| Carbon emission behavior and its consequences in the personal consumption field have increasingly become the focus of attention in the field of energy and climate change.For a long time,based on large emissions and operability in the industrial sector,countries around the world have successively introduced carbon taxes and established carbon trading markets to control industrial carbon emissions,but few regulate carbon emissions in personal consumption.With the continuous development of the economy and society,relevant researches show that the carbon emission growth rate in the personal consumption field gradually exceeds the industrial production field,gradually becoming the main reason for the growth of global carbon emission,which means that the field of personal consumption contains huge potential for emission reduction.In view of this,some scholars have proposed a personal carbon trading(PCT)scheme,aiming to reduce carbon emissions in the personal consumption field through market-based trading mechanisms,and encourage consumers to gradually develop low-carbon consumption lifestyle and live a low-carbon life.At present,China's coal-based power generation method has led to more than 40% of carbon emissions in the power sector,so that emission control for the power industry has gradually become an important breakthrough for the government to achieve emission reduction targets.In July 2012,China began to implement the residential increasing block pricing(IBP)policy in all areas of the mainland except Tibet and Xinjiang,with a view to guiding residents to save electricity so as to alleviate resource and environmental pressures.However,since its implementation in 2012,most provinces have rarely adjusted the structural parameters of the IBP,so the environmental negative externalities caused by power consumption have become increasingly prominent.With the gradual improvement of the living standards and consumption levels in China,residential carbon emissions has also increased year by year.In view of this,in order to achieve China's increasingly stringent emission reduction targets to fulfill its commitments,this thesis will take the carbon emissions in the residential electricity sector as an example,and combine with the individual carbon trading system to optimize the parameters of IBP policy,so that the carbon emissions in the field of residential electricity consumption will be regulated,while the policy target of IBP will be realized better as well.This thesis starts with the concept of IBP and PCT,sorts out the related research on IBP and PCT both at home and abroad,and points out the weakness of related issues such as the optimization design of the IBP policy and the implementation cost of PCT.After that,based on the consumer utility theory,this thesis constructs a consumer behavior model under the PCT system.On this basis,the optimization model of the IBP and the block length are constructed respectively based on the IBP policy targets.Then,combined with the CFPS(2014,2016)micro survey data and the IBP parameter information,the IBP parameters of 25 provinces in China are numerically simulated;and on the basis of estimating the elasticity of residential electricity demand,the impact of two types of parameter adjustments on the electricity demand and consumer welfare is analyzed through the construction of analytical framework for counterfactual scenarios and consumer welfare changes.Finally,based on the comparative analysis of the above results,the research conclusions are extracted,and corresponding policy implications are put forward.The main conclusions of this thesis are:First,all the two optimization IBP parameters from the perspective of PCT can change the current unified price structure into the IBP structure.After the IBP is optimized,the first IBP decreases,while the second and third blocks increases.After optimizing the block length,the threshold value of the two blocks is reduced,meanwhile,residents in the first block will receive a certain amount of free electricity.Taking the initial carbon quota of 1308 kg as an example(Scenario 1),after optimizing the price parameter,the first IBP decreased by 0.013Yuan/kWh,accounting for 1.62% of the first IBP,and the second and third IBPs rose by 0.023Yuan/kWh,0.035Yuan/kWh respectively,accounting for 4.01% and 4.16% of their price,but only residents with electricity consumption in the first block will adapt to the first block low price after parameter optimization,otherwise,the first IBP remains unchanged.After the block length parameter is optimized,the second and third block thresholds are reduced by 75 kWh and 63 kWh respectively,accounting for 3.27% and 4.27% of the first and second block lengths respectively,while residents in the first block can receive free electricity of 23 kWh,which accounted for about 0.99% of the average electricity consumption of the first-block residents.If the electricity consumption amount exceeds the first block,they will no longer receive free electricity.Second,the initial carbon quota determines the level of carbon price,and it also has an important impact on the adjustment of IBP parameter under the perspective of individual carbon trading.As the initial carbon quota gradually decreased from 1308kg(Scenario 1)to 1073kg(Scenario 4),the equilibrium carbon price gradually increased from RMB 25/ton to RMB 243/ton.Once the initial carbon quota is set,consumers are divided into high-emission and low-emission ones.Compared with residents in areas of no PCT policy,high-emission residents must pay more for electricity consumption,while low-emission residents can sell excess quota to get extra income.At this time,the parameters of the IBP are designed by simulating the income impact of PCT on different consumers and are largely determined by the equilibrium carbon price.Specifically,after the price parameters are optimized,from scenario 1 to scenario 4,for each initial carbon quota reduce by 1%,the equilibrium carbon price increases by an average of 48.61%,the first IBP decreases by an average of 0.36%,and the second and third IBPs increase by an average of 2.60%,2.18%;after optimization of length parameters,for each initial carbon quota decreased by 1%,free electricity for residents in the first block increased by an average of 37.32%,while the second and third thresholds decreased by an average of 2.13.%,1.05%.Third,from the perspective of individual carbon trading,different parameter design of the IBP have different effects on the electricity consumption and welfare status of residents with different blocks and income levels.Taking the initial carbon quota of 1073 kg as an example(Scenario 4),under the price parameter optimization scenario,the average residential electricity consumption decreased by 70 kWh,accounting for 3.43% of the average annual electricity consumption amount;while under the block length parameter optimization scenario,the average electricity consumption of residents increased by 4kWh,which has little impact on residential electricity consumption.From the perspective of blocks,after the optimization of the price parameters,the electricity consumption of the first block residents increased by 23 kWh on average,and the increase in welfare accounted for 8.23% of the annual electricity consumption.The average electricity consumption of the second and third blocks respectively reduced by 231 kWh and 401 kWh,and the welfare loss accounted for 54.65% and 28.11% of the annual average electricity consumption respectively.After the optimization of the length parameter,the first block electricity consumption increased by 24 kWh,and the increase in welfare accounted for 7.36% of the average annual electricity consumption.While the electricity consumption of the second and third blocks is reduced by an average of 32 kWh and 80 kWh respectively,and the welfare loss accounted for only 5.09% and 7.05% of the annual electricity consumption,which is far less than the impact of price parameter optimization on it.According to the income level,the difference between the two types of parameters affects the residents of different income classes.After the price parameters are optimized,the electricity consumption and welfare of all income groups are reduced,among which the welfare loss of low-income class accounted for 8.81%,while that of high-income class accounted for 27.06%;however,after the optimization of the length parameter,only the electricity consumption and welfare of the middle-income and high-income groups decreased slightly,and the welfare of the low-income class increased by 8.14%,while the welfare loss of the high-income class was only 3.85%.The policy implications of the above conclusions are as follows: First,although Chinese residents' income and electricity demands are increasing,their electricity demands are relatively inelastic,causing increasingly severe extravagancy of electricity.Therefore,energy conservation and emission reduction cannot be limited to the field of energy production.The government should take the regulation of carbon emissions on the consumption side into consideration and combine it with existing energy policies to reduce the cost of the regulation.Second,the PCT mechanism provides a feasible solution for the government to achieve the goal of controlling total carbon emission,however,the allocation of initial carbon quota has an important impact on the carbon market and the design of ladder price parameters from the perspective of carbon market.Therefore,regulators need to comprehensively consider the real environment to formulate quota allocation principles so as to rationally allocate initial carbon quota and give full play to the guiding role in the emission reduction process.Third,a reasonable residential IBP structure should be established.In addition to the incentives for energy conservation and efficiency,subsidy should be more targeted to the most needed groups(such as low-income families)to improve equity.However,it is difficult to avoid the free-rideing problem of high-income families to enjoy welfare and subsidy.Therefore,the optimization design should take the entire IBP structure into consideration,especially the interests of different income classes,to better realize the multiple policy objectives of “efficiency” and “fairness” of the IBP. |
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