Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach

Developments in the global electronics industry are typically monitored by tracking indicators that span a whole spectrum of activities in the sector. However, these indicators invariably give mixed signals at each point in time, thereby hampering efforts at prediction. In this paper, we propose a u...

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主要作者: Chow, Hwee Kwan
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出版: Institutional Knowledge at Singapore Management University 2004
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spelling sg-smu-ink.soe_research-18292018-06-01T03:40:46Z Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach Chow, Hwee Kwan Developments in the global electronics industry are typically monitored by tracking indicators that span a whole spectrum of activities in the sector. However, these indicators invariably give mixed signals at each point in time, thereby hampering efforts at prediction. In this paper, we propose a unified framework for forecasting the global electronics cycle by constructing a VAR model that captures the economic interactions between leading indicators representing expectations, orders, inventories and prices. The ability of the indicators to presage world semiconductor sales is first demonstrated by Granger causality tests. The VAR model is then used to derive the dynamic paths of adjustment of global chip sales in response to orthogonalized shocks in each of the leading variables. These impulse response functions confirm the leading qualities of the selected indicators. Finally, out-of-sample forecasts of global chip sales are generated from a parsimonious variant of the model viz., the Bayesian VAR (BVAR), and compared with predictions from a univariate benchmark model and a bivariate model which uses a composite index of the leading indicators. An evaluation of their relative accuracy suggests that the BVAR’s forecasting performance is superior to both the univariate and composite index models. 2004-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/830 https://ink.library.smu.edu.sg/context/soe_research/article/1829/viewcontent/Forecasting_the_Global_Electronics_Cycle_with_Leading_Indicators_.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Leading indicators; Global electronics cyle; VAR; Forecasting Econometrics Industrial Organization
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Leading indicators; Global electronics cyle; VAR; Forecasting
Econometrics
Industrial Organization
spellingShingle Leading indicators; Global electronics cyle; VAR; Forecasting
Econometrics
Industrial Organization
Chow, Hwee Kwan
Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach
description Developments in the global electronics industry are typically monitored by tracking indicators that span a whole spectrum of activities in the sector. However, these indicators invariably give mixed signals at each point in time, thereby hampering efforts at prediction. In this paper, we propose a unified framework for forecasting the global electronics cycle by constructing a VAR model that captures the economic interactions between leading indicators representing expectations, orders, inventories and prices. The ability of the indicators to presage world semiconductor sales is first demonstrated by Granger causality tests. The VAR model is then used to derive the dynamic paths of adjustment of global chip sales in response to orthogonalized shocks in each of the leading variables. These impulse response functions confirm the leading qualities of the selected indicators. Finally, out-of-sample forecasts of global chip sales are generated from a parsimonious variant of the model viz., the Bayesian VAR (BVAR), and compared with predictions from a univariate benchmark model and a bivariate model which uses a composite index of the leading indicators. An evaluation of their relative accuracy suggests that the BVAR’s forecasting performance is superior to both the univariate and composite index models.
format text
author Chow, Hwee Kwan
author_facet Chow, Hwee Kwan
author_sort Chow, Hwee Kwan
title Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach
title_short Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach
title_full Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach
title_fullStr Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach
title_full_unstemmed Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach
title_sort forecasting the global electronics cycle with leading indicators: a var approach
publisher Institutional Knowledge at Singapore Management University
publishDate 2004
url https://ink.library.smu.edu.sg/soe_research/830
https://ink.library.smu.edu.sg/context/soe_research/article/1829/viewcontent/Forecasting_the_Global_Electronics_Cycle_with_Leading_Indicators_.pdf
_version_ 1770569311865274368