Advanced Search
MyIDEAS: Login

Modelling Economic Potential of the Region (Zaporizhia Oblast Example)

Contents:

Author Info

  • Krymska Liubov O.

    ()
    (Zaporizhzhya National Technical University)

  • Popova Marharyta V.

    ()
    (Zaporizhzhya National Technical University)

Registered author(s):

    Abstract

    The article shows methodological grounds of construction of the model of economic potential of the region and selects indicators of main structure forming elements of economic potential on the basis of the resource approach to its determination, which could be used for construction of a mathematical model and also for assessment of economic potential. The article considers methods of construction of a mathematical model of economic potential of the region on the basis of the correlation and regression analysis and method of construction of neural networks. It develops a model of economic potential of the Zaporizhia oblast on the basis of construction of a neural network with the use of the Deductor Studio Academic software. The considered methods of construction of the model of economic potential could be used for construction of models of potential of other oblasts. Such models could be used for assessment of influence of each of indicators of structure forming components of economic potential upon the value of the gross regional product, short-term and medium-term forecasting of development of the region, development of programmes of regional development by local bodies of authority and identification of maximally possible gross regional product under condition of use of the whole available volume of resources.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.business-inform.net/pdf/2014/2_0/122_127.pdf
    Download Restriction: no

    Bibliographic Info

    Article provided by RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE), Kharkiv National University of Economics in its journal Business Inform.

    Volume (Year): (2014)
    Issue (Month): 2 ()
    Pages: 122_127

    as in new window
    Handle: RePEc:idp:bizinf:y:2014:i:2:p:122_127

    Contact details of provider:
    Web page: http://www.business-inform.net

    Related research

    Keywords: economic potential; indicators of structural components of economic potential; model; multiple regression; neural network;

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:idp:bizinf:y:2014:i:2:p:122_127. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alexey Rystenko).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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