Hi all,
Im currently working on a strongley balanced panel data set. I have 28 countries and 764 observations. I am looking at what factors influence the level of CO2 emissions in selected countries. All my variables are taken in log form, as i am working with the STIRPAT model. My dependent variable is level of CO2 emissions. My independent variables are as follows, GDP per capita, total population, petroelum prodcts usage of the transport sector and the total urban population. I had first used the fixed effects model to estimate my coeffcients but due to the high levels of multicolinearity i decided to use the ridge regression model.
Firstly my question is are there diagnostics tests avaiable to be run on a ridge regression model? for example tests for heteroskedascity and autocorrelation.
Secondly, due to the relationshsip between ridge regression and the OLS model i was wondering are the assumptions of OLS applicable to ridge regression?
Thank you in advance,
Colm
Im currently working on a strongley balanced panel data set. I have 28 countries and 764 observations. I am looking at what factors influence the level of CO2 emissions in selected countries. All my variables are taken in log form, as i am working with the STIRPAT model. My dependent variable is level of CO2 emissions. My independent variables are as follows, GDP per capita, total population, petroelum prodcts usage of the transport sector and the total urban population. I had first used the fixed effects model to estimate my coeffcients but due to the high levels of multicolinearity i decided to use the ridge regression model.
Firstly my question is are there diagnostics tests avaiable to be run on a ridge regression model? for example tests for heteroskedascity and autocorrelation.
Secondly, due to the relationshsip between ridge regression and the OLS model i was wondering are the assumptions of OLS applicable to ridge regression?
Thank you in advance,
Colm
