A quantile regression approach to study the impact of aluminium prices on manufacturing sector of India during COVID era. (2022)

• Record Type: Journal Article
• Authors: Mehta, Kiran; Sharma, Renuka; Vyas, Vishal
• Is Part Of: Materials today. Volume 65:Part 8(2022)
• Page Start: 3506
• Page End: 3511
• Publication Date: 2022
• Subjects: Aluminium -- Covid19 -- Manufacturing Index -- Quantile regression -- India; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.06.087
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Metal prices have a significant impact on the manufacturing sector. Aluminium as raw material and an essential component of various manufacturing processes have a considerable effect on the cost and price of manufactured items. Therefore, the present study focuses on the influence of aluminium price movements on India's manufacturing sector during the COVID period. The current research is empirical and examines the causal relationship between aluminium prices and the manufacturing index in India during the COVID era. Different methodologies are used to study aluminium price fluctuations. Many earlier studies focused on forecasting aluminium prices, while others looked at the relationship between aluminium and other indices or commodities. The current research uses a quantile regression approach to accomplish the study's objective. Quantile regression is a nonlinear data model that may provide lower or higher results than the conditional mean. This model is appropriate in situations when linearity is not expected. The study's findings are helpful for companies processing or using aluminium in their production processes, all manufacturing industries where aluminium is a crucial component of raw material, and regulators and policymakers working on boosting the aluminium industry and other stakeholders.