Modeling and Forecasting Ukraine’s Population by Time Series Using the Matlab Econometrics Toolbox
The article deals with modeling and forecasting the population of Ukraine by time series. It is shown that time series analysis is a complex, multicomponent econometric task which does not have a universal approach to its solution. This is due both to the diversity of methods of and approaches to ti...
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Published in | Bìznes ìnform (Multilingual ed.) Vol. 5; no. 496; pp. 98 - 105 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Research Centre of Industrial Problems of Development of NAS of Ukraine
01.05.2019
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Subjects | |
Online Access | Get full text |
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Abstract | The article deals with modeling and forecasting the population of Ukraine by time series. It is shown that time series analysis is a complex, multicomponent econometric task which does not have a universal approach to its solution. This is due both to the diversity of methods of and approaches to time series analysis which were developed over time and to the specifics of time series data. For example, the authors of the article worked with a univariate nonstationary time series, therefore, the approaches and methods presented in the article are not recommended for time series with different properties. The article has an enormous practical value, since it discusses in detail issues of computer modeling of tasks of the kind. The carried out analysis of the literature has shown the relevance of the problems considered, among which particular attention should be paid to the choice of the ARIMA model, data visualization, and forecast accuracy. |
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AbstractList | The article deals with modeling and forecasting the population of Ukraine by time series. It is shown that time series analysis is a complex, multicomponent econometric task which does not have a universal approach to its solution. This is due both to the diversity of methods of and approaches to time series analysis which were developed over time and to the specifics of time series data. For example, the authors of the article worked with a univariate nonstationary time series, therefore, the approaches and methods presented in the article are not recommended for time series with different properties. The article has an enormous practical value, since it discusses in detail issues of computer modeling of tasks of the kind. The carried out analysis of the literature has shown the relevance of the problems considered, among which particular attention should be paid to the choice of the ARIMA model, data visualization, and forecast accuracy. |
Author | Kovalova, K. O. Misiura, I. Y. |
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CorporateAuthor | Simon Kuznets Kharkiv National University of Economics |
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Title | Modeling and Forecasting Ukraine’s Population by Time Series Using the Matlab Econometrics Toolbox |
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