I'm finding myself confused and unable to find good answers to what seems to be a simple question:
I have (monthly) time series data on the prices of several products (for example call them: y x z). The model I wish to fit is:
y_t = a + bx_t + cz_t + e_t
The question is: do I need to test for stationarity just for y or also for x and z?
if the explanatory variables should be stationarity, is there someway to conduct a test for stationarity of all terms at once, or is stationarity of each variable separately, sufficient to establish stationarity of the model i wish to estimate?
And how do I go about doing these tests in stata? there are a lot of stationarity tests in stata, but they are restricted to testing one variable only - and I'm not sure that's appropriate.
Related Posts with stationarity of explanatory variables in time series regressions
Dealing with omitted variable bias in survival analysesHi, I would like to know how I could deal with an omitted variable bias in a survival analysis. My …
PSM overlapp assumptionHi all, I have this result from using PSM teffects overlap. Can someone please tell me if there is a…
Threshold regression using time series dataDear Community, I am a user of Stata 15. I am trying to estimate the threshold effects of inflation…
Panel Data Three Dimensions "repeated time values within panel"Hello everyone, First of all, I would like to apologize in advance if I commit any mistake on this …
Coefplot - colorDear all, I am using coefplot to display the coefficient estimates of one variable from differen…
Subscribe to:
Post Comments (Atom)
0 Response to stationarity of explanatory variables in time series regressions
Post a Comment