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1 through lr4 without any role played by

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Unformatted text preview: t; population parameters ( βo , β1 ); then I sort the estimates so obtained and graph them into 2 histograms. Melissa Tartari (Yale) Econometrics 25 / 27 Part II: Non-Normal Disturbances II ˆ ˆ Observe that, both the histograms for β1 and βo are centered about the true value of the parameters (namely 1 and 3): this is as it should since we know that unbiasedness of the OLS estimator holds under LR.1 through LR.4 without any role played by distributional assumptions on the disturbance u . Melissa Tartari (Yale) Econometrics 26 / 27 Part II: Non-Normal Disturbances II ˆ ˆ Observe that, both the histograms for β1 and βo are centered about the true value of the parameters (namely 1 and 3): this is as it should since we know that unbiasedness of the OLS estimator holds under LR.1 through LR.4 without any role played by distributional assumptions on the disturbance u . However, we also see that the two histograms resemble a Gaussian distribution: this is the implication of Theorem...
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This note was uploaded on 02/13/2014 for the course ECON 350 taught by Professor Donaldbrown during the Fall '10 term at Yale.

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