Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
권호 표지
DOI QR코드

DOI QR Code

N-point modified exponential model for household projections in Korea using multi-point register-based census data

  • Saebom Jeon (Department Marketing Bigdata, Mokwon University) ;
  • Tae Yeon Kwon (Department of International Finance, Hankuk University of Foreign Studies)
  • Received : 2023.11.29
  • Accepted : 2023.12.24
  • Published : 2024.07.31
Download PDF
⟨ Previous Next ⟩

Abstract

Accurate household projections are essential for sectors such as housing supply and tax policy planning, given the rapid social changes like declining birthrates, an aging population, and a rise in single-person households that impact household size and type. Korea introduced its first register-based census in 2015, transitioning from five-year general survey-based approach to an annual administrative data-based census. This change in census allows for more frequent and effective capturing the rapid demographic shifts and trends. However, this change in census has caused challenges in future projection by the existing household projection model due to the rapid dynamics. This paper proposes a new household projection method, the N-point Modified Exponential Model (MEM), that accurately reflects register-based census data and mitigates the impact of rapid demographic changes, in three types: the Weighted N-point MEM, the Regression-based N-point MEM, and the Rolling Weighted N+point MEM. Using register-based census data from 2016 to 2020 to forecast household headship rates by age, household size, and household type to 2051, the N-point modified exponential model outperformed the existing model in both long- and short-term forecast accuracy, suggesting its suitability as a future household projection model for Korea.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)(NRF-2022R1F1A1065520 to Jeon, and NRF-2021R1F1A1059513 to Kwon). This work was supported by Hankuk University of Foreign Studies Research Fund.

References

  1. Alias AR, Zainun NY, Rahman IA, Suratkon A, Sulaiman N, Ghazali FEM, and Shamsuddin N(2018). Headship rate projections for housing demand in Johor, Malaysia. In Journal of Physics: Conference Series, IOP Publishing.p.012005
  2. Australian Bureau of Statistics (2019). Household and Family Projections, Australia, Available from: https://www.abs.gov.au/statistics/people/population/household-and-family-projections-australia/2016-2041
  3. Beers HS (1945). Six-term formulas for routine actuarial interpolation, The Record of the American Institute of Actuaries, 34, 59-60.
  4. Bell M and Cooper J (1990). Household forecasting: Replacing the headship rate model, In Fifth National Conference, Australian Population Association, Melbourne, November.
  5. Bell M, Cooper J, and Les M (1995). Household and Family Forecasting Models: A Review, Commonwealth Department of Housing and Regional Development.
  6. Cho Y, Kim K, Jeon S, and Kim S (2018a). A study on adjustment of transition rates between marital status, Journal of The Korean Data Analysis Society, 20, 137-146.
  7. Cho Y, Kim K, Kim S, and Jeon S (2018b). Heuristic Lee-Carter model for long-term marital rate prediction, Journal of The Korean Data Analysis Society, 20, 125-136.
  8. Glick PC (1957). American families, a volume in the 1950 Census Monograph Series, New York: Wiley. 1957b The family cycle, American Sociological Review, 12, 164-174.
  9. Greville TN (1948). Recent developments in graduation and interpolation, Journal of the American Statistical Association, 43, 428-441.
  10. Hu Z and Peng X (2015). Household changes in contemporary China: An analysis based on the four recent censuses, The Journal of Chinese Sociology, 2, 1-20.
  11. van Imhoff E, Kuijsten A, Hooimeijer P, and van Wissen LJ (2013). Household demography and household modeling, Springer Science & Business Media.
  12. INSEE France (2024). Household Forecasts-Documentation on methodology, Available from: https://www.insee.fr/en/metadonnees/source/serie/s1317/documentation-methodologique
  13. Ironmonger DS and Lloyd-Smith CW (1992). Projections of households and household populations by household size propensities, Journal of the Australian Population Association, 9, 153-171.
  14. Jacobsen LA, Mather M, and Dupuis G (2012). Household change in the United States, Population Bulletin, 67, 2-13.
  15. Jun KH (2020). Singapore's transition to register-based population censuses and some lessons for 2020 round census in Asia, Social Science Study, 31, 237-259.
  16. Kajiwara K, Ma J, Seto T, Sekimoto Y, Ogawa Y, and Omata H (2022). Development of current estimated household data and agent-based simulation of the future population distribution of households in Japan, Computers, Environment and Urban Systems, 98, 101873.
  17. Kim S, Kim K, and Jeon S (2018). Heuristic Li-Lee model for long-term prediction of regional headship rate, Journal of The Korean Data Analysis Society, 20, 657-668.
  18. Leiwen J and O'Neill BC (2004). Toward a new model for probabilistic household forecasts, International Statistical Review, 72, 51-64.
  19. Makridakis S (1993). Accuracy measures: Theoretical and practical concerns, International Journal of Forecasting, 9, 527-529.
  20. Nash A (2021). Household projections for England: 2018-based, Office for National Statistics, UK, Available from: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationprojections/bulletins/householdprojectionsforengland/2018based
  21. National Institute of Population and Social Security Research, Japan (2018). Future estimate of the number of households in Japan, Available from: https://www.ipss.go.jp/pp-ajsetai/j/HPRJ2018/hprj2018_gaiyo_20180117.pdf
  22. Office for National Statistics, UK (2020). Local authority household projections for Wales: 2018-based, Available from: https://www.gov.wales/sites/default/files/statistics-and-research/2020-08/subnational-household-projections-local-authority-2018-based-272.pdf
  23. Park Y and Lee S (2017). For the reliability of the 2015 registration census and future population projection, Survey Research, 18, 1-37.
  24. Park YS, Park SK, Choi BS, and Kim KH (2009). A comparison of probability of death result using beers's interpolation coefficient and Greville's formula, Journal of the Korean Data Analysis Society, 11, 97-110.
  25. Rousseeuw PJ and Leroy AM (2005). Robust regression and outlier detection, John Wiley & Sons.
  26. Statistics Canada (2020). Housing market insight- CMHC household projection, National and provincial analysis, Available from: https://publications.gc.ca/site/eng/9.895677/publication.html
  27. Statistics Korea (2019). Household Projections by Province (2020~2050), Available from: https://kostat.go.kr/board.es?mid=a20108010000&bid=11742&act=view&list no=421634&tag=&nPage=5&ref_bid=11742,11743,11744,11745,11746,11747,11748,11749,11773,11774,11750&keyField=&keyWord=
  28. Taylor S (2020). Household Projections for Scotland: 2018-based, National Records of Scotland, Available from: https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/households/household-projections/2018-based-household-projections
  29. Wilson T (2013). The sequential propensity household projection model, Demographic Research, 28, 681-712.