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Forecasting Population and Demographic Composition of Kuwait Until 2030

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  • Osman Gulseven

    (Department of Math & Statistics, American University of the Middle East in Kuwait, Kuwait)

Abstract

State of Kuwait is one of the richest countries in the world. Thanks to its oil reserves, the country hosts millions of foreign workers whose numbers have outpaced the Kuwaiti population. This article aims to forecast the future population of Kuwait using regional and nationality-gender based population data. Both linear and exponential population projections are used to obtain the most reliable estimates with the least forecasting error. Using the data between 1998 and 2015, I forecast the population of distinct administrative regions, expatriate and Kuwaiti population as well as the overall population of Kuwait. The results suggest that the population of Kuwait is likely to reach 5 million by 2020, and 7 million in 2030. The growth in expatriate population particularly male expat workers will dominate the population growth. It is recommended that state policies should consider such demographic and geographical imbalances in planning the future growth of Kuwait.

Suggested Citation

  • Osman Gulseven, 2016. "Forecasting Population and Demographic Composition of Kuwait Until 2030," International Journal of Economics and Financial Issues, Econjournals, vol. 6(4), pages 1429-1435.
    • Handle: RePEc:eco:journ1:2016-04-20
    as

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    References listed on IDEAS

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    1. Cary Chi-Liang Tsai & Shuai Yang, 2015. "A Linear Regression Approach to Modeling Mortality Rates of Different Forms," North American Actuarial Journal, Taylor & Francis Journals, vol. 19(1), pages 1-23, January.
    2. Khorshid, Motaz, 1990. "A dynamic macroeconomic model for Kuwait : Analysis of the medium-term path," Energy Economics, Elsevier, vol. 12(4), pages 289-301, October.
    3. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    4. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    5. Arkadiusz Wiśniowski & Peter Smith & Jakub Bijak & James Raymer & Jonathan Forster, 2015. "Bayesian Population Forecasting: Extending the Lee-Carter Method," Demography, Springer;Population Association of America (PAA), vol. 52(3), pages 1035-1059, June.
    6. Stefan Rayer & Stanley Smith & Jeff Tayman, 2009. "Empirical Prediction Intervals for County Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 28(6), pages 773-793, December.
    7. Sulayman Al-Qudsi, 1998. "The demand for children in Arab countries: Evidence from panel and count data models," Journal of Population Economics, Springer;European Society for Population Economics, vol. 11(3), pages 435-452.
    8. Jeff Tayman & Stanley Smith & Jeffrey Lin, 2007. "Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(3), pages 347-369, June.
    9. Tzuling Lin & Cary Chi‐liang Tsai, 2015. "A Simple Linear Regression Approach to Modeling and Forecasting Mortality Rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 543-559, November.
    10. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    11. Smith, Stanley K., 1997. "Further thoughts on simplicity and complexity in population projection models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 557-565, December.
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    More about this item

    Keywords

    Population Forecasting; Demographics; Geographic Analysis; Linear Extrapolation; Exponential Extrapolation; Kuwait;
    All these keywords.

    JEL classification:

    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination

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