期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2021
卷号：3
期号：7
页码：2628-2640
DOI：10.35629/5252-030724762481
语种：English
出版社：IJAEM JOURNAL
摘要：Steel plays a crucial role in the economic development of a nation. It is the most widely used metal in the modern society and plays a key role for improving the standard of living, industrialization and urbanization. Steel intensity in the economy is an indicator of the state of the economic development of a country as the per capita consumption of steel in the developed nations is higher compared to the same in the developing nations. As steel is an intermediate product used for producing finished goods, its consumption is arrived at through the method of derived demand. As a result, predicting the demand for steel is more difficult and complex as compared to several other products. Forecasting demand for steel in India is considered necessary as steel industry is capital intensive with longer gestation periods. In view of this, unless actions are taken much in advance for enhancing the capacity of steel making, it would be difficult to meet the domestic demand for steel. It is also very important to develop a sophisticated forecasting technique for steel consumption as well, in order to match the demand and consumption levels. In the present study, forecasting steel demand in India has been carried out through aggregative method, which is a top down approach. In this method, a relation between steel consumption and major economic parameters has been established. Various forecasting techniques like curve fitting, correlation and regression have been explored for arriving at the forecasts. Out of these, Auto Regressive Integrated Moving Averages (ARIMA), which are time series multivariate models have been found to be suitable for the present study. Data sets of Gross Domestic Product (GDP) of India for 70 years, consisting of primary, secondary and tertiary sectors of the economy and steel consumption from 1950 to 2019 are used for the analysis.
