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Stephane
Convergence rates of estimators and small/big o notations?
I'm trying to wrap my head around small and big o notations in the context of asymptotics for estimators. For the sake of clarity, pick for example this model:
Y = XB + u.
Let b be the OLS estimator of B (i.e., b := (X'X)^-1 X'Y). Under certain conditions, we can show:
plim(b-B) = 0 and sqrt(N)(b-B) converges to a normal distribution centered at 0.
QUESTIONS (read '_p' as an index):
1. My understanding of the o_p(.) notation is that we could also write the first statement above as b-B = o_p(1). Is this correct?
2. What is the convergence rate of the OLS estimator?
3. How would you tie any of this to the big o notation O_p?
Thanks in advance!
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What I am looking for is some kind of hands-on approach with relevant examples. If I need to cross the t's and dot the i's later, this background will make it easier anyway.
In other words, for my purposes, a book that only goes through abstract theorems and proofs would be a huge waste of time because:
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Any help is appreciated. Thanks.
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