Economic Competitiveness of Selected European Countries

MACIEJ JESIONOWSKI"

ABSTRACT

In many publications, the notion of economic competitiveness has different meanings. For example, it could mean competitiveness by county or by crea "tmg more goods and services than competitors in the worm market [The World Competitiveness Report, 1994]. In this paper, a proposal is given for measuring competitiveness and preparing a ranking list for selected European countries (the European Union members and Poland) based on data obtained from The World Economic Competitiveness Report [1994]. To fulfill such an objective, special producers are used. Moreover, results obtained from similarity, distance, and development measures calculated for every country serve as the basis for dividing the analyzed countries into three homogeneous groups. (JEL C10)

INTRODUCTION

In many publications, the notion of economic competitiveness is used with different meanings. In The World Competitiveness Report [1994], it is defined as a country's ability to create more goods and services than other competitors in the world market. This is one of many methods of defining the economic competitiveness. The difficulty of measuring economic competitiveness plays a considerable role in different economic analyses. A successful measure can be used to rank the countries being analyzed.

Socioeconomic politics connected with integration into the European Union (EU) do not involve an individual subject but a set of subjects and their diagnostic features. Such an analysis requires the use of special procedures and measures borrowed from taxonomy methods.

In this paper, a proposal measuring the competitiveness of selected countries and their ranking based on data obtained from The Worm Economic Con~etitiveness Report [1994] is presented. The basic concepts used in taxonomy are an object unit (in this case, a country's economy) and diagnostic features (important characteristics of an economy with regard to evolution criteria). These features can have different values for different countries. Let [X~,j] be a matrix, where j is the characteristic and i is the country. To obtain relative values used for comparison, absolute values should be standardized for the individual objects.

In this paper, I try to rank the Central European countries which are candidates for the ELI. The basis for such an investigation was The Worm Competitiveness Report [1994], in which 381 characteristics of 41 world countries were considered. Before beginning the analysis, I had

"University of Lodz--Poland.

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296 INTERNATIONAL ADVANCES IN ECONOMIC RESEARCH

to fred those characteristics which were highly correlated. As a result of such a reduction, 80 characteristics were obtained. Fifteen EU countries were considered, along with three from Central Europe: the Czech Republic, Hungary, and Poland. Competitiveness factors were divided into eight groups: domestic economy, internationalization, government, finance, infrastructure, management, science and technology, and people.

TAXONOMY MEASURES FOR ECONOMIC COMPETITIVENESS

Two different measures will be constructed to make a comparison of the economic competitiveness of the selected European countries. Similarity (mi,o) is used to measure the structural fitness of two economies, i and o, The measure of distance (di,o) between two economies, i and o, determines differences between values of features characterizing two analyzed objects.

To illustrate these measures, the desirable economy will be defined as:

Wo, t = m a x Co, t , (1)

for all considered standardized data in such a way that all characteristics are stimulants. The similarity measures of two countries can be calculated [Michalski, 1995, p. 229] as:

o

C i W 0

: Ic,I * Iw01 ' ( 2 )

where c i and w 0 are the scalar product of vectors ci and w 0, and I cil and I w01 are the lengths of these vectors. The distance between two economies is determined traditionally according to (3) [Michalski, 1995, p. 230]:

1

o -- [ E ( c , j - w j ) 2 ] , ( 3 )

where c i j is the value of thej th feature of the ith object and wj is the value of thej th feature of the so-called desirable object.

To construct a ranking list of the economic competitiveness of the 17 analyzed countries for each object, the measure of similarity between a given country and a desirable object was calculated. The higher the level of this measure, the higher the position of a country in the ranking of competitiveness.

Using the distance measure di. o, one can also find the position of a given country. In this case, the lower the value of the distance measure, the higher the position of an analyzed country in the ranking list. The last measure, called the development indicator, does not need any assumptions about the desirable object. A measure was constructed based on the sum of all standardized values for each country:

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m

W, - ~ Zij , (4) m j=l

where m is the number of characteristics j of object i. This measure does not allow for distinguishing between the influence of characteristics describing structure and the influence of features determining the level of the economy.

RANKING BASED ON PROPOSED MEASURES

Using the 80 characteristics, three taxonomy methods were constructed: similarity #i.o, distance di,o, and a development indicator w~. The results of estimations for 17 countries are presented in Table 1.

TABLE 1 Economic Competitiveness Evaluation Measures

Values of Proposed Measures Country ]£i,o di wi

Germany 0.354832 33.99152 103.7928 Denmark 0.301743 40.85010 124.7243 Netherlands 0.289770 40.90043 87.60949 Sweden 0.273980 41.20129 100.2745 France 0.251665 41.36737 47.13134 Austria 0.239790 41.53585 82.91 ~ 4 A United Kingdom 0.139102 42.73159 31.21684 Belgium/Luxemburg 0.084425 43.21914 38.52295 Ireland 0.082264 43.48050 49.85209 Finland 0.051899 44.19659 45.77047 Spain -0.32875 47.42852 -66.2579 Italy -0.36405 49.38074 - 107.816 Czech Republic -0.37957 52.53353 -136.040 Portugal -0.38768 48.26595 -70.6449 Greece -0.42370 51.34388 - 128.881 Hungary -0.47777 53.79714 - 165.573 Poland -0.48573 55.95529 -205.275

I obtained values for each of the measures but in comparing the positions of countries by the values ui and di only, it is evident that there are no important differences among the countries. The variability of absolute values of wi is greater. In this case, I distinguish two

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groups of countries, one with positive values of wi and the other with negative values of w~. The last group contains seven countries: Spain, Portugal, Italy, Greece, the Czech Republic, Hungary, and Poland.

Comparing results obtained from the similarity and distance measures, there is a very small difference in the positions between those two values. Some interesting observations can be taken from the absolute values of the similarity measure i~i, o. Seven countries have very high ranges from 0.24-0.35. Those countries are the most developed members of the EU.

The next four countries are characterized by a middle value of the proposed measure, which ranges from 0.24-0.35. The last group contains seven countries, consisting of four members of the EU and three Central European countries. They are characterized by a negative value of the similarity measure izi. o compared to the so-called desirable object. This group has exactly the same results as those obtained from the negative value of w~.

Having only two ranking lists (because of the high correlation between/Zi,o and di,o) based on the proposed taxonomy methods, three groups of countries are distinguished by economic competitiveness (Table 2). The first group is characterized by a positive level of development indicators and high similarity of their economies to the desirable economy. The following countries belong to this group: Germany, Denmark, Holland, Sweden, France, and Austria. The second group is characterized by a positive value ofwi and middle value of #;.o: the United Kingdom, Belgium/Luxemburg, Ireland, and Finland. The third group contains countries which are characterized by a negative level of w~ and low level of/z~,o: Italy, Spain, Portugal, Greece, the Czech Republic, Hungary, and Poland.

TABLE 2 Groups of Countries by Similarity Measure ~i,o and Development Indicator di,o

Development Measure w~ Similarity Measure/zi. o

w i > 0 w i < 0

0.24 < /zi, o < 0.355

0.05 < #i,o • 0.14

-0.486 < #i,o < -0.328

Germany, Denmark, Holland, Sweden, France, Austria

United Kingdom, Belgium/Luxemburg, Ireland, Finland

Italy, Spain, Poland, Portugal, Greece, Hungary, Czech Republic

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CONCLUSION

Several interesting remarks emerge from the analysis. To analyze the competitiveness of countries, different economic and social characteristics should be used. Many of these characteristics are highly correlated and were reduced from the analysis. On the basis of 80 characteristics describing eight main sectors of economy, I calculated the following taxonomy measures: similarity, distance, and development indicators. Because of the high correlation between similarity and distance measures, only similarity and development indicators were considered. Those two parameters can be used for ranking EU countries and Central European countries.

Using positive and negative values of the development indicator and three levels of similarity measure (high, middle, and low), three groups of countries were distinguished. The most important remark from such an analysis is that Central European countries joined the group to which Italy, Spain, Portugal, and Greece also belong.

REFERENCES

Michalski, T. "Eastern Economies Towards European Union: Statistical Measures of Perspective Evaluation," International Advances in Economic Research, 1, 3, August 1995, pp. 227-31.

"The World Competitiveness Report," Worm Economic Forum, Lausanne, 1994.