The limitations of competition in the insurance markets of Slovenia, Croatia and Serbia

Abstract The article analyses the situation in the insurance markets of Slovenia, Croatia, and Serbia in order to provide the insight into the limitation of competition. The study of the limitation of competition was conducted using the theoretically founded indicators of concentration and inequality as follows: Concentration ratio, Herfindahl-Hirschman index, Lorenz curve, Gini coefficient, and Entropy index. The indicators were calculated for all the countries between 2004 and 2011. By comparatively analysing the obtained values of the indicators of concentration and inequality, we came to the conclusion that all three markets are characterised by a similar movement of the indicator, as well as that Croatian market, despite the relatively uneven market share distribution between individual companies, is more competitive than the other two.


Introduction
Studying the insurance market as a part of the financial market is very complex but also important because this sector occupies a significant position in the financial area of each country. The article analyses the limitations of the insurance markets of Slovenia, Croatia, and Serbia. Comparative analysis of the three markets aims to provide a clear image of the limited competition in the insurance markets, that is to say the level of concentration and inequality of market share distribution between insurance companies in these countries. The importance of the insurance market comes from the fact that it was among the first to participate in the process of internationalisation. The process of globalisation, liberalisation, and deregulation significantly affected the performance of the sector, the conditions of competition in it, and especially the business risks (Njegomir & Stojić, 2012). In the practice of anti-monopoly authorities it is customary to use indices of concentration and inequality for measuring the conditions of competition and companies' monopoly power, therefore the above indicators shall be used in this research (Saving, 1970).
Analysed markets were selected so as to represent the countries of a region characterised by different levels of development. Slovenia and Croatia have completed the transition and are already in the EU. Serbia is still in the process of slow and incomplete transition, away from full membership in the EU. For more than two decades these countries' markets have belonged to a single market, therefore it is interesting to analyse the development of competition in them from 2004, 15 years after their separation. The study is particularly interesting because today's economy is in the global economic crisis, which affects the business conditions in the sector, and requires a more comprehensive approach to the management of risk and insurance companies' capital (Marović, Njegomir, & Maksimović, 2010).
The article affirms the application of economic analysis in the field of competition. The application of economic analysis in this field is the world trend, which started in the US, continued in the EU, and with less intensity in the region as well. The article points out the advantages, but also the limitations in the application of the indicators of concentration and inequality. Further development of anti-monopoly legislation in the countries of the region will be towards greater use of economic analysis, especially the use of different indices of concentration and inequality.

Literature review
The measurement of the competition's limitation level in various markets is attracting the attention of many researchers. It has been studied on the example of the real sector and on the example of financial sector. Many authors have provided assessments on the conditions of competition using the usual indicators of concentration and inequality. One of the first and also the most important works in this field is the work of Adelman (1951), which deals with the theoretical analysis of different concentration indicators. The following is a very important work by Vanlommel, de Brabander, and Liebaers (1977), which examines the level of concentration on the example of 119 Belgian industry sectors, as well as the work by Curry and George (1983), which deals with the theoretical and practical analysis of aggregate concentration on the example of the UK and US economy in the period between 1909 and 1980. The works which deal with the sectorial assessment of the level of concentration and inequality of supply are also important. Belobaba and Van Acker (1994) studied the level of concentration in the US air transport market, and Einarsson (2008) investigated the level of concentration in the retail markets of the Nordic countries. The prominent works in the field of financial sector analysis are by Haaf (2002, 2002a), who applied different indicators of concentrations to analyse the conditions of competition in the banking sector of European and other developed countries. The contribution of the authors in studying the level of concentration and inequality in the financial sector is the most important. Significant work to explore the limitation of banking market is by Al-Muharrami, Matthews, and Kahabari (2006), which deals with the determination of concentration level of the Arab GCC banking system.
The work by Mitton (2008) should be distinguished in the study of concentration indicators, which designates that concentration level is greater in smaller countries, as well as that the importance of concentration is largely dependent on the institutional factors that give them a certain power. Regardless of the various theorists who have discussed various ways to determine the level of concentration and inequality of the market, the claim articulated by Davies (1979Davies ( , 1980 is still valid and states that a universal concentration indicator has not yet been found. Instead, we use several indicators in order to give a comprehensive image of competitive conditions in the market. The works that are prominent in the region, in which we are to study the level of insurance market limitation, are by Dumičić (2002, 2003) dealing with the supply concentration on the example of the banking sector in Croatia. As for Serbia, the interesting work which is related to the determination of concentration in the market of cable distributors is by Maksimović, Radosavljević, and Borisavljević (2011), and the work dealing with the concentration of non-specialist retail trade of Niš by Stojanović and Radivojević (2010).
The work to be presented is a continuation of the research previously conducted regarding Serbian insurance market (Kostić, 2009) and limitations in the application of concentration indicators on the example of the insurance market of a number of countries (Maksimović & Kostić, 2012). This work is more comprehensive and advanced research, since it contains a long time series data and the broader framework of analysis, in order for the assessment of competition conditions to be more comprehensive.

Research hypotheses
Based on the fact that the analysed markets are a part of the broader, European market and that there is a tendency for their further involvement in European integration, the reduction of limitation level is expected to be intensified in the insurance markets of the analysed countries.
The financial sector is constantly open to entry of foreign competition, so once leading insurance companies lose their importance. This finding confirms the conclusion given in a previous work where it is clearly indicated that, in some markets (in this case the Croatian insurance market), there was a reduction concerning the share of major competitors and the values of all the concentration indicators used (Tipurić et al., 2002). We shall try to verify this statement by testing appropriate hypotheses, whose proof is important because the research is carried out in considerably changed circumstances, primarily related to the financial and economic crisis. The research hypothesis that will be analysed is: Hypothesis 1: The level of supply concentration in all the analysed markets reduces in the entire period of the research.
The following hypothesis which is associated with the previous one and is related to the indicators of inequality is: Hypothesis 2: The level of inequality in the market share distribution in all the analysed markets reduces in the entire period of the research.
Given that this is a market that once belonged to a single market it can be concluded that in the value movement of the indicators of concentration and inequality in the analysed markets, there is a high level of agreement. This suggests a new research hypothesis: Hypothesis 3: Between the movement of the indicators' values in different markets there is a high level of statistically significant correlation.

Data collection and methodology
For the analysis of competition conditions in the insurance market of Slovenia, Croatia, and Serbia, we used the data on total premium at the disposal of the association of supervisors and individual agencies involved in the supervision of insurance companies. Data from the following institutions were used in the paper: International Association of Insurance Supervisors (IAIS) (http://www.iaisweb.org/IAIS-members-31), National Bank of Serbia (http://www.nbs.rs/internet/cirilica/60/60_2/index.html), Croatian Financial Services Supervisory Agency , 2009), and Slovenian Insurance Supervision Agency (2004, 2009. The total premium was chosen to be a variable for measuring concentration for the following reasons: the premium is the most important component of the insurance company's revenue and is the result of its core activity. Data on total premium are in regular reports and publications of the regulatory authorities responsible for the supervision and control of insurance companies (Kostić, 2009).
The data include eight consecutive years (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011). Using the collected data corresponding values of concentration indicators were obtained, and were used for a comparative analysis of the insurance markets' limitation level in these countries. Studying of the level of concentration and inequality in the insurance market was performed using a number of indicators of concentration and inequality, namely: Concentration ratio of the four largest companies and Herfindahl-Hirschman index, Gini coefficient, Lorenz curve, and Entropy index.

Concentration ratio
The Concentration ratio is a sum of market shares (s i ) of the largest n companies on the analysed market (Waldman & Jensen, 2001;Begović et al., 2002): This ratio is most often calculated as the sum of market shares of the four largest companies in the market. Taking a great number of companies reduces its analytical significance. Researchers or government agencies involved in the level of supply concentration supervision decide on the number of companies to be included in the calculation of this indicator, provided that they use it as an official indicator (Martin, 2002). Given that the most common number of companies included in the determination of the ratio is four, the indicator was named Concentration ratio of the four largest companies (CR4).
In the EU the high level of market concentration exists when the CR4 index exceeds the value of 25, while in the US the limit is 50. The market where the index is above 50 is considered to be highly concentrated, the one where the value is between 25 and 50 is moderately concentrated, and the one with the value below 25 is non-concentrated market (Kostić, 2009). In the literature, there are interpretations that the value of the index above 40 indicates an oligopolistic market, while the value over 90 designates market similar to monopoly (American Bar Association, Section of Antitrust Law, 2005).

Herfindahl-Hirschman index
The Herfindahl-Hirschman index, as a convex function of the analysed companies' market shares, is an index sensitive to the number of corporations and inequality in the distribution of their market shares. The importance assigned to each company corresponds to the value of its market share (w i =s i ), which implies that the index is determined as the sum of squared market shares of individual companies (Martin, 2002), i.e.: where s i is the market share of i firm. This index provides a more accurate image of the market concentration level, since, because of the squaring of market shares, greater importance is assigned to the firms with larger market share than to those with smaller. The index value is in the interval between 0 and 10.000, or between 0 and 1, depending on the method of expressing market share. Reference values of the index are shown in Table 1.

Lorenz curve
The Lorenz curve is often used as the indicator of inequality in the distribution of market shares between individual companies. Inequality is assessed through the deviations of the Lorenz curve from absolute equality (45° curve), which shows a hypothetical situation in which all companies would have equal market share ( Figure 1).

Gini coefficient
The Gini coefficient quantifies the deviation of the Lorenz curve from absolute equality curve, and measures inequality in the distribution of market shares between the companies. The Gini coefficient is determined by the following form (Lipczynski, Wilson, & Goddard, 2009): where n is the rank of firms sorted in descending order from largest to smallest, N is the number of firms involved in the calculation, and x i firm size measured through the value of sales (in the analysed case the total premium). The value of this indicator is in the interval between 0 and 1, where 0 means that the distribution of market shares between the companies is equal while 1 means that the overall market belongs to a corporation (White, 1982, 544).

Entropy index
The Entropy index is an indicator of inequality in the distribution of market shares ( where s i is the market share of i firm, and log e 1 s i the reciprocal value of the natural logarithms of market shares. The index value can range between 0, which indicates a monopoly, and E=log e (n) when there are n companies of the same size in the branch. The entropy coefficient is taken from the theory on information which shows the level of decision certainty. If there was only one company on the market, the uncertainty of customer retention for the monopolist would be minimal because customers would not have a choice. The opposite situation is when there are a lot of companies and then customers can choose and uncertainty of the choice increases.
Because of the unevenly defined upper threshold, the results can be incomparable between market structures that contain a different number of companies. For comparability of the index between branches and different moments of time, its relative value is used. The equation of the relative entropy index is as follows (Lipczynski et al., 2009): The value of the relative entropy index is in the interval between 0 and 1, where 0 corresponds to the situation when there is a monopoly, while 1 corresponds to a perfectly competitive market.

The research
The research on the limitation of the insurance markets of Slovenia, Croatia, and Serbia contains a part concerning the determination of the relevant market's limitations, a part which is related to the evaluation of the level of concentration and inequality of supply on the market thus defined, as well as the analysis of the correlation in the movement of these indicators for the three countries.

Relevant market
The relevant market implies a market with identical or similar competition conditions. It has two dimensions: product and geographic (Motta, 2008). It follows that in defining the boundaries of the relevant market it is necessary to define relevant product market and relevant geographic market. The relevant product market is defined as a set of products and services which are regarded as interchangeable by the consumer by reason of the products' intended use, characteristics, and their prices. On the other hand, the relevant geographic market comprises the area in which the conditions of competition are sufficiently homogeneous and are appreciably different from neighbouring areas (European Commission, 1997). Insurance market, which consists of all forms of insurance on the entire area of the analysed countries (Serbia, Croatia, and Slovenia), can be taken as a relevant market in this research for assessing the market power of corporations and limitations of supply. In defining the relevant product market, we started from the assumption that it is about a unique product which has no adequate substitute. Since we analysed the general assessment of the level of concentration and inequality, the division of insurance by types in this market was not conducted. As for the size of the relevant geographic market, the whole area of the countries was taken for assessing, as required by the very nature of business and the available data (Kostić, 2009). Furthermore, business conditions in one country are unique for all the participants, so they can make territorial completeness. The annual reports and regulatory bodies confirm that this market definition is good for the research being undertaken, where, among other, the approach we implemented is used as an item for the assessment of competitive conditions.

Analysis of the research results
Based on collected data, the research was conducted in the frame of the relevant market's defined borders. Analysis of the research results, using the appropriate indicators of concentration and inequality and based on them statistical estimates, requires the previous view of the number of insurance companies operating in the analysed markets in the research period. Some authors consider this component of the market to be significant in assessing the competitive conditions of market share distribution (White, 1982). The article assigns equal importance to both the elements, but we believe that the number of companies will largely determine competition conditions in the analysed markets. Table 2 shows changes in the number of insurance companies by countries for the entire research period.
As can be seen from Table 2 the largest number of active insurance companies is in Croatia, then in Serbia, and in the end in Slovenia. This arrangement of active insurance companies will affect the obtained indicator values, especially those related to the concentration.
Analysis of the research results will be carried out separately for concentration indicators and inequality indicators. Tables 3 and 4 and Figure 2 provide information on the movement of the indicators for the period between 2004 and 2011.
Based on the data presented in Table 3 we may give a rough estimate that in the period from 2004 to 2011 there was a decline in the value of concentration indicators, suggesting the concentration level reduction in all the analysed markets. Table 4 and Figure 2 provide information on the inequality in the distribution of market shares between the companies in the analysed markets, in the entire period of the research.
The analysis of inequality indicators leads to the following conclusion: although it can be said that there is a tendency to reduce inequality, it is not as clearly expressed as a trend of concentration reduction.    To confirm or challenge these findings it is necessary to perform further statistical analysis of the movement of the indicators of concentration and inequality, which will test the research hypotheses. Figure 3 and Table 5 present the analysis of the movement of concentration indicator's value in individual markets in the analysed period.
Based on Table 5 and Figure 3 it can be concluded that there is a statistically significant decrease of the concentration indicator's value, which points to the fact that in every market comes to the reduction of supply concentration. This confirms Hypothesis 1. In the case of inequality indicator, we also performed statistical testing and tried to prove Hypothesis 2 (Figure 4 and Table 6).
As can be seen from Figure 4 and Table 6, we cannot unambiguously confirm Hypothesis 2, but we can make its confirmation to a limited extent. First, there was a decrease in the value of the Gini coefficient in all the markets, but the decrease was not statistically  significant. This is illustrated by the Lorenz curve (Figure 2), which indicates a general tendency to reduce the inequality, which is not emphasised. On the other hand, the relative entropy index value increases in all markets, reflecting the growing uncertainty, and thus the competition among companies. However, this competition increase in the Serbian market is statistically slightly significant, whereas in Croatia and Slovenia is very significant (of course, not at the level of concentration indicator). We can conclude that Hypothesis 2 can be unambiguously confirmed only for the relative entropy index in the markets of Croatia and Slovenia.
Considering the above, we conclude that competitive conditions are better at the end of the research period than at the start.
Further research analyses the correlation in the movement of various indicators of concentration and inequality between the analysed markets. Correlation in the indicators' value movement between the analysed markets and the value of its statistical significance are given in Table 7.
As can be seen in Table 7, the movement of the analysed indicators of concentration and inequality between the insurance markets of Serbia, Croatia and Slovenia, shows a high level of correlation that is statistically significant. This suggests that identical movements of the level of concentration and inequality are achieved in all analysed markets, indicating the similarity of the business context in all the countries. This has confirmed Hypothesis 3.

Conclusion and limitations of the research
Based on the above, we can derive some conclusions. First, generally in all the analysed markets, there is a trend to reduce the concentration and inequality in the distribution of market share. Concentration reduction in all the markets is statistically significant, while inequality reduction is not. On this basis, we can conclude that competition strengthens in the observed markets which should provide greater choice for consumers and lower prices for provided services. The country with the lowest level of supply concentration in the insurance sector is Croatia, followed by Serbia, and then Slovenia. The probable reason for this is the fact that the largest number of active insurance companies is in the Croatian market. As for the inequality in the distribution of market share, Slovenia stands out with most properly distributed shares.
When we speak of consumers' certainty of choice, as yet another indicator of the market structure limitation, we can say that there is less certainty in Croatia and Slovenia than in Serbia. This indicates greater possibility of choices by consumers in the markets of Croatia and Slovenia than in Serbia.
The general conclusion to be drawn is that, despite the relatively uneven distribution of market share, the Croatian insurance market is more competitive than the other two.
As for the movement of the indicator of concentration and inequality, it can be said that the process is being achieved at a similar pace in all three countries, which indicates that these markets belong to the same business environment.
Presented research and conclusions contain certain limitations, primarily for the use of concentration indicators. Concentration indicators are a useful tool in assessing the level of market limitation: they give an exact evaluation of the level of concentration and equality of market share distribution and a relatively clear picture of companies' potentials to use market power. However, they are not immune to some of the problems and limitations.
The first problem is related to the definition of the relevant market's boundaries, i.e., market volume, in spatial and production sense. In the case of the insurance market the problem is related to the different types of insurance and their levels of substitutability. From this it follows that the entire insurance market can be seen as the relevant product market, but we can distinguish the life insurance and non-life insurance market. Also, as a separate market, it is possible to single out motor vehicle insurance or the health insurance market, and the like. In this article, we opted for a complete insurance market. The framework for the analysis was identical for all the countries so that the data is comparable.
The second problem is related to the inability of the indicators to acknowledge certain qualitative characteristics of the market, such as market structure stability, the level of product differentiation, the height of entry barriers, operating costs, etc. Also, these indices do not include industrial tradition, nor do they include features and objectives of managers who run the companies. The inclusion of these elements would make the assessment of market limitation more detailed and therefore more complete.
The third problem is related to the size of economy and market: the value of the indicator will not have the same meaning for 'small' and 'large' economy (Mitton, 2008). In a small economy it is normal that due to small space and low purchasing power there is a higher level of tolerance to a high value of concentration indicator. This problem has no great significance, given that in this case the countries have similar number of insurance beneficiaries.
Regardless of all the limitations, the research provides a clear image of competition conditions in the insurance market of the three countries, which is at the same time the image of competition conditions in the insurance market of the region they belong to.
The research should improve competition policy, through greater application of economic analysis. Oligopolisation in most markets, also in the insurance market, imposes the requirement to monitor the degree of limitation of competition and formulate measures to ensure competitive conditions through economic analysis. Competition policy, which contains high level of economic analysis, would be able to better encourage companies' competitive and prevent monopolistic practice through precise quantification of the results of uncompetitive behaviour, as well as measures taken by anti-monopoly authorities. Table A1. Data on slovenian insurance companies' total premium (in million EUR) and market share (ms) by year.  source: slovenian insurance supervision agency (2004, 2005, 2006, 2007, 2008, 2009, 2010, and 2011) annual Reports.    source: croatian Financial services supervisory agency (2004, 2005, 2006, 2007, 2008, 2009, 2010 and 2011) annual Reports.