| Summary: | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2009. === Includes bibliographical references (p. 77-78). === Energy intensity is defined as the amount of energy consumed per dollar of GDP (Gross Domestic Product). The People's Republic of China's (China's) energy intensity has been declining significantly since the late 1970s. The first part of this thesis is a direct descriptive statistical analysis at both the national level and provincial level. Regional variation in terms of energy production and consumption is pronounced especially between the inland provinces and coastal provinces. The role of railway transportation in moving coal from the inland regions to the coastal regions is studied. I find that the capacity limit of railways has indirectly affected the decline of China's energy intensity. The second part adopts methodology similar to that used by Sue Wing (2008), as well as Metcalf (2008) paper. I have created two indexes to decompose changes in energy intensity into intra-province (efficiency) and inter-province (structural) effects. Efficiency change refers to the energy-intensity reduction within a particular province due to factors such as fuel prices, temperature, economic sector shift, infrastructure investment, etc. The structural change refers to the change of energy intensity due to the growth of the share of provincial output in total GDP, such as when less energy-intensive provinces increase their share of output in total GDP. I find that the efficiency change has outperformed the structural change over the sample period of 1988-2006. The third part identifies and tests the potential factors that may positively or negatively contribute to the reduction of energy intensity within each province. === (cont.) As stated above, I collected a panel dataset of 29 provinces from 1988 to 2006 (= 551 observations) for analysis. I present results from the fixed-effect regression model of the energy intensity on economic- and temperature-related variables, namely, fuel prices, per capita income, heating degree days, cooling degree days, time trend, capital-labor ratio, and investment-capital ratio. The provincial analysis shows that the increases in per capita income, time trend and capital-labor ratio have played an important role in the decline of China's energy intensity. I further separated the 29 provinces into three major economic regions and conducted the same analysis. I found that regional-specific characteristics and regional variance in response to the energy use have been magnified. === by Xin Zhang. === M.C.P. === S.M.
|
|---|
