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Unformatted text preview: the VIFs. Based on VIF values ﬁnd out which variables are most aﬀected by multicollinearity. 3. Consider the following regression equation, Y i = β + β 1 X i + ± i (2) Now suppose, V ar ( ± i ) = σ 2 X 3 i (3) (3.a) How would you transform the model to achieve homoskedastic ( or constant) error variance? Explain. (3.b) Is the OLS estimator of the transformed regression BLUE? 4. Download RD.xls from Carmen. The ﬁle contains cross section data on Research and Development expenditure in US in 1988 for diﬀerent industries: Sales i sales in the industry i. RDexp i R&D expenditure in industry i. Now suppose you want to estimate, RDexp i = β + β 1 Sales i + ± i (4) 4.a Estimate (4) using Eviews. Submit your output. 4.b Using Park’s test, test whether there is heteroskedasticity in (4) at 5% level of signiﬁcance. Report your eviews output for this test and state clearly whether you ﬁnd heteroskedasticity in the data. 2...
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This note was uploaded on 04/13/2010 for the course ECON 444 taught by Professor Ogaki during the Winter '07 term at Ohio State.
 Winter '07
 OGAKI
 Econometrics

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