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Unformatted text preview: EC220 EXAMINATION AND MARKING SCHEME, 2005 Note to students using this examination for revision purposes At the time of this examination we were using the notation of the second edition of my text, Introduction to Econometrics . The notation in that edition had a major advantage over the present notation in that manipulation of regression expressions was much simpler. However, there was a problem in that the notation was nonstandard and as such not liked by many teachers of econometrics. In the third edition I reluctantly abandoned it in favour of standard Σ –notation. I have therefore reissued the 2005 examination and the marking scheme using the new notation. Only the new notation will be acceptable in future examinations. With the old notation, Question 7 (b) could be handled relatively easily. With the new notation, this is not the case. Consequently in future there will not be any questions of this type. Students should also be aware of a second change affecting EC220 examinations. Calculators are no longer permitted in the examination, and the format of the examination has been adapted accordingly. © LSE 2005/EC220 Page 1 of 12 Summer 2005 examination EC220 Introduction to Econometrics Updated with third edition notation Suitable for all candidates Instructions to candidates Time allowed: 3 hours + 15 minutes reading time This paper contains nine questions. Answer any four questions. All questions will be given equal weight (25%). You are supplied with: Graph paper Statistical tables Logarithm tables (available on request). You may also use: Electronic calculator (as prescribed in the examination regulations) © LSE 2005/EC220 Page 1 of 12 1. (a) Suppose that a variable Y depends on a variable X with the relationship Y = β 2 X + u where u is a disturbance term that satisfies the regression model assumptions. (i) [5 marks] Explain in principle how one would derive the ordinary least squares (OLS) estimator of β 2 . (ii) [2 marks] Demonstrate that for this model the OLS estimator is ∑ ∑ = = n i i n i i i X Y X 1 2 1 (iii) [3 marks] Explain in general terms why OLS is an attractive estimation procedure if the disturbance term in the model satisfies the regression model assumptions. Note : Mathematical proofs of any assertions are not required and will not earn credit. (b) A variable Y depends on a nonstochastic variable X with the relationship Y = β 1 + β 2 X + u where u is a disturbance term that satisfies the regression model assumptions. You may assume that ( ) ( ) ( ) ∑ ∑ = = − − − n i i n i i i X X Y Y X X 1 2 1 is the OLS estimator of β 2 for this model, that it is unbiased, and that it has population variance ( ) ∑ = − n i i u X X 1 2 2 σ ....
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 Spring '10
 öcal
 Econometrics, Regression Analysis

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