2019/12/04 by Hossein Kamalzadeh, Saeid Nassim Sobhan, Kamalzadeh, Hossein +7
Chemistry · Computer Science · Economics, Econometrics and Finance · #Economic and Technological Innovation #FOS: Computer and information sciences #FOS: Economics and business #General Economics (econ.GN) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Market Dynamics and Volatility #Spectroscopy and Chemometric Analyses #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.1912.02373
openalex publication_date 2019/12/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The steel industry has great impacts on the economy and the environment of both developed and underdeveloped countries. The importance of this industry and these impacts have led many researchers to investigate the relationship between a country's steel consumption and its economic activity resulting in the so-called intensity of use model. This paper investigates the validity of the intensity of use model for the case of Iran's steel consumption and extends this hypothesis by using the indexes of economic activity to model the steel consumption. We use the proposed model to train support vector machines and predict the future values for Iran's steel consumption. The paper provides detailed correlation tests for the factors used in the model to check for their relationships with the steel consumption. The results indicate that Iran's steel consumption is strongly correlated with its economic activity following the same pattern as the economy has been in the last four decades.