Regional disparities in Serbia

Abstract

demografija i budžetski prihodi. Indikatori su analizirani na sva tri NTSJ nivoa, definisanih Zakonom o regionalnom razvoj, i na lokalnom nivou (opštine i gradovi). U analizi se primenjuje neponderisani Gini indeks regionalnih razlika koji je korišćen za određivanje razlika u okviru svakog posmatranog indikatora. Rezultati analize su prestavljeni u okviru tabela i grafika koji prikazuju promene Gini indeksa tokom godina posmatranja. U radu je pokazano da su najveće regionalne razlike u Srbiji prisutne na lokalnom i na NTSJ 3 nivou. Regionalne razlike na ova dva nivoa su stabilne tokom godina. Sa druge strane, razlike na nivoima NTSJ 1 i NTSJ 2 su takođe velike ali manje nego na nižim teritorijalnim nivoima. Međutim, razlike u ova dva nivoa rastu mnogo brže nego na nižim nivoima. .OMXĉQH UHĉL regionalne razlike, regionalni razvoj, Gini indeks, Srbija $EVWUDFWThe paper presents a legislative and institutional framework of regional development in Serbia, as well as the analysis of regional disparities across different geography, elaborated through six selected indicators: population and population density (analysed as a single indicator), Regional GDP, Employment, Unemployment, Business Demography and Budgetary Revenues per capita. Indicators are analysed at the all three NUTS, as defined by the Law on Regional Development, and at the local level (cities and municipalities). In the analysis, the paper applies the unweighted Gini index of regional disparity that was used in calculating disparities within each observed indicator. The results are presented within the tables and figures that show changes of the Gini index across years of observation. The paper showed that highest regional disparities in Serbia are at the local and NUTS 3 level. Disparities at those two levels are stable across the years. Disparities at NUTS 1 and NUTS 2 levels are also high, yet lower than at the bellow territorial levels (NUTS 3 and the local level). However, disparity at these two levels grows much faster than at the NUTS 3 and local level.

Thinness in young schoolchildren in Serbia: another case of the double burden of malnutrition?

“…Our results confirm that living in an economically disadvantaged region may expose children to a higher risk of being thin, since participants from economically disadvantaged South Serbia were more likely to be underweight than their counterparts from the North region. Regional disparities in Serbia have increased significantly during the socio-economic transition, resulting in a North–South divide ( 28 ) . Furthermore, it turned out that school health education programmes might have a protective effect in terms of thinness prevalence, probably by teaching children about healthy lifestyle behaviours, including diet.…”

Regional inequalities in the Visegrad Group countries, Serbia and Croatia

“…In the case of Serbia and Croatia, the second and third lowest level of inequalities were demonstrated, even after the exclusion of their capitals, their level remained medium. In the case of Serbia, their lower level of inequalities is rather surprising, because a number of authors such as Mijačić and Paunović (2011), Lukić and Stoilković (2017) drew attention to their high rate compared to the other EU countries. The identified inequalities have their grounds in decreased economic efficiency in the northwestern-southeastern direction (in all the indicators), which is consistent with the works by Mijačić and Paunović (2011), Jakopin (2014) and Joksimović and Golić (2017).…”

“…In the case of Serbia, their lower level of inequalities is rather surprising, because a number of authors such as Mijačić and Paunović (2011), Lukić and Stoilković (2017) drew attention to their high rate compared to the other EU countries. The identified inequalities have their grounds in decreased economic efficiency in the northwestern-southeastern direction (in all the indicators), which is consistent with the works by Mijačić and Paunović (2011), Jakopin (2014) and Joksimović and Golić (2017). This originated in the late transformation process in the country (Winkler, 2012), unfavourable demographic trends, small scale industrial production, high unemployment rate and inadequate infrastructure (Joksimović & Golić, 2017) which manifested itself in the higher poverty risk rate in Europe (24.3%) as well as in the low Competitiveness Index Europe 2020 (Jakopin, 2014).…”

Social, Economic, Fishery and Conservational Issues Featuring Fly Fishing Community in Serbia

“…They reside in large municipalities of Belgrade and Niš and in the Vojvodina Province, which are the regions of Serbia with the highest level of economic activity. In 2009, according to Mijačić and Paunović (2011), regional disparities in Serbia were among the largest in Europe. If the national average was considered to be 100, regional GDP per capita in Belgrade was 179.4, in Vojvodina 95.2, in Central and Western Serbia 71.4, and in Southern and Eastern Serbia 63.3 (records for Kosovo and Metochia are not available).…”