Estimating intertemporal quadratic adjustment cost models with integrated processes: a VAR approach

Abstract

This paper extends the existing literature on linear quadratic adjustment cost (LQAC) models under rational expectations to the inferential issue arising when: (I) agents optimize with respect to a vector of endogenous variables; (II) the behavioral equation stemming from the agent's optimization problem are specified as 'exact' rational expectations models; (III) the stochastic processes involved are integrated of order one. We focus on estimation in e 'full-information' framework, and the key assumption is that agents compute expectations through a cointegrated VAR (CVAR) for the observable variables.