查詢結果分析
來源資料
相關文獻
- 灰色模型應用在國內生產毛額預測之研究
- A Novel Optimal Method for Improving the Predicted Accuracy of GM(1,1) Model
- Prediction of Mean Stress Effect on Fatigue Limit by Grey Model
- 財務分析師,管理當局及統計模式預測準確度之比較研究
- 應用灰色系統模型於半導體封裝測試之研究--以P公司為例
- 消費者信心指數與經濟活動臨近預測
- 資訊產品流通業之銷售預測模式分析
- 臺灣財政收入之預測
- 可能性灰色預測模型在臺灣股市加權指數上之應用
- 語音壓縮標準G.723.1在C62X DSP上的設計
頁籤選單縮合
題名 | 灰色模型應用在國內生產毛額預測之研究=Research on Gross Domestic Product (GDP) Forecasting in the Application of Grey Model |
---|---|
作者 | 楊振昌; | 書刊名 | 樹德學報 |
卷期 | 24 1999.08[民88.08] |
頁次 | 頁103-110 |
分類號 | 517 |
關鍵詞 | 國內生產毛額; 灰色模型; 預測; Gross domestic product; GDP; Grey model; Forecasting; |
語文 | 中文(Chinese) |
中文摘要 | 國內生產毛額(GDP)是一個國家的重要經濟指標,同時也是企業界研判國內景 氣變動的重要指標之一,故政府相關部門及許多研究機構都會進行GDP的預測。GDP的成 長與時間的關係並非線性關係,故勉強使用簡單迴歸分析來預測GDP,極可能造成極大的 誤差。因此大部分的學者以複迴歸分析預測GDP較多,但複迴歸分析自變數的決定並不容 易。 為了克服複迴歸分析的困難度,本研究以民國73年至民國84年新加坡GDP為例,使 用灰色模型預測GDP。經研究結果發現,灰色模型預測精確度高達95.8574%,非常接近顯 著優於簡單迴歸分析法。又灰色模型迴歸精確度高達98.8597%,顯著優於簡單迴歸分析法。 故以灰色模型預測GDP具有高精確性,且沒有複迴歸分析法決定自變數的困難,非常適合 相關單位使用。 |
英文摘要 | GDP is one of the most important indicators for the national economy and for the industry to evaluate the economy performance. Therefore, the governmental related agencies and a lot of research institutions involve themselves in GDP forecasting. The relationship between the GDP growth and time duration is non-linear. As a result, the use of simple regression analysis to GDP forecasting shall very possibly cause extreme errors. Most scholars thereof prefer to using multiple regression analysis for GDP forecasting. However, it is difficult to decide the independent variables of the multiple regression analysis. To overcome the difficulties in multiple regression analysis, the research will focus on using grey model for GDP forecasting by referring to the examples of Singapore GDP growth from 1984 to 1995. The research finds that the accuracy of grey model forecasting reaches high 95.8547%, that is clearly more appropriate than that of simple regression analysis. In addition, the accuracy of grey model regression gets to 98.8597%, apparently more fit than simple regression analysis. Conclusively, the grey model shall be very suitable for related agencies to use for its high accuracy in GDP forecasting and shortages of difficulty in deciding the independent variables like multiple regression analysis. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。