In the increasingly knowledge-based global economy, a well-educated and highly-skilled labour force and a significant degree of openness to international trade are vital for countries to successfully meet the challenge of worldwide competition. This paperhuman capital, openness to international trade, economic growth

Castagna Alina

Colantonio Emiliano

Scamuffa Domenico

English

Research Papers in Economics

554 
 
HUMAN CAPITAL AND OPENNESS TO INTERNATIONAL TRADE: EVIDENCE 
FROM THE ENLARGED EUROPE 
 
Scamuffa Domenico 
University of Chieti-Pescara Faculty of Management Sciences Viale Pindaro 42 – 65127 Pescara 
(Italy) domenico.scamuffa@gmail.com +39 085 4537679 
Colantonio Emiliano 
University of Chieti-Pescara Faculty of Management Sciences Viale Pindaro 42 – 65127 Pescara 
(Italy) colantonio@unich.it +39 085 4537577 
Castagna Alina 
University of Chieti-Pescara Faculty of Management Sciences Viale Pindaro 42 – 65127 Pescara 
(Italy) alinacastagna@yahoo.it +39 085 4537974 
 
In the increasingly knowledge-based global economy, a well-educated and highly-skilled labour force and 
a significant degree of openness to international trade are vital for countries to successfully meet the 
challenge of worldwide competition. This paper is meant to provide empirical insights into the patterns of 
human capital endowments and international economic integration across Europe. By using a number of 
indicators capturing the main aspects of these variables, we perform  a cluster analysis in an effort to show 
similarities and differences among the EU’s 27 Member States.   
 
Keywords: human capital, openness to international trade, economic growth 
 
JEL code: O4, F2 
 
1. Introduction 
Economists have long been concerned with the determinants of long-term economic growth. It is 
nowadays  widely  accepted  that  technological  progress,  high  levels  of  human  capital  and  a 
significant degree of openness to international trade, knowledge flows and financial flows, play a 
major role in fostering growth, particularly in an increasingly knowledge-based global economy. 
No wonder, then, two striking examples of economies experiencing sharp increases in growth 
rates, China and India, have become large scale exporters of manufactured goods of growing 
sophistication and benefited from a well-educated and skilled labour force. 
In this respect, the recent theoretical and empirical literature on economic growth has emphasized 
the relevance of intangible factors, mainly human capital diffusion and openness to international 
trade, in accounting for productivity growth. The aim of this paper is to shed more light on the 
determinants of growth and to provide a preliminary picture of the patterns of human capital 
endowments and trade integration across Europe. After a brief review of the main theoretical 
underpinnings, we perform a cluster analysis to show similarities and differences among the EU’s 
27 Member States in terms of human capital and international trade integration.  
 
2. Human capital and trade as engines of growth 
Over the recent years, the relationship between human capital, openness to international trade and 
economic  growth  has  been  explored  to  a  great  extent  in  literature.  In  this  respect,  the  key 
contributions have been developed within the framework of endogenous growth theory. This 
strand of research embraces a diverse body of theoretical and empirical studies, emerged during 
the 1980s as a reaction to the neoclassical growth model. The new growth theories have provided 
persuasive  intellectual  support  for  the  proposition  that  economic  growth  is  sustained  by 
knowledge, human capital and technological progress.  
Romer’s (1986) seminal paper paved the way for the new growth theory, by putting the emphasis 
on the process of accumulation of knowledge, whose spillovers across firms and individuals 
positively affects the long-run rate of growth. In the Lucas (1988) model, human capital has 555 
 
come into prominence as a major source of growth in economies. By treating human capital as an 
ordinary input in the production function, Lucas shows how growth is driven by the accumulation 
of knowledge and skills embodied in individuals. In this way, differences in growth rates across 
countries  are  assumed  to  be  primarily  due  to  differences  in  the  rates  of  human  capital 
accumulation. 
In contrast to Lucas’s assumption, other scholars relate growth to the level of human capital. 
Romer (1990) finds that economies with a larger total stock of human capital experience more 
rapid rates of technical progress and productivity growth. In this model, endogenous growth is 
ultimately  dependent  on  technical  progress  driven  by  private  investment  in  research  and 
development (R&D). R&D activities are assumed to give rise to new designs and products which 
generate temporary monopoly rents. These rents provide the financial incentives to innovate and 
to cover the cost of innovation. In this light, the stock of human capital employed in research 
activities determines the capacity of nations to innovate and does lie at the heart of economic 
growth. Similarly, Benhabib and Spiegel (1994; 2005) emphasize the role of the stock of human 
capital, which affects both a country’s ability to innovate and its speed of technological catch-up 
and diffusion. This model builds on Nelson and Phelps (1966), whose major contribution was to 
suggest that the rate at which the gap between the world technology frontier, represented by the 
country  leader,  and  the  follower’s  level  of  productivity  is  closed  depends  on  the  stock  of 
domestic human capital. The presumption behind these approaches is that an educated labour 
force is not only better at creating new technologies, but also at adopting and implementing 
technological advances from abroad. Accordingly, for Benhabib and Spiegel the stock of human 
capital affects growth through two mechanisms: it directly influences the rate of domestically 
produced technological innovations while speeding up the process of technological catch-up with 
more advanced countries. The significance of this model in both theoretical and empirical terms 
is that growth rates differ across countries due to differences in levels, rather than growth rates, of 
human capital stocks. 
In the wake of these findings, a number of attempts to trace the combined role of human capital 
and technology diffusion in economic growth has been made since. Grossman and Helpman 
(1991) and Barro and Sala-i-Martin (1995) have argued that countries that are more open to 
international trade have a greater ability to absorb innovations generated in leading nations. By 
considering  a  two-countries  world  (one  advanced  and  one  poorer),  Barro  and  Sala-i-Martin 
(1995, Ch. 8) find that the rate of growth in the developing country depends on the cost of 
imitation of innovations produced in the leading nation, and on its initial stock of knowledge. 
Intuitively, the model predicts that poorer countries may grow faster if they adopt more foreign 
technology by opening up to international trade. 
The existence of a positive correlation between a country’s degree of openness to international 
exchange and its growth performance is a well-documented empirical regularity, that is almost 
universally accepted by economists. Grossman and Helpman (1991, Ch. 9) describe four distinct 
mechanisms by which countries adopting outward-oriented policies experience rates of growth 
and technical progress much greater than those achievable with inward-oriented policies. First, as 
discussed  above,  international  trade  opens  channels  of  communication  that  facilitates  the 
exchange  of  technical  information  on  innovative  products  and  novel  methods  of  production. 
Secondly,  by  introducing  competition  between  firms  in  different  countries,  trade  gives 
entrepreneurs  in  each  location  a  strong  incentive  to  pursue  new  and  distinctive  ideas  and 
technologies.  Third,  economic  integration  enlarges  the  size  of  the  market  available  to  any 
producer.  Finally,  the  opening  of  trade  between  countries  induces  distinct  patterns  of 
specialization in different manufacturing activities for each trading partner. 
In this wake, Rivera-Batiz and Romer (1991) have outlined two channels for the transfer of 
technological  knowledge: the  transmission  of  ideas which  can  be  traded independently  from 556 
 
goods, and the trade of capital goods (machinery and equipment) that embody new knowledge. In 
their model, both international knowledge flows raise growth.  
The  new  paradigm  of  endogenous  growth  has  spurred  a  spate  of  research  that  tried  to  test 
empirically the contribution of these factors to total factor productivity growth. Over the 1990s, 
the conviction that  human  capital  was  good  for  growth  was  fostered  by  a  number  of cross-
country studies (e.g. Barro 1991, 1997; Gemmell 1996; Benhabib and Spiegel 1994), though 
there exists a number of empirical studies that are sometimes inconsistent with this expectation 
(Pritchett 1996). Similarly, economic literature has explored directly the quantitative relationship 
between trade openness and the level and growth of per capita GDP. Several empirical studies (to 
name  a  few,  Dollar    1992;  Sachs  and  Warner  1995;  Edwards  1998)  found  that  increased 
economic integration between countries has tended to increase the long-run rate of economic 
growth. 
Stemming from these findings, this paper performs a cluster analysis to highlight how human 
capital is distributed in Europe and to what degree European countries are open to international 
trade. 
 
3. Data and methodology 
In  this  section,  our  goal  is  to  identify  the  empirical  patterning  of  human  capital  stocks  and 
openness  to  trade  across  Europe.  In  line  with  the  main  findings  of  the  endogenous  growth 
literature, one could put forward the argument that countries that fare well in terms of human 
capital endowments and trade integration today are expected to exhibit rising GDP levels in the 
coming years. Can European countries be clustered according to the extent to which they have 
high or low levels of human capital or are more or less integrated with world markets? Can we 
detect any particular pattern among the data? To answer these questions, we apply an explanatory 
technique  –  cluster  analysis  –  in  order  to  partition  European  countries  into  homogeneous 
subgroups  without  any  constrains  or  a  priori  information.  In  this  respect,  cluster  analysis 
attempts to organize variables into distinct groups based on a statistical measure of their distance 
from each other. 
In order to operationally define and loose concepts such as human capital and trade integration, 
the analysis includes 15 indicators to reflect the multi-faceted dimensions of these variables
293. 
The data for this exercise come from the Eurostat
294 database and the World Bank
295 database and 
mainly refer to year 2006
296. The dataset covers all the 27 EU Member States. 
Variables are normalised into a range of 0 and 1 prior to the analysis to account for different 
variances  according  to  the  measurement  level.  In  the  clustering  process,  we  use  the 
agglomerative  hierarchical  method  that  merges  any  element  into  successively  larger  clusters 
                                                       
293 Eight indicators are used for the human capital domain: Graduates (ISCED 5-6) in maths, science and technology 
fields as a percentage of all fields; Ratio of students to teachers (ISCED 1-3); Total public expenditure on education 
(all levels of education combined) as a percentage of GDP; Students (ISCED 1-6) by sex aged 15-24 years as a 
percentage of the corresponding age population; Average number of foreign languages learned per pupil at ISCED 
level  3;  Total  R&D  personnel  as  a  percentage  of  total  employment;  Annual  expenditure  on  public  and  private 
educational institutions per pupil/student;  Gross tertiary school enrollment. Seven indicators are selected to account for 
the degree of openness to international trade: Foreign Direct Investment (FDI) intensity (calculated as the average 
value of inward and outward FDI flows divided by GDP - in percent); Imports of high technology products as a share 
of total imports;  Exports of high technology products as a share of total exports; Computer, communications and other 
services as a percentage of commercial service imports; Computer, communications and other services as a percentage 
of commercial service exports;  Exports of goods and services as a percentage of GDP; Imports of goods and services 
as a percentage of GDP. 
294 http://ec.europa.eu/eurostat. 
295 http://www.worldbank.org/data/onlinedatabases/onlinedatabases.html. 
296 Data from 2006 are not available for three indicators (Total public expenditure on education as a percentage of 
GDP, Total R&D personnel as a percentage of total employment, Annual expenditure on public and private educational 
institutions per pupil/student), for which we consider the data collected in 2005. 557 
 
combined sequentially until one single cluster is constructed. Euclidean distances are calculated 
to measure distance for the observed data. The average (between groups) linkage method is used 
to find reasonable cluster solutions. The traditional representation of this hierarchy is a clustering 
tree called dendrogram, under which the y-axis plots the objects of study (European countries) in 
descending order of similarity and the x-axis denotes the linkage distance among groups. The 
larger the index printed on the horizontal axis, the more differences can be observed between 
countries or clusters of countries. 
 
4. Results 
Figure 1 shows the cluster results in the form of the dendrogram that represents the similarities 
and  differences  concerning  the  distribution  of  human  capital  and  the  degree  of  openness  to 
international trade across European countries. The final cluster solution suggests five distinct and 
fairly homogenous clusters in this broad sample of countries, by cutting the tree at the index 
value of about 6 points.  
 
Fig. 1 - Clusters of human capital and trade integration in Europe 
 
The first cluster is composed of countries (Italy, Spain, Portugal, Austria, France and the United 
Kingdom) that are very similar as they merge at a very early stage of the process. This is a very 
homogeneous block of Western European countries which show values of human capital stocks 
ranging from medium to high and low levels of trade integration (they exhibit low values on trade 558 
 
as a share of GDP). The picture changes somewhat when considering the second cluster, made up 
of Eastern European countries (Czech Republic, Slovakia, Estonia, Bulgaria, Romania, Lithuania, 
Latvia, Poland and Slovenia) and Greece. This fairly similar grouping claims the bulk of Eastern 
Europe, which are low on the measures of human capital and average on the degree of trade 
openness. Cluster 3 includes three geographically non-proximate countries (Belgium, Sweden 
and Hungary), which score highly in terms of international trade integration and expenditure in 
education – though they show mixed results as to the other indicators of human capital diffusion. 
A similar pattern emerges in the fourth cluster. This grouping contains Germany, the Netherlands 
and Ireland, with medium to high levels of both human capital indicators and openness to trade. 
Cluster 5 consists of two Nordic countries, such as Denmark and Finland, which are high on 
human capital and average to high on trade integration. Not all the Member States are clustered 
within the five groups: Cyprus, Malta and Luxembourg are outliers. 
 
5. Conclusive remarks 
The arguments presented above suggest economists place a large emphasis on human capital and 
openness to international trade as determinants of growth. We have performed a cluster analysis 
to determine similarities and differences among European countries in this respect. The analysis 
shows that there are five distinct clusters showing different patterns of human capital diffusion 
and international integration across Europe. Clearly, the results leave open the question as to 
whether, and to what extent, these variables affect economic growth. Future research may want to 
address whether human capital and trade integration can be given a causal interpretation in the 
growth process. 
 
References 
1. Barro R.J. (1991), Economic Growth in a Cross Section of Countries, Quarterly Journal of 
Economics, 106(2), 407-443. 
2.  Barro,  R. J.  (1997).  Determinants  of  Economic Growth:  A  cross-country empirical  study. 
Cambridge Massachusetts: The MIT Press. 
3. Barro R.J. and Sala-i-Martin X. (1995), Economic Growth, McGraw-Hill, New York. 
4. Benhabib J. and Spiegel M.M. (1994), The Role of Human Capital in Economic Development: 
Evidence from Aggregate Cross-Country Data, Journal of Monetary Economics, 34, 143-173. 
5. Benhabib J. and Spiegel M.M. (2005), Human capital and technology diffusion, in Aghion P. 
and Durlauf S. (eds.), Handbook of economic growth, Elsevier, North-Holland, Amsterdam. 
6.  Dollar  D.  (1992),  Outward-oriented  developing  economies  really  do  grow  more  rapidly: 
evidence from 95 LCDs, 1976-1985, Economic Development and Cultural Change, 40, 523-544. 
7. Edwards S. (1998), Openness, productivity and growth: what do we really know?, Economic 
Journal, 108, 383-398. 
8. Gemmell N. (1996), Evaluating the Impacts of Human Capital Stocks and Accumulation on 
Economic Growth: Some New Evidence, Oxford Bulletin of Economics and Statistics, 58, 9-28. 
9. Grossman G.M. and Helpman E. (1991), Innovation and Growth in the Global Economy, MIT 
Press, Cambridge, MA.  
10.  Lucas  R.E.  (1988),  On  the  mechanics  of  economic  development,  Journal  of  Monetary 
Economics, 22(1), 3-42. 
11.  Nelson  R.  R.  and  Phelps  R.  (1966),  Investment  in  humans,  technological  diffusion  and 
economic growth, American Economic Review, 56(2), 69-75. 
12.  Pritchett  L.  (1996),  Where  has  all  the  education  gone?,  World  Bank  Policy  Research, 
Working Paper No. 1581 
13. Rivera Batiz L.A. and Romer P.M. (1991), Economic integration and endogenous growth, 
The Quarterly Journal of Economics, 106(2), 531-555. 559 
 
14. Romer P.M. (1986), Increasing Returns and Long-run Growth, Journal of Political Economy, 
94(5), 1002-37. 
15. Romer P.M. (1990), Endogenous Technological Change, Journal of Political Economy, 98, 
71-102. 
16. Sachs J. and Warner A. (1995), Economic reform and the process of global integration, 
Brookings Papers on Economic Activity, 1, 1-118. 

Determinants of Economic Growth: A cross-country empirical study. Cambridge Massachusetts:

Economic Growth in a Cross Section of Countries,

Economic integration and endogenous growth,

Economic reform and the process of global integration,

Endogenous Technological Change,

Evaluating the Impacts of Human Capital Stocks and Accumulation on Economic Growth: Some New Evidence,

Human capital and technology diffusion,

Increasing Returns and Long-run Growth,

Investment in humans, technological diffusion and economic growth,

On the mechanics of economic development,

Openness, productivity and growth: what do we really know?,

Outward-oriented developing economies really do grow more rapidly: evidence from 95 LCDs, 1976-1985,

The Role of Human Capital in Economic Development: Evidence from Aggregate Cross-Country Data,

Where has all the education gone?, World Bank Policy Research, Working Paper No.

HUMAN CAPITAL AND OPENNESS TO INTERNATIONAL TRADE: EVIDENCE FROM THE ENLARGED EUROPE

http://steconomice.uoradea.ro/anale/volume/2009/v2-economy-and-business-administration/93.pdf

HUMAN CAPITAL AND OPENNESS TO INTERNATIONAL TRADE: EVIDENCE FROM THE ENLARGED EUROPE

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics