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Detecting Islamic Calendar Effects on U.S. Meat Consumption: Is the Muslim Population Larger than Widely Assumed?

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  • Moayedi, Vafa

Abstract

By employing a parsimonious econometric approach, based on an ARIMA model, this study detects significant Islamic calendar effects on U.S. meat consumption. This surprising finding strengthens the assumption that the size of the Muslim community is considerably larger than assumed by U.S. authorities and NGOs. This study fills a gap in the existing literature which has not addressed this issue with such an approach before. Furthermore, this study suggests considering Islamic festivities for the seasonal adjustment of U.S. time series data.

Suggested Citation

  • Moayedi, Vafa, 2012. "Detecting Islamic Calendar Effects on U.S. Meat Consumption: Is the Muslim Population Larger than Widely Assumed?," MPRA Paper 41554, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:41554
    as

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    File URL: https://mpra.ub.uni-muenchen.de/41554/1/MPRA_paper_41554.pdf
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    References listed on IDEAS

    as
    1. Domenico Depalo, 2009. "A seasonal unit-root test with Stata," Stata Journal, StataCorp LP, vol. 9(3), pages 422-438, September.
    2. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    3. Bonato Leo, 2008. "Money and Inflation in the Islamic Republic of Iran," Review of Middle East Economics and Finance, De Gruyter, vol. 4(1), pages 41-58, January.
    4. Yucel, Eray M., 2005. "Does Ramadan Have Any Effect on Food Prices: A Dual-Calendar Perspective on the Turkish Data," MPRA Paper 1141, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    ARIMA; Calendar Effects; Islamic Festivities; Muslims; Seasonal Adjustment;

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • 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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