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Econometrics: A Modern Introduction

By Michael P. Murray

Published by Prentice Hall

Published Date: Aug 4, 2005

Table of Contents

OVERVIEW

Part I - The Linear Regression Model

1.  What is Econometrics?

2. Choosing Estimators: Intuition and Monte Carlo Methods

3.  Linear Estimators and the Gauss—Markov Theorem

4.  Blue Estimators for the Slope and Intercept of a Straight Line


5.  Residuals


6.   Multiple Regression

 

Part II - Specification and Hypothesis Testing

 

7.  Testing Single Hypotheses in Regression Models


8.  Superfluous and Omitted Variables, Multicollinearity and Binary Variables


9.  Testing Multiple Hypotheses


Part III - Further Topics in Regression

 

10.  Heteroskedastic Disturbances

 

11.  Autoregressive Disturbances

12.  Large Sample Properties Of Estimators:  Consistency and Asymptotic Efficiency

13.  Instrumental Variables Estimation

14.  Systems of Equations

15.  Randomized Experiments and Natural Experiments


16.  Analyzing Panel Data


17.  Forecasting


18.  Stochastically Trending Variables


19.  Logit and Probit Models: Truncated and Censored Samples

 

Statistical Appendix                                                                                      

 

WEB EXTENSION 1            USING CALCULUS AND ALGEBRA FOR THE SIMPLEST CASE: n = 3

 

WEB EXTENSION 2            LOCAL AVERAGE TREATMENT EFFECTS

 

WEB EXTENSION 3            GENERALIZED METHOD OF MOMENTS ESTIMATORS AND IDENTIFICATION

 

WEB EXTENSION 4            MAXIMUM LIKELIHOOD ESTIMATION

 

WEB EXTENSION 5            ESTIMATORS FOR SYSTEMS OF EQUATIONS

 

WEB EXTENSION 6            MULTIPLE COINTEGRATING RELATIONSHIPS

 

WEB EXTENSION 7            LOG-ODDS AND LOGIT MODELS: USING GROUPED DATA

 

WEB EXTENSION 8            MULTINOMIAL MODELS

These online resources are available at no cost.

Companion Website for Econometrics: A Modern Introduction

http://www.aw-bc.com/murray

Purchase Info

ISBN-10: 0-321-11361-6

ISBN-13: 978-0-321-11361-0

Format: Book

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