STATISTICAL METHODS FOR FORECASTING THE DEVELOPMENT OF DEMOGRAPHIC INDICATORS IN UKRAINE: APPLICATION CONTEXT
DOI:
https://doi.org/10.35774/jee2021.01.183Keywords:
Demographic forecast, demographic indicators, extrapolation methods, forecast, methods of demographic forecasting, methods of expert evaluations, methods of shifting ages, methods of statistical simulation, methods of statistics, prognostication.Abstract
The article examines the demographic processes and indicators of Ukraine over the years of its independence. The essence of the concepts «forecast», «forecasting» and «demographic forecast» is considered. It is demonstrated that the results of the demographic forecast and the subsequent strategic analysis constitute essential information for substantiating the prediction of the main parameters of population indicators, future demographic situation and socioeconomic processes in a given area. The conditions for application of demographic forecasting methods are defined. The statistical methods that are most often used in practice to forecast the future population are grouped into methods of extrapolation, methods of shifting ages, methods of statistical modelling (methods of mathematical modelling), methods of expert evaluations. It is determined that in practice each group of statistical methods of demographic forecasting has its purpose, characterizes a specific demographic phenomenon and is applied to a specific area. Recommendations on using the optimal methods for forecasting and predictive calculations of future demographic indicators of Ukraine are suggested in order to ensure the analytical and predictive component of management.
JEL: E20, J11.
References
Alho, J. M., & Spencer, B. D. (1985). Uncertain population forecasting. Journal of the American Statistical Association, 80(390), 306-314. https://doi.org/10.1080/01621459.1985.10478113
Anacka, M. (2017). Modelling and forecasting of demographic phenomena. JRCSAS-INGSA Summer School. https://ec.europa.eu/jrc/communities/sites/jrccties/files/3_modelling_forecasting.pdf
Beshelev, S. D., & Gurvich, F. G. (1980). Mathematical and statistical methods of expert valuations (2nd ed.) [in Russian]. Statistika.
Booth, H. (2006). Demographic forecasting: 1980 to 2005 in review. International Journal of Forecasting, 22(3), 547-581. URL: https://doi.org/10.1016/j.ijforecast.2006.04.001
Drukach, O. (2017, August 21). Minus 10 million: How the demographic structure of Ukraine was changing over the course of independence [in Ukrainian].
Kanal 24. https://24tv.ua/minus_10_milyoniv_yak_zminyuvalas_ demografichna_struktura_ukrayini_za_chasi_nezalezhnosti_n855191
Duliuk, I. V., & Matusov, Yu. P. (2010). Modeling of demographic processes in Ukraine using optimal recognition procedures [in Ukrainian]. Ekonomichnyi Visnyk NTUU "KPI", 7, 250-255. http://economy.kpi.ua/uk/taxonomy/term/749
Ermilov, A. P. (1987). Macroeconomic forecasting in the USA [in Russian]. Nauka.
Hnatiienko, H. M., & Snytiuk, V. Ye. (2008). Expert technologies of decisionmaking: monograph [in Ukrainian]. McLaut.
Hrabovetskyi, B. Ye. (2010). Methods of expert assessments: Theory, methodology, areas of use: monograph [in Ukrainian]. VNTU.
Keyfitz, N. (1985). A probability representation of future population. Zeitschrift für Bevölkerungswissenschaft, 11(2), 179-191.
Kildishev, G. S., Kozlova, L. L., & Ananieva, S. P. (1990). Population statistics with the basics of demography: textbook [in Russian]. Finansy i Statistika. Law of Ukraine "On state forecasting and development of programs of economic and social development of Ukraine" of December 2, 2012 [in Ukrainian]. https://zakon.rada.gov.ua/laws/show/ru/1602-14.
Libanova, E. M. (2007). Human development in regions of Ukraine: Analysis and forecast [in Ukrainian]. Ptoukha Institute for Demography and Social Studies of the National Academy of Sciences of Ukraine.
Libanova, E. M. (Ed.). (2015). Human development in Ukraine. Modernization of social policy: Regional Aspect (collective monograph) [in Ukrainian].Ptoukha Institute for Demography and Social Studies of the National Academy of Sciences of Ukraine.
Luchko, M. R. (2017). Economy of Ukraine: The analysis of the innovative way of the development. Economics, Management and Sustainability, 2(2), 95-103. https://doi.org/10.14254/jems.2017.2-2.10
Luchko, M. R., Arzamasova, O., & Vovk, I. (2019). Personnel potential of national economy and gross domestic product: The case of Ukraine. Montenegrin Journal of Economics, 15(2), 59-70.
Martino, J. P. (1977). Technological Forecasting for Decisionmaking [in Russian]. Progress. (Original work published in 1972).
Migration Policy Institute. (n.d.). Immigrant and Emigrant Populations by Country of Origin and Destination [Interactive map]. Retrieved from https://www.migrationpolicy.org/programs/data-hub/charts/immigrant-andemigrant-populations-country-origin-and-destination
Miller, T. (2006). Demographic models for projections of social sector demand. Latin American and Caribbean Demographic Centre (CELADE) - Population Division. https://core.ac.uk/download/pdf/45621163.pdf
Ministry of Finance of Ukraine. (n.d.). https://www.minfin.gov.ua.
Pflaumer, P. (1988). Confidence intervals for population projections based on Monte Carlo methods. International Journal of Forecasting, 4(1), 135-142. https://doi.org/10.1016/0169-2070(88)90015-5
Ptoukha Institute for Demography and Social Studies of the National Academy of Sciences of Ukraine. (n.d.). https://www.idss.org.ua/index
Radchenko, I., O., & Orlova, O. M. (Eds.). (2010). New thesaurus of modern Ukrainian language [in Ukrainian]. PP Holiaka V. M.
Shesternyak, М. М. (2019). Statistics in Ukraine: Main stages of development, status, trends and prospects [in Ukrainian]. Business Navigator. 4, 150- 157. http://www.business-navigator.ks.ua/journals/2019/53_2019/28.pdf
State Statistics Service of Ukraine. (n.d.). http://www.ukrstat.gov.ua.
Stoto, M. (1983). The accuracy of population projections. Journal of the American Statistical Association, 78(381), 13-20. https://doi.org/10.1080/01621459.1983.10477916
Tabeau, E., van den Berg Jeths, A., & Heathcote, C. (Eds.). (2001). Forecasting mortality in developed countries: Insights from a statistical, demographic and epidemiological perspective (Vol. 9). Springer Science & Business Media. https://link.springer.com/book/10.1007/0-306-47562-6#about https://doi.org/10.1007/0-306-47562-6
TSN. (2017, February, 1). Bloomberg named the countries most at risk of aging. Infographics [in Ukrainian]. https://tsn.ua/svit/starinnya-vdarit-po-rf-tabilorusi-ukrayina-blizka-do-mezhi-infografika-873468.html
Uriadovyi Kuriier. (2013, December 20). Forecast of the number and age of the population of Ukraine [in Ukrainian]. https://ukurier.gov.ua/uk/articles/ prognoz-chiselnosti-ta-vikovogo-skladu-naselennya
Vlasenko, N. S., Libanova, E. M., Makarova, O. V., Pyrozhkov, S. I. Pozniak, O. V., Stelmakh, L. M., Shvydka, H. Yu., & Shevchuk, P. Ye. (2006). Comprehensive demographic forecast for Ukraine until 2050 (E. M. Libanova, Ed.) [in Ukrainian]. Ukrainskyi tsentr sotsialnykh reform.
Volska, О. М., & Mykolaichuk, N. S. (2013). Information support as a tool for forecasting and planning the transition to sustainable development of the enterprise [in Ukrainian]. Economic Innovations, 54, 34-42.
Zakhozhai, V. B., & Fedorchenko, V. S. (2006). Theory of statistics: textbook [in Ukrainian]. MAUP.
Received: 15 January, 2021.
Revised: 19 January, 2021.
Accepted: 21 January, 2021.
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).