Title: | Nonrenewable, renewable energy consumption and economic performance in OECD countries: a stochastic distance function approach |
Author(s): | Nguyen Thi Ngan Thao |
Advisor(s): | Dr. Le Van Chon |
Keywords: | Nonrenewable energy; Renewable energy; Productivity change; Distance function |
Abstract: | Kyoto Protocol with the target of lowering greenhouse gas emission levels to mitigate the harsh aftermaths of global warming and climate change, primarily caused by fossil fuel using, has put a great pressure on developed countries, including OECD countries, which accounts for a large share of the world’s total energy consumption. This leads to the trend of shifting from nonrenewable energy to renewable energy recently, and also attracts the studies in this area. Utilizing the panel data of 34 OECD countries from 1990 to 2012, this paper estimates the stochastic distance function with four inputs (capital, labor, nonrenewable and renewable energy consumption) and one output (GDP) to analyze the effects of nonrenewable and renewable energy consumption on GDP, the relationship between two sources of energy, and the productivity change of OECD countries over the period. Nonrenewable and renewable energy are proved to be substitutes of each other and positively contribute to economic growth. On the other hand, the high values of technical efficiency suggest that average OECD country operates almost as effectively as the best performer in the whole group whereas the measurement of productivity change shows that all productivity gain is attributed to the outward shift of the production frontier. |
Issue Date: | 2015 |
Publisher: | University of Economics Ho Chi Minh City; VNP (Vietnam – The Netherlands Programme for M.A. in Development Economics) |
URI: | http://vnp.edu.vn/vi/nghien-cuu/luan-van-tot-nghiep/tom-tat-luan-van/940-nonrenewable-renewable-energy-consumption-and-economic-performance-in-oecd-countries-a-stochastic-distance-function-approach.html http://digital.lib.ueh.edu.vn/handle/UEH/58149 |
Appears in Collections: | MASTER'S THESES
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