STUDENT SOLUTIONS MANUAL Jeffrey M. Wooldridge Introductory Econometrics: A Modern Approach‚ 4e CONTENTS Preface Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Introduction The Simple Regression Model Multiple Regression Analysis: Estimation Multiple Regression Analysis: Inference Multiple Regression Analysis: OLS Asymptotics Multiple Regression Analysis: Further Issues Multiple Regression Analysis With Qualitative Information: Binary (or Dummy) Variables Heteroskedasticity
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A brief overview of the classical linear regression model What is a regression model? Regression versus correlation Simple regression Some further terminology Simple linear regression in EViews -- estimation of an optimal hedge ratio The assumptions underlying the classical linear regression model Properties of the OLS estimator Precision and standard errors An introduction to statistical inference 27 27 28 28 37 2.6 2.7 2.8 2.9 v 40 43 44 46 51 vi Contents
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Models Introduction The Simple Regression Model The Multiple Linear Regression Models Violations of the Assumptions of CLRMs Definition • Econometrics is the application of statistical‚ and mathematical techniques to the analysis of economic data with a purpose of verifying or refuting economic theories. Theory Mathematical Model Econometric Model As income increases‚ consumption also increases‚ but not as much as income. yi = f ( xi ) = β0 + β1xi y i = f ( x i ) = β0 + β1x i +
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eAUSTRALIAN SCHOOL OF BUSINESS SCHOOL OF ECONOMICS ECON2206 / ECON3290 (ARTS) Introductory Econometrics Course outline SESSION 2‚ 2011 Lecturer in Charge: Dr. Rachida Ouysse Room ASB441 Telephone: 9385 3321 Email: rouysse@unsw.edu.au Lectures: Fridays 9am-11am Venue: Law Theatre G04 Website: http://telt.unsw.edu.au/ TABLE OF CONTENTS 1 STAFF CONTACT DETAILS 1 1 1 1 1 1 2 2 2 2 3 3 3 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 7 9 9 9 10 10 10 12 13 13 13
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Hieu Nguyen – FIN 5309 Section 1 Assignment 1 2.3 Table 2.2 X=0 X=1 Total Y=0 0.15 0.07 0.22 Y=1 0.15 0.63 0.78 Total 0.30 0.70 1.00 With W = 3+6X and V = 20-7Y‚ we have: (W|X=0)=3 (W|X=1)=9 Total (V|Y=0)=20 0.15 0.07 0.22 (V|Y=1)=13 0.15 0.63 0.78 Total 0.30 0.70 1.00 a. E(W) = 3 x 0.3 + 9 x 0.7 = 7.2 E(V) = 20 x 0.22 + 13 x 0.78 = 14.54 b. = (3 – 7.2)2 x 0.3 + (9 - 7.2)2 x 0.7 = 7.56 = (20 – 14.54)2 x 0.22 + (13 – 14.54)2 x 0.78 = 8.4084 c. cov
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Answers to Selected Exercises For Principles of Econometrics‚ Fourth Edition R. CARTER HILL Louisiana State University WILLIAM E. GRIFFITHS University of Melbourne GUAY C. LIM University of Melbourne JOHN WILEY & SONS‚ INC New York / Chichester / Weinheim / Brisbane / Singapore / Toronto CONTENTS Answers for Selected Exercises in: Probability Primer 1 Chapter 2 The Simple Linear Regression Model 3 Chapter 3 Interval Estimation and Hypothesis Testing
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ECON2206/ECON3290: Introductory Econometrics Session 1‚ 2009 Course Project Solution Guide Each question is worth 1 mark - and there are 20 questions in total. Answers should be clear and legible. Note Instruction (d) on the Questions: “when performing statistical tests‚ to always state the null and alternative hypotheses‚ the test statistic and it’s distribution under the null hypothesis‚ the level of significance and the conclusion of the test.” Marks are not awarded when this instruction is not
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PART TWO Solutions to Empirical Exercises Chapter 3 Review of Statistics Solutions to Empirical Exercises 1. (a) Average Hourly Earnings‚ Nominal $’s Mean AHE1992 AHE2004 AHE2004 − AHE1992 (b) Average Hourly Earnings‚ Real $2004 Mean AHE1992 AHE2004 AHE2004 − AHE1992 15.66 16.77 Difference 1.11 SE(Mean) 0.086 0.098 SE(Difference) 0.130 95% Confidence Interval 15.49−15.82 16.58−16.96 95% Confidence Interval 0.85−1.37 11.63 16.77 Difference 5.14 SE(Mean) 0.064 0.098 SE(Difference) 0.117 95%
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Journal of Econometrics 41 (1989) 205-235. North-Holland TESTING INEQUALITY CONSTRAINTS IN LINEAR ECONOMETRIC MODELS Frank A. WOLAK* Stanford Received lJniversi[v‚ February Stunford‚ CA 94305‚ tiSA 1986‚ final version received July 1988 This paper develops three asymptotically equivalent tests for examining the validity of imposing linear inequality restrictions on the parameters of linear econometric models. First we consider the model .v = X/3 + e. where r
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ECON 140 Section 13‚ November 28‚ 2013 ECON 140 - Section 13 1 The IV Estimator with a Single Regressor and a Single Instrument 1.1 The IV Model and Assumptions Consider the univariate linear regression framework: Yi = β0 + β1 Xi + ui Until now‚ it was assumed that E (ui |Xi ) = 0‚ i.e. conditional mean independence. Let’s relax this assumption and allow the covariance between Xi and ui to be dierent from zero. Our problem here is that ui is not observed. Doing OLS
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