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Detection and Forecasting of Islamic Calendar Effects in Time series Data

Author

Listed:
  • Riaz Riazuddin

    () (State Bank of Pakistan)

  • Mahmood ul Hasan Khan

    () (State Bank of Pakistan)

Abstract

Detection of calendar and seasonal effects in time series data is a well-developed field in statistics and its importance can hardly be over emphasized. As the behavior of Islamic societies incorporates seasonal effects of both Gregorian and Islamic calendars, therefore the conventional seasonal adjustment methods will yield distorted results. In this paper we extend the standard ARIMA modeling to incorporate Islamic calendar effects. This methodology is applied to the monthly data of currency in circulation. The presence of Islamic calendar effects is strongly pronounced by the results. These results are extremely useful for policy makers of the central banks in tracking the path of currency in circulation. Furthermore, this methodology is of vital use for computing seasonal adjusted series and factors in Islamic countries.

Suggested Citation

  • Riaz Riazuddin & Mahmood ul Hasan Khan, 2002. "Detection and Forecasting of Islamic Calendar Effects in Time series Data," SBP Working Paper Series 02, State Bank of Pakistan, Research Department.
  • Handle: RePEc:sbp:wpaper:02
    as

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    File URL: http://www.sbp.org.pk/repec/sbp/wpaper/wp02.pdf
    File Function: First version, 2002
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    References listed on IDEAS

    as
    1. Halvorsen, Robert & Palmquist, Raymond, 1980. "The Interpretation of Dummy Variables in Semilogarithmic Equations," American Economic Review, American Economic Association, vol. 70(3), pages 474-475, June.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Madhavi Bokil & Axel Schimmelpfennig, 2006. "Three Attempts at Inflation Forecasting in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 45(3), pages 341-368.
    2. Riaz Riazuddin, 2012. "Construction and Seasonal Patterns of Islamic Hijri Calendar Monthly Time Series: An Application to Consumer Price Index (CPI) in Pakistan," SBP Working Paper Series 50, State Bank of Pakistan, Research Department.
    3. Bukhari, Syed Kalim Hyder & Abdul, Jalil & Rao, Nasir Hamid, 2011. "Detection and Forecasting of Islamic Calendar Effects in Time Series Data: Revisited," MPRA Paper 31124, University Library of Munich, Germany.
    4. Riaz Riazuddin, 2012. "Construction and Seasonal Patterns of Islamic Hijri Calendar Monthly Time Series: An Application to Consumer Price Index (CPI) in Pakistan," Working Papers id:4927, eSocialSciences.

    More about this item

    Keywords

    Forecasting; time-series data;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • 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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