# 2007 - THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF...

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THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF ECONOMICS Eco~ 2206 I"TRODUCTORY ECOI\'OMETRICS FINAL EXAMI~ATIO:'-! SESSION 1, 2007 1. TIME ALLOWED - 2 Hours. 2. TOTAL NUMBER OF QUESTIONS - 6. 3. ANSWER ALL QUESTIONS. 4. ALL QUESTIONS ARE OF EQUAL VALUE (The marks awarded to each part of a question are indicated - the total marks for this exam is 60). 5. CANDIDATES MAY BRING THEIR OWN CALCULATORS TO THE EXAM 6. STATISTICAL TABLES ARE PROVIDED AT THE END OF THE EXAM PAPER 7. ALL ANSWERS MUST BE WRITTEN IN PEN. PENCILS MAY BE USED ONLY FOR DRAWING, SKETCHING OR GRAPHICAL WORK.

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ANSWER ALL SIX QUESTIONS REMINDER: When performing statistical tests, always state the null and alternative hypothe- ses, the test statistic and it's distribution under the null hypothesis, the level of significance and the conclusion of the test. Question 1. (10 Marks). (i) Suppose that the correct population regression model is: (1.1) However we only have data only on y and Xl, and as a consequence we estimate the following model by OLS: (1.2) In what circumstance will the OLS estimator for model (1.2): (a) provide an unbiased estimate of the true population parameter /31 ? (2 marks) (b) provide an estimate of /3 1 that has positive (or upward) bias? (2 (ii) Outline the advantages of using larger samples of data in regression analysis. (iii) A model used analysing the effect of house characteristics on the sale price was: log(price) = /3 0 + area + 2 bdrms + 3 x bdnns + u where price is the house price, is the floor area of the house (measured in square metres), and is the number of bedrooms. What is the partial effect on log (price) of increasing by 1 square metre? (2 marks). (iv) What is the meaning of the term "contemporaneous exogeneity" as used in the context of time series data? What is the difference between contemporaneous exogeneity and "strict exogeneity" as used in multiple regression models for time series data? 2
Question 2. (10 Marks in total) The following regression model explains the monthly wages as a function of years of education (educ) , years of labour market experience (exper) and current job tenure (tenure): (2.1) With a random sample of data the following output was obtained using SHAZAM: Welcome to SHAZAM - Version 10.0 I_sample 1 722 I_read wage educ exper tenure 4 VARIABLES AND 722 OBSERVATIONS STARTING AT OBS 1 I_genr Inwage=log(wage) 1_* Model estimates I_ols Inwage educ exper tenure REQUIRED MEMORY IS PAR= 81 CURRENT PAR= 2000 OLS ESTIMATION 722 OBSERVATIONS DEPENDENT VARIABLE= LNWAGE ... NOTE .. SAMPLE RANGE SET TO: 1, 722 R-SQUARE = 0.1551 R-SQUARE ADJUSTED = 0.1524 VARIANCE OF THE ESTIMATE-SIGMA**2 = 0.19493 STANDARD ERROR ESTIMATE-SIGMA = 0.44151 SUM SQUARED ERRORS-SSE= 139.96 MEAN DEPENDENT VARIABLE = 6.7790 LOG LIKELIHOOD FUNCTION -438.839 ELASTICITY AT MEANS 0.1487 0.0261 0.0143 0.8108 ESTIMATED T-RATIO PARTIAL STANDARDIZED NAME COEFFICIENT 718 DF P-VALUE CORR. EDUC 0.74864E-Ol 0.6512E-02 11.50 0.000 0.353 0.3905 EXPER 0.15328E-Ol0.3370E-02 4.549 0.147 0.1592 TENURE 0.13375E-Ol0.2587E-02 5.170 0.167 0.1612 CONSTANT 5.4967 0.1105 49.73 0.852 0.0000 (i) What is the interpretation of the coefficient on education, (31 ? (2 marks).

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## This note was uploaded on 06/11/2011 for the course ECON 2206 taught by Professor Yang during the Three '11 term at University of New South Wales.

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2007 - THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF...

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