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Detection and Forecasting of Islamic Calendar Effects in Time Series Data: Revisited

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  • Bukhari, Syed Kalim Hyder
  • Abdul, Jalil
  • Rao, Nasir Hamid

Abstract

This paper is an attempt to revisit the pioneering work of Riazuddin and Khan (2002). A complete business cycle has been elapsed (2002-2010) since their study, so there is need to review the results with additional information. This revisited attempt, based on a theoretically specified framework, arrived at similar results and found significant impact of Islamic calendar. The Islamic months of Ramadan and Zilhaj have positive impact on currency holdings and negative impact on deposits. Although stylized facts indicate that consumer prices are significantly higher during Ramadan but econometric investigation rejects the upward exogenous shifts in prices during Ramadan. Therefore, structural relationship analyzed in co-integration framework has shown that inflation is not directly impacted by the Ramadan but indirectly through increase in its determinants. Inflationary tendencies during Ramadan are not due to exogenous increase by producers and retailers but possibly due to demand surge in the wake of redistribution of income. The months of June and December have positive effects on deposits and negative effects on currency in circulation indicating the presence of window dressing. Finally, as seasonal factors have important role in determining economic time series, therefore, ignoring those in monthly time series models will lead to omitted variable bias and inappropriate forecasts.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 31124.

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Date of creation: 15 May 2011
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Publication status: Published in State Bank of Pakistan Working Paper Sereis May 2011.Workin(2011): pp. 1-27
Handle: RePEc:pra:mprapa:31124

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Keywords: currency in circulation; deposits; cointegration; seasonal factors;

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  1. Beaulieu, J Joseph & MacKie-Mason, Jeffrey K & Miron, Jeffrey A, 1992. "Why Do Countries and Industries with Large Seasonal Cycles also Have Large Business Cycles?," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 621-56, May.
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  5. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
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  9. Franses, Philip Hans, 1991. "Seasonality, non-stationarity and the forecasting of monthly time series," International Journal of Forecasting, Elsevier, vol. 7(2), pages 199-208, August.
  10. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
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  12. Abeysinghe, Tilak, 1991. "Inappropriate use of seasonal dummies in regression," Economics Letters, Elsevier, vol. 36(2), pages 175-179, June.
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Cited by:
  1. 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.

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