Multi-equational linear quadratic adjustment cost models with rational expectations and cointegration

In this paper the econometric analysis of linear quadratic adjustment cost models with rational expectations and cointegrated variables is extended to a multi-equational set-up and the case of second-order adjustment costs. The proposed method is based on the idea of nesting the system of interrelated Euler equations stemming from the intertemporal optimization problem within a cointegrated Vector Equilibrium Correction Model representing the agent forecast tool. Contrary to previous practise a likelihood-based procedure can be set out without appealing to numerical optimization algorithms. Cointegration and generalized least squares techniques can be used to estimate and test the model.