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Modeling and forecasting CPI in Iran: A univariate analysis

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  • NYONI, THABANI

Abstract

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

Suggested Citation

  • Nyoni, Thabani, 2019. "Modeling and forecasting CPI in Iran: A univariate analysis," MPRA Paper 92454, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:92454
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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. 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.
    4. Mosayeb PAHLAVANI & Mohammad RAHIMI, 2009. "Sources of Inflation in Iran: An application of the ARDL Approach," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 9(1).
    5. 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.
    6. 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.
    7. Nyoni, Thabani, 2018. "Box-Jenkins ARIMA approach to predicting net FDI inflows in Zimbabwe," MPRA Paper 87737, University Library of Munich, Germany.
    8. Nyoni, Thabani, 2018. "Modeling and Forecasting Inflation in Zimbabwe: a Generalized Autoregressive Conditionally Heteroskedastic (GARCH) approach," MPRA Paper 88132, University Library of Munich, Germany.
    9. McAdam, Peter & McNelis, Paul, 2005. "Forecasting inflation with thick models and neural networks," Economic Modelling, Elsevier, vol. 22(5), pages 848-867, September.
    10. Abdolnaser Hemmati & Leili Niakan & Vida Varahrami, 2018. "The External Determinants of Inflation: The Case of Iran," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 22(3), pages 745-756, Summer.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Forecasting; Iran; inflation;
    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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