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2022-08-15

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Indian Economy
www.thehindu.com

A recent report commissioned by the NITI Aayog has estimated that five orders of the Supreme Court and the National Green Tribunal favouring larger protection for the environment had cost the government around Rs. 8,000 crore in revenue.

It recommends that the court undertake economic-impact analysis, based on forecasts put together by a group of experts, to address and adjudicate public interest cases involving economically sensitive matters.

Cases in spotlight

The report, prepared by Jaipur-based CUTS (Consumer Unity & Trust Society) International, studied the following five cases: the Mopa airport case, where the court required undertakings from the concessionaire GMR Goa International Airport Limited (GGIAL) ensuring additional environmental safeguards; the Goa mining cases, during which the court on two occasions cancelled iron ore mining licenses in Goa — the latest one in a 2018 case where Vedanta Group was arguing that their licence was still operational; the Sterlite Copper case; the regulation of sand mining; and the banning of construction activities in the National Capital Region to curb air pollution.

The report, after measuring the economic impact of judicial interventions in these cases, estimated that the government lost out on a possible revenue of Rs. 8,000 crore between mid-2018 and mid-2021, which if invested as capital expenditure, could have resulted in an economic impact of around Rs. 20,000 crore.

After submitting that the economic impact in these cases included a loss of Rs. 15,000 crore in possible revenue to the industry and Rs. 500 crore in wages, the report suggested that the SC should engage experts including economists, environmentalists, and sociologists, among others, to conduct an economic-impact assessment in cases “involving economic sensitive matters”.

The CUTS report also concludes that the judiciary should institutionalise the idea of a cost-benefit analysis as part of their decision-making, and the authorities should consider qualitative indicators that might not necessarily be quantifiable.


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