Introduction to Econometrics

by Koop, Gary

• ISBN13: 9780470032701
• ISBN10: 0470032707
• Edition: 1st
• Format: Paperback
• Copyright: 2008-03-10
• Publisher: WILEY

Summary

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

Author Biography

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

Table of Contents

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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