Is it true of false that the classical errors in variables (CEV) assumption is that the measurement error is correlated with the unobserved true value of the explanatory variable.
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Is it true of false that the classical errors in variables (CEV) assumption is that the measurement error is correlated with the unobserved true value of the explanatory variable.
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- When the regression error is heteroskedastic, all of the following statements are false, with the exception of: a. the conditional variance of the error term is not constant. b. the OLS estimator is unbiased but not consistent. C. the OLS estimator is still BLUE.(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.With respect to a given product, describe the connection that exists between equalibrium/disequalibrium and prediction. cite an unique example
- Using Y as the dependent variable and X1, X2, X3, X4 and X5 as the explanatoryvariables, formulate an econometric model for data that is (i) time series data (ii)cross-sectional data and (iii) panel data – (Hint: please specify the specific model herenot its general form).Which one of the following statements is true for a linear regression model with non-spherical disturbances (i.e. E(uu') = Ω): The GLS estimator covariance matrix is unreasonable. The OLS estimator is not consistent. The standard formula for the OLS estimator covariance matrix is incorrect. The GLS estimator is not consistent. All of the above. None of the above.Y 70 12 50 9 57 60 14 43 9 52 11 i. Find the estimators for Bi and B2 correct to decimal points and fit the regression equation for X and Y when X is the explanatory variable. Interpret the results from the obtained equation. calculate the sum of error squared. Find the variance of the sum square error ii. iii. iv. Find the standard error for B2 Find the coefficient of correlation and give its interpretation V. vi.
- Consider the OLS estimator 3;. Under the Gauss-Markov assumptions, O the estimator is the best linear unbiased estimator. O the estimator is asymptotically normally distributed. O the estimator has the properties stated in the other three possible answers. O the estimator is consistent.If the error term covariance matrix is not spherical, but it is diagonal, then you have: Autocorrelation, but no heteroskedasticity. Heterskedasticity and autocorrelation. Heteroskedasticity, but no autocorrelation. Both heteroskedasticity and autocorrelation. Neither hetroskedasticity or autocorrelation.8. Which of the following best describes the linear probability model? The model is the application of the linear multiple regression model to a binary dependent variable The model is an example of probit estimation The model is another form of logit estimation The model is the application of the multiple regression model with a binary variable as at least one of the regressors OO
- The assumption that is required to shows the efficiency of the OLS estimator, consistency and unbiasedness is: i) Cov(u,,u-;) { A0 ii) Var(u,) =o? iii) E(u,) = 0 iv) u, ~ N(0,0²) a) (i), (ii) and (iii) only b) (i) and (iii) only c) (ii) and (iv) only d) (i), (ii) (iii) and (iv) Answer O A ODConsider the following formula: y i - ( β 0 ^ + β 1 ^ x i ) . What does this formula describe? OLS slope estimator Error term Causal effect of x on y residualThe error term in a regression equation is said to exhibit homoskedasticty if ____________. a) it has the same variance for all values of the explanatory variable(s). b) None of the other possible answers correctly finish the sentence. c) it takes the value of one given any values of the explanatory variable(s). d) it has the same value for all values of the explanatory variable(s). e) it has a zero conditional mean.