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Evaluation of Information Content of Economic Variables for Inflation Forecasting in Iran (in Persian)

Author

Listed:
  • Atrianfar, Hamed

    (Iran)

  • Barakchian, Seyed Mahdi

    (Iran)

Abstract

An effective monetray policy requires forecasting inflation accurately. In this paper¡ we examine the information content of a broad range of variables for forecasting inflation over the period 1377-1387. The results show that¡ in general¡ the variables belonging to the price indices group have the most information content. But when forecasting inflation in real time¡ the variables belonging to the national accounts group have the best performance. And¡ in the medium run forecast horizon (three to four quarters ahead)¡ M1 and M2 perform the best. JEL: C53, E31, E37

Suggested Citation

  • Atrianfar, Hamed & Barakchian, Seyed Mahdi, 2011. "Evaluation of Information Content of Economic Variables for Inflation Forecasting in Iran (in Persian)," Journal of Monetary and Banking Research (فصلنامه پژوهش‌های پولی-بانکی), Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 3(8), pages 1-42, September.
    • Handle: RePEc:mbr:jmbres:v:3:y:2011:i:8:p:1-42
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    Citations

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    Cited by:

    1. Hematy , Maryam & Pedram , Mehdi, 2015. "Threshold Effects in Sticky Information Philips Curve: Evidence from Iran," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 10(1), pages 1-23, January.

    More about this item

    Keywords

    Out; of; Sample Forecasting; Inflation Rate; ARDL;
    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

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