KLJUČNE REČI: REGIONALNI RAZVOJ, DEMOGRAFIJA, MIGRACIJE, NUTS 3, SRBIJA KEYWORDS: REGIONAL DEVELOPMENT, DEMOGRAPHY, MIGRATION, NUTS 3, SERBIA application/pdf 380312 bytes Ekonomske ideje i praksa number: 53 startpage: 45 endpage: 61 SOCIOEKONOMSKI I MIGRATORNI PROFILI NUTS 3 OBLASTI U SRBIJI info:eu-repo/semantics/article 2024 http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode https://phaidrabg.bg.ac.rs/o:35851 doi:10.54318/eip.2024.mj.373 ISSN: 2217-6217 srp Jandrić, Maja Molnar, Dejan Tansković, Svetozar APSTRAKT: Cilj ovog rada je analiza osnovnih socioekonomskih i migratornih obeležja pojedinih NUTS 3 oblasti u Srbiji i utvrđivanje grupa sa sličnim karakteristikama. U analizu je uključen veliki broj ekonomskih i demografskih pokazatelja koji se odnose na pojedine oblasti, kao i njihove performanse po pitanju internih i eksternih migracija. Primenom analize glavnih komponenata (engl. Principal Component Analysis − PCA), socioekonomska obeležja su podeljena u dve grupe (dva faktora): elemente koji upućuju na razvijenost i one koji ukazuju na demografsku sliku oblasti. U narednom koraku je izvršena klaster analiza koja je pokazala da postoje tri relativno homogene grupe oblasti. Kako bi se prevazišli nedostaci K-means metoda grupisanja, primenjen je LCCA (engl. Latent Class Cluster Analysis) metod, koji je potvrdio postojanje tri grupe na nivou NUTS 3 oblasti: Beogradska i Južnobačka oblast se ističu kao oblasti sa višim nivoom razvoja i boljim pokazateljima internih i eksternih migracija; Pomoravska, Borska i Braničevska oblast imaju najlošiju poziciju po pitanju eksternih migracija, dok sve ostale oblasti pripadaju trećem klasteru. ABSTRACT: The aim of this paper is to analyse the basic socioeconomic and migration characteristics of NUTS 3 units in Serbia and to determine groups of units with similar characteristics. The analysis includes a large number of demographic and economic indicators of NUTS 3 units, as well as their performance in terms of internal and external migration. By applying the principal components analysis (PCA), socioeconomic indicators are divided into two groups (factors): elements that indicate the development level and elements that indicate the demographic picture of the area. In the next step, a cluster analysis was performed, which showed that there are three relatively homogenous groups of NUTS 3 units. In order to overcome the shortcomings of the K-means grouping method, LCCA (Latent Class Cluster Analysis) was applied, which confirmed the existence of three groups within the NUTS 3 units: Belgrade and South Bačka districts stand out as areas with higher level of development and better indicators of internal and external migration; Pomoravski, Borski and Braničevski districts have the worst position in terms of external migration, while all other areas belong to the third cluster.