Structured additive distributional hurdle Poisson modelling of individual fertility levels in Nigeria

Abstract

Abstract Fertility is one of the dynamic components of population and has been modelled through children ever born per woman, which is a count variable that can be characterized with excessive zeros origination from women without any births. In order to examine the spatial variation across states of Nigeria, we proposed the use of hurdle models that classifies the data into a truncated count and point mass of zeros. We adopt distributional regression model that allows all parameters of the hurdle model to be linked to covariates of different types so as to allow for accessing the spatial variations and nonlinear forms of metrical covariates on the level of fertility and in the likelihood of having no child. Data was sourced from the 2013 Nigeria Demographic and Health Survey. Findings reveal the existence of north-south divide in the average level of fertility and in the likelihood of a woman not giving birth to any child. Women with higher level of education and those from richer or richest households have higher likelihood of having no child, but this is not the case for women with primary or secondary education, users of traditional or modern contraceptive, ever-married women and those working. There is therefore the need to strengthen family planning policies so that investment in contraceptive would yield the expected results in Nigeria.