Econometric modeling for the influence of economic variables on secondary copper production in India
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作者:
Sourabh, Shalinee
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Indian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, IndiaIndian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, India
Sourabh, Shalinee
[1
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Pavithran, Sagar
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Indian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, IndiaIndian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, India
Pavithran, Sagar
[1
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Menon, Balagopal G.
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Indian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, IndiaIndian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, India
Menon, Balagopal G.
[1
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Mahanty, Biswajit
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Indian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, IndiaIndian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, India
Mahanty, Biswajit
[1
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机构:
[1] Indian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, 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.
机构:
Univ Trieste, Dept Econ Business Math & Stat, Trieste, Italy
Reg Autonoma Friuli Venezia Giulia, Trieste, ItalyUniv Trieste, Dept Econ Business Math & Stat, Trieste, Italy
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US Geol Survey, Natl Minerals Informat Ctr, 12201 Sunrise Valley Dr MS 991, Reston, VA 20192 USA
12201 Sunrise Valley Dr MS 991, Reston, VA 20192 USAUS Geol Survey, Natl Minerals Informat Ctr, 12201 Sunrise Valley Dr MS 991, Reston, VA 20192 USA
Renaud, Karine M.
Manley, Ross
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US Geol Survey, Natl Minerals Informat Ctr, 12201 Sunrise Valley Dr MS 991, Reston, VA 20192 USAUS Geol Survey, Natl Minerals Informat Ctr, 12201 Sunrise Valley Dr MS 991, Reston, VA 20192 USA
Manley, Ross
Nassar, Nedal T.
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US Geol Survey, Natl Minerals Informat Ctr, 12201 Sunrise Valley Dr MS 991, Reston, VA 20192 USAUS Geol Survey, Natl Minerals Informat Ctr, 12201 Sunrise Valley Dr MS 991, Reston, VA 20192 USA