IDEAS home Printed from https://ideas.repec.org/a/bla/ecinqu/v51y2013i1p707-721.html
   My bibliography  Save this article

Common Drivers Of Transnational Terrorism: Principal Component Analysis

Author

Listed:
  • GAIBULLOEV KHUSRAV
  • SANDLER TODD
  • SUL DONGGYU

Abstract

No abstract is available for this item.

Suggested Citation

  • Gaibulloev Khusrav & Sandler Todd & Sul Donggyu, 2013. "Common Drivers Of Transnational Terrorism: Principal Component Analysis," Economic Inquiry, Western Economic Association International, vol. 51(1), pages 707-721, January.
    • Handle: RePEc:bla:ecinqu:v:51:y:2013:i:1:p:707-721
    DOI: j.1465-7295.2012.00469.x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1465-7295.2012.00469.x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/j.1465-7295.2012.00469.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Georges Harb, 2019. "The impact of terrorism on inbound tourism: disentangling the cross-spatial correlation," Economics Bulletin, AccessEcon, vol. 39(1), pages 686-700.
    2. Maclean, Johanna Catherine & Popovici, Ioana & French, Michael T., 2016. "Are natural disasters in early childhood associated with mental health and substance use disorders as an adult?," Social Science & Medicine, Elsevier, vol. 151(C), pages 78-91.
    3. Serhan Cevik & John Ricco, 2020. "Shock and awe? Fiscal consequences of terrorism," Empirical Economics, Springer, vol. 58(2), pages 723-748, February.
    4. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
    5. George Kapetanios & M. Hashem Pesaran & Simon Reese, 2018. "A Residual-based Threshold Method for Detection of Units that are Too Big to Fail in Large Factor Models," CESifo Working Paper Series 7401, CESifo.
    6. Khusrav Gaibulloev & Todd Sandler & Donggyu Sul, "undated". "Reevaluating Terrorism and Economic Growth: Dynamic Panel Analysis and Cross-Sectional Dependence," Economics Working Papers 02-03/2013, School of Business Administration, American University of Sharjah.
    7. Kapetanios, G. & Pesaran, M.H. & Reese, S., 2021. "Detection of units with pervasive effects in large panel data models," Journal of Econometrics, Elsevier, vol. 221(2), pages 510-541.

    More about this item

    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:bla:ecinqu:v:51:y:2013:i:1:p:707-721. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/weaaaea.html .

    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.