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| Preface | |
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| An Overview of Econometrics | |
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| The Importance of Econometrics | |
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| Types of Economic Data | |
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| Working with Data: Graphical Methods | |
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| Working with Data: Descriptive Statistics and Correlation | |
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| Chapter Summary | |
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| Exercises | |
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| A Non-technical Introduction to Regression | |
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| Introduction | |
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| The Simple Regression Model | |
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| The Multiple Regression Model | |
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| Chapter Summary | |
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| Exercises | |
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| The Econometrics of the Simple Regression Model | |
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| Introduction | |
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| A Review of Basic Concepts in Probability in the Context of the Regression Model | |
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| The Classical Assumptions for the Regression Model | |
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| Properties of the Ordinary Least Squares Estimator of � | |
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| Deriving a Confidence Interval for � | |
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| Hypothesis Tests about � | |
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| Modifications to Statistical Procedures when � 2 is Unknown | |
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| Chapter Summary.Exercises | |
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| Proof of the Gauss-Markov theorem | |
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| Using a Asymototic Theory in the Simple Regression Model | |
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| The Econometrics of the Multiple Regression Model | |
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| Introduction | |
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| Basic Results for the Multiple Regression Model | |
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| Issues Relating to the Choice of Explanatory Variables | |
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| Hypothesis Testing in the Multiple Regression Model | |
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| Choice of Functional Form in the Multiple Regression Model | |
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| Chapter Summary | |
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| Exercises | |
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| Appendix: Wald and Lagrange multiplier tests | |
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| The Multiple Regression Model: Freeing up Classical Assumptions | |
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| Introduction | |
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| Basic Theoretical Results | |
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| Heteroskedasticity | |
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| The Regression Model with Autocorrelated Errors | |
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| The Instrumental Variables Estimator | |
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| Chapter Summary | |
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| Exercises | |
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| Appendix: Asymptotic Results for the OLS and Instrumental variables Estimators | |
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| Univariate Time Series Analysis | |
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| Introduction | |
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| Time Series Notation | |
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| Trends in Time Series Variables | |
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| The Autocorrelation Function | |
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| The Autoregressive Model | |
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| Defining Stationarity | |
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| Modelling Volatility | |
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| Chapter Summary | |
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| Exercises | |
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| Appendix: MA and ARMA Models | |
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| Regression with Time Series Variables | |
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| Introduction | |
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| Time Series Regression when X and Y are Stationary | |
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| Time Series Regression When Y and X have Unit Roots | |
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| Time Series Regression when Y and X have Unit Roots but are NOT Cointegrated | |
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| Granger Causality | |
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| Vector Autoregressions | |
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| Chapter Summary | |
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| Exercises | |
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| Appendix: The Theory of Forecasting | |
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| Models for Panel Data | |
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| Introduction | |
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| The Pooled Model | |
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| Individual Effects Models | |
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| Chapter Summary | |
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| Exercises | |
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| Qualitative Choice and Limited Dependent Variable Models | |
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| Introduction | |
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| Qualitative Choice Models | |
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| Limited Dependent Variable Models | |
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| Chapter Summary | |
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| Exercises | |
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| Bayesian Econometrics | |
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| An Overview of Bayesian Econometrics | |
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| The Normal Linear Regression Model with Natural Conjugate Prior and a Single Explanatory Variable | |
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| Chapter Summary | |
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| Exercises | |
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| Appendix: Bayesian Analysis of the Simple Regression Model with Unknown Variance | |
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| Mathematical Basics | |
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| Probability Basics | |
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| Basic Concepts in Asymptotic Theory | |
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| Writing an Empirical Project | |
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| Tables | |
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| Bibliography | |
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| Index | |