Which of the following are consequences of heteroscedasticity for regression analysis? Choose as many statements as you think are correct. Incorrect answers are penalised. O a. Confidence intervals computed using the standard methods do not have the correct probability coverage. O b. The standard OLS estimator of B, is biased for i = = 1,...,k O. The estimated standard errors of the coefficient estimators, computed using the standard method, are reliable. O d. The standard OLS estimator of a is biased. O e. The standard OLS estimator of B, is inefficient for i = 1,..., k. %3D Of. The t-statistics produced by the OLS procedure in Gretl should be disregarded, but the p-values are reliable.
Which of the following are consequences of heteroscedasticity for regression analysis? Choose as many statements as you think are correct. Incorrect answers are penalised. O a. Confidence intervals computed using the standard methods do not have the correct probability coverage. O b. The standard OLS estimator of B, is biased for i = = 1,...,k O. The estimated standard errors of the coefficient estimators, computed using the standard method, are reliable. O d. The standard OLS estimator of a is biased. O e. The standard OLS estimator of B, is inefficient for i = 1,..., k. %3D Of. The t-statistics produced by the OLS procedure in Gretl should be disregarded, but the p-values are reliable.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Which of the following are consequences of heteroscedasticity for regression analysis? Choose as many statements as you think are correct.
Incorrect answers are penalised.
O a. Confidence intervals computed using the standard methods do not have the correct probability coverage.
O b. The standard OLS estimator of B, is biased for i =
= 1,...,k
O. The estimated standard errors of the coefficient estimators, computed using the standard method, are reliable.
O d. The standard OLS estimator of a is biased.
O e. The standard OLS estimator of B, is inefficient for i = 1,..., k.
Of. The t-statistics produced by the OLS procedure in Gretl should be disregarded, but the p-values are reliable.
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