Teaching Computational Economics in an Applied Economics Program
Computational Economics
A MATLAB Solver for Nonlinear Rational Expectations Models
Computational Economics
Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks
Computational Economics
Computational Economics: Help for the Underestimated Undergraduate
Computational Economics
Multidimensional Spline Interpolation: Theory and Applications
Computational Economics
Teaching Computational Economics to Graduate Students
Computational Economics
Using Chebyshev Polynomials to Approximate Partial Differential Equations
Computational Economics
Robust mixture clustering using Pearson type VII distribution
Pattern Recognition Letters
Comparing Numerical Methods for Solving the Competitive Storage Model
Computational Economics
Hi-index | 0.00 |
From the Publisher: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.