Patterns of Regional Development in Serbia: A Multivariate Statistical Analysis
ISSN 0354-8724 (hard copy) | ISSN 1820-7138 (online)
Patterns of Regional Development in Serbia: A Multivariate Statistical Analysis
Čoček LadislavA Received: December 2009 | Revised: February 2010 | Accepted: February 2010
Abstract The primary objective of this paper is to examine patterns of regional development in Serbia and to identify un- derlying geographical factors of these patterns. Principal component analysis is used to reveal the basic dimen- sions of regional differentiation. Its results are described in the context of findings from thematically similar re- search on Central European countries. An area’s position in the national settlement system hierarchy has been identified as the strongest determinant of regional differentiation in Serbia. Other strong patterns seem to be connected with macro-geographical position. Success in economic development is most apparent in regions near the metropolitan area of Belgrade, and the general development level, along with a predisposition for agri- culture, exhibits a strong north-south polarization. Specific attention is directed at demographic development, which is characterized by a west-east gradient. Central patterns of regional differentiation are similar to those uncovered in previous Central European research. Regional policy in Serbia should, therefore, try to learn from experience within this region to cope with processes and problems that are often quite similar. Key words: Multivariate Analysis, Regional Development, Serbia
Introduction development in most post-communist countries In Central, Eastern and South-eastern Europe, of Central Europe are also valid for Serbia. The post-communist transformation has been pro- underlying idea is that core geographical determi- gressing at varying intensity with varying rates of nants are stable and, unless there is a strong force success. Of the countries involved, Serbia was the opposing them – such as communism’s directive last one to begin the transformation process and economic system or another autocracy, outcomes it has done so under difficult political and eco- will be similar and manifest themselves exten- nomic circumstances. While other post-commu- sively as soon as system changes allow them to do nist countries were already knocking on the door so. If this expectation holds true, it would strong- of the European Union (EU), Serbia was strug- ly support a hypothesis describing the transfera- gling to emerge from democratic revolution and bility of foreign experience with regional develop- to apply elementary, market-oriented reforms. Its ment into the Serbian environment. Such findings GDP p.c. was similar to that of Third World coun- could have significant implications for regional tries and its economy and politics were corrupt policy practices. and disorganized. “It is hard to find a society that, This article attempts to offer an overview of ba- in only ten years, could develop such a level of all- sic factors of regional differentiation in Serbia in round backwardness” (Mitrović, 2008, 135). One the broader context of Central and South-east- would expect that these specific conditions would ern Europe. First, contemporary concepts of re- lead to a pattern of regional development distinct gional development research in Central Europe from that of other post-communist countries. and Serbia are evaluated and compared in a the- This paper seeks to demonstrate, primarily on oretical background section. The objective here is a theoretical basis originating from the Czech Re- to present deficiencies in contemporary Serbian public, that, regardless of the specificity of the Ser- regional economic studies. Second, the meth- bian case, the basic factors determining regional odological framework of the paper is summa-
A Department of Social Geography and Regional Development, Faculty of Science, Charles University in Prague, Albertov 6, 128 43 Praha 2, Czech Republic; e-mail: [email protected]
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rized. The primary method employed is princi- Serbia has attempted to verify the applicability of pal component analysis (PCA). The third section, these theoretical presumptions. Therefore, this entitled dimensions of regional development in paper offers new explanatory insight into the re- Serbia, presents the results of the analysis and in- gional differentiation of Serbia. terprets them thoroughly. In the end, conclusions Nevertheless, certain factors must be interpreted are drawn, including practical implications and with caution, with regard for the regional specifics regional perspectives resulting from the research. of Serbia. For example, macro-geographical posi- tion must be carefully explained, making consider- ation for foreign centres of development, due to the Theoretical Background fact that Serbia does not border any region, such as Most research focusing on regional socioeco- Bavaria or Lower Austria for the Czech Republic or nomic differentiation in Serbia, during the trans- Vienna for Slovakia and Hungary. Vuksanović, et. formation period, has employed simple statisti- al. (2004), for example, provide some insight into cal methods or trivial comparison (Miletić, 2006; cross-border economic relationships of Vojvodina. Mitrović, 2008; Rosić, 2004). More thorough at- The west-east polarization of Central European tempts to unravel the complex patterns of region- countries is, in Serbia, traditionally replaced with a al development were often problem-oriented in north-south gradient (Mihailovič, 1990; Ocić, 1998), nature (Jakopin, 2007), and in academic publica- but questions remain as to whether the regions of tions such attempts were rare (Grčić, Ratkaj, 2006; western Romania or southern Hungary, although Radovanović, 2007). The problem of Serbia’s strik- currently more developed economically, could ex- ing regional differences is, nonetheless, widely ac- ert an influence similar to regions along the west- knowledged (Supić, 2007; Austrian Development ern border of the Czech Republic or Hungary. It is Cooperation, 2006; Jakopin, et. al., 2003) and cer- more accurate to assert that any north-south gradi- tainly calls for further investigation into its un- ent in Serbia is a result of physical geography or his- derlying causes, structural patterns and determi- torical reasons. nants. The phenomenon of increasing regional eco- nomic disparities during post-communist trans- Methodological Considerations formation is not new. Evidence of this process has For the purposes of this research concerning fac- been gathered in most of the countries of Cen- tors of regional differentiation in Serbia, the mul- tral, Eastern and South-eastern Europe (Blažek, tivariate method known as principal component 1996; Enyedi, 2005; Gorzelak, 1996; Hampl, 2007; analysis (PCA) was selected. The basic idea of PCA Tomeš, 2001; Tomeš, Hampl, 1999). The regional is the “identification and elimination of redun- pattern behind this observed development is not dancy in the information contained in variables random. Dostál and Hampl (2002) identify a set or groups of variables. The aim is to replace a high of primary geographical factors of regional de- number of preliminary characteristics and their velopment in the Czech Republic that could be relationships with a lower number of components” considered applicable for most post-communist (Heřmanová, 1991, 17). The objective is reached by countries. (1) The first of these factors is the hi- using matrix algebra and the resulting set of new erarchical position of a region (its centre) in its uncorrelated variables, or components, is only national settlement system hierarchy, with spe- one of an indefinite number of solutions. For a de- cial emphasis placed on the duality between met- tailed description of the method, see Heřmanová ropolitan and non-metropolitan regions. (2) The (1991) or Rummel (1970). macro-geographical position of an area, in terms The PCA algorithm can create as many compo- of its distance from developed centres, is the sec- nents as the initial number of variables, but with ond factor. This is derived, first, from the distance an appropriate dataset (the variables should be from the national capital and, second, from for- strongly correlated in a reasonably high number eign centres of development. (3) The third factor is of cases) the first few should be capable of- ex inherited economic specialization. In this context, plaining most of the total variability in a data- economic specialization applies primarily to re- set. The appropriate number of components to be gions with a concentration of declining industrial extracted is usually defined by the eigenvalues of branches and, therefore, it has generally negative the correlation matrix of initial variables. In the consequences. To offer some confirmation, Bar- case of this work, only components with eigenval- jak (2001), focusing on Poland and East Germa- ues (which represent the portion of total variabili- ny, identifies significant agglomerations as highly ty explained by a component) higher than one are developed regions and areas peripheral to signif- used in the subsequent analyses. The results are icant agglomerations, as well as former industri- usually further processed by rotating the space al regions, as problematic. As of yet, no study in defined by components to reach a solution that is
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easier to explain. In this work, the rotation meth- One characteristic in particular, the econom- od used was Varimax with Kaiser Normalization. ic aggregate (EA), does not occur frequently in sta- PCA is used here to define the most important tistics, but sometimes serves as a useful replace- basic and specific dimensions of regional variabil- ment for gross domestic product (Hampl, 2005). ity in Serbia. The territorial units used for analysis EA is calculated as the product of the wages and are districts (okruzi), which represent the meso-re- number of employees in a region. In addition, this gional level. Although these districts are not typ- paper uses national income (NI) instead of the ically organic regions, from the current Serbian more frequently applied gross domestic product. statistical regionalization, they are the most ap- These characteristics have a very similar purpose; propriate for such analysis. The preliminary var- they differ only in their method of calculation. NI iables cover a broad spectrum of socio-econom- and EA vary significantly at times, primarily due ic indicators. Table 1 presents the variables in six to over-employment and low productivity, in re- divisions. The economic development level is rep- gions with companies undergoing restructuring; resented by a set of four indicators. Development however, under ongoing transformation, the re- dynamics are evaluated using five indexes of pre- gional patterns of EA p.c. and NI p.c. are grow- dominantly economic indicators. The initial lev- ing closer. All initial data were taken from pub- el of development is determined by two starting lications of the Statistical Office of the Republic position indicators. Four indicators then focus on of Serbia. the structure of employment, followed by four de- The dataset shown in Figure 1 proved to be mographic indicators and two additional factors. suitable for PCA, according to the Kaiser-Meyer- Olkin Measure of Sampling Adequacy and Bar- tlett’s Test of Sphericity. This means that, within Table 1. List of preliminary indicators for PCA the set of variables, there are groups that correlate ECONOMIC INDICATORS significantly. 1 National income p.c. 2004 2 Unemployment rate 2007 Dimensions of Regional Development 3 Economic aggregate p.c. 2007 in Serbia 4 Employment rate 2007 The aim of the presented analysis is to identify the DEVELOPMENT INDICATORS main dimensions of socio-economic regional dif- ferentiation in Serbia. This objective is reached 5 National income p.c. index 2004/1989 with the extraction of an appropriate number of 6 Employment rate index 2007/1989 components from the initial dataset. The various 7 Economic aggregate p.c. index 2007/2001 components are then characterized with a com- 8 Unemployment rate index 2007/2001 ponent matrix describing the loadings of the in- Employment in industry and mining index itial variables. These loadings are the correlation 9 2007/1989 coefficients between the components and each of STARTING POSITION INDICATORS the initial variables. The components can be inter- preted as new axes in space defined by the original 10 Employment in industry and mining 1989 dataset – the coordinates of regions in this space 11 National income p.c. 1989 are called component scores. A squared compo- STRUCTURAL INDICATORS nent loading describes the share of total variance Employment in progressive sector (banking in a specific variable explained by the particular 12 and finance and real estate) 2007 component. The sum of all the variance shares 13 Employment in industry and mining 2007 from a set of variables that are described by a spe- 14 Employment in agriculture 2007 cific component, as shown in Table 2 for the ini- tial and rotated solutions, represents the total var- 15 Employment in industry and mining 2001 iance explained by the component. DEMOGRAPHIC INDICATORS The optimal solution, according to above-men- Annual population change between 1991 and 16 tioned criteria, that is presented in Table 2, ex- 2002 tracts five components. After rotation, Compo- 17 Natural increase 2007 nent 1 explains nearly 29% of the total variability, 18 Ageing index 2002 Components 2 and 3 explain roughly 18%, Com- 19 Education index 2002 ponent 4 less than 13% and Component 5 slight- ly more than 10% of the variability. Therefore, the OTHER FACTORS first three can be interpreted as basic dimensions 20 Population density 2002 accounting for a significant portion of initial var- 21 Agricultural population share 2002
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Table 2. Total variance explained by extracted components
Compo- Initial Eigenvalues Extraction Sums of Squared Rotation Sums of Squared nent Loadings Loadings Total % of Cumu- Total % of Cumu- Total % of Cumu- Variance lative % Variance lative % Variance lative % 1 9.042 43.058 43.058 9.042 43.058 43.058 6.030 28.716 28.716 2 3.020 14.379 57.437 3.020 14.379 57.437 3.797 18.079 46.795 3 2.361 11.242 68.680 2.361 11.242 68.680 3.614 17.209 64.004 4 2.138 10.181 78.861 2.138 10.181 78.861 2.644 12.591 76.595 5 1.675 7.977 86.838 1.675 7.977 86.838 2.151 10.243 86.838
iance, while the other two dimensions specify the ulation index between the last two censuses. The general pattern in certain special respects. fifth component also shows a specific dimension Table 3 presents the component loadings of the of variability, most closely related to recent em- various components. Component 1 is character- ployment in industry and mining, but also exhib- ized by the high loadings from employment in the iting high loadings from other indicators of indus- progressive sector and the education index which, trial employment including its development index. along with high loadings concerning the employ- ment rate and population density and a low load- Table 3: Rotated component matrix ing from agricultural population, imply that it should describe urban areas. Significant correla- Component tion with the most recent values of EA p.c. and NI 1 2 3 4 5 p.c. shows that these areas also rank among the Employment in progressive .934 most economically developed. These underlying sector 2007 characteristics indicate that Component 1 is con- Education index 2002 .917 nected with the concept of the settlement system Employment rate 2007 .839 hierarchy, achieving its highest values in regions EA p.c. 2007 .817 with important education centres, progressive services and a high degree of urbanization. Population density 2002 .800 Agricultural population share Developmental characteristics, including the -.754 employment rate, EA p.c. and NI p.c., have high 2002 Employment rate index loadings on Component 2, while recent unem- .924 ployment has a low component loading. This im- 2007/1989 plies that Component 2 characterizes develop- EA p.c. index 2007/2001 .862 ment dynamics, due to the employment rate and NI p.c. index 2004/1989 .673 EA p.c., which focus primarily on matters of em- Unemployment rate 2007 -.601 ployment; nonetheless, the NI p.c. loading shows Employment in agriculture that development of regional differences in pro- .841 2001 duction had a very similar pattern. Component 3 is characterized by high load- NI p.c. 1989 .714 Unemployment rate index ings describing employment in agriculture and NI -.668 p.c. (both initial and final) and low loadings from 2007/2001 the unemployment rate index and initial employ- NI p.c. 2004 .645 .656 ment in industry and mining. This indicates that Employment in industry and -.592 .535 regions with high scores on this component are mining 1989 those with a high level of development that is not Ageing index 2002 -.935 based on extensive industrialization, but rath- Natural increase 2007 .925 er on intensive agriculture or diversified industry Population index 2002/1991 .676 at a lower scale. This setup proves to be accompa- Employment in industry and nied by positive developments in the unemploy- .907 mining 2007 ment rate. Employment in industry and Component 4 shows a specific regional pat- .621 mining index 2007/1989 tern of demographic behaviour in Serbia. It has Employment in industry and very high negative loading from the ageing in- .568 dex and a significant positive loading from natu- mining 2001 ral increase, while also correlating with the pop- Note: Loadings lower than .500 are not shown.
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This component proved to be less interpretable, in particularly in terms of economic output and em- terms of its regional distribution, and, therefore, ployment and in light of the very low initial lev- it will not be evaluated further. el of these characteristics, the message of Figure Component 1 has high scores, especially in dis- 2 is clear: northern Central Serbia is coping with tricts containing Serbia’s main settlement centres, post-communist transformation and exhibits the including Novi Sad, Belgrade, Kragujevac and Niš. best results so far. In addition to these districts, The cartographic presentation in Figure 1 shows higher scores in Component 2 can also be iden- that these cities form a basic north-south axis in tified in metropolitan regions, which predictably Serbia. The preceding evaluation of component exploit the concentration of political or adminis- loadings indicated that a high level of develop- trative power and qualitatively higher-level activ- ment, reasonable quality of human capital and ities, such as tertiary education and quaternary an urban character are typical for Component 1. economic activities to achieve higher economic This fits the description of regions well positioned growth rates. in the national settlement system hierarchy. The Component 3 shows a clear north-south gra- visible pattern in Figure 1 confirms this assump- dient. Its scores, as presented in Figure 3, are tion. High Component 1 scores are found particu- highest in Vojvodina and decrease gradually to- larly in the main metropolitan areas of Serbia and wards southern Central Serbia. Evaluation of Ta- correspond with the position of regions in the na- ble 3 shows that there are multiple characteristics tional settlement system hierarchy. bound to this pattern. Most notable is employ- Component 2, as presented in Figure 2, has no- ment in agriculture, which proved to be a “built- tably high scores in the northern part of Central in stabilizer” during the 1990s (Babić, 1999) and, Serbia, especially in the Belgrade, Braničevo, Kol- along with the positioning of the most strategic ubara, Mačva, Podunavlje and Pomoravlje dis- chemical industry in Vojvodina, it was behind the tricts. Characteristics of these regions vary sub- region’s economic dominance, during the latter stantially - some are more industrial, others are, years of the totalitarian regime and continuing, for the most part, rural, some have a clearly spe- to a lesser extent, to the present time. Moreover, cialized industry while others are more differen- the historical development of Vojvodina, especial- tiated. Most of these districts saw a sharp decline ly concerning its agriculture and small scale in- in economic output, during or before the crisis dustry, meant that the area required less “forced” of the 1990s, and, consequently, they grew from socialist industrialization. “Naturally” occurring very low initial values, making their growth more industrial activities, traditionally located in Vojvo- pronounced. The resulting pattern cannot be in- dina, would not lose ground as easily as the “arti- terpreted as a universal development trend, but, ficially” implemented industry of southern Serbia
Figure 1: Component 1 scores Figure 2: Component 2 scores
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Figure 3: Component 3 scores Figure 4: Component 4 scores
(for more on industrial distribution in Vojvodina, Component 4 scores are extremely unfavourable see Romelić, et. al., 2007; Romelić, Tomić, 2004). in the area. On the other hand, this higher level of immuni- ty to the pronounced crisis of the 1990s probably caused the moderate or lower growth rate in the Conclusions subsequent period, as expressed in Component 2. From these dimensions (components) of region- Component 4, based on demographic indica- al differentiation, the first and the third compo- tors, shows a specific pattern of regional develop- nents can be considered to be particularly similar ment. As presented in Figure 4, its spatial differ- to processes in Central European transformational entiation is distinct from the other components. countries. The first dimension is generally of uni- The gradient of Component 4 is oriented from versal validity (Hall, Hay, 1980): an area’s position west to east and, in Central Serbia southwest to in the national settlement system hierarchy deter- northeast. There are multiple phenomena be- mines the localization of tertiary education facil- hind this pattern. 1) The influx of refugees from ities or government offices and is associated with Serb-inhabited areas in Bosnia-Herzegovina and the density of interpersonal contacts. These factors Croatia during 1990s was oriented primarily at re- lead to the placement of progressive services, banks gions along the western border of Serbia and the and R & D into major metropolitan areas, implying biggest cities. Therefore these areas did not suf- a higher level of economic development. The evo- fer a major decline in population. 2) In the south lution of such patterns shaped the transformation and southeast of Serbia (Pčinja, Raška and Zlati- period, although in some specific cases the switch- bor districts), ethnic minorities with different de- ing of functions from manufacturing to services mographic behaviour, Albanians and Bosniaks, brought a temporary decline to certain regions. In are concentrated. Because of their very high na- Serbia, this pattern of inherited, unfavourable spe- tality rates, these regions experienced natural in- cialization is notable in the cases of the Nišava and crease in population, which also expressed itself Šumadija districts (with the cities Niš and Kraguje- in general population developments. 3) Serbia was vac), which could be expected to have higher Com- subject to an extensive population exodus dur- ponent 1 scores. On the other hand, in the case of ing the 1990s. In the areas mentioned above, this Kragujevac, it could be argued that it is simply one was countered with natural increase or immigra- step lower in the national settlement system hier- tion. However, in the districts of eastern Serbia, archy than the cities of Belgrade, Novi Sad and Niš where the trend to emigrate is even more common and, therefore, that its score is reasonable. (Filipović, 2007), there was no process to reduce Another pattern that could be generalized to the massive depopulation occurring. As a result, describe most post-communist countries is gra-
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dient. In the case of Serbia, its direction is north- its tradition as an industrial centre, the city of south, while in Central European countries it is Kragujevac and its surrounding Šumadija district usually west-east. In both cases, however, it could could be expected to have the potential to achieve be argued that the gradient moves from borders better economic results. However, the process of with more developed neighbours towards the restructuring and privatizing Zastava, a compa- European periphery. Although the spatial pat- ny fundamental to the economic development of tern is similar, the question remains as to wheth- Kragujevac, was very complicated and its low pro- er its conditions differ or not. In Central Europe- ductivity consistently hindered regional growth. an countries, the usual source of such a gradient Now that privatization of the major parts of the is the proximity of developed cities and regions – company is done, an improvement in the econom- for the Czech Republic, this is Bavaria; for Slova- ic development of Šumadija can be expected. An- kia and Hungary, Vienna; for Poland, it could be other region with inherited unfavourable special- Berlin. More dynamic development in the west- ization is Bor in eastern Serbia – an area that was ern parts of these countries is supposed to be originally extremely dependent on one huge min- based on the diffusion of small and medium in- ing and metallurgic complex. Its export oriented vestment across state boundaries. What devel- production practically ceased to exist, during the opment pole, then, could Serbia be attached to? 1990s, and for such a giant enterprise to be eligi- Could Budapest, Pécs or Timişoara play such ble for privatization extensive restructuring (and a role? In the research presented in this paper, fragmentation) was required. Component 3, characterized by its north-south There are some places with even poorer pros- gradient, is based primarily on employment in pects – for example, the capacities of the textile agriculture, and its correlation with NI p.c. de- industries in Raška and Jablanica districts prac- clined between 1989 and 2004. This could raise tically disappeared and can hardly be expected doubts concerning the low progressivity and re- to reappear. Throughout most of Serbia’s periph- ceding character of Serbia’s north-south gradient. eral south, socialistic industrialization creat- On the other hand, developments in the unem- ed isolated activities with few connections to lo- ployment rate were positive during the post-com- cal resources and little embeddedness in the local munist transformation, which is a more valuable economic environment (acknowledged as a fun- achievement, considering the obsolete manner damental problem of Yugoslav attempts at region- of measuring NI, during the observed period. A al policy – see Mihajlović, 1990; Ocić, 1998). Such detailed analysis of how strong the cross-border activities were sustainable only under the com- diffusion of development is would be worthwhile, mand economy of socialism, during (often even but the effects would almost surely not reach the before) transformation, most of them went bank- magnitude possible in Central Europe. The grad- rupt. Now the problem is what strategy to select ual pattern of regional differentiation in Serbia is as a means of reviving economic activity in such probably caused by historical and cultural factors, peripheral areas – distance from poles of devel- rather than by neighbourhood effects. It is very opment, the poor quality of human capital and a likely that physical geography also plays a role in prevailing rural character leave few choices. Tour- the development and persistence of the north- ism could contribute significantly to local devel- south gradient, as agriculture is often regarded opment, but it would only have a major impact in as “the safest and most profitable sector in Ser- a few of the most attractive places. Ecotourism, bia” (Šabić, et. al., 2009, 27). Therefore, Vojvodina a frequently elicited option, could only serve as is provided with a competitive advantage against a complement to agricultural activities and light the rest of the country. manufacturing. Emphasis must be placed on inte- This gradient persists mainly in the duality gral development and local initiative, even though of Vojvodina (with Belgrade) and Central Serbia. this path to prosperity will be very long and diffi- However, Component 2 also shows that, within cult for peripheral areas. Central Serbia, development is most dynamic in The dualities present in Serbia will persist. The the northern part. This points to the evolution of underdeveloped south will always present a con- a more fluid north-south gradient and also to the trast with the dynamically progressing north. Bel- strengthening application of macro-geographical grade and its surroundings will prosper econom- position, especially in terms of the distance from ically while the southern periphery struggles for the national capital. The dynamic development of basic functionality. At present, there is one more regions close to Belgrade is a reflection of its -at challenge affecting the entire country – the - in tractiveness, while districts further to the south ternational economic crisis has impacted Serbia tend to be neglected by investors. heavily. Successful national and regional develop- Naturally, there are some disturbances among ment strategies in the aftermath of this crisis will all the basic component patterns. Considering be of crucial importance. The economic develop-
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ment of Serbia cannot be based solely on indige- nous resources. The need for an inflow of foreign References capital into the country – preferably in the form of Adamović, J. 2002. Indicators of Socio-econom- foreign direct investment (FDI) – is ongoing. The ic Development. Glasnik srpskog geografskog prospects for privatization, the dominant form of društva, 82,1, 9-16. (in Serbian) FDI throughout the early years of Serbia’s trans- Adžić, S. 2008. Regional Policies and European In- formation (Hall, 2005), have decreased consider- tegration of Vojvodina. Prometej, Novi Sad, 249 ably; the primary objective should be the attrac- pp. (in Serbian) tion of productive greenfield investments. In the Austrian Development Cooperation 2006. Serbia case of Serbia, a considerable portion of this strat- Country Programme 2006-2008. Federal Aus- egy has to be pursued through politics – the polit- trian Ministry for Foreign Affairs, Vienna, 27 ical climate in the country has been the main de- pp. terminant of FDI inflow, during the first decade Babić, S. 1999. The Political Economy of Ad- of the 21st century. The best guarantee for foreign justment to Sanctions: The Case of Serbia. investors would be EU candidate status; however, Međunarodni odnosi, 2. Available at
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tional Processes and Their General Context. Organisation of Industry in Bačka. Geographica Charles University in Prague, Prague 147 pp. (in Pannonica, 11, 43-47. Czech) Romelić, J., Tomić, P. 2004. Geographical Bases Hampl, M. 2007. Regional Differentiation of Con- of Industry Distribution in Vojvodinian Part of temporary Socio-economic Development in Banat. Geographica Pannonica, 8, 38-42. the Czech Republic. Sociologický časopis, 43,5, Rosić, I. (ed.) 2004. Strategy of Regional Develop- 889–910. (in Czech) ment in Serbia. Economic Faculty, Kragujevac, Heřmanová, E. 1991. Selected Multivariate Statis- 299 pp. (in Serbian) tical Methods in Geography. Státní pedagog- Rosić, I. 2007. Absence of Branch-regional and Bal- ické nakladatelství, Prague, 133 pp. (in Czech) anced Development in Serbia. In Aranđelović, Z. Jakopin, E. (ed.) 2007: Regional Development (ed.). Regional Development and Demographic Strategy of the Republic of Serbia. Republic De- Flows in the Countries of Southeastern Europe. velopment Bureau, Belgrade, 210 pp. Economic Faculty, Niš, 25-35. (in Serbian) Jakopin, E., Radosavljević, S., Tontić, S. 2003. Re- Rummel, R. J. 1970. Applied Factor Analysis. gional Poverty of Serbia. In Aranđelović, Z. Northwestern University Press, Evaston, 592 pp. (ed.). Regional Development and Demographic Statistical Office of the Republic of Serbia. Acces- Flows in the Balkan Countries. Economic Fac- sible at
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