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The Marginal Abatement Cost of Carbon Emissions in China

Chunbo Ma and Atakelty Hailu

Year: 2016
Volume: Volume 37
Number: China Special Issue
DOI: 10.5547/01956574.37.SI1.cma
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Abstract:
There is an emerging literature estimating the marginal cost of carbon mitigation in China using distance function approaches; however, empirical estimates vary widely in magnitude and variation, which undermines support for policies to curb carbon emission. Applying three commonly used distance functions to China's provincial data from 2001 to 2010, we show that the variability can be partially explained by the difference in the input/output coverage and whether the estimated marginal abatement cost (MAC) is conditional on the abatement of other correlated pollutants. We also argue that the substantial heterogeneity in abatement cost estimates could be related to an economic interpretation that radial measures reflect the short-run MACs while non-radial measures reflect the long-run MACs. Our mean short-run MAC for carbon is 20 US$ per tonne, an amount that is very close to the carbon prices observed in China's recently launched pilot markets.



Endogenous Bad Outputs and Technical Inefficiency in U.S. Electric Utilities

Mike Tsionas and Subal C. Kumbhakar

Year: 2024
Volume: Volume 45
Number: Number 1
DOI: 10.5547/01956574.45.1.mtsi
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Abstract:
In this paper, we consider a simultaneous modeling of good and bad outputs. We use an input distance function (IDF) with endogenous inputs as well as endogenous bad outputs, which is novel in the literature. Moreover, we model input efficiency to depend on the production of bad outputs which allows us to investigate whether emissions of pollutants (bad outputs) are related to technological performance (technical efficiency). We also model production of each bad output with a spatial structure separately, each depending on production of good outputs, inputs and other exogenous variables. These bad output production functions allow us to estimate both direct and indirect effects of good output on the production of bad outputs, which may be of special interest because they show the cost (to the society) in terms of releasing pollutants to the environment in order to increase production of good outputs. We apply the new technique to a data set on U.S. electric utilities with four bad outputs, three inputs and two good outputs. We used a Bayesian technique to estimate the model which is a system consisting of the input distance function, reduced form equations for each input, dynamics of inefficiency and bad output production technology—separately for each. Empirically, bad outputs are found to affect inefficiency positively. Percentage increases in inefficiency due to a percentage increase in each bad output are found to vary from 0.225% to 0.42%. Energy prices are found to be positively related to inefficiency. From the spatial specifications of bad outputs, we find that the spillover effects of increasing production of good outputs account for the majority of the total effect, indicating that neighborhood effects are more important than own effects. This means, the neighboring utilities played a crucial role indicating "contagion" of practices.





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