1 / 46

REVIEW OF: LINEAR MODELS AND MATRIX ALGEBRA

Why Matrix Algebra. As more and more commodities are included in models, solution formulas become cumbersome.Matrix algebra enables to do us many things: provides a compact way of writing an equation systemleads to a way of testing the existence of a solution by evaluation of a determinantgives

valerian
Télécharger la présentation

REVIEW OF: LINEAR MODELS AND MATRIX ALGEBRA

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. REVIEW OF: LINEAR MODELS AND MATRIX ALGEBRA From Chapter 4-5 Chiang and Wainwright, Fundamental Methods of Mathematical Economics 4th edition

    2. Why Matrix Algebra As more and more commodities are included in models, solution formulas become cumbersome. Matrix algebra enables to do us many things: provides a compact way of writing an equation system leads to a way of testing the existence of a solution by evaluation of a determinant gives a method of finding solution (if it exists)

    3. Catch Catch: matrix algebra is only applicable to linear equation systems. However, some transformation can be done to obtain a linear relation. y = axb log y = log a + b log x

    4. Matrices and Vectors Example of a system of linear equations: c1P1 + c2P2 = -c0 ?1P1 + ?2P2 = -?0 In general, a11 x1 + a12 x2 ++ a1nXn = d1 a21 x1 + a22 x2 ++ a2nXn = d2 am1 x1 + am2 x2 ++ amnXn = dm coefficients aij variables x1, ,xn constants d1, ,dm

    5. Matrices as Arrays

    6. Example: 6x1 + 3x2+ x3 = 22 x1 + 4x2+-2x3 =12 4x1 - x2 + 5x3 = 10

More Related