Economics at your fingertips  

Statistical detection and classification of background risks affecting inputs and outputs

Nadezhda Gribkova () and Ričardas Zitikis ()
Additional contact information
Nadezhda Gribkova: Saint Petersburg State University
Ričardas Zitikis: Western University

METRON, 2019, vol. 77, issue 1, 1-18

Abstract: Abstract Systems are exposed to a variety of risks, including those known as background or systematic risks. Therefore, advanced economic, financial, and engineering models incorporate such risks, thus inevitably making the models more challenging to explore. A number of natural questions arise. First and foremost, is the given system affected by any of such risks? If so, then is the system affected by the risks at the input or output stage, or at both stages? In the present paper we construct an algorithm that answers such questions. Even though the algorithm is based on intricate probabilistic considerations, its practical implementation is easy.

Keywords: Input; Output; Background risk; Gini index; Statistical model (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from

DOI: 10.1007/s40300-019-00148-3

Access Statistics for this article

METRON is currently edited by Marco Alfo'

More articles in METRON from Springer, Sapienza Università di Roma
Bibliographic data for series maintained by Sonal Shukla ().

Page updated 2020-05-02
Handle: RePEc:spr:metron:v:77:y:2019:i:1:d:10.1007_s40300-019-00148-3