Exploring the impact of agriculture and physical geography on poverty in the East Coast of Malaysia: A spatial analysis

Poverty is one of the most significant issues facing humanity in the 21st century. In Malaysia, awareness of poverty was more heavily weighted toward developing a prosperous lifestyle. Hence, the objectives of this study were to explore the spatial pattern of poverty and the effects of agricultural growth and physical geography on poverty in East Coast, Malaysia. Secondary data on the heads of poor households from 2020 were obtained from the e-Kasih database. The dependent variable was the number of poor household heads in each district, which count variable and acts as an indicator for measuring poverty. Therefore, a Generalised Linear Model (GLM) was used. Since a spatial autocorrelation was detected in the model using Moran’s I statistic, a Poisson Log Linear Leroux Conditional Autoregressive was fitted to the data. RStudio software was used to analyze the data. The results of this study indicate that the variables of the number of people without education, number of female heads of households, number of government servants, total land area for cash crops, and slope significantly influence the number of poor household heads in each district. The estimated poverty risk in each district was measured. ArcMap software created the poverty distribution map in Kelantan, Pahang, and Terengganu. The estimated poverty risk map shows a nearly similar spatial pattern to the Standardised Poverty Rate (SPR) map. This research adds new literature on poverty models in Kelantan, Pahang, and Terengganu for other researchers studying poverty factors in these regions.