Abstract

For the sustainable development of a country or a city, it is important to know the accurate idea of the population of that region. The local authorities can easily implement their various development plans if they know the future scenario of the population. This study aims to forecast the population of Sylhet City Corporation, which was transformed into a city corporation 20 years ago. Three frequently used and popular methods of population forecasting Arithmetic Increase Method, Geometric Increase Method, and Incremental Increment Method are used to forecast the population. Population data from 2001 to 2015 are used to train and data from 2016 to 2021 are used to verify the methods. The average percentage of error of these three methods is about 3%. Among the three methods, the Geometric Increase Method provides the best result with a percentage of error of 0.15655%. 

Keywords

  • Population prediction
  • Sylhet City Corporation
  • Geometric Increase Method

References

  1. Kabir, M. and Chowdhury, A. A.(1982). Population Growth and Food Production in Bangladesh, Rural Demography, IX (1 & 2): 25-56
  2. Mallick, A. A. (1980), Implausibility of Attaining Zero Population Growth in Banthin Next 100 Years, Rural Demography, VII (1 & 2): 33-39
  3. Beekman, J. A.(1984), Population and Social Security Projection Techniques, Rural Demography”, XI (1 & 2): 1-20.
  4. Rahman, M. M. (1993), National Growth Rate Method with Varying Internal Migration Rate, The Bangladesh Development Studies, XXI (2): 73-76.
  5. Wilson, T., Brokensha, H., Rowe, F., and Simpson, L. (2018). Insights from the evaluation of past local area population forecasts. Population Research and Policy Review 37(1): 137–155. doi:10.1007/s11113-017-9450-4.
  6. Rayer, S. (2008). Population forecast errors: A primer for planners. Journal of Planning Education and Research 27(4): 417–430. doi:10.1177/0739456X07313925.
  7. Rayer, S. and Smith, S.K. (2014). Population projections by age for Florida and its counties: Assessing accuracy and the impact of adjustments. Population Research and Policy Review 33(5): 747–770. doi:10.1007/s11113-014-9325-x.
  8. Statistics New Zealand (2008). How accurate are population projections? An evaluation of Statistics New Zealand population projections, 1991–2006. Wellington: Statistics New Zealand. http://archive.stats.govt.nz/browse_for_stats/population/ estimates_and_projections/how-accurate-are-population-projections.aspx.
  9. Tayman, J. (2011). Assessing uncertainty in small area forecasts: State of the practice and implementation strategy. Population Research and Policy Review 30(5): 781–800. doi:10.1007/s11113-011-9210-9.
  10. Yamauchi, M., Koike, S., and Kamata, K. (2017). How accurate are Japan’s official subnational projections? Comparative analysis of projections in Japan, Englishspeaking countries and the EU. In: Swanson, D.A. (ed.). The frontiers of applied demography. Dordrecht: Springer: 305–328. doi:10.1007/978-3-319-43329- 5_15.
  11. Chi, G., Zhou, X. & Voss, P.R. (2011). Small-area population forecasting in an urban setting: a spatial regression approach. J Pop Research 28:185–201. https://doi.org/10.1007/s12546-011-9053-6
  12. Manojkumar Tiwari (2018) , Waste water generation and quantity estimation, Week 2, Lecture 6, NPTEL, IIT Kharagpur
  13. Hoque, M. A., Ahmed, F. and Sarker, M. M. (1995): An Estimation of future population of Bangladesh, Journal of Statistical Studies of Jahangir nagar University. 15:75-88.
  14. Ara, S(2014). Impact of Temporal Population Distribution on Earthquake Loss Estimation: A Case Study on Sylhet, Bangladesh. Int J Disaster Risk Sci 5: 296–312 .https://doi.org/10.1007/s13753-014-0033-2