From vision to outcomes: How government leadership and foresight shape national development through institutional channels

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Type of the article: Research Article

Abstract
The widening development gap between well-governed and poorly governed nations – highlighted by the reversal since 2020 of two decades of human development convergence – underscores the need to understand which specific governance capabilities drive development and how. This study aims to estimate the effect of government leadership and foresight on national development and to identify the institutional channels through which this effect is transmitted. Drawing on the Chandler Good Government Index merged with World Bank and UNDP indicators, the analysis employs pooled OLS with year fixed effects, mediation analysis with bootstrap inference, and a comprehensive set of robustness tests on an unbalanced panel of 120 countries over 2021–2025. Leadership and foresight are positively and significantly associated with GDP per capita, life expectancy, and the Human Development Index (β = 4.049, p < 0.01 for ln GDP per capita; a one-standard-deviation increase corresponds to a 79% increase in GDP). The mediation analysis – the study’s central contribution – reveals that 152.1% of the total effect is transmitted indirectly through other governance capabilities, principally robust laws (157.4%), strong institutions (137.6%), and attractive marketplace (133.4%), while the direct residual effect is negative (β = −2.110, p < 0.01), indicating a “vision–capacity gap.” The effect is significant only in high-income economies (β = 1.506, p < 0.01) and absent in lower-income contexts. These findings demonstrate that leadership functions as a meta-governance capability whose developmental impact is channeled through, rather than independent of, the broader institutional architecture.

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    • Figure 1. Leadership and foresight and economic development across countries
    • Figure 2. Mediation path diagram: L&F → Other governance capabilities → Development
    • Figure 3. Heterogeneity of the L&F-development relationship across income groups
    • Table 1. Variable definitions, sources, and expected signs
    • Table 2. Descriptive statistics
    • Table 3. Main estimation results: Leadership and foresight and development outcomes
    • Table 4. Mediation analysis: Transmission channels from L&F to development
    • Table 5. Complementarity: Interaction between L&F and other governance capabilities
    • Table 6. Pillar-level decomposition: Individual predictive power of CGGI dimensions
    • Table 7. Sub-sample analysis by income group
    • Table 8. Robustness checks
    • Table A1. Countries in the sample by World Bank 2024 income classification
    • Table B1. Pearson correlation matrix
    • Table C1. Pooled OLS vs. Country fixed effects
    • Table D1. Country-level scores, outcomes, and model residuals
    • Conceptualization
      Sevinj Abbasova, Zuzana Kubaščikova, Mehriban Aliyeva
    • Funding acquisition
      Sevinj Abbasova, Mehriban Aliyeva
    • Methodology
      Sevinj Abbasova, Zuzana Kubaščikova, Mehriban Aliyeva, Elnara Samedova
    • Resources
      Sevinj Abbasova, Elnara Samedova
    • Supervision
      Sevinj Abbasova, Zuzana Kubaščikova, Elnara Samedova
    • Validation
      Sevinj Abbasova, Mehriban Aliyeva, Leyla Huseynova
    • Writing – original draft
      Sevinj Abbasova, Zuzana Kubaščikova, Mehriban Aliyeva, Elnara Samedova, Leyla Huseynova
    • Writing – review & editing
      Sevinj Abbasova, Zuzana Kubaščikova, Mehriban Aliyeva, Elnara Samedova, Leyla Huseynova
    • Formal Analysis
      Zuzana Kubaščikova, Mehriban Aliyeva
    • Visualization
      Zuzana Kubaščikova, Elnara Samedova
    • Software
      Mehriban Aliyeva, Leyla Huseynova
    • Data curation
      Elnara Samedova, Leyla Huseynova
    • Investigation
      Elnara Samedova, Leyla Huseynova
    • Project administration
      Leyla Huseynova