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  4. Project Cost and Efficiency Analysis of Clean Development Mechanism: Investment Performance of Credit Countries with Different Technology Levels
 
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Project Cost and Efficiency Analysis of Clean Development Mechanism: Investment Performance of Credit Countries with Different Technology Levels

Date Issued
2016
Date
2016
Author(s)
Qiu, Ke-Zhen
DOI
10.6342/NTU201600910
URI
http://ntur.lib.ntu.edu.tw//handle/246246/275925
Abstract
With the climate change generated by global warming and its potential impact on human life and ecology system, United Nations signed the Kyoto Protocol and proposed clean development mechanism (CDM): industrialized countries become the credit countries that invest reduction technologies in developing countries that are host countries. It is expected that the emission of greenhouse gas (GHG) will decline in developing countries under CDM. However, credit countries may spend too much transaction costs on searching suitable host countries, and monitoring host countries to abate GHG, etc. The abatement costs will then increase, that is the inefficiency. This research mainly analyzes the abatement costs, cost efficiency (CE), and technology gap ratio (TGR) in order to find out the specific cost saving. According to the above estimation, it is essential to analyze how the political and economic conditions, including foreign direct investment (FDI), education, trade policy, electricity usage, and accumulated GHG emission, etc. of host countries affect cost inefficiency, that is the cost difference analysis. In addition, it intends to compute the abatement costs of different CDM project type in different host countries in order to find out the suitable project portfolio for Kyoto second commitment. For the sake of cost efficiency analysis, this research estimates stochastic abatement cost frontier for host countries with different technological competitiveness by stochastic frontier approach (SFA). In such a manner, it can use corrected ordinary least squares (COLS) to explore the meta abatement cost frontier with cost effectiveness. CDM project data for the research are from May 2005 to December 2014. It categorized host countries into four groups with different technology levels including technological readiness and innovation indexes. This research also applies the information of GHG emission reductions, project duration, project type, income level of host countries, project registered date, electricity productions, and the methodologies of the project to estimate abatement cost function for each group. The result of estimation implies that the abatement costs decline with the improvement of technology. On average, high technological-completeness countries, upper-middle technological-completeness countries, lower-middle technological- completeness countries and lower technological-completeness countries should save 159, 529, 311, and 852 U.S. dollars per ton, respectively. The cost difference analysis suggests that the host countries should be aware of the following consideration: the pollution in specific sector once trade openness increases, making good use of technology derived from FDI, avoiding waste of energy while enhancing the popularity of electricity usage, enhancing the environmental awareness while increasing the enrollment rates of tertiary education, and reducing the accumulated emission of carbon dioxide equivalents. Host countries may attract more CDM projects to enhance national competitiveness and improve environment once they reduce the cost differences. According to the measurement of abatement costs, there are different ideal investment portfolios for different emission reduction quantities. Credit countries can distribute their own reduction commitment into several CDM projects. However, less reduction quantities may come along with higher transaction costs; on the contrary, too much reduction quantities may come along with higher investment risk. The above facts make the credit countries ought to pay attention to the allocation of the project portfolio.
Subjects
clean development mechanism
abatement cost
stochastic frontier approach
meta-frontier analysis
cost efficiency
technology gap ratio
SDGs

[SDGs]SDG9

[SDGs]SDG10

[SDGs]SDG11

[SDGs]SDG13

Type
thesis
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ntu-105-R03627008-1.pdf

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