Inverse Demand for Meat and Fishery Products in Taiwan

臺灣漁畜產品逆需求之研究

江福松(Fu-Sung Chiang) ； 李仲英(Jonq-Ying Lee)

《臺灣水產學會刊》 27卷2期 (2000/06) Pp. 139-147

https://doi.org/10.29822/JFST.200006.0006

摘要

本研究比較不同時間序列模式用來預測印度洋長鰭鮪之漁獲量。以月別漁獲量為因變數及經一般線性模式法校正後的月別單位努力漁獲量為自變數，建立三類時間序列模式，分別為：自我回歸整合移動平均模式、回歸模式涵自我回歸整合移動平均誤差項及轉換函數模式。月別漁獲量序列分別以1968-1996年為內部模擬區間及1997年為外部預測區間。六種統計決策值分別用來比較三類模式的預測能力。結果顯示，三類時間序列模式皆能模擬漁獲量序列的年內季節變動性和年間的震盪，且時間延遲並不存在於月別漁獲量和其相對的月別標準化單位努力漁獲量之間。個別的統計誤差決策值比較顯示，在內部模擬區間，雙變量模式略優於單變量模式；在外部預測區間，單變量模式則較優於雙變量模式。但全部統計百分誤差決策值比較之下，雙變數之回歸模式涵自我回歸整合移動平均誤差項則在預測印度洋長鰭鮪漁獲量上似較優於單變數之自我回歸整合移動平均模式，但具有較保守的預測值。

關鍵字

鹿特丹逆需求模型 ； 漁畜產品需求 ； 模型設定比較 ； 臺灣

並列摘要

Time series models were used and compared to forecast commercial catch of albacorein the Indian Ocean.Three time series models,i.e.,auto-regressive integratedmoving average(ARIMA),regression model with the ARIMA error(RAE)and transfer functionnoise(TN)models were built.Monthly catch was used as dependent variable andadjusted catch per unit effort(ACPUE)standardized by the general linear model was usedas the independent variable in the RAE and TN models.Catch data 1969-1996 were usedas the inner simulated period,and 1997 data were used in the outer forecasting period.Six statistical criteria,ME,MPE,MAE,MAPE,RMSE and RMSPE were used to evaluate theperformance of the built models.The results indicate that three selected time seriesmodels can closely trace the pattern of the yearly periodicity and the fluctuation of thecatch series.Time delay did not exist between the catch and the ACPUE series.Thebivariate model(TN,RAE)used in the inner simulation and the ARIMA model used in outerforecasting seems sound by the individual comparison of the statistical criteria in thepresent study.For overall comparison the bivariate RAE model seems best among thethree built time series models using in forecasting the albacore catch in the Indian Ocean,but a conservative prediction may be observed during forecasting using RAE.

並列關鍵字

Rotterdam Inverse Demand Model ； Demand for Meat and Fishery Products ； Model Specification Comparison ； Taiwan