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Poland in Europe - the economic periphery, or a leader?

dr Ewa Lechman

eda@zie.pg.gda.pl

In 1990 the Polish economy had a unique and unrepeatable opportunity to "get back on its feet" and come into being as a strong and dynamic economy in Europe. 1990 was also the moment when a large pool of economists began to keep a close eye on the path of development of our economy. After many, often very painful, reforms and after 20 years of so-called economic transformation, here we are! Indeed... Who are we?

Can and should the Polish economy be seen as a leader among the former Eastern Bloc countries? How are we doing compared to other countries, also undergoing transformation? Is the Polish economy catching up with those countries in Europe, which now enjoy the highest level of socio-economic development? Or maybe the opposite is true and Poland should be treated more as a peripheral country in economic terms? I will try to answer this very question by examining the results of my "home-made" statistical analysis.


Let's start by defining the term "economic peripherality". The expression "periphery" has traditionally been associated with a certain distance in a geographical (physical) sense. Peripheral areas are those (in classical terms), which are characterized by a considerable distance from so-called centres - highly urbanized economically strong areas with high population density. So-called "areas of raw materials" were also often regarded as peripheries. However, since the early 1980's, we have observed a trend away from the treatment of "peripherality" only in a narrow geographical context. The term "peripherality" is beginning to be associated also with a certain "distance" in the economic and social sense (see Milne (1997) and Krugman (1991 and 1995)). This means that now issues of peripherality tend to be analyzed in a multi-faceted manner. Consequently, a change of the classification criteria is inevitable. It is no longer one determinant - as in the case of geographical distance - which is crucial. This time, many elements must be taken into account- also those qualitative, such as: standard of living, solarization, life expectancy, access to new technologies.

However, given the rapid development of new ICTs (Information and Communication Technologies) during the past 15 - 20 years, we should treat the peripherality of regions rather as an economic weakness - moving away from the traditional, purely geographical approach. New ICTs are technologies which have become so common that they can be regarded as essential tools that help to achieve goals as a part of economic policy. The use of ICTs radically changes the way businesses are run and  more importantly,  modifies the path of economic growth and development. Application of new technologies liberates from the so-called "tyranny of distance" - a geographical situation no longer acts as a brake on economic development. The distance between market players is no longer of key significance for doing business. We can therefore conclude that currently the issues of peripherality should be considered not only in terms of geographical distance - if at all, but rather regarded as a problem of the economic distance and differences in socio-economic development. If we want to depart from the traditional perception of peripherality we have to stop using the traditional classification criteria. Instead, we should use those allowing us to assess whether a given region (country) ought to be regarded as peripheral in terms of level of socio-economic development.


For the purposes of our analysis I have adapted my own definition of the peripheral area. As peripheral in economic terms we will (now) treat every region, which is characterized by a relative, multifaceted weakness of the economy. The phrase "relative" means that the concept of economic peripherality should be analyzed only in relative and not absolute terms. Such a viewpoint significantly modifies the perception of peripherality. It should also be emphasized that a hypothetical introduction of the concept of economic peripherality in absolute terms has no practical and theoretical reasons. The weakness or strength of the economy can be assessed only in relative terms. Such a theoretical approach implies a methodology for analysis and evaluation of peripherality. In order to state whether a given region ought to be treated as a peripheral, we should adapt a relatively wide range of indicators that will assess the relative weakness (or strength) of a particular economy. It is also necessary to adopt an adequate methodology that will let us measure the "degree of backwardness" of a particular economy in relation to other countries included in the analysis. Peripherality is a multifaceted problem and it should be discussed in this context . The classical approach (a purely geographic one) seems to have no reason in terms of multidimensional analysis. Therefore, it is legitimate to apply the multi-threading approach in the analysis of peripheral regions.


And now for some numbers! To estimate the size of the country's backwardness in relation to another, I have applied a taxonomical method - the estimation of so-called metric distances (in practice non-negative numbers) which may be an approximant of "distance" of a given object (here: country) in relation to another. Leaving aside the methodological issue, we assume that the higher the metric (number), the more distant a country is from another, with which it is compared. We can therefore consider metric distance values as an indication of the size of the so-called development gap between the two economies.


My analysis involves 27 European economies in the 2000-2009 period. The data used for analysis originate from the Eurostat database. In individual cases, data can come from years other than 2000 or 2009 due to lack of full data availability. For the analysis I took account of 20 variables, which I considered approximants of the level of social, economic and technological development. Those were: the value of final production per capita according to purchasing-power parity, the share of surplus value generated in the financial sector in the total surplus value of a given year, the rate of total employment, labor productivity 1,

rate of investment, expenditure on R&D (as a percentage of GDP), public expenditure on education (as a percentage of GDP), average life expectancy at the age of 65, the number of patents in Europe per 1 million inhabitants,

percentage of people aged between 16 and 74 who have never used the Internet, the number of science and technology graduates (aged 20-29) per 1000 people,

 the number of patents per 1 million people which are submitted to the U.S. Patent Office2, the percentage of population participating in Life Long Learning courses, the value of KEI (Knowledge Economy Index), 

the percentage of workforce employed in high-tech sector, the share of high technology products in total value of exports, the number of patents submitted to the European Patent Office3,

value of ICT Development Index (divided into three sub-indices)4.


The estimations result in a matrix of metric distances which indicate the relative backwardness of a given object (the economy) in relation to all others. I used the method of estimating the squared Euclidean distance. I inserted the results of calculations for 2000 and 2009 into two separate matrices. Based on the results in tables, we can infer the relative level of socio-economic development of the object (the country) in relation to all others. From the data in Table 1, we can draw conclusions about Polish position in relation to other European countries in 2000 and 2009. We can therefore find an answer to the question whether the position of Poland in relation to other European countries has improved or deteriorated. Higher metric values indicate a relatively weaker position of Poland in comparison with a given country. In 2000, the Polish economy recorded relatively worst performance in relation to Sweden (metric 107), Finland (metric 94), Luxembourg (metric 81) and Denmark (metric 76). In 2000, we were relatively close to Latvia, Hungary and Slovakia. The data in Table 1 also suggest that in 2009 Polish economy was relatively weakest in comparison with Luxembourg (metric 123), Sweden (metric 86), Finland (metric 72) and Denmark (metric 75).


Table 1. Development gap between Poland and other European countries. 2000 and 2009

Country

Metric - 2000

Metric - 2009

Change of the metric in the 2000-2009 period.

Source: Own calculations

Table 2. Poland compared to other countries under economic transformation. Quick matrix of metric distances. 2000.

Source: own elaboration


From the data presented in the Table 2 we can draw conclusions about the relative position of Poland in comparison with the most developed countries in Europe against the economies of the countries under the economic transformation (9 countries). In relation to Sweden, Bulgaria has achieved the worst result (137), followed by Slovakia (111), Poland (107) and Latvia (107). Countries with better results: Czech Republic, Estonia, Lithuania, Hungary, Slovenia. In relation to Finland, and ahead of us: The Czech Republic, Estonia, Latvia, Lithuania, Hungary and Slovenia; In comparison with Luxembourg: Czech Republic, Estonia, Hungary, Slovakia and Slovenia, and in relation to Denmark : Czech Republic, Estonia, Latvia, Lithuania, Hungary, Slovenia. In 2000, compared to nine countries under the economic transformation, Poland and Bulgaria were the weakest in comparison to most developed countries in Europe. Therefore, there are grounds for classifying Poland and Bulgaria  as economically peripheral regions. It is worth adding that the differences in metric values between Poland and Estonia or Slovenia are significant, which means that even in comparison with the countries in transition, the economy shows the relative weakness.


Table 3. Poland compared to other countries under economic transformation. Quick matrix of metric distances. 2009.

Source: own elaboration.


in Table 3 I have compared the results of all countries in transition compared to the most developed economies in Europe. In comparison with Denmark, Poland has achieved poorer results than the Czech Republic, Estonia, Lithuania, Hungary, Slovenia. In relation to Luxembourg, it achieved worse results than the Czech Republic, Estonia, Latvia, Hungary, Slovenia and Slovakia. In relation to Finland: worse than the Czech Republic, Estonia , Lithuania, Hungary, Slovenia.  Compared to Sweden Poland achieved poorer results than the Czech Republic, Estonia, Lithuania, Hungary, Slovenia. In each case, only Bulgaria received worse results (higher metric values), which indicates that in comparison with the economies of the most developed countries in Europe Bulgaria lags behind even more than Poland. This means that in economic terms Poland and Bulgaria are the relatively weakest countries  in Europe. What is also important, in the 2000-2009 period the relative position of Poland has not improved.


In Table 4 I have gathered the comparative data of changes in metric values (2000-2009 period) of all nine countries in transition in relation to each of the economies included in the analysis. Values in Table 4 signify changes in the metric of a given country in the 2000 - 2009 period. Positive values indicate an increase of the difference in the level of development of a particular country in relation to another, while negative values indicate the reduction of this difference. From the data in Table 10 we can deduce that, apparently, the differences between Luxembourg and the transforming economies have widened. The change value of Poland equals 41.9 and it is the highest among the remaining 8 countries. This means that in comparison with other countries, Poland has become most distant to Luxembourg.  It should, however, be noted that relations of Poland, as well as other countries in transition, in comparison to Sweden, Finland and the UK have improved significantly.


Table 4. Changes in the metric distances of the countries in transition compared to the rest of the Europe. Change in the 2000-2009 period.

(The) average

0,4

-1,4

-1,2

2,1

1,4

-0,2

-1

1,6

-4,1

Source: own calculations.


The data suggest a significant decrease in the value of metrics in 2000-2009, which, in turn, indicates a relative improvement of Polish position in relation to those economies. The last line shows the average changes in the metric values for a given country in relation to the remaining 26 countries. The biggest "jump" was noted for the economy of Estonia, where the average distance from other European countries decreased by 4.1. Relative positions were also improved by countries such as: The Czech Republic, Bulgaria, Slovenia and Lithuania. Four of the economies worsened their positions in relation to other countries. Those are: Poland, Hungary, Slovakia and Latvia. The only comforting fact is that the position of Poland, being among the 4 "stragglers", worsened to the least extent.


The above analysis shows that, although Poland has embarked on a path of socio-economic development, our "results in catching up with" the rest of the Europe are not encouraging. Rather, our country is moving away from the most developed economies. Probably, only large-scale activities aimed at accelerating the pace of socio-economic development could help Poland improve its economic position in relation to other European countries.


1 In relative terms, given that for all countries, labour productivity equals 100.

2 USPTO – United States Patent and Trademark Office

3 EPO – European Patent Office.

4 ICT Development Index, provides the level of implementation and application of ICTs in social and economic spheres.


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