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Forecasting the population of Brazil using the Box-Jenkins ARIMA approach

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  • NYONI, THABANI

Abstract

Employing annual time series data on total population in Brazil 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 Brazil annual total population is non-stationary in all levels; for simplicity purposes, the study has assumed that the POP series is I (2). Based on the AIC, the study presents the ARIMA (6, 2, 0) model as the optimal model. The diagnostic tests further indicate that the presented model is stable and that its residuals are stationary. The results of the study reveal that total population in Brazil will continue to rise in the next three decades and in 2050 Brazil’s total population will be approximately 256 million people. Four policy prescriptions have been suggested for consideration by the government of Brazil.

Suggested Citation

  • Nyoni, Thabani, 2019. "Forecasting the population of Brazil using the Box-Jenkins ARIMA approach," MPRA Paper 92437, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:92437
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    File URL: https://mpra.ub.uni-muenchen.de/92437/1/MPRA_paper_92437.pdf
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    References listed on IDEAS

    as
    1. Nyoni, Thabani, 2018. "Box-Jenkins ARIMA approach to predicting net FDI inflows in Zimbabwe," MPRA Paper 87737, University Library of Munich, Germany.
    2. Nyoni, Thabani, 2018. "Modeling and Forecasting Naira / USD Exchange Rate In Nigeria: a Box - Jenkins ARIMA approach," MPRA Paper 88622, University Library of Munich, Germany, revised 19 Aug 2018.
    3. Song, Haiyan & Witt, Stephen F. & Jensen, Thomas C., 2003. "Tourism forecasting: accuracy of alternative econometric models," International Journal of Forecasting, Elsevier, vol. 19(1), pages 123-141.
    4. du Preez, Johann & Witt, Stephen F., 2003. "Univariate versus multivariate time series forecasting: an application to international tourism demand," International Journal of Forecasting, Elsevier, vol. 19(3), pages 435-451.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Brazil; forecasting; population;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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