In this exploratory research, the author employed a fixed effects model on data from 27 OECD member states, to measure the impact of variables on the level of emission of carbon dioxide, with particular interest in variables representing policies in force. Seeing no other specific research that measures the impact of various policies across countries, the author endeavored to determine whether there would be any useful information to pursue more complex studies on understanding what kinds of policies are most effective to reduce emissions.
Employing data from the UN, World Bank, and International Energy Agency, this research found that certain policy variables would reduce per capita CO2 emissions, while the method of measuring policies for the purpose of categorizing them under variables severely reduced the explanatory power of these policy variables.
Although this is a step towards providing some more detail on the kinds of policies that may be relatively effective in CO2 reduction efforts, other factors, such as whether there were cumulative effects of multiple but similar policies, could not be measured. Thus, while the estimators should not be biased, the actual explanatory power of the statistical output is severely undercut by the nature of quantifying policies that are rich in many qualities.
|Department:||Public Policy & Policy Management|
|School Location:||United States -- District of Columbia|
|Source:||MAI 48/05M, Masters Abstracts International|
|Subjects:||Climate Change, Public policy|
|Keywords:||Carbon dioxide reduction, Policy impact, Quantify policy|
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