This is an interesting case study using geodemographic data to analyze social economical factors’ impact on carbon dioxide emissions. Regardless of how carbon dioxide emissions affected by different social economic determinants, I am curious about the original geodemographic data used for further analysis. The study uses geodemographic data in ACORN database and conducts research based on lifestyle classification, and my question is what lifestyle exactly means and what rules are based on for ACORN classification defined. Also, the socioeconomic variables used in regression analysis are from wider categories of housing, families, education, work and finance, etc. Are these the typical variables or objects which geodemographic theory usually deals with and are these the research contents that demographic researchers focus on? Moreover, the geodemographic data are coded at the postal code level which could be explained as scale that the data built on. Is there any possibility that regression analysis results of what impact CO2 emissions would change if the scale changed? Does policy districts or postal code allocation rule play a role of noise in the analysis.
Another thing I want to point out is that we did learn about human mobility in last week seminar and could movement theory study be applied into studying geodemographic in aspect of changing over time, or it does not matter in developing the geodemographic theory.