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Research On The Allocation Efficiency Of Provincial Carbon Emission Rights Under The Unified Carbon Market

Posted on:2020-01-31Degree:MasterType:Thesis
Country:ChinaCandidate:L K SunFull Text:PDF
GTID:2381330590963323Subject:Applied Economics
Abstract/Summary:PDF Full Text Request
The issue of excessive carbon dioxide emissions poses severe challenges to the survival and development of mankind.Reducing the consumption of fossil energy and emissions of carbon dioxide are the common vision of all countries in the world.At the end of 2017,China launched the national unified carbon market.As the largest developing country in the world,it is worthwhile to study the specificity and diversity of our country in detail if we want to build a successful national unified carbon market.The transaction situation of the seven pilot provinces and cities that have been established and operated in China provides rich experience and lessons for establishing a unified national carbon market.One of the core issues of the unified carbon market is the initial quota allocation mechanism.A good initial distribution method is the premise of generating the secondary trading market,it will also affect the activity of carbon market transactions and the reasonableness of trading prices.Therefore,it is of great significance to study the scientific allocation method in different provinces and cities under the premise of constant total carbon emission quotas in China.Firstly,this thesis uses the DEA(Data Envelopment Analysis)with input orientation and variable returns to scale(VRS)to measure the allocative efficiency of carbon emission rights under the historical distribution method in China's 13 th Five-Year Plan period.It is found that most provinces have not reached the DEA efficiency;On this basis,the carbon dioxide emissions,population,GDP and energy consumption are taken as input and output variables,the total carbon emission is fixed as the constraint,using the zero-sum gains DEA(ZSG-DEA)which used to find the optimal comprehensive efficiency as distribution method,readjust the initial allocation results of carbon emission rights in various provinces and cities across the country,calculating the optimal number of emission rights for each province and city.Further,according to the inter-provincial emission rights adjustment results,with the goal of maximizing the output of each province and city in 2016-2020,the centralized allocation of DEA model was used to allocate the total amount of carbon emission rights effectively in time dimension,and obtained the optimal annual emission allowance while maximizing output of all provinces and cities.The research shows that:(1)Only six provinces and cities have reached the effective level of DEA under the historical distribution method,they are Beijing,Shandong,Guangdong,Hainan,Sichuan,and Qinghai,the national average efficiency level is 0.8152.(2)The efficiency under the historical distribution method determines the adjustment direction of carbon emission rights in various provinces and cities,the provinces and cities with historical distribution efficiency above the national average level,the number of carbon emission rights in the adjustment process is increasing continuously.On the contrary,the number of carbon emission rights in the adjustment process is decreasing continuously while the provinces or cities' historical distribution efficiency below the national average level.(3)The results of inter-provincial efficiency distribution after adjustment show that: Shandong,Jiangsu and Guangdong have the largest number of carbon emission rights while Hainan,Qinghai and Ningxia have the least amount of carbon emission rights.(4)Provincial inter-temporal distribution results show that: most developed provinces and cities have greater carbon emission rights than their actual carbon emissions,while most provinces in the northeast and northwest regions will face greater pressure to reduce emissions in the future.
Keywords/Search Tags:Unified Carbon Market, Carbon Emission Rights, Allocative Efficiency, ZSG-DEA Model
PDF Full Text Request
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