Econometrics 710 Midterm Exam 2000
1. The model is
yi = xiβ + ei E (ei| xi ) = 0
where xi , β and ei are scalar. We consider the estimator
β˜ = y-/x = i=1Σnyi/i=1Σnxi
We assume that xi and ei have finite fourth moments and that {yi, xi} are a random sample (iid).
(a) Find E(β˜| X).
(b) Find V ar (β˜| X).
(c) Show that β˜ →p β as n → ∞. Does this require any additional assumptions?
(d) Find the asymptotic distribution of √n(β˜ - β). as n →∞.
(e) Without imposing any additional assumptions, is β˜ necessarily less efficient than OLS? (By efficiency, I mean lower asymptotic variance.)
2. Take the linear regression Y = Xβ + e with E(ei | xi) = 0. Let θ = 1/β1where β1 is the first element of β. Let βˆ be the OLS estimator of β and Vˆ be the estimator of V ar (β)ˆ. Find au asymptotically valid 95% confidence interval for θ. (Give the explicit formula as a function of βˆ aud Vˆ.)
3. In the linear regression Y = Xβ + e with E(ei|xi) = 0, it is known that the true β satisfies the restriction
Rβ = 0
where R is a q × k matrix with q < k. Consider the estimator
β˜ = βˆ - (X'X)-1 R'[R (X'X)-1R']-1Rβˆ.
(a) Show that Rβ˜ = 0.
(b) Find E(β˜|X).
(s) Find V ar (β˜| X). [Hint: First write β˜ as a linear function of βˆ.]
(d) Give an expression for a valid standard error for the elements of β˜. You do not need to give a proof of validity.
4. Take the linear regression Y = Xβ + e with E(ei|xi) = 0. For one particular value of x, the object of interest is the conditional mean
E(yi|xi = x) = g(x).
Describe how you would use the percentile-t bootstrap to construct a confidence interval for g(x).