Spatial Smoothing of Fertility Rate in Rural Areas of Iran (2011-2016)

Abstract

Fertility is one of the basic processes of the population that has an important effect on the dynamics and change of population structure. The declining burden is a global phenomenon; in the past decades, developed countries and today many developing countries are experiencing it, and in Iran, the overall fertility rate has reached less than the replacement level. Estimation of fertility rate in rural areas is mainly affected by population size and space unit size. Therefore, estimating fertility rates and mapping them in small and sparsely populated geographical areas is challenging. This study aims to accurately estimate and identify spatial patterns of fertility in rural areas using spatial smoothing methods for 2016 and 2011. Experimental Bayes and spatial Bayes smoothing methods were used to analyze the data. While the average GFR of 2011 and 2016 are 51.1 and 71.6 (children per 1000 women), respectively, the findings show that spatial smoothing methods, especially the experimental spatial Bayesian method, have good efficiency in estimating fertility in small areas. Adjusting the fertility rate in densely populated areas is less and in sparsely populated areas it makes a significant adjustment. The results also show the occurrence of high rural fertility in less developed border areas (southeast, east and south) and the spread of low rural fertility from north to south and then the central and western villages. The persistence of low fertility in most of the rural areas is causing serious challenges in the economic, social and political spheres.

Keywords

• fertility rate
• spatial smoothing
• spatial empirical bayes
• spatial autocorrelation
• rural areas