Analyzing the Influence of Gross Domestic Product on the Human Development Index Worldwide in 2021 Using a Nonparametric Regression Approach Based on Penalized Spline Estimator

Authors

  • Dita Amelia Universitas Airlangga
  • Azizah Atsariyyah Zhafira Amelia
  • Bryan Given Christiano Ginzel Universitas Airlangga
  • Fery Yulian Putra Universitas Airlangga
  • Yoga Setya Wibawa Universitas Airlangga

DOI:

https://doi.org/10.12962/j24775401.ijcsam.v11i2.8851

Keywords:

Index Terms - Gross Domestic Product, Human Development Index, Penalized Spline Estimator

Abstract

People’s welfare is a universal goal that is the main focus of all countries in the world. One of the indicators used to measure welfare is the Human Development Index (HDI), which includes education, health and per capita income. On the other hand, Gross Domestic Product (GDP) is the main measure of a region’s economic growth. This research aims to highlight how regional economic dynamics affect human welfare in the world in 2021 and the data source was obtained from OurWorldInData. This research uses nonparametric regression with a penalized spline estimator approach. Penalized Spline analysis shows that the best model for predicting HDI based on GDP per capita is to use 2 knot points, namely k1=8000 and k2=50000. This model produces a Mean Squared Error (MSE) value of 0.0018 and Generalized Cross Validation (GCV) of 0.0019. In addition, this model has the ability to explain response variability of R2=91.58%. The grouping of countries by GDP per capita reveals that economic improvement impacts human development differently across income levels. By tailoring strategies to specific income groups, policymakers can more effectively enhance human development outcomes, fostering a more equitable and prosperous society

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Published

2025-12-15

How to Cite

Amelia, D., Zhafira, A. A., Ginzel, B. G. C., Putra, F. Y., & Wibawa, Y. S. (2025). Analyzing the Influence of Gross Domestic Product on the Human Development Index Worldwide in 2021 Using a Nonparametric Regression Approach Based on Penalized Spline Estimator. (IJCSAM) International Journal of Computing Science and Applied Mathematics, 11(2), 68–75. https://doi.org/10.12962/j24775401.ijcsam.v11i2.8851

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