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A Study on Price Forecasting of the Milkfish and Tilapia
|關鍵字:||Milkfish;虱目魚;Tilapia;Price Forecasting;Three-Stage Least Squares;System Method;ARIMA;Price Simulation;Aquatic Products by Breeding;吳郭魚;價格預測;三階段最小平方法;體系法;ARIMA時間數列分析;價格模擬;漁產品養殖||出版社:||農業經濟學系||摘要:||
The influence of quantities of aquatic products by breeding to their prices has a phenomenon of time lag that is reflected by its biological characteristics. The appearance of things comes into existence as the cobweb theory of economics. Consequently, the price of aquatic products by breeding has been seriously impacted, the income of fishing population affected, and development of fishery industry blocked.
Because of the conditions as set out above, the government has made a lot of price stabilizing policies about aquatic products not only to ensure a fair and reasonable income for fishing population in particular, but also maintain steady commodities prices in general. To establish correct policies and proper production plans, the most important premise we have is to catch well the trend of price and quantity variation. For this reason, the objectives of this study were to explore the supply－demand behaviors of aquatic products, so as to enhance the ability of price forecasting.
This study used three modes－Naive Mode, Extrapolation Mode, and ARIMA (Auto-Regression Integrated Moving-Average) Mode to estimate the equations of supply, demand, and marketing for Milkfish and Tilapia by Three Stage Least Squares (3SLS) of system method. Based on the results obtained from estimation, it is summarized as follows:
1. Parameters of fry and fishmeal of Milkfish and Tilapia displayed noticeable and slightly noticeable after proving by system methods. According to this result, the government should pay attention to the prices of fry and fishmeal and the trend of their variations. Otherwise, the costs of breeding will be increased, interest of breeding lowered, and the market equilibrium affected. Meanwhile, the parameter of retail price of Milkfish and Tilapia showed slightly noticeable, after proving a national income increased. The result, therefore, indicated that Milkfish and Tilapia were normal goods.
2. At the aspect of simulation, the result of ARIMA Forecasting Mode was superior to Naive Forecasting Mode and Extrapolation Forecasting Mode.
3. Regarding the price forecasting of Milkfish, on one hand, Naive Mode made the best performance of price forecasting. The second was Extrapolation. All of the three modes of price forecasting could capture the trend of price variations correctly. On the other hand, concerning the price forecasting of Tilapia, Extrapolation Mode had the most excellent performance of price forecasting among the three, though all of them could very correctly provide in hand the trend of price variations.
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