Abstract
Pricing the natural capital is very critical for the achievement of carbon neutrality. This paper uses the Shephard input distance function to derive the shadow price of natural capital under regulatory constraints, which corrects the biased estimates without these constraints of previous studies. We relax the assumption of cost-minimizing behavior at market price and incorporate the price inefficiency in our model. This model is applied to the Chinese provincial dataset from 2004 to 2017. We observe that the average shadow prices of mineral, water, woodland and forest are 391[Formula: see text]CNY/metric tons of coal equivalent (tce), 0.13[Formula: see text]CNY/m3, 772[Formula: see text]CNY/hm2 and 344[Formula: see text]CNY/hm2, respectively. For the dynamic effect, the shadow prices of natural capital rise sharply between 2004 and 2014. By testing the price efficiency, we demonstrate that regulatory constraints have an impact on shadow prices of natural capital in practice.
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