Effective coordination between fiscal and monetary policy is crucial for macroeconomic stability, yet achieving it presents significant challenges due to differing objectives and institutional setups. This study evaluates the strategic interaction between fiscal and monetary authorities in Hungary from 2013 to 2023, employing the Nash equilibrium framework under the assumption of non-cooperative behavior. By modeling the authorities as independent players optimizing distinct payoff functions based on key economic indicators (interest rates, government spending, inflation, output gap, fiscal deficit, and public debt), the analysis estimates the best response strategies and computes the resulting Nash equilibrium. The key findings reveal persistent deviations between actual policies and the computed equilibrium strategies. Specifically, actual fiscal policy was consistently more expansionary (average actual deficit −2.6% to 7.6% GDP vs. equilibrium recommendations ranging from 8.5% surplus to −3.0% deficit) than the Nash equilibrium indicated, particularly during periods of economic growth. Monetary policy often lagged in equilibrium recommendations, maintaining low interest rates (e.g., 0.9% actual vs. 11.5% equilibrium in 2019) before implementing sharp increases (13% actual vs. approx. 3.5–3.8% equilibrium in 2022–2023) that significantly overshot the equilibrium. These misalignments underscore potential suboptimal outcomes arising from independent policymaking, contributing to increased public debt and heightened inflationary pressures in the Hungarian context. This study highlights the potential benefits of aligning policies closer to mutually consistent strategies, suggesting that improved coordination frameworks could enhance macroeconomic stability, offering insights relevant to Hungary and similar economies.

The increasing data scales in today’s business sectors coupled with the necessity of risk management raise the importance of business intelligence tools as an integrated solution for the insurance industry. These tools have mostly been used to achieve effective risk management. Although methods of risk management in the insurance industry have been proposed many years ago, the research effort has primarily been focused on predictive analyses. This study aimed to investigate the role of business intelligence as a solution to illustrate its potential in risk management particularly for decision-makers in agricultural insurance. We hypothesized that this would make a preferable decision in uncertain conditions. Sample data from the online transaction process system of Iran agricultural insurance fund were preprocessed in SQL server. Multidimensional online analytical processing architecture was analyzed using Targit business intelligence tool. Our results identified financial risks that lead to a framework of controlling risk based on business intelligence in the agricultural insurance fund.

The interplay between fiscal and monetary policy is critical for small open economies exposed to global volatility, yet the regime-dependent nature of this transmission often remains underexplored. This study investigates whether the Hungarian economy operated under fiscal or monetary dominance from 2010 to 2024, a period marked by significant external shocks. Adopting a Markov Regime-Switching VAR (MS-VAR) framework tailored to an open-economy context, the research estimates state-dependent reaction functions and Impulse Response Functions (IRFs) for both the central bank and the fiscal authority. The model explicitly controls for exogenous geopolitical and economic crises and is validated through rigorous stationarity and regime-selection tests. Empirical results reveal that Hungary predominantly operated under fiscal dominance, with the fiscal authority exhibiting non-Ricardian behavior and no significant response to debt accumulation across the sample. Conversely, the Magyar Nemzeti Bank demonstrated regime-switching behavior: a “Passive” stance accommodating fiscal expansion from 2013 to 2019, followed by a forced shift to an “Active” regime in 2022 characterized by aggressive responses to inflation and high-interest rate volatility. These findings suggest that in small open economies, policy dominance is frequently dictated by external constraints, with the burden of macroeconomic stabilization falling disproportionately on monetary policy during crisis episodes.

Although coordinating fiscal and monetary policy is essential for stabilizing small and globally exposed economies, researchers frequently oversimplify by treating the Visegrad Group (V4) as a uniform entity. This study investigates whether the Czech Republic, Hungary, Poland, and Slovakia are converging toward a unified macroeconomic standard or diverging due to institutional heterogeneity. Employing a hybrid framework combining Markov Regime-Switching Vector Autoregressive (MS-VAR) and single-regime robust OLS models alongside dynamic Impulse Response Functions (IRFs) on quarterly data from 2010 to 2024, the research estimates policy reaction functions to identify active and passive stances across the region. Empirical results suggest considerable regime heterogeneity. The Czech Republic and Poland demonstrate stable, single-regime monetary dominance grounded in strict Ricardian fiscal discipline. Conversely, Hungary exhibits structural fiscal dominance and severe institutional conflict, resulting in forced, high-volatility monetary tightening. Slovakia demonstrates persistent fiscal dominance but avoids macroeconomic destabilization because the market discipline provided by its Eurozone membership is economically negligible. The findings indicate that a country’s institutional setup and approach to monetary integration dictate its resilience to external shocks. This confirms that the V4 nations possess deep, underlying macroeconomic divergence.