鋼鐵價格決定機制及影響因素分析

An Empirical Study on the Pricing Mechanism of International Steel Prices

林詩彥(Shih-Yen Lin)

指導教授 ： 林師模

中原大學/商學院/國際貿易研究所/碩士(2006年)

https://doi.org/10.6840/cycu200600080

摘要

鋼鐵業為一國之基礎工業，產業特性為資本、技術與能源密集；此外，鋼鐵業的產業關聯性高，緊密聯結經濟體系中之上游原物料與下游工業。基於鋼鐵工業的發展與其他產業間關係緊密並會影響一國之工業化程度，其經濟地位極為重要，然而鋼鐵業的成長亦與世界經濟息息相關，2001年，全球鋼鐵市場因供需失衡以及經濟萎縮則進一步造成對鋼鐵需求的銳減。有鑑於鋼鐵對一國經濟發展的重要性，本研究首先就鋼鐵分類與鋼鐵市場特性、產業發展逐一討論。隨後，依據前述分析選取影響鋼鐵價格之重要因素(例如：全球粗鋼產量、全球鋼鐵價格指數、煉鋼原料價格指數、中國焦炭產量、中國重工業產值等)進行實證分析，希望藉以瞭解鋼鐵市場中鋼鐵價格及其影響變數間的互動關係。本研究使用E-views軟體，先對變數作單根檢定，並以VAR 模型估計變數間的互動關係。之後，依據變數間的相互影響關係再分為四組變數加以探討，各分別以VAR 模型進行配適，經配適後若殘差項仍具有異質變異現象，則再進一步結合多變量GARCH(1,1)模型探討。實證結果顯示煉鋼原料與燃煤、焦炭等因素會影響鋼鐵價格，證明煉鋼原料價格與燃料成本上漲時，鋼鐵價格會隨之上升，意謂對煉鋼原料及燃料的需求增加會造成鋼鐵價格上的波動。

關鍵字

多變量GARCH模型 ； 鋼鐵價格 ； VAR模型

並列摘要

Steel industry is the fundamental industry of a country. The highly concentrations of capital, technology and energy are the industrial characters of steel maker. Otherwise, steel industry is with a highly industrial correlation. It closely connects the supplier of raw materials and other industrial demanders in the economic system. The growth of the steel industry not only plays an important role for the development of a country and closely connects with other industries, but also rigidly links the economics of the world. In 2001, the steel market worldwide was declined sharply due to the unbalance between supply and demand, also the economic recession. The present study discussed the products of steel, the characteristics of steel market and the development of steel industry, step by step. And then, according to these topics, we analyzed the important factors that can influence the price of steel. For example, the production of crude steel worldwide, the global steel prices index , the metallic steel price index, the production of coke in China and the heavy industry production in China… etc, are the factors. We proposed to realize the interactive relationships between the price of steel and the variables. The EViews software was used to test the unit root of variables in the present study, and the VAR model was used to estimate the interactive relationships among the variables. Moreover, according to the interactive relationships among the variables, we separated them into four sets to progress the discussion. Each set was fitted in with the VAR model. Through the fitted, if the heteroskedasticity phenomenon was still found in residuals, the multivariate GARCH model was specified to take into account the underlying movements between variables of interest. The empirical results showed that the steel price is affected by the prices of metallic steel, coal and coke. And they verified that the advance of the costs of the metallic steel and fuel has raised the price of steel. It means that the strength of demand for the metallic steel and fuel will cause the price of steel to fluctuate.

並列關鍵字

multivariate GARCH model ； VAR model ； Steel prices

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