Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis

Ayoola Femi Joshua; Gbadamosi Idris Isaac; Odularu Gbadebo Olusegun; Ikem Fidelis

doi:doi:10.11648/j.ajtas.20221103.13

| Peer-Reviewed

Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis

Ayoola Femi Joshua, Gbadamosi Idris Isaac, Odularu Gbadebo Olusegun, Ikem Fidelis

Published in American Journal of Theoretical and Applied Statistics (Volume 11, Issue 3)

Received: 9 April 2022 Accepted: 3 May 2022 Published: 8 June 2022

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

The outbreak of COVID-19 has led to an unprecedented impact on the health, population growth, and economic development of countries globally. The government in most countries came up with measures to curtail the spread of this deadly virus not minding its impacts on their economic growth and population growth. This study examined the relationship between Population Dynamics (PD) and Economic Growth (EG) in twenty-five selected African countries using panel data spanning from 1993 to 2020. Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat were used to determine the stationarity conditions of the variables. Also, the pooled mean autoregressive distributed lag model was used to determine the short-run and long-run relationship existing among the variables while the Granger causality test was adopted to determine the direction of the relationship between the dependent and independent variables. The outcome of research findings showed that Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat test reveal that the variables were stationery at different orders and the pooled mean autoregressive distributed lag model analysis reveals there are short run and long-run relationships between economic EG and PD. The Granger causality analysis reveals the bidirectional causality between EG and PD. It has shown that PD has a significant impact on EG with the birth rate having a long-run relationship with GDP per Capita which implies that when the economy is booming or viable, there is every tendency that the population will increase through birth rate in a long run in these developing African countries.

Published in	American Journal of Theoretical and Applied Statistics (Volume 11, Issue 3)
DOI	10.11648/j.ajtas.20221103.13
Page(s)	94-101
Creative Commons	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.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Economic Growth, Population Dynamics, African Countries, Panel Data, Granger Causality

References

[1]	Adeosun, O. T., & Gbadamosi, I. I. (2021). Impact of non-oil sectors on GDP/capita in selected African countries: evidence from panel analysis. World Journal of Science, Technology and Sustainable Development.
[2]	Amoah, A., Tetteh, C., Korle, K., & Quartey, S. H. (2021). Human Development and Net Migration: the Ghanaian Experience. Journal of International Migration and Integration, 1-26.
[3]	Ayoola, F. J. (2017). Exploration Analysis of Some Panel Data Estimators in the Presence of One-Sided Exponential Heteroscedasticity Structure. American Journal of Theoretical and Applied Statistics. Vol. 6, No. 5, 2017, pp. 248-253.
[4]	Ekum, M. I, Farinde, D. A, and Ayoola, F. J. (2013). Panel Data: The Effects of Some World Development Indicator (WDI) on GDP, Per Capita of Selected African Union (AU) Countries (1981-2011). International Journal of Science and Technology (IJST) Vol. 2 No. 12, 2013, pp. 900-907.
[5]	Bankole, A. S., & Odularu, G. O. (2009). Urbanization and Economic Growth in West Africa: A Panel Data Approach. Journal of Population and Social Studies [JPSS], 17 (2), 151-168. Retrieved from https://so03.tci-thaijo.org/index.php/jpss/article/view/84651
[6]	Bloom, D. E., & Williamson, J. G. (1998). Demographic transitions and economic miracles in emerging Asia. The World Bank Economic Review, 12 (3), 419-455.
[7]	Centers for Disease Control and Prevention. 2020a. ‘Coronavirus Disease 2019 (COVID-19): How It Spreads.’
[8]	Centers for Disease Control and Prevention. 2020b. ‘Social Distancing, Quarantine, and Isolation’. Available at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/social-distancing.html
[9]	Choi, J., Dutz, M. A., & Usman, Z. (Eds.). (2020). The future of work in Africa: Harnessing the potential of digital technologies for all. World Bank Publications.
[10]	Crist, E., Mora, C. & Engelman, R. (2017). The interaction of human population, food production and biodiversity protection. Science 356 (6335): 260-264.
[11]	Essien, E. B.(2016) Population growth and Economic Growth performance In Nigeria (1981-2014). Turkish Economic Review 3 (1) 1-17.
[12]	Eze-Michael, E. N. (2020). Youth restiveness and economic development in Nigeria: A Study of Niger-Delta. Journal of Political Science and International Relations, 3 (3), 54-70.
[13]	Hamza, L. (2015). Panel Data Analysis of Population Growth and It Implication on Economic Growth of Developing Countries. Proceedings of the International Symposium on Emerging Trends in Social Science Research. Chennai-India, paper Id C509.
[14]	Hassan, O. M., Abu, J., & Adayi, J. O. (2018). An analysis of the population-poverty cycle in Nigeria: Implications for human welfare. Journal of Emerging Trends in Economics and Management Sciences, 9 (3), 151-159.
[15]	Kaba, A. J. (2020). Explaining Africa’s rapid population growth, 1950 to 2020: Trends, factors, implications, and recommendations. Sociology Mind, 10 (4), 226-268.
[16]	Kumar, M. (2014). Importance of population growth in future economic development of Pakistan. The Nigeria Hospitality Industry Experience on Customer Relationship Management and Marketing Effectiveness, 1 (8), 42.
[17]	Nwosu, C. Dike, A. O. and Okwara, K. K. (2014). The Effects of Population Growth on Economic Growth in Nigeria. The International Journal of Engineering and Science (IJES) 3 (11): 7-18.
[18]	Odularu G., Adetunji B., Odularu A. 2020. Conclusion and Policy Recommendations: Creating an Enabling Business Ecosystem for Fostering Trade Opportunities in the Digital Age. In: Odularu G., Hassan M., Babatunde M. (eds) Fostering Trade in Africa. Advances in African Economic, Social and Political Development. Springer, Cham. https://doi-org-443.webvpn.jnu.edu.cn/10.1007/978-3-030-36632-2_10
[19]	Odularu G., Alege P. 2019. Trade Facilitation Capacity Needs. Palgrave Pivot, Cham. https://link.springer.com/book/10.1007/978-3-030-05946-0
[20]	Odularu G., Aluko O. A., Odularu A., Akokuwebe M., Adedugbe A. 2020. Conclusion: Fostering Nutrition Security, Climate Adaptation and Sustainable Agriculture Strategies Amid COVID-19 Pandemic. In: Odularu G. (eds) Nutrition, Sustainable Agriculture and Climate Change in Africa. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-47875-9_12
[21]	Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American statistical Association, 94 (446), 621-634.
[22]	Peter, A., & Bakari, I. (2018). Impact of population growth on economic growth in Africa: A dynamic panel data approach (1980-2015). Pakistan Journal of Humanities and Social Science (PJHSS), 6 (4), 412-427.
[23]	Sajini, F. I. (2021). Human population growth and the socioeconomic effects in warri metropolitan city Delta State Nigeria. Linguistics and Culture Review, 5 (S1), 878-889.

Cite This Article

Plain Text BibTeX RIS

APA Style

Ayoola Femi Joshua, Gbadamosi Idris Isaac, Odularu Gbadebo Olusegun, Ikem Fidelis. (2022). Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis. American Journal of Theoretical and Applied Statistics, 11(3), 94-101. https://doi.org/10.11648/j.ajtas.20221103.13

Copy | Download

ACS Style

Ayoola Femi Joshua; Gbadamosi Idris Isaac; Odularu Gbadebo Olusegun; Ikem Fidelis. Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis. Am. J. Theor. Appl. Stat. 2022, 11(3), 94-101. doi: 10.11648/j.ajtas.20221103.13

Copy | Download

AMA Style

Ayoola Femi Joshua, Gbadamosi Idris Isaac, Odularu Gbadebo Olusegun, Ikem Fidelis. Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis. Am J Theor Appl Stat. 2022;11(3):94-101. doi: 10.11648/j.ajtas.20221103.13

Copy | Download

@article{10.11648/j.ajtas.20221103.13,
  author = {Ayoola Femi Joshua and Gbadamosi Idris Isaac and Odularu Gbadebo Olusegun and Ikem Fidelis},
  title = {Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {11},
  number = {3},
  pages = {94-101},
  doi = {10.11648/j.ajtas.20221103.13},
  url = {https://doi.org/10.11648/j.ajtas.20221103.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20221103.13},
  abstract = {The outbreak of COVID-19 has led to an unprecedented impact on the health, population growth, and economic development of countries globally. The government in most countries came up with measures to curtail the spread of this deadly virus not minding its impacts on their economic growth and population growth. This study examined the relationship between Population Dynamics (PD) and Economic Growth (EG) in twenty-five selected African countries using panel data spanning from 1993 to 2020. Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat were used to determine the stationarity conditions of the variables. Also, the pooled mean autoregressive distributed lag model was used to determine the short-run and long-run relationship existing among the variables while the Granger causality test was adopted to determine the direction of the relationship between the dependent and independent variables. The outcome of research findings showed that Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat test reveal that the variables were stationery at different orders and the pooled mean autoregressive distributed lag model analysis reveals there are short run and long-run relationships between economic EG and PD. The Granger causality analysis reveals the bidirectional causality between EG and PD. It has shown that PD has a significant impact on EG with the birth rate having a long-run relationship with GDP per Capita which implies that when the economy is booming or viable, there is every tendency that the population will increase through birth rate in a long run in these developing African countries.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis
AU  - Ayoola Femi Joshua
AU  - Gbadamosi Idris Isaac
AU  - Odularu Gbadebo Olusegun
AU  - Ikem Fidelis
Y1  - 2022/06/08
PY  - 2022
N1  - https://doi.org/10.11648/j.ajtas.20221103.13
DO  - 10.11648/j.ajtas.20221103.13
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 94
EP  - 101
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20221103.13
AB  - The outbreak of COVID-19 has led to an unprecedented impact on the health, population growth, and economic development of countries globally. The government in most countries came up with measures to curtail the spread of this deadly virus not minding its impacts on their economic growth and population growth. This study examined the relationship between Population Dynamics (PD) and Economic Growth (EG) in twenty-five selected African countries using panel data spanning from 1993 to 2020. Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat were used to determine the stationarity conditions of the variables. Also, the pooled mean autoregressive distributed lag model was used to determine the short-run and long-run relationship existing among the variables while the Granger causality test was adopted to determine the direction of the relationship between the dependent and independent variables. The outcome of research findings showed that Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat test reveal that the variables were stationery at different orders and the pooled mean autoregressive distributed lag model analysis reveals there are short run and long-run relationships between economic EG and PD. The Granger causality analysis reveals the bidirectional causality between EG and PD. It has shown that PD has a significant impact on EG with the birth rate having a long-run relationship with GDP per Capita which implies that when the economy is booming or viable, there is every tendency that the population will increase through birth rate in a long run in these developing African countries.
VL  - 11
IS  - 3
ER  -

Copy | Download

Author Information

Ayoola Femi Joshua

College of Business, Jackson State University, Jackson, USA
Gbadamosi Idris Isaac

Department of Statistics, University of Ibadan, Ibadan, Nigeria
Odularu Gbadebo Olusegun

Department, of Economics, Business and Finance, Bay Atlantic University (BAU), Washington DC, USA
Ikem Fidelis

College of Business, Jackson State University, Jackson, USA

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Ayoola Femi Joshua, Gbadamosi Idris Isaac, Odularu Gbadebo Olusegun, Ikem Fidelis. (2022). Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis. American Journal of Theoretical and Applied Statistics, 11(3), 94-101. https://doi.org/10.11648/j.ajtas.20221103.13

Copy | Download

ACS Style

Ayoola Femi Joshua; Gbadamosi Idris Isaac; Odularu Gbadebo Olusegun; Ikem Fidelis. Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis. Am. J. Theor. Appl. Stat. 2022, 11(3), 94-101. doi: 10.11648/j.ajtas.20221103.13

Copy | Download

AMA Style

Ayoola Femi Joshua, Gbadamosi Idris Isaac, Odularu Gbadebo Olusegun, Ikem Fidelis. Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis. Am J Theor Appl Stat. 2022;11(3):94-101. doi: 10.11648/j.ajtas.20221103.13

Copy | Download

@article{10.11648/j.ajtas.20221103.13,
  author = {Ayoola Femi Joshua and Gbadamosi Idris Isaac and Odularu Gbadebo Olusegun and Ikem Fidelis},
  title = {Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {11},
  number = {3},
  pages = {94-101},
  doi = {10.11648/j.ajtas.20221103.13},
  url = {https://doi.org/10.11648/j.ajtas.20221103.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20221103.13},
  abstract = {The outbreak of COVID-19 has led to an unprecedented impact on the health, population growth, and economic development of countries globally. The government in most countries came up with measures to curtail the spread of this deadly virus not minding its impacts on their economic growth and population growth. This study examined the relationship between Population Dynamics (PD) and Economic Growth (EG) in twenty-five selected African countries using panel data spanning from 1993 to 2020. Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat were used to determine the stationarity conditions of the variables. Also, the pooled mean autoregressive distributed lag model was used to determine the short-run and long-run relationship existing among the variables while the Granger causality test was adopted to determine the direction of the relationship between the dependent and independent variables. The outcome of research findings showed that Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat test reveal that the variables were stationery at different orders and the pooled mean autoregressive distributed lag model analysis reveals there are short run and long-run relationships between economic EG and PD. The Granger causality analysis reveals the bidirectional causality between EG and PD. It has shown that PD has a significant impact on EG with the birth rate having a long-run relationship with GDP per Capita which implies that when the economy is booming or viable, there is every tendency that the population will increase through birth rate in a long run in these developing African countries.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Population Dynamics and Africa’s Poise for Post-COVID-19 Growth: Panel Data Analysis
AU  - Ayoola Femi Joshua
AU  - Gbadamosi Idris Isaac
AU  - Odularu Gbadebo Olusegun
AU  - Ikem Fidelis
Y1  - 2022/06/08
PY  - 2022
N1  - https://doi.org/10.11648/j.ajtas.20221103.13
DO  - 10.11648/j.ajtas.20221103.13
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 94
EP  - 101
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20221103.13
AB  - The outbreak of COVID-19 has led to an unprecedented impact on the health, population growth, and economic development of countries globally. The government in most countries came up with measures to curtail the spread of this deadly virus not minding its impacts on their economic growth and population growth. This study examined the relationship between Population Dynamics (PD) and Economic Growth (EG) in twenty-five selected African countries using panel data spanning from 1993 to 2020. Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat were used to determine the stationarity conditions of the variables. Also, the pooled mean autoregressive distributed lag model was used to determine the short-run and long-run relationship existing among the variables while the Granger causality test was adopted to determine the direction of the relationship between the dependent and independent variables. The outcome of research findings showed that Levin, Lin, and Chu test and Lm, Pesaran, and Shin W-stat test reveal that the variables were stationery at different orders and the pooled mean autoregressive distributed lag model analysis reveals there are short run and long-run relationships between economic EG and PD. The Granger causality analysis reveals the bidirectional causality between EG and PD. It has shown that PD has a significant impact on EG with the birth rate having a long-run relationship with GDP per Capita which implies that when the economy is booming or viable, there is every tendency that the population will increase through birth rate in a long run in these developing African countries.
VL  - 11
IS  - 3
ER  -

Copy | Download