Estimation and Projection of the Fertility at Bagmati Province
Keywords:bagmati province, estimation, projection, arriga, brass
Information on fertility levels and patterns can assist to formulate and evaluate policies related to population change (Brass, 2015). Policy infertility can affect the population change. Fertility relies upon accepted practices and desired family size (Bongaart, 2017). Fertility provides positive contribution to population growth if it is above the replacement level. The negative contribution occurs if it is below replacement level (Pressat,1973). So, actual scenario of fertility data is essential for policy formulation. Fertility decline in Nepal has been tested and tried with different studies gives different figures like demographic health survey and national census data but varies data in provincial level. This study describes number of children ever born and number of births before 12 months who were given birth by reproductive (15-49) age group of women. The study has utilized census data from CBS that were conducted in 2001 and 2011. From census data files 1156521 and 1583063 number of reproductive age group (12.5% of the sample data) of women were identified through analysis. It was used to the Arriaga method and changing P/F ratio method in the estimation of Bagmati Province. The TFR values of Bagmati Province exact years 2016, 2021, 2026 and 2031 were obtained by linear interpolation and extrapolation by 2031, it will too low TFR replacement level.