Matrix Algebra for Applied Economics

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Edition: 1st
Format: Hardcover
Pub. Date: 2001-09-13
Publisher(s): Wiley-Interscience
List Price: $206.87

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Summary

Coverage of matrix algebra for economists and students of economics Matrix Algebra for Applied Economics explains the important tool of matrix algebra for students of economics and practicing economists. It includes examples that demonstrate the foundation operations of matrix algebra and illustrations of using the algebra for a variety of economic problems. The authors present the scope and basic definitions of matrices, their arithmetic and simple operations, and describe special matrices and their properties, including the analog of division. They provide in-depth coverage of necessary theory and deal with concepts and operations for using matrices in real-life situations. They discuss linear dependence and independence, as well as rank, canonical forms, generalized inverses, eigenroots, and vectors. Topics of prime interest to economists are shown to be simplified using matrix algebra in linear equations, regression, linear models, linear programming, and Markov chains. Highlights include: * Numerous examples of real-world applications * Challenging exercises throughout the book * Mathematics understandable to readers of all backgrounds * Extensive up-to-date reference material Matrix Algebra for Applied Economics provides excellent guidance for advanced undergraduate students and also graduate students. Practicing economists who want to sharpen their skills will find this book both practical and easy-to-read, no matter what their applied interests.

Author Biography

SHAYLE R. SEARLE, PhD, is Professor Emeritus of Biometry at Cornell University. He is the author of Linear Models, Linear Models for Unbalanced Data, Matrix Algebra Useful for Statistics, and also (with C. E. McCulloch) Generalized, Linear, and Mixed Models, all from Wiley.

Table of Contents

I. BASICS
Introduction
3(18)
Basic Matrix Operations
21(42)
Special Matrices
63(24)
Determinants
87(30)
Inverse Matrices
117(30)
II. NECESSARY THEORY
Linearly (In)dependent Vectors
147(14)
Rank
161(24)
Canonical Forms
185(18)
Generalized Inverses
203(10)
Solving Linear Equations
213(14)
Eigenroots and Eigenvectors
227(22)
Miscellanea
249(22)
III. WORKING WITH MATRICES
Applying Linear Equations to Economics
271(14)
Regression Analysis
285(38)
Linear Statistical Models
323(28)
Linear Programming
351(22)
Markov Chain Models
373

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