Numerical Methods in EconomicsMIT Press, 28. 9. 1998 - Počet stran: 656 To harness the full power of computer technology, economists need to use a broad range of mathematical techniques. In this book, Kenneth Judd presents techniques from the numerical analysis and applied mathematics literatures and shows how to use them in economic analyses. The book is divided into five parts. Part I provides a general introduction. Part II presents basics from numerical analysis on R^n, including linear equations, iterative methods, optimization, nonlinear equations, approximation methods, numerical integration and differentiation, and Monte Carlo methods. Part III covers methods for dynamic problems, including finite difference methods, projection methods, and numerical dynamic programming. Part IV covers perturbation and asymptotic solution methods. Finally, Part V covers applications to dynamic equilibrium analysis, including solution methods for perfect foresight models and rational expectation models. A website contains supplementary material including programs and answers to exercises. |
Obsah
2 | 26 |
3 | 33 |
6 | 39 |
Optimization | 93 |
Nonlinear Equations | 147 |
Approximation Methods | 195 |
Numerical Integration and Differentiation | 251 |
II | 306 |
Numerical Dynamic Programming | 399 |
Regular Perturbations of Simple Systems | 447 |
Regular Perturbations in Multidimensional Systems | 487 |
Advanced Asymptotic Methods | 511 |
Solution Methods for Perfect Foresight Models | 537 |
Solving Rational Expectations Models | 573 |
| 609 | |
| 623 | |
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agent algorithm analysis applied approach asset assume asymptotic basic capital stock change of variables chapter Chebyshev polynomials choice choose coefficients compute concave condition number constraints construct consumption convergence defined derivatives deterministic differential equation direction dynamic programming economic equilibrium error evaluate example Figure finite fixed-point iteration formula function iteration Gauss-Jacobi Gauss-Seidel Gaussian Gaussian quadrature global go to step gradient Hessian idea implies initial guess integral interpolation Jacobian least squares least squares approximation matrix Monte Carlo methods multidimensional multivariate Newton's method nodes nonlinear equation one-dimensional optimization problems orthogonal polynomial Padé approximation parameters perturbation points policy function procedure produce projection methods pseudorandom quadratic quadrature quasi-Monte Carlo methods random variable sequence simple solution solve spline steady stochastic Suppose Table Taylor series tensor theorem tion utility function value function vector xk+1 zero
Odkazy na tuto knihu
Handbook of Computational Economics, Svazek 2 Hans M. Amman,Leigh Tesfatsion,Kenneth L. Judd,David A. Kendrick,John Rust Náhled není k dispozici. - 2006 |