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Modeling and forecasting CPI in Myanmar: An application of ARIMA models

Author

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  • NYONI, THABANI

Abstract

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

Suggested Citation

  • Nyoni, Thabani, 2019. "Modeling and forecasting CPI in Myanmar: An application of ARIMA models," MPRA Paper 92420, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:92420
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    References listed on IDEAS

    as
    1. Marcos Álvarez-Díaz & Rangan Gupta, 2015. "Forecasting the US CPI: Does Nonlinearity Matter?," Working Papers 201512, University of Pretoria, Department of Economics.
    2. Subhani, Muhammad Imtiaz, 2009. "Relationship between Consumer Price Index (CPI) and Government Bonds," MPRA Paper 36161, University Library of Munich, Germany.
    3. 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.
    4. 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.
    5. Nyoni, Thabani, 2018. "Box-Jenkins ARIMA approach to predicting net FDI inflows in Zimbabwe," MPRA Paper 87737, University Library of Munich, Germany.
    6. 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; Myanmar;
    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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