Policy makers constantly face optimal control problems: what controls allow to achieve certain targets in, e.g., GDP growth or inflation? Conventionally this is done by applying certain linear-quadratic optimization algorithms to dynamic econometric models. Several algorithms extend this...

The linear-quadratic (LQ) optimization is a close to standard technique in the optimal control framework. LQ is very well researched and there are many extensions for more sophisticated scenarios like nonlinear models. Usually, the quadratic objective function is taken as a prerequisite for...

Optimal control of dynamic econometric models has a wide variety of applications including economic policy relevant issues. There are several algorithms extending the basic case of a linear-quadratic optimization and taking nonlinearity and stochastics into account, but being still limited in a...

Optimal control of dynamic econometric models has a wide variety of applications including economic policy relevant issues. There are several algorithms extending the basic case of a linear-quadratic optimization and taking nonlinearity and stochastics into account, but being still limited in a...

This article presents an introduction to the main existing analytical results relating to problems of uncertainty and economic policy. It addresses specifically the question of “caution” versus “intensity” in the use of instruments of economic policy under uncertainty in dynamic...

By following the spirit in Favero and Milani (2005), we use recursive thick modeling to take into account model uncertainty for the choice of optimal monetary policy. We consider an open economy model and generate multiple models for only the aggregate demand and aggregate supply. Models are...

The choice of monetary policy is the most important concern of central banks. However, this choice is always confronted, inter alia, with two relevant aspects of economic policy: parameter instability and model uncertainty. This paper deals with both types of uncertainty using a very specific...

In this paper an analytical framework using robust control was developed for the one-state and one-control variable model to examine the response of the control to changes in the "free" parameter. However, in contrast to Gonzalez and Rodriguez (2003), the sign of the ``free" parameter in the...

By applying robust control the decision maker wants to make good decisions when his model is only a good approximation of the true one. Such decisions are said to be robust to model misspecification. In this paper it is shown that both a “probabilistically sophisticated” and a...

In this note a one-state, one-control variable quadratic linear problem with robust control and discount factor is developed to examine the optimal response of the first-period control to changes in future model uncertainty. A change in future model uncertainty has an effect on the optimal...