I would like to estimate a confidence interval for coefficients of my regression. I calculate the coefficients of the regression with the following code:

myRegression <- lm(x ~ y)
coeftest(myRegression, vcov = NeweyWest(myRegression, lag = NULL))

And the confidence interval with this code:

confint(Regression, vcov = NeweyWest(myRegression, lag = NULL),level = 0.95)

However, when I try

confint(Regression, level = 0.95)

I get the same confidence interval, although the standard error changes with the Newey West method.

Can someone explain me whether I make a mistake?

  • $\begingroup$ "Coefficients" is plural. What, then, do you mean by a single "confidence interval" for them? Do you mean a set of CIs? $\endgroup$ – whuber Jan 13 '17 at 20:01
  • $\begingroup$ @whuber : Or maybe an ellipsoid. $\endgroup$ – Michael Hardy Jan 13 '17 at 20:07
  • $\begingroup$ Sorry for being not precise. I have a multiple regression with several coefficients. For each one of them I would like to calculate an CI $\endgroup$ – user144267 Jan 13 '17 at 20:23
  • $\begingroup$ Are you assuming i.i.d. normally distributed errors? The Newey–West method seems to be intended for use with weaker assumptions. $\endgroup$ – Michael Hardy Jan 13 '17 at 20:36
  • $\begingroup$ Its a time series analysis, I am expecting autocorrelation and heteroskedacity in the error terms - thats why I am using Newey-West... $\endgroup$ – user144267 Jan 13 '17 at 20:45

The confint() method does not allow to plug in vcov arguments. Therefore such the function coefci() has been added to lmtest (starting from version 0.9-35). The default coefci(Regression) yields the same as confint(Regression). However, you can also do coefci(Regression, vcov = NeweyWest). This should give what you are looking for.


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