This paper presents a set of rules for matrix differentiation with respect to a vector of parameters, using the flattered representation of derivatives, i.e. in form of a matrix. We also introduce a new set of Kronecker tensor products of matrices. Finally we consider a problem of...

We describe algorithm to find higher order approximations of stochastic rational expectations models near the deterministic steady state. Using matrix representation of function derivatives instead of tensor representation we obtain simple expressions of matrix equations determining higher order...

This paper presents a set of rules for matrix differentiation with respect to a vector of parameters, using the flattered representation of derivatives, i.e. in form of a matrix. We also introduce a new set of Kronecker tensor products of matrices. Finally we consider a problem of...