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Numerical Methods in Economics

by Kenneth L. Judd

List Price:$80.00
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Editorial Reviews
Product Description
Honorable Mention in the category of Economics in the 1998 Professional/Scholarly Publishing Annual Awards Competition presented by the Association of American Publishers, Inc.

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 web site contains supplementary material including programs and answers to exercises.


All Customer Reviews
Average Customer Review:4.5 out of 5 stars
0 of 0 people found the following review helpful:

5 out of 5 starsGreat exercises, very easy to follow, 2007-10-25
This is a great introduction to computational economics. The exercises are well-organized and very useful. His exposition is straightforward. Judd has clearly thought deeply about how computation contributes to economics as well as its limitations.


0 of 5 people found the following review helpful:

5 out of 5 starsGreat job!, 2007-05-18
The book was in a great condition, and it arrived just as promised.


7 of 7 people found the following review helpful:

5 out of 5 starsAn excellent and useful text, 2006-09-09
This is the type of book I've been looking for for a long time: It tells you directly what problems are solved by numerical approximation, what methods have been developed for such applications, how to use them, what to watch out for and most importantly, what "tricks" are available to make things easier - this is something you will never pick up in an academic paper and in very few courses.

The structure is very illuminating: simple examples of common problems are followed by generalized versions which are usefull for anyone to apply to their own work. Care is taken to point out the strenghts and weaknesses of various procedures so that the best one can be selected.

As to the critisisms that it does not go deep enough: its not supposed to. It covers in enough detail most (all) of the important methods used by the top economic researchers today, and if the problem you are working on requires more detail than is in the text, precise and extensive references are provided to further understand that particular area.

a very practical and forthright book.


3 of 6 people found the following review helpful:

3 out of 5 starstoo hard for uninitiated, 2006-07-28
this book may be good for those who already know smth about numerical methods.


46 of 49 people found the following review helpful:

5 out of 5 starsAn essential resource for all applied economists., 1999-05-03
Judd ties together a vast amount of material--from the most basic to the most advanced--that is essential to anyone doing computational work in economics, econometrics or finance. The book is sufficiently self-contained to serve as the single reference book on computational methods for the average economist. In addition, Judd highlights the origins of most methods and points to strengths, weaknesses, and future theoretical research directions. Economic/finance examples are used throughout the book to make the concepts easy to understand and apply. The only thing keeping this book from being perfect is a complete set of software tools, but given the breadth of the book, this might be too much to ask.




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