Stimation of time varying parameters in an optimal control problem

Abstract

In this paper, we employ a non-linear state space model and the extended Kalman filter to simultaneously estimate the time-varying parameters in an optimal control problem, where the objective (loss) function is quadratic. Our methodology also allows us to derive the difference between the optimal control and the observed control variable. A simulation exercise based on a simple intertemporal model shows that the estimated parameter values are very close to their population values, which provide further support for the estimation methodology introduced in this paper