Intra-European economic exchanges modelling in the EU-27, Under globalization.

Dogaru, Vasile

Abstract: Under the present circumstances, where enlargement of the Single Market is being part of globalizing process, there is increased necessity to measure economic competitiveness in terms of comparative advantage and total factor productivity. Competitiveness requires to be analyzed as nonlinear relation between the comparative advantage and the productivity. We centred our research upon measurement of total comparative advantage, underpinned by the convergence criterion at the level of NUTS I regions and observed in its relation to the gross domestic product (GDP). The regressive study between the total comparative advantage and the real income in one country reveals a reversed relation.

Key words: competitiveness, regional convergence, Roegenian modelling, comparative advantage, total factor productivity.

1. INTRODUCTION

The increasing development of intra-European trade as ruled by globalization results in further necessity for insight and more accurate measurement of economic processes in Single Market. The survey of Single Market in terms of economic competitiveness involves measurement and modelling of its trading processes. The competitiveness is presently measured by composite indexes (http://www.weforum.org/en/initiatives /gcp/index.htm, http://www.compete.org/et/), structural analyses or substitution of the labour productivity by the total factor productivity (O'Mahony, 2003; www.euklems.net). One has to explain the European competitiveness in the context of carrying out regional convergence and globalizing exchange phenomena.

Economic competitiveness is a nonlinear relation between comparative advantage (CA) and total factor productivity (Dogaru, 2006). Although entities might achieve CA for periods of limited duration, the lacking increased productivity of total factor could not further maintain the CA level. In competitive monetary economies, the maximizing CA as monetarily (profit) shaped is the main incentive to commodity trading business. In empirical economy, although the increase of the total factor productivity is generally included in the CA size, price doesn't necessarily change once with productivity.

Certain authors suggest a reversed linear relation between prices, which includes profit, and productivity. The changing productivity in competitive economy is usually followed by maintenance of prices. Due to the concern for maintaining comparative advantage as high as possible, the economic entity will change further the price as a result of competitive pressure. In a highly competitive economy, productivity increase will lead to decreasing prices and vice versa.

Price maintenance makes the calculated productivity (not the actual one) be constant, while other elements are kept unchanged. The influence of price over productivity calculation is eliminated (Griliches, Productivity: measurement problem, in Eatwell, 1987). Still, the ensuing price change, after a while since productivity has changed, makes the two measures to be not in a reversed well-timed relation. This peculiar relation requires further study. This is the reason why the comparative advantage measurement in terms of prices is usually inclined and not correlative to the same measurement in terms of productivity. It is strictly necessary, also, to study the competitiveness thoroughly the productivity.

The task of competitiveness growth in the EU's economy is a strategic priority. Along this article, we observe//watch the main element of competitiveness, CA, by means of the relation between the total CA and the increase of domestic incomes. This relation modelling in a weak way, mathematically and literally, should be underpinned by an insight into economic processes as a whole (Georgescu-Roegen, 1971).

2. RESEARCH COURSE

Our research is being focused upon the study of the relationship between each country's real income as GDP per capita, expressed by the purchasing power parity (PPP), and the corresponding level of the total CA. We used the PPP and the regressive analysis as research tools. Because of the mobility of production factors, we suppose prices of various goods categories influence each other, owing to the hysteretic effect (Georgescu-Roegen, 1971; Dogaru, 2003). As well, a further increase in lower incomes from one EU's (New) Member State is supposed to be accompanied by the same level of CA which is now found in higher income countries. It is thus supposed that each country will follow a future regressive deduced line of the CA, as incomes grow.

The total CA was measured by appropriate use of the basic formula of Manoilescu generalized scheme (MGS) (Dogaru, 2005) for a hypothetical exchange of non-food and food products. Should another point of reference be supposed, i.e. clothes instead of foodstuffs to be exchanged against all the other goods, including food products too, calculation would lead to the same results at this level of generality. The main goal of analysis is to identify o possible relation between the income size (GDP) and total CA.

The use of the total relative CA formula from the MGS--sometimes measured as an inequality in the specialized literature (Deardorff, 2005), in order to identify a partner's possibility to achieve a real exchange--is similar to the way that the enterprising individual will calculate it (CA) by discrete figures. But the real exchange is only possible if the total CA is shared by participants under mutual agreement. Other algorithms of the scheme will enable measuring a real exchange, with trade costs and use of currency. Both MGS algorithms can be reduced to the barter-exchange algorithm (their possible common reference point) which measures the total and partial CA.

Under such close circumstances to empirical reality and taking into account investigating tools available in Economics, the modelling of CA from exchanges can also ground the exchange of Best Available Techniques under observation of the Integrated Pollution and Prevention Control requirements (EC 96/61 Regulation).

Source: OECD, 2002. Note: own calculations; the sizes in brackets are the t Student values of the coefficients. Critical values (1st regression): [F.sub.0.1;1;25] test = 2.9; t [Student.sub.0,1;25] =1.71. Critical values (2nd regression): [F.sub.0.1;1;2] test =8.53; t [Student.sub.0,1;2]=2.92. ESE-Error standard estimation.

In Economics, there has been demonstrated the qualitative leap (Georgescu-Roegen, 1971), which grounds this modelling and indirectly supports the explanation of infant industries' phenomenon (Manoilescu argument).

The relation between total comparative advantage, measured by the relative prices ratio, and the GDP per capita, is measured through the regression equation (1).

[GDP.sub.c] = [[beta].sub.1] [R.sub.pr] * + [[beta].sub.0] (1)

where: [R.sub.pr] is the relative price ratio (price parity) between the two groups of goods (food and non-food products), GDPc is the GDP per capita, [B.sub.1] and [B.sub.0] are independent variable and constant factor coefficients.

The connection between the two variables is measured at a satisfactory level with the R2 coefficient (0.63). The increase in international exchange volume at a global level, during 1950-1999, by 20.4 times, as compared to the production's volume, occurred more than 6.5 times (World Trade Organization, 2001), thus pointing out a growing interest in the exchange area. Thus, ensuing necessity occurs for measurement of CA from intra-European as well as global exchanges. It is only by measuring total factor productivity, alongside of comparative advantage, that one can check the observance of minimumeffort principle. It is further possible that, as a matter of the increasing relative lack of resources, the weight of the total factor productivity, used in competitiveness measurement, may increase as compared to the CA.

If one splits the 27 Member States into groups according to four intervals of the income, and then calculates the coefficients of the regression equation (1) alongside of other data, a surprising R2-coefficient increase of 40% is visible. The R2 coefficient increases at the 0.87 level, and the F test is passed (table 1, 3rd column). The results of such splitting into several groups point out an obvious relationship: the GDP increase brings about a decrease in total comparative advantage.

The data interpretation is limited herein, because exchanges weight and GDP weight are not equally. The tendency of total CA to decrease as the growth of incomes increases is also argued by the previous results for a number of countries, as grouped at world level (Dogaru, 2003).

3. CONCLUSION

The analyzed data enable us to assert that the New Member States joining the EU makes possible for total comparative advantages to increase in the Single Market. The deduced relation explains the interest of the states with higher incomes in enlarging the Single Market, through sharing an ever higher total CA among participants in the intra-European exchanges. We have also checked the validity of MGS, which underpin the measurement of the CA from the goods exchanges (technological transfer included), so that the phenomenon of the "infant industries" should be explained in terms of necessity. The qualitative leap from the economic processes within the Single Market is thus accepted as well. As a matter of fact, along the dynamic analyse of certain developed countries' total advantages by means of unit value ratios (Ark, 1995)--similar to PPP -, there appears an oscillation of time (Dogaru, 2003), which justifies these leaps.

The deduced relation supports the interest in the globalization of exchanges. Within economic blocks prove the necessity to study this qualitative phenomenon by means of measurement, as it is so vast and sometimes stated in excessively general terms that make difficult its measurement and modelling. The intra-European exchanges need to be studied starting from certain findings of the present paper and stating additional prerequisites, in respect of the analytical economicity principle. Completion of data bases which are being carried out according to EU KLEMS 2003 (www.euklems.net), so as to measure the total advantage in relation to the partial advantages of the two partners, will be another necessary step in further reorganization of data bases on criteria of competitiveness. We intend to carry on our study, by placing it at a regional level (NUTS II), for the relation (1) and the nonlinear relation existing between comparative advantage and total factor productivity.

4. REFERENCES

Ark, van B. (1995). Manufacturing prices productivity and labour costs in five economies, Monthly Labour Review, Vol. 118, no. 7, July 1995, pp. 56-72

Deardorff, A. (2005). How Robust is Comparative Advantage? Available from: http://www.spp.umich.edu/rsie/working papers/wp.html, discussion paper no. 537, accessed: 2007-02-24

Dogaru, V. (2003). The Population Income and the Prices of Agri-Food Products. Comparative analysis of countries trend between 1950-2002, Expert Publishing House, ISBN 973-8177-68-5, Bucharest

Dogaru, V. (2005). The Comparative Advantage in Generalized Manoilescu Scheme, Romanian Journal for Economic Forecasting, no. 3, ISSN 1222-5436, pp. 91-113, Bucharest

Dogaru, V. (2006). Manoilescu generalized scheme regarding the international goods exchange--a general presentation, Probleme economice (Economic Issues), nr. 226-227, National Institute for Economic Research, Romanian Academy, ISBN 973-7885-47-3, 978-973-7885-47-0, Bucharest

Eatwell, J. and others, editors. (1987). The New Palgrave. A Dictionary of Economics, tome I-IV, The Macmillan Press Limited, ISBN 0-333-372352, London

Georgescu-Roegen, N (1971). The Entropy Law and the Economic Process, Harvard University Press, ISBN 674-25780-4, Cambridge, Massachusetts

O'Mahony, M. & van Ark, B, editors. (2003). EU Productivity and Competitiveness: An Industry Perspective. Can Europe Resume the Catching-up Process? European Communities, ISBN 92-894-6303-1, Luxembourg

Organisation for Economic Co-operation and Development (OECD) (2002). Purchasing Power Parity and Real Expenditures, OECD, Paris

World Trade Organisation (WTO) (2001). International Trade Statistics, WTO, ISBN 92-870-1220-2, Geneva

Table 1. The relative prices' regression depending on the GDP, 27
countries, 1999 (1 regression equation).

 1st regression 2nd regression
 (27 countries) (4 groups)

[[beta].sub.1] -12971.31 -15899.56
 (-6.52) (-3.66)
[[beta].sub.0] 38384.93 43090.10
 (11.76) (6.16)
R2 0.63 0.87
F 42.56 13.39
ESE 5409.14 4045.32