Guia de econometria - kennedy 98

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A Guide to Econometrics Kennedy, Peter. MIT Press 0262112353 9780262112352 9780585202037 English Econometrics. 1998 HB139.K45 1998eb 330/.01/5195 Econometrics. cover Page iii

A Guide to Econometrics Fourth Edition

Peter Kennedy Simon Fraser University The MIT PressCambridge, 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 2.7Mean 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 SingleHypothesis: 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 AssumptionOne: Wrong Regressors, Nonlinearities, and Parameter Inconstancy 6.1 Introduction 6.2 Incorrect Set of Independent Variables 6.3 Nonlinearity

6.4 Changing Parameter Values General Notes Technical Notes 7 Violating Assumption Two: Nonzero Expected Disturbance General Notes 8 Violating Assumption Three: Nonspherical Disturbances 8.1 Introduction 8.2 Consequences of Violation 8.3 Heteroskedasticity8.4 Autocorrelated Disturbances General Notes Technical Notes page_vi

9 Violating Assumption Four: Measurement Errors and Autoregression 9.1 Introduction 9.2 Instrumental Variable Estimation

9.3 Errors in Variables 9.4 Autoregression General Notes Technical Notes 10 Violating Assumption Four: Simultaneous Equations 10.1 Introduction 10.2 Identification 10.3 Single-equation Methods 10.4Systems Methods 10.5 VARs General Notes Technical Notes 11 Violating Assumption Five: Multicollinearity 11.1 Introduction 11.2 Consequences 11.3 Detecting Multicollinearity

11.4 What to Do General Notes Technical Notes 12 Incorporating Extraneous Information 12.1 Introduction 12.2 Exact Restrictions 12.3 Stochastic Restrictions 12.4 Pre-test Estimators 12.5 Extraneous Information and MSE GeneralNotes Technical Notes 13 The Bayesian Approach 13.1 Introduction 13.2 What is a Bayesian Analysis? 13.3 Advantages of the Bayesian Approach page_vii

13.4 Overcoming Practitioners' Complaints General Notes Technical Notes 14 Dummy Variables 14.1 Introduction 14.2 Interpretation 14.3 Adding Another Qualitative Variable 14.4 Interacting with Quantitative Variables 14.5 Observation-specific Dummies14.6 Fixed and Random Effects Models General Notes Technical Notes 15 Qualitative Dependent Variables 15.1 Dichotomous Dependent Variables 15.2 Polychotomous Dependent Variables 15.3 Ordered Logit/Probit

15.4 Count Data General Notes Technical Notes 16 Limited Dependent Variables 16.1 Introduction 16.2 The Tobit Model 16.3 Sample Selection 16.4 Duration Models General Notes Technical Notes...
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