This is the third in a sequence of posts about some basic concepts relating to large-sample asymptotics and the linear regression model. The first two posts (here and here) dealt with items 1 and 2 in the following list, and you'll find it helpful to read them before proceeding with this post:
- The consistency of the OLS estimator in a situation where it's known to be biased in small samples.
- The correct way to think about the asymptotic distribution of the OLS estimator.
- A comparison of the OLS estimator and another estimator, in terms of asymptotic efficiency.
Here, we're going to deal with item 3, again via a small Monte Carlo experiment, using EViews.