IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02332090.html

Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries

Author

Listed:
  • Roman Matkovskyy

    (Rennes SB - Rennes School of Business)

Abstract

This paper considers the application of copula models to study the shifts in extremaleconomic dependence of the Eastern European countries, i.e., Ukraine and its neigh-bouring countries, from 1969 to 2014. Extremal economic dependence is analysed interms of poverty and affluence and with regard to growth rate. This paper contributes tothe previous literature by applying the copula approaches to derive the measurementsof the economic interdependence in terms of poverty and affluence. The receivedresults depict the pattern of the (inter)dependence and its evolution across the anal-ysed countries. Dependence on other countries in the extreme values can potentiallybe useful in adjustments of the economic policy of a country to minimize poverty andprevent high inequality.

Suggested Citation

  • Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
  • Handle: RePEc:hal:journl:hal-02332090
    DOI: 10.1007/s40953-018-0151-6
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Jalan, Akanksha & Matkovskyy, Roman & Yarovaya, Larisa, 2021. "“Shiny” crypto assets: A systemic look at gold-backed cryptocurrencies during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 78(C).
    2. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    3. Roman Matkovskyy, 2020. "A measurement of affluence and poverty interdependence across countries: Evidence from the application of tail copula," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 404-416, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:hal:journl:hal-02332090. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.