Hello everyone,
My dependent variable is green investment. In my model, I have four categories that I add progressively to my models until I reach the final model with all four categories. Each category has at least two variables.
I want to understand which category explains green investment the best, so I want to use variance composition analysis. However, I am unsure of which code to use.
I saw this code in an article: runmlwin dependent_var cons, level4(category4: cons) level3(category3: cons) level2(category2: cons) level1(category1: cons). If this is the correct code, how do I define the levels? If it's not, then what is the correct one?
My data is cross-sectional.
Thank you,
My dependent variable is green investment. In my model, I have four categories that I add progressively to my models until I reach the final model with all four categories. Each category has at least two variables.
I want to understand which category explains green investment the best, so I want to use variance composition analysis. However, I am unsure of which code to use.
I saw this code in an article: runmlwin dependent_var cons, level4(category4: cons) level3(category3: cons) level2(category2: cons) level1(category1: cons). If this is the correct code, how do I define the levels? If it's not, then what is the correct one?
My data is cross-sectional.
Thank you,
