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Comprehensive Review of Quantitative Frameworks for Optimizing Fiscal Policy Response to global shocks
Subject area: Science,Engineering and Technology · Area of research: Quantitative Frameworks for Fiscal Policy
Abstract
The increasing frequency and intensity of global economic shocks have underscored the importance of resilient fiscal policy frameworks. From financial crises to trade disruptions and pandemics, governments require adaptive tools to mitigate volatility and ensure macroeconomic stability. This paper presents a comprehensive review of quantitative frameworks for optimizing fiscal policy response to global shocks. It synthesizes theoretical foundations, empirical approaches, and policy applications while critically analyzing the effectiveness and limitations of different methodologies. By categorizing frameworks into econometric, simulation-based, and hybrid models, the study highlights their strengths and constraints in addressing issues of fiscal sustainability, countercyclical stabilization, and international spillovers. The methodology applies a structured literature review and comparative framework analysis, emphasizing the role of predictive modeling, scenario analysis, and dynamic policy simulation. Results demonstrate that hybrid models incorporating machine learning and traditional econometric structures offer superior adaptability under uncertainty. The discussion section explores policy trade-offs, model transparency, and political feasibility, arguing for multi-framework integration as a way forward. The paper concludes that future fiscal policy optimization requires a dynamic blend of quantitative rigor, computational innovation, and institutional adaptability.
Keywords
Fiscal Policy, Quantitative Frameworks, Global Shocks, Econometrics, Simulation Models, Optimization)
How to cite this paper
@article{1711040,
author = {Melvin J. Oshomegie, Omodolapo Eunice Ogunsola, Blessing Olajumoke Farounbi},
title = {Comprehensive Review of Quantitative Frameworks for Optimizing Fiscal Policy Response to global shocks},
journal = {Iconic Research And Engineering Journals},
year = {2019},
volume = {2},
number = {8},
pages = {311-320},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1711040.pdf},
abstract = {The increasing frequency and intensity of global economic shocks have underscored the importance of resilient fiscal policy frameworks. From financial crises to trade disruptions and pandemics, governments require adaptive tools to mitigate volatility and ensure macroeconomic stability. This paper presents a comprehensive review of quantitative frameworks for optimizing fiscal policy response to global shocks. It synthesizes theoretical foundations, empirical approaches, and policy applications while critically analyzing the effectiveness and limitations of different methodologies. By categorizing frameworks into econometric, simulation-based, and hybrid models, the study highlights their strengths and constraints in addressing issues of fiscal sustainability, countercyclical stabilization, and international spillovers. The methodology applies a structured literature review and comparative framework analysis, emphasizing the role of predictive modeling, scenario analysis, and dynamic policy simulation. Results demonstrate that hybrid models incorporating machine learning and traditional econometric structures offer superior adaptability under uncertainty. The discussion section explores policy trade-offs, model transparency, and political feasibility, arguing for multi-framework integration as a way forward. The paper concludes that future fiscal policy optimization requires a dynamic blend of quantitative rigor, computational innovation, and institutional adaptability.},
keywords = {Fiscal Policy, Quantitative Frameworks, Global Shocks, Econometrics, Simulation Models, Optimization)},
month = {February},
}