Show the estimated variance for β0
The basic form of multiple regression equation for ‘n’ observation is
yi =
0 + 1xi1 + 2xi2 +
... pxip + i for
i = 1,2, ... n.
= independent variable (predictors of y)
β0 = common intercept or constant in the regression equation
coefficient of respective independent variable (x)
Considering the regression result, the regression equation for given problem is,
If the values are substitute,
Hence the value of = -8.8123
The indicates the slope of the regression curve without any influence of independent variables or predictors (x)
Consider a population linear regression model: Yt=β0 + β1Xt + ut Calculate: 1. Variance 2. Covariance of ut and Xt 3. β0 4. β1
Consider the regression model y=β0+β1x1+β2x2+u Suppose this is estimated by Feasible Weighted Least Squares (FWLS) assuming a conditional variance function Varux=σ2h(x). Which of the following statements is correct? A) The function h(x) does not need to be estimated as part of the procedure B) If the assumption about the conditional variance of the error term is incorrect, then FWLS is still consistent. C) FWLS is the best linear unbiased estimator when there is heteroscedasticity. D) None of the above answers...
3. Give the population model Yi = β0 + β1Xi + ui T he variance of β1 will (BLANK) as the variation in x decreases, and it will decrease if we (BLANK) the variance of the error term. a) increase. increase b) increase. decrease c) decrease. decrease d) decrease. increase
6. Assuming the conditional variance of disturbance term is given by var (u Ix) σ2exp (β0 + βίχί + . . . + ßkxk), List the steps to get the weighted least square estimator for 0.P1*..Pk 6. Assuming the conditional variance of disturbance term is given by var (u Ix) σ2exp (β0 + βίχί + . . . + ßkxk), List the steps to get the weighted least square estimator for 0.P1*..Pk
Exhibit a. y = β0 + β1x1 + β2x2 + ε b. E(y) = β0 + β1x1 c. = b0 + b1 x1 + b2 x2 d. E(y) = β0 + β1x1 + β2x2 3. Refer to Exhibit. Which equation describes the multiple regression equation? a. equation a b. equation b c. equation c d. equation d
Suppose that ∆Yt follows the AR(1) model ∆Yt = β0 +β1∆Yt−1 +ut . Show that Yt follows an AR(2) model.
Suppose that ∆Yt follows the AR(1) model ∆Yt = β0 +β1∆Yt−1 +ut . Show that Yt follows an AR(2) model.
Use the knowledge of "Introductions to Econometrics" to answer the following questions: Yt=β0+β1Xt+Ut Show that for the Least Square Estimators: a) The sum of the residuals equals zero. b) The sum of the product of the independent variable and residuals equals zero. Step by step
Suppose the true model is given by y = β0 + β1x1 + β2 x2 + u , if we estimate the following models: (I) y = β0 + β1x1 + β2 x2 + β3x3 + u (II) y = β0 + β1x1 + u what are the consequences?
D Question 1 Select the best description for the symbols βί and β0 in a lnear model ßi is the population intercept and β0 is the population slope respectively βί is the sample intercept and β0 is the sample slope respectively. B is the population slope and Bo is the population intercept respectively β1 is the sample slope and β0 is the sample intercept respectively. o ๏ DQuestion 2 Select the best representation of the population regression line.