A Nonparametric Regression Approach Address Poverty Problems in East Nusa Tenggara Province

Abstract

The administration is focused on reducing poverty, which is still a significant issue. Since the regression curve is unknown and the truncated spline nonparametric regression approach offers a high degree of flexibility, the study was conducted to determine what factors influence it, particularly in the East Nusa Tenggara area. The goal of this study is to develop a nonparametric regression model. The average length of schooling, life expectancy, percentage of the illiterate population aged 15 and over, labor force participation rate, percentage of households based on the information source, and population density affect poverty in the East Nusa Tenggara area. With a minimum GCV of 39.57, it was determined that 1 knot point were the ideal knot point. To some extent, the characteristics that influenced poverty were life expectancy, labor force participation rate, percentage of households with a proper light source, and population density. The best model met these criteria with an R2 of 81.28%. The findings suggest that targeted interventions to improve these factors can significantly reduce poverty in East Nusa Tenggara