Detection and Forecasting of Islamic Calendar Effects in Time series Data

Riaz Riazuddin (riaz.riazuddin@sbp.org.pk) and Mahmood ul Hasan Khan (mahmood.khan@sbp.org.pk)
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Riaz Riazuddin: State Bank of Pakistan
Mahmood ul Hasan Khan: State Bank of Pakistan

No 2, SBP Working Paper Series from State Bank of Pakistan, Research Department

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.

Keywords: Forecasting; time-series data (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2002-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Published in SBP Research Bulletin, Volume 1, Number 1, 2005, pages 25-34

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