Description

Book Synopsis
This rigorous but brilliantly lucid book presents a self-contained treatment of modern economic dynamics. Stokey, Lucas, and Prescott develop the basic methods of recursive analysis and illustrate the many areas where they can usefully be applied.

Trade Review
The book is a tour de force. The authors present a unified approach to the techniques and applications of recursive economic theory. The presentations of discrete-time dynamic programming and of Markov processes are authoritative. There is a wide-ranging series of examples drawn from all branches of the discipline, but with special emphasis on macroeconomics. In the short run, the book will be a vital reference in any advanced course in macroeconomic theory. In the long run, it may help to remove the traditional boundaries between microeconomic theory and macroeconomic theory. -- Andrew Caplin, Columbia University
This book is a wonderful collection of results on the techniques of dynamic programming with great applications to economics written by giants in the field. -- Sanford J. Grossman, University of Pennsylvania
A magnificent work that is bound to have immense influence on the ways economists think about dynamic systems for many years to come. My own guess is that this book will eventually acquire the stature, say, of Hicks’s Value and Capital or Samuelson’s Foundations. -- Thomas J. Sargent, The Hoover Institution

Table of Contents
I. THE RECURSIVE APPROACH 1. Introduction 2. An Overview 2.1 A Deterministic Model of Optimal Growth 2.2 A Stochastic Model of Optimal Growth 2.3 Competitive Equilibrium Growth 2.4 Conclusions and Plans II. DETERMINISTIC MODELS 3. Mathematical Preliminaries 3.1 Metric Spaces and Normed Vector Spaces 3.2 The Contraction Mapping Theorem 3.3 The Theorem of the Maximum 4. Dynamic Programming under Certainty 4.1 The Principle of Optimality 4.2 Bounded Returns 4.3 Constant Returns to Scale 4.4 Unbounded Returns 4.5 Euler Equations 5. Applications of Dynamic Programming under Certainty 5.1 The One-Sector Model of Optimal Growth 5.2 A "Cake-Eating" Problem 5.3 Optimal Growth with Linear Utility 5.4 Growth with Technical Progress 5.5 A Tree-Cutting Problem 5.6 Learning by Doing 5.7 Human Capital Accumulation 5.8 Growth with Human Capital 5.9 Investment with Convex Costs 5.10 Investment with Constant Returns 5.11 Recursive Preferences 5.12 Theory of the Consumer with Recursive Preferences 5.13 A Pareto Problem with Recursive Preferences 5.14 An (s, S) Inventory Problem 5.15 The Inventory Problem in Continuous Time 5.16 A Seller with Unknown Demand 5.17 A Consumption-Savings Problem 6. Deterministic Dynamics 6.1 One-Dimensional Examples 6.2 Global Stability: Liapounov Functions 6.3 Linear Systems and Linear Approximations 6.4 Euler Equations 6.5 Applications III. STOCHASTIC MODELS 7. Measure Theory and Integration 7.1 Measurable Spaces 7.2 Measures 7.3 Measurable Functions 7.4 Integration 7.5 Product Spaces 7.6 The Monotone Class Lemma

Recursive Methods in Economic Dynamics

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A Hardback by Nancy L. Stokey, Robert E. Lucas, Edward C. Prescott

15 in stock


    View other formats and editions of Recursive Methods in Economic Dynamics by Nancy L. Stokey

    Publisher: Harvard University Press
    Publication Date: 01/10/1989
    ISBN13: 9780674750968, 978-0674750968
    ISBN10: 0674750969

    Description

    Book Synopsis
    This rigorous but brilliantly lucid book presents a self-contained treatment of modern economic dynamics. Stokey, Lucas, and Prescott develop the basic methods of recursive analysis and illustrate the many areas where they can usefully be applied.

    Trade Review
    The book is a tour de force. The authors present a unified approach to the techniques and applications of recursive economic theory. The presentations of discrete-time dynamic programming and of Markov processes are authoritative. There is a wide-ranging series of examples drawn from all branches of the discipline, but with special emphasis on macroeconomics. In the short run, the book will be a vital reference in any advanced course in macroeconomic theory. In the long run, it may help to remove the traditional boundaries between microeconomic theory and macroeconomic theory. -- Andrew Caplin, Columbia University
    This book is a wonderful collection of results on the techniques of dynamic programming with great applications to economics written by giants in the field. -- Sanford J. Grossman, University of Pennsylvania
    A magnificent work that is bound to have immense influence on the ways economists think about dynamic systems for many years to come. My own guess is that this book will eventually acquire the stature, say, of Hicks’s Value and Capital or Samuelson’s Foundations. -- Thomas J. Sargent, The Hoover Institution

    Table of Contents
    I. THE RECURSIVE APPROACH 1. Introduction 2. An Overview 2.1 A Deterministic Model of Optimal Growth 2.2 A Stochastic Model of Optimal Growth 2.3 Competitive Equilibrium Growth 2.4 Conclusions and Plans II. DETERMINISTIC MODELS 3. Mathematical Preliminaries 3.1 Metric Spaces and Normed Vector Spaces 3.2 The Contraction Mapping Theorem 3.3 The Theorem of the Maximum 4. Dynamic Programming under Certainty 4.1 The Principle of Optimality 4.2 Bounded Returns 4.3 Constant Returns to Scale 4.4 Unbounded Returns 4.5 Euler Equations 5. Applications of Dynamic Programming under Certainty 5.1 The One-Sector Model of Optimal Growth 5.2 A "Cake-Eating" Problem 5.3 Optimal Growth with Linear Utility 5.4 Growth with Technical Progress 5.5 A Tree-Cutting Problem 5.6 Learning by Doing 5.7 Human Capital Accumulation 5.8 Growth with Human Capital 5.9 Investment with Convex Costs 5.10 Investment with Constant Returns 5.11 Recursive Preferences 5.12 Theory of the Consumer with Recursive Preferences 5.13 A Pareto Problem with Recursive Preferences 5.14 An (s, S) Inventory Problem 5.15 The Inventory Problem in Continuous Time 5.16 A Seller with Unknown Demand 5.17 A Consumption-Savings Problem 6. Deterministic Dynamics 6.1 One-Dimensional Examples 6.2 Global Stability: Liapounov Functions 6.3 Linear Systems and Linear Approximations 6.4 Euler Equations 6.5 Applications III. STOCHASTIC MODELS 7. Measure Theory and Integration 7.1 Measurable Spaces 7.2 Measures 7.3 Measurable Functions 7.4 Integration 7.5 Product Spaces 7.6 The Monotone Class Lemma

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