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Suppose that, for n observations y1,,yn, we have specified a multiple linear regression model of
the form yi=0+1xi1+2xi2+ei where the ei are uncorrelated errors, with E(eiX)=0 and Var(eiX)=2.
Consider the situation where we are interested not in the values of the coefficients 1 and 2
separately, but instead in their difference =12. a) Show that the estimator ^=^1^2 is an umbiased
estimator of . That is, show that E(^X)= b) Derive an expression for the variance of this estimator,
Var(), in terms of the relevant entries of the variance-covariance matrix Var(), where is the OLS
estimator of =(0,1,2)T.

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Suppose that for n observations y1yn we have specified .pdf

  • 1. Suppose that, for n observations y1,,yn, we have specified a multiple linear regression model of the form yi=0+1xi1+2xi2+ei where the ei are uncorrelated errors, with E(eiX)=0 and Var(eiX)=2. Consider the situation where we are interested not in the values of the coefficients 1 and 2 separately, but instead in their difference =12. a) Show that the estimator ^=^1^2 is an umbiased estimator of . That is, show that E(^X)= b) Derive an expression for the variance of this estimator, Var(), in terms of the relevant entries of the variance-covariance matrix Var(), where is the OLS estimator of =(0,1,2)T.