IDEAS home Printed from https://ideas.repec.org/a/scn/00rbes/y2017i4p22-36.html
   My bibliography  Save this article

Применение многомерного статистического анализа для конструкции предупреждающих прогнозов // Implementation of Multivariate Statistical Analysis for Warning Forecasting

Author

Listed:
  • Z. Mierzwa

    (Financial University)

  • З. Межва

    (Финансовый университет)

Abstract

Traditionally, for the purposes of forecasting socio-economic phenomena are used econometric methods (methods). Much less frequently for these purposes, we used the methods of multidimensional comparative analysis, including the Wroclaw method of taxonomy. This methodology allows not only classifying the analyzed objects, such as countries or regions but also, taking into account time, to determine the trajectory of the actual development. By modeling the numerical values of variables one can determine a desired or optimal path of development. The third method of application of Wroclaw taxonomy is a ranking of the studied objects about the level of development. The article presents the fundamentals of the Wroclaw taxonomy and basic methodological issues that arise in its application. Традиционно для целей прогнозирования социально-экономических явлений используются эконометрические методы (модели). Значительно реже для этих целей применялись методы многомерного сравнительного анализа, в том числе метод Вроцлавской таксономии. Эта методология позволяет не только классифицировать исследуемые объекты, например страны или регионы, но также, с учетом времени, определять траекторию фактического развития. Путем моделирования числовых значений переменных можно определить желаемую или оптимальную траекторию развития. Третьим способом применения Вроцлавской таксономии является ранжирование исследуемых объектов по уровню развития. В статье представлены основы Вроцлавской таксономии и основные методологические вопросы, возникающие при ее применении.

Suggested Citation

  • Z. Mierzwa & З. Межва, 2017. "Применение многомерного статистического анализа для конструкции предупреждающих прогнозов // Implementation of Multivariate Statistical Analysis for Warning Forecasting," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 5(4), pages 22-36.
  • Handle: RePEc:scn:00rbes:y:2017:i:4:p:22-36
    as

    Download full text from publisher

    File URL: https://rbes.fa.ru/jour/article/viewFile/70/70.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Agata Mesjasz-Lech, 2010. "A Comparative Analysis Of The Development Of Sustainable Energetic Resources In Poland With Relation To Other Eu Countries," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 4(1), pages 170-180, December.
    2. Barbara Jurkowska, 2014. "The Federal States Of Germany – Analysis And Measurement Of Development Using Taxo-Nomic Methods," Oeconomia Copernicana, Institute of Economic Research, vol. 5(3), pages 49-73, September.
    Full references (including those not matched with items on IDEAS)

    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. Adam P. Balcerzak, 2016. "Technological Potential of European Economy. Proposition of Measurement with Application of Multiple Criteria Decision Analysis," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 12(3), pages 7-17.
    2. Anna Tatarczak & Oleksandra Boichuk, 2018. "The multivariate techniques in evaluation of unemployment analysis of Polish regions," Oeconomia Copernicana, Institute of Economic Research, vol. 9(3), pages 361-380, September.

    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:scn:00rbes:y:2017:i:4:p:22-36. 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: Алексей Скалабан (email available below). General contact details of provider: http://rbes.fa.ru/ .

    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.