- #1

- 76

- 2

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.