부산대학교 도서관

The purpose of this study is to construct a double-quantile regression model for 104 countries in the year of 1990-2005. This is a model by combining quantify one dimension for different levels of CO_2 emissions and quantify the other dimension for different levels of GDP. It is expected to have better portrait between the emissions of CO_2 and economic development while emissions of CO_2 and developments of economy are accounted for simultaneously. Due to the characteristics of data, meta-technology ratio (MTR) is appropriate to catch country and time effect. The income elasticity of CO_2 emission, i.e. every 1% change of GDP to the impact on the emission of CO_2 will then be compared both for double-quantile regression model and traditional quantile regression model. The results indicate that a positive relationship exists between annual CO_2 emission per capita and annual GDP per capita. That is, for either type of the country with any CO_2 emission level, there is no inversed-U shaped between annual CO_2 emission per capita and annual GDP per capita. The results from double-quantile regression model show that every 1% increase of annual GDP per capita will generate much higher annual CO_2 emission per capita for low-income countries than that for high-income countries. Specifically, the income elasticities of CO_2 emission for high-income and high-emission countries from the double-quantile regression model are the lowest among all countries at all income and emission levels. This implies that these countries are rich enough and willing to control the emission of CO_2. On the contrary, since income elasticities of CO_2 emission for low income countries are higher than those for high income countries this has led to a much higher conflict between the development of economy and control of CO_2 emission for low development countries as these countries have significant pressure of economic development.