Using ARIMA and Vector Auto Regression Model to Analyze Revenue of the Semiconductor Industry in Hsinchu Science Park

• Main Authors: Lee, Tsung Han, 李宗翰
• Other Authors: Chan, Haiso
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/89354497876568884656

碩士 === 國立交通大學 === 管理學院管理科學學程 === 102 === Since Hsinchu Science Park (HSP) had initiated from 1980, over the past thirty-ish years, its successful expansion had be playing a major role of shaping the entire technology industry of Taiwan. It created the industry cluster effect with technological innovation and specialization, which ranks Taiwan one of the biggest semiconductor nations in the world. Among the six major industries in the Science Park, the semiconductor industry accounted for 70% of the entire revenue. And in Taiwan's semiconductor industry, HSP almost account for nearly 50 percent of entire industry. The revenue is a reflection of achievements, but also as important indicator to the rise or fall to the industry. This research focuses on semiconductor’s revenue from firms in Hsinchu Science Park based on the data (1983 to 2012) of industry output and amount of R &; D expenses providing by Hsinchu Science Park Administration. Then those data were processed with software, EView 8.0, to do time series prediction of matching the correct study model, and ultimately to create the forecast model for the entire semiconductor industry by using autoregression integrated moving average (ARIMA) and vector autoregression (VAR). The research shows: 1.VAR model does a better job in predicting the revenue than other ARIMA models. By taking the data of capital amount and R&;D expenses into our study, the multivariable prediction model has better forecast capability than the single variable prediction model. 2.The test results of Granger shows that capital expenditures and amount invests in R&;D affect the future revenue to the semiconductor industry. Capital expenditures and amount invests in R&;D are leading indicators of revenue forecast. The semiconductor industry is highly capital-intensive and technology-intensive industries. 3.This research model produces more accurate data to if the year target is more recent which could be a good reference data to both the industry firms and the government in making decision