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The cost of low-carbon transition for China's coal-fired power plants: A quantile frontier approach

Ning Zhang, Xuhui Huang () and Yunxiao Liu

Technological Forecasting and Social Change, 2021, vol. 169, issue C

Abstract: Estimating the shadow price of carbon dioxide (CO2) emissions is the key to understanding the cost of low-carbon transition for China. This study estimates the shadow price of CO2 emissions for China's coal-fired power plants over the period 2005 to 2010 by applying a conventional approach introduced by Färe et al. (2012), which combines quadratic directional distance function (DDF) with the stochastic frontier analysis (SFA). We further extend the model by introducing the quantile regression (QR) method, which is more robust to perturbations and outliers. We also compare the estimated shadow price from QR with the prices obtained from the ordinary least square (OLS) regression and standard SFA. The estimated average shadow price of CO2 emissions is 10,442.70 Yuan/ton and 10,231.97 Yuan/ton for the OLS regression and SFA, respectively. The average shadow price of CO2 emissions estimated by the QR is lower: 9623.95 Yuan/ton at the 50th percentile, 9304.21 Yuan/ton at the 56th percentile, 9588.74 Yuan/ton at the 80th percentile, and 9565.11 Yuan/ton at the 95th percentile. Finally, the spatial distribution of estimated shadow prices is reported. The results show that coastal provinces and municipalities have higher shadow prices of CO2 emissions.

Keywords: Shadow price; China's coal-fired power plants; Parametric approach; Directional distance function; Quantile regression; The optimal quantile (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.techfore.2021.120809

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