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The Changing Geopolitics in the Arab World: Implications of the 2017 Gulf Crisis for Business

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Listed:
  • Jamal Bouoiyour

    (CATT, IRMAPE)

  • Refk Selmi

    (CATT, IRMAPE)

Abstract

The international community was caught by surprise on 5 June 2017 when Saudi Arabia, the United Arab Emirates (UAE), Bahrain and Egypt severed diplomatic ties with Qatar, accusing it of destabilizing the region. More than one year after this diplomatic rift, several questions remain unaddressed. This study focuses on the regional business costs of the year-long blockade on Qatar. We split the sample to compare the stock market performances of Qatar and its Middle Eastern neighbors before and after the Saudi-led Qatar boycott. We focus our attention on the conditional volatility process of stock market returns and risks related to financial interconnectedness. We show that the Gulf crisis had the most adverse impact on Qatar together with Saudi Arabia and the UAE. Although not to the same degree as these three countries, Bahrain and Egypt were also harmfully affected. But shocks to the volatility process tend to have short-lasting effects. Moreover, the total volatility spillovers to and from others increase but moderately after the blockade. Overall, the quartet lobbying efforts did not achieve the intended result. Our findings underscore Qatar's economic vulnerability but also the successful resilience strategy of this tiny state. The coordinated diplomatic efforts of Qatar have been able to fight the economic and political embargo.

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  • Jamal Bouoiyour & Refk Selmi, 2019. "The Changing Geopolitics in the Arab World: Implications of the 2017 Gulf Crisis for Business," Papers 1903.08076, arXiv.org.
  • Handle: RePEc:arx:papers:1903.08076
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    1. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Historical Episodes Of Exuberance And Collapse In The S&P 500," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1043-1078, November.
    2. Bollerslev, Tim & Engle, Robert F, 1993. "Common Persistence in Conditional Variances," Econometrica, Econometric Society, vol. 61(1), pages 167-186, January.
    3. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    4. Omar, Ayman M.A. & Wisniewski, Tomasz Piotr & Nolte, Sandra, 2017. "Diversifying away the risk of war and cross-border political crisis," Energy Economics, Elsevier, vol. 64(C), pages 494-510.
    5. Geoffrey P. Miller & Fabrizio Cafaggi, 2013. "The Governance and Regulation of International Finance," Books, Edward Elgar Publishing, number 14682.
    6. Luis Alberiko & OlaOluwa S. Yaya & Olarenwaju I. Shittu, 2015. "Fractional integration and asymmetric volatility in european, asian and american bull and bear markets. Applications to high frequency stock data," NCID Working Papers 07/2015, Navarra Center for International Development, University of Navarra.
    7. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    8. Massimo Guidolin & Eliana La Ferrara, 2010. "The economic effects of violent conflict: Evidence from asset market reactions," Journal of Peace Research, Peace Research Institute Oslo, vol. 47(6), pages 671-684, November.
    9. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    10. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    11. Peter C. B. Phillips & Yangru Wu & Jun Yu, 2011. "EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 201-226, February.
    12. Antonakakis, Nikolaos & Gupta, Rangan & Kollias, Christos & Papadamou, Stephanos, 2017. "Geopolitical risks and the oil-stock nexus over 1899–2016," Finance Research Letters, Elsevier, vol. 23(C), pages 165-173.
    13. Bouoiyour, Jamal & Selmi, Refk & Wohar, Mark E., 2018. "Measuring the response of gold prices to uncertainty: An analysis beyond the mean," Economic Modelling, Elsevier, vol. 75(C), pages 105-116.
    14. Balcilar, Mehmet & Gupta, Rangan & Pierdzioch, Christian, 2016. "Does uncertainty move the gold price? New evidence from a nonparametric causality-in-quantiles test," Resources Policy, Elsevier, vol. 49(C), pages 74-80.
    15. Christos Kollias & Stephanos Papadamou & Vangelis Arvanitis, 2013. "Symposium - Does Terrorism Affect the Stock-Bond Covariance? Evidence from European Countries," Southern Economic Journal, John Wiley & Sons, vol. 79(4), pages 832-848, April.
    16. Gil-Alana, Luis A. & Shittu, Olanrewaju I. & Yaya, OlaOluwa S., 2014. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 149-162.
    17. Faheem Aslam & Hyoung-Goo Kang, 2015. "How Different Terrorist Attacks Affect Stock Markets," Defence and Peace Economics, Taylor & Francis Journals, vol. 26(6), pages 634-648, December.
    18. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    19. Choudhry, Taufiq, 2010. "World War II events and the Dow Jones industrial index," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1022-1031, May.
    20. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    21. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    1. Tarek Ben Hassen & Hamid El Bilali & Mohammed Al-Maadeed, 2020. "Agri-Food Markets in Qatar: Drivers, Trends, and Policy Responses," Sustainability, MDPI, vol. 12(9), pages 1-31, May.
    2. Buigut, Steven & Kapar, Burcu, 2020. "Effect of Qatar diplomatic and economic isolation on GCC stock markets: An event study approach," Finance Research Letters, Elsevier, vol. 37(C).
    3. Charfeddine, Lanouar & Al Refai, Hisham, 2019. "Political tensions, stock market dependence and volatility spillover: Evidence from the recent intra-GCC crises," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    4. Jamal Bouoiyour & Refk Selmi, 2018. "The gruesome murder of Jamal Khashoggi : Saudi Arabia's new economy dream at risk ?," Working Papers hal-01965085, HAL.

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