Spatial analysis on distribution patterns of poverty incidences in Peninsular Malaysia

Abstract

Poverty problem faced by most of the countries worldwide. Poverty is not having access to monies, food, healthcare, education and other factors of a person or a household which usually measure by level of household income. Despite the fact that various actions have been taken to handle the poverty problem, most countries still having challenges this problem. The objective of this study is to analyze the spatial cluster patterns of poverty in Peninsular Malaysia by using the exploratory spatial data analysis (ESDA). Spatial autocorrelation (cluster), Global Moran's I and Local Moran's Ii index were used to analyse. The hypothesis of spatial randomness was rejected indicating cluster effect existed in the study area. The hot spot and cold spot areas were identified. The findings reveal that poverty was distributed nonrandomly, suggestive of positive spatial autocorrelation.