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A Guide to Modern Econometrics 5th Edition

August 2017, ©2017
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A Guide to Modern Econometrics, 5th
 has become established as a highly successful textbook. It serves as a guide to alternative techniques in econometrics with an emphasis on intuition and the practical implementation of these approaches. This fifth edition builds upon the success of its predecessors. The text has been carefully checked and updated, taking into account recent developments and insights. It includes new material on causal inference, the use and limitation of p-values, instrumental variables estimation and its implementation, regression discontinuity design, standardized coefficients, and the presentation of estimation results.
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Table of Contents

 Preface xiii

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

2.2 The Linear Regression Model 12

2.3 Small Sample Properties of the OLS Estimator 15

2.4 Goodness-of-fit 20

2.5 Hypothesis Testing 23

2.6 Asymptotic Properties of the OLS Estimator 33

2.7 Illustration: The Capital Asset Pricing Model 39

2.8 Multicollinearity 44

2.9 Missing Data, Outliers and Influential Observations 48

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

3.3 Misspecifying the Functional Form 73

3.4 Illustration: Explaining House Prices 76

3.5 Illustration: Predicting Stock Index Returns 79

3.6 Illustration: Explaining Individual Wages 85

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

4.4 Testing for Heteroskedasticity 108

4.5 Illustration: Explaining Labour Demand 110

4.6 Autocorrelation 114

4.7 Testing for First-order Autocorrelation 119

4.8 Illustration: The Demand for Ice Cream 121

4.9 Alternative Autocorrelation Patterns 124

4.10 What to do When you Find Autocorrelation? 126

4.11 Illustration: Risk Premia in Foreign Exchange Markets 129

Wrap-up 136

Exercises 136

5 Endogenous Regressors, Instrumental Variables and GMM 139

5.1 A Review of the Properties of the OLS Estimator 140

5.2 Cases Where the OLS Estimator Cannot be Saved 143

5.3 The Instrumental Variables Estimator 150

5.4 Illustration: Estimating the Returns to Schooling 157

5.5 Alternative Approaches to Estimate Causal Effects 162

5.6 The Generalized Instrumental Variables Estimator 163

5.7 Institutions and Economic Development 171

5.8 The Generalized Method of Moments 175

5.9 Illustration: Estimating Intertemporal Asset Pricing Models 181

Wrap-up 184

Exercises 185

6 Maximum Likelihood Estimation and Specification Tests 187

6.1 An Introduction to Maximum Likelihood 188

6.2 Specification Tests 198

6.3 Tests in the Normal Linear Regression Model 204

6.4 Quasi-maximum Likelihood and Moment Conditions Tests 208

Wrap-up 212

Exercises 212

7 Models with Limited Dependent Variables 215

7.1 Binary Choice Models 216

7.2 Multiresponse Models 229

7.3 Models for Count Data 240

7.4 Tobit Models 246

7.5 Extensions of Tobit Models 256

7.6 Sample Selection Bias 265

7.7 Estimating Treatment Effects 269

7.7.1 Regression-based Estimators 271

7.8 Duration Models 278

Wrap-up 284

Exercises 285

8 Univariate Time Series Models 288

8.1 Introduction 289

8.2 General ARMA Processes 294

8.3 Stationarity and Unit Roots 299

8.4 Testing for Unit Roots 301

8.5 Illustration: Long-run Purchasing Power Parity (Part 1) 309

8.6 Estimation of ARMA Models 313

8.7 Choosing a Model 316

8.8 Illustration: The Persistence of Inflation 320

8.9 Forecasting with ARMA Models 324

8.10 Illustration: The Expectations Theory of the Term Structure 330

8.11 Autoregressive Conditional Heteroskedasticity 335

8.12 What about Multivariate Models? 342

Wrap-up 343

Exercises 344

9 Multivariate Time Series Models 348

9.1 Dynamic Models with Stationary Variables 349

9.2 Models with Nonstationary Variables 352

9.3 Illustration: Long-run Purchasing Power Parity (Part 2) 358

9.4 Vector Autoregressive Models 360

9.5 Cointegration: the Multivariate Case 364

9.6 Illustration: Money Demand and Inflation 372

Wrap-up 378

Exercises 379

10 Models Based on Panel Data 382

10.1 Introduction to Panel Data Modelling 383

10.2 The Static Linear Model 386

10.3 Illustration: Explaining Individual Wages 403

10.4 Dynamic Linear Models 405

10.5 Illustration: Explaining Capital Structure 414

10.6 Panel Time Series 419

10.7 Models with Limited Dependent Variables 426

10.8 Incomplete Panels and Selection Bias 433

10.9 Pseudo Panels and Repeated Cross-sections 439

Wrap-up 444

A Vectors and Matrices 450

A.1 Terminology 450

A.2 Matrix Manipulations 451

A.3 Properties of Matrices and Vectors 452

A.4 Inverse Matrices 453

A.5 Idempotent Matrices 454

A.6 Eigenvalues and Eigenvectors 454

A.7 Differentiation 455

A.8 Some Least Squares Manipulations 456

B Statistical and Distribution Theory 458

B.1 Discrete Random Variables 458

B.2 Continuous Random Variables 459

B.3 Expectations and Moments 460

B.4 Multivariate Distributions 461

B.5 Conditional Distributions 462

B.6 The Normal Distribution 463

B.7 Related Distributions 466

Bibliograph

 

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Author Information

MARNO VERBEEK is Professor of Finance at Rotterdam School of Management, Erasmus University (RSM). He held previous positions at KU Leuven and Tilburg University, and visiting appointments at Trinity College, Dublin and Université Panthéon-Assas Paris II. He has published in a wide variety of international journals, including Journal of Econometrics, Journal of Applied Econometrics, Management Science, Journal of Business and Economic Statistics, Review of Economics and Statistics, International Economic Review, and the Journal of Financial and Quantitative Analysis.

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New To This Edition

  • Clear and intuitive exposition, with a focus on implementation and practical relevance
  • Concise and attractive presentation, providing a useful guide to more specialized literature
  • More than 25 detailed empirical illustrations, each covering 2 to 9 pages, taken from a wide variety of fields
  • Coverage of a wide range of topics, including time series analysis, limited dependent variable models, panel data analysis and causal inference
  • Supplementary material, including PowerPoint slides for lectures, data sets of the empirical illustrations and exercises, and solutions to selected exercise, available through the book's website
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Wiley E-Text   
A Guide to Modern Econometrics, 5th Edition
ISBN : 978-1-119-40111-7
520 pages
June 2017, ©2018
$64.00   BUY

Paperback   
A Guide to Modern Econometrics, 5th Edition
ISBN : 978-1-119-40115-5
520 pages
August 2017, ©2017
$154.95   BUY

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