NYONI, THABANI (2019): Can Algeria be the first African country to outsmart the Malthusian population trap? Insights from the ARIMA approach.
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Abstract
Using annual time series data on total population in Algeria from 1960 to 2017, we 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 Algeria annual total population is I (2). Based on the AIC, the study presents the ARIMA (4, 2, 0) model as the optimal model. The diagnostic tests further show that the presented model is stable and that its residuals are integrated of order zero. The results of the study reveal that total population in Algeria will continue to rise gradually in the next three decades and in 2050 Algeria’s total population will be approximately 62 million people. In order to outsmart the Malthusian population trap, 4 policy prescriptions have been suggested for consideration by the government of Algeria.
Item Type: | MPRA Paper |
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Original Title: | Can Algeria be the first African country to outsmart the Malthusian population trap? Insights from the ARIMA approach |
Language: | English |
Keywords: | Algeria; 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 |
Item ID: | 92425 |
Depositing User: | MR. THABANI NYONI |
Date Deposited: | 01 Mar 2019 18:55 |
Last Modified: | 30 Sep 2019 21:11 |
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 & Bonga, W. G (2017). Population growth in Zimbabwe: A Threat to Economic Development? DRJ – Journal of Economics and Finance, 2 (6): 29 – 39. [8] Nyoni, T (2018). Modeling and Forecasting Naira / USD Exchange Rate in Nigeria: a Box – Jenkins ARIMA approach, University of Munich Library – Munich Personal RePEc Archive (MPRA), Paper No. 88622. [9] Nyoni, T (2018). Modeling and Forecasting Inflation in Kenya: Recent Insights from ARIMA and GARCH analysis, Dimorian Review, 5 (6): 16 – 40. [10] 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. [11] Song, H., Witt, S. F. & Jensen, T. C. (2003b). Tourism forecasting: accuracy of alternative econometric models, International Journal of Forecasting, 19: 123 – 141. [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. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/92425 |