Iztok Podbregar (Author), Goran Šimić (Author), Mirjana Radovanović (Author), Sanja Filipović (Author), Polona Šprajc (Author)

Abstract

The main objective of this paper is to analyze model settings of the International Energy Security Risk Index developed by the U.S. Chamber of Commerce. The study was performed using stepwise regression, principal component analysis, and Promax oblique rotation. The conclusion of the regression analysis shows that Crude Oil Price and Global Coal Reserves are sufficient to explain 90% of the variance of the Index. However, if a model that explains 100% of the variance of the Index is chosen and other variables are added, Global Coal Reserves loses importance due to the presence of other parameters in which it is contained. Regardless of the chosen model of analysis, it is evident that there is room for revising the Index and removing variables that do not contribute to its precision. The research showed that the main disadvantage of the variables that make up the Index rests with the fact that the variables are of different degrees of generality, that is, one parameter is contained in other parameters (unclear which other). The research covers data for 25 countries over a 26-year period, with the first year of the research being 1980 and the last 2016 (the latest available report).

Keywords

indeks tveganja mednarodne energetske varnosti;analiza;stopenjska regresija;analiza glavnih komponent;international energy security risk index;analysis;stepwise regression;principal component analysis;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UM FOV - Faculty of Organizational Sciences
Publisher: MDPI
UDC: 351
COBISS: 20478979 Link will open in a new window
ISSN: 1996-1073
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Other data

Secondary language: Slovenian
Secondary keywords: indeks tveganja mednarodne energetske varnosti;analiza;stopenjska regresija;analiza glavnih komponent;
Type (COBISS): Scientific work
Pages: str. 1-15
Volume: ǂVol. ǂ13
Issue: ǂiss. ǂ12 (3234)
Chronology: 2020
DOI: 10.3390/en13123234
ID: 25839035