EMPLOYMENT, DEVELOPMENT AND RESEARCH EXPENDITURE IN THE EUROPEAN UNION : ANALISYS OF CAUSALITY AND COMPARISON WITH THE UNITED STATES, 1993-2003 GUISAN, Maria-Carmen*
AGUAYO, Eva Abstract
We analyse causality between real values of expenditure on Research and Development, RD, and Gross Domestic Product, Gdp, in 15 countries of European Union and the United States for 1993-2003, by means of Granger´s test and an interdependent dynamic model.
The lower averages of RD expenditure per inhabitant of many European countries, in comparison with the US, play an important role to explain lower levels of real Gdp per inhabitant and lower rates of Employment. The main conclusion points to the convenience of fostering support to research in several European countries in all fields, both technological and non-technological, in order to get a higher degree of convergence to the levels of income per inhabitant and rates of employment of the USA.
JEL classification C5, C51, O18, O52
Keywords: Causality, European Union, USA, Employment, Research and Development
1. Introduction
This study is aimed to foster employment and development in the European Union as a whole, and particular in those countries with lower rates of employment and real income per inhabitant, focusing on the important role that expenditure on Research and Development, RD, has shown in this regard in the United States and in other advanced economies. Section 2 presents a summary of some selected bibliographical references on this regard. Section 3 present a
* Maria-Carmen Guisan is Professor of Econometrics and Director of Master on International Sectoral Economics at the University of Santiago de Compostela, Spain, e-mail: eccgs@usc.es, and Eva Aguayo is Coordinator of that Master at the same university, eaguayo@usc.es
comparison of employment, development and research expenditure per inhabitant in the European Union, EU, and the United States of America, USA. Section 4 analyses causality between RD expenditure and Gdp, section and the effects of both variables on employment and wages. Finally section 5 presents the main conclusions.
2. Economic literature on RD and development.
It is widely recognised that knowledge and innovation is very important for economic development, although not always it is easy to demonstrate their positive effects in quantitative studies. The experience of the second half of the 20th century shows clearly that all the countries which have fostered education and research have got great profits for the well-being of their population, with high levels of real income per inhabitant and high levels of employment. Since the some pioneering studies on the positive role of RD expenditure as those of Jaffee(1989) in the field of the real effects of academic research, and Fagerberg(1987) on the effects of technological gap, the interest of economics researchers on this field has been growing.
Vickerman and Armstrong(1995) present an interesting selection of studies related with the positive effects of RD activities on European regional development, and Magrini(1998) analyses the growth process at work in the European Union during the period 1979-1990, with particular emphasis on the role played by human capital, research activities and spillovers of technological knowledge, including the estimation of an econometric model with data of 122 major European Functional Urban Regions (FURs), which show the positive and highly significant coefficients of RD activities on regional development. Another interesting studies on the positive effects of RD activities on European development are those of Badinger and Tondls(2002), Barrio and Garcia-Quevedo(2003), Korres, Chionis, and Staikouras(2004), Martin, Mulas-Granados, and Sanz(2004), Moreno-Serrano, Paci, and Usai (2003), Guisan(2004), and Guisan and Aguayo(2005), among other articles cited in the bibliography. In our experience the positive role of RD on economic development is not limited to technological advances but we found that non technological research has also a great relevance.
Lederman and Maloney(2003) present an international comparison of countries with different RD policies, and they point to the striking finding that some countries in Europe and Asia have radically deviated from the predicted trajectory with impressive takeoffs of RD expenditures and high increases in their economic performance.
They found low improvements in this regard in Latin American countries and analyse why RD efforts differ among countries.
2. Research, real Gdp and Employment in Europe and the USA
Table 1 presents the evolution of the following variables in European Union and the USA during the period 1993-2003:
Lth = employment per thousand inhabitants (rate of employment) Gdph = real Gdp per inhabitant ($ at 2000 prices and exchange rates)
Rdh = Expenditure per inhabitant on Research and Development, RD, ($ at 2000 prices and exchange rates)
Data has been elaborated from OECD and Eurostat statistics using real exchanges rates of year 2000 for conversion to dollars.
During the last decades of the 20th century the European Union has experienced more economic problems than the USA regarding the evolution of real wages, real income per inhabitant and rates of employment, as it has been analysed in several studies, such as Guisan and Cancelo (2004) and Guisan and Aguayo(2005), among others. Although there are big differences among EU countries, the fact is that Europe as a whole has a level of research expenditure per inhabitant very low in comparison with the USA and the European economic capacity, so some improvements in EU policies should be advisable in this regard.
Graphs 1 and 2 show that the fifteen countries of the UE15, had in this period a rate of employment below the USA, in spite of a lower cost per employee. The cause of the lower rates of employment in Europe are not bigger salaries but lower levels of production per inhabitant, which depend in part of RD expenditure.
Table 1. Employment, Gdp, and RD expenditure (dollars per inhabitant, in $ at 2000 prices)
European Union United States Year
Lth Gdph Rdh lth Gdph Rdh 1993 403 17713 341 465 28737 718 1994 401 18155 341 473 29543 709 1995 403 18544 345 474 29936 745 1996 404 18812 350 475 30698 777 1997 407 19241 358 479 31713 812 1998 413 19746 369 481 32667 846 1999 419 20277 389 483 33746 888 2000 426 20945 409 489 34611 935 2001 430 21211 423 485 34544 936 2002 430 21344 429 479 34870 921 2003 430 21445 429 477 35488 979
Source: Elaboration from OECD and Eurostat statistics.
Graph 1. Rate of Employment Graph 2. Labour cost per worker (number per one thousand inhabitants) (thousand $ at 2000 PPPs)
360 380 400 420 440 460 480 500
60 65 70 75 80 85 90 95 00 USA
Europena Union
10 15 20 25 30 35 40
1965 1970 1975 1980 1985 1990 1995 2000 USA
European Union
Graph 3 shows the positive relationship of RD per inhabitant, Rdh, and Gdph. Th relationship is bilateral, because Rdh contributes to increase real Gdph, while countries with highest levels of Gdph are usually more prone to increase expenditure on research, and graph 4 shows the value of Research and Development Expenditure of the 16
countries of this study in year 2003. We can notice the very low averages of Spain, Greece and Portugal.
Graph 3. Gdph and Rdh; EU15 and USA, 1993-2003 ($ per inhabitant, at 2000 prices)
1 6 2 0 2 4 2 8 3 2 3 6 4 0
0 . 3 0 . 4 0 . 5 0 . 6 0 . 7 0 . 8 0 . 9 1 . 0
R d h G d p h
Source: Elaborated from data of table 1.
Graph 4. RD expenditure per inhabitant in Europe and USA, 2003 (thousand dollars at 2000 prices and exchange rates)
0 . 0 0 . 2 0 . 4 0 . 6 0 . 8 1 . 0 1 . 2
At B e D e D k E s F r F i G r I r It Lu N e P t S e U k U s
Source: Own elaboration from Eurostat and OECD Statistics. Austria (At), Belgium (Be), Germany (De), Denmark (Dk), Spain (Es), France (Fr), Finland (Fi), Greece (Gr), Ireland (Ir), Italy (It), Luxembourg (Lu), Netherlands (Ne), Portugal (Pt), Sweden (Se), United Kingdom (Uk), and the United States (Us).
Graphs 5 and 6 show, respectively, the evolution of total expenditure on Research and Development, RD, and research expenditure per inhabitant, in the European Union and the United
States for the period 1993-2003, with data expressed in dollars at 2000 prices and exchange rates ($2000). These graphs clearly show the lower support of European Union to the important activities of researchers, in comparison with the USA.
Graph 5. RD expenditure Graph 6. RDH expenditure (million $2000) ($2000 per inhabitant)
120000 160000 200000 240000 280000 320000
93 94 95 96 97 98 99 00 01 02 03 USA
EU15
300 400 500 600 700 800 900 1000
93 94 95 96 97 98 99 00 01 02 03 USA
EU15
An improvement in the EU policy of support to research should have highly positive effects on EU development and employment.
Now we analyse some causality relationships in this regard.
3. Econometric models and analysis of causality
Table 2 shows the results of applying Granger´s test of causality to the relationship between Gdph and Rdh in each European country and the USA, with data presented in Guisan(2005).We notice that, because the high degree of multicollinearity that is often present in the application of this test, the causal relationship can only be accepted in 8 cases out of 16 for Rdh depending on Gdph and in 5 cases for the reverse relationship. We test the joint nullity of coefficients of the lagged values of Gdph in (1) and the joint nullity of coefficients of the lagged values of Rdh in (2):
Rdhht = f(Gdpht-1, Gdpht-2, Rdht-1, Rdht-2) (1) Gdpht = f(Gdpht-1, Gdpht-2, Rdht-1, Rdht-2) (2)
Table 2. Granger´s Causality test for Gdph and Rdh, 1993-2003
Country F1 p1 F2 p2
Austria 6.5983 0.0541 11.535 0.0218
Belgium 1.5376 0.3196 0.2590 0.7837 Denmark 24.927 0.0055 10.640 0.0250 Finland 27.633 0.0045 6.6091 0.0539 France 2.1596 0.2311 2.6451 0.1853 Germany 1.1570 0.4013 2.0451 0.2444 Greece 1.5556 0.3163 22.539 0.0066 Ireland 8.1492 0.0388 0.7281 0.5374 Italy 5.0944 0.0794 0.5161 0.6318 Luxembourg 0.4411 0.6661 1.0407 0.4188 Netherlands 0.5890 0.5967 0.5755 0.6030 Portugal 3.7230 0.1221 14.547 0.0146 Spain 0.4357 0.6742 0.1639 0.8542 Sweden 26.346 0.0049 0.1454 0.8690 UK 9.8949 0.0282 1.7192 0.2891 USA 6.8386 0.0512 0.1574 0.8593
Note: F1 is the F-statistic to test H1: “Gdph does not cause Rdh” in (1) and F2 corresponds to H2 :”Rdh does not cause Gdph” in (2), while p1
and p2 are the significance levels for 2 lags. Non-causality is rejected at the 10% level of significance in 8 cases for F1 and in 5 cases for F2.
Granger´s test with the 144 observations of the pool of 16 countries, shows that both variables have a bilateral relationship, with the following results for the F statistics of (1) and (2), with coefficients which are highly significant:
F1 = (∆SCE1/2)/(SCE1/(144-4)) = 675.82 > Fα; F0.05(2,140) = 3.07 F2 = (∆SCE2/2)/(SCE2/(144-4)) = 230.68 < Fα; F0.05(2,140) = 3.07
In order to analyse the contemporaneous relationship between both variables we present in table 3 the estimated coefficients for the period 1993-2003 of the following mixed dynamic model:
RDH = C(11)*RDH(-1) + C(21)*D(GDPH) (3) GDPH = C(12)*GDPH(-1) + C(22) *D(RDH) (4)
Table 3. Estimation of (3) and (4), with 160 observations, 1994-2003
Method C(11) C(21) C(12) C(22) LS, White 1.0264
(151.27)
0.0131 (4.36)
1.0198 (500.44)
6.4447 (4.31) TSLS 1.0308
(206.43)
0.0088 (2.34)
1.0228 (463.96)
2.8815 (1.51) Note: terms between parentheses are the t-statistics. All the coefficients, but C(22) in TSLS are significant at 5% level.
Results of table 3 show that a contemporaneous relationship holds for relation (3) but that one or more lags are usually needed to show the impact of Rdh on Gdph.
Finally we analyse the causality between RD and Employment having into account the models of employment estimated in Guisan(2005). Here we analyse causality between real Gdp ( which is positively influenced by Rd expenditure) and real value of Ce (which influences positively both employment and wages).
Table 4. Granger´s Causality test for Gdp and Ce, 1964-2000
sample F1 p1 F2 p2
EU15 1966-2000 3.8968 0.0313 1.2019 0.3145 United States 1964-2000 3.5618 0.0401 1.0127 0.3745 Note: F1 to test H1: “Gdp does not cause Ce” and F2 to test H2 : ”Ce does not cause Gdph”; p1 and p2 are the significance levels for 2 lags. Non-causality is rejected for H1 and non rejected for H2. 5. Conclusions
The analysis of causality has shown a positive influence of research expenditure on economic development and employment. We recommend that European Union should foster dialogue between EU Parliament and the Associations of European researchers in order to improve the financial support to researchers in all areas of knowledge, not only in technological ones, because both types of research have a positive impact on socio-economic development.
The report of the Council of Europe(2000) includes some interesting
do not fully agree with this report regarding its recommendations about the systems of financing with high dependence on bureaucratic procedures. Methods more friendly for researchers should be implemented in Europe with a higher degree of dialogue with researchers and scientific associations. More support to RD expenditure in EU will contribute positively to a higher level of convergence to the levels of income and employment of the USA.
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