Suppose the conditional mean function is Y = Bo + B1X + B2X² + B3X3 + U where E[U|X]3D0. By mistake, a researcher omitted X^2 and X^3 terms in the regression and ran regression of Y on X and an intercept only. It turns out that covariance between X and B2X +B3X is nonzero. Is the OLS estimator researcher computed consistent for beta_1? Yes, since the omitted variables are just functions of X. O Yes, since the covariance between X and B2X2 + B3X° is nonzero No, since the covariance between X and B2X4 + B3X is nonzero No, since the omitted variables are negligibly small.
Suppose the conditional mean function is Y = Bo + B1X + B2X² + B3X3 + U where E[U|X]3D0. By mistake, a researcher omitted X^2 and X^3 terms in the regression and ran regression of Y on X and an intercept only. It turns out that covariance between X and B2X +B3X is nonzero. Is the OLS estimator researcher computed consistent for beta_1? Yes, since the omitted variables are just functions of X. O Yes, since the covariance between X and B2X2 + B3X° is nonzero No, since the covariance between X and B2X4 + B3X is nonzero No, since the omitted variables are negligibly small.
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 91E
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