69004 Željko LovrinÄ?ević Davor Mikulić INRODUCTION Systematic analysis of living standards, poverty, inequality and regional development are not performed on a regular basis in Croatia. Comprehensive profile of living standards and poverty has not been derived since the last World Bank report in 2001, while regional growth and social profile have not been examined at all. Therefore, the aim of this research is to provide a comprehensive profile of social and economic characteristics of Croatia's regions at NUTS III level. Regional profile of government’s social transfers to households is also analyzed. In this paper, demographic and economic structure of Croatian economy is analyzed, as well as the process of secondary distribution of income in Croatia on the regional level. According to data availability limitation, the analysis was restricted to the period 2001-2003. We also tried to assess effectiveness of government social transfers to households given the regional inequality profile. Also, sources of growth on the regional level and growth prospects were identified. Final draft includes two appendices. The first appendix presents the regional GDP by counties for period 2001-2003, and the second appendix presents preliminary data on gross disposable income of household sector in Croatia. REGIONAL TRENDS IN THE NMS10 COUNTRIES AND EU15 Prior to the development analysis of the Croatian counties, we briefly outline the experiences of the new NMS10 members as well as EU countries in terms of the regional development level differences. According to the GDP dynamics, employment, unemployment and population figures in the NUTS II regions of the new member states (NMS101), four groups of NUTS II regions can be identified in terms of the convergence process towards the EU15:2: ï‚· Regions with high convergence potential ï‚· Regions with moderate convergence potential ï‚· Regions with moderate divergence risk ï‚· Regions with high divergence risk. 1 Cyprus, the Check Republic, Estonia, Latvia, Lithuania, Hungary, Malta, Poland, Slovakia and Slovenia. 2 Revue élargissement no. 75, 11th April, 2005. Figure 4.1 shows the average annual GDP growth rates in the various EU25 NUTS II regions. In the period 1995 - 2002, 31 out of the total of 41 regions on the NUTS II level of the new member states have recorded reductions in the difference in economical development, according to the GDP p.c. PPS with respect to the EU25 average. On average, the annual GDP p.c. PPS growth rate for the NMS10 amounted to 5.6 percent, while the EU15 countries recorded annual growth of 4 percent. Six out of the ten NUTS II regions in the NMS10, which have grown at a slower rate in comparison to the EU25 average, are in the Check Republic, which is, along with Cyprus, the only country with a recorded slower rate of growth in comparison to the average of the older EU15 members. In the first group of NUTS II regions with high convergence potential, the three Baltic countries (Estonia, Lithuania and Latvia) and Slovenia are included, representing small economies which have been classified as one NUTS II region despite being nation states. Also, the three Hungarian regions are included here, located in the area between Vienna and Budapest, and the eastern region surrounding Debrecen, as well as the two Slovakian regions: Bratislava and Eastern Slovakia (Kosice). All of these regions are characterized by a high GDP growth levels, reductions in unemployment levels, gradual reductions or increases in the number of employees, and favorable demographic trends (increases or small reductions in the population figures). NUTS II regions with moderate convergence potential are characterized by relatively dynamic growth (average GDP per capita growth rate, according to PPS above 4.5 percent), but in conditions of gradual increases in unemployment or decreases in employment. In these regions, it is expected that the positive components of the "creative destruction" process will overwhelm the negative ones, thus the continuation should record positive trends towards further convergence. In the NUTS II regions with moderate divergence risk, which are, in addition to Cyprus, found mainly along the borders of Check Republic and Germany, slower growth has been recorded (less or around the NMS10 average), however with increases in the unemployment rates. This group also includes the regions with slower GDP growth, but with reductions in the unemployment rates (Plzen, Karl. Vary). The high divergence risk group includes 11 NUTS II regions, where the average annual increases of the GDP per capita PPS are more than one standard deviation lower than the NMS10 average. Apart from the slower growth, these regions are characterized by increases in the unemployment figures which, in addition to the reductions of the employment levels, lead to significant increases of the unemployment rate. Regions in this group also exhibit the worst demographic trends (reduction in population numbers). The NUTS II region classification according to the economic growth potential is shown in Table 4.1. It should be emphasized that, for the benefit of easier location of the various regions on the map, the central cities of specific regions have been stated, and not the official name of the region. Figure 1.1: Average Annual Real GDP Growth Rates of EU25 NUTS II Regions, 1995-2002, in % Source: Eurostat DG REGIO. Table 1.1: Average Annual GDP p.c. PPS (1995-2002), Unemployment (1999-2003), Employment (1999-2003) and Population (1995-2002) Growth Rates NUTS II level regions GDP growth Unemployment Employment Population Regions with high convergence potential Budapest 8.1 -5.1 0.6 -0.3 Talinn 7.8 -2.9 0.5 -0.7 Riga 7.7 -5.3 0.7 -0.8 Bratislava 7.4 -0.8 -0.1 -0.4 Vilnius 7.1 -1.5 -0.8 -0.6 Gyor 6.5 0.9 0.2 0.0 Tatabanya 6.1 -5.5 1.2 0.0 Kosice 6.0 0.5 0.4 0.3 Ljubljana 5.5 -2.0 0.3 0.1 Debrecen 5.1 -7.8 1.5 0.1 Regions with moderate convergence potential Warsaw 8.2 9.8 -3.0 0.2 Prague 6.5 1.0 -0.4 -0.6 Poznan 6.4 11.8 -0.3 0.1 Zilina 6.2 2.0 -0.1 0.0 Trnava 5.2 2.3 0.6 -0.1 La Valette 5.0 0.5 0.6 0.8 Pecs 4.9 -1.0 0.5 -0.1 Miskolc 4.6 -3.5 1.4 -0.1 Kladno 4.5 -8.3 0.9 0.2 Regions with moderate divergence risk Bialystok 5.8 7.7 -3.2 -0.1 Wroclaw 5.7 11.9 -4.4 -0.3 Kielce 5.6 7.7 -2.1 -0.3 Lodz 5.5 10.1 -1.1 -0.4 Krakow 5.4 14.1 -1.3 0.2 Gdansk 5.4 13.1 -2.1 0.1 Nikosia 3.8 -5.0 3.2 1.1 Jihaliva 3.6 -2.8 -0.2 -0.2 Hradec 3.4 -3.3 -0.1 -0.1 Plzen 3.1 -4.0 0.1 -0.1 Karl. Vary 1.5 -3.7 0.1 -0.1 Regions with high divergence risk Szcecin 5.0 5.2 -2.9 -0.1 Olsztyn 4.9 4.2 -1.0 -0.2 Rzeszow 4.8 7.0 -0.8 0.0 Bydgoszcz 4.6 10.6 -0.5 -0.1 Katowice 4.4 12.7 -2.1 -0.4 Zielona G. 4.4 7.8 -0.7 -0.3 Lublin 4.1 8.5 -0.5 -0.1 Szeged 3.9 2.3 -0.4 0.0 Opole 3.4 5.4 -3.1 -0.3 Brno 2.6 -2.2 -0.2 -0.1 Ostrava 2.2 2.5 -0.6 -0.3 Source: Revue élargissement, no. 75, 11th April 2005. It is important to notice that during the period 1995-2002, in the group of new member states there was a worsening of the ratio between the most developed and least developed region in all of the 4 analyzed countries with defined several NUTS II regions (Table 4.2).3 3 Malta, Cyprus, Estonia, Latvia, Lithuania and Slovenia are simultaneously state and NUTS II regions. Table 1.2: Ratio between NUTS II Region with Highest/Lowest GDP p.c. PPS, 1995-2002 Country 1995 1997 1999 2001 2002 NMS Check Republic 2.4 2.5 2.6 2.9 2.9 Hungary 2.0 2.2 2.4 2.4 2.6 Poland 1.7 1.8 2.1 2.1 2.2 Slovakia 2.8 2.8 2.9 3.0 3.1 EU15 Belgium 3.0 3.1 3.2 3.2 3.1 Germany 2.9 2.9 2.8 2.9 2.8 Greece 2.1 1.9 1.8 1.9 1.9 Spain 2.1 2.1 2.1 2.1 2.1 France 3.0 3.0 2.9 3.0 3.1 Ireland 1.4 1.5 1.5 1.5 1.6 Italy 2.4 2.3 2.3 2.3 2.4 Netherlands 1.6 1.7 1.7 1.7 1.7 Austria 2.3 2.2 2.2 2.2 2.1 Portugal 1.9 2.0 1.9 1.9 1.8 Finland 1.6 1.7 1.9 1.9 1.9 Sweden 1.5 1.6 1.6 1.6 1.6 Great Britain 4.1 4.2 4.4 4.3 4.3 Source: Eurostat. The most significant regional development differences are noted in Slovakia and the Check Republic, while the relatively highest increases in inequalities are recorded in Hungary. Usually, this increasing divergence is consequence of the above average growth of regions comprising the capital city and the surrounding regions. That phenomenon occurs as a result of the so called "gateway" effect, where almost all of the capital cities in the transition countries represent the entry point for foreign investments. That implies a concentration of primarily financial services, telecommunications, IT and other logistic activities in the capital cities. The process is clear and present despite the efforts by the governments in the transition countries to achieve balanced regional development. On the other hand, old member countries (EU15) are clearly experiencing an end of the trend of further centralization of economic activities in the most developed areas. The primary reason for this is the planned policy of balanced regional development supported by the European structural funds. Therefore in the NMS group, an end of the trend of centralization of economic activities and an emphasis on a more balanced regional development can be expected in the long run. In the continuation, the dynamic of the economic structure changes in the European NUTS II regions are analyzed. Table 4.3 shows the growth rates of different activities, as classified in the National classification of economic activities (NACE), for the EU25 countries. It is clear that throughout the period, the GDP of new members grew at a faster rate in comparison to the old members, as expected since with the EU accession process, real convergence process begun, thus there is a so called low basis effect present. On average, the real growth of the new members was faster by 0.87 percentage points. However, when analyzing the growth according to activities, it is noticeable that the highest average growth among the new member states is recorded in the retail, hotel, restaurant and transportation sector, (G, H and I) and the business and financial services sector (J and K). Industry (C, D and E) and construction (F) are growing slightly faster than the total GDP, with noticeable seasonal pattern over the year, while the activities of public administration, education, health and other personal and community services (L, M, N and O) are growing at a slower rate in comparison to the average. The slowest growth (and in some cases real decreases) have been recorded in agriculture and fisheries (A and B). Such trends indicate that the economic structure greatly influences the growth potential of certain NUTS II regions. A more favorable current economic structure (a higher proportion of propulsive service sectors and a smaller proportion of agriculture and government services) ensures higher growth rates in the middle run. Thus, this influenced further increases in the differences between the developed and less developed regions in the NMS10, since the most favorable economic structure is found in the most developed regions. Table 1.3: Real GDP Growth Rates of the EU25 According to the NACE Classification Activities, 2000-2003 GDP A, B C, D, E F G, H, I J, K L, M, N , 00 01 02 03 00 01 02 03 00 01 02 03 00 01 02 03 00 01 02 03 00 01 02 03 00 01 02 03 euro- 3.5 1.6 0.9 0.5 -0.6 -2.4 0.6 -3.8 4.3 0.6 0.2 0.0 2.7 0.0 -0.5 -0.4 4.4 3.2 1.2 0.5 4.9 2.9 0.8 1.4 2.3 1.8 2.2 0.6 zone EU25 3.6 1.7 1.1 0.9 -0.6 -2.4 1.3 -3.3 4.2 0.2 0.1 0.4 2.5 0.2 0.0 0.2 4.6 3.2 1.6 1.0 4.9 3.1 1.0 1.9 2.3 1.8 2.2 0.7 EU15 3.6 1.7 1.0 0.8 -0.5 -2.8 1.4 -3.4 4.1 0.2 0.0 0.1 2.5 0.4 0.0 0.2 4.6 3.1 1.5 0.9 4.9 3.1 1.0 1.9 2.3 1.8 2.2 0.7 Members BE 3.9 0.7 0.9 1.3 1.0 -11.3 12.7 -3.2 5.0 -0.3 -0.2 -0.3 7.7 1.2 -1.5 -0.4 2.9 2.3 3.5 0.8 2.3 1.6 0.1 3.0 2.6 1.3 0.9 1.6 CZ 3.9 2.6 1.5 3.7 5.7 -7.0 2.6 -1.0 7.1 -5.0 7.8 7.1 -0.3 -8.2 3.1 -0.5 1.7 9.1 -1.0 -0.9 4.8 11.9 -3.9 5.3 3.8 1.4 0.9 1.6 DK 2.8 1.6 1.0 0.4 6.4 -1.5 -4.3 3.3 3.3 0.0 -0.4 -0.2 1.6 4.0 0.6 -2.7 7.3 2.9 1.9 1.5 3.9 3.9 1.3 0.4 -0.2 1.3 1.8 0.6 DE 2.9 0.8 0.1 -0.1 -0.8 0.3 -1.8 -0.7 4.6 -1.3 -0.4 0.5 -2.3 -5.6 -4.8 -4.4 3.4 3.9 1.4 0.9 4.8 3.8 0.1 0.5 2.1 0.2 1.6 -0.4 EE 7.8 6.4 7.2 5.1 -0.8 -5.4 0.1 -1.5 13.9 8.5 12.9 8.0 13.8 4.3 20.6 7.7 7.2 9.1 4.2 7.2 8.3 5.9 5.4 2.1 2.6 4.1 3.9 1.8 EL 4.5 4.3 3.6 4.5 -3.7 -3.8 -1.2 -4.0 5.3 3.0 2.6 2.6 5.7 14.4 0.8 11.2 7.6 7.0 3.6 6.1 5.1 4.2 -0.2 4.3 1.4 3.1 8.0 3.4 ES 4.4 2.8 2.2 2.5 2.7 -2.9 1.7 -1.4 3.9 2.5 0.7 1.3 6.1 5.3 5.2 4.3 3.8 3.5 1.9 1.6 5.9 6.1 0.4 1.3 4.4 2.5 2.8 3.3 FR 3.8 2.1 1.2 0.5 -2.2 -4.0 4.7 -7.4 4.2 2.8 0.8 -0.1 7.1 1.5 -0.1 -1.4 4.5 2.4 0.4 -0.8 4.8 0.8 1.6 3.1 2.4 3.3 3.4 -0.1 IE 9.9 6.0 6.1 3.7 IT 3.0 1.8 0.4 0.3 -2.9 -0.5 -3.9 -5.7 2.3 -0.2 -0.3 -1.0 3.5 3.1 2.5 2.5 5.6 3.5 -0.1 0.0 5.1 2.8 1.8 1.2 1.0 2.1 1.2 0.6 CY 5.0 4.1 2.1 1.9 -5.9 3.8 5.4 4.5 3.4 0.3 0.4 0.6 -1.2 4.0 4.7 4.4 8.8 5.2 -0.3 -0.7 6.4 5.5 3.5 2.7 3.6 3.1 4.0 4.3 LV 6.9 8.0 6.4 7.5 11.5 6.4 4.4 1.0 4.4 9.7 8.1 7.8 8.2 6.1 10.8 13.7 8.2 10.2 8.1 10.4 12.3 12.2 5.5 4.3 1.4 2.0 2.8 3.3 LT 3.9 6.4 6.8 9.7 6.4 -4.6 8.2 2.2 5.4 13.9 4.6 15.8 -18.2 7.4 12.7 22.0 6.7 8.1 9.3 9.1 5.0 5.6 6.6 6.2 4.3 -0.9 2.9 2.4 LU 9.0 1.5 2.5 2.9 -7.2 -15.1 0.1 -2.3 6.9 1.0 2.0 2.6 5.1 8.0 5.3 4.3 9.4 6.3 3.3 3.4 9.4 -0.5 2.5 1.7 2.9 4.7 1.0 3.6 HU 5.2 3.8 3.5 3.0 -7.4 23.4 -12.1 -4.0 6.4 0.4 1.3 5.4 19.2 5.2 12.9 1.2 0.8 5.0 4.7 4.3 8.3 4.4 6.3 -1.3 3.3 3.4 2.3 3.0 MT 6.4 -2.4 2.6 -0.3 NL 3.5 1.4 0.6 -0.9 1.5 -3.6 -1.6 -1.9 3.5 0.5 -1.0 -2.1 4.2 2.1 -3.2 -3.0 6.3 0.7 0.8 -1.3 2.9 1.6 -0.4 -0.1 1.6 2.8 2.8 2.3 AT 3.4 0.7 1.2 0.8 -3.0 0.6 -0.5 -1.3 6.2 2.5 1.7 0.2 1.7 -3.5 0.4 5.1 3.2 2.0 2.5 1.8 6.3 0.7 1.6 0.6 1.3 -0.7 -1.3 -0.5 PL 4.0 1.0 1.4 3.8 -7.9 9.2 2.0 2.1 6.5 -0.3 -0.2 6.3 0.3 -7.9 -6.8 -2.9 4.0 3.6 5.9 2.3 4.5 2.7 -0.1 5.8 2.5 0.4 0.2 3.4 PT 3.4 1.7 0.4 -1.2 -4.0 -0.3 5.7 -6.7 2.7 1.9 -1.0 -0.5 4.9 2.8 -3.8 -11.4 4.1 4.0 1.0 0.1 7.1 4.3 0.9 2.0 3.5 2.1 1.5 -1.4 SI 3.9 2.7 3.3 2.5 0.8 -12.1 15.4 -15.3 8.4 5.0 4.7 3.3 0.9 -2.2 0.6 3.4 2.1 3.7 3.4 3.1 1.2 4.7 4.0 4.3 4.8 3.3 2.3 3.0 SK 2.0 3.8 4.6 4.0 1.9 4.9 -1.6 4.4 0.8 1.4 -0.3 9.5 0.2 -0.5 9.3 6.9 2.2 9.7 -3.2 -2.4 2.5 1.9 17.5 8.9 2.8 14.0 16.6 5.5 FI 5.1 1.1 2.3 2.0 10.6 -4.8 3.6 0.6 11.0 0.3 2.1 0.9 -2.6 -2.9 2.5 1.3 5.3 2.8 2.3 3.3 5.3 0.7 2.6 3.6 2.1 3.0 1.8 0.5 SE 4.3 1.0 2.0 1.5 2.8 4.3 2.8 1.2 8.2 -1.6 4.5 1.9 0.7 5.2 -0.4 0.8 3.7 0.5 1.7 2.3 4.9 1.8 -0.3 1.9 1.7 1.4 1.9 1.3 UK 3.9 2.3 1.8 2.2 -0.6 -9.1 11.9 -2.6 1.9 -1.6 -2.5 -0.2 1.3 1.8 3.8 5.2 5.1 2.9 3.6 2.5 5.0 4.6 2.1 4.6 3.2 2.4 2.6 1.3 Source: Eurostat DG REGIO. DEMOGRAPHIC AND ECONOMIC CHARACTERISTICS OF THE CROATIAN REGIONS After the experience of the NMS10, in this section demographic and economic features of Croatian regions are analyzed. Because of some doubts regarding final regional breakdown of Croatia instead of preliminary NUTS II region, we rather used breakdown based on so-called analytical regions. According to main features Croatia could be divided in 5 analytical regions: Zagreb region, Central Croatia, Eastern Croatia, Adriatic North and Adriatic South. Besides analytical regions, all data are presented using current administrative breakdown on counties. Such administrative division of Croatia fulfils all of the EU criteria for NUTS III breakdown. Demographic structure Tables 4.4 and 4.5 show the demographic structure of the Croatian regions. The working population comprises 64 percent of the total population in Croatia, i.e. the male population between the age 15 and 64 and female population between 15 and 59. Senior population accounts for little less than 19 percent-and the remaining 17 percent of the total population are children. Table 5.1.4: Demographic Structure of Croatia, by County (NUTS III) Demographic structure Demographic structure, % Senior Senior County Working Working population population Children contingent Children contingent (F above (F above (0-14) (F 15-59, (0-14) (F 15-59, 60, M 60, M M 15-64) M 15-64) above 65) above 65) Zagreb 53 822 202 003 51 866 17.5 65.7 16.9 Krapina-Zagorje 24 293 89 662 28 142 17.1 63.1 19.8 Sisak-Moslavina 29 948 114 647 40 331 16.2 62.0 21.8 Karlovac 20 521 86 853 33 496 14.6 61.7 23.8 Varaždin 31 807 118 247 34 061 17.3 64.2 18.5 Koprivnica-Križevci 21 064 78 410 24 604 17.0 63.2 19.8 Bjelovar-Bilogora 22 805 82 283 27 544 17.2 62.0 20.8 Primorje-Gorski kotar 42 835 201 527 59 482 14.1 66.3 19.6 Lika-Senj 8 200 30 896 14 315 15.4 57.8 26.8 Virovitica-Podravina 16 962 57 820 18 059 18.3 62.3 19.5 Požega-Slavonia 16 966 52 097 16 420 19.8 60.9 19.2 Slavonski Brod- 34 728 108 692 32 353 19.8 61.8 18.4 Posavina Zadar 29 496 101 242 30 336 18.3 62.9 18.8 Osijek-Baranja 58 719 210 882 60 036 17.8 64.0 18.2 Å ibenik-Knin 18 953 67 375 26 063 16.9 59.9 23.2 Vukovar-Sirmium 39 359 128 317 36 119 19.3 63.0 17.7 Split-Dalmatia 85 585 296 386 79 531 18.5 64.2 17.2 Istria 31 177 135 445 38 984 15.2 65.9 19.0 Dubrovnik-Neretva 22 467 76 565 23 282 18.4 62.6 19.0 MeÄ‘imurje 21 964 76 703 19 484 18.6 64.9 16.5 City of Zagreb 122 963 512 580 140 381 15.8 66.1 18.1 Croatia 754 634 2 828 632 834 889 17.1 64.0 18.9 Source: Census 2001, CBS. 7 The demographic structure of certain counties (NUTS III level) and 5 analytical regions significantly differ from the Croatian average. Therefore, according to the ratio of children, the two "youngest" counties are the County of Požega-Slavonia and Slavonski Brod-Posavina, in which children account for almost a fifth of the total population. If one considers that County of Vukovar-Sirmium can also be included in this group of counties with a high proportion of children, it can be concluded that Eastern Croatia is the youngest region in Croatia. The highest proportion of the working population is present in three most developed counties (according to the GDP per capita levels – see Table 4.8), i.e. County of Primorje-Gorski kotar, County of Istria and the City of Zagreb (66 percent). The Zagreb region has the highest proportion of the working population in the overall population, followed by Adriatic North. Central Croatia is the most senior region in Croatia, with more than 20 percent of senior population, closely followed by the Adriatic North. The counties with the highest proportion of seniors are County of Lika-Senj (26.8 percent), County of Karlovac (23.8 percent) and County of Å ibenik-Knin (23.2 percent). Table 1.5: Demographic Structure of Croatia by Analytical Region Demographic structure Demographic structure, % Senior Senior Region Working Working population population Children contingent Children contingent (F above (F above 60, (0-14) (F 15-59, (0-14) (F 15-59, 60, M M above M 15-64) M 15-64) above 65) 65) Zagreb region* 176 785 714 583 192 247 16.3 65.9 17.7 Central Croatia** 172 402 646 805 207 662 16.8 63.0 20.2 Adriatic North*** 82 212 367 868 112 781 14.6 65.4 20.0 Adriatic South**** 156 501 541 568 159 212 18.3 63.2 18.6 Eastern Croatia***** 166 734 557 808 162 987 18.8 62.8 18.4 Croatia 754 634 2 828 632 834 889 17.1 64.0 18.9 *the City of Zagreb, the County of Zagreb ** Counties of Krapina-Zagorje, Sisak-Moslavina, Karlovac, Varaždin, Koprivnica-Križevci, Bjelovar-Bilogora, MeÄ‘imurje *** Counties of Istria, Primorje-Gorski kotar, Lika-Senj, ****Counties of Zadar, Å ibenik-Knin, Split-Dalmatia, Dubrovnik-Neretva *****Vukovar-Sirmium, Osijek-Baranja, Slavonski Brod-Posavina, Požega-Slavonia, Virovitica-Podravina Source: Census 2001, CBS. Tables 4.6 and 4.7 show the education structure of the Croatian regions. The inhabitants of certain counties and regions have been classified according to the education level into three groups: ï‚· Primary education (no school and elementary school) ï‚· Secondary education (high school) ï‚· Tertiary education (higher education and university level). The most prominent education level in Croatia is the high school or secondary education level (47.4 percent), with the lowest share of the higher school education and university levels of education (12.0 percent). The regions with the poorest education structure are the Central and Eastern Croatia, where almost half of the population has no school or have elementary education only. Higher and university educated population in these regions comprise 7 percent of total population. The extremely unfavorable education structure is recorded in County of Koprivnica-Križevci (58.2 percent of the population with primary education and 7.0 percent with higher school and university level education) and the County of Virovitica-Podravina (56.8 percent of the population with primary education and 5.8 percent with higher school and university level education). The highest proportion of the tertiary education level can be found in the Zagreb region (18.5 percent) and the Adriatic North (13.5 percent). 8 Table 1.6: Education by County, 2001, in % County of Primary Secondary Tertiary Zagreb 43.6 48.5 7.9 Krapina-Zagorje 53.0 41.1 5.8 Sisak-Moslavina 48.7 43.7 7.6 Karlovac 47.3 44.1 8.7 Varaždin 46.0 45.6 8.4 Koprivnica-Križevci 58.2 34.8 7.0 Bjelovar-Bilogora 54.9 38.5 6.6 Primorje-Gorski kotar 30.2 54.5 15.3 Lika-Senj 52.2 40.7 7.1 Virovitica-Podravina 56.8 37.4 5.8 Požega-Slavonia 53.4 39.9 6.8 Slavonski Brod-Posavina 49.7 43.4 6.9 Zadar 40.8 48.4 10.8 Osijek-Baranja 46.6 44.2 9.2 Å ibenik-Knin 42.8 47.6 9.5 Vukovar-Sirmium 51.5 41.8 6.7 Split-Dalmatia 34.0 52.4 13.6 Istria 36.9 50.5 12.6 Dubrovnik-Neretva 34.5 51.4 14.0 MeÄ‘imurje 48.3 45.2 6.6 City of Zagreb 25.1 52.3 22.6 Croatia 40.6 47.4 12.0 Source: Census 2001, CBS. Table 1.7: Education by region, 2001, in % Analytical regions Primary Secondary Tertiary Zagreb region 30.3 51.2 18.5 Central Croatia 50.5 42.1 7.3 34.7 51.7 13.5 Adriatic North 36.5 50.9 12.6 Adriatic South Eastern Croatia 50.0 42.4 7.6 Croatia 40.6 47.4 12.0 Source: Census 2001, CBS. Economic Structure The three most developed counties according to the GDP per capita are the City of Zagreb, the County of Istria and the County of Primorje-Gorski kotar. Tables 4.8 and 4.9 show the development level of the Croatian counties according to that indicator. In addition to the City of Zagreb, County of Istria and County of Primorje-Gorski kotar, only County of Koprivnica-Križevci in 2001 and 2002 and County of Lika-Senj in 2003 have reached the GDP per capita levels above the Croatian average. 9 At the regional level, the Zagreb region and Adriatic North have above average GDP p.c. and along with Adriatic South generate the highest increases in GDP levels. The least developed are Counties of Vukovar-Sirmium and Slavonski Brod-Posavina, where the GDP per capita levels reach less then 60 percent of the Croatian national average. It should be noted that some of the less developed counties generate below average growth levels of GDP (Counties of Krapina-Zagorje, Požega-Slavonia and Slavonski Brod-Posavina), and are therefore lagging even further in relation to the other counties (the last three columns in Table 4.8). Table 1.8: Gross Domestic Product per capita, by County, Croatia =100 Index Index Index County of 2001 2002 2003 2002/2001 2003/2002 2003/2001 Zagreb 67.9 77.1 74.2 125.1 106.5 133.3 Krapina-Zagorje 79.0 74.6 72.6 102.6 105.8 108.6 Sisak-Moslavina 86.8 81.2 77.0 101.7 103.2 104.9 Karlovac 84.9 85.4 77.7 109.1 98.7 107.7 Varaždin 95.1 98.1 94.2 112.5 104.6 117.6 Koprivnica-Križevci 103.5 101.9 95.8 107.2 102.5 109.9 Bjelovar-Bilogora 78.5 79.8 74.7 110.4 101.7 112.2 Primorje-Gorski kotar 117.5 112.5 118.1 104.6 114.8 120.2 Lika-Senj 80.2 90.9 103.4 122.9 124.1 152.5 Virovitica-Podravina 80.0 78.1 75.4 106.2 105.1 111.6 Požega-Slavonia 73.9 71.2 72.2 105.2 110.6 116.3 Slavonski Brod-Posavina 61.0 60.1 57.5 107.6 104.5 112.5 Zadar 72.1 73.4 80.1 112.4 120.7 135.8 Osijek-Baranja 77.6 80.1 75.3 112.7 102.6 115.6 Å ibenik-Knin 63.6 65.8 69.7 113.2 116.2 131.6 Vukovar-Sirmium 58.0 58.3 57.5 109.3 107.3 117.3 Split-Dalmatia 75.8 75.1 75.3 109.2 110.4 120.5 Istria 134.5 135.6 137.5 110.7 111.6 123.6 Dubrovnik-Neretva 90.2 86.8 88.4 105.7 111.8 118.2 MeÄ‘imurje 83.1 84.9 80.2 111.8 103.3 115.5 City of Zagreb 176.4 174.8 179.2 108.4 112.3 121.8 Croatia 100.0 100.0 100.0 109.4 109.5 119.8 Source: Project CBS-EIZG, Regional GDP preliminary results. Table 1.9: Gross Domestic Product per capita by regions, Croatia = 100 Index Index Index Analytical regions 2001 2002 2003 2002/2001 2003/2002 2003/2001 Zagreb region 145.5 146.8 148.9 110.7 111.4 123.3 Central Croatia 87.5 86.7 81.9 107.8 102.9 110.9 Adriatic North 120.2 118.9 123.8 108.3 114.1 123.6 Adriatic South 75.5 75.2 77.3 109.6 113.2 124.1 Eastern Croatia 69.7 70.0 67.4 109.6 104.9 115.0 Croatia 100.0 100.0 100.0 109.4 109.5 119.8 Source: Project CBS-EIZG, Regional GDP preliminary results. Tables 4.10 and 4.11 describe the employment structure according to the economic activities and unemployment rates. The economic activities have been separated into agriculture, i.e. the primary 10 sector (activities A and B), industry, i.e. the secondary sector (activities C, D and E) and services, i.e. the tertiary sector, further separated into the public sector (activities L, M and N) and other service sector (activities F, G, H, I, J, K, O and P). At the national level, the highest employment can be found in the service sector (45.7 percent), and lowest employment in agriculture (10.4 percent). Table 1.10: Employment Structure by Economic Activity and Unemployment Rate, by County, 2003, in % F, G, H, I, J, Unemployment County of A, B C, D, E L, M, N K, O, P rate* Zagreb 15.9 27.6 41.7 14.8 22.0 Krapina-Zagorje 25.5 28.8 28.6 17.1 16.3 Sisak-Moslavina 12.6 33.2 33.1 21.1 31.9 Karlovac 12.9 28.2 39.1 19.9 29.8 Varaždin 11.2 36.1 33.9 18.8 16.9 Koprivnica-Križevci 28.5 30.7 25.9 14.9 18.6 Bjelovar-Bilogora 35.0 22.6 26.4 16.0 26.0 Primorje-Gorski kotar 2.4 22.0 54.6 20.9 16.5 Lika-Senj 18.2 13.6 44.5 23.7 26.7 Virovitica-Podravina 26.0 27.1 29.0 17.8 30.9 Požega-Slavonia 20.8 27.7 30.1 21.4 25.4 Slavonski Brod-Posavina 18.1 25.3 37.0 19.6 32.7 Zadar 7.0 15.8 53.1 24.2 30.1 Osijek-Baranja 14.3 22.5 41.6 21.6 29.5 Å ibenik-Knin 5.6 22.5 48.1 23.8 35.4 Vukovar-Sirmium 24.5 16.1 38.1 21.3 36.2 Split-Dalmatia 3.9 20.7 52.9 22.5 28.4 Istria 3.9 23.5 54.1 18.6 11.3 Dubrovnik-Neretva 6.3 11.8 60.4 21.5 22.7 MeÄ‘imurje 25.0 29.2 32.0 13.9 15.6 City of Zagreb 1.4 19.9 55.0 23.7 12.5 Croatia 10.4 23.3 45.7 20.7 21.9 * registered unemployment, not ILO definition. Source: CBS. Croatia is characterized by significant differences in regional unemployment levels, outlined by the data in the last column of Table 4.10. On one hand, there are most developed counties with relatively low unemployment levels in comparison with the Croatian national average (21.9 percent in 2002.). Thus, the County of Istria has 11.3 percent unemployment rate, and the City of Zagreb 12.5 percent. On the other hand, certain counties are recording high unemployment levels, namely County of Vukovar-Sirmium (36.2 percent), County of Å ibenik-Knin (35.4 percent) and County of Slavonski Brod-Posavina (32.7 percent). Table 1.11: Employment Structure by Economic Activities, by Analytical Regions, 2003, in % F, G, H, I, J, Total Analytical regions A, B C, D, E L, M, N K, O, P employment Zagreb region 3.9 21.2 52.7 22.2 100.0 Central Croatia 20.9 30.3 31.4 17.5 100.0 Adriatic North 4.0 22.1 53.8 20.1 100.0 Adriatic South 5.0 18.6 53.6 22.8 100.0 Eastern Croatia 18.9 22.8 37.5 20.7 100.0 Croatia 10.4 23.3 45.7 20.7 100.0 Source: CBS. 11 The highest proportion of employment in agriculture can be found in Central Croatia (20.9 percent), where the leaders are Counties of Bjelovar-Bilogora (35.0 percent), Koprivnica-Križevci (28.5 percent), Krapina-Zagorje (25.5 percent) and MeÄ‘imurje (25.0 percent). The high proportion of employment in agriculture is also present in the traditional agriculture counties in Eastern Croatia. The Zagreb region, Adriatic North and Adriatic South have single-digit agriculture employment levels, with the lowest percentage recorded in the City of Zagreb (1.4 percent). Central Croatia is also characterized with the relatively highest proportion of employment in the industry sector (C, D, E). In this case, Counties of Varaždin and Sisak-Moslavina are the leaders with over a third of total employment in the industry sector. Other regions have similar proportions of industry employment (ranging from 18.6 percent to 22.8 percent). The lowest proportion of employment in the industry sector has been recorded in the County of Dubrovnik-Neretva (11.8 percent) and the County of Lika-Senj (13.6 percent). The Zagreb region, the Adriatic North and the Adriatic South have the highest share of the service sector. Over a half of total employment in these regions is in the service sector. The highest proportions have been recorded in the County of Dubrovnik-Neretva (60.4 percent) and the City of Zagreb (55.0 percent). The most equalized employment level can be found in the public sector. The highest proportions are in the County of Zadar (24.2 percent), County of Å ibenik-knin (23.8 percent), County of Lika-Senj and the City of Zagreb (both with 23.7 percent). Table 4.12 shows the approximation of labor productivity according to the regions in Croatia, measured by the relation of gross value added per employee. It should be emphasized that different data sources are used regarding the value added (national accounts data) and number of person employed (administrative data). Productivity calculated in that way therefore is treated only as indication of real productivity. Methodological issues and different data sources can influence the reliability of productivity indicator. Because of that, productivity indicator is not presented on the county, but only on region level. The only two regions with above-average productivity are the Zagreb region (17.4 percent above average) and North Adriatic (5.8 percent above average). The Zagreb region has above average labor productivity in all sectors, except the primary sector. Eastern and Adriatic North and South recorded above-average labor productivity in the primary sector. Table 1.12: Estimation of Labor Productivity by Economic Activities, by Analytical Regions, 2003, Croatia = 100 F, G, H, I, J, Analytical regions A, B C, D, E L, M, N Total K, O, P Zagreb region 93.5 133.9 115.1 103.9 117.4 Central Croatia 76.9 82.8 96.7 95.8 87.1 Adriatic North 144.8 121.4 97.4 97.4 105.8 Adriatic South 137.9 83.0 85.9 100.0 91.0 Eastern Croatia 120.9 67.2 86.7 99.2 88.8 Croatia 100.0 100.0 100.0 100.0 100.0 Source: Project CBS-EIZG, Regional GDP preliminary results. Table 4.13 shows the road and water infrastructure indicators for Croatian counties. Infrastructure equipment is an important prerequisite for economic development. The end of this section will show the correlation analysis results, attempting to identify the various factors relevant in explaining the regional development differences, i.e. identify the factors showing statistically significant correlation with the regional GDP per capita levels. GDP per capita has been alternatively linked with specific variables from various groups of explanatory factors. As data on GDP are available for period 2001- 2003 only, it is not possible to construct a strong econometric model implying causality in GDP and explanatory variables trends. Correlation coefficients are to be used as indication whether GDP and other variables are moving in the same or opposite direction. 12 Table 1.13: Infrastructure Development Indicators Waste waters Total water Road density in from public Number of inhabitants delivered to County of relation to surface sewage per road km users area (km/km2) (m3/household) (m3/household) 2001 2003 2001 2003 2001 2001 Zagreb 160.351 165.033 0.616 0.612 59.538 113.30 Krapina-Zagorje 151.231 153.034 0.763 0.758 32.949 10.69 Sisak-Moslavina 90.722 90.713 0.455 0.463 43.698 34.84 Karlovac 86.604 86.860 0.447 0.449 50.533 33.99 Varaždin 165.971 160.616 0.879 0.909 59.343 54.76 Koprivnica-Križevci 112.898 105.655 0.632 0.672 38.614 52.23 Bjelovar-Bilogora 90.706 88.652 0.540 0.564 25.392 26.35 Primorje-Gorski kotar 199.091 203.837 0.426 0.417 110.320 74.99 Lika-Senj 28.319 28.169 0.345 0.355 93.794 18.27 Virovitica-Podravina 102.418 101.996 0.446 0.451 34.747 26.03 Požega-Slavonia 116.637 118.388 0.398 0.397 37.322 29.98 Slavonski Brod- 192.001 191.209 0.444 0.455 29.105 23.16 Posavina Zadar 95.860 95.032 0.455 0.463 74.237 34.46 Osijek-Baranja 199.961 205.656 0.394 0.389 43.600 37.25 Å ibenik-Knin 92.696 94.293 0.404 0.403 80.236 38.06 Vukovar-Sirmium 196.658 200.969 0.411 0.413 39.315 18.43 Split-Dalmatia 185.232 186.813 0.545 0.546 93.797 63.74 Istria 110.839 112.308 0.660 0.650 121.130 52.75 Dubrovnik-Neretva 124.868 125.912 0.548 0.548 89.693 32.87 MeÄ‘imurje 212.866 214.286 0.748 0.756 39.880 16.01 City of Zagreb 1..039.215 1037.543 1.158 1.172 105.450 112.50 Croatia 155.792 155.689 0.497 0.501 71.688 - Source: CBS. The first group comprises structural variables, defined as the proportion of employed population in various economy sectors for each specific county. Sectors are defined in the same manner used in the explanations accompanying Tables 4.10 and 4.11. As shown in Table 4.14, it is evident that there is a statistically significant correlation between the proportion of employed in the primary sector and the size of GDP per capita in a specific county, a correlation with medium intensity and a negative sign (-0.46 for period 2001- 2003). In other words, less developed counties on average have higher employment levels in the primary sector. The proportion of employment in the secondary sector has not been identified as significant as an explanation for regional development, same as in the case of tertiary sector employment. However, the latter variable does show statistical correlation with the regional GDP per capita. When excluding the public sector employees from the sample, the correlation coefficient becomes significant, with a medium intensity positive sign (0.41). The correlation coefficient increases even further following the exclusion of tourist sector employees (0.47). Furthermore, the county infrastructure equipment levels also have a statistically significant correlation with the regional GDP per capita. In this analysis, all of the infrastructure variables included have shown a positive correlation with the level of regional GDP per capita, with medium and strong intensity. The correlation coefficient between the GDP per capita and the road density is 0.63, while in the case of the correlation with the total water delivered to users, the resulting value is 0.62. The education structure in specific counties has also been found as significant variable in explaining regional development differences.4 The correlation analysis has established a statistically significant correlation between the regional GDP per capita and the proportion of population with primary and tertiary education levels. The correlation coefficient in the first example has a negative sign and the 4 The education structure of the population in specific Croatian regions has been shown by Tables 4.6 and 4.7. 13 value of -0.59, while in the second case, an even stronger positive relationship has been established, with the coefficient value of 0.75. Table 1.14: Overview of Correlation Coefficients between County GDP p. c. and Various Variables Correlation between GDP p.c. and: 2001 2002 2003 2001-2003 Structural variables -0.45 -0.44 -0.50 -0.46 Employed in primary sector (-2.26)* (-2.22) (-2.61) (-4.09) Employed in tertiary sector (without 0.37 0.40 0.48 0.41 public service) (1.8) (1.93) (2.44) (3.61) Employed in tertiary sector (without 0.44 0.46 0.52 0.41 tourism) (2.19) (1.93) (2.74) (3.61) Infrastructure variables 0.67 0.67 0.61 0.63 Road intensity (4.06) (4.07) (3.42) (6.50) 0.59 0.62 0.71 0.62 Water (3.26) (3.54) (4.48) (6.37) Educational structure -0.59 -0.59 -0.63 -0.59 Primary education (-3.31) (-3.26) (-3.65) (-5.81) 0.77 0.76 0.79 0.75 High education (5.40) (5.18) (5.73) (9.01) Demographic structure -0.57 -0.59 -0.60 -0.57 Children (-3.10) (-3.28) (-3.31) (-5.51) 0.55 0.53 0.46 0.49 Working contingent (2.92) (2.79) (2.33) (4.53) *Note: in parentheses are t-statistics Source: Own calculations. Finally, the demographic structure is equally important in explaining of regional development discrepancies. A statistically significant correlation with the regional GDP per capita have the variables of the proportion of children in the total county population levels, and the level of working population, while the ratio of senior population has not been shown as significant. The correlation between the regional GDP per capita and the proportion of children (as an indicator of economically supported population) has a negative sign, with medium to strong intensity (-0.57). On the other hand, the working population has shown a positive relationship with the regional GDP per capita, also with a medium to strong intensity (0.49). SOURCES OF GROWTH OF THE CROATIAN COUNTIES – REGIONAL ECONOMY STRUCTURE ACCORDING TO SECTORS, ENTERPRISE SIZE AND OWNERSHIP This section analyses the relationship between the economic growth of certain counties on one hand, and the regional economy structure according to sectors, enterprise size and ownership on the other. The findings of this section research, in addition to the previously illustrated education and demographic indicators, as well as infrastructure capabilities indicators, provide a complete picture concerning the growth potential of certain Croatian counties. Economy Structure of Croatian Counties The experiences of the new EU member states show that the economy structure has a significant influence on the economy growth rates. The regions with a higher share of the tertiary sector (excluding the public sector) in the process of EU accession and transition into a market economy, are 14 experiencing higher rates of GDP growth. In regards to industry sector5 (industries C, D and E of NACE classification), the growth rates are dependant on the internal industrial structure (export orientation, technology transfer), rather than the total share of industry sector. The areas with a significant share of agriculture and public sector mainly experience slower growth in comparison to the average. This section analyses the relationship between the economy structure of the Croatian counties and the average rate of nominal growth in the period 2001-2003. The regional accounts system has started developing in Croatia only recently; therefore the data on the gross value added and GDP are available only in current prices. The real growth rates on the county level are not calculated at this point even for experimental purposes. Due to the differing regional economy structure not only in terms of sector distribution, but also the difference regional market conditions, the use of the national GDP deflator which does not reflect the differences in the levels and regional price trends in specific activities would not be justified. However, the analysis of the nominal GDP growth in various sectors brings us to some conclusion on the relationship between the economy structure and the growth rate. For analytical purposes, the activities have been grouped into five sectors. The primary sector includes agriculture (A) and fisheries (B). The secondary sector includes the processing industry with mining, manufacturing and electricity distribution (C, D and E). The tertiary sector has been separated into three sub-sectors. The first is comprised of services similar to manufacturing industry (construction, F) or activities that are closely related to product distribution (trade, G, transport and communications, I, and hotels and restaurants, H). The second sub-sector within the tertiary sector comprise financial services (J), business services (K), other personal services (O), and private households (P). The third service sub-sector in general comprises the government units, and includes public administration (L), education (M) and health (N). Table 4.15 shows the industry structure of gross value added in various counties in Croatia in the period 2001 - 2003. On the level of the total economy, the service sector (F, G, H and I) is dominant and comprises 33.3 percent of total value added. In all counties, apart from the Counties of Varaždin, Koprivnica- križevci, Sisak-Moslavina and MeÄ‘imurje, the proportion of this sector is the most significant. If financial, business, personal services and private households (industries J, K, O and P) are added, it is clear that the total tertiary sector (excluding public services) comprises 48.3 percent of total value added. As a rule, a higher proportion of the tertiary sector in the gross value added (GVA) is found in developed counties. In addition, some less developed counties close to the Adriatic Sea (for example, Counties of Zadar and Å ibenik-Knin) have a high share of tertiary sector (tourism)6. The development level of various counties is well illustrated by the proportion of the primary sector (A and B) in a way that less developed counties have a higher proportion of the primary sector in total value added. Primarily, this refers to the counties in Eastern and Central Croatia. Significant differences between counties in GVA proportions have been recorded in industry sector (C, D and E). Therefore the smallest proportion, just above 10 percent has been recorded in the County of Zadar (13.1 percent) and Dubrovnik-Neretva (11.7 percent), while the highest proportions have been recorded in the County of MeÄ‘imurje (35.7 percent), Koprivnica-Križevci (35.5 percent) and Sisak-Moslavina (32.4 percent). The relationship between the share of this sector and total development levels are not clearly identifiable. 5 Industry sector comprises mining and quarrying (C), manufacturing (D) and electricity supply (E). 6 More detailed sectoral breakdown of value added is presented in Appendix 1. 15 Table 1.15: Regional Distribution of GVA, Current Prices in the Period 2001-2003, in % County of A, B C, D, E F, G, H, I J, K, O, P L, M, N TOTAL Zagreb 15.0 30.5 35.9 7.1 11.5 100.0 Krapina-Zagorje 12.8 30.1 30.4 7.1 19.6 100.0 Sisak-Moslavina 12.0 32.4 28.3 8.0 19.3 100.0 Karlovac 10.0 25.4 37.5 8.7 18.4 100.0 Varaždin 11.8 32.1 28.5 9.5 18.1 100.0 Koprivnica-Križevci 21.8 35.5 22.6 6.9 13.2 100.0 Bjelovar-Bilogora 27.9 19.8 24.6 9.0 18.6 100.0 Primorje-Gorski kotar 2.3 23.5 41.7 14.8 17.6 100.0 Lika-Senj 17.0 19.0 37.2 6.4 20.3 100.0 Virovitica-Podravina 28.6 22.5 26.5 6.3 16.1 100.0 Požega-Slavonia 21.9 21.5 25.3 6.9 24.4 100.0 Slavonski Brod-Posavina 18.7 21.0 28.9 10.0 21.4 100.0 Zadar 10.1 13.1 40.0 14.4 22.3 100.0 Osijek-Baranja 19.3 18.4 29.6 12.3 20.3 100.0 Å ibenik-Knin 8.4 16.4 36.9 13.6 24.7 100.0 Vukovar-Sirmium 27.2 13.4 30.4 7.2 21.8 100.0 Split-Dalmatia 4.0 20.8 37.7 15.8 21.6 100.0 Istria 5.2 30.9 35.9 14.1 14.0 100.0 Dubrovnik-Neretva 8.4 11.7 39.9 17.3 22.7 100.0 MeÄ‘imurje 15.8 35.7 23.6 10.0 14.8 100.0 City of Zagreb 0.4 25.2 32.7 23.2 18.4 100.0 Croatia 8.7 24.6 33.3 15.0 18.4 100.0 Source: Author’s calculations. In continuation, Table 4.16 presents the average nominal GDP growth rates in the period 2001 - 2003 according to various sectors and counties. It is clear that the fastest growth has been recorded in the tertiary sector (except public administration). Thus , fastest growth, 19.0 percent, has been recorded in the business, financial and personal services. The sub - sector comprising of activities F, G, H and I in the analyzed period has increased at a very high average nominal rate of 16.9 percent. On the other hand, the nominal decrease in gross value added has been recorded in agriculture and fisheries (-2.4 percent). Slow nominal growth has been recorded in the public sector (L, M and N, 4.8 percent). In industry, the average nominal growth amounted to relative low 6.8 percent, but with significant differences across counties. Here, industrial production growth rates higher than 20 percent have been recorded in the Counties of Vukovar-Sirmium, Zagreb, Požega-Slavonia, Lika-Senj and Å ibenik- Knin, and on the other hand the largest decreases have been recorded in the County of Sisak- Moslavina (-7.5 percent) and Split-Dalmatia (-4.2 percent). It is evident that in industry sector the county structure of industrial manufacture is crucial since industry encompasses at the same time rapidly developing companies (publishing, part of capital products manufacture) but also decreasing traditional activities under the influence of the growing international competition (textiles, metal industry, etc.). 16 Table 1.16: Gross Value Added Average Nominal Growth Rate, Current Prices, in the Period 2001-2003, in % County of A, B C, D, E F, G, H, I J, K, O, P L, M, N TOTAL Zagreb 2.5 28.2 15.0 18.8 11.6 16.7 Krapina-Zagorje -4.4 8.4 5.9 15.5 2.8 5.3 Sisak-Moslavina -4.9 -7.5 19.2 4.2 6.9 3.5 Karlovac 3.6 10.2 0.4 15.8 2.3 4.9 Varaždin -1.5 0.0 26.2 20.7 6.3 9.6 Koprivnica-Križevci -1.3 4.0 12.4 21.1 4.7 6.0 Bjelovar-Bilogora -1.7 4.2 18.3 22.2 2.9 7.0 Primorje-Gorski kotar -0.2 0.6 16.4 20.8 6.6 10.8 Lika-Senj -2.7 24.9 52.6 26.1 4.0 24.8 Virovitica-Podravina -4.0 10.5 16.2 16.8 2.3 6.7 Požega-Slavonia -4.6 27.3 11.0 17.7 3.2 9.0 Slavonski Brod-Posavina -4.5 1.0 21.2 11.3 5.3 7.2 Zadar -2.0 13.7 31.9 17.5 6.5 17.8 Osijek-Baranja -3.2 5.7 19.5 16.8 3.9 8.7 Å ibenik-Knin -2.6 28.0 22.0 18.2 5.8 15.9 Vukovar-Sirmium -5.6 33.7 16.4 13.6 5.4 9.5 Split-Dalmatia -5.2 -4.2 23.1 16.7 5.3 10.9 Istria 2.3 14.0 10.7 22.3 7.8 12.4 Dubrovnik-Neretva -2.7 1.9 15.2 19.0 3.1 9.9 MeÄ‘imurje -4.6 8.4 17.0 18.5 5.0 8.6 City of Zagreb -0.3 6.0 15.3 19.9 3.3 11.5 Croatia TOTAL -2.4 6.8 16.9 19.0 4.8 10.6 Source: Author’s calculations. The highest average nominal growth rate has been recorded in the County of Lika-Senj (24.8 percent). It should be noted that during the analyzed period, this county benefited from intensive motorway construction, which had positive impacts not only on the construction industry, but on other industries, either directly (construction material manufacture, transport, wholesale retailing) or indirectly through increased spending by the temporary labor force (retail, hotels and restaurants, personal and business services). However, as motorway construction moves towards the Adriatic South, it is to be expected that the positive effect will be transferred to the southern counties (Zadar, Å ibenik-Knin, Split-Dalmatia), and that the County of Lika-Senj will experience the fate of the County of Karlovac which recorded very low growth rates after the finalization of the transport routes. Apart from the County of Lika-Senj, the other fastest growing counties were in central Dalmatia (Zadar 17.8 percent, Å ibenik-Knin 15.9 percent), and the County of Zagreb (16.7 percent). In the observed period, the first two counties benefited, apart from motorway construction, from rapid tourism growth. In the case of the County of Zagreb, there is a favorable economic structure and a favorable position surrounding the capital city. The proximity of the City of Zagreb and the cost aspects (lower property prices, lower tax burdens) have influenced entrepreneurship growth which is growing more rapidly in the proximity of Zagreb than in the city itself. The three most developed counties (the City of Zagreb, the Counties of Istria and Primorje-Gorski kotar) with their favorable economic structure have secured high and stable growth rates above Croatian average (10.6 percent). The highest average growth rate in that group was recorded in Istria (12.4 percent), following with the City of Zagreb (11.5 percent), and Primorje-Gorski kotar (10.8 percent). However, if the temporary motorway construction effects (the County of Lika-Senj), and the low basis phenomenon (tourism in central and southern Dalmatia) are excluded, it is clear that the most developed counties will continue to increase the difference in the development level in comparison to the rest of Croatia. 17 On the other hand, the less favorable economic structure (relatively high proportion of agriculture and companies not yet restructured) in some counties of Central (Counties of Krapina-Zagorje, Sisak- Moslavina and Karlovac), and Eastern Croatia (primarily Counties of Virovitica-Podravina and Slavonski Brod-Posavina, but others as well) represent a significant risk of further lagging behind. Table 4.17 shows the contribution to the GDP growth across various activity groups in Croatia in the period 2001-2003. Table 1.17: Contribution to Total Gross Value Added Growth, Current Prices, in the Period 2001-2003, in % of Total Nominal GVA Increase County of A, B C, D, E F, G, H, I J, K, O, P L, M, N TOTAL Zagreb 2.29 48.31 32.93 8.02 8.45 100.00 Krapina-Zagorje -10.82 47.21 33.91 19.37 10.33 100.00 Sisak-Moslavina -17.03 -73.75 143.61 9.58 37.58 100.00 Karlovac 7.12 54.22 2.79 27.10 8.77 100.00 Varaždin -1.91 1.63 71.40 19.84 12.30 100.00 Koprivnica-Križevci -4.89 24.21 46.96 23.12 10.59 100.00 Bjelovar-Bilogora -6.96 12.27 59.85 26.98 7.87 100.00 Primorje-Gorski kotar -0.04 1.37 61.27 26.56 10.84 100.00 Lika-Senj -2.00 18.18 73.87 6.42 3.53 100.00 Virovitica-Podravina -17.33 36.20 60.62 14.89 5.62 100.00 Požega-Slavonia -11.45 57.31 32.24 12.93 8.97 100.00 Slavonski Brod-Posavina -12.20 3.05 78.45 14.88 15.83 100.00 Zadar -1.20 10.83 67.96 13.89 8.52 100.00 Osijek-Baranja -7.53 12.30 62.77 23.16 9.29 100.00 Å ibenik-Knin -1.43 25.67 50.78 15.45 9.53 100.00 Vukovar-Sirmium -16.92 43.15 51.14 10.03 12.61 100.00 Split-Dalmatia -2.03 -8.32 76.11 23.58 10.66 100.00 Istria 0.98 33.45 32.32 24.27 8.97 100.00 Dubrovnik-Neretva -2.32 2.35 61.23 31.47 7.28 100.00 MeÄ‘imurje -8.87 34.98 44.86 20.10 8.92 100.00 City of Zagreb -0.01 13.76 42.32 38.44 5.49 100.00 Croatia -2.04 16.12 51.61 25.80 8.52 100.00 Source: Author’s calculations. It is clear that more than 50 percent of nominal gross value added increases originates from the growth of the sector which includes construction, retail, hotels and restaurants, and transport and communications (F, G, H and I). In all counties, except for Counties of Zagreb, Požega-Slavonia and Karlovac, the growth contribution of this sector is the most significant. If financial, business and personal services and private households are added (industries J, K, O and P), it is clear that the total tertiary sector (except public administration) comprises more than 75 percent of the growth of total gross value added. The negative contribution to the nominal increases to value added stems from the primary sector (A and B). This sector positively influences the increases of value added only in Counties of Karlovac, Istria and Zagreb. In terms of the secondary sector (C, D and E), it is clear that there are significant differences between various counties. On one side, there are counties with a favorable industry sector structure and a strong growth potential, while on the other side, there are non-restructured industrial manufacturers in certain counties even creating nominal reductions in total industrial manufacture. The high contribution of industrial manufacture to the total increases of gross value added has been recorded in the counties of Zagreb, Požega-Slavonia, Karlovac, Krapina-Zagorje and Vukovar-Sirmium. It should not be forgotten that in certain counties this is a result of low base phenomenon. On the other hand, the significant nominal reduction of gross value added in the industry sector has been recorded in the Counties of Sisak-Moslavina and Split-Dalmatia. 18 In the period observed, the sector containing the public units activities (L, M and N) has recorded low nominal growth (on the level of total economy even real decreases), and thus total nominal growth contributions are low. Clear demonstration of the relationship between the economy structure and the growth potential is given by Figure 4.2. It can be seen that the counties with a significant proportion of the tertiary sector (except public administration) have recorded on average higher nominal gross value added growth rates. The highest proportion of the tertiary sector (higher than 50 percent) has been recorded in the three most developed counties (the City of Zagreb, Istria and Primorje-Gorski kotar counties) and the counties in Adriatic South (Zadar, Split-Dalmatia, Å ibenik-Knin and Dubrovnik-Neretva). On the other hand, the lowest proportion of the tertiary sector (with a high proportion of the primary sector) has been recorded in the counties of Eastern and Central Croatia which are underdeveloped. Such economy structure in the middle run within the EU accession process could contribute to the widening of the inequalities among the Croatian counties. Figure 1.2: The Relationship between the Proportion of Tertiary Sector (except public administration) in gross value added and the nominal growth index in the period 2001-2003 60,0 55,0 Services, in % of GVA 50,0 45,0 40,0 35,0 30,0 25,0 20,0 0,0 5,0 10,0 15,0 20,0 25,0 30,0 Nominal growth rate Source: In continuation, other factors influencing the differences in growth rates of the Croatian counties are investigated. Primarily, this refers to the effects of small and medium entrepreneurship growth and the differences in the ownership structure. Economy Growth and Enterprise Size According to Counties This section analyses the economy structure of certain Croatian counties according to enterprise size. Economy structure data, according to the unit size are not officially calculated and published in Croatia even on the level of the national economy. Therefore, the author’s estimates based on various information sources are presented.7 For analytical purposes, the estimation of the economy structure has been formulated according to size and separated into four sectors. These are the small and medium enterprise sector, large entrepreneurs sector, financial institutions sector and the general government administration units sector. The small and medium enterprise sector has been separated into two sub-sectors: small and medium market producers (crafts, small and medium legal units), and 7 Primarily, this is the data set covering the FINA (financial agency) surveys, used in the official GDP calculations. The authors would like to thank the colleagues from DZS, and particularly Mrs. Maja Gorjan BregeÅ¡ for the help and assistance in data processing for the purposes of this research. 19 non-market producers (owner occupied dwellings and individual agricultural producers). Table 4.18 shows the average proportions of various sectors in the period 2001 - 2003. Table 1.18: Average Proportions in the GVA of Various Unit Groups According to Size in the Period 2001-2003 SME County of Large entrepreneurs Financial institutions Government units Total Market Non-market Zagreb 42.5 16.7 28.4 2.2 10.2 100.0 Krapina- 35.9 15.8 28.1 3.1 17.1 100.0 Zagorje Sisak- 19.7 15.5 43.7 3.2 17.9 100.0 Moslavina Karlovac 30.2 13.0 36.9 3.1 16.8 100.0 Varaždin 34.9 13.3 32.0 3.6 16.2 100.0 Koprivnica- 18.0 24.2 42.9 3.2 11.7 100.0 Križevci Bjelovar- 29.0 27.3 22.6 4.2 16.9 100.0 Bilogora Primorje- 39.4 6.2 33.7 4.6 16.1 100.0 Gorski kotar Lika-Senj 20.7 15.9 42.1 2.7 18.6 100.0 Virovitica- 18.1 25.0 39.0 3.1 14.7 100.0 Podravina Požega- 22.1 19.8 32.5 3.1 22.5 100.0 Slavonia Slavonski 30.8 20.2 25.6 3.7 19.7 100.0 Brod- Posavina Zadar 35.0 11.2 28.5 4.8 20.5 100.0 Osijek- 24.8 15.5 36.8 4.3 18.6 100.0 Baranja Å ibenik- 30.0 12.6 29.4 5.1 22.9 100.0 Knin Vukovar- 25.5 24.1 27.9 2.3 20.1 100.0 Sirmium Split- 41.9 7.6 25.8 4.6 20.1 100.0 Dalmatia Istria 39.9 8.8 34.1 4.5 12.8 100.0 Dubrovnik- 36.0 12.2 24.6 6.0 21.2 100.0 Neretva MeÄ‘imurje 40.0 16.8 26.3 3.8 13.1 100.0 City of 35.0 5.1 35.0 7.9 16.9 100.0 Zagreb Croatia 33.8 11.2 32.9 5.1 16.9 100.0 Source: Author’s calculations. The largest proportion of GVA is created by the small and medium market producers (33.8 percent). This is followed by the large entrepreneurs sector with 32.9 percent, and government units with 16.9 percent proportion. The smallest proportion, amounting to 5.1 percent in total gross value added, is recorded for financial institutions (banks and insurance) and the non market small producers (11.2 percent). Market oriented small and medium entrepreneurs have the most significant proportion in the County of Zagreb (42.5 percent), followed by the County of Split-Dalmatia (41.9 percent), MeÄ‘imurje (40.0 percent) and Istria (39.9 percent). On the other hand, the smallest proportion of this group has been recorded in the County of Koprivnica-Križevci (18.0 percent), Virovitica-Podravina (18.1 percent), and Sisak-Moslavina (19.7 percent). The low share of this sector (below 30 percent) has been 20 recorded in almost all of the counties in Eastern Croatia. All three most developed counties (The City of Zagreb, Counties of Istria and Primorje-Gorski kotar) have above-average share of this sector. The differences in non-market small producers’ proportions are mainly due to the differences in the proportions of agriculture producers, considering that the proportion of household owners (imputed dwelling rent) does not vary significantly across counties. Thus, the highest proportions have been noted in the Eastern and Central Croatia (Counties of Bjelovar-Bilogora, 27.3 percent, Virovitica- Podravina, 25.0 percent, Vukovar-Sirmium, 24.1 percent and Koprivnica-Križevci, 24.2 percent). Expectedly, the lowest share of this sector has been recorded in the three most developed counties. Due to the fact that the large enterprises includes public companies (INA, HEP, HP, HT) which are equally active in all parts of Croatia, low levels of proportional variation have been recorded in comparison to the small manufacturers. However, depending on the geographical position of the other large entrepreneurs (private or state owned) certain differences do exists. Thus, the smallest proportion of large entrepreneurs has been estimated in the County of Bjelovar-Bilogora (22.6 percent) and the largest for the County Sisak-Moslavina (43.7 percent). On the other hand, significant differences in the county proportions in the GVA have been registered in the financial sector (banks and insurance). The economic development differences, business profitability but also disposable income of households has a significant influence of the regional distribution of the financial services covering households and companies. Thus the highest proportions of this sector have been recorded in the City of Zagreb (7.9 percent) and the smallest in the County of Zagreb (2.2 percent). In this example, suggested explanation is that the business branches of the financial institutions in the City of Zagreb simultaneously serve households and entrepreneurs from the surrounding counties as well. In principle, it can be stated that there is a strong positive relationship between the proportion of the financial institutions sector and the development of a certain county. In addition, the counties in the costal regions have even higher financial sector proportion than indicated by their development levels. An explanation is that financial institutions try to service the needs of the domicile units and foreign tourists as well and therefore collect the foreign exchange deposits originating from tourism income. In terms of government administration units, it should be noted that the relative differences between the proportions of this sector in the GVA in certain counties are relatively smaller in comparison to the case of small entrepreneurs and financial institutions. Table 4.19 shows the average nominal growth rates of various sectors in the period 2001 - 2003. It is clear that on the total economy level, the highest nominal growth rate has been recorded in the financial institutions sector (19.2 percent), followed by sector of market small and medium enterprises (13.6 percent). The financial institutions sector has recorded double-figure nominal average growth rates in all counties except the Counties of Sisak-Moslavina (7.4 percent) and Slavonski Brod- Posavina (8.3 percent). The highest growth rate of this sector has been found in Counties of Split- Dalmatia (27.9 percent), Bjelovar-Bilogora (21.9 percent), and the City of Zagreb (21.8 percent), which also has the highest proportion of gross value added in this sector. The small market enterprises in the analyzed period have been experiencing stable high growth rates. The highest nominal growth (50.0 percent) has been recorded in County of Lika-Senj where it is evident that motorway construction has stimulated additional activities, with small and medium sector as the most flexible in that respect. According to growth rates, the County of Lika-Senj is followed by Counties of Å ibenik-Knin (23.6 percent) and Vukovar-Sirmium (23.3 percent). Small and medium entrepreneurs generated the least momentum in the County Virovitica-Podravina even with average nominal reductions, amounting to 0.6 percent annually. Low growth rates in this sector have also been recorded in Counties of Osijek-Baranja (4.5 percent) and Karlovac (7.2 percent). In the analysis of these indicators, the above average presence of the underground economy in the SME sector should be expected. Therefore the reported value added and hence the increases are most likely underestimated. The counties with a significant proportion of areas of special state concern with 21 significant tax incentives have recorded the highest value added growth rates in this sector (Counties of Lika-Senj, Vukovar-Sirmium and Å ibenik-Knin). Table 1.19: Average Nominal GVA Growth Rates in the Period 2001 - 2003, in % SME Large Financial Government County of Non- Total Market entrepreneurs institutions units market Zagreb 17.6 2.6 26.0 18.1 10.8 16.4 Krapina-Zagorje 12.7 -7.3 4.7 12.3 1.1 5.1 Sisak-Moslavina 17.7 1.1 -2.4 7.4 6.1 3.5 Karlovac 7.2 4.5 4.8 13.2 0.4 5.0 Varaždin 9.1 -1.6 16.3 16.8 5.0 9.5 Koprivnica-Križevci 8.8 0.6 7.1 21.7 4.0 5.9 Bjelovar-Bilogora 10.6 2.0 10.0 21.9 2.0 7.0 Primorje-Gorski kotar 12.9 1.4 11.0 15.3 5.5 10.4 Lika-Senj 50.0 1.0 34.3 14.6 3.6 24.1 Virovitica-Podravina -0.6 -0.4 16.1 17.4 1.5 6.6 Požega-Slavonia 8.8 -6.6 23.5 16.7 2.1 8.7 Slavonski Brod- 11.1 -2.6 12.0 8.3 4.4 7.0 Posavina Zadar 11.8 -7.4 47.7 16.9 5.7 17.1 Osijek-Baranja 4.5 3.5 16.7 11.6 2.9 8.6 Å ibenik-Knin 23.6 4.9 21.1 17.2 4.7 15.4 Vukovar-Sirmium 23.3 -2.3 11.4 16.3 4.4 9.3 Split-Dalmatia 16.3 -2.9 8.2 27.9 4.4 10.6 Istria 10.3 -0.9 18.5 17.8 6.8 11.9 Dubrovnik-Neretva 20.3 -3.5 7.3 15.9 2.1 9.6 MeÄ‘imurje 7.8 -2.1 19.9 14.1 2.9 8.4 City of Zagreb 14.9 4.8 11.2 21.8 1.6 11.2 Croatia 13.6 0.3 12.9 19.2 3.5 10.4 Source: Author’s calculations. Above average nominal growth rate has also been recorded in the large entrepreneurs sector. On one hand, the growth of income of large entrepreneurs is a result of the infrastructure cycle which is mainly undertaken by large entrepreneurs (construction), but also consolidation and value added growth rate (price liberalization) in the case of public companies (INA, HEP, HT). On the other hand, the counties with a significant proportion of the large, unstructured manufacturers (textiles industry, metal processing, etc.) have recorded low growth rates or even decreases of gross value added in the case of large entrepreneurs. Consequently, the largest value added increases among large entrepreneurs have been noted in the County of Zadar (47.7 percent) and the County of Lika-Senj (34.3 percent). Large entrepreneurs have demonstrated the worst results in the County of Sisak- Moslavina (nominal reduction of 2.4 percent), and low nominal growth rates were also recorded in Counties of Krapina-Zagorje (4.7 percent), Karlovac (4.8 percent), and Koprivnica-križevci (7.1 percent). Slow nominal growth (real reduction) on total economy level has been noted in the government administration units sector, and the small non-market manufacturers sector, where agriculture is the most significant. Such trends in these sectors are not unexpected. In the analyzed period, the bulk of the structural adjustments involved the consolidation of public finances, which explains the gross value added trends in the government administration units sector. The expected public sector reform, as well as further transition process towards market economy will definitely influence the slow growth of the government sector in the following period. In terms of non-market manufacturers, reduction of their proportions is to be expected, and partly a transformation into competitive market manufacturers. 22 From the above mentioned, it can be concluded that there is a positive relationship between the proportion of the market small and medium entrepreneurs in total gross value added and economy growth rates (see Figure 4.3). Financial institutions sector contributed to the rapid growth in the analyzed period, while counties with a higher proportion of government administration units and non- market producers have recorded lower rates of growth on average. Figure 1.3: Relationship between he Average Nominal Growth rate of the Total GVA and the proportion of Market Small and Middle Entrepreneurs in Total Gross Value Added 45,0 Market SME, in % of total GVA 40,0 35,0 30,0 25,0 20,0 15,0 0,0 5,0 10,0 15,0 20,0 25,0 30,0 Avarage nominal growth rate of total GVA Source: The Economic Growth and Ownership Structure According to Counties This section analyses the influence of ownership structure on the growth at the county level. The data concerning the ownership structure are not officially published; therefore the data used in this analysis represents the author’s estimates based on available data sources. For analytical purposes, the ownership structure has been classified into four sectors. These are the private ownership sector, public ownership sector, mixed ownership sector with the majority private stake and the mixed ownership sector with the majority public stake. Private property also includes the crafts sector, property owners and residents, privately-owned companies, and private financial institutions. The analysis used the data from FINA research, and since there is no statistical registry in Croatia which contains updated data concerning the ownership structure, this estimate should be considered as estimation only and not entirely accurate. Apart from the lack of a satisfactory statistical registry, an additional problem should be mentioned, concerning the related companies where it is very difficult to establish the final ownership structure. This is especially important in cases relating to state property where the registered owners are often various units owned by the government. In addition, the unsolved cases of property returns present further problems as well. Therefore, it remains questionable to what extent do the units filling in the statistical forms actually have full knowledge of the complete ownership structure. However, such estimates enable an insight into the relative importance of the private and the state property in various counties. Table 4.20 shows the estimated proportions of private and state ownership shown as the proportion of total gross value added in a certain county. The total proportion of private property on the total national economy level has been estimated at 69.0 percent, while the proportion of gross value added created by the state owned units in the same period amounted to 31.0 percent. The largest proportion of private property has been estimated in the County of MeÄ‘imurje, 79.1 percent in the period 2001 - 23 2003. The County of Zagreb had a slightly smaller proportion, 78.9 percent, followed by the County of Koprivnica-Križevci with 78.6 percent. On the other hand, the smallest proportion of private property has been estimated in the county of Lika-Senj (49.6 percent), followed by the Counties of Å ibenik-Knin (59.2 percent), Osijek-Baranja (66.0 percent) and Požega-Slavonia (66.1 percent). Table 1.20: Estimated GVA Proportion According to the Ownership Structure in the Period 2001-2003, in % of Total GVA for the County Private property State property Mixed, County of Mixed, mainly Full mainly Total Full Total state private Zagreb 73.5 5.4 78.9 20.0 1.1 21.1 Krapina-Zagorje 66.6 9.0 75.6 23.1 1.2 24.4 Sisak-Moslavina 48.2 20.4 68.6 28.4 3.0 31.4 Karlovac 63.2 9.1 72.4 25.3 2.3 27.6 Varaždin 63.0 10.4 73.4 24.6 2.0 26.6 Koprivnica-Križevci 55.5 23.1 78.6 19.9 1.5 21.4 Bjelovar-Bilogora 69.1 6.1 75.2 24.3 0.6 24.8 Primorje-Gorski kotar 61.2 6.9 68.1 28.9 3.0 31.9 Lika-Senj 44.1 5.6 49.6 48.5 1.8 50.4 Virovitica-Podravina 59.1 14.9 74.0 22.5 3.5 26.0 Požega-Slavonia 58.9 7.3 66.1 29.8 4.1 33.9 Slavonski Brod-Posavina 59.3 7.7 66.9 28.2 4.9 33.1 Zadar 64.0 6.1 70.1 29.1 0.9 29.9 Osijek-Baranja 57.4 8.6 66.0 31.2 2.8 34.0 Å ibenik-Knin 51.0 8.2 59.2 32.8 8.0 40.8 Vukovar-Sirmium 56.9 7.2 64.1 31.3 4.6 35.9 Split-Dalmatia 61.1 6.8 67.9 28.8 3.2 32.1 Istria 64.5 10.3 74.8 21.8 3.4 25.2 Dubrovnik-Neretva 52.8 9.4 62.2 31.2 6.6 37.8 MeÄ‘imurje 72.9 6.2 79.1 19.3 1.6 20.9 City of Zagreb 56.1 9.8 65.9 32.3 1.7 34.1 Croatia 59.6 9.4 69.0 28.5 2.5 31.0 Source: Author’s calculations. Table 4.21 shows the average annual nominal growth of gross value added according to the ownership structure in the period 2001 - 2003. It is clear that gross value added in the units with private owners (12.5 percent) grew at a much faster rate in comparison to the state owned units (5.7 percent). However, the interpretation of these estimates should be read with caution since there is a distinct possibility that a part of the units initially owned by the state have transferred ownership into private hands within the privatization process. In addition, it is possible that is some cases the failure to meet the payments to the government results in the government increasing its ownership share. In that way, some proportion of the difference in the growth rate most probably originates from the statistical reclassification. However, it can be concluded that in all counties, apart from the County of Zagreb, the gross value added of the units in private property is growing at a faster rate in comparison to the units in state ownership. 24 Table 1.21: Average Annual Nominal GVA Growth According to the Ownership Structure in the Period 2001-2003 Private ownership Government ownership County of Mixed, mainly Mixed, mainly Full TOTAL Full TOTAL private state Zagreb 17.9 -14.0 15.4 19.1 54.5 20.5 Krapina-Zagorje 14.4 -34.7 6.7 0.6 0.0 0.6 Sisak-Moslavina 7.9 4.6 6.9 2.2 -41.2 -3.2 Karlovac 7.4 4.1 7.0 0.1 -3.2 -0.1 Varaždin 12.9 20.0 13.7 0.6 -19.4 -1.1 Koprivnica-Križevci 10.0 -1.9 6.2 4.4 10.4 4.8 Bjelovar-Bilogora 10.0 -10.3 8.2 2.9 27.4 3.3 Primorje-Gorski kotar 14.0 -5.3 11.9 7.4 6.6 7.3 Lika-Senj 31.0 19.5 29.5 19.2 19.9 19.3 Virovitica-Podravina 16.1 -4.8 11.5 4.9 -57.2 -6.0 Požega-Slavonia 11.1 4.9 10.4 5.6 6.0 5.6 Slavonski Brod-Posavina 10.5 -15.2 7.3 4.7 16.4 6.4 Zadar 20.0 17.8 19.8 10.9 22.4 11.2 Osijek-Baranja 11.0 -0.6 9.4 6.9 8.4 7.0 Å ibenik-Knin 22.8 8.3 20.8 7.5 11.6 8.2 Vukovar-Sirmium 11.4 5.8 10.7 1.0 51.8 7.0 Split-Dalmatia 17.8 -9.6 14.7 0.4 25.1 2.7 Istria 14.3 0.7 12.2 3.5 112.1 11.0 Dubrovnik-Neretva 16.1 16.2 16.1 0.9 -5.4 -0.2 MeÄ‘imurje 11.2 -3.4 10.0 3.7 -6.3 2.8 City of Zagreb 18.8 -10.6 14.0 5.6 14.1 6.0 Croatia 15.4 -4.4 12.5 5.2 11.2 5.7 Source: Author’s calculations. The highest growth rate of private sector is recorded in the County of Lika-Senj with average annual nominal growth of 29.5 percent. It is followed by the County of Å ibenik-Knin (20.8 percent) and the County of Zadar (19.8 percent). The private sector exhibited the slowest growth in the Counties of Krapina-Zagorje (6.7 percent) and Koprivnica-križevci (6.2 percent). In the case of the ownership structure it can be concluded that faster growth of private ownership in comparison to state ownership can be expected, but it cannot be concluded that higher share of the private sector in itself ensures higher growth rates. Figure 4.4 shows that for instance, 15 percent growth rates are simultaneously achieved by the County of Zagreb with the private sector share of almost 80 percent and the County of Å ibenik-Knin with the proportion of private sector lower than 60 percent. Figure 1.4: The Relationship between the Gross Value Added Growth Rate and Private Sector Share 30 Avarage nominal growth rate of GVA 25 20 15 10 5 0 45,0 50,0 55,0 60,0 65,0 70,0 75,0 80,0 85,0 Private sector, in % GVA Source: 25 In conclusion, in terms of the structural characteristics of the Croatian counties, it can be stated that economic growth primarily depends on the economy structure according to the activities in a way that favorable economy structure, with a high share of the tertiary sector (except public administration) ensures the generation of high economic growth. Growth is significantly stimulated by propulsive small and medium market oriented entrepreneurs, and not own-account producers. A higher proportion of private property in the analyzed period has not shown itself to be the factor which individually ensures high growth rates. The probable cause is the fact that within private property there are two basic divisions, privatized and new-private. The majority of the research so far discusses the problems with a part of the privatized property (tycoonisation), while the situation is significantly better in the case of new property. However, on the aggregate level there are no clear conclusions. In terms of the structural characteristics the following can be concluded: ï‚· The most developed counties, the City of Zagreb, the County of Istria and Primorje-Gorski kotar according to the economy structure characterised by a high proportion of the tertiary sector and a relatively propulsive small and medium entrepreneurs’ sector, as well as a solid group of large entrepreneurs in both private and state ownership, have above average growth potential which could lead to further increases of regional development inequalities. ï‚· The large infrastructure projects contributes significantly to county growth where these are implemented, but the largest direct and indirect impacts are felt during the period wherein these projects are underway, followed by expectedly much slower growth rates. The best examples for this claim are the Counties of Karlovac and Lika-Senj. In the observed period, the County of Karlovac was in the final part of the infrastructural motorway construction cycle, and exhibited very low nominal increases, while motorway construction through the County of Lika-Senj was at the most intensive stage, which corresponds with the highest growth rates in this county. Therefore the effects of the projects can be considered to be temporary only. ï‚· The counties in Adriatic Croatia, in addition to the propulsive small and medium enterprises sector, as well as demographic and educational structure, also have extremely favorable economic structure which ensures above average growth in the future. However, it should be noted that the growth of the gross value added and the development of the SME sector is largely linked with the extremely positive tourism results in Croatia in the analyzed period. This also represents a certain level of risk in light of changing consumer preferences, but also this is a source of threat as tourism is volatile on a global level, therefore the economies of these areas are potentially in jeopardy. ï‚· The county which definitely has an enormous growth potential is the County of Zagreb, characterized by a favorable economic structure and extremely propulsive SME sector. In the analyzed period, this county was only in the initial phases of complete exploitation of its geographical position as the “ringâ€? surrounding the capital city. The relatively favorable cost aspects (property values, commercial spaces, housing, and lower taxes) as well as the proximity of the City of Zagreb make this area extremely attractive for entrepreneurs. ï‚· The analytical regions Central and Eastern Croatia are exposed to the largest risk of further lagging behind the most developed counties. The reasons for the smaller growth potential are relatively unfavorable economic structure (with high agriculture and non-market manufacturers share), war-related damages, and the slow developments in the process of restructuring the large companies (Table 4.22). 26 Table 1.22: Average Annual Growth Rates: GDP p.c. (2001-03), Population (2001-03) County of GDP Population Employment Counties with high convergence potential Zadar 17.8 1.0 2.4 Zagreb 16.7 0.9 3.2 Å ibenik-Knin 15.9 0.2 2.1 City of Zagreb 11.5 0.1 2.6 Split-Dalmatia 10.9 0.7 3.4 Istria 12.4 0.5 2.0 Counties with moderate convergence potential Lika-Senj 24.8 -0.6 10.4 Varaždin 9.6 -0.4 3.2 Dubrovnik-Neretva 9.9 0.3 -0.4 Primorje-Gorski kotar 10.8 -0.1 1.8 MeÄ‘imurje 8.6 0.0 3.1 Counties with moderate divergence risk Vukovar-Sirmium 9.5 -0.6 1.9 Osijek-Baranja 8.7 -0.2 0.9 Požega-Slavonia 9.0 -0.3 1.2 Bjelovar-Bilogora 7.0 -0.8 0.6 Koprivnica-Križevci 6.0 -0.5 1.4 Counties with high divergence risk Slavonski Brod-Posavina 7.2 -0.2 0.4 Virovitica-Podravina 6.7 -0.6 -1.9 Karlovac 4.9 -0.9 0.4 Krapina-Zagorje 5.3 -0.6 1.1 Sisak-Moslavina 3.5 -0.7 0.2 Source: CBS, author’s estimates. Underground Economy and Regional Development This section shows the results of the underground economy calculations (lower estimation boundary – Eurostat approach) in various counties in Croatia. Considering the fact that the regional GDP calculations are relatively new, therefore the data available only refers to the period 2001-2003, the underground economy estimation refers to this period as well. The results are given by Table 4.23. The methodological framework for the calculation of the underground economy on county level is influenced by the data availability. On one hand, there is data concerning regional gross value added and regional GDP separated according to activities, while on the other hand there is data describing the proportion of the underground economy according to activities, but only on the national level. It is for that reason that the regional division of the underground economy can only be executed by applying the proportions according to activity on a national level to all of the counties in Croatia. Figure 4.5 shows the size of the underground economy in various counties, i.e. the proportion of the underground economy in the GDP of various Croatian counties. Figure 1.5: Underground Economy Size According to County, 2002 (Eurostat Approach) 18,0 17,0 16,0 15,0 14,0 13,0 12,0 11,0 Vukovar-Sirmium Primorje-Gorski kotar Split-Dalmatia Sisak-Moslavina Bjelovar-Bilogora Virovitica-Podravina Slavonski Brod-Posavina Å ibenik-Knin Koprivnica-Križevci Lika-Senj MeÄ‘imurje Osijek-Baranja Varaždin Požega-Slavonia Dubrovnik-Neretva Karlovac City of Zagreb Istria Croatia Krapina-Zagorje Zagreb Zadar Source: 27 Table 1.23: Underground Economy Size in Various Counties in Croatia (lower estimation boundary – Eurostat approach), 2002, in HRK thousands Methodological Underground Total Correction percentage changes to the Total Correction County of Official GDP economy (N1- corrected including housing housing rent corrections percentage, in % N7) GDP rent, as % of GDP calculations Zagreb 9 839 1 128 457 1 584 11 423 11.5 16.1 Krapina-Zagorje 4 305 441 179 620 4 925 10.2 14.4 Sisak-Moslavina 6 097 643 293 936 7 033 10.6 15.4 Karlovac 4 895 584 228 812 5 707 11.9 16.6 Varaždin 7 371 780 318 1 098 8 469 10.6 14.9 Koprivnica-Križevci 5 146 522 257 778 5 924 10.1 15.1 Bjelovar-Bilogora 4 296 433 210 643 4 939 10.1 15.0 Primorje-Gorski kotar 14 021 1 696 695 2 391 16 412 12.1 17.1 Lika-Senj 1 974 187 95 281 2 255 9.5 14.2 Virovitica-Podravina 2 955 296 138 434 3 389 10.0 14.7 Požega-Slavonia 2 490 231 112 342 2 832 9.3 13.8 Slavonski Brod-Posavina 4 332 432 187 619 4 951 10.0 14.3 Zadar 4 916 569 237 806 5 722 11.6 16.4 Osijek-Baranja 10 777 1 119 517 1 636 12 413 10.4 15.2 Å ibenik-Knin 3 043 306 140 446 3 489 10.0 14.7 Vukovar-Sirmium 4 847 471 206 677 5 524 9.7 14.0 Split-Dalmatia 14 350 1 536 585 2 122 16 472 10.7 14.8 Istria 11 481 1 446 554 2 000 13 481 12.6 17.4 Dubrovnik-Neretva 4 379 452 195 647 5 026 10.3 14.8 MeÄ‘imurje 4 107 440 197 637 4 744 10.7 15.5 City of Zagreb 55 610 6 392 2 442 8 834 64 444 11.5 15.9 Croatia 181 231 20 102 8 242 28 344 209 575 11.1 15.6 Source: Author’s calculations. 28 In relation to the 2002 Croatian average of 15.6 percent of the underground economy in the total GDP, above average proportions of the underground economy have been recorded in the Counties of Istria (17.4 percent), Primorje-Gorski kotar (17.1 percent), Karlovac (16.6 percent), Zadar (16.4 percent), Zagreb (16.1 percent) and the City of Zagreb (15.9 percent). All other counties have recorded below average proportions of the underground economy in the official GDP. The lowest proportion has been observed in the Counties of Požega-Slavonia (13.8 percent) and Vukovar-Sirmium (14.0 percent). In continuation, we show the results of the correlation analysis which aimed to establish the factors influencing or linking the county differences in the underground economy size. These factors have been grouped in various groups. The first is the demographic structure of the counties. The proportions of various age categories have been taken for each county, i.e. children (population younger than 14 years of age), working contingent (female population between 15 and 59 years of age and male population between 15 and 64) and senior population (females older than 60, males older than 65). The second group of factors is the educational population structure. Depending on the education level, the population in each county has been separated into those with no education and with finished primary education, with finished secondary education and those with finished higher education programs and universities and masters levels, called tertiary education. The third group of factors is the economic structure of the economies in the counties. The economic structure is comprised on the basis of the proportions of employment in various activities in the total employment figures, and contains the employment in the primary (agriculture and fisheries, A+B), secondary (industry, C+D+E) and the tertiary sectors (services, G+H+I+J+K+L+M+N+O+P). The tertiary sector has been additionally separated into the group containing the public employees, those employed in education and health services, and others in the other group. The county differences in the size of the underground economy have been examined in comparison with some other factors. Primarily these are the total tax incomes of the local authorities, as the approximation of the tax burden across counties. Another analysis involved examining the link between the underground economy according to counties and the development levels (measured by the regional GDP), and the county differences in the unemployment levels. The correlation analysis results are given in Table 4.24. Table 1.24: The Correlation Coefficients between Certain Variables and County Proportions of the Underground Economy in the GDP Figure Variable Correlation coefficient Demographic structure Children -0.53* Working contingent 0.67* Seniors -0.22 Education structure Lower qualification level -0.75* Middle qualification level 0.76* High and higher qualification level 0.65* Economic structure Employment ratio in the primary sector -0.70* Employment ratio in the secondary sector -0.08 Employment ratio in the tertiary sector 0.56* Employment ratio in the tertiary sector, except government services 0.66* Employment ratio in the tertiary sector, except tourism and governmnt. services 0.69* Total local authority tax income as a % of GVA 0.71* Per capita GDP 0.55* Note: * 5 percent significance level. Source: Author’s calculations. 29 Regarding demographic structure, statistically significant relationship can be found in the case of variables children and the working contingent. With the educational structure of the Croatian counties, all of the variables have shown a statistically significant and strong relationship with the county differences in the size of the underground economy. The middle, high and the highest qualifications have positive signs, indicating that on average, the Croatian counties with a more favorable education structure have higher levels of the underground economy. The most interesting results refer to the relationship between the underground economy and the economy structure of certain Croatian counties. The counties with higher ratios of population employed in the primary sector, on average exhibit lower proportions of the underground economy. The relationship between employment in the secondary sector and the size of the underground economy is weak and not statistically significant. However, the relationship between the tertiary sector and the size of the underground economy is significant and medium strong positive sign. This implies that the counties with higher shares of the service sector have on average higher proportions of the underground economy. This relationship is strengthened if the scope of the tertiary sector excludes the public services, education and health (correlation coefficient 0.66), and if in addition, one excludes tourism as well (0.69). The tax income is also statistically significantly correlated with the size of the underground economy in various Croatian counties. The correlation coefficient is 0.71 with a positive sign, confirming the theoretical assumption that one of the main reasons for the growth of the underground economy is the increases in the tax burden. The more developed counties on average have higher proportions of the underground economy. The correlation coefficient between the county development level, measured by the per capita GDP and the size of the underground economy is 0.55. SECONDARY DISTRIBUTION OF INCOME Tables 4.25, 4.26 and 4.27 show gross disposable income (GDI), primary income, and the disposable income and GDP ratios per county and regions.8 These indicators are significant for the identification of the sectoral distribution of regional value added. The influence of the redistribution policies is also presented. As can be seen from Table 4.25 process of income redistribution significantly reduces the difference measured by GDP p.c. between the most developed county (City of Zagreb) and the least developed counties (County of Vukovar-Sirmium in 2001 and 2002, County of Slavonski Brod – Posavina in 2003). The ratio between the most and the least developed county in terms of GDP p.c. was 3.04 (2001) to 3.08 (2003), and in terms of household GDI p.c. the ratio was 1.59 (2001) to 1.69 (2003). The higher ratio between the disposable and primary income of the household sector indicates higher net income transfers to the region (increased by the social and other transfers and reduced by taxes on income and social security contributions) within the secondary income distribution process. In the Croatian economy, the highest indicator has been recorded in Counties of Vukovar-Sirmium (117.9 in 2001, 116.0 in 2002 and 115.1 in 2003), Slavonski Brod-Posavina (114.8, 112.9 and 113.0), Lika-Senj (113.4, 111.6 and 106.6), and Å ibenik-Knin (116.9, 113.4 and 112.6). This is an expected result, since these are the less developed counties, but also counties with the highest proportion of the population in areas of special state concern status. On the other hand, the highest net provider is the City of Zagreb. The lowest ratio 8 Primary income records gross wages and salaries, gross operating surplus (consumption of fixed capital included), mixed income and property income. Disposable income is derived from primary income after adding and subtracting all secondary distribution transaction (social transfers, other transfers, taxes and social security contributions). More about the concept of primary and disposable income see in ESA 1995 or SNA 1993. 30 between the disposable income and primary income has been recorded in the City of Zagreb (87.3 in 2003), followed by Counties of Zagreb (91.3), Istria (92.6) and Primorje-Gorski kotar (95.9). Table 1.25: Gross Disposable Income of Households per capita, by county, Croatia =100 County of 2001 2002 2003 2002/2001 2003/2002 2003/2001 Zagreb 100.4 101.2 100.9 105.8 107.6 113.8 Krapina-Zagorje 93.3 93.0 91.7 104.6 106.3 111.2 Sisak-Moslavina 95.0 95.3 94.4 105.3 106.8 112.5 Karlovac 93.3 96.5 96.3 108.5 107.6 116.8 Varaždin 95.6 97.3 95.4 106.8 105.7 112.9 Koprivnica-Križevci 102.8 103.2 102.8 105.3 107.4 113.1 Bjelovar-Bilogora 95.4 95.3 96.3 104.8 109.0 114.3 Primorje-Gorski kotar 109.3 109.5 109.8 105.1 108.2 113.7 Lika-Senj 96.8 100.0 104.3 108.3 112.6 121.9 Virovitica-Podravina 91.9 90.1 89.0 102.8 106.5 109.5 Požega-Slavonia 88.7 87.7 84.5 103.7 103.9 107.8 Slavonski Brod-Posavina 79.4 77.7 76.5 102.7 106.2 109.0 Zadar 89.9 88.1 88.1 102.9 107.8 110.9 Osijek-Baranja 90.7 90.0 89.7 104.0 107.5 111.9 Å ibenik-Knin 87.9 88.4 88.8 105.6 108.4 114.5 Vukovar-Sirmium 81.6 81.1 80.4 104.4 106.9 111.5 Split-Dalmatia 88.1 87.3 87.2 103.9 107.7 111.9 Istria 115.5 116.5 114.4 105.8 106.0 112.1 Dubrovnik-Neretva 96.3 96.4 94.5 105.1 105.7 111.1 MeÄ‘imurje 86.2 85.9 86.2 104.5 108.3 113.1 City of Zagreb 126.7 126.6 129.0 104.9 109.9 115.3 Croatia 100.0 100.0 100.0 104.9 107.9 113.2 Source: The disposable income, as the broadest measure of household current purchasing power, in relation to GDP, apart from the aspect of secondary income distribution, encompasses the aspect of value added distribution among the residential and non-residential households inhabiting the county. It also encompasses the aspect of value added distribution between the various institutional sectors, households, government, entrepreneurs and the foreign sector. The lowest ratio between disposable income and GDP has been recorded in the City of Zagreb. There are numerous factors influencing the value of this indicator. The first is the already mentioned distribution policy. The second factor is the significant number of residents of neighboring counties employed in the City of Zagreb, thus according to the residential rules, GDP is recorded in the residence of the producers, and the household income in the region where the residential employee household is located. The third factor relates to the distribution of value added between the households and the entrepreneurs. The City of Zagreb is the location of domestic and foreign companies with high profits (banks, insurance companies, large state companies, successful foreign-owned companies), therefore a significant proportion of value added is not allocated to the household sector, but is allocated to non-household owners (government, entrepreneurs, abroad) through the income distribution. 31 Apart from the City of Zagreb, the below-average levels of this indicator have been recorded in other counties with the above average GDP per capita: Counties of Istria and Primorje-Gorski kotar. On the other hand, from the household viewpoint, the most favorable ratio has been recorded in Counties of Vukovar-Sirmium, Å ibenik-Knin, Slavonski Brod-Posavina and Zagreb. Table 1.26: Some Derivative Indicators on Disposable Income by Households, Primary Income and GDP by counties, ratio in % Disposable income/primary income Disposable income/GDP County of 2001 2002 2003 2001 2002 2003 Zagreb 94.1 92.2 91.3 96.4 82.1 83.8 Krapina-Zagorje 102.0 100.2 99.5 76.9 77.9 77.8 Sisak-Moslavina 108.6 106.5 106.6 71.3 73.4 75.5 Karlovac 107.1 104.3 103.2 71.6 70.6 76.3 Varaždin 100.7 98.3 97.9 65.5 62.0 62.4 Koprivnica-Križevci 100.0 98.9 98.9 64.8 63.3 66.1 Bjelovar-Bilogora 105.4 104.5 103.8 79.2 74.7 79.4 Primorje-Gorski kotar 98.5 96.4 95.9 60.6 60.9 57.3 Lika-Senj 113.4 111.6 106.6 78.7 68.7 62.1 Virovitica-Podravina 108.3 107.5 109.0 74.9 72.1 72.7 Požega-Slavonia 108.2 105.4 106.1 78.2 77.0 72.1 Slavonski Brod-Posavina 114.8 112.9 113.0 84.8 80.9 81.9 Zadar 107.5 105.9 104.4 81.3 75.1 67.7 Osijek-Baranja 107.4 105.4 104.7 76.2 70.3 73.4 Å ibenik-Knin 116.9 113.4 112.6 90.0 84.0 78.6 Vukovar-Sirmium 117.9 116.0 115.1 91.6 87.0 86.1 106.5 102.9 101.8 75.8 72.7 71.4 Split-Dalmatia Istria 94.3 92.5 92.6 56.0 53.7 51.3 104.8 101.5 100.0 69.6 69.4 65.8 Dubrovnik-Neretva MeÄ‘imurje 101.7 99.9 99.3 67.6 63.2 66.3 90.4 88.2 87.3 46.8 45.3 44.4 City of Zagreb Croatia 100.6 98.4 97.6 65.2 62.5 61.6 Source: Project CBS-EIZG, Regional GDP preliminary results. At the level of analytical regions, it is evident that the indicator of the ratio between disposable income and primary income indicate the development level of a specific region to a great extent, meaning that a higher indicator implies lower regional development. Therefore, the indicator is the highest in the case of Eastern Croatia, and the lowest for Zagreb region. The strong link can also be established between the development level and the ratio of disposable income and GDP. In comparison to the EU member countries, Croatia, according to the estimated indicators, has significantly high ratio between the total disposable income and primary income (97.6 perecnt in 2003). 32 The EU average in 2001 was 87 percent.9 Mainly, this originates from the high value of the estimated transfers from abroad. If the value of transfers received from abroad were to be excluded from the calculation, then this indicator would be slightly above the EU average at 91.5 percent. Due to the same reason, the ratio between the disposable income of the household sector and GDP is also higher than the EU average, with 65.2 percent in Croatia and 61 percent in the EU (both for 2001). However, this indicator in the EU member countries is demonstrating same characteristics as evident in the case of Croatia. The more developed regions have noted lower values of ratios between disposable income and primary income, as well as disposable income and GDP. Table 1.27: Some Derivative Indicators on Disposable Income by Households, Primary Income and GDP by analytical regions, ratio in % Disposable income/primary income Disposable income/GDP Analytical regions 2001 2002 2003 2001 2002 2003 Zagreb region 91.3 89.1 88.2 53.4 50.8 50.0 Central Croatia 103.7 101.8 101.3 70.5 68.8 71.3 Adriatic North 97.9 96.0 95.5 59.9 58.4 55.2 Adriatic South 107.6 104.5 103.3 77.3 73.9 70.6 Eastern Croatia 111.0 109.1 108.9 80.7 76.1 77.1 Croatia 100.6 98.4 97.6 65.2 62.5 61.6 Source: Project CBS-EIZG, Regional GDP preliminary results. Tables 4.28 and 4.29 show the regional data on the social transfer ratios (subcategory at the secondary income distribution account) in the household disposable income, primary income and GDP. Social transfers include pensions, social care, child allowance, health insurance compensations and the unemployment benefits10. According to the sum of all social transfers, the County of Å ibenik-Knin has highest share of social transfers received. This county is followed by the County of Vukovar-Sirmium, thus it can be concluded that all of the indicators observed are in an inverse proportional relationship with the economic development level. The Spearman's rank correlation analysis between the indicators of the ratios of social transfers in GDP and GDP per capita of certain counties has shown a negative relationship (at the 5 percent significance level, the resultant coefficient was significant, with the value of -0.70). The significance of the negative correlation has been confirmed by the correlation analysis between the ratio of social transfers in primary income and GDP per capita (-0.42), while in the third case the correlation is insignificant, albeit with a negative sign (-0.22). In addition to Counties of Å ibenik-Knin and Vukovar-Sirmium, the highest ratio of social transfers in the primary income can be found in Counties of Slavonski Brod-Posavina, Lika-Senj, Split-Dalmatia and Zadar. It leads to the conclusion that according to this criterion, the regions with the highest social transfer income are the Eastern and Adriatic Croatia. The lowest ratio of social transfers in primary income in 2003 was identified in Counties of Zagreb (17.6 percent), Koprivnica-Križevci (17.9 percent) and MeÄ‘imurje (20.0 percent). The three last mentioned counties have also recorded the lowest proportion of social transfers in disposable income. According to this indicator, the order changes somewhat in relation to the previous 9 According to Eurostat: Income of private households and gross domestic products in Europe's regions, Statistics in focus, 2003. 10 Structure of disposable income in more detail is presented in Appendix 2. 33 indicator. The first is still the County of Å ibenik-Knin (32.1 percent in 2003), followed by Counties of Split-Dalmatia (28.6 percent), Vukovar-Sirmium (28.3 percent), Zadar (27.8 percent), Slavonski Bro- Posavina (27.6 percent and Lika-Senj (27.4 percent). This clarifies the conclusion that Adriatic Croatia has the highest total proportion of social transfers in disposable income. It is interesting to note that the City of Zagreb has also recorded an above average proportion of social transfers in disposable income (25.3 percent), despite the highest GDP per capita level in Croatia. Primarily, this is a consequence of the significant proportion of pension supplements, which are mostly not dependant on the social status of the recipients. Finally, the highest proportion of social transfers in GDP is found in Eastern Croatia (20.4 percent in 2003), where Counties of Vukovar-Sirmium and Slavonski Brod-Posavina county have notably high proportions. High proportions have also been recorded in certain counties of the Adriatic South (County of Å ibenik-knin, 25.2 percent). The lowest proportion of social transfers in GDP has been noted in the the City of Zagreb (11.2 percent), the County of Istria (11.5 percent), County of Koprivnica-Križevci (12.0 percent in 2003) and the County of MeÄ‘imurje (13.3 percent). Table 1.28: Social Transfers Relations to Primary Income, Disposable Income and GDP by counties, in % Social transfers/ primary Social transfers/ disposable Social transfers/GDP County of income income 2001 2002 2003 2001 2002 2003 2001 2002 2003 Zagreb 19.2 18.4 17.6 20.4 20.0 19.3 19.6 16.4 16.2 Krapina-Zagorje 23.8 23.3 22.7 23.3 23.2 22.8 17.9 18.1 17.7 Sisak-Moslavina 30.5 29.6 29.2 28.1 27.8 27.4 20.1 20.4 20.7 Karlovac 31.2 29.5 28.3 29.1 28.2 27.4 20.8 19.9 20.9 Varaždin 23.9 22.5 22.3 23.7 22.9 22.7 15.5 14.2 14.2 Koprivnica-Križevci 18.6 18.1 17.9 18.6 18.3 18.1 12.0 11.6 12.0 Bjelovar-Bilogora 23.1 22.9 21.8 21.9 21.9 21.0 17.4 16.3 16.7 Primorje-Gorski kotar 27.5 26.8 25.5 27.9 27.8 26.6 16.9 16.9 15.2 Lika-Senj 33.9 32.6 29.2 29.9 29.2 27.4 23.5 20.1 17.0 Virovitica-Podravina 24.8 24.8 25.5 22.9 23.1 23.4 17.2 16.7 17.0 Požega-Slavonia 27.2 25.8 26.3 25.1 24.5 24.8 19.7 18.9 17.9 Slavonski Brod- 32.3 31.4 31.2 28.2 27.8 27.6 23.9 22.5 22.6 Posavina Zadar 30.8 30.2 29.0 28.6 28.5 27.8 23.3 21.4 18.8 Osijek-Baranja 29.3 28.3 27.3 27.3 26.8 26.1 20.8 18.9 19.2 Å ibenik-Knin 39.6 37.6 36.1 33.9 33.2 32.1 30.5 27.9 25.2 Vukovar-Sirmium 34.3 33.3 32.6 29.1 28.7 28.3 26.7 24.9 24.4 Split-Dalmatia 32.5 30.6 29.1 30.5 29.7 28.6 23.2 21.6 20.4 Istria 21.7 21.3 20.8 23.0 23.0 22.5 12.9 12.4 11.5 Dubrovnik-Neretva 28.1 26.4 25.8 26.8 26.0 25.7 18.7 18.1 16.9 MeÄ‘imurje 21.2 20.8 20.0 20.9 20.8 20.1 14.1 13.2 13.3 24.3 23.6 22.1 26.9 26.8 25.3 12.6 12.1 11.2 City of Zagreb Croatia 26.5 25.5 24.5 26.3 26.0 25.1 17.1 16.2 15.5 Source: Project CBS-EIZG, Regional GDP preliminary results. The negative correlation between social transfers, as source of disposable income of households and the level of economic development can be seen in Figure 4.6. Figure 1.6: The Relationship between Social Transfers and Economic Development of Croatian Counties 34 190 170 GDP p.c., Croatia = 100 150 130 110 90 70 50 10 15 20 25 30 social transfers, as % of GDP Source: Table 1.29: Social Transfers Relations to Primary Income, Disposable Income and GDP by Analytical Regions, in % Social transfers/ primary Social transfers/ disposable Social transfers/GDP income income Analytical regions 2001 2002 2003 2001 2002 2003 2001 2002 2003 Zagreb region 23.1 22.4 21.0 25.3 25.1 23.8 13.5 12.8 11.9 Central Croatia 24.9 24.1 23.4 24.0 23.6 23.1 16.9 16.3 16.5 25.7 25.0 24.0 26.2 26.1 25.1 15.7 15.2 13.9 Adriatic North Adriatic South 32.3 30.7 29.4 30.0 29.4 28.5 23.2 21.7 20.1 30.1 29.2 28.8 27.1 26.8 26.4 21.9 20.4 20.4 Eastern Croatia Croatia 26.5 25.5 24.5 26.3 26.0 25.1 17.1 16.2 15.5 Source: Project CBS-EIZG, Regional GDP preliminary results. The largest category within the social transfers is pensions. Table 4.30 shows the proportion of pensions in the total pension amount in Croatia, as well as the significance of pension income in the total disposable income of a certain county. Apart from the demographic structure, the proportion of pensions in the total disposable income depends considerably on the proportion of disabled and retired war veterans in the county's total population. Furthermore, it depends on the structural problems of certain counties influencing the lower levels of primary income (wages, mixed income, proprietor's income) which influences the proportion of pension income in the total disposable income. Table 1.30: Pension Income Regional Distribution in Croatia Proportion of county's pensions in the Proportion of pension income in total total national pensions disposable income County of 2001 2002 2003 2001 2002 2003 35 Zagreb 5.2 5.3 5.3 12.4 12.3 12.1 Krapina-Zagorje 2.6 2.6 2.6 14.2 14.4 14.4 Sisak-Moslavina 4.2 4.2 4.2 17.6 17.7 17.8 Karlovac 3.3 3.3 3.3 18.5 18.1 17.8 Varaždin 3.4 3.4 3.4 14.3 14.0 14.1 Koprivnica-Križevci 1.8 1.8 1.9 10.5 10.6 10.7 Bjelovar-Bilogora 2.1 2.2 2.2 12.5 12.7 12.5 Primorje-Gorski kotar 8.7 8.7 8.6 19.3 19.3 18.6 Lika-Senj 1.4 1.4 1.4 20.2 19.9 18.8 Virovitica-Podravina 1.5 1.4 1.5 12.5 12.8 13.3 Požega-Slavonia 1.5 1.5 1.5 14.3 14.4 14.9 Slavonski Brod-Posavina 3.0 3.0 3.0 15.7 16.1 16.3 Zadar 3.5 3.5 3.6 18.0 18.1 18.0 Osijek-Baranja 6.6 6.6 6.6 16.2 16.4 16.2 Å ibenik-Knin 2.8 2.8 2.8 20.7 20.4 20.0 4.0 4.0 4.0 17.8 17.9 17.9 Vukovar-Sirmium Split-Dalmatia 10.6 10.5 10.4 19.0 18.9 18.4 5.0 5.1 5.0 15.5 15.5 15.2 Istria Dubrovnik-Neretva 2.7 2.7 2.7 16.6 16.5 16.6 1.5 1.5 1.5 10.9 11.2 10.9 MeÄ‘imurje City of Zagreb 24.6 24.6 24.4 18.4 18.4 17.5 Croatia 100.0 100.0 100.0 16.6 16.6 16.3 Source: Project CBS-EIZG, Regional GDP preliminary results. As evident, the lowest proportion of pensions in the total disposable income has been recorded in Counties of Koprivnica-Križevci (10.7 percent in 2003), MeÄ‘imurje (10.9 percent) and Zagreb (12.1 percent). On the other hand, the proportion of pension in the total disposable income of the household income sector is the highest in Counties of Å ibenik-Knin (20.0 percent) and Lika-Senj (18.8 percent). As opposed to total social transfers, pensions are positively correlated to economic development (Figure 4.7). It can be explained by the way how individual pension is determined. The amount of individual pension primarily depends on period in which contributions are paid, as well as the wage level. As the average wage was higher in the more developed regions, the pensions are also above average in the most developed regions. Figure4.8 presents even stronger negative correlation of economic development of Croatian counties and the share of social transfers in disposable income, when pensions are excluded from social transfers. Figure 1.7: The Relationship between Figure 1.8: The Relationship between Pensions and Economic Development of Social Transfers, without Pensions and Croatian Counties Economic Development of Croatian Counties 36 190 190 170 170 GDP p.c., Croatia = 100 GDP p.c., Croatia = 100 150 150 130 130 110 110 90 90 70 70 50 50 6 8 10 12 10 15 20 25 social transfers, w ithout pensions, as % of pensions, as % of disposable income disposable income Source: Source: Apart from the pensions and health insurance compensations, the most significant items of social transfers in Croatia are social welfare (social care allowances), unemployment benefits and child allowances. Tables 4.31 and 4.32 show the number of social welfare beneficiaries. Table 1.31: Number of Social Welfare Beneficiaries, by counties, 2003 Number of social Proportion of social welfare beneficiaries County of Population welfare beneficiaries in the total population (%) Zagreb 316 011 3 518 1.1 Krapina-Zagorje 140 521 1 517 1.1 Sisak-Moslavina 182 838 9 079 5.0 Karlovac 139 113 6 464 4.6 Varaždin 183 214 3 551 1.9 Koprivnica-Križevci 123 169 3 299 2.7 Bjelovar-Bilogora 130 836 4 301 3.3 Primorje-Gorski kotar 305 139 3 125 1.0 Lika-Senj 52 988 1 276 2.4 Virovitica-Podravina 92 200 4 753 5.2 Požega-Slavonia 85 414 3 200 3.7 Slavonski Brod-Posavina 176 221 9 098 5.2 Zadar 165 757 4 496 2.7 Osijek-Baranja 328 803 14 454 4.4 Å ibenik-Knin 113 644 12 785 11.3 Vukovar-Sirmium 202 488 7 232 3.6 Split-Dalmatia 471 017 8 200 1.7 Istria 208 627 1 336 0.6 Dubrovnik-Neretva 123 863 1 967 1.6 MeÄ‘imurje 118 429 5 797 4.9 City of Zagreb 780 019 12 067 1.5 Croatia 4 440 311 121 515 2.7 Source: Ministry of Health and Social Welfare. Table 1.32: Number of Social Welfare Beneficiaries, by Analytical Regions, 2003 Proportion of social Number of social Analytical regions Population welfare beneficiaries in welfare beneficiaries the total population (%) Zagreb region 1 096 030 15 585 1.4 37 Central Croatia 1 018 120 34 008 3.3 Adriatic North 566 754 5 737 1.0 Adriatic South 874 281 27 448 3.1 Eastern Croatia 885 126 38 737 4.4 4 440 311 121 515 2.7 Croatia Source: Ministry of Health and Social Welfare. It is visible that, according to the proportion in the total number of inhabitants, the largest number of beneficiaries is present in the County of Å ibenik-Knin (11.3 percent of the population). A high proportion of population receiving benefits has also been recorded in Counties of Slavonski Brod-Posavina (5.2 percent), Virovitica-Podravina (5.2 percent), Sisak-Moslavina (5.0 percent) and MeÄ‘imurje (4.9 percent). As expected, the lowest number of social welfare beneficiaries has been recorded in the most developed counties. Hence, the smallest number of social welfare beneficiaries has been observed in the County of Istria (0.6 percent of the population), followed by the County of Primorje-Gorski kotar (1.0 percent), the City of Zagreb (1.5 percent), and the Counties of Zagreb and Krapina-Zagorje (1.1 percent). Eastern Croatia has the largest proportion of beneficiaries in total number of inhabitants (4.4 percent), while Zagreb region has the lowest (1.4 percent). The average for Croatia is 2.7 percent. The number of beneficiaries of unemployment benefits, apart from the development levels, additionally indicates the structural problems of certain counties, faced with the problems of restructuring companies in the area and the consequent unemployment (Tables 4.33 and 4.34). Consequently, the proportion of beneficiaries of unemployment benefits in the total population has grown significantly in 2002, but then again in 2003 came to the same level as in 2001. The highest proportion in 2003 has been recorded in Counties of Karlovac (2.08 percent of the population), Virovitica-Podravina (2.05 percent) and Dubrovnik-Neretva (1.93 percent). In 2002, except these three counties levels above 2 percent of the beneficiaries of unemployment benefits in the total population have also been recorded in Counties of Split-Dalmatia, Bjelovar-Bilogora, Slavonski Brod-Posavina, Sisak-Moslavina, Osijek- baranja and Zadar. The lowest proportion of beneficiaries of unemployment benefit in 2003 has been noted in the City of Zagreb (1.12 percent), Counties of Požega-Slavonia, Varaždin, Zagreb and Lika-Senj. Croatian average of the proportion of beneficiaries of unemployment benefits in 2003 was 1.53 percent. Only Zagreb region was below that average (1.17 percent), while all other analytical regions where above average, with highest proportion in Eastern Croatia (1.76 percent), and Adriatic South (1.75 percent). Table 1.33: Number of Beneficiaries of Unemployment Benefits by Counties Proportion of total population in % County of 2001 2002 2003 2001 2002 2003 Zagreb 4 236 5 050 4 147 1.34 1.60 1.31 38 Krapina-Zagorje 2 560 2 717 2 156 1.82 1.93 1.53 Sisak-Moslavina 3 401 3 713 2 681 1.86 2.03 1.47 Karlovac 2 707 3 422 2 899 1.95 2.46 2.08 Varaždin 2 623 2 910 2 513 1.43 1.59 1.37 Koprivnica-Križevci 1 778 2 081 1 822 1.44 1.69 1.48 Bjelovar-Bilogora 2 347 2 960 2 167 1.79 2.26 1.66 Primorje-Gorski kotar 4 936 4 858 4 446 1.62 1.59 1.46 Lika-Senj 700 912 698 1.32 1.72 1.32 Virovitica-Podravina 1 696 2 127 1 891 1.84 2.31 2.05 Požega-Slavonia 1 175 1 322 1 166 1.38 1.55 1.37 Slavonski Brod- 3 026 3 755 3 146 1.72 2.13 1.79 Posavina Zadar 2 607 3 378 2 827 1.57 2.04 1.71 Osijek-Baranja 6 279 6 987 5 904 1.91 2.12 1.80 Å ibenik-Knin 1 607 1 971 1 760 1.41 1.73 1.55 Vukovar-Sirmium 2 861 3 619 3 455 1.41 1.79 1.71 8 604 10 295 8 320 1.83 2.19 1.77 Split-Dalmatia Istria 3 061 3 376 3 020 1.47 1.62 1.45 2 181 2 886 2 396 1.76 2.33 1.93 Dubrovnik-Neretva MeÄ‘imurje 1 683 1 888 1 837 1.42 1.59 1.55 10 302 10 569 8 728 1.32 1.35 1.12 City of Zagreb Croatia 70 370 80 796 67 979 1.58 1.82 1.53 Source: Croatian Employment Service. Table 1.34: Number of Beneficiaries of Unemployment Benefits by Analytical Regions Proportion of total population in % Analytical regions 2001 2002 2003 2001 2002 2003 Zagreb region 14 538 15 619 12 875 1.33 1.43 1.17 Central Croatia 17 099 19 691 16 075 1.68 1.93 1.58 Adriatic North 8 697 9 146 8 164 1.53 1.61 1.44 Adriatic South 14 999 18 530 15 303 1.72 2.12 1.75 Eastern Croatia 15 037 17 810 15 562 1.70 2.01 1.76 70 370 80 796 67 979 1.58 1.82 1.53 Croatia Source: Croatian Employment Service. A significant category of government social transfers relates to child allowance. However, this category correlates more significantly with the demographic characteristics, rather than development level. On the basis of the data from Tables 4.35 and 4.36, it is clear that the highest proportion of child allowance in the total Croatian child allowance amount has been provided in Eastern Croatia (28.0 percent), while the smallest proportion of child allowance has been recorded in Adriatic Norht (7.7 percent). The county with the highest share of child allowance is the County of Split-Dalmatia (11.9 percent in 2002), and the smallest share is recorded in the County of Lika-Senj (1.1 percent). 39 Table 1.35: Child Allowance, by counties, 2001-2003 in HRK structure, in % County of 2001 2002 2003 2001 2002 2003 Zagreb 143 965 208 101 998 569 95 437 563 6.0 6.1 5.9 Krapina-Zagorje 74 231 490 55 295 196 51 899 654 3.1 3.3 3.2 Sisak-Moslavina 101 198 122 71 824 648 69 970 009 4.2 4.3 4.3 Karlovac 66 339 838 44 167 597 41 265 683 2.7 2.6 2.6 Varaždin 104 989 622 75 650 531 71 451 482 4.3 4.5 4.4 Koprivnica-Križevci 72 375 928 54 448 343 53 441 480 3.0 3.2 3.3 Bjelovar-Bilogora 83 303 955 64 677 047 62 833 740 3.4 3.9 3.9 Primorje-Gorski kotar 100 076 650 67 353 594 62 212 662 4.1 4.0 3.9 Lika-Senj 26 245 348 17 720 786 16 887 273 1.1 1.1 1.0 Virovitica-Podravina 63 873 625 49 303 532 49 099 047 2.6 2.9 3.0 Požega-Slavonia 65 944 945 46 315 726 44 833 073 2.7 2.8 2.8 Slavonski Brod- 142 731 863 101 863 007 100 529 838 5.9 6.1 6.2 Posavina Zadar 96 735 939 67 761 166 64 800 471 4.0 4.0 4.0 Osijek-Baranja 225 715 452 155 987 161 149 824 176 9.3 9.3 9.3 Å ibenik-Knin 71 050 325 49 106 011 47 363 124 2.9 2.9 2.9 Vukovar-Sirmium 144 465 304 107 585 457 106 417 957 6.0 6.4 6.6 Split-Dalmatia 302 789 050 199 827 242 196 315 922 12.5 11.9 12.2 Istria 67 717 663 48 211 912 45 001 534 2.8 2.9 2.8 Dubrovnik-Neretva 81 552 933 51 253 878 49 514 309 3.4 3.1 3.1 MeÄ‘imurje 72 267 614 55 060 947 53 135 887 3.0 3.3 3.3 City of Zagreb 307 300 937 193 774 020 179 365 169 12.7 11.5 11.1 Croatia 2 414 871 812 1 679 186 373 1 611 600 053 100.0 100.0 100.0 Source: Croatian Institute for Pension Insurance – HZMO. Table 1.36: Child Allowance, by Analytical Regions, 2001-2003 in HRK structure, in % Analytical regions 2001 2002 2003 2001 2002 2003 Zagreb region 451 266 145 295 772 589 274 802 731 18.7 17.6 17.1 Central Croatia 574 706 570 421 124 310 403 997 935 23.8 25.1 25.1 Adriatic North 194 039 661 133 286 293 124 101 469 8.0 7.9 7.7 Adriatic South 552 128 246 367 948 297 357 993 827 22.9 21.9 22.2 Eastern Croatia 642 731 190 461 054 884 450 704 091 26.6 27.5 28.0 Croatia 2 414 871 812 1 679 186 373 1 611 600 053 100.0 100.0 100.0 Source: Croatian Institute for Pension Insurance – HZMO. As conclusion, Table 4.37 presents correlation coefficients between social transfers and the level of economic development in terms of both, GDP p.c., as well as gross disposable income per capita in period 2001-2003. According to expectations social transfers are negatively correlated with development variables, meaning that more developed counties have a lower share of social transfers in GDP (GDI). Coefficients are negative and significant at 5 percent significance level for all presented types of social transfer except pensions. Those results confirm the hypothesis that income redistribution process significantly reduces the inequality in welfare of Croatian counties, but the impact of various types of transfers is different. Transfers in the scope of obligatory social security system are not significantly correlated with development level of individual county. Table 1.37: The Correlation Coefficients between Social Transfer Variables and the Level of Economic Development Variable GDP p.c. GDI p.c. 40 Total social transfers -0.17 -0.23 Pensions 0.08 0.05 Social transfers without pensions -0.61* -0.73* Unemployment benefits -0.67* -0.73* Social welfare benefits -0.56* -0.64* Child allowances -0.62* -0.72* Note: * 5 percent significance level. Source: Author’s calculations. 41 Table A3.1. Gross domestic product in current prices, 2001 Counties GDP, mil. GDP, mil. GDP, Structure. GDP p.c. Index kn EUR mil. USD in % kn EUR USD Croatia = 100) Croatia 165 639 22 177 19 863 100.0 37 309 4 995 4 474 100.0 Zagreb 7 863 1 053 943 4.7 25 334 3 392 3 038 67.9 Krapina-Zagorje 4 194 561 503 2.5 29 485 3 948 3 536 79.0 Sisak-Moslavina 5 997 803 719 3.6 32 375 4 335 3 882 86.8 Karlovac 4 486 601 538 2.7 31 693 4 243 3 801 84.9 Varaždin 6 553 877 786 4.0 35 490 4 752 4 256 95.1 Koprivnica- 4 801 643 576 2.9 38 598 5 168 4 629 103.5 Križevci Bjelovar- 3 893 521 467 2.4 29 304 3 923 3 514 78.5 Bilogora Primorje-Gorski 13 399 1 794 1 607 8.1 43 853 5 871 5 259 117.5 kotar Lika-Senj 1 606 215 192 1.0 29 934 4 008 3 590 80.2 Virovitica- 2 783 373 334 1.7 29 834 3 994 3 578 80.0 Podravina Požega-Slavonia 2 367 317 284 1.4 27 567 3 691 3 306 73.9 Slavonski Brod- 4 026 539 483 2.4 22 768 3 048 2 730 61.0 Posavina Zadar 4 372 585 524 2.6 26 899 3 601 3 226 72.1 Osijek-Baranja 9 565 1 280 1 147 5.8 28 955 3 877 3 472 77.6 Å ibenik-Knin 2 687 360 322 1.6 23 747 3 179 2 848 63.6 Vukovar- 4 434 594 532 2.7 21 648 2 898 2 596 58.0 Sirmium Split-Dalmatia 13 146 1 760 1 576 7.9 28 272 3 785 3 390 75.8 Istria 10 368 1 388 1 243 6.3 50 174 6 718 6 017 134.5 Dubrovnik- 4 142 555 497 2.5 33 642 4 504 4 034 90.2 Neretva MeÄ‘imurje 3 673 492 440 2.2 31 010 4 152 3 719 83.1 City of Zagreb 51 284 6 866 6 150 31.0 65 820 8 812 7 893 176.4 42 Table A3.2. Gross DomesticPproduct in Current Prices, 2002. Counties GDP, mil. GDP, mil. GDP, Structure, GDP p.c. Index kn EUR mil. USD in % kn EUR USD Croatia = 100) Croatia 181 231 24 468 23 047 100.0 40 814 5 510 5 190 100.0 Zagreb 9 839 1 328 1 251 5.4 31 456 4 247 4 000 77.1 Krapina-Zagorje 4 305 581 548 2.4 30 453 4 112 3 873 74.6 Sisak-Moslavina 6 097 823 775 3.4 33 127 4 472 4 213 81.2 Karlovac 4 895 661 623 2.7 34 873 4 708 4 435 85.4 Varaždin 7 371 995 937 4.1 40 051 5 407 5 093 98.1 Koprivnica- Križevci 5 146 695 654 2.8 41 577 5 613 5 287 101.9 Bjelovar- Bilogora 4 296 580 546 2.4 32 564 4 397 4 141 79.8 Primorje-Gorski kotar 14 021 1 893 1 783 7.7 45 903 6 197 5 837 112.5 Lika-Senj 1 974 267 251 1.1 37 116 5 011 4 720 90.9 Virovitica- Podravina 2 955 399 376 1.6 31 873 4 303 4 053 78.1 Požega-Slavonia 2 490 336 317 1.4 29 041 3 921 3 693 71.2 Slavonski Brod- Posavina 4 332 585 551 2.4 24 521 3 311 3 118 60.1 Zadar 4 916 664 625 2.7 29 958 4 045 3 810 73.4 Osijek-Baranja 10 777 1 455 1 371 5.9 32 675 4 411 4 155 80.1 Å ibenik-Knin 3 043 411 387 1.7 26 839 3 624 3 413 65.8 Vukovar- Sirmium 4 847 655 616 2.7 23 797 3 213 3 026 58.3 Split-Dalmatia 14 350 1 937 1 825 7.9 30 636 4 136 3 896 75.1 Istria 11 481 1 550 1 460 6.3 55 335 7 471 7 037 135.6 Dubrovnik- Neretva 4 379 591 557 2.4 35 429 4 783 4 505 86.8 MeÄ‘imurje 4 107 554 522 2.3 34 650 4 678 4 406 84.9 City of Zagreb 55 610 7 508 7 072 30.7 71 355 9 634 9 074 174.8 43 Table A3.3. Gross domestic product in current prices, 2003. Counties GDP, mil. GDP, mil. GDP, Structure, GDP p.c. Index kn EUR mil. USD in % kn EUR USD Croatia = 100) Croatia 198 422 26 235 29 609 100.0 44 689 5 909 6 669 100.0 Zagreb 10 480 1 386 1 564 5.3 33 165 4 385 4 949 74.2 Krapina-Zagorje 4 556 602 680 2.3 32 427 4 287 4 839 72.6 Sisak-Moslavina 6 290 832 938 3.2 34 409 4 549 5 135 77.0 Karlovac 4 831 639 721 2.4 34 730 4 592 5 183 77.7 Varaždin 7 709 1 019 1 150 3.9 42 080 5 564 6 279 94.2 Koprivnica- Križevci 5 275 697 787 2.6 42 817 5 661 6 389 95.8 Bjelovar- Bilogora 4 367 577 652 2.2 33 387 4 414 4 982 74.7 Primorje-Gorski kotar 16 100 2 129 2 402 8.1 52 770 6 977 7 874 118.1 Lika-Senj 2 449 324 365 1.2 46 208 6 109 6 895 103.4 Virovitica- Podravina 3 105 411 463 1.5 33 677 4 453 5 025 75.4 Požega-Slavonia 2 754 364 411 1.4 32 248 4 264 4 812 72.2 Slavonski Brod- Posavina 4 528 599 676 2.3 25 698 3 398 3 835 57.5 Zadar 5 936 785 886 3.0 35 802 4 734 5 342 80.1 Osijek-Baranja 11 059 1 462 1 650 5.6 33 634 4 447 5 019 75.3 Å ibenik-Knin 3 536 468 528 1.8 31 127 4 115 4 645 69.7 Vukovar- Sirmium 5 203 688 776 2.6 25 694 3 397 3 834 57.5 Split-Dalmatia 15 839 2 094 2 364 8.0 33 628 4 446 5 018 75.3 Istria 12 814 1 694 1 912 6.5 61 429 8 122 9 167 137.5 Dubrovnik- Neretva 4 896 647 731 2.5 39 516 5 225 5 897 88.4 MeÄ‘imurje 4 241 561 633 2.1 35 819 4 736 5 345 80.2 City of Zagreb 62 454 8 257 9 320 31.5 80 069 10 586 11 948 179.2 44 Table A3.4. Sectoral Structure of GDP, 2001, by counties L, M, Counties A, B C, D, E F G H I J, K TOTAL N, O Croatia 9.5 25.7 5.2 12.1 3.6 10.5 10.6 22.8 100.0 Zagreb 16.6 27.1 4.8 20.0 2.1 10.0 5.8 13.6 100.0 Krapina-Zagorje 13.6 29.3 4.8 13.8 2.5 9.5 4.9 21.6 100.0 Sisak-Moslavina 12.7 36.2 5.5 6.6 1.6 10.5 6.4 20.4 100.0 Karlovac 9.8 25.4 19.3 6.9 3.2 8.2 5.6 21.5 100.0 Varaždin 12.8 35.2 4.8 10.1 1.9 7.5 6.8 21.0 100.0 Koprivnica- Križevci 22.7 36.0 3.5 10.0 1.6 6.7 5.1 14.4 100.0 Bjelovar- Bilogora 29.6 20.8 5.3 6.4 2.1 8.0 6.6 21.2 100.0 Primorje-Gorski kotar 2.5 26.8 5.4 11.0 8.1 14.9 10.3 21.0 100.0 Lika-Senj 20.8 18.1 10.6 4.1 4.9 11.4 4.2 26.0 100.0 Virovitica- Podravina 30.9 22.7 3.2 13.4 1.2 6.2 4.3 18.0 100.0 Požega-Slavonia 24.1 17.4 4.7 12.0 1.5 8.0 4.5 27.8 100.0 Slavonski Brod- Posavina 20.6 23.4 5.3 8.6 1.2 9.8 6.7 24.4 100.0 Zadar 11.6 14.3 7.2 10.6 5.4 12.3 10.6 27.9 100.0 Osijek-Baranja 21.4 19.2 5.3 10.6 1.6 9.1 8.5 24.3 100.0 Å ibenik-Knin 9.5 13.8 5.8 11.4 5.2 13.3 9.0 32.0 100.0 Vukovar- Sirmium 30.8 10.9 8.4 11.2 1.3 7.8 4.7 24.8 100.0 Split-Dalmatia 4.6 23.5 4.9 12.6 4.4 12.1 11.4 26.4 100.0 Istria 5.6 29.4 5.6 10.0 12.7 9.2 9.6 17.8 100.0 Dubrovnik- Neretva 9.0 12.5 4.5 7.2 9.0 18.2 11.8 27.9 100.0 MeÄ‘imurje 17.6 35.9 5.9 7.5 1.4 7.0 7.7 16.9 100.0 City of Zagreb 0.5 27.1 3.6 15.1 2.0 10.7 16.2 25.0 100.0 45 Table A3.5. Sectoral structure of GDP, 2002., by counties L, M, Counties A, B C, D, E F G H I J, K TOTAL N, O Croatia 9.1 24.2 5.6 13.6 3.8 10.3 11.5 22.0 100.0 Zagreb 15.6 31.7 5.1 18.6 2.8 8.5 5.6 12.0 100.0 Krapina-Zagorje 13.6 29.8 7.5 9.8 2.8 9.6 5.8 21.0 100.0 Sisak-Moslavina 12.5 32.1 5.5 8.2 2.9 11.9 6.0 20.9 100.0 Karlovac 10.7 22.7 20.1 7.6 4.3 8.4 6.4 19.8 100.0 Varaždin 12.4 32.1 6.5 12.8 2.5 7.1 6.8 19.7 100.0 Koprivnica- Križevci 23.1 35.7 3.5 10.4 1.7 5.8 5.5 14.2 100.0 Bjelovar- Bilogora 29.0 19.0 4.6 9.2 3.1 8.5 7.4 19.2 100.0 Primorje-Gorski kotar 2.5 21.8 6.5 13.1 7.9 14.9 12.0 21.5 100.0 Lika-Senj 17.7 20.8 12.6 7.0 5.2 9.6 4.4 22.7 100.0 Virovitica- Podravina 29.9 20.4 4.1 15.2 1.9 5.8 4.9 17.8 100.0 Požega-Slavonia 23.0 23.4 4.6 8.7 1.9 7.3 5.0 26.0 100.0 Slavonski Brod- Posavina 19.4 19.0 5.9 12.1 1.8 10.0 7.3 24.5 100.0 Zadar 10.8 11.8 9.5 13.1 6.2 11.1 10.9 26.6 100.0 Osijek-Baranja 19.7 17.9 5.0 13.9 1.9 9.4 8.9 23.2 100.0 Å ibenik-Knin 8.9 18.4 6.7 10.6 5.3 12.8 9.2 28.1 100.0 Vukovar- Sirmium 27.9 12.9 7.6 10.7 2.3 9.3 4.6 24.6 100.0 Split-Dalmatia 4.1 21.3 5.7 14.2 4.6 12.8 11.4 26.0 100.0 Istria 5.4 32.9 6.1 10.0 11.2 6.3 10.8 17.3 100.0 Dubrovnik- Neretva 9.1 11.8 5.1 8.0 7.2 18.0 13.9 27.0 100.0 MeÄ‘imurje 16.2 35.5 6.7 9.0 2.2 6.0 8.8 15.6 100.0 City of Zagreb 0.4 24.0 3.3 17.2 2.1 10.8 18.0 24.1 100.0 46 Table A3.6. Sectoral structure of GDP, 2003., by counties L, M, Counties A, B C, D, E F G H I J, K TOTAL N, O Croatia 7.4 24.0 6.6 14.5 4.0 10.1 12.7 20.8 100.0 Zagreb 12.8 32.7 6.0 18.0 3.1 8.7 6.1 12.6 100.0 Krapina-Zagorje 11.2 31.1 6.7 11.1 3.0 10.2 6.3 20.5 100.0 Sisak-Moslavina 10.7 28.9 5.9 10.2 3.1 13.1 6.4 21.8 100.0 Karlovac 9.6 28.1 10.8 9.4 5.1 9.1 7.3 20.7 100.0 Varaždin 10.3 29.0 9.5 12.9 2.5 7.2 8.4 20.0 100.0 Koprivnica- Križevci 19.7 34.7 4.3 12.3 2.0 5.9 6.8 14.2 100.0 Bjelovar- Bilogora 25.0 19.7 5.9 9.8 3.4 7.4 9.0 19.7 100.0 Primorje-Gorski kotar 2.0 22.1 8.2 13.3 7.5 14.4 12.5 20.0 100.0 Lika-Senj 12.6 18.1 25.9 5.6 4.7 10.1 3.9 19.1 100.0 Virovitica- Podravina 25.0 24.3 4.5 16.7 1.9 5.5 5.3 16.8 100.0 Požega-Slavonia 18.4 23.8 6.2 11.3 2.8 6.9 5.5 25.1 100.0 Slavonski Brod- Posavina 16.3 20.7 6.8 12.4 2.5 10.2 7.6 23.5 100.0 Zadar 8.0 13.3 14.3 12.9 6.8 10.6 10.7 23.4 100.0 Osijek-Baranja 17.0 18.1 5.6 15.2 2.0 9.3 10.3 22.5 100.0 Å ibenik-Knin 6.7 16.9 10.5 11.5 5.3 12.3 10.0 26.9 100.0 Vukovar- Sirmium 22.9 16.3 8.6 11.9 2.5 9.6 4.9 23.4 100.0 Split-Dalmatia 3.4 17.5 7.5 16.3 4.8 13.2 12.8 24.4 100.0 Istria 4.7 30.2 7.1 11.0 11.5 6.9 12.2 16.4 100.0 Dubrovnik- Neretva 7.1 10.8 7.3 9.6 8.1 17.7 14.5 25.0 100.0 MeÄ‘imurje 13.6 35.8 7.3 9.3 2.3 6.4 9.2 16.1 100.0 City of Zagreb 0.4 24.5 3.9 17.8 2.0 9.7 19.8 22.0 100.0 47 Table B3.1: Primary, Secondary and Total Gross Disposable Income of Household Sector in Croatia in 2001, by counties in millions of kunas Structure, as % of county disposable Total Structure, income Primary Secondary Counties disposable as % of total income income Total income income Primary Secondary disposable income income income Croatia 107 294 681 107 975 100 99.4 0.6 100.0 Zagreb 8 056 -477 7 579 7.0 106.3 -6.3 100.0 Krapina-Zagorje 3 164 63 3 227 3.0 98.1 1.9 100.0 Sisak-Moslavina 3 938 339 4 278 4.0 92.1 7.9 100.0 Karlovac 2 999 213 3 211 3.0 93.4 6.6 100.0 Varaždin 4 259 32 4 291 4.0 99.3 0.7 100.0 Koprivnica- Križevci 3 110 1 3 111 2.9 100.0 0.0 100.0 Bjelovar- Bilogora 2 924 159 3 082 2.9 94.9 5.1 100.0 Primorje-Gorski kotar 8 246 -125 8 121 7.5 101.5 -1.5 100.0 Lika-Senj 1 115 149 1 263 1.2 88.2 11.8 100.0 Virovitica- Podravina 1 927 159 2 086 1.9 92.4 7.6 100.0 Požega-Slavonia 1 712 140 1 851 1.7 92.4 7.6 100.0 Slavonski Brod- Posavina 2 976 439 3 415 3.2 87.1 12.9 100.0 Zadar 3 305 248 3 552 3.3 93.0 7.0 100.0 Osijek-Baranja 6 790 500 7 290 6.8 93.1 6.9 100.0 Å ibenik-Knin 2 069 349 2 418 2.2 85.6 14.4 100.0 Vukovar- Sirmium 3 446 617 4 063 3.8 84.8 15.2 100.0 Split-Dalmatia 9 362 604 9 966 9.2 93.9 6.1 100.0 Istria 6 155 -353 5 803 5.4 106.1 -6.1 100.0 Dubrovnik- Neretva 2 751 131 2 882 2.7 95.5 4.5 100.0 MeÄ‘imurje 2 442 42 2 484 2.3 98.3 1.7 100.0 City of Zagreb 26 551 -2 548 24 002 22.2 110.6 -10.6 100.0 48 Table B3.2. Primary, secondary and total gross disposable income of household sector in Croatia in 2002, by counties in millions of kunas Structure, as % of county disposable Total Structure, income Primary Secondary Counties disposable as % of total income income Total income income Primary Secondary disposable income income income Croatia 115 146 -1 840 113 306 100 101.6 -1.6 100.0 Zagreb 8 766 -687 8 079 7.1 108.5 -8.5 100.0 Krapina-Zagorje 3 350 5 3 355 3.0 99.8 0.2 100.0 Sisak-Moslavina 4 204 273 4 477 4.0 93.9 6.1 100.0 Karlovac 3 314 142 3 456 3.1 95.9 4.1 100.0 Varaždin 4 651 -81 4 570 4.0 101.8 -1.8 100.0 Koprivnica- Križevci 3 294 -35 3 259 2.9 101.1 -1.1 100.0 Bjelovar- Bilogora 3 070 138 3 207 2.8 95.7 4.3 100.0 Primorje-Gorski kotar 8 848 -315 8 533 7.5 103.7 -3.7 100.0 Lika-Senj 1 216 141 1 357 1.2 89.6 10.4 100.0 Virovitica- Podravina 1 983 149 2 132 1.9 93.0 7.0 100.0 Požega-Slavonia 1 819 99 1 918 1.7 94.8 5.2 100.0 Slavonski Brod- Posavina 3 102 401 3 502 3.1 88.6 11.4 100.0 Zadar 3 485 204 3 690 3.3 94.5 5.5 100.0 Osijek-Baranja 7 183 389 7 572 6.7 94.9 5.1 100.0 Å ibenik-Knin 2 255 302 2 557 2.3 88.2 11.8 100.0 Vukovar- Sirmium 3 634 583 4 216 3.7 86.2 13.8 100.0 Split-Dalmatia 10 144 291 10 435 9.2 97.2 2.8 100.0 Istria 6 666 -500 6 166 5.4 108.1 -8.1 100.0 Dubrovnik- Neretva 2 996 44 3 041 2.7 98.5 1.5 100.0 MeÄ‘imurje 2 601 -3 2 597 2.3 100.1 -0.1 100.0 City of Zagreb 28 566 -3 380 25 186 22.2 113.4 -13.4 100.0 49 Table B3.3. Primary, secondary and total gross disposable income of household sector in Croatia in 2003, by counties in millions of kunas Structure, as % of county disposable Total Structure, income Primary Secondary Counties disposable as % of total income income Total income income Primary Secondary disposable income income income Croatia 125 190 -2 971 122 220 100 102.4 -2.4 100.0 Zagreb 9 611 -832 8 779 7.2 109.5 -9.5 100.0 Krapina-Zagorje 3 563 -18 3 546 2.9 100.5 -0.5 100.0 Sisak-Moslavina 4 459 292 4 751 3.9 93.8 6.2 100.0 Karlovac 3 572 115 3 687 3.0 96.9 3.1 100.0 Varaždin 4 914 -105 4 809 3.9 102.2 -2.2 100.0 Koprivnica- Križevci 3 524 -40 3 484 2.9 101.1 -1.1 100.0 Bjelovar- Bilogora 3 342 127 3 468 2.8 96.4 3.6 100.0 Primorje-Gorski kotar 9 611 -392 9 219 7.5 104.2 -4.2 100.0 Lika-Senj 1 428 94 1 522 1.2 93.8 6.2 100.0 Virovitica- Podravina 2 072 187 2 258 1.8 91.7 8.3 100.0 Požega-Slavonia 1 871 115 1 986 1.6 94.2 5.8 100.0 Slavonski Brod- Posavina 3 283 427 3 710 3.0 88.5 11.5 100.0 Zadar 3 848 170 4 018 3.3 95.8 4.2 100.0 Osijek-Baranja 7 753 364 8 117 6.6 95.5 4.5 100.0 Å ibenik-Knin 2 469 311 2 779 2.3 88.8 11.2 100.0 Vukovar- Sirmium 3 893 588 4 480 3.7 86.9 13.1 100.0 Split-Dalmatia 11 103 199 11 302 9.2 98.2 1.8 100.0 Istria 7 093 -523 6 570 5.4 108.0 -8.0 100.0 Dubrovnik- Neretva 3 220 1 3 221 2.6 100.0 0.0 100.0 MeÄ‘imurje 2 829 -19 2 810 2.3 100.7 -0.7 100.0 City of Zagreb 31 733 -4 030 27 703 22.7 114.5 -14.5 100.0 50 Table B3.4. Structure of primary income of household sector in Croatia in 2001, by counties in millions of kunas Structure, as % of county primary income Gross Other Total Mixed Counties wages and primary primary income ** Other salaries* income*** income Mixed Gross W&S primary income income Croatia 83 708 17 053 6 533 107 294 78.0 15.9 6.1 Zagreb 6 304 1 450 302 8 056 78.3 18.0 3.7 Krapina-Zagorje 2 291 723 149 3 164 72.4 22.9 4.7 Sisak-Moslavina 2 997 701 241 3 938 76.1 17.8 6.1 Karlovac 2 366 458 176 2 999 78.9 15.3 5.9 Varaždin 3 209 801 249 4 259 75.3 18.8 5.8 Koprivnica- Križevci 1 983 916 211 3 110 63.8 29.4 6.8 Bjelovar- Bilogora 1 835 921 167 2 924 62.8 31.5 5.7 Primorje-Gorski kotar 6 818 854 574 8 246 82.7 10.4 7.0 Lika-Senj 784 265 66 1 115 70.3 23.7 5.9 Virovitica- Podravina 1 231 580 116 1 927 63.9 30.1 6.0 Požega-Slavonia 1 205 414 93 1 712 70.4 24.2 5.4 Slavonski Brod- Posavina 2 049 776 150 2 976 68.9 26.1 5.0 Zadar 2 512 611 181 3 305 76.0 18.5 5.5 Osijek-Baranja 5 243 1 149 398 6 790 77.2 16.9 5.9 Å ibenik-Knin 1 626 337 106 2 069 78.6 16.3 5.1 Vukovar- Sirmium 2 291 996 159 3 446 66.5 28.9 4.6 Split-Dalmatia 7 709 1 199 453 9 362 82.3 12.8 4.8 Istria 4 736 963 456 6 155 76.9 15.7 7.4 Dubrovnik- Neretva 2 127 464 160 2 751 77.3 16.9 5.8 MeÄ‘imurje 1 708 576 159 2 442 69.9 23.6 6.5 City of Zagreb 22 684 1 899 1 968 26 551 85.4 7.2 7.4 *Gross wages and salaries includes social contribution and taxes on personal income ** Mixed income presents income from unincorporated enterprises in the ownership of households (craftsman and agricultural producers) ***Other primary incomes includes property income and imputed dwelling rents 51 Table B3.5. Structure of primary income of household sector in Croatia in 2002, by counties in millions of kunas Structure, as % of county primary income Gross Other Total Mixed Counties wages and primary primary income ** Other salaries* income*** income Mixed Gross W&S primary income income Croatia 90 125 18 076 6 945 115 146 78.3 15.7 6.0 Zagreb 6 784 1 609 372 8 766 77.4 18.4 4.2 Krapina-Zagorje 2 466 739 145 3 350 73.6 22.1 4.3 Sisak-Moslavina 3 230 728 246 4 204 76.8 17.3 5.8 Karlovac 2 609 515 190 3 314 78.7 15.5 5.7 Varaždin 3 505 877 269 4 651 75.4 18.9 5.8 Koprivnica- Križevci 2 103 966 225 3 294 63.8 29.3 6.8 Bjelovar- Bilogora 1 944 946 180 3 070 63.3 30.8 5.9 Primorje-Gorski kotar 7 330 931 586 8 848 82.9 10.5 6.6 Lika-Senj 851 285 80 1 216 70.0 23.4 6.6 Virovitica- Podravina 1 273 592 118 1 983 64.2 29.8 6.0 Požega-Slavonia 1 310 415 93 1 819 72.0 22.8 5.1 Slavonski Brod- Posavina 2 149 798 155 3 102 69.3 25.7 5.0 Zadar 2 675 613 197 3 485 76.8 17.6 5.7 Osijek-Baranja 5 550 1 196 437 7 183 77.3 16.7 6.1 Å ibenik-Knin 1 774 367 114 2 255 78.7 16.3 5.0 Vukovar- Sirmium 2 454 1 011 169 3 634 67.5 27.8 4.7 Split-Dalmatia 8 394 1 280 471 10 144 82.7 12.6 4.6 Istria 5 161 1 028 476 6 666 77.4 15.4 7.1 Dubrovnik- Neretva 2 340 494 163 2 996 78.1 16.5 5.4 MeÄ‘imurje 1 867 564 170 2 601 71.8 21.7 6.5 City of Zagreb 24 357 2 121 2 088 28 566 85.3 7.4 7.3 *Gross wages and salaries includes social contribution and taxes on personal income ** Mixed income presents income from unincorporated enterprises in the ownership of households (craftsman and agricultural producers) ***Other primary incomes includes property income and imputed dwelling rents 52 Table B3.6. Structure of primary income of household sector in Croatia in 2003, by counties in millions of kunas Structure, as % of county primary income Gross Other Total Mixed Counties wages and primary primary income ** Other salaries* income*** income Mixed Gross W&S primary income income Croatia 99 433 18 434 7 324 125 190 79.4 14.7 5.8 Zagreb 7 613 1 622 376 9 611 79.2 16.9 3.9 Krapina-Zagorje 2 705 704 155 3 563 75.9 19.7 4.3 Sisak-Moslavina 3 423 791 245 4 459 76.8 17.7 5.5 Karlovac 2 841 552 179 3 572 79.6 15.4 5.0 Varaždin 3 817 824 273 4 914 77.7 16.8 5.6 Koprivnica- Križevci 2 296 1 000 228 3 524 65.2 28.4 6.5 Bjelovar- Bilogora 2 126 1 031 184 3 342 63.6 30.9 5.5 Primorje-Gorski kotar 8 018 956 636 9 611 83.4 10.0 6.6 Lika-Senj 1 046 288 94 1 428 73.3 20.2 6.6 Virovitica- Podravina 1 322 624 125 2 072 63.8 30.1 6.0 Požega-Slavonia 1 380 389 102 1 871 73.7 20.8 5.5 Slavonski Brod- Posavina 2 320 803 161 3 283 70.6 24.5 4.9 Zadar 3 032 591 226 3 848 78.8 15.4 5.9 Osijek-Baranja 5 984 1 327 441 7 753 77.2 17.1 5.7 Å ibenik-Knin 1 932 406 130 2 469 78.3 16.5 5.3 Vukovar- Sirmium 2 651 1 057 185 3 893 68.1 27.2 4.7 Split-Dalmatia 9 357 1 246 499 11 103 84.3 11.2 4.5 Istria 5 582 1 004 507 7 093 78.7 14.2 7.2 Dubrovnik- Neretva 2 573 472 175 3 220 79.9 14.7 5.4 MeÄ‘imurje 2 064 593 172 2 829 73.0 20.9 6.1 City of Zagreb 27 349 2 153 2 231 31 733 86.2 6.8 7.0 *Gross wages and salaries includes social contribution and taxes on personal income ** Mixed income presents income from unincorporated enterprises in the ownership of households (craftsman and agricultural producers) ***Other primary incomes includes property income and imputed dwelling rents 53 Table B3.7. Sources of secondary income of household sector in Croatia in 2001, by counties in millions of kunas Total Other social Health Social Unemploy. Child sources of Counties Pensions and various insurance welfare benefits allowances secondary transfers* income Croatia 17 990 1 593 981 731 2 415 12 013 35 723 Zagreb 944 117 41 44 144 767 2 056 Krapina-Zagorje 459 44 25 27 74 359 987 Sisak-Moslavina 753 58 57 35 101 504 1 508 Karlovac 596 46 44 28 66 388 1 168 Varaždin 613 61 43 27 105 473 1 322 Koprivnica- Križevci 328 38 26 18 72 301 783 Bjelovar- Bilogora 387 35 35 24 83 331 895 Primorje-Gorski kotar 1 567 130 45 51 100 878 2 771 Lika-Senj 255 15 12 7 26 151 466 Virovitica- Podravina 261 24 33 18 64 233 632 Požega-Slavonia 264 23 23 12 66 218 607 Slavonski Brod- Posavina 537 40 52 31 143 451 1 253 Zadar 639 47 40 27 97 436 1 286 Osijek-Baranja 1 181 100 89 65 226 874 2 535 Å ibenik-Knin 500 31 65 17 71 322 1 006 Vukovar- Sirmium 723 44 45 30 144 533 1 520 Split-Dalmatia 1 899 147 104 89 303 1 270 3 812 Istria 900 90 27 32 68 562 1 679 Dubrovnik- Neretva 480 41 21 23 82 331 977 MeÄ‘imurje 272 33 39 17 72 281 714 City of Zagreb 4 432 430 117 107 307 2 352 7 745 *Includes net transfers from abroad 54 Table B3.8. Sources of secondary income of household sector in Croatia in 2002, by counties in millions of kunas Total Other social Health Social Unemploy. Child sources of Counties Pensions and various insurance welfare benefits allowances secondary transfers* income Croatia 18 858 2 023 1 131 866 1 679 12 682 37 239 Zagreb 991 152 47 54 102 818 2 164 Krapina-Zagorje 482 55 29 29 55 378 1 028 Sisak-Moslavina 791 72 66 40 72 530 1 571 Karlovac 625 59 51 37 44 409 1 224 Varaždin 639 79 49 31 76 497 1 372 Koprivnica- Križevci 345 47 30 22 54 317 816 Bjelovar- Bilogora 406 44 40 32 65 348 935 Primorje-Gorski kotar 1 647 164 52 52 67 930 2 913 Lika-Senj 270 19 14 10 18 159 490 Virovitica- Podravina 273 29 38 23 49 245 656 Požega-Slavonia 277 29 26 14 46 229 621 Slavonski Brod- Posavina 563 48 60 40 102 472 1 286 Zadar 669 60 46 36 68 463 1 343 Osijek-Baranja 1 239 125 102 75 156 917 2 614 Å ibenik-Knin 523 40 75 21 49 340 1 048 Vukovar- Sirmium 756 55 52 39 108 559 1 568 Split-Dalmatia 1 973 188 120 110 200 1 338 3 929 Istria 954 116 31 36 48 600 1 785 Dubrovnik- Neretva 502 53 24 31 51 349 1 010 MeÄ‘imurje 290 42 45 20 55 298 750 City of Zagreb 4 642 547 135 113 194 2 487 8 117 *Includes net transfers from abroad 55 Table B3.9. Sources of secondary income of household sector in Croatia in 2003, by counties in millions of kunas Total Other social Health Social Unemploy. Child sources of Counties Pensions and various insurance welfare benefits allowances secondary transfers* income Croatia 19 919 2 039 1 225 836 1 612 13 534 39 163 Zagreb 1 062 156 51 51 95 883 2 298 Krapina-Zagorje 510 55 31 27 52 401 1 075 Sisak-Moslavina 845 70 71 33 70 564 1 652 Karlovac 655 58 55 36 41 432 1 277 Varaždin 680 78 53 31 71 530 1 444 Koprivnica- Križevci 372 47 32 22 53 339 866 Bjelovar- Bilogora 432 44 43 27 63 370 979 Primorje-Gorski kotar 1 712 165 56 55 62 987 3 036 Lika-Senj 287 21 15 9 17 170 518 Virovitica- Podravina 301 27 41 23 49 263 705 Požega-Slavonia 296 28 28 14 45 244 656 Slavonski Brod- Posavina 603 47 65 39 101 505 1 360 Zadar 722 62 50 35 65 501 1 434 Osijek-Baranja 1 315 122 111 73 150 977 2 747 Å ibenik-Knin 555 40 81 22 47 364 1 108 Vukovar- Sirmium 801 54 56 42 106 596 1 656 Split-Dalmatia 2 080 193 130 102 196 1 432 4 133 Istria 1 001 115 34 37 45 641 1 873 Dubrovnik- Neretva 535 53 26 29 50 373 1 066 MeÄ‘imurje 306 42 49 23 53 319 791 City of Zagreb 4 851 562 146 107 179 2 643 8 488 *Includes net transfers from abroad 56 Table B3.10. Sources of secondary income of household sector in Croatia in 2001, by counties, as % of total disposable income Total Other social Health Social Unemploy. Child sources of Counties Pensions and various insurance welfare benefits allowances secondary transfers* income Croatia 16.7 1.5 0.9 0.7 2.2 11.1 33.1 Zagreb 12.5 1.5 0.5 0.6 1.9 10.1 27.1 Krapina-Zagorje 14.2 1.3 0.8 0.8 2.3 11.1 30.6 Sisak-Moslavina 17.6 1.3 1.3 0.8 2.4 11.8 35.3 Karlovac 18.6 1.4 1.4 0.9 2.1 12.1 36.4 Varaždin 14.3 1.4 1.0 0.6 2.4 11.0 30.8 Koprivnica- 10.5 1.2 0.8 0.6 2.3 9.7 25.2 Križevci Bjelovar- 12.5 1.1 1.1 0.8 2.7 10.7 29.0 Bilogora Primorje-Gorski 19.3 1.6 0.6 0.6 1.2 10.8 34.1 kotar Lika-Senj 20.2 1.2 1.0 0.6 2.1 11.9 36.9 Virovitica- 12.5 1.1 1.6 0.8 3.1 11.2 30.3 Podravina Požega-Slavonia 14.3 1.3 1.2 0.7 3.6 11.8 32.8 Slavonski Brod- 15.7 1.2 1.5 0.9 4.2 13.2 36.7 Posavina Zadar 18.0 1.3 1.1 0.8 2.7 12.3 36.2 Osijek-Baranja 16.2 1.4 1.2 0.9 3.1 12.0 34.8 Å ibenik-Knin 20.7 1.3 2.7 0.7 2.9 13.3 41.6 Vukovar- 17.8 1.1 1.1 0.7 3.6 13.1 37.4 Sirmium Split-Dalmatia 19.1 1.5 1.0 0.9 3.0 12.7 38.2 Istria 15.5 1.6 0.5 0.5 1.2 9.7 28.9 Dubrovnik- 16.7 1.4 0.7 0.8 2.8 11.5 33.9 Neretva MeÄ‘imurje 10.9 1.3 1.6 0.7 2.9 11.3 28.8 City of Zagreb 18.5 1.8 0.5 0.4 1.3 9.8 32.3 *Includes net transfers from abroad 57 Table B3.11. Sources of secondary income of household sector in Croatia in 2002, by counties, as % of total disposable income Total Other social Health Social Unemploy. Child sources of Counties Pensions and various insurance welfare benefits allowances secondary transfers* income Croatia 16.6 1.8 1.0 0.8 1.5 11.2 32.9 Zagreb 12.3 1.9 0.6 0.7 1.3 10.1 26.8 Krapina-Zagorje 14.4 1.6 0.9 0.9 1.6 11.3 30.7 Sisak-Moslavina 17.7 1.6 1.5 0.9 1.6 11.8 35.1 Karlovac 18.1 1.7 1.5 1.1 1.3 11.8 35.4 Varaždin 14.0 1.7 1.1 0.7 1.7 10.9 30.0 Koprivnica- 10.6 1.4 0.9 0.7 1.7 9.7 25.0 Križevci Bjelovar- 12.7 1.4 1.2 1.0 2.0 10.9 29.1 Bilogora Primorje-Gorski 19.3 1.9 0.6 0.6 0.8 10.9 34.1 kotar Lika-Senj 19.9 1.4 1.0 0.7 1.3 11.7 36.1 Virovitica- 12.8 1.3 1.8 1.1 2.3 11.5 30.8 Podravina Požega-Slavonia 14.4 1.5 1.4 0.7 2.4 11.9 32.4 Slavonski Brod- 16.1 1.4 1.7 1.1 2.9 13.5 36.7 Posavina Zadar 18.1 1.6 1.2 1.0 1.8 12.6 36.4 Osijek-Baranja 16.4 1.6 1.4 1.0 2.1 12.1 34.5 Å ibenik-Knin 20.4 1.6 2.9 0.8 1.9 13.3 41.0 Vukovar- 17.9 1.3 1.2 0.9 2.6 13.2 37.2 Sirmium Split-Dalmatia 18.9 1.8 1.1 1.1 1.9 12.8 37.7 Istria 15.5 1.9 0.5 0.6 0.8 9.7 29.0 Dubrovnik- 16.5 1.7 0.8 1.0 1.7 11.5 33.2 Neretva MeÄ‘imurje 11.2 1.6 1.7 0.8 2.1 11.5 28.9 City of Zagreb 18.4 2.2 0.5 0.4 0.8 9.9 32.2 *Includes net transfers from abroad 58 Table B3.12. Sources of secondary income of household sector in Croatia in 2003, by counties, as % of total disposable income Total Other social Health Social Unemploy. Child sources of Counties Pensions and various insurance welfare benefits allowances secondary transfers* income Croatia 16.3 1.7 1.0 0.7 1.3 11.1 32.0 Zagreb 12.1 1.8 0.6 0.6 1.1 10.1 26.2 Krapina-Zagorje 14.4 1.6 0.9 0.7 1.5 11.3 30.3 Sisak-Moslavina 17.8 1.5 1.5 0.7 1.5 11.9 34.8 Karlovac 17.8 1.6 1.5 1.0 1.1 11.7 34.6 Varaždin 14.1 1.6 1.1 0.6 1.5 11.0 30.0 Koprivnica- 10.7 1.3 0.9 0.6 1.5 9.7 24.8 Križevci Bjelovar- 12.5 1.3 1.2 0.8 1.8 10.7 28.2 Bilogora Primorje-Gorski 18.6 1.8 0.6 0.6 0.7 10.7 32.9 kotar Lika-Senj 18.8 1.4 1.0 0.6 1.1 11.2 34.1 Virovitica- 13.3 1.2 1.8 1.0 2.2 11.7 31.2 Podravina Požega-Slavonia 14.9 1.4 1.4 0.7 2.3 12.3 33.0 Slavonski Brod- 16.3 1.3 1.8 1.0 2.7 13.6 36.6 Posavina Zadar 18.0 1.5 1.2 0.9 1.6 12.5 35.7 Osijek-Baranja 16.2 1.5 1.4 0.9 1.8 12.0 33.8 Å ibenik-Knin 20.0 1.4 2.9 0.8 1.7 13.1 39.9 Vukovar- 17.9 1.2 1.3 0.9 2.4 13.3 37.0 Sirmium Split-Dalmatia 18.4 1.7 1.1 0.9 1.7 12.7 36.6 Istria 15.2 1.8 0.5 0.6 0.7 9.8 28.5 Dubrovnik- 16.6 1.6 0.8 0.9 1.5 11.6 33.1 Neretva MeÄ‘imurje 10.9 1.5 1.7 0.8 1.9 11.4 28.2 City of Zagreb 17.5 2.0 0.5 0.4 0.6 9.5 30.6 *Includes net transfers from abroad 59