Hei!
I have a dataset that is a hierarchical, cross-sectional time series.
There are 438 units that all belong to one of the 19 superior clusters. The observations run 46 occations (monthly data e.g: 2012m1, 201510, making 20130 observations.
I have a question about whether or not the same preconditions exist for simple multivariate linear regression models and multivariate cross-sectional time series models?
Some of the usual preconditions specified in my literature (which is in the Norwegian Language, so it won't be helpful here), echoed in the dss.princeton.edu/training series for Stata are:
reg Y X1 X2 X3
estat hettest
ovtest
linktest
swilk
Are these tests and others that are based on the regress command functional when the loaded data is set to be time series cross-sectional and have run xtset id time?
I have tried to find the answers in methodology literature (as per Statlists FAQ). Maybe the question is too basic, but how do I test the basic assumptions of the regression methodology when i have xt-data? I know many of them are not relevant when correcting for them (robust standard errors for heteroskedsticity), but I still want to inspect for flaws.
Alternatively:
What are the definitive model precondition statistical tests for xt-data that I cannot do without?
Thanks,
Andreas Roaldsnes
I have a dataset that is a hierarchical, cross-sectional time series.
There are 438 units that all belong to one of the 19 superior clusters. The observations run 46 occations (monthly data e.g: 2012m1, 201510, making 20130 observations.
I have a question about whether or not the same preconditions exist for simple multivariate linear regression models and multivariate cross-sectional time series models?
Some of the usual preconditions specified in my literature (which is in the Norwegian Language, so it won't be helpful here), echoed in the dss.princeton.edu/training series for Stata are:
- normally distributed residualsThese preconditions are tested with these commands:
- the abscence of heteroskedasticity
- the abscence of omitted variable-bias.
reg Y X1 X2 X3
estat hettest
ovtest
linktest
swilk
Are these tests and others that are based on the regress command functional when the loaded data is set to be time series cross-sectional and have run xtset id time?
I have tried to find the answers in methodology literature (as per Statlists FAQ). Maybe the question is too basic, but how do I test the basic assumptions of the regression methodology when i have xt-data? I know many of them are not relevant when correcting for them (robust standard errors for heteroskedsticity), but I still want to inspect for flaws.
Alternatively:
What are the definitive model precondition statistical tests for xt-data that I cannot do without?
Thanks,
Andreas Roaldsnes
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