Solution Manual for Introductory Econometrics A Modern Approach 5th Edition by Wooldridge

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  • ISBN-10 ‏ : ‎ 1111531048
  • ISBN-13 ‏ : ‎ 978-1111531041
  • Author: Jeffrey M. Wooldridge

Discover how empirical researchers today actually think about and apply econometric methods with the practical, professional approach in Wooldridge’s INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 5E. Unlike traditional books on the subject, INTRODUCTORY ECONOMETRICS unique presentation demonstrates how econometrics has moved beyond just a set of abstract tools to become a genuinely useful tool for answering questions in business, policy evaluation, and forecasting environments. Organized around the type of data being analyzed, the book uses a systematic approach that only introduces assumptions as they are needed, which makes the material easier to understand and ultimately leads to better econometric practices. Packed with timely, relevant applications, the text emphasizes incorporates close to 100 intriguing data sets in six formats and offers updates that reflect the latest emerging developments in the field.

Table Of Contents:

1 Introduction 1

1.1 About Econometrics 1

1.2 The Structure of This Book 3

1.3 Illustrations and Exercises 4

2 An Introduction to Linear Regression 6

2.1 Ordinary Least Squares as an Algebraic Tool 7

2.1.1 Ordinary Least Squares 7

2.1.2 Simple Linear Regression 9

2.1.3 Example: Individual Wages 11

2.1.4 Matrix Notation 11

2.2 The Linear Regression Model 12

2.3 Small Sample Properties of the OLS Estimator 15

2.3.1 The Gauss–Markov Assumptions 15

2.3.2 Properties of the OLS Estimator 16

2.3.3 Example: Individual Wages (Continued) 20

2.4 Goodness-of-Fit 20

2.5 Hypothesis Testing 23

2.5.1 A Simple t-Test 23

2.5.2 Example: Individual Wages (Continued) 25

2.5.3 Testing One Linear Restriction 25

2.5.4 A Joint Test of Significance of Regression Coefficients 26

2.5.5 Example: Individual Wages (Continued) 28

2.5.6 The General Case 29

2.5.7 Size, Power and p-Values 30

2.5.8 Reporting Regression Results 32

2.6 Asymptotic Properties of the OLS Estimator 33

2.6.1 Consistency 33

2.6.2 Asymptotic Normality 35

2.6.3 Small Samples and Asymptotic Theory 37

2.7 Illustration: The Capital Asset Pricing Model 39

2.7.1 The CAPM as a Regression Model 40

2.7.2 Estimating and Testing the CAPM 41

2.7.3 The World’s Largest Hedge Fund 43

2.8 Multicollinearity 44

2.8.1 Example: Individual Wages (Continued) 47

2.9 Missing Data, Outliers and Influential Observations 48

2.9.1 Outliers and Influential Observations 48

2.9.2 Robust Estimation Methods 50

2.9.3 Missing Observations 51

2.10 Prediction 53

Wrap-up 54

Exercises 55

3 Interpreting and Comparing Regression Models 60

3.1 Interpreting the Linear Model 60

3.2 Selecting the Set of Regressors 65

3.2.1 Misspecifying the Set of Regressors 65

3.2.2 Selecting Regressors 66

3.2.3 Comparing Non-nested Models 71

3.3 Misspecifying the Functional Form 73

3.3.1 Nonlinear Models 73

3.3.2 Testing the Functional Form 74

3.3.3 Testing for a Structural Break 74

3.4 Illustration: Explaining House Prices 76

3.5 Illustration: Predicting Stock Index Returns 79

3.5.1 Model Selection 80

3.5.2 Forecast Evaluation 82

3.6 Illustration: Explaining Individual Wages 85

3.6.1 Linear Models 85

3.6.2 Loglinear Models 88

3.6.3 The Effects of Gender 91

3.6.4 Some Words of Warning 92

Wrap-up 93

Exercises 94

4 Heteroskedasticity and Autocorrelation 97

4.1 Consequences for the OLS Estimator 98

4.2 Deriving an Alternative Estimator 99

4.3 Heteroskedasticity 100

4.3.1 Introduction 100

4.3.2 Estimator Properties and Hypothesis Testing 103

4.3.3 When the Variances Are Unknown 104

4.3.4 Heteroskedasticity-consistent Standard Errors for OLS 105

4.3.5 Multiplicative Heteroskedasticity 106

4.3.6 Weighted Least Squares with Arbitrary Weights 107

4.4 Testing for Heteroskedasticity 108

4.4.1 Testing for Multiplicative Heteroskedasticity 108

4.4.2 The Breusch–Pagan Test 109

4.4.3 The White Test 109

4.4.4 Which Test? 110

4.5 Illustration: Explaining Labour Demand 110

4.6 Autocorrelation 114

4.6.1 First-order Autocorrelation 116

4.6.2 Unknown ? 118

4.7 Testing for First-order Autocorrelation 119

4.7.1 Asymptotic Tests 119

4.7.2 The Durbin–Watson Test 120

4.8 Illustration: The Demand for Ice Cream 121

4.9 Alternative Autocorrelation Patterns 124

4.9.1 Higher-order Autocorrelation 124

4.9.2 Moving Average Errors 125

4.10 What to Do When You Find Autocorrelation? 126

4.10.1 Misspecification 126

4.10.2 Heteroskedasticity-and-autocorrelation-consistent Standard Errors for OLS 128

4.11 Illustration: Risk Premia in Foreign Exchange Markets 129

4.11.1 Notation 129

4.11.2 Tests for Risk Premia in the 1-Month Market 131

4.11.3 Tests for Risk Premia Using Overlapping Samples 134

Wrap-up 136

Exercises 136

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