Poverty, a global challenge, is particularly acute in developing nations. This study addresses the gap in research on the direct impact of political factors on poverty, moving beyond simple correlations to quantify the frequency with which these factors contribute to poverty's persistence. The study's purpose is to analyze how corruption, democracy, governance, and political globalization affect both income poverty and human health poverty in a selection of developing countries. Understanding these dynamics is crucial for developing effective poverty reduction strategies. The study uses a novel approach by creating both income and human health poverty indices to capture the multifaceted nature of poverty. Advanced econometric techniques are employed to address endogeneity and cross-sectional dependence, strengthening the reliability and generalizability of the findings. The study period (1997-2022) encompasses significant global economic events, including the Asian financial crisis and the global financial crisis, providing valuable context for the analysis. The core hypothesis is that political factors significantly impact both income and human health poverty.

Existing literature shows a complex relationship between political factors and poverty. Some studies reveal correlations between democracy and poverty reduction, while others find no clear relationship. Research on the impact of corruption varies, with some suggesting short-term effects while others identify long-term consequences. The influence of political globalization is also debated, with potential benefits and drawbacks noted. However, a significant gap remains in quantifying the direct impact of these political factors on both income and human health poverty in developing countries. This study aims to address this gap by employing robust econometric techniques and a comprehensive data set.

This study employed panel data from 24 developing countries over a 26-year period (1997-2022). Income Poverty Index (IPI) was constructed using poverty headcount and poverty gap, while the Human Health Poverty Index (HHPI) used infant and child mortality rates. Principal Component Analysis (PCA) was used to create composite indices. The study used data from the World Bank, Freedom House, Transparency International, and the KOF Globalization datasets. To address endogeneity and cross-sectional dependence, the study utilized advanced econometric methods: Two-Stage Least Squares (2SLS), System Generalized Method of Moments (SGMM), and fixed effects with Driscoll-Kraay standard errors. Before estimation, tests for cross-sectional dependence (Pesaran CD test), slope homogeneity (Pesaran and Yamagata test), and stationarity (CIPS test) were conducted. Pedroni's co-integration test was used to investigate long-run associations between variables. The models included lagged dependent variables (IPI and HHPI) to account for dynamic effects.

The study found strong evidence of a positive and statistically significant relationship between corruption and both income and human health poverty across multiple estimation methods (FE, DK, SGMM, and 2SLS). Democracy showed a significant negative association with income poverty but was insignificant for human health poverty. Governance demonstrated a mixed relationship; its positive effect was significant in some estimations but insignificant in others. Political globalization showed a significant negative relationship with both income and human health poverty. In both income and human health poverty models, lagged dependent variables were positive and significant, indicating the persistence of poverty. The AR(2) and Sargan tests confirmed the validity of the instrumental variables used in the SGMM and 2SLS estimations.

The findings support the hypothesis that political factors significantly influence poverty. The strong positive relationship between corruption and poverty underscores the need for robust anti-corruption measures. The negative association between democracy and poverty highlights the importance of democratic institutions in poverty reduction. The mixed results regarding governance suggest that its impact on poverty reduction may depend on other contextual factors or require a certain threshold level of quality before a discernible effect is observed. The negative association between political globalization and poverty supports the idea that international cooperation can be beneficial in reducing poverty. The persistence of poverty as indicated by the significant lagged dependent variable coefficients suggests that long-term strategies are necessary to break the cycle of poverty.

This study provides robust evidence of the influence of political factors on poverty in developing countries. Corruption is detrimental, while democracy and political globalization show beneficial impacts. Governance shows a more nuanced effect. Future research could explore the non-linear effects of governance and regional variations in the relationship between political factors and poverty. The findings offer valuable insights for policymakers to design effective poverty reduction strategies focusing on anti-corruption measures, strengthening democratic institutions, and promoting international cooperation.

The study's limitations include the potential for omitted variable bias despite the use of various econometric techniques. Regional heterogeneity may also influence the results. The choice of specific indicators for political factors may also influence the findings. Future research employing more granular data and alternative methodological approaches could provide further insights into these complex dynamics.