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This post is following of above post.
Let's do time-series regression.
Firstly, let's make a static time series model
In time-series regression, we have to care about serial correlation of the error term.
Firstly, I load dynlm package and lmtest package.
Before testing serial correlation, let's plot error term.
Since I don't have good experiences, I cannot tell if there is serial correlation or not by just seeing the plot.
Let's test AR(1) Serial Correlation.
p-value is less than 2e-16, it is alomost 0. So mod_static has serial correlation.
We need orcutt package to do Cochrane-Orcutt estimation and I will use cochrane.orcutt() function.
Let's compare mod_static and mod_orcutt.
I use stargazer package.
sd_bci coefficient is negative and statistically significant. It means that when there are large variance of bci, bci level is lower than when varicance is small.
That's it. Thank you!
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