This book is an effective, concise text for students and researchers that combines the tools of dynamic programming with numerical techniques and simulation-based econometric methods. Doing so, it bridges the traditional gap between theoretical and empirical research and offers an integrated framework for studying applied problems in macroeconomics and microeconomics. In part I the authors first review the formal theory of dynamic optimization; they then present the numerical tools and econometric techniques necessary to evaluate the theoretical models. In language accessible to a reader with a limited background in econometrics, they explain most of the methods used in applied dynamic research today, from the estimation of probability in a coin flip to a complicated nonlinear stochastic structural model. These econometric techniques provide the final link between the dynamic programming problem and data. Part II is devoted to the application of dynamic programming to specific areas of applied economics, including the study of business cycles, consumption, and investment behavior. In each instance the authors present the specific optimization problem as a dynamic programming problem, characterize the optimal policy functions, estimate the parameters, and use models for policy evaluation. The original contribution of Dynamic Economics: Quantitative Methods and Applicationslies in the integrated approach to the empirical application of dynamic optimization programming models. This integration shows that empirical applications actually complement the underlying theory of optimization, while dynamic programming problems provide needed structure for estimation and policy evaluation.

Jerome Adda is a Lecturer in the Department of Economics at University College, London, and a Research Associate at the Institute of Fiscal Studies Russell Cooper is Professor in the Department of Economics at the University of Texas, Austin

1 Overview

1

(6)

I Theory

2 Theory of Dynamic Programming

7

(26)

2.1 Overview

7

(1)

2.2 Indirect Utility

7

(2)

2.2.1 Consumers

7

(1)

2.2.2 Firms

8

(1)

2.3 Dynamic Optimization: A Cake-Eating Example

9

(7)

2.3.1 Direct Attack

10

(2)

2.3.2 Dynamic Programming Approach

12

(4)

2.4 Some Extensions of the Cake-Eating Problem

16

(8)

2.4.1 Infinite Horizon

16

(4)

2.4.2 Taste Shocks

20

(2)

2.4.3 Discrete Choice

22

(2)

2.5 General Formulation

24

(7)

2.5.1 Nonstochastic Case

24

(5)

2.5.2 Stochastic Dynamic Programming

29

(2)

2.6 Conclusion

31

(2)

3 Numerical Analysis

33

(28)

3.1 Overview

33

(1)

3.2 Stochastic Cake-Eating Problem

34

(12)

3.2.1 Value Function Iterations

34

(6)

3.2.2 Policy Function Iterations

40

(1)

3.2.3 Projection Methods

41

(5)

3.3 Stochastic Discrete Cake-Eating Problem

46

(4)

3.3.1 Value Function Iterations

47

(3)

3.4 Extensions and Conclusion

50

(2)

3.4.1 Larger State Spaces

50

(2)

3.5 Appendix: Additional Numerical Tools

52

(9)

3.5.1 Interpolation Methods

52

(3)

3.5.2 Numerical Integration

55

(4)

3.5.3 How to Simulate the Model

59

(2)

4 Econometrics

61

(42)

4.1 Overview

61

(1)

4.2 Some Illustrative Examples

61

(18)

4.2.1 Coin Flipping

61

(13)

4.2.2 Supply and Demand Revisited

74

(5)

4.3 Estimation Methods and Asymptotic Properties

79

(18)

4.3.1 Generalized Method of Moments

80

(3)

4.3.2 Maximum Likelihood

83

(2)

4.3.3 Simulation-Based Methods

85

(12)

4.4 Conclusion

97

(6)

II Applications

5 Stochastic Growth

103

(36)

5.1 Overview

103

(1)

5.2 Nonstochastic Growth Model

103

(8)

5.2.1 An Example

105

(2)

5.2.2 Numerical Analysis

107

(4)

5.3 Stochastic Growth Model

111

(11)

5.3.1 Environment

112

(1)

5.3.2 Bellman's Equation

113

(2)

5.3.3 Solution Methods

115

(5)

5.3.4 Decentralization

120

(2)

5.4 A Stochastic Growth Model with Endogenous Labor Supply

122

(3)

5.4.1 Planner's Dynamic Programming Problem

122

(2)

5.4.2 Numerical Analysis

124

(1)

5.5 Confronting the Data

125

(7)

5.5.1 Moments

126

(2)

5.5.2 GMM

128

(2)

5.5.3 Indirect Inference

130

(1)

5.5.4 Maximum Likelihood Estimation

131

(1)

5.6 Some Extensions

132

(6)

5.6.1 Technological Complementarities

133

(1)

5.6.2 Multiple Sectors

134

(2)

5.6.3 Taste Shocks

136

(1)

5.6.4 Taxes

136

(2)

5.7 Conclusion

138

(1)

6 Consumption

139

(26)

6.1 Overview and Motivation

139

(1)

6.2 Two-Period Problem

139

(8)

6.2.1 Basic Problem

140

(3)

6.2.2 Stochastic Income

143

(2)

6.2.3 Portfolio Choice

145

(1)

6.2.4 Borrowing Restrictions

146

(1)

6.3 Infinite Horizon Formulation: Theory and Empirical Evidence

147

(17)

6.3.1 Bellman's Equation for the Infinite Horizon Problem

147

(1)

6.3.2 Stochastic Income

148

(2)

6.3.3 Stochastic Returns: Portfolio Choice

150

(3)

6.3.4 Endogenous Labor Supply

153

(3)

6.3.5 Borrowing Constraints

156

(4)

6.3.6 Consumption over the Life Cycle

160

(4)

6.4 Conclusion

164

(1)

7 Durable Consumption

165

(22)

7.1 Motivation

165

(1)

7.2 Permanent Income Hypothesis Model of Durable Expenditures

166

(5)

7.2.1 Theory

166

(2)

7.2.2 Estimation of a Quadratic Utility Specification

168

(1)

7.2.3 Quadratic Adjustment Costs

169

(2)

7.3 Nonconvex Adjustment Costs

171

(16)

7.3.1 General Setting

172

(1)

7.3.2 Irreversibility and Durable Purchases

173

(2)

7.3.3 A Dynamic Discrete Choice Model

175

(12)

8 Investment

187

(28)

8.1 Overview and Motivation

187

(1)

8.2 General Problem

188

(1)

8.3 No Adjustment Costs

189

(2)

8.4 Convex Adjustment Costs

191

(11)

8.4.1 Q Theory: Models

192

(1)

8.4.2 Q Theory: Evidence

193

(5)

8.4.3 Euler Equation Estimation

198

(3)

8.4.4 Borrowing Restrictions

201

(1)

8.5 Nonconvex Adjustment: Theory

202

(7)

8.5.1 Nonconvex Adjustment Costs

203

(5)

8.5.2 Irreversibility

208

(1)

8.6 Estimation of a Rich Model of Adjustment Costs

209

(4)

8.6.1 General Model

209

(3)

8.6.2 Maximum Likelihood Estimation

212

(1)

8.7 Conclusion

213

(2)

9 Dynamics of Employment Adjustment

215

(26)

9.1 Motivation

215

(1)

9.2 General Model of Dynamic Labor Demand

216

(1)

9.3 Quadratic Adjustment Costs

217

(7)

9.4 Richer Models of Adjustment

224

(5)

9.4.1 Piecewise Linear Adjustment Costs

224

(2)

9.4.2 Nonconvex Adjustment Costs

226

(2)

9.4.3 Asymmetries

228

(1)

9.5 The Gap Approach

229

(6)

9.5.1 Partial Adjustment Model

230

(1)

9.5.2 Measuring the Target and the Gap

231

(4)

9.6 Estimation of a Rich Model of Adjustment Costs

235

(3)

9.7 Conclusion

238

(3)

10 Future Developments

241

(24)

10.1 Overview and Motivation

241

(1)

10.2 Price Setting

241

(7)

10.2.1 Optimization Problem

242

(2)

10.2.2 Evidence on Magazine Prices

244

(1)

10.2.3 Aggregate Implications

245

(3)

10.3 Optimal Inventory Policy

248

(6)

10.3.1 Inventories and the Production-Smoothing Model

248

(4)

10.3.2 Prices and Inventory Adjustment

252

(2)

10.4 Capital and Labor

254

(1)

10.5 Technological Complementarities: Equilibrium Analysis

255

(2)

10.6 Search Models

257

(6)

10.6.1 A Simple Labor Search Model

257

(2)

10.6.2 Estimation of the Labor Search Model

259

(1)

10.6.3 Extensions

260

(3)

10.7 Conclusion

263

(2)

Bibliography

265

(10)

Index

275

What is included with this book?

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

Amazon no longer offers textbook rentals. We do!

Amazon no longer offers textbook rentals. We do!

We're the #1 textbook rental company. Let us show you why.

Dynamic Economics Quantitative Methods and Applications

9780262012010

0262012014

Supplemental Materials

Summary

Author Biography

Table of Contents

Supplemental Materials

Rewards Program