Peter Kennedy – Law & Economics Center at George Mason

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title:   A Guide to Econometrics
          author:     Kennedy, Peter.
       publisher:     MIT Press
    isbn10 | asin:    0262112353
    print isbn13:     9780262112352
   ebook isbn13:      9780585202037
       language:      English
         subject      Econometrics.
publication date:     1998
               lcc:   HB139.K45 1998eb
             ddc:     330/.01/5195
         subject:     Econometrics.
                       cover

                                                Page iii


            A Guide to Econometrics
                  Fourth Edition
                           Peter Kennedy
                       Simon Fraser University

                          The MIT Press
                      Cambridge, Massachusetts

                               page_iii

                                                                Page iv



 1998 Peter Kennedy
All rights reserved. No part of this book may be reproduced in any form
or by any electronic or mechanical means (including photocopying,
recording, or information storage and retrieval), without permission in
writing from the publisher.
Printed and bound in The United Kingdom by TJ International.
ISBN 0-262 11235-3 (hardcover), 0-262-61140-6 (paperback)
Library of Congress Catalog Card Number: 98-65110

                               page_iv




Contents
Preface
I
Introduction
   1.1
   What is Econometrics?
   1.2
   The Disturbance Term
   1.3
   Estimates and Estimators
   1.4
   Good and Preferred Estimators
   General Notes
   Technical Notes
2
Criteria for Estimators
   2.1
   Introduction
   2.2
   Computational Cost
   2.3
   Least Squares
   2.4
   Highest R2
   2.5
   Unbiasedness
   2.6
   Efficiency
   2.7
   Mean Square Error (MSE)
   2.8
   Asymptotic Properties
   2.9
   Maximum Likelihood
   2.10
   Monte Carlo Studies
   2.11
   Adding Up
   General Notes
   Technical Notes
3
The Classical Linear Regression Model
   3.1
   Textbooks as Catalogs
   3.2
   The Five Assumptions
   3.3
   The OLS Estimator in the CLR Model
   General Notes
   Technical Notes


                                page_v


4
Interval Estimation and Hypothesis Testing
   4.1
   Introduction
   4.2
   Testing a Single Hypothesis: the t Test
   4.3
   Testing a Joint Hypothesis: the F Test
   4.4
   Interval Estimation for a Parameter Vector
   4.5
   LR, W, and LM Statistics
   4.6
   Bootstrapping
   General Notes
   Technical Notes
5
Specification
   5.1
   Introduction
   5.2
   Three Methodologies
   5.3
   General Principles for Specification
   5.4
   Misspecification Tests/Diagnostics
   5.5
   R2 Again
   General Notes
   Technical Notes
6
Violating Assumption One: Wrong Regressors, Nonlinearities, and Parameter
Inconstancy
   6.1
   Introduction
   6.2
   Incorrect Set of Independent Variables
   6.3
   Nonlinearity
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