How to obtain the confidence interval

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Reference no: EM131132328

Question 1- Short questions

Please answer True or False. Answer without explanation will not receive credits. Full credit requires a formal proof.

(a) The inclusion of an irrelevant variable will always reduce precision (False or True?)

(b) Assume the model: Yi = β0 + β1Xi + Ui

but the true model is Yi = β0 + β1Xi + γZi + Ui Assuming that γ > 0, then β^1OLS will be upward biased.

(c) Suppose your are studying the effect of Gender and Race on wages. You are working with the following variables

Yi: Log wage

DiG: A gender dummy (0 if female, 1 if male)

DiR: A race dummy (1 if Black, 0 if White)

and the following model

Yi = α0 + α1DiG + α2DiR + Ui.

In this set up, you can interpret α0 as the average (log) wage for White females, i.e.,

E(Yi|DiG = 0, DiR  = 0) = α0.

(False or True?)

Question 2 - In the context of the linear model:

Y = α + βX + U

(a) Suppose you obtain α^ and Var^^). Describe how to obtain the confidence interval at the 90% confidence level for α.

(b) Suppose you obtain β^ and Var^^). Describe the procedure to test H0: β = 1 against the alternative hypothesis H1: β ≠ 1.

Question 3 - Generate a data of 1000 observations using the following structure:

Y = -0.3 - 0.2X1 + 0.3X2 + U

where X1 ∼ N(1, 4), X2 = 0.3 × X1 +V , U ∼ N(0, 1) and V ∼ N(0, 1).

(a) Does the model satisfy the GAUSS-MARKOV theorem? Would your estimates be BLUE?

(b) Drop V, U from your model. Present the OLS results of a regression of Y on X1. Interpret your findings. Are they biased? Why?

(c) Add X2 to your regression. Interpret your results. Did your R2 increase? Why? Present a formal proof.

(d) Suppose that now X2 = V and V ∼ N(2, 1). Run the regression Y on X1 and X2 and compare your results with those from a regression of Y on X1. Are you getting biased results? Why?

(e) Suppose now you got information on a third variable X3. Construct X3 ∼ Uniform(-1, 4). Add X3 to your original regression model (i.e., where X2 = 0.5 × X1 + V, U ∼ N(0, 1)).

Interpret the new R2. Explain the changes on your coefficients and t-tests.

Reference no: EM131132328

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