Question

sub : Econometrics The true model is : y=X1*beta1 + e ..(1) but we estimate y...

sub : Econometrics

The true model is :

y=X1*beta1 + e ..(1)

but we estimate

y = X1*beta1 + X2*beta2 + e = X*beta + e ..(2)

where X = (X1,X2) and beta' = (beta1', beta2'). Let the estimator of beta in (1) be beta~(tilde) and the estimator of beta in (2) be beta^.

(a) Show that E(beta1^) = beta1 and E(beta2^)=0

(b) Show that beta1^ in (2) has larger variance than beta1tilde in (1)

(c) Explain why the probablility of a Type 2 error increases in (2)

pls help me

Business   Economics   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Question 1 Suppose you estimate the following regression function where Y, X1, and X2 are continuous...
Question 1 Suppose you estimate the following regression function where Y, X1, and X2 are continuous variables measured in integers: Yhat=0.5+0.25*X1 −0.01*X2−0.43*X
3 Suppose that X2=X1*X1 The standard error of beta0hat is 0.10. The standard error of beta1hat is 0.05. The standard error of beta2hat is 0.005. The standard error of beta3hat is 0.05. What is the marginal effect of X1 when it increases from 3 to 4? Round to two decimal places. 10 points Question 2 Refer to question...
Let X1, X2, ..., Xn be a random sample from a distribution with probability density function...
Let X1, X2, ..., Xn be a random sample from a distribution with probability density function f(x; θ) = (θ 4/6)x 3 e −θx if 0 < x < ∞ and 0 otherwise where θ > 0 . a. Justify the claim that Y = X1 + X2 + ... + Xn is a complete sufficient statistic for θ. b. Compute E(1/Y ) and find the function of Y which is the unique minimum variance unbiased estimator of θ. b.  Compute...
DATA 1 ID X1 Y A 0 9 B 1 10 C 0 5 D 1...
DATA 1 ID X1 Y A 0 9 B 1 10 C 0 5 D 1 1 E 0 0 The zero order model is Ŷ = 8 − 2.5X1 1. What is the residual error in using the zero order model to predict Y for ID C? (Correct answer is -3, please show me how to find it) 2. What is the error in using the mean of Y to predict Y for ID C? (correct answer is -2,...
Let X1,X2...Xn be i.i.d. with N(theta, 1) a) find the CR Rao lower-band for the variance...
Let X1,X2...Xn be i.i.d. with N(theta, 1) a) find the CR Rao lower-band for the variance of an unbiased  estimator of theta b)------------------------------------of theta^2 c)-----------------------------------of P(X>0)
(a) Show that the parametric equations x = x1 + (x2 − x1)t,    y = y1 +...
(a) Show that the parametric equations x = x1 + (x2 − x1)t,    y = y1 + (y2 − y1)t where 0 ≤ t ≤ 1, describe (in words) the line segment that joins the points P1(x1, y1) and P2(x2, y2). (b) Find parametric equations to represent the line segment from (−1, 6) to (1, −2). (Enter your answer as a comma-separated list of equations. Let x and y be in terms of t.)
Consider an estimated multiple regression model as given below. log(y)ˆ=3.45+0.12log(x1)−0.42x2+0.36x3 Which of the following statements is...
Consider an estimated multiple regression model as given below. log(y)ˆ=3.45+0.12log(x1)−0.42x2+0.36x3 Which of the following statements is correct in relation to the above estimated model? 1. If x3 increases by 1 unit, y declines by 0.36 2. If x2 falls by 2 per cent, log(y) decreases by 42percent 3. When the values of x1, x2 and x3 are three, the predicted value of y is 5.2 4. f x1 increases by 1 percent, y rises by 0.12 percent
Consider the data below: x1 x2 y -1 1 1 -1 2 3 -1 3 6...
Consider the data below: x1 x2 y -1 1 1 -1 2 3 -1 3 6 1 1 2 1 1 3 1 3 8 a) Fit the model Y = B0 + B1x1 + B2x2 + B3x22 + error. For i = 1,2,...,6, error is normal, with a mean of 0 and a variance of sigma2. b) Test if B3 < 1, at a 5% level of significance.
Consider the multiple regression model E(Y|X1 X2) = β0 + β1X1 + β2X2 + β3X1X2 Can...
Consider the multiple regression model E(Y|X1 X2) = β0 + β1X1 + β2X2 + β3X1X2 Can we interpret β1 as the change in the conditional mean response for a unit change in X1 holding all the other predictors in the model fixed? Group of answer choices a. Yes, because that is the traditional way of interpreting a regression coefficient. b. Yes, because the response variable is quantitative and thus the partial slopes are interpreted exactly in that manner. c. No,...
For our estimates of the population parameters to be consistent in a multivariable regression model, we...
For our estimates of the population parameters to be consistent in a multivariable regression model, we need which of the following assumptions to be true? a)There are no large outliers in X1, X2, …, Xk, or Y. b)There is no perfect multicollinearity. c)The variance of the error, u, given every value of every X, is constant. d)There is no imperfect multicollinearity. e)The sample is randomly selected from the population of interest. f)The errors, u, are normally distributed. g) E[u |...
Let X1, . . . , Xn be i.i.d from pmf f(x|λ) where f(x) = (e^(−λ)*(λ^x))/x!,...
Let X1, . . . , Xn be i.i.d from pmf f(x|λ) where f(x) = (e^(−λ)*(λ^x))/x!, λ > 0, x = 0, 1, 2 a) Find MoM (Method of Moments) estimator for λ b) Show that MoM estimator you found in (a) is minimal sufficient for λ c) Now we split the sample into two parts, X1, . . . , Xm and Xm+1, . . . , Xn. Show that ( Sum of Xi from 1 to m, Sum...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT