Siswadi, Siswadi
Universitas Singaperbangsa Kerawang

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Influence of World Development Indicators on Human Development: A Multiple Linear Regression and PSI Ranking Approach Irvan, Irvan; Zahedi, Zahedi; Nusantara, Badai Charamsar; Romantica, Krishna Prafidya; Siswadi, Siswadi; Nasution, Marah Doly
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24087

Abstract

This study investigates the influence of World Development Indicators (WDI) on the Human Development Index (HDI) within the regional context of Asian countries. Understanding the interaction between these indicators and HDI holds strategic relevance for enhancing the formulation of evidence-based development policies. The analysis focuses on five key indicators: population growth, voice and accountability, government effectiveness, GDP per capita growth, and control of corruption. These variables represent essential dimensions of governance and socioeconomic advancement. The dataset comprises information from 46 Asian countries sourced from the World Bank. The methodological framework integrates multiple linear regression to evaluate the magnitude of each variable’s contribution to HDI. The Preference Selection Index (PSI) is utilized to establish a performance-based ranking of countries grounded in the selected indicators. Results demonstrate that population growth and government effectiveness have significant impacts on HDI outcomes, while the remaining variables exhibit no statistically significant effects. Comparative analysis using PSI reveals inconsistencies between development indicator values and actual HDI positions. South Korea shows the highest consistency between quantitative rankings and HDI classification. These findings offer practical insights for policy prioritization by identifying the most influential determinants of human development in the region. The study emphasizes the importance of tailored development strategies and encourages future research to strengthen model robustness through control variable inclusion, sensitivity analysis, and non-linear modeling approaches.
Influence of World Development Indicators on Human Development: A Multiple Linear Regression and PSI Ranking Approach Irvan, Irvan; Zahedi, Zahedi; Nusantara, Badai Charamsar; Romantica, Krishna Prafidya; Siswadi, Siswadi; Nasution, Marah Doly
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.23925

Abstract

This study investigates the influence of World Development Indicators (WDI)on the Human Development Index (HDI) within the regional context of Asiancountries. Understanding the interaction between these indicators and HDIholds strategic relevance for enhancing the formulation of evidence-baseddevelopment policies. The analysis focuses on five key indicators: populationgrowth, voice and accountability, government effectiveness, GDP per capitagrowth, and control of corruption. These variables represent essentialdimensions of governance and socioeconomic advancement. The datasetcomprises information from 46 Asian countries sourced from the World Bank.The methodological framework integrates multiple linear regression to evaluatethe magnitude of each variable’s contribution to HDI. The Preference SelectionIndex (PSI) is utilized to establish a performance-based ranking of countriesgrounded in the selected indicators. Results demonstrate that population growthand government effectiveness have significant impacts on HDI outcomes, whilethe remaining variables exhibit no statistically significant effects. Comparativeanalysis using PSI reveals inconsistencies between development indicator valuesand actual HDI positions. South Korea shows the highest consistency betweenquantitative rankings and HDI classification. These findings offer practicalinsights for policy prioritization by identifying the most influential determinantsof human development in the region. The study emphasizes the importance oftailored development strategies and encourages future research to strengthenmodel robustness through control variable inclusion, sensitivity analysis, andnon-linear modeling approaches.