Population forecasting models play an important role in analyzing current population processes and predicting their future development. The Republic of the Congo saw population growth from 1.02 million to 5.66 million people between 1960 and 2021. This is an increase of 455.6% over 61 years. Urbanization is a trend that is accelerating and growing at a 3.2% yearly rate with the country's current economic situation, which is not ideal. The objective of this study is to show and forecast the population growth rate in Congo B using the ARIMAX system. Based on the data of per capita GDP and population growth rate in Congo B from 1982 to 2019, this paper uses per capita GDP as the input variable and population growth rate as the response variable and uses the ARIMAX model for research. The predictions for Congo B's population growth rate in 2020-2024 were correct. The results were 11.77‰, 11.60‰, 11.55‰, 11.34‰, 11.03‰, respectively. This indicates a country with a lower population growth rate. The results of this work allow the government and Congolese leaders to use them as a reference when creating a baseline and responsible growth strategy because they show that the rate of population expansion in Congo B will slow over the next five years and that migration will remain moderate.
| Published in | International Journal of Business and Economics Research (Volume 12, Issue 1) |
| DOI | 10.11648/j.ijber.20231201.11 |
| Page(s) | 1-8 |
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2024. Published by Science Publishing Group |
Population Growth Rate, Per Capita GDP, Arimax Model, SAS Software
| [1] | He X H, Zhang S H and WangYing X J 2017 Prediction of China's population under the Comprehensive two-Child Policy based on the two-tier “small World” Model [J]. Scientist 17 11, 44. |
| [2] | David Shapiro and B. Oleko Tambashe Workshop on Prospects for Fertility Decline on High Fertility Countries, Population Division, Department of Economic and Social Affairs, United Nations Secretariat, New York, 9–11 July, 2001. |
| [3] | Jie Dai and Shuping Chen. College of Mathematics, Xiamen University of Technology, Xiamen 361024, China The application of ARIMA model in forecasting population data to cite this article: Jie Dai and Shuping Chen 2019 J. Phys.: Conf. Ser. 1324 012100 View the article online for updates and enhancement. |
| [4] | Yuniar Farida, Mayandah Farmita, Nurissaidah Ulinnuha, Dian Yuliati Forecasting Population of Madiun Regency Using ARIMA Method CAUCHY –Jurnal Matematika Murni dan Aplikasi Volume 7 (3) (2022), Pages 420-431 p-ISSN: 2086-0382; e-ISSN: 2477-3344. |
| [5] | Guarnaccia C, Graziuso G, Mancini S, Quartieri J. On the Use of ARIMA Models to Predict Urban Sound Pressure Levels. InForum Acusticum 2020 Dec 7 (pp. 1677-1683). |
| [6] | Nyoni T, Mutongi C. Prediction of total population in Togo using ARIMA models. |
| [7] | Tu X L and Tu H Y 2009 A Comparative study of ARIMA and exponential smoothing method in population Prediction in China [J]. Statistics and Decision 16 21-23. |
| [8] | Farida Y, Farmita M, Ulinnuha N, Yuliati D. Forecasting Population of Madiun Regency Using ARIMA Method. CAUCHY: Jurnal Matematika Murni dan Aplikasi. 2022 Oct 11; 7 (3): 420-31. |
| [9] | Eralda DHAMO, Llukan PUKA. An ARIMA birth number per month model for Albanian population 1st International Symposium on Computing in Informatics and Mathematics (ISCIM 2011)” in Collabaration between EPOKA University and University of “Aleksandër Moisiu” Durrës on June 2-4 2011, Tirana-Durres, ALBANIA. |
| [10] | Muhammad Zakria and Faqir Muhammad Forecasting the population of Pakistan using ARIMA models. Pak. J. Agri. Sci., Vol. 46 (3), 2009. |
| [11] | YI Dan-hui, WANG Yan. Application Time Series Analysis [M]. 5th ed. Beijing: Renmin University Press, 2019: 248. |
| [12] | Xiao DH, Xie QM, Yang WD. Application of Integrated Forecasting Model Based on Multi-variables in Tunnel Vault Settlement. Journal of Highway and Transportation Research and Development. 2018 Sep 30; 12 (3): 46-52. |
| [13] | Wang YL, Wang Xi. Prediction of the trend of birth rate in Fenghua district of Ningbo city by autoregressive moving average model [J]. International Journal of Epidemiology and Epidemic disease, 2020 (4): 341-343. |
| [14] | Kahlil M, Kahlil M, Kahlil M, et al. Birth Rate Prediction in China [J]. Journal of Population Science, 2000, 35 (3): 256-264. |
| [15] | Ren Dong, Li Ping, Li Ping. Factors Affecting Birth Rate and Policy Options: 1994 ~ 2014 [J]. Reform, 2015 (10): 23-31. |
| [16] | Zhu Qian. Fertility Rate and Economic Development in China [J]. Cooperative Economics and Technology, 2019 (14): 11-13. |
| [17] | GUAN Heshan, ZOU Pure Brightness, LUO Zhi-chao. Classification and identification of stationary time series [J]. Forum of Statistics and Information theory, 2016, 31 (4): 3-8. |
| [18] | Wang Yuanzheng, Xu Yajing. Application of ARIMAX Model for Multivariate Stationary Time Series [J]. Statistics and Decision Making, 2007, 23 (18): 134-137. |
| [19] | Chen Yan. ARIMAX Model Approach: Disposable Income and Consumption Expenditure of Chongqing Urban Residents [J]. Journal of Chongqing Technology and Business University (Natural Science Edition), 2015, 32 (11): 80-85. |
APA Style
Itoba Ongagna Ipaka Safnat Kaito, Zhang Ding Hai. (2023). Application of the ARIMAX Model in Forecasting the Population Growth Rate of Congo B. International Journal of Business and Economics Research, 12(1), 1-8. https://doi.org/10.11648/j.ijber.20231201.11
ACS Style
Itoba Ongagna Ipaka Safnat Kaito; Zhang Ding Hai. Application of the ARIMAX Model in Forecasting the Population Growth Rate of Congo B. Int. J. Bus. Econ. Res. 2023, 12(1), 1-8. doi: 10.11648/j.ijber.20231201.11
AMA Style
Itoba Ongagna Ipaka Safnat Kaito, Zhang Ding Hai. Application of the ARIMAX Model in Forecasting the Population Growth Rate of Congo B. Int J Bus Econ Res. 2023;12(1):1-8. doi: 10.11648/j.ijber.20231201.11
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Download@article{10.11648/j.ijber.20231201.11,
author = {Itoba Ongagna Ipaka Safnat Kaito and Zhang Ding Hai},
title = {Application of the ARIMAX Model in Forecasting the Population Growth Rate of Congo B},
journal = {International Journal of Business and Economics Research},
volume = {12},
number = {1},
pages = {1-8},
doi = {10.11648/j.ijber.20231201.11},
url = {https://doi.org/10.11648/j.ijber.20231201.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20231201.11},
abstract = {Population forecasting models play an important role in analyzing current population processes and predicting their future development. The Republic of the Congo saw population growth from 1.02 million to 5.66 million people between 1960 and 2021. This is an increase of 455.6% over 61 years. Urbanization is a trend that is accelerating and growing at a 3.2% yearly rate with the country's current economic situation, which is not ideal. The objective of this study is to show and forecast the population growth rate in Congo B using the ARIMAX system. Based on the data of per capita GDP and population growth rate in Congo B from 1982 to 2019, this paper uses per capita GDP as the input variable and population growth rate as the response variable and uses the ARIMAX model for research. The predictions for Congo B's population growth rate in 2020-2024 were correct. The results were 11.77‰, 11.60‰, 11.55‰, 11.34‰, 11.03‰, respectively. This indicates a country with a lower population growth rate. The results of this work allow the government and Congolese leaders to use them as a reference when creating a baseline and responsible growth strategy because they show that the rate of population expansion in Congo B will slow over the next five years and that migration will remain moderate.},
year = {2023}
}
TY - JOUR T1 - Application of the ARIMAX Model in Forecasting the Population Growth Rate of Congo B AU - Itoba Ongagna Ipaka Safnat Kaito AU - Zhang Ding Hai Y1 - 2023/01/10 PY - 2023 N1 - https://doi.org/10.11648/j.ijber.20231201.11 DO - 10.11648/j.ijber.20231201.11 T2 - International Journal of Business and Economics Research JF - International Journal of Business and Economics Research JO - International Journal of Business and Economics Research SP - 1 EP - 8 PB - Science Publishing Group SN - 2328-756X UR - https://doi.org/10.11648/j.ijber.20231201.11 AB - Population forecasting models play an important role in analyzing current population processes and predicting their future development. The Republic of the Congo saw population growth from 1.02 million to 5.66 million people between 1960 and 2021. This is an increase of 455.6% over 61 years. Urbanization is a trend that is accelerating and growing at a 3.2% yearly rate with the country's current economic situation, which is not ideal. The objective of this study is to show and forecast the population growth rate in Congo B using the ARIMAX system. Based on the data of per capita GDP and population growth rate in Congo B from 1982 to 2019, this paper uses per capita GDP as the input variable and population growth rate as the response variable and uses the ARIMAX model for research. The predictions for Congo B's population growth rate in 2020-2024 were correct. The results were 11.77‰, 11.60‰, 11.55‰, 11.34‰, 11.03‰, respectively. This indicates a country with a lower population growth rate. The results of this work allow the government and Congolese leaders to use them as a reference when creating a baseline and responsible growth strategy because they show that the rate of population expansion in Congo B will slow over the next five years and that migration will remain moderate. VL - 12 IS - 1 ER -
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