Analysis of Economic Data / Edition 3

Analysis of Economic Data / Edition 3

by Gary Koop
     
 

ISBN-10: 0470713895

ISBN-13: 9780470713891

Pub. Date: 03/17/2009

Publisher: Wiley

The third edition of Analysis of Economic Data has been fully revised and updated and builds on the successes of the previous two editions. It teaches methods of data analysis to students whose primary interest is not in econometrics, statistics or mathematics, as well as those who are facing economic data analysis for the first time.  It shows

Overview

The third edition of Analysis of Economic Data has been fully revised and updated and builds on the successes of the previous two editions. It teaches methods of data analysis to students whose primary interest is not in econometrics, statistics or mathematics, as well as those who are facing economic data analysis for the first time.  It shows students how to apply econometric techniques in the context of real-world empirical problems. Analysis of Economic Data adopts a largely non-mathematical approach relying on verbal and graphical intuition and covers most of the tools used in modern econometrics research e.g. correlation, regression and extensions for time-series methods. 

New content includes:

  • More empirical examples, including more empirical project topics.
  • New material on financial volatility, including ARCH and GARCH models.
  • Extensive use of real data examples and involves readers in hands-on computer work.

The new edition is accompanied by a website www.wileyeurope.com/college/koop containing information for instructors and students, including datasets, PowerPoint slides, sample exam questions and answer sheets for problems in the book.

Product Details

ISBN-13:
9780470713891
Publisher:
Wiley
Publication date:
03/17/2009
Edition description:
Older Edition
Pages:
264
Product dimensions:
6.67(w) x 9.63(h) x 0.76(d)

Table of Contents

Preface to the Third Edition xi

Preface to the Second Edition xii

Preface to the First Edition xiii

Chapter 1 Introduction 1

Organization of the Book 3

Useful Background 4

Appendix 1.1 Mathematical Concepts Used in this Book 4

Endnote 7

References 7

Chapter 2 Basic Data Handling 8

Types of Economic Data 8

Obtaining Data 13

Working with Data: Graphical Methods 15

Working with Data: Descriptive Statistics 20

Appendix 2.1 Index Numbers 23

Appendix 2.2 Advanced Descriptive Statistics 29

Appendix 2.3 Expected Values and Variances 30

Endnotes 33

Chapter 3 Correlation 34

Understanding Correlation 34

Understanding Why Variables Are Correlated 39

Understanding Correlation through XY-plots 41

Correlation between Several Variables 45

Appendix 3.1 Mathematical Details 46

Endnotes 46

Chapter 4 An Introduction to Simple Regression 48

Regression as a Best Fitting Line 49

Interpreting OLS Estimates 53

Fitted Values and R2: Measuring the Fit of a Regression Model 56

Nonlinearity in Regression 60

Appendix 4.1 Mathematical Details 65

Endnotes 66

Chapter 5 Statistical Aspects of Regression 68

Which Factors Affect the Accuracy of the Estimate <$$$>? 69

Calculating a Confidence Interval for β 73

Testing whether β=0 79

Hypothesis Testing Involving R2: The F Statistic 84

Appendix 5.1 Using Statistical Tables for Testing whether β=0 87

Endnotes 88

References 89

Chapter 6 Multiple Regression 90

Regression as a Best Fitting Line 92

Ordinary Least Squares Estimation of the Multiple Regression Model 92

Statistical Aspects of Multiple Regression 92

Interpreting OLS Estimates93

Pitfalls of Using Simple Regression in a Multiple Regression Context 96

Omitted Variables Bias 98

Multicollinearity 100

Appendix 6.1 Mathematical Interpretation of Regression Coefficients 106

Endnotes 107

Chapter 7 Regression with Dummy Variables 109

Simple Regression with a Dummy Variable 111

Multiple Regression with Dummy Variables 112

Multiple Regression with Dummy and Nondummy Explanatory Variables 115

Interacting Dummy and Nondummy Variables 118

What if the Dependent Variable is a Dummy? 119

Endnotes 121

Chapter 8 Regression with Time Lags: Distributed Lag Models 122

Aside on Lagged Variables 124

Aside on Notation 126

Selection of Lag Order 130

Appendix 8.1 Other Distributed Lag Models 133

Endnotes 134

Chapter 9 Univariate Time Series Analysis 136

The Autocorrelation Function 139

The Autoregressive Model for Univariate Time Series 143

Nonstationary versus Stationary Time Series 146

Extensions of the AR(1) Model 148

Testing in the AR(p) with Deterministic Trend Model 153

Appendix 9.1 Mathematical Intuition for the AR(1) Model 158

Endnotes 159

References 160

Chapter 10 Regression with Time Series Variables 161

Time Series Regression when X and Y Are Stationary 162

Time Series Regression when Y and X Have Unit Roots: Spurious Regression 166

Time Series Regression when Y and X Have Unit Roots: Cointegration 166

Time Series Regression when Y and X Are Cointegrated: The Error Correction Model 173

Time Series Regression when Y and X Have Unit Roots but Are NOT Cointegrated 177

Endnotes 179

Chapter 11 Applications of Time Series Methods in Macroeconomics and Finance 181

Volatility in Asset Prices 182

Autoregressive Conditional Heteroskedasticity (ARCH) 188

Granger Causality 193

Vector Autoregressions 199

Appendix 11.1 Hypothesis Tests Involving More than One Coefficient 215

Endnotes 218

Chapter 12 Limitations and Extensions 220

Problems that Occur when the Dependent Variable Has Particular Forms 221

Problems that Occur when the Errors Have Particular Forms 222

Problems that Call for the Use of Multiple Equation Models 225

Endnotes 229

Appendix A Writing an Empirical Project 231

Description of a Typical Empirical Project 231

General Considerations 233

Project Topics 234

References 238

Appendix B Data Directory 239

Index 243

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