Introduction to Econometrics

Introduction to Econometrics has been written as a core textbook for a first course in econometrics taken by undergraduate or graduate students. It is intended for students taking a single course in econometrics with a view towards doing practical data work. It will also be highly useful for students interested in understanding the basics of econometric theory with a view towards future study of advanced econometrics. To achieve this end, it has a practical emphasis, showing how a wide variety of models can be used with the types of data sets commonly used by economists. However, it also has enough discussion of the underlying econometric theory to give the student a knowledge of the statistical tools used in advanced econometrics courses. Key Features: * A non-technical summary of the basic tools of econometrics is given in chapters 1 and 2, which allows the reader to quickly start empirical work. * The foundation offered in the first two chapters makes the theoretical econometric material, which begins in chapter 3, more accessible. * Provides a good balance between econometric theory and empirical applications. * Discusses a wide range of models used by applied economists including many variants of the regression model (with extensions for panel data), time series models (including a discussion of unit roots and cointegration) and qualitative choice models (probit and logit). An extensive collection of web-based supplementary materials is provided for this title, including: data sets, problem sheets with worked through answers, empirical projects, sample exercises with answers, and slides for lecturers. URL: www.wileyeurope.com/college/koop

Gary Koop is Professor of Economics at the University of Strathclyde. Gary has published numerous articles econometrics in journals such as the Journal of Econometrics and Journal of Applied Econometrics. Gary has taught econometrics for many years and is the author of following textbooks, all published by John Wiley & Sons Ltd: Analysis of Economic Data 2ed, Analysis of Financial Data and Bayesian Econometrics

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

Summary

Author Biography

Table of Contents

Supplemental Materials