Proceedings of the 33rd International Academic Conference, Vienna

DYNAMIC OPTIMIZATION UNDER UNCERTAINTY: A CASE STUDY FOR AUSTRIAN MACROECONOMIC POLICIES.

REINHARD NECK, SOHBET KARBUZ

Abstract:

Results from optimum control problems with uncertain parameters are investigated in a numerical case study for Austria. Optimal budgetary policies are calculated under varying assumptions about stochastic parameters within the framework of a problem of quantitative economic policy. An intertemporal objective function is minimized subject to the constraints of a small macroeconometric model, and approximately optimal values for federal budget expenditures and revenues are determined. It is shown that the deterministic and the fully stochastic optimal policies are rather similar. If only some parameters are assumed to be stochastic, or if covariances between different parameters are not taken into account, on the other hand, optimization results can be very different from deterministic or fully stochastic optimization results.

Keywords: optimal control; fiscal policy; stochastic control; stochastic parameters; econometric models

DOI: 10.20472/IAC.2017.33.049

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