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# HW5 - the VIFs Based on VIF values ﬁnd out which...

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Econ 444 Elementary Econometrics (Winter 2010) HOMEWORK EXERCISE: 5 Due in class on Wed, March 3 1. State with reasons whether the following statements are true or false. (1.a) Despite perfect multicollinearity, OLS estimators are BLUE. (1.b) One of the consequences of heteroskedasticity is that OLS estimators are no longer unbiased and hence are not BLUE. (1.c) If heteroskedasticity is present the conventional t and F tests are invalid. 2. Download Multi.xls from Carmen. It provides data on following variables: Y : New passenger Cars Sold ( in thousands). X1 : New Cars Consumer price index ( 1967=100). X2 : Consumer Price Index for all Items( 1967=100). X3 : Personal Disposable Income( in billions of \$). X4 : Interest rate (in %). X5 : Labor force. ( in thousands). Suppose we want to estimate, Y i = β 0 + β 1 X 1 i + β 2 X 2 i + β 3 X 3 i + β 4 X 4 i + β 5 X 5 i + i (1) (2.a) Estimate (1) in Eviews and submit your computer output for the same. 1

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(2.b) Calculate the VIF for each of the estimated coefficient. Report these and also your Eviews output for all the equations you estimate for calculating
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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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