I am proposing to research conceptualizations of climate change within environmental policy because I want to find out what explains variation in the US governmental funding allocated towards environmental factors which directly relate to climate change in order to help my reader understand the effects of theoretical discussions and scholarship on policymaking decisions.
If completing a large n statistical analysis for my project, I would use US government funding allocated towards environmental factors which directly relate to climate change for my dependent variable. This is broader than just funding allocated to specific agencies such as the Environmental Protection Agency, but narrower than any funding directed towards something that relates to the environment. Using past budgets, I would add the funding allocated to various departments, projects, or funds that have a specific goal of adapting to or mitigating the effects of climate change. This would yield a specific number for each fiscal year, making this interval-ratio data. Some examples include the budget of the EPA, the Department of Interior’s budget to reduce the environmental effects of natural gas and oil use, the Department of Agriculture’s program to increase rural renewable energy use, or the Department of Energy’s budget to research and develop innovations in energy. This information is available via the Office of Management and Budget’s list of annual budgets.
The creation of this data set would allow me to identify other variables. I would be able to label the percentage of the total US budget to this area. This would be interval-ratio data. I could also identify what agencies or projects receive the highest percent of this area of the budget, which may suggest what kind of framing the government views climate change under. This would be considered nominal data. I have access to yearly information from the most recent fiscal year back to 1996 (25 cases) via the Office of Management and Budget and additional access to earlier years in a print source at the AU library.
The main limitation of this dataset is that because I have not been able to find this data in the existing scholarship I have to craft it myself and therefore use my own discretion in deciding what elements to consider part of the dependent variable and what not. I would obviously make these choices based on literature, but ultimately it means that how I operationalize this information is not widely accepted or used by other scholars.
 “Fiscal Year 2015 Budget of the U.S. Government,” Office of Management and Budget. (Washington D.C.: GPO, 4 March 2014), 133, 98, 46, 74.
“Fiscal Year 2015 Budget of the U.S. Government,” Office of Management and Budget. (Washington D.C.: GPO, 4 March 2014).