Liu and
Shu-Shih Weng ()
Additional contact information
Shu-Shih Weng: National Chung Cheng University
Empirical Economics, 2018, vol. 54, issue 2, No 14, 673-703
Abstract This study considers the model uncertainty and utilizes the Bayesian model averaging (BMA) approach to identify useful predictors of the semiconductor industry cycle from a list of 70 potential predictors. The posterior inclusion probabilities, posterior means, and posterior standard deviations over the period of 1995:05–2012:10 are estimated and consequently used to identify the main determinants of the industry cycle. It is found that the Philadelphia Semiconductor Index and total inventories in various downstream industries have important roles in signaling the industry growth. The results from an out-of-sample forecasting exercise also reveal the predictive potential and usefulness of BMA for the long-term prediction.
Keywords: Bayesian model averaging; Semiconductor; Industry cycle (search for similar items in EconPapers)
JEL-codes: C11 C53 L16 L63 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s00181-016-1198-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:spr:empeco:v:54:y:2018:i:2:d:10.1007_s00181-016-1198-x
Ordering information: This journal article can be ordered from
http://www.springer. ... rics/journal/181/PS2
Access Statistics for this article
Empirical Economics is currently edited by Robert M. Kunst, Arthur H.O. van Soest, Bertrand Candelon, Subal C. Kumbhakar and Joakim Westerlund
More articles in Empirical Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().