Modelling poverty in Zimbabwe based on the demographic health survey dataset using GLMs and GAMMs.

Abstract

Zimbabwe has been in a state of political, economic, and social crisis for the past 15 years. In 2004, 80% of Zimbabweans were living below the national poverty line. By January 2009, only 6% of the population held jobs in the formal sector. Living in poverty may lead to stressful conditions that are linked to poor mental health problems in adults and developmental issues in children. This study investigates the risk factors that affect poverty status in Zimbabwe and makes recommendations for current policy on poverty, using statistical models such as generalized linear models (GLMs) and generalized additive mixed models (GAMMs). This study makes use of the Zimbabwe 2015 Demographic and Healthy Survey Dataset (DHS). The index was created using 29 variables questions from a principal component analysis. The first component was taken and the factor score was used. There was a cutoff below the median and above the median. Hence, the dichotomous response variable was socioeconomic status (SES) (1=Poor, 2=Not poor).The DHS data has explanatory variables such as the level of education, sex of the household head and age of the household head, size of the household head, and place of residence and sex of the household head. The results in both models (GLMs and GLMMs) reveal that these demographic factors are key determinants of poverty of households in Zimbabwe. This study demonstrates that the government of Zimbabwe needs to pay attention and intervene by looking into the demographic factors that affect poverty status.