Explaining the Fertility Differences of Iranian Provinces using Shannon Entropy Method

Despite the government's policies and efforts to boost fertility rates in Iran, the total fertility rate has been declining over the past two decades. This research aims to identify the weight of determinants of fertility in Iran's provinces and provide relevant policy recommendations. The study utilizes the mathematical methods of Shannon entropy and K-means clustering. The findings reveal that per capita gross product holds the highest weight coefficient among fertility determinants across the provinces. Furthermore, the influence of economic, social, and demographic indicators on fertility varies among provinces. Provinces with higher coefficients in social and demographic indicators tend to exhibit higher fertility rates. Notably, provinces such as Sistan and Baluchistan, North Khorasan, and South Khorasan, despite low economic indicators, maintain fertility levels above replacement level. In conclusion, this research emphasizes the significance of understanding localized determinants of fertility and advocating for tailored policy interventions at the provincial level. Hence, a nuanced approach to regional politics becomes imperative. Furthermore, provinces like Alborz, Semnan, Gilan, Kermanshah, Ilam, and Isfahan, which score low on the overall index, should be prioritized for targeted population policies.