A computationally robust solution method for linear rational expectations models is displayed, based on the QZ matrix decomposition. Any rational expectations model, in continuous or discrete time, can be solved by this approach. It requires that the model be cast into first-order form, but it does not require that it be reduced so that the number of states matches the number of equations. It also avoids the artificial requirement that variables be designated as jump variables or not. (Instead, how expectational error terms enter the system must be specified - a more general specification.) -A computationally robust solution method for linear rational expectations models is displayed, based on the QZ matrix decomposition. Any rational expectations model, in continuous or discrete time, can be solved by this approach. It requires that the model be cast into first-order form, but it does not require that it be reduced so that the number of states matches the number of equations. It also avoids the artificial requirement that variables be designated as　jump　variables or not. (Instead, how expectational error terms enter the system must be specified - a more general specification.)