Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/13836
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Andreou, Andreas S. | - |
dc.contributor.author | Zombanakis, G. A. | - |
dc.contributor.other | Ανδρέου, Ανδρέας Σ. | - |
dc.date.accessioned | 2019-05-31T06:31:59Z | - |
dc.date.available | 2019-05-31T06:31:59Z | - |
dc.date.issued | 2000-02-01 | - |
dc.identifier.citation | Defence and Peace Economics, 2000, vol. 11, no. 4, pp. 403-426. | en_US |
dc.identifier.issn | 1024-2694 | - |
dc.description.abstract | This paper aims at forecasting the burden on the Greek economy resulting from the arms race against Turkey and at concentrating on the leading determinants of this burden. The military debt and the defence share of GDP are employed alternatively in order to approximate the measurement of the arms race pressure on Greece, and the method used is that of artificial neural networks. The use of a wide variety of explanatory variables in combination with the promising results derived, suggest that the impact on the Greek economy resulting from this arms race is determined, to a large extent, by demographic factors which strongly favour the Turkish side. Prediction on both miltary debt and defence expenditure exhibited highly satisfactory accuracy, while the estimation of input significance, indicates that variables describing the Turkish side are often dominant over the corresponding Greek ones. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.relation.ispartof | Defence and Peace Economics | en_US |
dc.rights | ©Τaylor and francis group | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Defence expenditure | en_US |
dc.subject | Greek military debt | en_US |
dc.subject | Neural networks | en_US |
dc.title | Financial versus human resources in the Greek-Turkish arms race: A forecasting investigation using artificial neural networks | en_US |
dc.type | Article | en_US |
dc.collaboration | University of Patras | en_US |
dc.collaboration | Bank of Greece | en_US |
dc.subject.category | Electrical Engineering - Electronic Engineering - Information Engineering | en_US |
dc.journals | Open Access | en_US |
dc.country | Greece | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1080/10430710008404956 | en_US |
dc.identifier.scopus | 2-s2.0-0000762060 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/0000762060 | en |
dc.contributor.orcid | #NODATA# | en |
dc.contributor.orcid | #NODATA# | en |
dc.relation.issue | 4 | en_US |
dc.relation.volume | 11 | en_US |
cut.common.academicyear | 2000-2001 | en_US |
dc.identifier.spage | 403 | en_US |
dc.identifier.epage | 426 | en_US |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.fulltext | No Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairetype | article | - |
crisitem.journal.journalissn | 1476-8267 | - |
crisitem.journal.publisher | Taylor & Francis | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0001-7104-2097 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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