What will be Botswana's population in 2050? Evidence from the Box-Jenkins approach

NYONI, THABANI (2019): What will be Botswana's population in 2050? Evidence from the Box-Jenkins approach.

Abstract

Employing annual time series data on total population in Botswana from 1960 to 2017, I model and forecast total population over the next 3 decades using the Box – Jenkins ARIMA technique. Diagnostic tests such as the ADF tests show that Botswana annual total population is neither I (1) nor I (2) but for simplicity purposes, the researcher has assumed it is I (2). Based on the AIC, the study presents the ARIMA (3, 2, 1) model as the optimal model. The diagnostic tests further indicate that the presented model is indeed stable. The results of the study reveal that total population in Botswana will continue to rise in the next three decades and in 2050 Botswana’s total population will be approximately 3 665 140 people. In order to benefit from an increase in total population in Botswana, 3 policy recommendations have been suggested.

• Item Type: MPRA Paper
• Language: English
• Keywords: Botswana; forecasting; population
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q56 - Environment and Development ; Environment and Trade ; Sustainability ; Environmental Accounts and Accounting ; Environmental Equity ; Population Growth; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R2 - Household Analysis > R23 - Regional Migration ; Regional Labor Markets ; Population ; Neighborhood Characteristics

References

[1] Asteriou, D. & Hall, S. G. (2007). Applied Econometrics: a modern approach, Revised Edition, Palgrave MacMillan, New York.

[2] Ayele, A. W & Zewdie, M. A (2017). Modeling and forecasting Ethiopian human population size and its pattern, International Journal of Social Sciences, Arts and Humanities, 4 (3): 71 – 82.

[3] Beg, A. B. M. R. A & Islam, M. R (2016). Forecasting and modeling population growth of Bangladesh, American Journal of Mathematics and Statistics, 6 (4): 190 – 195.

[4] Dominic, A., Oluwatoyin, M. A., & Fagbeminiyi, F. F (2016). The determinants of population growth in Nigeria: a co-integration approach, The International Journal of Humanities and Social Studies, 4 (11): 38 – 44.

[5] Du Preez, J. & Witt, S. F. (2003). Univariate and multivariate time series forecasting: An application to tourism demand, International Journal of Forecasting, 19: 435 – 451.

[6] Goh, C. & Law, R. (2002). Modeling and forecasting tourism demand for arrivals with stochastic non-stationary seasonality and intervention, Tourism Management, 23: 499 – 510.

[7] Nyoni, T (2018). Modeling Forecasting Naira / USD Exchange Rate in Nigeria: a Box – Jenkins ARIMA approach, University of Munich Library – Munich Personal RePEc Archive (MPRA), Paper No. 88622.

[8] Nyoni, T (2018). Modeling and Forecasting Inflation in Kenya: Recent Insights from ARIMA and GARCH analysis, Dimorian Review, 5 (6): 16 – 40.

[9] Nyoni, T. (2018). Box – Jenkins ARIMA Approach to Predicting net FDI inflows in Zimbabwe, Munich University Library – Munich Personal RePEc Archive (MPRA), Paper No. 87737.

[10] Song, H., Witt, S. F. & Jensen, T. C. (2003b). Tourism forecasting: accuracy of alternative econometric models, International Journal of Forecasting, 19: 123 – 141.

[11] Statistics Botswana (2015). Botswana Population Projections (2011 – 2026), Statistics Botswana, Gaborone.

[12] Tartiyus, E. H., Dauda, T. M., & Peter, A (2015). Impact of population growth on economic growth in Nigeria, IOSR Journal of Humanities and Social Science (IOSR-JHSS), 20 (4): 115 – 123.

[13] Todaro, M & Smith, S (2006). Economic Development, 9th Edition, Vrinda Publications, New Delhi.

[14] United Nations (2015). World Population Prospects: The 2015 Revision, Key Findings and Advance Tables, Department of Economic and Social Affairs, Population Division, Working Paper No. ESA/P/WP/241.

[15] Zakria, M & Muhammad, F (2009). Forecasting the population of Pakistan using ARIMA models, Pakistan Journal of Agricultural Sciences, 46 (3): 214 – 223.