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In econometrics, the equations of a structural form model are estimated in their theoretically given form, while an alternative approach to estimation is to first solve the theoretical equations for the endogenous variables to obtain reduced form equations, and then to estimate the reduced form equations.
In linear algebra, reduction refers to applying simple rules to a series of equations or matrices to change them into a simpler form. In the case of matrices, the process involves manipulating either the rows or the columns of the matrix and so is usually referred to as row-reduction or column-reduction, respectively.
A system of linear equations is said to be in row echelon form if its augmented matrix is in row echelon form. Similarly, a system of linear equations is said to be in reduced row echelon form or in canonical form if its augmented matrix is in reduced row echelon form. The canonical form may be viewed as an explicit solution of the linear system.
Now through application of elementary row operations, find the reduced echelon form of this n × 2n matrix. The matrix A is invertible if and only if the left block can be reduced to the identity matrix I; in this case the right block of the final matrix is A −1. If the algorithm is unable to reduce the left block to I, then A is not invertible.
When the Cowles Commission introduced the term "reduced form" it was used to define a set of equations where the "left-hand" dependent variables never appeared on the right-hand of the equations, as opposed to the simultaneous equations, where the dependent variable of an equation can appear as an input in other formulas.
In algebra, a cubic equation in one variable is an equation of the form + + + = ... all cubic equations can be reduced to this form if one allows m and n to be ...
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