Econometric modeling for the influence of economic variables on secondary copper production in India

The stocks and flows of primary metal resources, and the estimates of so generated secondary scrap metal flows are tracked and analysed utilizing the traditional analytical method of 'material flow analysis'. However, the scrap availability and hence the secondary metal production is also influenced by fluctuating economic conditions. Here we utilize the autoregressive distributed lag approach to model the influence of selected economic variables on secondary metal production and hence the scrap availability in the country. We find electricity index, mining index, and electric power generation and distribution correlate with secondary copper production in long-run; and electricity index correlate with secondary copper production in short-run. A 1% increase in electricity index initially leads to 1.76% drop in secondary copper production in short-run, and 3.69% increase in secondary copper production in long-run. A 1% increase in both mining index, and electric power generation and distribution leads to 4.57% and 5.18% decrease in secondary copper production in long-run respectively. The CUSUM and CUSUMSQ charts show the developed ARDL model to be stable over time. Based on the model dependence, we suggest that the policy makers shall devise policies towards reducing copper mining activities thereby encouraging stakeholders to focus on effective collection and efficient recycling of copper towards conservation of natural metal resources.

Automated summary

This study analyzes the stocks and flows of primary metal resources and scrap metal flows using material flow analysis. It also examines the influence of economic variables on secondary metal production and scrap availability. The findings suggest that electricity index, mining index, and electric power generation and distribution are correlated with secondary copper production in the long run. A stable autoregressive distributed lag model is developed. Based on the model, policymakers are recommended to reduce copper mining and promote effective collection and recycling of copper.