- #1
slakedlime
- 76
- 2
This isn't a homework problem - I'm just confused by something in a textbook that I'm reading (not for a class, either). I'd appreciate an intuitive clarification, or a link to a good explanation (can't seem to find anything useful on Google or in my textbook).
My book states that one of the least squares assumptions (e.g. for ordinary least squares, OLS, estimation) is that large outliers are unlikely.
That is, for the following equation:
[itex]Y_{i}[/itex] = [itex]β_{0}+β_{1}X_i+u_{i}[/itex]
It must be that ([itex]X_{i}[/itex], [itex]Y_{i}[/itex]), i = 1, ..., n have nonzero finite fourth moments.
Why is this significant? What is the relationship between large outliers and nonzero finite fourth moments? I don't intuitively see the mathematical explanation. Any help and/or direction is much appreciated.
My book states that one of the least squares assumptions (e.g. for ordinary least squares, OLS, estimation) is that large outliers are unlikely.
That is, for the following equation:
[itex]Y_{i}[/itex] = [itex]β_{0}+β_{1}X_i+u_{i}[/itex]
It must be that ([itex]X_{i}[/itex], [itex]Y_{i}[/itex]), i = 1, ..., n have nonzero finite fourth moments.
Why is this significant? What is the relationship between large outliers and nonzero finite fourth moments? I don't intuitively see the mathematical explanation. Any help and/or direction is much appreciated.