= 2. Let z be a column vector of K exogenous variables; in the case above z consisted only of Z. The structural linear model is where is a vector of structural shocks, and A and B are matrices; A is a square M × M matrix, while B is M × K. The reduced form of the system is: with vector of reduced form errors that each depends on all structural errors, where the matrix A must be nonsingular for the reduced form to exist and be unique. Again, each endogenous variable depends on potentially each exogenous variable. Without restrictions on the A and B, the coefficients of A and B cannot be identified from data on y and z: each row of the structural model is just a linear relation between y and z with unknown coefficients. (This is again the parameter identification problem.) The M reduced form equations (the rows of the matrix equation y = Π z above) can be identified from the data because each of them contains only one endogenous variable. See also Simultaneous equations model#Structural and reduced form System of linear equations Simultaneous equations "Reduced form" is also an approach to credit spread-modelling; see under Jarrow–Turnbull model. Further reading External links Econometric modeling