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![In the linear model, if B = 0, then it means:
OA. the value of 'B' in the model is unknown.
OB. the value of 'u' in the model is zero.
Oc. E(u) = 0.
OD.
none of the above.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ffb9bb1c8-fccc-4c05-9f0d-4021f59cbb0e%2F782845d9-389c-4324-8484-11b3c8de790e%2F17kyaj_processed.jpeg&w=3840&q=75)
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- This is model question. I need100% accurate answer. Please review it.Consider the output here from a regression in R. What is 3₂? Coefficients: Estimate (Intercept) 1.708 5.404 -1.478 9.531 X1 X2 X3 Std. Error 0.555 2.792 0.6 2.758An independent variable in a model is also called:a. explained variable.b. unexplained variable.c. explanatory variable.d. dependent variable.
- (Econmetrics) Q.1 How can you test for general misspecification of model if it would have only (any of) two independent variables?A(n) variable is calculated from within the model. A(n). endogenous; endogenous endogenous; exogenous exogenous; endogenous exogenous; exogenous none of the above variable can never be taken as given.potter makes and sells ceramic bowls. It is observed that when the price is $32, only 9 bowls are sold in a week; but when the price decreases to $10, weekly sales rise to 20. Assuming that demand can be modelled by a linear function, (a) obtain a formula for Pin terms of Q (b) Calculate for the slope of the curve if the relationship between p and Q is linear. (c) comment on the likely reliability of the model
- The predicted value of Y is... a. The value that y takes on when X equal 0 b. The effect that a one unit change in dependent variable is expected to have on the independent variable, holding all else constant c. The value of Y when the slope is multiplied a specific X and then that value is added to the intercept d. The observed value of the dependent variable that is associated with a specific value of the independent variable.Quantile regression (QR) is different from OLS in that: a. QR estimates marginal effects at the mean values of the dependent variables. b. QR does not estimate marginal effects at the mean values of the dependent and independent variables. c. QR minimizes the sum of squared residuals to obtain the coefficient estimates. d. QR only uses the data below the quantile where the quantile regression is being estimated.The O'Neill Shoe Manufacturing Company will produce a special-style shoe if the order size is large enough to provide a reasonable profit. For each special-style order, the company incurs a fixed cost of $2,625 for the production setup. The variable cost is $55 per pair, and each pair sells for $80. (a) Let x indicate the number of pairs of shoes produced. Develop a mathematical model for the total cost (C) of producing x pairs of shoes. C = (b) Let P indicate the total profit. Develop a mathematical model for the total profit realized from an order for x pairs of shoes. P = (c) How large must the shoe order be before O'Neill will break even? x =
- QUESTION 7 Estimation of the IV regression model: а. is possible if the number of instruments is equal to the number of endogenous variables. b.is possible if the model is over-identified. C. is possible if the number of instruments is larger than the number of endogenous variables. d. is possible if there is exact identification. е. All of the above. O f. None of the above.QUESTION 1 In the equation, y = 8o + Bjx1 + 8zx2 + u, 8z is a(n) O a. intercept parameter O b. slope parameter O. dependent variable O d. independent variable QUESTION 2 If an independent variable in a multiple linear regression model is an exact linear combination of other independent variables, the model suffers from the problem of O a. perfect collinearity O b.heteroskedasticty O . homoskedasticity O d. omitted variable bias QUESTION 3 Which of the following is true of R 2? O a. R- usually decreases with an increase in the number of independent variables in a regression. O b.R2 shows what percentage of the total variation in the dependent variable, Y, is explained by the explanatory variables. OC.A low R2 indicates that the Ordinary Least Squares line fits the data well. O d. R² is also called the standard error of regression. QUESTION 4 We estimate the model Wage, = -2.91+0.568educ; + 0.033 exper; +0.115 tenure; by OLS, where wage is the hourly wage of a worker measured in dollars,…(a) Interpret the elasticity of cigarette consumption with respect to prices. (b) Does this regression model return the expected sign for this relationship? Explain. (c) Is the independent variable's coefficient statistically significant at a = 0.05? Explain. (d) As you have noticed, both the dependent and independent variables are defined in logs. Does this fact violate the linearity portion of CLRM Assumption I? Explain your answer. (e) A Shapiro-Wilk test on this model's residuals returns a p-value of 0.5329. Given this fact, is CLRM Assumption VII satisfied? Explain.
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