Optimal fiscal policy in times of uncertainty: a stochastic control approach
Reinhard Neck (),
Dmitri Blueschke and
Viktoria Blueschke-Nikolaeva
Additional contact information
Dmitri Blueschke: Alpen-Adria-Universität Klagenfurt
Viktoria Blueschke-Nikolaeva: Alpen-Adria-Universität Klagenfurt
Empirica, 2025, vol. 52, issue 1, No 5, 99-120
Abstract:
Abstract This paper deals with the possibilities of designing optimal fiscal policy under uncertainty. First, different forms of uncertainty are discussed for economic policy analysis and design. For dynamic models under uncertainty, a stochastic optimum control framework is presented. Algorithms for nonlinear models are briefly reviewed: OPTCON1 for open-loop control, OPTCON2 for open-loop feedback (passive learning) control, and OPTCON3 for dual control with active learning. The OPTCON algorithms determine approximately optimal fiscal policies. The results from calculating these policies for a small macroeconometric model for Slovenia serve to illustrate the applicability of the OPTCON algorithms and compare their solutions. The results show that the most sophisticated and time intensive active-learning solution, which requires the use of an extremely small and simple model of the economy, is not necessarily superior to the simpler solutions. For actual policy design problems and policy advice, it will often be better to neglect the stochastic uncertainty and use deterministic optimization instead, especially since in practice, the most important forms of uncertainty are not stochastic but relate to the model specification, the behaviour of other policy makers or other agents, or fundamental uncertainty that cannot be dealt with at all.
Keywords: Stochastic control; Optimization; Algorithms; Fiscal policy; Slovenia (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10663-024-09626-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:kap:empiri:v:52:y:2025:i:1:d:10.1007_s10663-024-09626-y
Ordering information: This journal article can be ordered from
http://www.springer. ... ration/journal/10663
DOI: 10.1007/s10663-024-09626-y
Access Statistics for this article
Empirica is currently edited by Fritz Breuss and Fritz Breuss
More articles in Empirica from Springer, Austrian Institute for Economic Research, Austrian Economic Association Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().