Real Wage and GDP convergence in the European Union: · PDF fileReal Wage and GDP convergence...

Very Preliminary Version – 08 September 2008

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Real Wage and GDP convergence in the European Union: a contribution to the trade and growth debate Aristea Gkagka, [email protected] Zarotiadis, [email protected] University of Ioannina - Greece, Department of Economics

Abstract:

The effect of international trade on economic growth has been the subject of a vigorous debate. The richness of relevant literature results in having many and partly controversial arguments regarding the question of whether / how trade affects growth and vice versa. Conclusions are highly sensitive to differences in the underlying assumptions, the variables used, the sample and the statistical data, as well as the econometric techniques applied.

In the present paper, we first review the empirical studies, focusing on the relations among trade and growth. Our main concern was to reveal mutual conclusions, as well as conflicting observations. We sort out various empirical findings regarding causality and sign of trade-growth relations, considering the use of different types of data (international or interregional, cross-section, time series or panel data) and different empirical methodologies.

In the second part of the paper, we proceed by analyzing empirically the convergence of real wages and GDP growth rates among the countries of the EU. The gradual development of a European Common Market serves as a historical paradigm for the formation of a nearly perfectly internationalized environment. We find evidence for a structural worsening of both inter- as well as intra-regional inequality (captured through σ-convergence in GDP per capita and real compensation by employee) since the middle 1980s. Additionally, a first look on the data shows that this (regionally constrained) internationalization process has no-positive growth effect.

Keywords and JEL-Classification:

Globalization, Trade and Growth Relations – F43, R11

mailto:[email protected]

mailto:[email protected]


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1. Introduction

The effect of international trade on economic growth has been the subject of a vigorous discussion. There was a boom in relevant literature, especially the empirical studies, during the 1980s (Romer 1986), but the passionate debate continues till our days. Both, subjective reasons - answering the specific question relates strongly to the service of various sociopolitical interests - but also objectives ones, like differences in the underlying theoretical assumptions, the variables used, the sample and the statistical data, as well as the econometric techniques applied, generated a huge range of partly controversial empirical results and arguments.

Table A.1 in the appendix presents some of the main empirical contributions, sorted by the year of publication. It enables us to get a quick overview of the various findings regarding causality and sign (whether / how trade affects growth and vice versa), the use of different types of data (international or interregional, cross-section, time series or panel data) and different empirical methodologies. The dominant position in the relevant literature is that trade contributes significantly to the strengthening of growth rates. However, even though the majority of researchers have been using all different sets of data and applying sophisticated methodologies, empirical results do not provide us with a clear picture: There are plenty of studies, which either show no relation, or, even worst, relate trade and growth in a significantly negative way. Both, the sign and the causality of the effects from trade to growth, vary from country to country and from time to time (Khalafalla and Webb, 2001). The time specific, particular socioeconomic conditions of each region are of great importance, disputing thereby the usefulness of the empirical results (Levine and Renelt, 1992 and Chuang 2002).1 They may be valuable in discussing specific cases, but it seems quite difficult to draw conclusions of a generalized validity.

Especially when we deal with questions that produce such abundant controversies and thinking, it comes often to a point, where we should draw a line, try to get an overview and trace the path for the future debate. The present paper should be understood as an effort to contribute exactly to this exercise. So let us think once again, which was the primary motivation that gave rise to this discussion. In a time when globalisation tendencies are building up, concerns raised regarding the effects of this socio-economic phenomenon on the living conditions: Will this strengthen the ability of our economies to grow or not and will this help towards the reduction of inequalities? On the basis of these questions, authors started speculating, theoretically and empirically, on the effects of the intensity of international trade. Trade was anticipated as the main channel through which globalisation has been evolving. Empirical studies use trade-volume, net-exports or exports and imports separately to draw conclusions on the possible growth effects.2

Yet, trade alone does not depict globalisation forces. FDI-flows and migration become increasingly important. In the meantime, international political and economic developments provide us with cases, where national borders have been progressively removed, almost completely. The development of a European Common Market is such a case: it serves as a historical paradigm for the formation of a nearly perfectly internationalized environment.

In the frame of the present study, we make use of the European Union and its gradual (economic) completion. Bearing in mind the subsequent institutional steps that have been

1 Kali et al (2007) gather all different thinkable reasons for having diversified empirical results. They refer to the work of Grossman and Helpman (1991), Matsuyama (1992), Walde and Wood (2005), Rodriguez and Rodrik (2001) and Yanikkaya (2003). 2 It seems that studies, which consider exports and imports separately, fit better to the data and reveal more effectively the underlying relations.


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taken in the last 5 decades, we consider EU-15 as the outcome of a regionally evolving internationalization process. After presenting the data and the methodology we use in the next section, we proceed by looking at the convergence of both, real wages and per capita income, as well as growth rates in the EU-15 countries, from 1960 till 2005. We complete the third section of the paper by checking the tendency of growth rates and real wages in the same period (related to the respective rates and levels for the world economy), for each country-member and for the EU-15 as a whole. Based on the empirical findings we draw the respective conclusions.

2. Data and Methodology

For the needs of the present paper, we employ mainly data on real GDP per capita (level and change rate) and on real wages (real compensation per employee), for EU-15 as a whole and for each country-member also, in the period 1960-2006. We used the database of Eurostat,3 combined with the OECD database4. Especially for employees’ compensation, we took tables from AMECO database, the annual macro-economic database of the European Commission's Directorate General for Economic and Financial Affairs.5 Additionally, we considered also data on the annual real GDP growth per capita for the world economy as a whole. Therefore, we used the World Development Indicators 2007 (The World Bank – WDI dataset)6.

Our approach is quite simple, yet it serves the ultimate goal of the present study in a satisfactory way. At the end we conclude on some crucial facts and paradoxes, which lead us to subsequent, more sophisticated questions for further research. The analysis can be described as following: The first part of our analysis helps getting some indications regarding the development of cross-country inequalities. We estimate the standard deviation of real wages among the different countries of EU-15, on an annual basis. Checking the characteristics of the derived time series (1960-2006) enables us to deduce on the convergence of real wages. Similarly, we proceed with analyzing σ-convergence for real GDP per capita and finally, after we estimate annual real GDP per capita growth rate by subtracting the calculated population change rate from the published annual real GDP growth rates, we do the same for σ-convergence of change rates, again within EU-15.

In the second part, we consider annual GDP per-capita and compensation per employee, in real terms, in order to look at the development of inequalities within each country. Finally, in the last part of the following third section we search for inference regarding the ability of EU-15 to grow. We check this by analyzing the time series of real GDP per capita growth in the different countries – both, in absolute terms, but also in comparison to the growth rates of the world economy.

3. Empirical findings

In the present version, we simply provide the initial basic empirical results, along with some clarifying information regarding the applied procedure and the significance of the findings. In the subsequent section, we conclude on these fundamental observations and we

3 “European Economy - Annual Economic Report for 1997, No 63, 1997”, European Commission, Directorate General for Economic and Financial Affairs; 4 “OECD Factbook 2008: Economic, Environmental and Social Statistics”, www.oecd.org . 5 http://ec.europa.eu/economy_finance/indicators/annual_macro_economic_database/ameco_en.htm 6 http://web.worldbank.org/WBSITE/EXTERNAL/DATASTATISTICS

http://www.oecd.org/

http://ec.europa.eu/economy_finance/indicators/annual_macro_economic_database/ameco_en.htm

http://web.worldbank.org/WBSITE/EXTERNAL/DATASTATISTICS


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set the path for a more detailed, clarifying empirical analysis in the future versions of the paper.

3.1 Real wage & GDP convergence

Equalization of real factors’ remuneration among open economies is one of the main theoretical outcomes of standard trade theory. The creation of a common market should close any price divergence and eliminate the existing gaps across participating countries. The following table provides stationary and trend estimations for the annual standard deviation (expressed as % of EU-15 average) of real wages per employee and real GDP per capita, in the EU-15 countries.7

Regarding real wages, overall it seems that there is a significant negative trend, especially when we use the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test. Yet, a closer look in the following diagram gives us a clear picture: there was a convergence, but it took place only during 1960s and 70s. After the middle 1980s standard deviation of real compensation per employee shows a remarkable stagnation.

The picture for real GDP per capita is to some extent different, but it reproduces the mentioned dualism. In the first two decades of our period, there is a clear evidence for σ-convergence. Nevertheless, again starting from 1985, standard deviation (expressed as % of EU-15 average) rebounds and follows an upward trend, which is so strong that KPSS for the whole period provides a significant estimation of a slightly positive trend.8

Finally, it is worth mentioning that we do not find any trend at all, regarding growth rates of real GDP per capita among EU-15 countries: they neither converge, nor do they diverge (see figure 2). Yet, there are specific “outliners” that need to be checked more carefully (in 1975, 1981 1992 and 1993).

Table 1: Characteristics of σ-convergence of real wages per employee, real GDP per capita and real GDP per capita growth.

Estimation of trend Estimation of stationary ADF (AIC) ADF (SIC) PP KPSS σ-convergence

of ADF (AIC)

ADF (SIC) PP KPSS coefficient t-statistic coefficient t-statistic coefficient t-statistic coefficient t-statistic

real wages per employee (GDP deflator)

-1,511 -1,511 -1,570 0,223§ 0,000 1,533 0,000 1,533 0,000 1,533 -0,002 -7,48***

real wages per employee (final consum-ption deflator)

-2,599 -1,291 -1,053 0,228§ 0,000 1,077 0,000 0,156 0,000 0,156 -0,002 -13,2***

real GDP per capita -2,199 -2,199 -2,210 0,225§ 0,001 5,740*** 0,001 5,740*** 0,001 5,740*** 0,001 2,123**

real GDP per capita growth -8,208§ -8,208§ -9,560§ 0,143† 0,014 0,873 0,014 0,873 0,014 0,873 0,010 0,687

Notes: †, ‡ and § denotes rejection of the 0-hypothesis of unit roots for Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests and rejection of the 0-hypothesis of stationary for the KPSS (Kwiatkowski-Phillips-Schmidt-Shin) test at the 10%, 5% and 1% significance level, respectively. *, **and *** denotes statistical significance at 10%, 5% and 1% significance levels, respectively.

7 We estimate real wages by deflating the nominal compensation per employee in two ways: once we use GDP deflator and then final consumption deflator. Results do not differ significantly. 8 Some of the relevant literature provides us with various indications for β-convergence (Barro and Sala-i-Martin, 1991 and Kaitila, 2005).


Figure 1: σ-convergence of real GDP per capita and real compensation pre employee in EU-15

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Figure 2: σ-convergence of real GDP per capita growth rates in EU-15

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3.2 Real wage effects – by country and EU average

Previous pictures provide doubts regarding the validity of standard theoretical results, or at least, they raise questions about the political and economic character of EU-15 after the 80s. It seems that, for some reasons, interregional convergence stopped, or even changed into divergence, around 1985. In the following we check the developments of intra-regional inequalities. Again, we should bear in mind that the comparisons presented in this version

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of the paper could be improved in various ways.9 However, for the moment we could concentrate ourselves in the major structural observations.

Table 2: Characteristics of real compensation per employee by region in EU-15 (deflated with GDP deflator)

Estimation of trend Estimation of stationary ADF (AIC) ADF (SIC) PP KPSS Countries ADF (AIC)

ADF (SIC) PP KPSS coefficient

t-statistic coefficient



t-statistic

Austria -0,240 -0,544 0,008 0,202‡ -0,007 -0,234 0,001 0,079*** -0,025 -1,334 0,558 39,89***

Belgium -0,132 -0,132 -0,434 0,204‡ -0,010 -0,366 -0,010 -0,366 -0,010 -0,366 0,631 32,18***

Denmark -2,778 -2,778 -2,737 0,141† 0,095 2,629** 0,095 2,629** 0,095 2,629** 0,489 63,21***

Finland -3,392† -2,149 -2,393 0,131† 0,234 3,384*** 0,101 2,127** 0,101 2,127** 0,526 64,23***

France -1,283 -1,283 -1,324 0,215‡ 0,009 0,691 0,009 0,691 0,004 0,311 0,520 30,55***

Germany -4,861§ -4,861§ -1,695 0,131† 0,183 4,659*** 0,183 4,659*** 0,026 1,013 0,548 37,41***

Greece -2,113 -2,113 1,711 0,171‡ 0,017 1,493 0,017 1,493 0,011 0,920 0,239 12,50***

Ireland -2,917 -2,917 -2,359 0,124† 0,154 2,940*** 0,154 2,940*** 0,114 2,221** 0,558 68,94***

Italy -1,056 -1,056 -1,056 0,226§ -0,011 -1,058 -0,011 -1,058 -0,011 -1,058 0,401 16,97***

Luxembourg -1,676 -1,676 -2,022 0,125† 0,100 1,494 0,100 1,494 0,100 1,494 0,615 43,88***

Netherlands -3,024 -3,024 -1,508 0,192‡ 0,036 2,474** 0,036 2,474** 0,005 0,347 0,510 20,80***

Portugal -2,627 -2,459 -0,981 0,123† 0,052 2,354** 0,038 2,215** 0,015 0,732 0,296 33,19***

Spain 0,070 0,070 0,466 0,225§ -0,014 -1,437 -0,014 -1,437 -0,032 -3,60*** 0,374 16,69***

Sweden -2,126 -1,223 -1,546 0,120† 0,085 2,475** 0,030 1,191 0,030 1,191 0,433 25,93***

UK -2,085 -2,085 -1,717 0,107 0,088 2,175** 0,088 2,175** 0,054 1,324 0,498 60,03***

EU-15 -1,853 -1,254 -1,375 0,199‡ 0,021 1,346 0,008 0,493 0,008 0,493 0,454 30,34***


Table 3: Characteristics of real compensation per employee by region in EU-15 (deflated with final-consumption deflator)

Estimation of trend Estimation of stationary ADF (AIC) ADF (SIC) PP KPSS Countries ADF (AIC)





t-statistic

Austria -0,008 -0,483 0,018 0,207‡ -0,025 -0,686 -0,002 -0,086 -0,024 -1,303 0,567 32,30***

Belgium -1,378 0,019 -0,665 0,182‡ 0,033 1,007 -0,015 -0,470 -0,015 -0,470 0,655 32,86***

Denmark -2,179 -2,179 -2,209 0,137† 0,061 2,004* 0,061 2,004* 0,061 2,004* 0,519 45,23***

Finland -2,513 -2,513 -1,619 0,147‡ 0,092 2,406** 0,092 2,406** 0,060 1,503 0,553 49,53***

France -1,757 -1,757 -1,683 0,205‡ 0,013 0,869 0,013 0,869 0,013 0,869 0,520 29,56***

Germany -4,701§ -1,829 -1,405 0,139† 0,193 4,368*** 0,042 1,487 0,017 0,567 0,574 32,32***

Greece -2,634 -2,104 -1,715 0,169‡ 0,044 2,446** 0,026 1,666 0,018 1,123 0,283 14,91***

Ireland -3,595‡ -2,622 -2,642 0,068 0,391 3,618*** 0,182 2,678*** 0,182 2,678*** 0,557 83,87***

Italy -0,737 -0,737 -0,775 0,226§ -0,015 -1,150 -0,015 -1,150 -0,015 -1,150 0,428 17,13***

Luxembourg -2,281 -1,219 -1,545 0,169‡ 0,081 2,002* 0,031 0,881 0,031 0,881 0,637 31,00***

Netherlands -3,597 -3,597 -1,586 0,192‡ 0,031 2,720*** 0,031 2,720*** -0,001 -0,094 0,512 14,77***

Portugal -3,902‡ -3,902‡ -1,843 0,079 0,081 3,642*** 0,081 3,642*** 0,024 1,183 0,288 32,95***

Spain -0,415 -0,415 -0,136 0,221§ -0,010 -0,878 -0,010 -0,878 -0,022 -2,112** 0,397 19,01***

Sweden -2,411 -2,411 -2,056 0,117 0,050 2,250** 0,050 2,250** 0,032 1,434 0,372 16,70***

UK -2,831 -2,831 -1,595 0,087 0,248 2,887*** 0,248 2,887*** 0,052 1,117 0,550 57,64***

EU-15 -1,424 -1,424 -1,160 0,204‡ 0,011 0,838 0,011 0,838 0,001 0,043 0,497 32,30***


Table 2 and 3 gives stationary and trend estimations for the annual development of real compensation per employee, deflated once by GDP deflator and then by the one measured

9 Real compensation of employees is surely not the only way to express labor’s income and it can be improved in various ways (for instance we could/should consider also the indirect net subventions, health and social security costs, etc). Also, comparing this to the real GDP per capita, as we do in figure 4, in order to show the development of inequality within the country, is a method that has a lot of, partly improvable, weaknesses.


on the basis of final consumption. There seems to be a clear positive trend over the whole period of 1960-2006. The same can be said for the development of real GDP per capita. As expected, it seems to move clearly upwards (despite the cyclically reappearing periods of slowing down). Figure 3 gives the development of both real compensation (ω) and real GDP (y), in per capita terms, together.

Table 4: Characteristics of real GDP per capita by region Estimation of trend Estimation of stationary ADF (AIC) ADF (SIC) PP KPSS Countries ADF

(AIC) ADF (SIC) PP KPSS coefficient




t-statistic

Austria -2,647 -2,647 -2,790 0,078§ 0,122 2,661** 0,122 2,661** 0,122 2,661** 0,438 107,9***

Belgium -2,324 -2,324 -2,366 0,096§ 0,087 2,314** 0,087 2,314** 0,087 2,314** 0,392 91,2***

Denmark -3,966‡ -3,966‡ -2,485 0,061§ 0,101 3,920*** 0,101 3,920*** 0,045 1,965* 0,272 43,6***

Finland -2,864 -2,864 0,718 0,076 0,080 2,998*** 0,080 2,998*** 0,038 1,143 0,438 38,4***

France -2,642 -2,642 -2,067 0,150‡ 0,062 2,544** 0,062 2,544** 0,044 1,759* 0,370 71,3***

Germany -2,736 -2,736 -2,197 0,121† 0,104 2,749*** 0,104 2,749*** 0,081 2,221** 0,418 56,3***

Greece -3,098 -2,141 -0,515 0,135† 0,041 3,261*** 0,021 2,173** 0,010 0,971 0,208 19,3***

Ireland -1,522 -0,632 0,333 0,210‡ 0,059 2,112** 0,016 1,717* 0,017 1,439 0,562 16,0***

Italy -1,729 -1,729 -1,671 0,201‡ 0,023 0,725 0,023 0,725 0,023 0,725 0,349 74,6***

Luxembourg -0,239 0,199 0,012 0,225§ 0,042 1,197 0,036 1,088 0,036 1,088 0,948 22,0***

Netherlands -1,881 -1,881 -1,440 0,135† 0,037 1,943* 0,037 1,943* 0,024 1,102 0,382 45,4***

Portugal -1,949 3,502† 2,360 0,085 0,042 1,933** 0,053 3,423*** 0,031 1,709* 0,222 50,1***

Spain -2,176 -2,176 -1,602 0,125† 0,023 2,248** 0,023 2,248** 0,012 0,862 0,264 40,9***

Sweden -0,787 -1,724 -1,133 0,228§ 0,069 1,584 0,079 2,080** 0,079 2,080** 0,454 26,4**

UK -3,419† -3,419† -2,691 0,059§ 0,001 3,407*** 0,001 3,407*** 0,001 2,468** 0,002 30,8***

EU-15 -3,112 -3,112 -2,142 0,084§ 0,096 3,109*** 0,096 3,109*** 0,068 2,137** 0,351 92,5***


Figure 3: Real GDP per capita and real compensation per employee in EU-15 (in 1000 € at 2000 prices)

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Yet, what we should focus in are the patterns of discrimination, within each country and also in EU-15 as a whole. If we imagine that labor’s compensation is, on average, lower than the income of other classes of the western society, the ratio of real compensation per

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employee over the real GDP per capita (ω/y) is a thinkable way to express the degree of inequality.10

The following figure presents the development of this ratio over the whole period (1960-1995). Conformity, although not yet empirically testified, is remarkable: intra-regional income distribution seems to become gradually fairer till the middle of 1970s. Afterwards, following a period of stagnation, shortly before the middle of 1980s, it starts to worsen again, causing a deepening of inequality that outreaches the level of 1960: ω/y falls to less than 1,4.

Figure 4: Compensation per employee relative to GDP per capita in EU-15

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In the next version, we need to include a table showing stationary and trend estimations for ω/y, for each country separately, so that we can show in details the reproduction of this development.

3.3 Growth effects – by country and EU average

The last part of our empirical, mostly descriptive, analysis concentrates on the growth rate itself. We calculate annual change rates of real GDP per capita for EU-15 as a whole as well as for each country member. Growth dynamic in EU-15 seems to follow a significantly negative trend. With the exception of Ireland, all significant trend coefficients are negative. Figure 5 shows the same for EU-15 as a whole (blue line).

Picture barely changes when we compare EU-15 growth rates to those for the world economy as a whole. Although there is no trend for EU-15 as a whole (this becomes obvious with the red line in figure 5), there are 7 countries that show an increasing hysterisis compared to the world-wide growth rates: Austria (only with ADF estimation), Belgium, France, Greece, Italy, Portugal and Spain (only with KPSS estimation). The opposite is true only for Luxemburg, the exceptional case of Ireland and the UK, which is the country that is relatively less integrated in the European Common Market.

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10 Note however that, as we mentioned already, the use of this ration may underestimate the degree of worsening in inequality, especially in periods of decreasing employment rate (increase of unemployment and of “non-participation” rate).


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Based on these observations, the historical paradigm of the European Union does not support the notion that removing borders contributes significantly to the strengthening of growth rates. If anything, it shows a case where, despite (or because of) a “regionally constrained process of internationalisation”, the prospects of the economy to grow have been affected in a negative way.

Table 5: Characteristics of real GDP per capita growth by region Estimation of trend Estimation of stationary ADF (AIC) ADF (SIC) PP KPSS Countries ADF

(AIC) ADF (SIC) PP KPSS coefficient




t-statistic

Austria -6,330§ -6,330§ -6,359§ 0,072 -0,062 -2,84*** -0,062 -2,84*** -0,062 -2,84*** -0,064 -3,6***

Belgium -6,350§ -6,350§ -6,349§ 0,127† -0,066 -2,90*** -0,066 -2,90*** -0,066 -2,90*** -0,068 -3,6***

Denmark -6,364§ -6,364§ -6,364§ 0,091 -0,038 -1,539 -0,038 -1,539 -0,038 -1,539 -0,045 -1,9*

Finland -3,350‡ -4,335§ -3,665§ 0,207 -0,026 -0,815 -0,028 -0,991 -0,009 -0,315 -0,044 -1,4 France -4,952§ -4,952§ -4,953§ 0,130† -0,059 -2,93*** -0,059 -2,93*** -0,059 -2,93*** -0,081 -5,2***

Germany -6,082§ -5,286§ -7,823§ 0,218§ -0,070 -3,08*** -0,048 -2,21*** -0,048 -2,213** -0,061 -3,3***

Greece -2,116 -4,573§ -4,709§ 0,210‡ -0,015 -0,351 -0,059 -1,397 -0,059 -1,397 -0,010 -2,8***

Ireland -4,018§ -4,018§ -4,010§ 0,095 0,044 1,536 0,044 1,536 0,044 1,536 0,060 2,1**

Italy -5,590§ -6,457§ -7,051§ 0,113 -0,114 -3,71*** -0,094 -3,54*** -0,094 -3,54*** -0,103 -5,1***

Luxembourg -5,355§ -5,355§ -5,318§ 0,233 0,038 1,026 0,038 1,026 0,038 1,026 0,043 1,2 Netherlands -4,290§ -4,290§ -4,260§ 0,100 -0,028 -1,448 -0,028 -1,448 -0,028 -1,448 -0,038 -2,0**

Portugal -3,998‡ -3,998‡ -4,343§ 0,073 -0,097 -2,191** -0,097 -2,191** -0,078 0,051* -0,122 -3,3***

Spain -3,697§ -3,697§ -3,697§ 0,165‡ -0,018 -0,845 -0,018 -0,845 -0,018 -0,845 -0,095 -3, 7***

Sweden -2,918† -4,078§ -3,972§ 0,245 0,053 1,638 -0,006 -0,312 -0,006 -0,312 -0,029 -1,3 UK -5,574§ -5,574§ -5,271§ 0,080 -0,001 -0,058 -0,001 -0,058 0,004 0,231 0,003 0,2 EU-15 -4,606§ -4,606§ -4,528§ 0,040 -0,029 -1,754* -0,029 -1,754* -0,029 -1,754* -0,047 -3,2***

World -3,966§ -3,966§ -3,987§ 0,253§ -0,028 -1,672 -0,028 -1,672 -0,023 -1,450 -0,040 -2,7***

Notes: †, ‡ and § denotes rejection of the 0-hypothesis of unit roots for Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP)

tests and rejection of the 0-hypothesis of stationary for the KPSS (Kwiatkowski-Phillips-Schmidt-Shin) test at the 10%, 5% and 1% significance level, respectively. *, **and *** denotes statistical significance at 10%, 5% and 1% significance levels, respectively.

Table 6: Characteristics of differences in real GDP per capita growth between each region and the world

Estimation of trend Estimation of stationary ADF (AIC) ADF (SIC) PP KPSS Countries

ADF (AIC)





t-statistic

Austria -3,400† -6,259§ -6,304§ 0,255 -0,040 -1,839* -0,023 -1,224 -0,023 -1,224 -0,024 -1,36 Belgium -4,112‡ -6,970§ -6,965§ 0,060 -0,031 -1,711* -0,030 -1,807* -0,030 -1,807* -0,028 -1,85*

Denmark -6,600§ -6,600§ -6,600§ 0,054 0,001 0,068 0,001 0,068 0,001 0,068 -0,004 -0,24 Finland -2,120 -4,226§ -4,092§ 0,085 0,002 0,071 0,006 0,242 0,006 0,242 -0,004 -0,15 France -5,911§ -5,911§ -5,916§ 0,048 -0,038 -2,629** -0,038 -2,629** -0,038 -2,629** -0,041 -3,21***

Germany -5,239§ -4,081§ -3,821§ 0,253 -0,018 -1,232 -0,018 -1,232 -0,013 -0,875 -0,021 -1,35 Greece -2,184 -5,721§ -5,942§ 0,196‡ -0,017 -0,479 -0,047 -1,346 -0,047 -1,346 -0,068 -2,08**

Ireland -1,497 -5,094§ -5,166§ 0,068 0,123 1,613 0,082 2,510** 0,082 2,510** 0,100 3,58***

Italy -6,042§ -6,042§ -6,022§ 0,146‡ -0,051 -2,433** -0,051 -2,433** -0,051 -2,433** -0,063 -3,46***

Luxembourg -5,558§ -5,558§ -5,558§ 0,110 0,071 2,071** 0,071 2,071** 0,071 2,071** 0,084 2,76***

Netherlands -1,672 -5,235§ -5,243§ 0,084 0,000 0,037 -0,004 -0,268 -0,004 -0,268 0,002 0,14 Portugal -1,627 -4,203§ -4,492§ 0,061 -0,043 -0,967 -0,079 -2,216** -0,062 -1,896* -0,081 -2,62**

Spain -4,618§ -4,618§ -4,591§ 0,127† -0,016 -0,813 -0,016 -0,813 -0,016 -0,813 -0,054 -2,49**

Sweden -3,058‡ -5,444§ -4,851§ 0,101 0,023 0,872 0,014 0,767 0,013 0,711 0,011 0,57 UK -5,102§ -5,026§ -4,888§ 0,124† 0,035 1,917* 0,033 1,909* 0,033 1,909* 0,044 2,84***

EU-15 -3,774§ -3,774§ -3,815§ 0,177 -0,003 -0,387 -0,003 -0,387 -0,003 -0,387 -0,007 -0,67



Figure 5: Real GDP per capita and real growth rates in EU-15 and differences to the world

-4,00

-3,00

-2,00

-1,00

0,00

1,00

2,00

3,00

4,00

5,0019

61

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

real GDP per capita growth ratereal GDP per capita growth rate in EU-15 related to the world

4. Conclusions

Conclusions of this version of the present paper should be discussed especially carefully. Yet, on the other hand, we find them very interesting too! First, there is a clear evidence for a structural change regarding the distributional patterns that found place around the middle 1980s. Till then, both, inter- and intra-regional inequality got narrower, but afterwards it shows a clear worsening. The previous trend of closing the gap among the countries reversed completely, while inequality within each country separately becomes also much deeper.

On the other hand, the experience from this historical paradigm of the European Union does not support the notion that removing borders contributes significantly to the strengthening of growth rates. If anything, it shows that the prospects of the economy to grow have been affected in a negative way. Partly, this could be explained because we have a “regionally constrained process of internationalisation”. Andriamananjara and Hillberty (2001) also noticed that trade relations with different countries strengthen domestic growth, especially when they apply to “third” countries, outside the borders of the area of a regional trade agreement regime (like the European Union). Similarly, Wooster et al (2008) find that trade within the countries of EU-13 has less, yet still positive, effect on economic growth compared to the effect from trade with non-EU countries. Nevertheless, they do no report a negative effect! Standard theory provide us with a range of arguments for why the unconditional, regionally unlimited expansion of trade is preferable compared to the one that results within the borders of regional agreements, but it does not (want to…) say anything about a negative effect on growth.

The importance of the mentioned observations forces us to work on a more thorough analysis. It is crucial to back them by using more sophisticated methodologies, which can enlighten more aspects of the underlying questions. A straightforward proposal is to apply a panel-data regression (annually and by country i) in order to check if there is a relation

10


among the development of inequalities within each country and the difference it has compared to EU-15 average, having in mind that there might be a specific trend because of the continuous process of internationalization. The proposed equation could be the following (fixed effect model):

(ω/y)i,t = α0 +α1(ωi,t–ωEU,t)/ωEU,t + α2(yi,t–yEU,t)/yEU,t + α3t + α4,iDVi + α5,tDVt + ε

Last but not least, it might be interesting to check all the above, but without Denmark, Sweden and UK, as these countries have not yet introduced €.

11


12

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15

Appendix

Table A,1: Overview of empirical literature for trade-growth relations STUDY DATA METHODOLOGY COUNTRIES TRADE GROWTH CAUSALITY SIGN NOTES

Michaely (1977) cross-country Spearman correlation Both OECD & Non OECD exports to GNP GNP per capita Trade--->Growth positive Growth--->Trade negative average level of exports to GNP positive value of exports to GNP at the end of the period Balassa (1978) cross-country Spearman correlation

& OLS Both OECD & Non OECD export growth GNP growth Trade--->Growth positive time-periods: 1960-1973, 1960-1966, 1966-1973

& sample: total exports, manufacturing exports Tyler (1981) cross-country Pearson & Spearman

correlation & OLS Both OECD & Non OECD export growth GDP growth Trade--->Growth positive total exports & manufacturing exports

Feder (1982) cross-country OLS Both OECD & Non OECD export growth GDP growth Trade--->Growth positive Kavoussi (1984) cross-country Spearman correlation

& OLS Both OECD & Non OECD growth rate of

real exports real GNP growth Trade--->Growth positive

Jung and Marshall (1985) time-series Granger causality test Both OECD & Non OECD export growth GDP growth Trade--->Growth positive for 4 out of 37 countries Trade--->Growth negative for 2 out of 37 countries Growth--->Trade positive for 3 out of 37 countries Growth--->Trade negative for 6 out of 37 countries Trade<-x->Growth none for 23 out of 37 countries Chow (1987) time-series Sims causality test Both OECD & Non OECD exports manufactured

output Trade<--->Growth positive exports & industrial development

Kwasi Fosu (1990)a panel data OLS Both OECD & Non OECD export growth GDP growth Trade--->Growth positive

Kwasi Fosu (1990)b cross-country OLS Non OECD export growth GDP growth Trade--->Growth positive manufactured exports stat, insignificant in case of primary exports Ahmad and Kwan (1991) time-series Granger causality test Non OECD real exports real GDP per

capita Trade<-x->Growth none

Bahmani-Oskooee et al (1991)

time-series Granger causality test Both OECD & Non OECD real export growth

real GDP growth Trade--->Growth positive for 5 out of 20 countries

negative for 3 out of 20 countries Trade-x->Growth none for 10 out of 20 countries Growth--->Trade positive for 4 out of 20 countries negative for 1 out of 20 countries Growth-x->Trade none for 13 out of 20 countries Dodaro (1991) cross-country OLS Both OECD & Non OECD exports real GDP growth Trade--->Growth positive manufactured exports as a percentage of total

merchandise exports Serletis (1992) time-series Granger causality test OECD exports &

imports GNP Trade--->Growth positive export growth & past GNP growth

Granger cause future GNP growth


16

Table A,1: Overview of empirical literature for trade-growth relations (continued) STUDY DATA METHODOLOGY COUNTRIES TRADE GROWTH CAUSALITY SIGN NOTES

Oxley (1993) time-series Engle and Granger's error correction approach

OECD real exports real GDP Growth--->Trade positive

Van den Berg and Schmidt (1994)

time-series Engle and Granger's error correction approach

Both OECD & Non OECD exports real GDP growth Trade--->Growth positive stat, insignificant cases are quite possibly due to exceptional circumstances

Abhayaratne (1996) time-series Engle and Granger's error

correction approach & SUR Non OECD real exports

& real imports real GDP Trade<-x->Growth none

Van den Berg (1996) time-series 3-stage LS Both OECD & Non OECD real exports

& real imports GDP per capita growth

Trade--->Growth positive

McNab and Moore (1998) cross-country OLS, 3SLS Both OECD & Non OECD export growth GDP growth Trade<--->Growth positive export growth weighted by the initial export to GDP

ratio Dhawan and Biswal (1999)

time-series Engle and Granger's error correction approach & VAR

Both OECD & Non OECD real exports real GDP Trade--->Growth positive short-run

Growth--->Trade positive short-run & long-runFrankel and Romer (1999) cross-country OLS & IV Both OECD & Non OECD exports +

imports GDP Trade--->Growth positive

Ghali (1999) time-series Engle and Granger's error

correction approach OECD exports +

imports to GDP GDP Trade<--->Growth positive

Greenaway et al (1999) panel data GMM Both OECD & Non OECD exports GDP per capita Trade--->Growth positive Andriamananjara and Hillberry (2001)

time-series GTAP model (Global Trade Analysis Project Model)

Non OECD exports + imports

GDP Trade--->Growth positive less dynamic gains from trade than expected by TDCA

Khalafalla and Webb (2001)


Non OECD real exports & real imports

real GDP Trade--->Growth positive however, causality depends on time period, time orientation and variables as well as primary and manufactured exports

Lutz (2001) cross-country Pearson correlation Both OECD & Non OECD imports per

capita GNP per capita Trade--->Growth positive positive relationship that becomes weaker and less

stat, significant as time passes, total & manufacturing imports per capita

Ramos (2001) time-series Engle and Granger's error correction approach

OECD real exports & real imports

real GDP Trade<--->Growth positive

Chuang (2002) cross-country OLS Both OECD & Non OECD imports +

exports GDP per capita Trade--->Growth positive


17


Liu et al (2002) time-series Engle and Granger's error correction approach

Non OECD exports & imports

GDP Trade<--->Growth positive

Panas and Vamvoukas (2002)


OECD real exports real GNP Growth--->Trade positive long-run

Coulombe (2003) pooled data Granger causality test OECD exports +

imports to GDP GDP Trade--->Growth positive international & interprovincial trade

(exports + imports) Dar and AmirKhalkhali (2003)

panel data random coefficients GLS model

OECD exports growth real GDP growth Trade--->Growth positive

Lewer and Van den Berg (2003)

time-series OLS & GLS Both OECD & Non OECD exports + imports growth

GDP growth Trade--->Growth positive Mazumdar's hypothesis (1996)

panel data fixed effects Wacziarg and Welch (2003)

panel data random (SUR model) & fixed effects

Both OECD & Non OECD exports + imports to GDP

real GDP per capita growth

Trade--->Growth positive however, in many individual countries the sign might be negative

Yanikkaya (2003) cross-country Pearson correlation, OLS, SUR, 3SLS & fixed effects

Both OECD & Non OECD exports + imports to GDP

GDP per capita growth


tariffs Barriers--->Growth positive resource allocation and/or positive externalities De Matteis (2004) panel data fixed effects Both OECD & Non OECD exports GDP per capita Trade--->Growth positive Dollar and Kraay (2004) cross-country OLS, IV Both OECD & Non OECD exports +

imports to GDP real GDP per capita growth


Gagnon (2004) cross-country OLS Both OECD & Non OECD real exports real GDP Growth--->Trade positive time-periods: 1960-2000, 1960-1980, 1980-2000 &

sample: all the countires, the countries which mainly export manufactured goods & services

Thangavelu and Rajaguru (2004)


Both OECD & Non OECD imports & exports

labour productivity growth

Trade--->Growth positive for 6 out of 9 countries (trade=imports)

Growth--->Trade positive for 4 out of 9 countries (trade=imports) Trade--->Growth positive for 4 out of 9 countries (trade=exports) Growth--->Trade positive for 6 out of 9 countries (trade=exports) Reppas and Christopoulos (2005)

panel data fully modified OLS Non OECD real exports real GDP Growth--->Trade positive


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Kónya (2006) panel data SUR estimator (Zellner, 1962) & Granger causality test

OECD real exports real GDP Trade--->Growth positive for 8 out of 24 countries

Growth--->Trade positive for 7 out of 24 countries Trade<--->Growth positive for 3 out of 24 countries Trade<-x->Growth none for 6 out of 24 countries Tsen (2006) time-series Engle and Granger's error

correction approach Non OECD imports +

exports to GDP real GDP per capita

Trade<--->Growth positive

Awokuse (2007) time-series Engle and Granger's error

correction approach Both OECD & Non OECD real exports

& real imports real GDP growth Trade<--->Growth positive for Bulgaria, where trade=exports but when

trade=imports there is only growth--->trade Trade--->Growth positive for Czech Republic, where trade=exps+imps Trade--->Growth positive for Poland, where trade=importsCoulombe (2007) panel data DS, ECM OECD imports +

exports GDP per capita Trade--->Growth positive

Kali et al (2007) cross-country OLS, IV Both OECD & Non OECD imports +

exports to GDP GDP per capita Trade--->Growth positive for the poor countries

negative … but stat, insognificant for the rich countries panel data fixed effects positive … but stat, insognificant for the whole sample of

countries Minondo (2007) cross-country OLS & IV Both OECD & Non OECD exports GDP per capita Trade<-x->Growth none take into account the the quality differences within

products panel data fixed effects & GMM Nath and Mamun (2007) time-series Engle and Granger's error

correction approach & VAR

Non OECD real exports + real imports to real GDP

real GDP per capita

Trade<--->Growth positive

exports Trade<--->Growth positivePacheco-López and Thirlwall (2007)

panel & pooled data

random & fixed effects Both OECD & Non OECD

trade balance to GDP

GDP growth Trade--->Growth negative … but stat, insignificant,

Wooster et al (2008) panel data fixed effects OECD exports +

imports to GDP GDP per capita growth

Trade--->Growth positive intra-regional & extra-regional trade (exports + imports)

Yakovlev (2007) panel data fixed & random effects,

GMM Both OECD & Non OECD

net arms exports real GDP per capita growth

Trade--->Growth positive net arms exporter & military spending

negative net arms exporterAwokuse (2008) time-series Engle and Granger's error

correction approach Non OECD real exports

& real imports real GDP growth Trade<--->Growth positive focus on imports

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