28Original scientific paper Economics of Agriculture 4/2017
UDC: 338.431(4-191.2)
ECONOMIC PERFORMANCES OF AGRICULTURE OF CEFTA AND FORMER CEFTA COUNTRIES1
Jelena Birovljev2, Danilo Dokic3, Bojan Matkovski4, Zana Kleut5
Summary
All CEFTA countries had very similar stages of economic development after World War II. Many of them were centrally-planned socialist economies and the political changes that have occurred in these countries in the late 20th century caused changes in the whole economic system, as well as in the agricultural sector. Aim of this paper is to compare economic performances of agriculture of these countries with former CEFTA countries (Poland, Czech Republic, Slovakia, Hungary, Slovenia, Bulgaria, Romania and Croatia) which joined EU after 2004. The development performances of agriculture are considered according to the production and export performances of this economic sector, using a comparative approach. The results showed that there is a gap in development of agriculture between CEFTA countries and selected EU countries, so performances of agricultural sector are far from EU.
Key words: Agriculture, Promethee method, Cluster analysis, EU, CEFTA. JEL: Q17, Q18, F15
Introduction
The economic performance of the agricultural sector is difficult to define precisely and comprehensively. Many authors have considered a variety of indicators to explain this term. Some studies use partial labour productivity, capital productivity and land productivity (Van
1 The paper presents a part of research on the project: Sustainable Agriculture and Rural Development in terms of the Republic of Seibia strategic goals implementation within Danube region (III 46006), finances by Ministry of Education, Science and Technological Development of Republic of Serbia.
2 Jelena Birovljev, Phd, Full Professor, University of Novi Sad, Faculty of Economics in Subotica, Segedinsku put 9-11, 24000 Subotica, Serbia, Phone: +38124628066, E-mail: birovljevj@ef.uns.ac.rs
3 Danilo Dokic, MSc, Teaching Assistant, University of Novi Sad, Faculty of Economics in Subotica, Segedinsku put 9-11, 24000 Subotica, Serbia, Phone: +381214852907, E-mail: danilo.djokic@ef.uns.ac.r5
4 Bojan Matkovski, MSc, Teaching Assistant, University of Novi Sad, Faculty of Economics in Subotica, Segedinsku put 9-11, 24000 Subotica, Seibia, Phone: +38124628046, E-mail: bojanmatkovski@ef.uns.acjs
5 Zana Kleut, MSc, Teaching Assistant, University of Novi Sad, Faculty of Economics in Subotica, Segedinsku put 9-11, 24000 Subotica, Serbia, Phone: +381214852907, E-mail: zana.kleut@ef.uns.ac.rs
Passel et al., 2007). In order to evaluate position of Slovakian agriculture in EU (European Union), Szabo and Grznar (2015) used the following indicators - agricultural production for the evaluation of effectiveness, intermediate consumption, fixed assets, labour force, levels of livestock, and supports/subsidies for the rendition of the level of inputs. In their study of the agriculture sector of the Western Balkans, Nikolic et al. (2017) used share of agriculture in total employment, net production index number, balance of agriculture product trade, agricultural gross value added as variables that describe importance of agricultural sector. Usually, unavailability of some data for all observed countries has influence on the selection of variables.
The Central European Free Trade Agreement (CEFTA) is a trade agreement between non-EU countries, members of which are now mostly located in Southeastern Europe. Founded in 1992 by Poland, Czechoslovakia and Hungary, CEFTA has been significantly transformed (Table 1). Its essential purpose, as contained in the founding Treaty signed in Cracow in December 1992 was to liberalize their mutual trade in a timescale which paralleled trade liberalization with the EU (Dangerfield, 2006). Today, members of CEFTA are Serbia, Bosnia and Herzegovina, Montenegro, Macedonia, Albania, Moldova and Kosovo (as UNMIK). Other countries have left CEFTA after their accession to EU.
Table 1. Members of CEFTA
Members of CEFTA Joined Former members of CEFTA Joined Left
FYR Macedonia 2006 Hungary 1992 2004
Serbia 2007 Czech Republic 1992 2004
B&H 2007 Slovakia 1992 2004
Albania 2007 Poland 1992 2004
Moldova 2007 Slovenia 1996 2004
Montenegro 2007 Romania 1997 2007
Kosovo (as UNMIK) 2007 Bulgaria 1999 2007
Croatia 2003 2013
Source: CEFTA Portal, 2017
CEFTA is very important for Western Balkan countries. As Kikerova (2009) concluded, in only two years of implementation, the CEFTA agreement achieved noticeable positive effect in the form of significant growth of total trade in goods between these countries. On the other hand, CEFTA has played a modest, but useful role in the EU enlargement process, at no stage was there any serious intention (or possibility) that it would be anything other than an interim arrangement to serve a basic market integration function as a part of EU pre-accession (Dangerfield, 2006). Deeper integration within the CEFTA agreement, in preparation for entry into the EU, is crucial purpose of this agreement, because all countries belonging to CEFTA agreement are in different stages of the EU integration process, with the exception of Moldova (Table 2).
Table 2. CEFTA countries in process of EU integration
Country Status Year Open negotiations
FYR Macedonia Candidate country 2005 No
Montenegro Candidate country 2010 Yes
Serbia Candidate country 2012 Yes
Albania Candidate country 2014 No
B&H Potential candidate - No
Kosovo (as UNMIK) Potential candidate - No
Moldova - - -
Source: European Commission, 2017 (ec.europa.eu)
The aim of this paper is identification and comparison of the economic performances of agriculture in current and former CEFTA countries. First, the importance of agriculture in the overall economy will be determined in these countries by the following indicators: the share of agriculture in GDP, the share of agriculture in total employment and the share of agriculture in foreign trade. Then, this paper will provide an answer to the question of difference in economic performances of agriculture of CEFTA countries and former CEFTA countries that became members of EU. Economic performances are observed according to production performances and export performances. Also, the Netherlands, Germany and France are included in analysis as a benchmark due to their overall economic development.
Materials and methods
Analysis of agricultural performances of CEFTA and selected EU countries is divided in two stages. In the first stage, the goal was to group selected countries by importance of agriculture in their economy. In order to achieve this goal, cluster analysis was performed. Cluster analysis is the modern statistical method of partitioning an observed sample population into relatively homogeneous classes, to produce an operational classification (Stanojevic et al., 2017). The objective is to sort observations into groups called clusters so that the degree of statistical association is high among members of the same group and low between members of different groups (Berlage and Terweduwe, 1988). The grouping in cluster analysis was based on the results (scores) calculated according to the characteristic values of all the variables, separately for each observed unit. K-means method was used in this study in order to divide countries in only two groups. The goal of the K-means method is to split the total number of observations into a prearranged number of k homogenous groups based on preferred characteristics (Lattin et al., 2003). The indicators of the agricultural importance in the economic development were used as variables are:
X1 - Share of agriculture in GDP (%);
X2 - Share of agriculture in total employment (%);
X3 - Share of agriculture in total export (%).
In the second stage, the goal was to rank selected countries by economic performances of their agriculture. In order to achieve this goal, the PROMETHEE method was used as
an adequate method for solving problems whose aim is multi-criteria ranking of final set of alternatives based on a number of criteria which need to be maximized or minimized (Nikolic et al., 2017). For each observed alternative it calculate its value expressed in level of preferences. Thereby, each alternative is evaluated based on the two preference flows. Positive preference flow 9 + (P) indicate how much is given alternative better than the other (according to all criteria). Accordingly, the higher this preference flow is, the alternative is better. The negative flow of preference 9 - (P) indicates how much a given alternative is worse than the rest, and therefore if this flow is lower, the alternative is better. After that, the PROMETHEE method accounts net preference flow 9 (P) as the difference between these two flows (Brans, Mareschal, Vincke, 1984; Brans, Vincke, 1985). The multi-criteria analysis was conducted by using the Visual PROMETHEE software package in order to rank selected countries by their performances of agriculture. Economic performances of agriculture are described by variables given in Table 3. Variables Y1, Y2, Y3 and Y4 are indicators of production performances, while other variables are indicators of export performances.
Table 3. Indicators of economic performances of agriculture
Mark Variable Unit Description
Y1 Structure of resources in agriculture ha/active farmer Represented by the relationship land/labour. In the development of agriculture, land/labour ratio is the dominant factor for selection of production technology (chemical-biological and/ or mechanical), i.e. it has a crucial influence on preferences towards labour-saving or land-saving technologies.
Y2 Land productivity in agriculture $/ha The ratio of value of agricultural products to the area of agricultural land in use. It can be indicator of intensification of production.
Y3 Labour productivity in agriculture $/active farmer The ratio of value of agricultural products to the number of active farmers. Higher values indicate more effective absorption of the labour factor in agricultural production, and consequently a higher residual income per unit of agricultural labour
Y4 Share of livestock production in total agricultural production % The ratio of value of livestock production to total agricultural production. Lower level of this share indicate that agriculture is extensive i.e. the agricultural structure was dominated mainly by lower-value, plant-origin products, which were insufficiently used for conversion into livestock products with higher added values
Y5 Export of agricultural products per hectare of agricultural land $/ha The ratio of export value of agricultural products to the area of agricultural land in use. This is indicator of export performances of agriculture.
Y6 Export of agricultural products per active farmer $/active farmer The ratio of export value of agricultural products to import value. Higher values indicate better export performances of agriculture.
Mark Variable Unit Description
Y7 The export/import coverage of the agricultural products % The ratio of export value of agricultural products to the number of active farmers. Values above 100% indicate positive trade balance of agricultural products.
Source: Author
The empirical research was based on the data of the Food and Agriculture Organization (FAO), especially the data related to the resources, production and foreign trade of agricultural products in the period 2011-2013. The data of share of agriculture in gross domestic product (GDP) and GDP per capita were taken from World Bank database.
Results and discussion
Analysis of economic performances of agriculture in CEFTA and former CEFTA countries is divided in two sections. In first, economic relevance of agriculture is observed, while in second production and export performances are analyzed. Table 3 presents the economic relevance of agriculture in the CEFTA countries, as well as a synthetic indicator of socioeconomic development - GDP per capita. According to Nowak and Kaminska (2016), Netherlands, Germany and France are three countries with the highest performances of agricultural sector in EU. Because of that, these countries are included in analysis as a benchmark of the level of agricultural development (Table 4). Beside these countries, the highest level of GDP per capita is recorded in Slovenia (20,729 euro), Czech Republic (17,557 euro), Slovakia (16,089 euro), Poland (12,559 euro) and Hungary (12,366 euro). All of these countries joined EU in 2004.
Table 4. Economic relevance of agriculture in the CEFTA countries (average for period 2011-2013)
Country Share of agriculture in GDP (%) Share of agriculture in total employment (%) Share of agriculture in total export (%) GDP per capita ( $ )
Netherlands 1.78 2.30 13.39 44,290
Germany 0.85 1.53 5.62 41,178
France 1.76 2.97 12.55 36,353
Slovenia 2.15 8.47 5.82 20,729
Czech Republic 2.56 3.03 4.62 17,557
Slovakia 3.63 3.20 5.15 16,089
Poland 3.16 12.50 11.44 12,559
Hungary 4.60 4.93 8.79 12,366
Croatia 4.51 12.53 11.34 11,593
Romania 6.26 29.43 9.23 8,981
Bulgaria 5.29 6.63 16.31 6,994
Montenegro 9.44 5.67 15.52 6,408
Country Share of agriculture in GDP (%) Share of agriculture in total employment (%) Share of agriculture in total export (%) GDP per capita ( $ )
Serbia 9.68 21.17 22.01 5,237
FYR Macedonia 10.97 18.23 14.98 4,853
B&H 8.01 21.42 8.37 4,249
Albania 21.71 45.80 4.60 3,945
Moldova 14.33 27.57 41.72 1,848
Source: The authors' calculations on the basis of World Bank and FAOstat. 2017
The least developed countries are current members of CEFTA and all of these countries are part of Western Balkan region, except Moldova. The transformation of the agricultural sector in these countries created a gap not only in agricultural development performances between the countries and the EU countries but also in export performances. Although agriculture's share in the economy has decreased since 2000, it is still relatively more important in the CEFTA than in the EU, both in terms of value added and employment. Rule that in the countries with a lower level of the socio-economic development, agriculture is more important for the economy is once more confirmed (Gajic et al., 2015).
Cluster analysis was performed in order to divide these countries in two groups. The analysis refers to the factors that determine the importance of agriculture in the overall economy - the share of agriculture in total employment, the creation of GDP and exports. Results are shown in Table 5. First cluster includes all countries that are members of EU, except Montenegro. In these countries, importance of agriculture in overall economy is at low level.
Table 5. Cluster analysis of agriculture in the CEFTA countries
Cluster 1 Cluster 2
Country Distance Country Distance
Netherlands 2.99 Romania 5.57
Germany 3.89 Serbia 4.79
France 2.43 FYR Macedonia 5.35
Slovenia 3.01 B&H 6.33
Czech Republic 3.57 Albania 14.03
Slovakia 3.20 Moldova 14.45
Poland 3.96
Hungary 1.05
Croatia 3.99
Bulgaria 3.77
Montenegro 4.62
Source: The authors' calculations on the basis of World Bank and FAOstat, 2017
On the other hand, members of second cluster are Romania, Serbia, FYR Macedonia, Bosnia and Herzegovina, Albania and Moldova. Membership in the EU does not mean that it will necessarily get to the agricultural consolidation and the gradual disappearance of small farms. On the contrary, the number of farms with less than 2 hectares in Romania increased (Hubbard et al., 2014). Beside other factors, this probably slow downed the development of Romanian agriculture and placed it in second cluster.
The multi-criteria analysis was conducted by using the Visual PROMETHEE software package in order to rank selected countries by trade and production performances of agriculture. These performances were described by the variables presented in Table 3.
In terms of values of the analyzed variables, the individual countries are characterized by a high degree of differentiation. The variation ranges from about 33% to 275% (Table 6). The greatest diversity of the surveyed units is manifested in the case of variable Y5 -export of agricultural products per hectare of agricultural land ($/ha) and Y6 - export of agricultural products per active farmer ($/active farmer), both variables being indicators of export performances. This high level of variation could be expected if export performances of Netherlands (48,103 $/ha and 467,458 $/farmer) and Albania (80 $/ha and 145 $/farmer) are concerned. The smallest variation was seen in case of variable Y4 - share of livestock production in total agricultural production (%). Interestingly, in period 2004-2014, share of livestock production has declined in most of observed countries, especially CEFTA countries, while Netherlands and Germany still have high level of this share (above 64%). According to Miklos (2014) the decline of the animal sector has serious consequences for the whole sector in Hungary. Beside economic effects, as the total number of livestock units dropped to less than half of what it was in the mid-1980, the lack of enough natural manure makes it more and more difficult to improve the quality of the soils. According to this, it could be concluded that Hungarian livestock products have not be able to compete with same products from "old" EU countries.
Table 6. Characteristics of the variables describing the production and trade performances of the agricultural sector of the selected countries
Y1 Y2 Y3 Y4 Y5 Y6 Y7
Minimum 1.8 Albania 421 B&H 1,857 Albania 21 Macedonia 80 Albania 145 Albania 11 Albania
Maximum 38.86 Montenegro 7,191 Netherlands 69,778 Netherlands 72 Netherlands 48,103 Netherlands 467,458 Netherlands 187 Serbia
Average 17.1 1,262 19,327 43.3 4,145 55,804 97.6
Standard Dev. 12.2 1,577 20,355 14.2 11,398 112,494 55.3
Source: The authors' calculations on the basis of World Bank and FAOstat, 2017
On the basis of The PROMETHEE method, the countries were ranked by development performances of their agricultural sector. Table 7 shows the results of the analysis. Net preference flow (9) takes the values from -0.6607 to 0.8125. The best rated was the
Netherlands (the value of 0.8125), followed by Germany (0.6864) and France (0.6369). According to this ranking, agricultural sector of these countries is the most developed and therefore taking them as benchmark is justified. Next group are: Hungary, Czech Republic, Slovakia, Slovenia and Poland, the countries that joined EU in 2004. Their net preference flow 9 is still above zero. Good performance of their agricultural sector is a result of joining the EU. According to Chrastinova and Burianova (2009) the results achieved by Slovak agriculture in 2004-2007 (i.e. after the integration into the EU) suggest that the income within the sector has improved also due to the inflow of the EU subsidies. In spite of good ranking of Czech Republic and Slovakia, they have one common problem connected with export performances. Czech agricultural production covers the domestic consumption by only 60% to 70% in the case of Slovakia, the situation is even worse, as the domestic production covers the local consumption by only a little more than 40% (Bielik et al., 2013).
Experience of other new EU member states from Central and Eastern Europe shows that price, production and trade can significantly change after accession, as well as during the pre-accession period. The extent of this adjustment occurring before or after accession depends on the pre-accession policy and market adjustments. Crucial tasks for these countries during the accession process are finding niche markets or being cost competitive (Mizik and Meyers, 2013).
Table 7. The classification of the selected countries in terms of trade and production performances of agriculture
Rank Country 9 9 + 9 -
1 hh 0.8125 0.9018 0.0893
2 Germany 0.6964 0.8393 0.1429
3 France 0.6339 0.8125 0.1786
4 Hungary 0.4018 0.6964 0.2946
5 Czech Republic 0.3393 0.6696 0.3304
6 Slovakia 0.2232 0.6071 0.3839
7 Slovenia 0.1786 0.5804 0.4018
8 Poland 0.1339 0.5536 0.4196
9 Bulgaria -0.0536 0.4643 0.5179
10 Serbia -0.0893 0.4464 0.5357
11 Montenegro -0.1964 0.4018 0.5982
12 Croatia -0.3661 0.3036 0.6696
13 FYR Macedonia -0.4375 0.2768 0.7143
14 Moldova -0.4821 0.2500 0.7321
15 Romania -0.5179 0.2411 0.7589
16 Bosnia and Herzegovina -0.6161 0.1875 0.8036
17 Albania -0.6607 0.1696 0.8304
Source: The authors' calculations on the basis of World Bank and FAOstat, 2017
All other countries had net preferences flow smaller than zero. Good ranking of Serbia can be explained by export performances of this country, especially positive export/ import coverage that is consequences of trade agreements of Serbia with the EU, CEFTA countries and EFTA (Switzerland, Norway, Iceland and Liechtenstein) as well as with Russia, Belarus, Kazakhstan and Turkey. The dominant export market for agricultural products from Serbia is the EU market, where last year exported more than 50% of agricultural products. The second most important market of the region is the market of CEFTA agreement. This structure of exports indicates that the most important markets for Serbia are EU and CEFTA (Ristic and Obradovic, 2015).
Figure 1. Correlation between GDP per capita and economic performances of agriculture
GDP
per capia
50,000 NL
DE^
40,000 fr/
30,000 SI
20,000 K 01 /
™ HR RO BA/\ / PL/ \ / vbi sk V 10,000^^ H(j ME RS BG 0
AL^ VMK
-0.8 -0.6 -0.4 -0.2 0 0,2 0.4 0.6 0,8 1 <P
Source: The authors' calculations on the basis of World Bank and FAOstat, 2017
It is very important to notice that there is a strong positive correlation between the levels of development (observed as GDP per capita) of selected countries and the performances of the agricultural sector (Coefficient of correlation is 0.87). Therefore, it is possible to conclude that among other factors, the level of economic development has a significant impact on economic performance of agriculture (Figure 1).
Conclusion
The study assesses the economic performances of agriculture of current and former CEFTA. The Netherlands, Germany and France are included in analysis as a benchmark. Two clusters of selected countries were identified, differing significantly in terms of the importance of agriculture in their economy. Importance of agricultural sector is still high in Romania. Therefore, Romania is more similar to CEFTA than EU countries. On the other hand, Montenegro was placed among EU countries. In order to rank development performances of these countries, PROMETHEE method was used. Based on this analysis, countries can be roughly divided into three groups. First group consisted of
the most developed countries that were used as a benchmark. Members of the second group are former CEFTA countries that joined EU in 2004. All other countries are members of the third group. The study showed that there is a gap in development of agriculture between CEFTA countries and selected EU countries. Among EU countries, Bulgaria, Croatia and Romania have the least developed agricultural sector. It can be assumed that effects of EU accession have yet to become visible. On the other hand in CEFTA countries performances of agricultural sector are far from EU. Among these countries, the best ranking has Serbia, and agricultural sector in Albania is the least developed. With respect to all limitations of the study related to definition of economic performances of agriculture, conclusions can be summarized as follows:
• Empirical analyses of agriculture in the CEFTA and selected EU countries indicate a large differentiation between these countries. Among other factors, the level of economic development has a significant impact on economic performance of agriculture. So, economic development of agriculture is determined by the level of socio-economic development.
• Significant difference between production and export performances of agricultural sector of the EU and CEFTA countries indicate that there is a need for adequate instruments of agricultural policy that will improve agricultural sector in these countries before EU assessment. Agricultural policy of CEFTA countries must still be oriented on increasing of productivity of agricultural sector in order to reach out EU and to get chance to compete on EU market.
• In recent years, the EU has been faced with different economic, social and political problems. In addition to the global economic crisis and migrant crisis, the new serious problem is the decision of citizens of Great Britain to leave the EU. In these circumstances, it is unlikely that the further enlargement of the EU will be soon reached. Therefore, the position of the countries that aspiring to join the EU is not favourable. This political-economic trends are forcing these countries to find temporary alternative solutions for achieving higher economic growth. One of the possible solutions is deeper integration within the CEFTA agreement, in preparation for entry into the EU.
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EKONOMSKE PERFORMANSE POLJOPRIVREDE U CEFTA I BIVSIM CEFTA ZEMLJAMA6
Jelena Birovljev7, Danilo Bokic8, Bojan Matkovski9, Zana Kleut10
Rezime
Sve zemlje CEFTEsu se nakon IIsvetskog rata susrele sa veoma slicnimfazama ekonomskog razvoja. Vecina ovih zemalja su bile centralno-planske socijalisticke ekonomije, a politicke promene sa kojim su se susrele krajem 20. veka, uticale su na promene u celokupnom ekonomskom sistemu, pa i u poljoprivrednom sektoru. Cilj ovog rada je komparativna analiza ekonomskih performansi poljoprivrede ovih zemalja i zemalja koje su ranije cinile CEFTU (Poljska, Ceska, Slovacka, Mactarska, Slovenija, Bugarska, Rumunija i Hrvatska), a koje su se pridruzile Evropskoj uniji nakon 2014. godine. Razvojne performanse poljoprivrede su posmatrane sa stanovista proizvodnih i izvoznih performansi ovog sektora ekonomije, koristeci komparativnu analizu. Rezultat su pokazali da postoji gep u razvoju poljoprivrede izmetu CEFTA zemalja i selektovanih zemalja EU, a performanse poljoprivrednog sektora ovih zemalja su daleko od EU.
Kljucne reci: Poljoprivreda, Promethee metod, Klaster analiza, EU, CEFTA. JEL: Q17, Q18, F15
6 Rad predstavija deo istrazivanja na projektu: Odrziva poljoprivreda i ruralni razvoj u funkciji ostvarivanja strateskih ciljeva Republike Srbije u okviru Dunavskog regiona (III 46006), finansiran od strane Ministarstva prosvete, nauke i tehnoloskog razvoja Republike Srbije.
7 Redovni profesor dr Jelena Birovljev, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinsku put 9-11, 24000 Subotica, Srbija, Telefon: +38124628066, E-mail: birovljevj@ef.uns.ac.rs
8 Danilo Bokic, asistent, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinsku put 9-11, 24000 Subotica, Srbija, Telefon: +381214852907, E-mail: danilo. djokic@ef.uns.ac.rs
9 Bojan Matkovski, asistent, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinsku put 9-11, 24000 Subotica, Srbija, Telefon: +38124628046, E-mail: bojan. matkovski@ef.uns.ac.rs
10 Zana Kleut, asistent, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinsku put 9-11, 24000 Subotica, Srbija, Telefon: +381214852907, E-mail: zana.kleut@ef.uns.ac.rs
