Dear Statalist,
I have cross-sectional survey data and I want to determine how much an individual trusts others given the democratic history in his country. I constructed a variable 'demcapital' that measures the democratic history in the country and ranges from 0 to 1. My code in Stata is:
reg trust demcapital male age i.education i.religion i.socialclass lngdppercapita warincountry socialistpast colony_uk colony_esp africa asia i.country i.year, vce(robust)
However, when I regress this, Stata omits 5 countries and 1 year "because of collinearity".
Since the number of observations is not small (more than 100,000 observations), most part of the variables are statistically significant and not correlated, I have not been able to find the source of collinearity. Also, if I choose other dependent variables, where the number of observations shrinks to aproximatelly 40,000 the number of omitted countries and years dobles.
Could anyone advice me if it is an error in my model and should be more advisable to use a multilevel model?
Thank your for your attention.
I have cross-sectional survey data and I want to determine how much an individual trusts others given the democratic history in his country. I constructed a variable 'demcapital' that measures the democratic history in the country and ranges from 0 to 1. My code in Stata is:
reg trust demcapital male age i.education i.religion i.socialclass lngdppercapita warincountry socialistpast colony_uk colony_esp africa asia i.country i.year, vce(robust)
However, when I regress this, Stata omits 5 countries and 1 year "because of collinearity".
Since the number of observations is not small (more than 100,000 observations), most part of the variables are statistically significant and not correlated, I have not been able to find the source of collinearity. Also, if I choose other dependent variables, where the number of observations shrinks to aproximatelly 40,000 the number of omitted countries and years dobles.
Could anyone advice me if it is an error in my model and should be more advisable to use a multilevel model?
Thank your for your attention.