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Informationen zum Autor Gary Koop is Professor of Economics at the University of Strathclyde. He previously held professorial positions at the Universities of Toronto, Edinburgh, Glasgow and Leicester. He has also held academic posts at the University of Cambridge, the London School of Economics, Boston University and Queen's University, Canada. Gary is the associate editor of the Journal of Econometrics, Econometrics Reviews, the Journal of Empirical Finance, Studies in Nonlinear Dynamics and Econometrics and the Journal of Applied Econometrics. He is the author of: Introduction to Econometrics, Bayesian Econometrics and Analysis of Financial Data, all of which are published by Wiley. Klappentext Analysis of Economic Data has, over three editions, become firmly established as a successful textbook for students studying data analysis whose primary interest is not in econometrics, statistics or mathematics.It introduces students to basic econometric techniques and shows the reader how to apply these techniques in the context of real-world empirical problems. The book adopts a largely non-mathematical approach relying on verbal and graphical inuition and covers most of the tools used in modern econometrics research. It contains extensive use of real data examples and involves readers in hands-on computer work. Zusammenfassung Analysis of Economic Data has, over three editions, become firmly established as a successful textbook for students studying data analysis whose primary interest is not in econometrics, statistics or mathematics. Inhaltsverzeichnis Preface to the Fourth Edition xi Preface to the Third Edition xiii Preface to the Second Edition xiv Preface to the First Edition xv 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 28 Appendix 2.3: Expected Values and Variances 30 Endnotes 32 Chapter 3 Correlation 34 Understanding Correlation 34 Understanding Why Variables Are Correlated 38 Understanding Correlation Through XY-Plots 41 Correlation Between Several Variables 45 Appendix 3.1: Mathematical Details 46 Endnotes 46 Chapter 4 Introduction to Simple Regression 48 Regression as a Best Fitting Line 48 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 64 Endnotes 66 Chapter 5 Statistical Aspects of Regression 67 Which Factors Affect the Accuracy of the Estimate ß¿ ? 68 Calculating a Confidence Interval for ß 72 Testing whether ß = 0 78 Hypothesis Testing Involving R2: The F-Statistic 82 Appendix 5.1: Using Statistical Tables to Test Whether ß = 0 85 Endnotes 87 References 88 Chapter 6 Multiple Regression 89 Regression as a Best Fitting Line 91 OLS Estimation of the Multiple Regression Model 91 Statistical Aspects of Multiple Regression 91 Interpreting OLS Estimates 92 Pitfalls of Using Simple Regression in a Multiple Regression Context 95 Omitted Variables Bias 97 Multicollinearity 99 Appendix 6.1: Mathematical Interpretation of Regression Coefficients 105 Endnotes 105 Chapter 7 Regression with Dummy Variables 107 Simple Regression with a Dummy Variable 109 Multiple Regression with Dummy Variables 110 Multiple Regression with Dummy and Non-dummy Explanatory Variables 113
