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Predicting CPI in Singapore: An application of the Box-Jenkins methodology

Author

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  • NYONI, THABANI

Abstract

This research uses annual time series data on CPI in Singapore from 1960 to 2017, to model and forecast CPI using the Box – Jenkins ARIMA technique. Diagnostic tests indicate that the S series is I (1). The study presents the ARIMA (1, 1, 2) model for predicting CPI in Singapore. The diagnostic tests further show that the presented optimal model is actually stable and acceptable. The results of the study apparently show that CPI in Singapore is likely to continue on an upwards trajectory in the next decade. The study basically encourages policy makers to make use of tight monetary and fiscal policy measures in order to control inflation in Singapore.

Suggested Citation

  • Nyoni, Thabani, 2019. "Predicting CPI in Singapore: An application of the Box-Jenkins methodology," MPRA Paper 92413, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:92413
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    References listed on IDEAS

    as
    1. Subhani, Muhammad Imtiaz, 2009. "Relationship between Consumer Price Index (CPI) and Government Bonds," MPRA Paper 36161, University Library of Munich, Germany.
    2. Meyler, Aidan & Kenny, Geoff & Quinn, Terry, 1998. "Forecasting irish inflation using ARIMA models," MPRA Paper 11359, University Library of Munich, Germany.
    3. Anders Bredahl Kock & Timo Teräsvirta, 2013. "Forecasting the Finnish Consumer Price Inflation Using Artificial Neural Network Models and Three Automated Model Selection Techniques," Finnish Economic Papers, Finnish Economic Association, vol. 26(1), pages 13-24, Spring.
    4. Michael J. Boskin, 1998. "Consumer Prices, the Consumer Price Index, and the Cost of Living," Journal of Economic Perspectives, American Economic Association, vol. 12(1), pages 3-26, Winter.
    5. Muhammad Imtiaz Subhani & Kiran Panjwani & Amber Osman, 2009. "Relationship between Consumer Price Index (CPI) and Government Bonds," South Asian Journal of Management Sciences (SAJMS), Iqra University, Iqra University, vol. 3(1), pages 11-14, Spring.
    6. Nyoni, Thabani, 2018. "Box-Jenkins ARIMA approach to predicting net FDI inflows in Zimbabwe," MPRA Paper 87737, University Library of Munich, Germany.
    7. McAdam, Peter & McNelis, Paul, 2005. "Forecasting inflation with thick models and neural networks," Economic Modelling, Elsevier, vol. 22(5), pages 848-867, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Forecasting; Inflation; Singapore;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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