Lecture 4 Flashcards

1
Q

State Theorem 13. Hint, relates eigenvalues to convergence.

A

Given a linear regression model with E[ui] = 0, E[ui*uj] = σ^2I(i = j)
Then the LSE estimator Bn converges in second mean to B iff the smallest eigenvalue of Z’Z goes to infinity.

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2
Q

What are two sufficient condition for an estimator to be consistent?

A

If E[Bn] = B and V(Bn) -> 0

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3
Q

Are the two conditions for sufficiency of consistency of an estimator necessary?

A

No, because consistency does not require any moments to be finite.

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4
Q

Given a stochastic Xn, define the notion that Xn = Op(fn).

A

If for all ε > 0, ∃ c >= 0 and n0 > 0 s.t
P{|Xn| > c*fn} < ε, for all n >= n0

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5
Q

Given a stochastic Xn, define the notion that Xn = op(fn).

A

If Xn/fn converges in probability to 0.

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6
Q

Describe the difference between Op(1) and op(1) withoout using the standard definitions.

A

Op(1) means P{|Xn| >c} < ε for some c > 0 while op(1) means for ALL c > 0.

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7
Q

What are the three components of Theorem 15? Hint: they link Op(f) to op(f) and the moments of Xn.S

A
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8
Q

Wat is Theorem 16? Hint: it links operations of variables to Op() and op().

A
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9
Q

State theorem 12

A
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