Cover

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Title Page, copyright

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Contents

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pp. v-vi

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Series Editors’ Introduction

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pp. vii-viii

The Econometric and Tinbergen Institutes Lectures deal with topics in econometrics that have important policy implications. The lectures cover a wide range of topics and are not confined to any one area or subdiscipline. Leading international scientists in the fields of econometrics in which applications play a major role are invited...

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Preface

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p. ix

This book elaborates the substance of the Econometric and Tinbergen Institutes Lectures that I presented at Erasmus University Rotterdam in June 2008. I am grateful to the Econometric Institute, Princeton University Press, and especially to Herman van Dijk for this opportunity to synthesize themes in my research program from the past decade. I am indebted to several anonymous reviewers for their comments, and to Gianni Amisano...

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1 Introduction

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pp. 1-6

Models are the venue for expressing, comparing, and evaluating alternative ways of addressing important questions in economics. Applied econometricians are called upon to engage in these exercises using data and, often, formal methods whose properties are understood in decision-making contexts. This is true of work in other sciences as well. There is a...

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2 The Bayesian Paradigm

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pp. 7-33

The Bayesian paradigm provides a powerful and practical structure for managing the risk inherent in decision making. This chapter discusses the elements of this structure, which is standard in the subjective Bayesian approach to inference and decision making. A number of recent texts provide more detailed consideration of this approach in econometrics, including Poirier...

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3 Prior Predictive Analysis and Model Evaluation

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pp. 34-85

Prior predictive analysis, described in section 2.4.1, is a versatile tool that provides insight into the characteristics of a model and the means to evaluate a model’s adequacy for given data. This chapter illustrates prior predictive analysis and introduces two new techniques: one for studying model characteristics and the other for model evaluation. The emphasis is on...

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4 Incomplete Structural Models

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pp. 86-121

The dynamic stochastic general equilibrium (DSGE) model has become a central analytical tool in studying aspects of economic behavior in which aggregate uncertainty is important. Models in this family abstract sufficiently from measured economic behavior that clarification of the dimensions of reality they are intended to mimic is important. This clarification is essential if these models...

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5 An Incomplete Model Space

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pp. 122-160

The formal solutions of most decision problems in economics, in the private and public sectors as well as in academic contexts, require probability distributions for magnitudes that are as yet unknown. Point forecasts are rarely sufficient. For econometric investigators whose work may be used by clients in different situations the rationale for producing predictive distributions is clear. Increasing awareness of these requirements, combined with advances...

References

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pp. 161-165