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9780262633093

Applied Computational Economics and Finance

by ;
  • ISBN13:

    9780262633093

  • ISBN10:

    0262633094

  • Format: Paperback
  • Copyright: 2004-09-01
  • Publisher: Mit Pr

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Summary

This book presents a variety of computational methods used to solve dynamic problems in economics and finance. It emphasizes practical numerical methods rather than mathematical proofs and focuses on techniques that apply directly to economic analyses. The examples are drawn from a wide range of subspecialties of economics and finance, with particular emphasis on problems in agricultural and resource economics, macroeconomics, and finance. The book also provides an extensive Web-site library of computer utilities and demonstration programs. The book is divided into two parts. The first part develops basic numerical methods, including linear and nonlinear equation methods, complementarity methods, finite-dimensional optimization, numerical integration and differentiation, and function approximation. The second part presents methods for solving dynamic stochastic models in economics and finance, including dynamic programming, rational expectations, and arbitrage pricing models in discrete and continuous time. The book uses MATLAB to illustrate the algorithms and includes a utilities toolbox to help readers develop their own computational economics applications.

Author Biography

Mario J. Miranda is Professor and Chair of Graduate Studies. Department of Agricultural, Environmental, and Development Economics, Ohio State University Paul L. Fackler is Associate Professor, Department of Agricultural and Resource Economics. North Carolina State University

Table of Contents

Preface xv
Introduction
1(6)
Some Apparently Simple Questions
1(2)
An Alternative Analytic Framework
3(4)
Exercises
4(3)
Linear Equations and Computer Basics
7(22)
L-U Factorization
8(2)
Gaussian Elimination
10(2)
Rounding Error
12(1)
Ill Conditioning
13(2)
Special Linear Equations
15(1)
Iterative Methods
16(13)
Exercises
19(1)
Appendix 2A: Computer Arithmetic
20(4)
Appendix 2B: Data Storage
24(2)
Bibliographic Notes
26(3)
Nonlinear Equations and Complementarity Problems
29(30)
Bisection Method
30(2)
Function Iteration
32(1)
Newton's Method
33(3)
Quasi-Newton Methods
36(4)
Problems with Newton Methods
40(2)
Choosing a Solution Method
42(2)
Complementarity Problems
44(3)
Complementarity Methods
47(12)
Exercises
52(5)
Bibliographic Notes
57(2)
Finite-Dimensional Optimization
59(26)
Derivative-Free Methods
60(5)
Newton-Raphson Method
65(1)
Quasi-Newton Methods
66(4)
Line Search Methods
70(2)
Special Cases
72(2)
Constrained Optimization
74(11)
Exercises
78(5)
Bibliographic Notes
83(2)
Numerical Integration and Differentiation
85(30)
Newton-Cotes Methods
85(3)
Gaussian Quadrature
88(2)
Monte Carlo Integration
90(2)
Quasi-Monte Carlo Integration
92(2)
An Integration Tool Kit
94(3)
Numerical Differentiation
97(8)
Initial Value Problems
105(10)
Exercises
110(4)
Bibliographic Notes
114(1)
Function Approximation
115(40)
Interpolation Principles
116(2)
Polynomial Interpolation
118(5)
Piecewise Polynomial Splines
123(6)
Piecewise Linear Basis Functions
129(1)
Multidimensional Interpolation
130(4)
Choosing an Approximation Method
134(1)
An Approximation Tool Kit
135(6)
The Collocation Method
141(5)
Boundary Value Problems
146(9)
Exercises
149(3)
Bibliographic Notes
152(3)
Discrete Time, Discrete State Dynamic Models
155(34)
Discrete Dynamic Programming
155(2)
Economic Examples
157(6)
Mine Management
157(1)
Asset Replacement
158(1)
Asset Replacement with Maintenance
159(1)
Option Pricing
160(1)
Water Management
161(1)
Bioeconomic Model
162(1)
Solution Algorithms
163(4)
Backward Recursion
164(1)
Function Iteration
165(1)
Policy Iteration
165(1)
Curse of Dimensionality
166(1)
Dynamic Simulation Analysis
167(2)
A Discrete Dynamic Programming Tool Kit
169(3)
Numerical Examples
172(17)
Mine Management
172(3)
Asset Replacement
175(1)
Asset Replacement with Maintenance
176(2)
Option Pricing
178(2)
Water Management
180(2)
Bioeconomic Model
182(3)
Exercises
185(3)
Bibliographic Notes
188(1)
Discrete Time, Continuous State Dynamic Models: Theory and Examples
189(34)
Continuous State Dynamic Programming
190(1)
Euler Conditions
191(3)
Continuous State, Discrete Choice Models
194(3)
Asset Replacement
194(1)
Industry Entry and Exit
195(1)
American Option Pricing
196(1)
Continuous State, Continuous Choice Models
197(11)
Economic Growth
197(1)
Renewable Resource Management
198(2)
Nonrenewable Resource Management
200(1)
Water Management
201(1)
Monetary Policy
202(2)
Production-Adjustment Model
204(1)
Production-Inventory Model
205(2)
Livestock Feeding
207(1)
Dynamic Games
208(4)
Capital-Production Game
209(1)
Income Redistribution Game
210(1)
Marketing Board Game
211(1)
Rational Expectations Models
212(11)
Asset Pricing Model
214(1)
Competitive Storage
215(2)
Government Price Controls
217(1)
Exercises
218(3)
Bibliographic Notes
221(2)
Discrete Time, Continuous State Dynamic Models: Methods
223(88)
Linear-Quadratic Control
223(4)
Bellman Equation Collocation Methods
227(3)
Implementation of the Collocation Method
230(7)
A Continuous State Dynamic Programming Tool Kit
237(1)
Postoptimality Analysis
238(2)
Computational Examples: Discrete Choice
240(6)
Asset Replacement
240(3)
Industry Entry and Exit
243(3)
Computational Examples: Continuous Choice
246(27)
Economic Growth
246(4)
Renewable Resource Management
250(3)
Nonrenewable Resource Management
253(3)
Water Management
256(3)
Monetary Policy
259(5)
Production-Adjustment Model
264(2)
Production-Inventory Model
266(5)
Livestock Feeding
271(2)
Dynamic Game Methods
273(18)
Capital-Production Game
279(4)
Income Redistribution Game
283(3)
Marketing Board Game
286(5)
Rational Expectations Methods
291(20)
Asset Pricing Model
295(3)
Competitive Storage
298(4)
Government Price Controls
302(4)
Exercises
306(3)
Bibliographic Notes
309(2)
Continuous Time Models: Theory and Examples
311(60)
Arbitrage-Based Asset Valuation
311(9)
Bond Pricing
314(1)
Black-Scholes Option Pricing Formula
315(1)
Stochastic Volatility Model
316(1)
Exotic Options
317(2)
Multivariate Affine Asset Pricing Model
319(1)
Continuous Action Control
320(8)
Choice of the Discount Rate
324(1)
Euler Equation Methods
325(2)
Bang-Bang Problems
327(1)
Continuous Action Control Examples
328(14)
Nonrenewable Resource Management
328(1)
Neoclassical Growth Model
329(1)
Optimal Renewable Resource Extraction
330(2)
Stochastic Growth
332(1)
Portfolio Choice
333(3)
Production with Adjustment Costs
336(1)
Harvesting a Renewable Resource
337(1)
Sequential Learning
338(4)
Regime Switching Methods
342(5)
Machine Abandonment
343(2)
American Put Option
345(1)
Entry-Exit
345(2)
Impulse Control
347(24)
Asset Replacement
354(1)
Timber Harvesting
355(1)
Storage Management
356(1)
Capacity Choice
356(1)
Cash Management
357(1)
Exercises
358(9)
Appendix 10A: Dynamic Programming and Optimal Control Theory
367(1)
Bibliographic Notes
368(3)
Continuous Time Models: Solution Methods
371(88)
Solving Arbitrage Valuation Problems
372(33)
A Simple Bond Pricing Model
373(2)
More General Assets
375(4)
An Asset Pricing Solver
379(3)
Black-Scholes Option Pricing Formula
382(3)
Stochastic Volatility Model
385(2)
American Options
387(4)
Exotic Options
391(9)
Affine Asset Pricing Models
400(1)
Calibration
401(4)
Solving Stochastic Control Problems
405(7)
A Solver for Stochastic Control Problems
406(3)
Postoptimality Analysis
409(3)
Stochastic Control Examples
412(16)
Optimal Growth
412(3)
Renewable Resource Management
415(2)
Production with Adjustment Costs
417(3)
Optimal Fish Harvest
420(3)
Sequential Learning
423(5)
Regime Switching Models
428(9)
Asset Abandonment
431(1)
Optimal Fish Harvest
432(2)
Entry-Exit
434(3)
Impulse Control
437(22)
Asset Replacement
440(1)
Timber Management
441(2)
Storage Management
443(12)
Cash Management
455(1)
Optimal Fish Harvest
456
Exercises
450(15)
Appendix 11 A: Basis Matrices for Multivariate Models
465
Bibliographic Notes
457(2)
Appendix A: Mathematical Background
459(18)
A.1 Normed Linear Spaces
459(3)
A.2 Matrix Algebra
462(2)
A.3 Real Analysis
464(1)
A.4 Markov Chains
465(2)
A.5 Continuous Time Mathematics
467(10)
A.5.1 Ito Processes
467(3)
A.5.2 Forward and Backward Equations
470(3)
A.5.3 The Feynman-Kac Equation
473(2)
A.5.4 Geometric Brownian Motion
475(1)
Bibliographic Notes
476(1)
Appendix B: A Matlab Primer
477(16)
B.1 The Basics
477(4)
B.2 Conditional Statements and Looping
481(2)
B.3 Scripts and Functions
483(5)
B.4 Debugging
488(2)
B.5 Other Data Types
490(1)
B.6 Programming Style
491(2)
References 493(6)
Index 499

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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.

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