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Unformatted text preview: ECON2206/ECON3290: Introductory Econometrics Session 1, 2010 Course Project Solution Guide Each question is worth 1 mark  and there are 20 questions in total. Note Instruction (d): Remember that when performing statistical tests, always state the null and alternative hypotheses, the test statistic and its distribution under the null hypothesis, the level of signi f cance and the conclusion of the test. Full credit cannot be given if this is ignored. A printout of the SHAZAM output must be attached at the end of the answers (otherwise 5 marks are to be deducted). (1) What is the average, minimum, and maximum value and standard deviation for each of the variables in the HPRICEN.RAW sample ? 23926 2 5394 5 4474 6 3615 3 8835 37 756 5000 006 3 850 3 560 1 130 18 70 50001 88 976 8 710 8 780 12 130 71 100 9414 8 7 1497 1 1699 7322 2 1206 14 916 (2) Would you expect the correlation between and to be positive or negative ? Would you expect the correlation between and to be positive or negative ? Explain. What is the correlation between and and and , in the sample ? I would expect the correlation between and to be negative  that prices will be higher in areas where there is less pollution or lower re F ecting consumers demand. People would be willingness to pay more for cleaner air and a nice environment, which in turn implies a negative association between and  which is a measure of air pollution. By similiar reasoning, I would also expect a negative association between and  which is a local area bad. High crime areas are undesirable, so people would be willing to buy houses in higher crime areas only if the price is lower. From the sample of data, the raw correlations are ( ) = 35732 , and ( ) = 34937 . Simple Regression Model (3) Consider the simple regression model: log( ) = + 1 log( ) + (1) What is the in terpretation of the coe cient 1 in the model ? What is the interpretation of the coe cient in (1) ? Explain. The coe cient 1 represents the change in expected log( ) due to a one unit change in log( ) . Given the loglog functional form, 1 is also the elasticity of expected with respect to . The coe cient is expected log( ) when log( ) is equal to 0 [note: it is not d log( ) when...
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This note was uploaded on 06/05/2011 for the course ECON 2206 taught by Professor Yang during the Three '11 term at University of New South Wales.
 Three '11
 yang
 Econometrics

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