Hi
I experience heavy (perfect) multicollinearity between a control variable and my main independent (which is also used as interaction term). But the control variable is vital and can't be excluded, so don't know what to do.
The data is Eurobarometer, i.e. individual level. I want to examine whether globalisation at the country level (X1) influences the effect of the Trump election (X2) on democratic satisfaction (Y). So, an interaction with an objective, country level measure for globalisation.
However, I also need to have the individual's country as a control variable, to leave out any influence from cultural, historic etc. factors. Given that I must include this control, is there anything I can do to avoid (perfect) collinearity?
I have already tried 1) to make the metric globalisation variable categorical, grouping countries in everything between 2 and 6 globalisation levels. But even when I make a dummy globalisation variable, the collinearity persists. 2) Running a - bysort reg - with these categorical globalisation variables. This obviously removes the collinearity problem, but doesn't feel methodologically justified(?)
Thanks
Related Posts with Collinearity between two country variables, one nominal (country name) and the other metric (globalisation level)
Generalized difference in differences problemI am evaluating a government program using difference in differences. The program was implemented in…
.ado Programming in Stata without invoking mata: Invalid Name error from within the functionStata Status: Beginner I have declared a local variable inside my function. And whenever I referenc…
Calculating Risk for Repeated Measures with Varying & Overlapping PredictorsI have data on several measures for 150 survey respondents: Infection (binary outcome of interest), …
Difference in proportion adjusted for baseline characteristics (Mantel Haenszel method)Hi, I am analysing the results of a trial & would like to compare the proportion of individuals…
Help required for variable forecast procedureDear All I need some help with commands relating to earnings forecasts model: EARN(t+1)=b0+ b1EARN…
Subscribe to:
Post Comments (Atom)
0 Response to Collinearity between two country variables, one nominal (country name) and the other metric (globalisation level)
Post a Comment