Projection of the Fertility at Madhesh Province, Nepal

Accurate estimation of fertility is crucial toward the comprehension of population dynamics for the purpose of policy formulation in Nepal. Consequently, both the Arriaga and the P/F methods, as well as the related demographic modeling techniques, were brought to bear on the problem of analyzing fertility trends in Madhesh Province. The study applied census data from 2011 and 2021 and estimated ASFR, TFR, and interpolation of inconsistencies using indirect estimation techniques. The findings of this study reveal that the province of Madhesh is facing continuing declines in fertility, as the TFR leveled off from 3.362 in 2011 to 3.059 by 2021. Projection under clear logistic curve suggests that TFR would further decline to reach replacement level (2.1) by 2031. Age-sex pyramids developed from the census data suggest significant demographic shifts with an increasing ageing index and decreasing dependency ratio-suggestive of flowing population structure. The study consensuses considerable variation in changing fertility rates among various subgroups while emphasizing the critical impact of socio-economic and demographic factors. This study shows that indirect estimations are important for estimation logistic function applied here for fertility projection fundamentally provides a more reliable means of constraining demographic estimates that policymakers can justly defend. Linear interpolation was used to derive the TFR values for 2021 and 2026, and extrapolation for the period of 2030 and 2031; an indirect concern may intern that the TFR for 2031 is predicted to fall beyond the replacement level. A necessary onset for low fertility rates throughout Madhesh Province becomes ongoing demographic monitoring and improving data-collection techniques-wildly helpful for making informed decisions on population planning and resource allocation. The study contributes substantially toward the understanding of fertility trends in Nepal by drawing upon demographic transitions and their implications for future growth.