David Kendrick, P. Mercado, Hans Amman
The ability to conceptualize an economic problem verbally, to formulate it as a mathematical model, and then represent the mathematics in software so that the model can be solved on a computer is a crucial skill for economists. Computational Economics contains well-known models--and some brand-new ones--designed to help students move from verbal to mathematical to computational representations in economic modeling. The authors' focus, however, is not just on solving the models, but also on developing the ability to modify them to reflect one's interest and point of view. The result is a book that enables students to be creative in developing models that are relevant to the economic problems of their times.
Unlike other computational economics textbooks, this book is organized around economic topics, among them macroeconomics, microeconomics, and finance. The authors employ various software systems--including MATLAB, Mathematica, GAMS, the nonlinear programming solver in Excel, and the database systems in Access--to enable students to use the most advantageous system. The book progresses from relatively simple models to more complex ones, and includes appendices on the ins and outs of running each program.
The book is intended for use by advanced undergraduates and professional economists and even, as a first exposure to computational economics, by graduate students.
- Organized by economic topics
- Progresses from simple to more complex models
- Includes instructions on numerous software systems
- Encourages customization and creativity
Table of Contents
PART I: Once Over Lightly ...
Chapter 1: Growth Model in Excel 9
Finance Chapter 2: Neural Nets in Excel 25
Chapter 3: PartIal Equilibrium in Mathematica 37
Chapter 4: Transportation in GAMS 55
Chapter 5: Databases in Access 67
Chapter 6: Thrift in GAMS (with Genevieve Solomon) 91
Chapter 7: Portfolio Model in MATLAB 119
PART II: Once More ...
Chapter 8: General Equilibrium Models in GAMS 149
Chapter 9: Cournot Duopoly in Mathematica (with Daniel Gaynor) 173
Chapter 10: Stackelberg Duopoly in Mathematica (with Daniel Gaynor) 189
Chapter 11: Genetic Algorithms and Evolutionary Games in MATLAB 201
Chapter 12: Genetic Algorithms and Portfolio Models in MATLAB 223
Chapter 13: Macroeconomics in GAMS 247
Agent-Based Computational Economics Chapter 14: Agent-Based Model in MATLAB 267
Chapter 15: Global Warming in GAMS 291
Chapter 16: Dynamic Optimization in MATLAB 309
PART III: Special Topic:tochastic Control
Chapter 17: Stochastic Control in Duali 339
Chapter 18: Rational Expectations Macro in Duali 361
A. Running GAMS 389
B. Running Mathematica 391
C. Running the Solver in Excel 393
D. Ordered Sets in GAMS 394
E. Linearization and State-Space Representation of Hall and Taylor's Model 396
F. Introduction to Nonlinear Optimization Solvers 403
G. Linear Programming Solvers 407
H. The Stacking Method in GAMS 411
I. Running MATLAB 413
J. Obtaining the Steady State of the Growth Model 414