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Identifying good inflation forecaster

Author

Listed:
  • Duasa, Jarita
  • Ahmad, Nursilah

Abstract

The objective of this paper is to identify the best indicator variable in forecasting inflation in Malaysia. Due to the fact that Malaysia experienced the rise of CPI by 4.8 percent in March 2006, the country’s highest inflation rate in seven years, there is a need to foresee future trend of general price level. To determine whether certain indicator (variable) could predict inflation, we construct a simple forecasting model that incorporates the variable. We estimate a two-variable VECM model of quasi-tradable inflation using monthly data covering the period 1980:01 to 2006:12. We alternate between the following inflation indicators: commodity prices, financial indicators and economic activities. We evaluate each model using out-of-sample forecast. The study proposes that a simple model using industrial production index improves the accuracy of inflation forecasts. The results support our hypothesis.

Suggested Citation

  • Duasa, Jarita & Ahmad, Nursilah, 2008. "Identifying good inflation forecaster," MPRA Paper 13302, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:13302
    as

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    File URL: https://mpra.ub.uni-muenchen.de/13302/1/MPRA_paper_13302.pdf
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    References listed on IDEAS

    as
    1. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    2. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    3. Michael F. Bryan & Stephen G. Cecchetti, 1993. "The consumer price index as a measure of inflation," Economic Review, Federal Reserve Bank of Cleveland, issue Q IV, pages 15-24.
    4. Jonas D. M. Fisher, 2000. "Forecasting inflation with a lot of data," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue Mar.
    5. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Goods inflation; VECM ; Malaysian economy;

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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