The objective of this study is to examine the impact of government support policies—particularly insurance and subsidies—on reducing the poverty gap among households. To achieve this objective, two analytical approaches are employed: an Ordinary Least Squares (OLS) model and behavioral simulation within a dynamic systems framework. The data include quarterly observations from 2010 to 2024, as well as hypothetical data used for scenario modeling. The key variables consist of household income, assets, expenditures, losses, and access to government-provided insurance and subsidies. In the model, households are exposed to varying levels of initial income and assets, along with a range of routine expenses and financial shocks, such as damages resulting from accidents or illnesses. Simulation results indicate that the combined use of insurance and targeted subsidies plays a significant role in preventing asset depletion and income loss, thereby contributing to a reduction in the poverty gap. According to the findings, these policies lead to a 7% increase in household income, a 3% rise in investment, and a 5% reduction in expenditures. These outcomes underscore the importance of designing and implementing social protection policies grounded in insurance mechanisms to address structural poverty.
Purpose/Aims:
The primary aim of this research is to investigate the impact of government support policies, particularly insurance schemes and targeted subsidies, on reducing household poverty gaps. Poverty, as a multifaceted socioeconomic phenomenon, extends far beyond income insufficiency; it encompasses disparities in access to health care, education, employment opportunities, and social protection mechanisms. In many developing economies, a substantial proportion of households remain economically vulnerable, such that adverse shocks—including natural disasters, illness, unemployment, or market volatility—can readily push them below the poverty line. This study builds upon the existing literature by addressing the structural and dynamic nature of poverty, conceptualizing it not as an inherent societal condition but as a consequence of systemic inequalities shaped by institutions, cultural practices, and economic structures. Although numerous policies have been implemented globally to mitigate poverty, the combined effect of insurance coverage and targeted subsidies on poverty dynamics—particularly their role as economic shock absorbers—remains insufficiently explored in a comprehensive and quantitative manner. Previous studies have often relied on static, cross-sectional analyses, thereby failing to capture the interactive, behavioral, and long-term impacts of such policies. This research seeks to bridge that gap by employing both econometric analysis and dynamic behavioral simulation to assess how the simultaneous implementation of insurance and subsidies can mitigate income losses, prevent capital erosion, and ultimately reduce poverty disparities.
Methodology & Framework:
The study adopts a dual methodological framework comprising an OLS  regression model and dynamic behavioral simulation using system dynamics. Data were drawn from quarterly datasets provided by the Central Bank of Iran, the World Bank, and the Iranian Parliament, covering the period 2010–2024. Additional hypothetical data were incorporated for scenario modeling extending to 2051 (1430). The core variables include household income (Y), initial capital (K), essential expenditures (S), financial shocks such as damages, illnesses, or natural disasters (H), insurance compensation (B), and direct subsidies received (G). The dependent variable is the household poverty gap (PG). The OLS regression was employed to estimate the relationship between these variables and the poverty gap, expressed as:
This econometric estimation provided baseline elasticities and the statistical significance of the explanatory variables. Subsequently, the estimated coefficients informed the system dynamics simulation developed using Vensim software. The simulation modeled household-level behavior over time under varying scenarios of insurance and subsidy provision, incorporating random shocks and heterogeneous income–capital distributions. This dynamic approach enabled the analysis to capture both short-term buffering effects and long-term structural implications of policy interventions.
Findings:
The OLS results revealed that household income and initial capital, although positively associated with wealth accumulation, also exhibited a statistically significant association with widening poverty gaps, suggesting that unequal distributions of these resources contribute to inequality. Conversely, essential expenditures and unexpected financial shocks exerted a positive and significant effect on the poverty gap, underscoring their role in intensifying financial distress among vulnerable households. Importantly, both targeted subsidies and insurance coverage demonstrated a negative and statistically significant relationship with the poverty gap, confirming their mitigating effects. The system dynamics simulation further illustrated that a combined policy approach—in which households simultaneously benefit from insurance compensation and targeted subsidies—produces a synergistic effect. Specifically, the results indicated a 7% increase in household income, a 3% increase in investment, and a 5% reduction in household expenditures under optimal policy conditions. The protective effects were most pronounced among lower-income households with limited initial capital, suggesting that well-targeted interventions yield disproportionately larger welfare gains for the most vulnerable segments of society. Moreover, the interaction between insurance and subsidies functioned as a complementary mechanism, reducing the severity of financial shocks and enhancing household resilience. In the absence of these protective measures, simulated scenarios projected a deeper and more persistent poverty gap over the modeled period.
Discussion & Conclusion: 
The findings provide strong empirical support for the implementation of integrated social protection strategies in developing economies. The dual role of insurance and subsidies—as instruments of risk mitigation and as drivers of household financial stability—underscores their relevance within contemporary poverty reduction frameworks. Unlike one-time cash transfers, these mechanisms offer a structural buffer against income volatility and asset depletion, thereby preventing transient shocks from evolving into chronic poverty. From a policy perspective, this research advocates for refining subsidy allocation to ensure that it remains targeted and responsive to household vulnerability levels. Similarly, expanding insurance coverage, particularly in health-related and employment-linked sectors, can foster a more resilient socioeconomic environment. The results are consistent with prior studies but extend existing insights by incorporating dynamic simulations that capture feedback effects and long-term outcomes. Notably, the analysis indicates that the marginal benefits of these policies diminish for higher-income groups, highlighting the importance of progressive targeting and adaptive policy design. Furthermore, the study emphasizes the relevance of behavioral responses in policy evaluation. Households receiving predictable insurance and subsidy support are more likely to sustain investment activities and less likely to resort to adverse coping strategies, such as asset liquidation or high-interest borrowing. These dynamics carry important long-term implications for poverty eradication efforts, suggesting that strategic, complementary, and behaviorally informed interventions can disrupt persistent poverty cycles. In conclusion, the research demonstrates that a well-coordinated combination of insurance schemes and targeted subsidies is effective in reducing poverty gaps, improving household income and investment, and mitigating the adverse effects of financial shocks. Policymakers are encouraged to adopt dynamic modeling approaches when designing future interventions, as static analyses may underestimate the cumulative benefits of sustained and synergistic social protection measures. This study contributes to the growing body of literature on structural poverty alleviation by offering both empirical evidence and a dynamic analytical framework applicable to other developing contexts.