Proc. Latv. Univ. Agr., 2012, 28(323) DOI: 10.2478/v10236-012-0011-4

Efficiency of the European Social Fund Contribution Effect of Integration on the Gross Value Added in to the Regions of Latvia the Baltic States Dairy Sector Secondary Level

Ilze Latviete* Jānis Ozoliņš* Department of Economics, LLU Faculty of Economics, LLU

Abstract. From 2004 till mid-2007, the economics of Latvia experienced fast development, which to some Abstract. Dairy sector is an essential part of Baltic States economies in terms of created gross value added extent was influenced by accessing the European Union (EU), which in its turn provided access to the EU funds (GVA) and labour usage. The dairy sector’s potential to create economic effect is underutilised as a result of and subsequently to significant investment in the country’s development, thus also affecting the topicalities of fragmented production structure and ensuing low economic efficiency. Integration can facilitate concentration social security and employment. Because of the world recession, the EU has experienced an economic downfall of the sector’s market structure. The aim of this paper is to evaluate the effect of dairy sector secondary-level which hit Latvia and its regions very hard, causing a significant reduction in the economic activity, increase in company integration on the creation of GVA. To accomplish the aim, an extensive sample of 54 companies the unemployment level, and the risk of social stratification. To facilitate the socio-economic development of is used whereas previous research has been based on data of only 5–10 largest Baltic States companies. It is the regions, to increase the level of welfare in the regions with lower socio-economic development indicators, concluded that integration characteristics of dairy processing companies significantly influence relationships as well as to prevent the possibility of appearance of unfavourable situations in the future, it is necessary to use which express their GVA creation pattern. Dominating horizontally integrated dairy processing companies correctly the EU funds available in Latvia, including the financing of the European Social Fund (ESF). In the are the most valuable to the economy as their GVA increase rate which results from net turnover growth is period from 2004 till 2010, the Riga region has acquired 33% of the total ESF financing in the welfare sector, the highest. Non-integrated companies’ GVA growth rate provided that their net turnover grows is lower than Latgale has the second largest financing – 25%, but the other resources have been acquired in a more or less for dominating horizontally integrated companies. Increases in company size do not statistically significantly equal amounts in the other regions: Kurzeme (16%), Zemgale (14%), and Vidzeme (12%). The ESF financing increase the relation of GVA to the sum of net turnover and other operating income. Both successful and in the welfare sector has influenced the socio-economic indicators of the regions. Functional correlations are commercially weak companies can produce high GVA in respect to their size. However, only the successful observed among the ESF financing in the welfare sector and the value changes in the number of registered companies are expected to generate positive growth dynamics, be economically efficient and can be relied unemployed persons, job seekers and the territory development index. upon as driving force of dairy sector growth. Key words: European Social Fund, financing, activity, development of territories. Key words: Dairy processing, integration, economic effect. crime, drug addiction and alcoholism also increases Introduction 2007), therefore Latvian, Estonian and Lithuanian and, as a result, general social degradation sets in, Dairy sector is an essential part of Baltic States dairy sectors should preferably be analysed which can spread in the entire country and cause a economies by created GVA and labour usage weight together. Each of the Baltic States has specific deep economic crisis. in the total respective indicators of these countries. problems, nevertheless the main problems both in The EU funds are the main financial instrument Appropriate natural resources, existing infrastructure, the primary and secondary level of the dairy sector that supports less favourable areas and unsecured dairy farming and processing traditions, are fragmented production structure and resulting groups of population to reduce socio-economic favourable geographic position in the context low economic efficiency (Vasiliev et al., 2011; differences between the Member States and their of world agricultural market liberalisation are Jansik, 2009; Krieviņa, 2009; Zemeckis, Gapšys, regions. Thus, Latvia receives financing as a country main elements of rationale to retain and develop Mikelionyte, Eicaite, & Girgždiene, 2009; Lepasalu, not particular its regions, as it is practised in most of the sector. Transition from command to market Arney, Soidla, & Poikalainen, 2009; Sepp & Ohvril, the EU Member States. economy and separation from the USSR milk 2009; Jasjko et al., 2007; Špoģis & Radžele, 2007; Previous research shows that regional market, according to Eurostat data, resulted in Glinskiené, Daraškevičiūté, & Lipinskiené, 2006). opportunities and interests to acquire the EU funds a decrease of produced raw milk in the Baltic The structural problems of dairy sector secondary financing are not equal. The response of the region’s States by 42–49% in the period from 1990 level are the most significant factor hindering economics on the efficiency of the invested resources until 1996. In the period until 2010 there has development of the whole sector. Baltic States is not identical either because there are different been no significant increase in the amount of dairy processing companies are small in the world economic advantages and economic development produced raw milk, and growth trends in milk market and export mainly industrial products while interests between the regions (Saktiņa, 2008). In processing products have been minimal. The dairy competing with high value added products in the the territories which have attracted larger EU funds sector’s potential to create economic effect is narrow and shrinking local market. The amount of financing faster development has taken place, whereas underutilised. value added created is not sufficient to pay higher the improvement of the socio-economic indicators in Existing trade patterns confirm that a single prices for raw milk which according to Miglavs et al. the other regions is slower, their differences continue market for raw milk and fresh milk products exists (2008) is the main stimulus to produce more and thus increasing. in the Baltic States (Estonian Competition Board, is a precondition for the sector to develop. ______* Author’s email: [email protected] © Latvia University of Agriculture (LLU) 2012 J. Ozoliņš Effect of Integration on the Gross Value Added in the Baltic States Dairy Sector

Integration can directly or indirectly facilitate not specialized in goat’s milk processing, were not production capacity utilisation, increases in scope of engaged primarily in ice cream production not production, economic efficiency, cost optimisation, using fresh milk, did not produce milk candy, or higher value added production, research and did not generate more than 40% of income from development, and acquiring new markets. GVA other activities than dairy processing (Pārtikas is the main indicator for measuring the economic un veterinārais ..., 2010; Valstybinė maisto ..., effect of a branch of economy because it specifies its 2010; Veterinaar-ja toiduamet, 2010). Companies contribution to the GDP. As integration in secondary undergoing liquidation were also not included in the level is an instrument that may be used to realise research sample. the economic potential of dairy sector, it is useful to Taking into account availability of Lithuanian research the impact of integration on GVA created by data starting from year 2004 (prior to this period the the dairy processing companies in the Baltic States. companies in this country were not obliged to submit The impact of integration characteristics on the annual reports to the Valstybės įmonė Registrų GVA created by the dairy processing companies centras) and involved countries’ EU membership has not been researched to a sufficient extent. since 2004, this year was selected as the starting Existing integration-related research of the Latvian period for the research. The end of research period sector includes Leimane et al. (2006), Jasjko et al. is year 2010 because annual reports in some of the (2007), Krieviņa (2009). Several scientists have Baltic States are publically accessible 10 months devoted fragments of their papers, except for fully subsequent to the end of the respective financial year. devoted but not recent work by Kedaitiene, to dairy The sample of dairy processing companies was close sector integration problems in the other Baltic to the whole population as in the year 2008 sample States (Girgzdiene, Hartmann, Kuodys, Vaikutis, & companies were creating approximately 98% of dairy Wandel, 1999; Hartmann, Berkum, & Wandel, processing turnover. 1999; Kedaitiene & Hockmann, 2002; Vaznonis In order to analyse the economic effect of various & Danilevičé, 2006). A significant drawback of types of dairy processing companies, the author all existing research papers is reliance on general used GVA at factor cost. Information included in industry statistics and data of 5–10 largest dairy the annual reports allowed for calculation of GVA processing companies only. Usage of detailed data at factor cost in accordance with methodology of companies covering all the spectrum of company suggested by the Central Statistical Bureau of sizes and types is an important research opportunity. Latvia (Latvijas Republikas Centrālā ..., 1999) for The author has set the following paper hypothesis: 80% of annual reports’ data in Estonia and 88% of dairy sector secondary-level company integration the respective Latvian data. Data availability limited characteristics significantly influence the GVA which the calculation of GVA only to four companies in they create. The aim of this paper is to evaluate the the Lithuanian sub-group. However, Lithuanian effect of dairy sector secondary-level company data are important because they are for companies integration on the creation of GVA. The following AB “Pieno žvaigždės”, AB “Rokiškio sūris”, AB tasks had been set to reach the aim: (1) evaluation “Žemaitijos pienas”, and UAB “Vilkyškių pieninė” of independent factors determining creation of GVA which were all dominating horizontally integrated for various integration types of dairy processing companies. When considering their turnover they companies; (2) analysis of companies which create were the largest not only in Lithuania but also in the highest absolute amount of GVA; (3) exploration Baltic States. Log-transformed versions of several of GVA weight in net turnover and other operating variables were used in order to achieve close to income. normal distribution. Integration can be characterized by at least seven Materials and Methods integration dimensions (Ozoliņš, 2010) whereas this A database including data of Latvian, Lithuanian paper uses one of them – integration direction. Several and Estonian (the Baltic States) dairy processing integration direction dimension categories used in the companies’ annual reports submitted to the enterprise paper need to be explained. Non-integrated companies registrars was used to accomplish the research tasks. are dairy processing companies neither owned by The sample included all Baltic States’ approved other dairy processing companies nor dairy farmers dairy processing companies as of October 1, 2010 and their organizations. Non-integrated companies unless they had not submitted annual reports, were that both produce and process milk are dairy farms J. Ozoliņš Effect of Integration on the Gross Value Added in the Baltic States Dairy Sector that have extended their scope of activity into did not result in statistically significant relationships. small-scale processing. Vertically integrated dairy Therefore the author concluded that relationship processing companies are owned by dairy farmers or between company size, expressed in log-transformed their organizations such as co-operatives. Dependent net turnover, and GVA can be used to reveal the horizontally integrated companies are owned by impact of integration on the economic effect of other dairy processing companies. Dominating various categories of dairy processing companies. horizontally integrated companies or their owners Log-transformations of both dependent and own other dairy processing companies, or other dairy independent variables were carried out to ensure that processing companies have been merged to the dairy data are close to normally distributed. As a result of processing company. their interpretation specifics (Arhipova & Bāliņa, Descriptive statistics, time series analysis, 2006), log-log models are very practical to explain non-parametric and parametric statistical analysis relationships. Direction coefficients (β) denote methods, abstract-logical and monographic methods increase in GVA in percentage in case net turnover were used. Linear and non-linear regression methods increases by 1%. Although for two dairy processing with single and multiple independent variables were company categories (Table 1) regression model used. Solely integration via ownership connections constants were statistically insignificant, models was taken into account on account of reasons of data were statistically significant and direction coefficients availability. Other integration arrangements such as were analytically valuable. contractual are not examined due to confidentiality Regression model analysis indicates that highest of information. Currency conversion from Lithuanian GVA increase in percentage can be expected litas (LTL) and Estonian kroon (EEK) to Latvian lats when the net turnover of dominating horizontally (LVL) was carried out using Bank of Latvia official integrated companies increases: 1% increase in exchange rate as of the end of each year. net turnover results in 1.1% increase in GVA. Approximately the same is the result for non- Results and Discussion integrated dairy processing companies that both Univariate analysis of variance allowed produce and process milk. Lowest growth of GVA suggesting that statistically significant differences is expected for dependent horizontally integrated exist between log-transformed mean GVA values of companies – only 0.86% increase per 1% net turnover non-integrated, dominating horizontally integrated increase. The β value for vertically integrated and dependent horizontally integrated dairy companies is very close to the model prepared for all processing companies. GVA values of vertically sample companies. integrated companies did not have statistically Dominating horizontally integrated dairy significant differences. processing companies, as suggested by regression In order to explore independent variables which analysis results, are the most valuable to the influence GVA, the author analysed over 100 research economy, because their GVA increase rate would be database variables, including dummy variables the highest, provided that they are able to develop. As for various integration dimensions, most income these companies (unless mergers have taken place) statement and balance sheet items and derived own dependent horizontally integrated companies financial ratios. Correlation, ANOVA, linear and whose GVA growth rate is the lowest, it can be non-linear regression methods were used. The author suggested that redistribution of resources within the found that several income statement and balance sheet company groups takes place in favour of dominating variables describing company size had the highest companies. Nevertheless, the redistribution of influence on GVA. Highest determination coefficients resources can not be the major factor contributing and statistically significant model estimates were to higher results of dominating companies because achieved when log-transformed net turnover was dependent companies are in most cases small relative used as a single independent variable. Integration to their parent companies. of dairy processing companies results in larger- Although the growth rate of economic effect sized economic structures. Net turnover is one of the for the small companies which both produce and key parameters used to assess the size of company process milk is approximately the same as for the (European Commission…, 2008). Evaluation of category with the highest value, such companies can other variables used to determine company size in the not create a significant part of the dairy processing EU, balance sheet value and number of employees branch economic effect. Small size mostly limited J. Ozoliņš Effect of Integration on the Gross Value Added in the Baltic States Dairy Sector

Table 1 Gross value added log-log models of selected Baltic States’ dairy processing company categories

95% confidence interval 95% confidence interval for constant for β Category Regression model R square lower upper lower upper bound bound bound bound Sample Y=-0.96+0.94x 0.91 -1.36 -0.56 0.92 0.97 Non-integrated Y=-0.01+0.95x 0.86 -1.65 -0.37 0.90 1.00 Dominating horizontally Y=-3.6+1.10x 0.84 -5.47 1.21 0.99 1.21 integrated Dependent not not horizontally Y=0.10+0.86x 0.87 statistically statistically 0.79 0.92 integrated significant significant Vertically not not integrated Y=-0.75+0.92x 0.95 statistically statistically 0.85 0.98 significant significant Non-integrated which produce Y=-2.17+1.09x 0.84 -4.48* 0.15* 0.91 1.27 and process milk Note. Table includes models, constants and β values which are statistically significant at least at 0.05 level if not indicated otherwise; Y – ln (gross value added at factor cost); x – ln (net turnover); * – statistically significant at 0.1 level. by on-farm milk production capacity allows such all companies (except Latvian company “Rīgas companies to pursue segment differentiation piensaimnieks”) were horizontally integrated strategies in local market which is characterized by (Table 2). Among the 20 companies with negative demographic tendencies. A considerable part highest mean GVA, 65% of companies were of their GVA is attributable to public support which horizontally integrated, 10% – vertically integrated, they receive as agricultural companies. Thus, they and the rest being non-integrated. Largest dairy can not be expected to become major contributors processing companies by GVA created were also to the economic effect of the dairy sector secondary important providers of job opportunities, especially level. Vertically integrated and non-integrated in Lithuania. Estonian dairy processing companies companies’ rate of GVA increase is similar and close were the most effective in the Baltic States in terms to the general value of the whole sample. However, it of GVA per employee. should be noted that vertically integrated companies GVA per employee for the leading Estonian are tended to maximize the income of their owners – company “Tere” was more than four times higher dairy farmers. Thus, GVA data reflects results after than for Latvian company “Latgales piens”. partial redistribution of resources via higher raw milk “Tere” was the largest Estonian dairy processing purchasing prices to the dairy farmers. Higher milk company – its turnover in 2010 was over prices stimulate dairy farmers to produce more raw 10 times higher than for “Latgales piens”. Although milk, which facilitates growth of the dairy sector. specialisation of both companies is similar (fresh Vertically integrated companies have a potential milk products), execution differs radically. “Tere” or are major contributors to the economic effect of produces a wide range of innovative products in the dairy processing both in the Baltic States and world-class packaging for the Baltic States market. several EU-15 countries while the contribution Dairy products of “Latgales piens” are packaged in a of the non-integrated companies tends to be very simple way or even sold in bulk as company has relatively smaller. 20 sales outlets in the low-income Latgale region in Among the 10 sample companies with highest which 70% of products are sold. In addition, “Latgales mean GVA, during the period of 2004–2010, piens” is in position of dependence. It is owned J. Ozoliņš Effect of Integration on the Gross Value Added in the Baltic States Dairy Sector

Table 2 The Baltic States’ dairy processing companies generating the highest economic effect, mean sample company data, 2004–2010

Mean GVA Mean GVA, thous. Mean number Rank Company name Country per employee, LVL of employees thous. LVL 1 Pieno žvaigždės Lithuania 28500 2573 11 2 Rokiškio sūris Lithuania 19354 1794 10 3 Žemaitijos pienas Lithuania 16541 1841 9 4 Tere Estonia 8527 342 24 5 Rīgas piena kombināts Latvia 6972 551 12 6 Rīgas piensaimnieks Latvia 5571 280 19 7 Vilkyškių pieninė Lithuania 4452 449 9 8 Valmieras piens Latvia 3438 435 7 9 Preiļu siers Latvia 3147 321 9 10 Valio Eesti Estonia 2953 163 18 11 E-piim Estonia 2688 199 13 12 Maag Piimatööstus Estonia 2360 153 15 13 Vöru juust Estonia 2299 152 15 14 Saaremaa piimatööstus Estonia 2240 279 8 15 Tukuma piens Latvia 2167 203 10 16 Balbiino Estonia 1690 156 10 Põltsamaa meierei 17 Estonia 1566 79 19 juustutööstus 18 Latgales piens Latvia 1021 171 6 19 Smiltenes piens Latvia 995 100 10 20 Talsu piensaimnieks Latvia 944 96 9 Note. Table includes the data of companies whose annual reports’ data included information for GVA calculation. by 2nd largest Latvian dairy processing company and allows exploring GVA creation issues from a “Preiļu siers” in which GVA per employee is not different angle. significantly higher. The author draws a conclusion Scatterplot analysis of GVA coefficient and that the key factors contributing to the large efficiency other possible independent variables influencing gap between “Tere” and “Latgales piens” are scope it did not point to existence of linear or non-linear of production, degree of innovation orientation, relationships. It was possible to obtain regression chosen target market segments, and channels models with sufficient R square values neither using of distribution. the least squares method nor maximum-likelihood The author introduced a derived variable estimation. The author also drew a conclusion calculated as GVA over the sum of net turnover and that increases in company size do not statistically other operating income to measure dairy processing significantly change the GVA coefficient values. companies’ efficiency in creating GVA (further A wide variety of company types explains lack of in the text – GVA coefficient). It should be noted general relationship. For example, among large that GVA coefficient does not measure economic companies there are the ones who are listed on stock efficiency – in fact, economically inefficient exchange, thus interested to present their profitability companies with excessive personnel expenses, high indicators to their shareholders while others attempt depreciation and negative profit ratios can have high to work without profit for tax avoidance reasons. GVA coefficient values. It does, however, measure Some large companies produce an extensive variety companies’ economic effect in relation to their size of high value added products while others specialise J. Ozoliņš Effect of Integration on the Gross Value Added in the Baltic States Dairy Sector in producing a few industrial commodity-type dairy dairy processing company in the Baltic States products in large quantity. according to net turnover of group, was 6th by In the period of 2004–2010, mean GVA rank. “Rīgas piensaimnieks”, 8th by rank, is one coefficient values were highest for several companies of the large Latvian dairy processing companies. (Table 3) which both produce and process milk GVA coefficient values of these companies were (“DK Daugava”, “Saidafarm”, “Nopri talumeierei”), mainly influenced by personnel costs and positive and for two small processing companies “Codori” profit ratios. and “Druvas pārtika”. Main factors contributing Companies “Richterite meierei” and “Unik” had a to superior indicator values were the high relatively high personnel cost ratio and negative mean weight of personnel-related costs, positive profit profit ratios. Although these companies’ economic ratios, and depreciation for some companies. effect in relation to their size was rather high, they Lithuanian “Pieno žvaigždės”, the 2nd largest were commercially not successful. Companies such

Table 3 Mean values of gross value added coefficient and its influencing components in the sample of the Baltic States’ dairy processing companies, 2004–2010, times

Relation of depreciation Gross value and the total of net Rank Company name Country added Profit ratio turnover and other coefficient operating income 1 Nopri talumeierei Estonia 0.42 0.06 0.09 2 DK Daugava Latvia 0.42 0.15 -0.02 3 Codori Estonia 0.37 0.02 0.01 4 Saidafarm Estonia 0.33 0.08 0.08 5 Druvas pārtika Latvia 0.26 0.06 0.01 6 Pieno žvaigždės Lithuania 0.25 0.06 0.03 7 Richterite meierei Estonia 0.24 0.24 -0.09 Rīgas 8 Latvia 0.24 0.03 0.06 piensaimnieks 9 Unik Estonia 0.24 0.03 -0.04 Vigala 10 Estonia 0.23 0.04 0.05 piimatööstus 11 Braslas Latvia 0.22 0.08 -0.01 Eesti juustu 12 Estonia 0.20 0.01 0.00 tootmise 13 Žemaitijos pienas Lithuania 0.20 0.04 0.03 Põltsamaa meierei 14 Estonia 0.19 0.05 0.07 juustutööstus Lazdonas 15 Latvia 0.19 0.04 0.01 piensaimnieks Maag 16 Estonia 0.18 0.03 0.06 piimatööstus 17 Latgales piens Latvia 0.18 0.03 0.02 Talsu 18 Latvia 0.18 0.04 0.02 piensaimnieks 19 Dessert Estonia 0.18 0.05 0.01 20 Dundaga Latvia 0.18 0.02 0.01 Note. Table includes the data of companies whose annual reports’ data included information for GVA coefficient calculation. J. Ozoliņš Effect of Integration on the Gross Value Added in the Baltic States Dairy Sector as “Pieno žvaigždės” have stimulus to objectively markets. Thus they are not expected to grow show profit (due to share listing on stock exchange), significantly. their size makes it difficult to avoid paying salaries 3. Vertically integrated companies’ GVA growth and related taxes in full compliance with legal rates when subjected to increased net turnover requirements, and are large enough to compete at are close to average. The calculation can not least in the Baltic States market. These companies objectively evaluate the share of GVA that is are most valuable to the economy. Their market redistributed to the primary level of the dairy power though should be counterbalanced by support sector via raw milk prices. to cooperation structures in the primary level of the 4. Non-integrated companies are not among the dairy sector in order to preserve and increase stimuli companies that create highest GVA in absolute to produce more raw milk. terms. Non-integrated companies’ GVA growth Correlation analysis in the Baltic States rate provided that their net turnover grows dairy processing company data set did not yield is lower than for dominating horizontally statistically significant relationships between net integrated companies. turnover and profit ratio. A study in Irish dairy 5. Large efficiency gaps exist between the Baltic processing, on the contrary, found that with some States’ dairy processing companies in terms of exceptions company size was strongly correlated GVA per employee. Estonian dairy processing with profitability due to growth in efficiency companies tend to have superior results over the (Department of Agriculture..., 2003). Among the 1st other Baltic States in this aspect. Factors such quartile of Baltic States dairy processing companies as scope of production, degree of innovation with the highest profit ratios, the author found that orientation, chosen target market segments half of them specialise in high value added products and channels of distribution determine the (mainly companies that both produce and process differences. milk or exploit results of successful R&D). Only 6. Increases in company size do not statistically about 12% of companies were large production scope significantly increase the relation of GVA to companies by the Baltic States standards. Second the sum of net turnover and other operating quartile comprises the largest dairy processing income. Both successful and commercially weak companies and a few small companies who companies can produce high GVA in respect specialise in high value added products. to their size. 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Acknowledgements The paper has been supported by the European Social Fund within the project “Support for the Implementation of Doctoral Studies at Latvia University of Agriculture” (sub-activity 1.1.2.1.2. Support for the Implementation of Doctoral Studies); agreement No. 2009/0180/1DP/1.1.2.1.2/ 09/IPIA/ VIAA/017, contract No. 04.4-08/EF2.PD.44.