IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1903.08076.html
   My bibliography  Save this paper

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

Author

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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1903.08076
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Refk Selmi & Jamal Bouoiyour, 2020. "Arab geopolitics in turmoil: Implications of Qatar-Gulf crisis for business," International Economics, CEPII research center, issue 161, pages 100-119.
    2. Bouoiyour, Jamal & Selmi, Refk & Hammoudeh, Shawkat & Wohar, Mark E., 2019. "What are the categories of geopolitical risks that could drive oil prices higher? Acts or threats?," Energy Economics, Elsevier, vol. 84(C).
    3. Rangan Gupta & Mark Wohar, 2019. "The role of monetary policy uncertainty in predicting equity market volatility of the United Kingdom: evidence from over 150 years of data," Economics and Business Letters, Oviedo University Press, vol. 8(3), pages 138-146.
    4. Jamal Bouoiyour & Refk Selmi, 2017. "Ether: Bitcoin's competitor or ally?," Working Papers hal-01567277, HAL.
    5. Selmi, Refk & Bouoiyour, Jamal & Miftah, Amal, 2020. "Oil price jumps and the uncertainty of oil supplies in a geopolitical perspective: The role of OPEC’s spare capacity," International Economics, Elsevier, vol. 164(C), pages 18-35.
    6. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    7. CHIA-LIN CHANG & MICHAEL McALEER & ROENGCHAI TANSUCHAT, 2012. "Modelling Long Memory Volatility In Agricultural Commodity Futures Returns," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 1-27.
    8. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    9. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    10. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    11. Köksal, Bülent, 2009. "A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns," MPRA Paper 30510, University Library of Munich, Germany.
    12. Tae-Hwy Lee & Yong Bao & Burak Saltoğlu, 2007. "Comparing density forecast models Previous versions of this paper have been circulated with the title, 'A Test for Density Forecast Comparison with Applications to Risk Management' since October 2003;," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 203-225.
    13. Carnero, María Ángeles, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. El Jebari, Ouael & Hakmaoui, Abdelati, 2018. "GARCH Family Models vs EWMA: Which is the Best Model to Forecast Volatility of the Moroccan Stock Exchange Market? || Modelos de la familia GARCH vs EWMA: ¿cuál es el mejor modelo para pronosticar la ," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 237-249, Diciembre.
    15. Turgut Kısınbay, 2010. "Predictive ability of asymmetric volatility models at medium-term horizons," Applied Economics, Taylor & Francis Journals, vol. 42(30), pages 3813-3829.
    16. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
    17. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    18. Hatemi-J, Abdulnasser, 2013. "A New Asymmetric GARCH Model: Testing, Estimation and Application," MPRA Paper 45170, University Library of Munich, Germany.
    19. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
    20. Pourkhanali, Armin & Tafakori, Laleh & Bee, Marco, 2023. "Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect," International Review of Financial Analysis, Elsevier, vol. 89(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1903.08076. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.