Stochastic Control of Econometric Models for Slovenia

Reinhard Neck, Dmitri Blueschke and Viktoria Blüschke-Nikolaeva^*

This paper considers the optimal control of small econometric models applying the OPTCON algorithm. OPTCON is an algorithm for the optimal control of nonlinear stochastic systems which is particularly applicable to econometric models. It delivers approximate numerical solutions to optimum control problems with a quadratic objective function for nonlinear econometric models with additive and multiplicative (parameter) uncertainties. The algorithm was programmed in C\# and MATLAB and allows for deterministic and stochastic control, the latter with open-loop and passive learning (open-loop feedback) information patterns. The applicability of the algorithm is demonstrated by experiments with two small quarterly macroeconometric models for Slovenia, the nonlinear model SLOVNL and the linear model SLOVL. The results for both models are similar, with open-loop feedback controls giving better results on average and less outliers than open-loop controls. The number of outliers is higher in the nonlinear case and especially under high parameter uncertainty. This illustrates the convergence and the practical usefulness of the algorithm and (in most cases) the superiority of open-loop feedback over open-loop controls.

Mathematics Subject Classification: 93E20 93C55, 90B99, 91B70, 65P99

Keywords: Optimal control, Stochastic control, Algorithms, Econometric modeling, Policy applications

Minisymposion: Computational Optimization Methods in Statistics, Econometrics and Finance