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All Journal International Journal of Quantitative Research and Modeling
Rehena Nasrin
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Physics

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Age-specific Age-specific Female Population Projection of Bangladesh in 2026 and 2031Using Leslie Matrix Model Nurain Arju; Khandker Farid Uddin Ahmed; Rehena Nasrin
International Journal of Quantitative Research and Modeling Vol. 7 No. 1 (2026): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i1.1129

Abstract

The population density of Bangladesh is higher than many other countries in the world. According to the preliminary census report of the Bangladesh Census and Household Survey 2022, the total population of Bangladesh at the time of the 2022 census was 165,158,616. The total number of females and males was 8,33,47,206 and 8,17,12,824, respectively. As a country’s equilibrium in environment, economics, and even administration is highly influenced by its population, these demographic data are essential for a well-regulated impact. Population projection helps a country achieve its desired population for overall prosperity. A widely used model for projecting population growth is the Leslie model. In this research, Leslie's matrix model is applied to predict the age-specific female population of Bangladesh and population growth in 2026 and 2031 by using female survival and birth rates. The eigenvalues of the Leslie matrix are used to calculate the population growth rate of women, where the principal eigenvalues are taken as the desired growth rate, and the corresponding eigenvectors are used to obtain the age-specific female population. In this research, the results indicate a gradual decrease in the female population growth rate, with the principal eigenvalue estimated at approximately 0.99 for 2026 and 0.97 for 2031, suggesting a slow and steady decline.
Co-Authors Khandker Farid Uddin Ahmed Nurain Arju