[Gretl-users] Re: How to adjust heteroskedasticity
On Wed, 22 Apr 2020, John C Frain wrote:
On Wed, 22 Apr 2020 at 11:32, Sven Schreiber <svetosch(a)gmx.net>
wrote:
> Am 21.04.2020 um 21:54 schrieb robdans2(a)gmail.com:
>> Thanks for the quick answer, what do you think would be a better fix?
> Changing the variable (for example making it a log)?
>
> All I'm saying is that we're talking about an outlier that is going to
> be removed. I know that this affects the test outcome of a diagnostic
> test for heteroskedasticity, but it is still a different topic, most of
> the time.
Failure of your heteroskedasticity test can be regarded as indicating
misspecification. [...]
True indeed. I have one more observation to throw in.
In his introductory economics textbook, Wooldridge has a house-price
example which he treats as a poster-case for heteroskedasticity, its
detection and treatment. I was messing around with the dataset in
question (scatter plots and so on) and noticed that it contained one
serious outlier: a house with a huge lotsize but very low price. In
any regression of price on a list of regressors containing lotsize,
the standard tests for heteroskedasticity would light up like
Christmas trees. But remove that one observation and everything was
fine and dandy. This was actually a poster-case for outlier
detection.
So this is a possibility worth considering when heteroskedasticity
is flagged by "mechanical" means. Of course, in gretl you have
direct means of detecting outliers (see the "leverage" command).
Allin