Section 1: True/False, & explain why three or more sentences:
2. In the regression model Yi = β0 + β1Xi + β2Di + β3(Xi × Di) + ui, where X is a continuous variable and D is a binary variable, β3 has no meaning since (Xi×Di) = 0 when Di= 0.
ANSWER:
Yes, it is true when
=0,
= 0 then
Yi becomes

so here in the above equation, there is no
, so when
=0:
has no
meaning
The effect of X depends on D
=increment
to the effect of X, when D= 1 then Yi becomes

here
increment
to the effect of X
and when these two
=1
and
=0 indicates the
difference in slopes of two regression lines

Section 1: True/False, & explain why three or more sentences: 2. In the regression model Yi...
Suppose that we have data on ECON 333 test scores (Yi), duration for which student i studies for exam (Xi), and the major of the student, call it Di, where Di =( 1, if economics major 0, if non economics major Consider the following model: Yi = β0 + β1Xi + β2Di + β3DiXi + ui (1) where Assumption 1 holds: E (ui|Xi,Di) = 0. (2) Yi is the score between 0 and 100. Xi is the duration studied in...
3. Determine whether the following are true or false and explain why: a) R2 can be negative. b) R2 can be larger than 1. c) Adjusted R2 can be negative. d) Adjusted R2 can be larger than 1. e) suˆ is a measure of out-of-sample fit f) CV is a measure of out-of-sample fit Now consider the following two models: Yi = β0 + β1Xi + ui (M1) Yi = β0 + β1Xi + β2X2 i + ui (M2) 1...
Consider the regression model: yi = β0 + β1Xi + εi for…. i = 1 Where the dummy variable (0 = failure and 1 = success). Suppose that the data set contains n1 failure and n2 successes (and that n1+n2 = n) Obtain the X^T(X) matrix Obtain the X^T(Y) matrix Obtain the least square estimate b
1. If a true model of simple linear regression reads: yi −y ̄ = β0 +β1(xi −x ̄)+εi for i = 1, 2, · · · , n, showβ0 =0andβˆ0 =0. (1pt) (hint: use the formula of estimator βˆ0 = y ̄ − βˆ1x ̄.)
Section 1: True/False, & explain why in two or three sentences: 4. You are trying to forecast the quarterly US dollar-Euro exchange rate as a function of the difference between US & EU benchmark interest rates in this quarter and the previous quarter. This is an autoregressive distributed lag model.
Consider the linear probability model Yi = β0 + β1Xi + ui. Assume E(ui|Xi)=0. Which of the following statements are true? Question 5 options: The predicted value of the dependent variable can be greater than 1 or less than 0. Thus, the OLS estimator of β1 is biased. The predicted value of the dependent variable will always be between 0 and 1. Thus, the OLS estimator of β1 is unbiased. The predicted value of the dependent variable will always be...
Consider the following regression model: Xi = Bo + Bixi + y; where yi is individual i's University GPA and xi is the individual's high school grades. a. What do you think is in ui? Do you think E[ulx) = 0? Suggest a variable that you think might affect University GPA that isn't included in the regression equation but should be. c. What sign of bias would you expect in an OLS regression of y on x? Briefly explain. d....
Testing the equality of two regression coefficients. Suppose that you
are given the following regression model:
Yi = β1 + β2X2i + β3X3i + ui
and you want to test the hypothesis that β2 = β3. If we assume that the ui
are normally distributed, it can be shown that
t = βˆ
2 − βˆ
3
var (βˆ
2) + var (βˆ
3) − 2 cov (βˆ
2, βˆ
3)
follows the t distribution with n − 3...
TRUE or FALSE and Explain why: In a multiple regression model, the inclusion of a variable
TRUE or FALSE and Explain why: If the error term in a simple regression model is heteroskedastic, the estimated OLS coefficients are biased.