Pregled bibliografske jedinice broj: 425856
Cluster and Factor Analysis of Structural Economic Indicators for Selected European Countries
Cluster and Factor Analysis of Structural Economic Indicators for Selected European Countries // WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS, 6 (2009), 7; 331-341 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 425856 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Cluster and Factor Analysis of Structural Economic Indicators for Selected European Countries
Autori
Kurnoga Živadinović, Nataša ; Dumičić, Ksenija ; Čeh Časni, Anita
Izvornik
WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS (1109-9526) 6
(2009), 7;
331-341
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Classification; Structural economic indicators; Multivariate methods; Hierarchical cluster analysis; Non-hierarchical cluster analysis; Factor analysis
Sažetak
The last wave of EU enlargement ended on 1st January 2007 with the accession of Romania and Bulgaria. Many countries of the South-Eastern Europe aspire to join the EU. Croatia appears to be the next prospective member, so the aim of this paper was to classify Croatia and EU 27 Member States according to the structural economic indicators. These countries were gathered into homogenous groups in terms of the following structural economic indicators: GDP per capita, total employment rate, comparative price levels, employment rate of older workers, long term unemployment and productivity of national economies expressed in relation to the European Union (EU-27) average. Firstly, the cluster analysis was used on three structural economic indicators: GDP per capita, total employment rate and comparative price levels. The hierarchical cluster analysis and non-hierarchical cluster analysis were applied and gave similar results. The factor analysis was then provided to find out the common factors of six structural economic indicators: GDP per capita, total employment rate, comparative price levels, employment rate of older workers, long term unemployment and productivity of national economies. Two factors were extracted and the factor scores for each observation were calculated. The factor scores were used in further cluster analysis and again similar results of classification was given.
Izvorni jezik
Engleski
Znanstvena područja
Ekonomija
POVEZANOST RADA
Projekti:
067-0161711-2483 - Statističko modeliranje za povećanje konkurentnosti suvremenih organizacija (Dumičić, Ksenija, MZOS ) ( CroRIS)
Ustanove:
Ekonomski fakultet, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus
Uključenost u ostale bibliografske baze podataka::
- INSPEC