Complete and Incomplete Econometric Models
1st Edition
Published on 8. February 2010
176 pages
978-1-4008-3524-9 (ISBN)
Description
Econometric models are widely used in the creation and evaluation of economic policy in the public and private sectors. But these models are useful only if they adequately account for the phenomena in question, and they can be quite misleading if they do not. In response, econometricians have developed tests and other checks for model adequacy. All of these methods, however, take as given the specification of the model to be tested. In this book, John Geweke addresses the critical earlier stage of model development, the point at which potential models are inherently incomplete.
Summarizing and extending recent advances in Bayesian econometrics, Geweke shows how simple modern simulation methods can complement the creative process of model formulation. These methods, which are accessible to economics PhD students as well as to practicing applied econometricians, streamline the processes of model development and specification checking. Complete with illustrations from a wide variety of applications, this is an important contribution to econometrics that will interest economists and PhD students alike.
Summarizing and extending recent advances in Bayesian econometrics, Geweke shows how simple modern simulation methods can complement the creative process of model formulation. These methods, which are accessible to economics PhD students as well as to practicing applied econometricians, streamline the processes of model development and specification checking. Complete with illustrations from a wide variety of applications, this is an important contribution to econometrics that will interest economists and PhD students alike.
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John Geweke
Complete and Incomplete Econometric Models
Book
02/2010
1st Edition
Princeton University Press
€82.50
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Person
John Geweke is Distinguished Research Professor at the University of Technology Sydney, and research professor at the University of Colorado. He is the coeditor of the Journal of Econometrics and his most recent previous book is Contemporary Bayesian Econometrics and Statistics (Wiley).
Content
Series Editors' Introduction vii
Preface ix
Chapter 1: Introduction 1
Chapter 2: The Bayesian Paradigm 7
2.1 Complete Models 10
2.2 Model Comparison and Averaging 16
2.3 Simulation 19
2.4 Model Evaluation 23
Chapter 3: Prior Predictive Analysis and Model Evaluation 34
3.1 Data and Models 35
3.2 Prior Predictive Analysis 47
3.3 Comparison with an Incomplete Model 71
3.4 Appendix: A Gaussian Copula for Evaluating Predictive Densities of
Vector Functions of Interest 84
Chapter 4: Incomplete Structural Models 86
4.1 The Essential Elements of DSGE Models 88
4.2 Strong Econometric Interpretation 95
4.3 Weak Econometric Interpretation 98
4.4 Minimal Econometric Interpretation 109
4.5 Implications for Structural Modeling 118
Chapter 5: An Incomplete Model Space 122
5.1 Context and Motivation 123
5.2 Pools of Two Models 130
5.3 Examples of Two-Model Pools 135
5.4 Pools of Multiple Models 142
5.5 Multiple-Model Pools: An Example 150
5.6 Pooling and Model Improvement 155
5.7 Consequences of an Incomplete Model Space 158
References 161
Preface ix
Chapter 1: Introduction 1
Chapter 2: The Bayesian Paradigm 7
2.1 Complete Models 10
2.2 Model Comparison and Averaging 16
2.3 Simulation 19
2.4 Model Evaluation 23
Chapter 3: Prior Predictive Analysis and Model Evaluation 34
3.1 Data and Models 35
3.2 Prior Predictive Analysis 47
3.3 Comparison with an Incomplete Model 71
3.4 Appendix: A Gaussian Copula for Evaluating Predictive Densities of
Vector Functions of Interest 84
Chapter 4: Incomplete Structural Models 86
4.1 The Essential Elements of DSGE Models 88
4.2 Strong Econometric Interpretation 95
4.3 Weak Econometric Interpretation 98
4.4 Minimal Econometric Interpretation 109
4.5 Implications for Structural Modeling 118
Chapter 5: An Incomplete Model Space 122
5.1 Context and Motivation 123
5.2 Pools of Two Models 130
5.3 Examples of Two-Model Pools 135
5.4 Pools of Multiple Models 142
5.5 Multiple-Model Pools: An Example 150
5.6 Pooling and Model Improvement 155
5.7 Consequences of an Incomplete Model Space 158
References 161
