Carmela Martín, Carlos Mulas-Granados* and Ismael Sanz
ABSTRACT: This article explores the spatial distribution of regional technology indicators in the EU over the last decade and its impact on cohesion. Thus, we find that public R&D spending and
patent applications have converged among regions during the nineties. On the other hand, private R&D activities have diverged, as a result of an asymmetric expansion during the second half of the
nineties. We show that when the dispersion of public R&D across regions diminished in the second half of the nineties, income disparities at regional level also decreased. Therefore, while
technology policy based on efficiency criteria should remain as a policy tool for economic growth, this policy should be counterbalanced by R&D funds to the least developed regions to maintain
JEL classification: O19, O38, R11.
Key words: Spatial Distribution, EU Technology Policy, economic cohesion, Convergence, Technology Indicators.
The European Union announced in Lisbon 2000 the objective of becoming by 2010 the most competitive knowledge-based economy in the world, and committed itself to undertake all necessary reforms in
national and Community policies to achieve this goal. This strategy was based on the firm conviction that government policy can positively affect the long-run growth rate of the economy through
economic incentives for the accumulation of various forms of capital and through the promotion of technological innovations. Such a conviction relies on the postulates of endogenous growth models
(Romer, 1986 and 1990; Lucas 1988) and has motivated the proliferation of numerous national and European technology programs over the last decades. The idea behind each of these programs is the
following: R&D generates innovation and new technologies, and innovation and new technologies generate then economic growth. This will happen because new technologies increase the productivity of
production factors and therefore have a positive supply side effect on the growth potential of the economy. If this linear R&D—Tech/Innovation—Growth mechanism holds, then economic policy
authorities would be very interested in promoting innovation and technology through strong R&D programs in the first place. Nevertheless, the relative success of these programs in achieving real
innovation, and the relative success of these inventions in effectively generating higher rates of economic growth is still a matter of debate. The question of whether technology policies have really
had any significant role in promoting economic growth or improving economic cohesion, still needs to be answered. Note, however, that the resolution of such research question would imply the
development of a qualitative study based on the description of different policy initiatives which would complicate enormously the attribution of causality relationships between technology
policies and economic performance. Instead, a better strategy is to study the evolution of some important technology indicators (mainly R&D spending and patent applications), assuming that there
exists a connection between technology policies and technology outcomes in terms of R&D spending and patent applications. By doing this, a systematic quantitative analysis can be developed. The
research question could then be reformulated as follows: Have R&D spending and patent applications had any positive or negative effect on economic growth and cohesion? This is the question that
this paper will answer, and in doing so, the article not only wants to contribute to the debate on technology and growth, but also wants to investigate the possible existence of a trade off between
economic growth and economic cohesion mediated by technology policies in general, and by technology indicators in particular. Aware of the likely existence of this trade off, Community policies have
combined until now economic growth initiatives —such as R&D and technology programs— and explicit actions for economic cohesion —mainly through the structural funds— (Peterson and Sharp, 1998 and
Pavitt, 1998). Now that these policies are being questioned in the current debate for the reorganization of European funds and policies it is crucial to link the answer of the research question that
motivates this paper to the possible existence of the mentioned trade off. In order to do this, section 2 studies the spatial distribution of technology indicators over the last decade. Since the
main finding of this section is that regional government R&D spending has converged while total R&D spending has diverged over the last decade, section 3 and section 4 focus on the likely
different effect that these two R&D indicators may have had on economic performance. Therefore, section 3 re-interprets the evolution of these technology indicators vis á vis economic cohesion,
and section 4 replicates the analysis for economic growth. Finally section 5 recapitulates and concludes.
2. Spatial distribution of technology indicators over the last decade
Technology policies are very difficult to measure quantitatively, and therefore their analysis has to rely on a set of technology indicators that approximate different phases of these policies,
assuming that they follow a certain input-output sequence. Following the trend in the specialized literature we use total R&D expenditures by all sectors in % of GDP (TERD) as the best technology
input indicator. The idea that total expenditures in R&D is a good indicator of technological innovation is basically derived from the so-called linear model of innovation, which assumes that
investment in basic research is strongly positively correlated with technological innovation in the market place. Independently of whether this assumption holds or not, this is the best indicator to
have an idea of the resource allocation to R&D in a particular region.
As an indicator of technology output we take the number of patent applications per million people. This is the so-called «inventiveness coefficient» and should be interpreted with care since
Southern European regions are much less inclined to fill in patents for innovative products of processes (European Commission, 1997: 349). In spite of this fact, this is the best indicator to give an
idea of the technology output intensity in a particular region . Finally, because we want to analyze separately if publicly finance policies have a different relative impact than the previous
standard technology indicators, we analyze separately the evolution of government R&D expenditures (GERD), which is in itself a portion of the more general total R&D spending by all sectors .
The use that we make in this section of all these indicators is twofold: first we just describe their spatial and temporal evolution, and then we report the results of a systematic convergence
analysis whereby the common measures of economic and technological convergence are calculated and reported. In this respect, although in the specialized literature there is an open debate on the
relative merits of different convergence measures , the two most popular measures are: the beta-convergence and the sigma-convergence. The former implies that the poor countries (regions) grow faster
than the richer ones and it is generally tested by regressing the growth in per capita GDP on its initial level for a given cross-section of countries (regions). In turn, this beta-convergence covers
two types of convergence: absolute and conditional (on a factor or a set of factors in addition to the initial level of per capita GDP). Under sigma-convergence we mean the reduction of per capita
GDP dispersion within a sample of countries (regions) (see Barro and Sala-i-Martin (1995:11) for further details). We begin with the simplest indicator of all: the absolute beta-convergence index.
Xie, Zou, and Davoodi (1999) elaborate a endogenous growth model based on Barro (1990) and Devarajan, Swaroop, and Zou (1996), where the production function has private capital and different
components of government spending. Assuming a Cobb-Douglas production function, these authors obtain that the growth-maximizing share of a component of government expenditure in total government
expenditures is equal to its elasticity divided by the sum of elasticities of all the components. Following this model, Sanz and Velazquez (2004) show that if output elasticities with respect to each
component of government expenditure are similar across countries and that governments maximize growth, we should expect convergence in the composition of government expenditures among countries.
Thus, as long as the elasticity of growth with respect to public R&D spending is similar across countries, we should expect convergence across public R&D spending in EU countries.
Indeed, Gemmell and Kneller (2002) show that long-run growth elasticity of productive expenditures exhibit a high degree of uniformity across OECD countries. We start with the examination of β
convergence, with the object of evaluating whether regions that have a higher public R&D spending increase (decrease) this percentage to a lesser (greater) extent than regions in which public
R&D spending is lower. We will also adapt this analysis to aggregate R&D spending and patents in order to evaluate whether regions in which aggregate R&D spending and patents are lower
have higher rates of growth. In this way we will be able to compare convergence in public R&D spending with aggregate R&D spending and patents. For this purpose we use the well-known ‘Barro
type regression’: In (TIit) – In (TIi,t–1) = αi + β In (TIi,t–1) + εit 
where: TIt : is the Technology Indicator (patents, R&D, etc.) in year t. i: 205 regions of the EU at the NUTS II level of disaggregation for regional convergence t: all the years in the period
1989-2000 α: regional dummy. β: coefficient reflecting the existence and the speed of convergence. According to this equation, if the coefficient β takes a negative and significant value, there has
been a convergence process in this technology indicator. Also, there would be absolute convergence in two cases: firstly if the GLS estimator is unbiased and hence we do not include any other
variable apart from the previous year’s value as an explanatory variable for the change of rate; and secondly if only the within estimator is unbiased, but we can not reject the hypothesis of country
dummies being equal for all the regions (De la Fuente, 2000). In this case all the regions will converge to the same steady state. Then, because the existence of beta-convergence is a necessary but
not sufficient condition for convergence (Barro and Sala-i-Martin, 1992), we also compute the standard deviation of the logarithm of each technology indicator. In this context, the sigma-convergence
explores if the dispersion among the different measures of technology inputs or outputs among European regions has been reduced. Finally, to complement and illustrate the results provided by the
beta-convergence and sigmaconvergence analyses, we also plot Tukey’s box-and whisker plots for all technology indicators under study. The Tukey’s box-and-whisker plot is a histogram-like method of
displaying data, where the box ends at the quartiles Q1 and Q3, and the statistical median is represented by a line that crosses the box. The farthest points that are not outliers (i.e. that are
within 3/2 times the interquartile range of Q1 and Q3) are connected to the box by the «whiskers», and for every point that is more than 3/2 further away the end of the box, we draw a dot. To put the
previous spatial distribution of total R&D expenditures in context, it is very important to note that statistics at the regional level show the more severe disparities between regions that
remain hidden in statistics at national level. This is specially true for data on technology indicators. For example, disparities in technology input (TERD/GDP) and output (patents per million
people) are as much as 20 and 55 times respectively higher at regional than at the national level. If one looks at the distribution of European regions that invested most in total R&D (as % of
GDP) in 2000, we observe important disparities. Among the regions that invested most we find Braunschweig (7.19%), Stuttgart (4.92%), Oberbayern (4.79%), Pohjois-Suomi (4.73%); Pohjois Suomi (4.73%),
Uusimaa (4.09%) and Tübingen (4.31%). And among the regions that invested least we find Calabria (0.24%), Castilla-la Mancha (0.22%), Sterea (0.18%), Dykiti Makedonia (0.07%) and Notio Aigaio
(0.06%). In 2000, the EU’s average regional R&D spending was 1.22% of GDP with a 1.01 standard deviation. The spatial distribution of patent applications presents more disparities across regions
than the distribution of total R&D expenditures. There are many regions which in 2000 filled out less than 4 patent applications per million people. Among them we find for example, Dessau (3.3),
Andalusia (2.8), Molise (1.9), Galicia (1.5) or Calabria (0.9). On the opposite side, there were many regions which filled out more than 180 applications per million people. These were the cases of
Koln (189.3), Berkshire (197.1), Stockholm (219.7), Noord-Brabant (266.8), Darmstadt (306.6) and Oberbayern (441.95), among others. Such a degree of disparity placed the EU’s average of patent
applications per million people at regional level in 152.8, with a standard deviation of 147.9 in year 2000. It is worth noting that once controlled for the outliers, the regional disparity in
technological development is not so high. This is because patenting activity is Europe is dominated by a small set of regions (an «Archipielago» of ten regions as suggested by Hilpert (1992)), with
all others making only a marginal contribution. When compared to the spatial distributions of the two previous technology indicators, the regional distribution of public R&D (as % of GDP) is less
dispersed. While there is a group of regions with very low levels of public R&D spending that range between 0.01 and the 0.04 of the region’s GDP (Schwaben, Sterea Ellada, Oberfranken, Koblenz,
Rioja and Voralberg), there is another group that spends more public funds in R&D but at a moderate distance (Berlin 1.1%, MidiPyrénées 1.46% and Flevoland 1.87%). In 2000 the average level of
EU’s regional public R&D spending remained at 0.19% of GDP with a standard deviation of 0.27. In view of the situation that technology indicators presented by the end of 2000, the question is now
whether the spatial distribution of these indicators converged, diverged or remained intact along the last decade. In first place, Arellano and Bover (1990) test show that there are significant
individual effects (see tables 1-3). There has been conditional convergence in R&d figures and in patent applications. This overall convergence has been, however, stronger in terms of patent
applications than in total R&D expenditures. As the different coefficients in tables 1-3 show, the same has occurred with government R&D expenditures which have converged at a higher
speed than any other technology indicator. It should be pointed out, however, that the results obtained in column 2 of tables 1-3 may be biased by the ‘country effect’, i.e.: by the fact that
technology is more affected by the development of the country to which regions belong than by the actual features of the region. Consequently, we proceed in two ways to confirm that there has been
regional convergence. First, in equation (3) we estimate convergence for the 205 regions including a dummy for the 15 Member States that takes value 1 if the region belong to a particular country and
0 if otherwise. Thus, we reduce the spatial self-correlation caused by the fact of the regions belonging to the same geographical areas (Armstrong, 1995). In this way, we obtain the results very
similar to column (2) in all the tables. Second, in equation (4) we estimate regional convergence but taking the regional technological indicators in relation to the country average to which each
region belongs. By means of this procedure, similar to that used in Rodríguez-Pose (1996), a very similar estimate to column (2) and (3) is obtained. Hence, from both procedures, it may be verified
that, apart from the ‘country effect’ there is a technological convergent tendency specific of the regions. Furthermore, results corroborate that convergence in public R&D spending is higher than
in aggregate government R&D spending. In fact, the different path of convergence of total and government R&D over the 1990-2000 period intensified during the second half of the nineties up to
a point where regional total R&D expenditures started to diverge. This progressive divergence between both measures of R&D spending probably reflects the impact of the rapid expansion of
private R&D spending as a share of total R&D expenditures. During the second half of the nineties while private R&D investment boosted, public R&D expenditures remained frozen at
constant levels under the influence of general framework of budget stability. The sigma-convergence analysis reports very similar results to those provided by the previous beta-convergence analysis
with only one exception (see figure 1). While both the beta and sigma-convergence analyses point to a convergence in patent applications and public R&D expenditures, particularly strong between
1996 and 2000, the picture for the evolution of total R&D expenditures is more heterogeneous. Apparently there exists beta-convergence and sigma-divergence over time. The existence of beta
convergence would mean that regions with lower shares of total R&D in 1990 have increased their R&D expenditures at higher rates than those regions which started at higher levels. At the same
time, the existence of sigma-divergence would imply that the dispersion from the average share of total R&D spending has increased. Nevertheless, these two results are not incompatible, because
the existence of beta–convergence is a necessary but not a sufficient condition for sigma-convergence (De la Fuente, 2000). Random shocks may have increased temporarily the dispersion of total
R&D expenditures even in the presence of beta-convergence or regions may be approaching their steady state shares (conditional convergence) with higher dispersion than at the beginning of the
period. In addition, evidence of beta-convergence may be reflecting Galton’s fallacy, i.e. the tendency for regions to regress towards the mean (Quah, 1993). Just by looking at figure 1 it is easy to
arrive at a very interesting finding: at the beginning of the nineties the fact of measuring the technological gap using different indicators really made a difference. In 1990, the existing
technological gap measured by the sigma in patent applications (1.6) was twice the technological gap if the indicator to be used was total R&D expenditures (0.8). In 2000 the technological gap
that both indicators measure is much closer, since in that year the sigma for patent applications was 1.6 while the sigma for total R&D expenditures was 1.3. Finally, all the dynamic evolution of
the different distributions under study that was described in previous paragraphs is confirmed again when the three Tukey’s box and whisker figures are plotted. average total R&D spending has
increased along time, as well as its degree of dispersion. However, the average level of public R&D has remained almost constant along the past decade and so has its degree of dispersion (plot
2). Finally, the average number of the log of patent applications has increased slightly in the last decade, while its dispersion diminished specially in 1995 and again in 2000. It is interesting to
analyze the shape of the different Tukey’s box plots because they offer some new information on the sources of the existing disparities in the distribution of each technology indicator. The fact that
dots are above the upper whiskers in the plots for total and public R&D expenditures implies that most regional disparities in R&D expenditures originate in regions that clearly spend
long above the regional average. On the contrary the problem with patent applications is exactly the opposite: there is a significant number of regions that fill in very few patent applications and
are therefore way below the regional average. Interestingly enough, and as we will see in next section , income disparities seem to be somewhat in between and find their roots in the existence of
both very rich and very poor regions. Summing up the results reported until now, the most striking finding that the convergence analysis has provided is the empirical evidence showing that public and
total spending in R&D have followed different dynamics over the last decades. If this different evolution has been translated into a different impact on economic cohesion and growth is the
subject of the two following sections.
3. Spatial distribution of technology indicators vis á vis Economic Cohesion This section turns now, therefore, to explore the relationship between technology policy and economic performance.
Following a logic structure we focus first on the link between the spatial distribution of technology indicators and the spatial distribution of income across European regions (also known as regional
economic cohesion). Before this analysis can proceed it is necessary to briefly describe the evolution of the distribution of regional income per capita during the same period. Since we have
assumed along the paper that there exists economic cohesion when the regional dispersion in GDP per capita diminishes, we want to estimate the relative impact that changes in the regional dispersion
of technology indicators have on the regional dispersion of income per capita. To do so, we estimate the following equation, where all dependent and independent variables are transformed into their
SigmaINCOME = SigmaPATENTS + SigmaTERD + SigmaGERD + ε 
regions in all EU and among regions by country. The influence of public R&D spending on economic cohesion is weaker8 but works in a similar direction. This direct relationship between the
dispersion in all technology indicators and the dispersion in income per capita can be re-interpreted in view of the actual evolution of each indicator along the nineties that was portrayed in
section 2 of this paper . A 10% increase in the dispersion of total R&D expenditures as the one occurred between 1998 and 2000, produced a 0.3% increase in the dispersion of income distribution
across regions in Europe. On the other hand, a 10% decrease in the dispersion of public R&D expenditures as the one occurred between 1993 and 1995 and again between 1997 and 1999 produced each
time a reduction of 0.1% in the income dispersion across regions in Europe. Apparently, the experience of the nineties shows that while the distribution of total R&D spending became more unequal
(led by an unequal expansion of its private component) the only reason why this did not turn into a more unequal distribution of income per capita was due to the compensating effect performed by
public R&D spending and patent applications. As the distribution of patents and public R&D converged, income per capita converged too. Since the only indicator that can be directly affected
by policy-makers is the share of public funds that they dedicate to R&D activities, it looks like the government R&D has been used purposefully and successfully along the nineties to reduce
the economic disparities that other technology indicators promoted. Whether this «cohesive» role played by public R&D expenditures has had any damaging impact on the rate of economic growth of
these regions is a question that remains for the final section.
4. Spatial distribution of technology indicators vis á vis Economic Growth
There is a long tradition of empirical and theoretical studies on the role that technology plays on economic growth. While some recent works have found that economic convergence depends on a set
of factors among which technology is only one of them (Paci, 1997; Dunford and Smith, 2000; Tondl, 2001), others have emphasized the decisive role that technology plays for long run economic
convergence (Fagerberg, Verspagen and Caniels, 1997; Paci and Usai, 2000; and Paci and Pigliaru, 2001)9 . In order to study the relationship between the three technology indicators and economic
growth this final section proceeds as follows: first, we simply study the correlation between the three technology indicators and income per capita. Then, we present the results of a multiple
regression for the impact of technology on economic growth (measured as the annual change in GDP per capita). The correlation analysis provides clear-cut findings. The same occurs with the
correlations between income per capita and total R&D spending (0.4). On the contrary, the correlations between income per capita and public spending in R&D are much weaker (0.15) and
dilute over time. The joint role that all those technology indicators have in explaining economic growth measured by the annual change in income per capita can be discerned by estimating the
∆GDPit = α0 + βo (GDPli,t–1) + β1 (TIfi,t–1) + βg (TIgi *cohesiongi,t–1) + + δt + ωp + øi + εti 
where: ∆GDPit: is the annual change in income per capita β1: is the coefficient reflecting the effect that all technology indicators (patent applications, total R&D spending, and public
R&D spending) have on regional economic growth. βg: is the coefficient reflecting the effect that all technology indicators (patent applications, total R&D spending, and public R&D
spending) have in regional economic growth in cohesion countries (Spain, Greece, Ireland and Portugal). The reason for including an interaction for the group of cohesion countries is that the
relation between technology and growth might be different for different clusters (Clarysse and Muldur, 1999: 4). Clearly cohesion countries share common initial conditions and in this respect they
can be considered as a separate cluster. δt : is the time dummy; øi : is the region dummy; ωp: is the country dummy. Note that growth might influence R&D spending decisions of both the business
sector and the government. Growth increases government revenues, which in turn would raise the resources allocated to R&D spending. Companies in countries recording high growth rates may also
devote more funds to R&D activities. For this reason, we introduce the lag values of the independent variables. In fact, regression (3) resembles the Beck and Katz´s dynamic model (1995, 1996 and
2005). Indeed, estimating equation (3) yields the same results as estimating GDP on its lagged value and independent variables. Thus, we are capturing long-term relationship between GDP and patents,
aggregate R&D spending and government R&D spending. Moreover, endogeinity is not an issue anymore, as long as there is not first order autocorrelation in the error term (Beck and Katz, 1996).
In the absence of first order autocorrelation, the error term will not be correlated with independent variables. Furthermore, Beck and Katz (1996) claim that «If the errors show serial correlation in
the presence of a lagged dependent variable, the standard estimation strategy is instrumental variables. While this has fine asymptotic properties, it may perform very poorly in practical research
situations (...) Thus it may well be the case that it is better to estimate with OLS, even in the presence of a small, but statistically significant, level of residual serial correlation of the
errors». This is our case, The Lagrange Multiplier test shows that lagged residuals are marginally significant in predicting residuals from equation (3). Therefore, equation (3) is estimated through
GLS with robust standard errors. Results are reported in table. As can be observed, real convergence is once again confirmed: the lower the existing regional income per capita in t-1, the higher the
subsequent economic growth. In addition, the contribution of patent applications in t-1 to subsequent economic growth in year t is very positive. An increase of 1% in patent applications produces an
increase in regional economic growth of 0.017. However, this effect is not so strong for cohesion countries. This can be interpreted as follows: where the stock of patents is very low, one additional
patent is not sufficient to start economic growth. Instead, the innovative effort required to produce an isolated patent could diverting resources from more productive activities. More importantly,
the role of total R&D expenditures is also strongly positive for all countries (including cohesion ones). The crucial impact of total R&D for economic growth is somewhat at odds with the
insignificant effect that public R&D spending has on economic performance. However, this weak (even negative) short run impact of public R&D on economic growth, turns into a very strong and
positive influence in the medium run. An increase of 1% in public R&D spending today is likely to increase the rate of growth by 0.04% in four years from now12. This 4-years lagged positive
effect of public R&D on economic growth holds also for cohesion countries, what is very important given the fact that public R&D spending has to compensate for the low presence of private
R&D initiatives in these regions.
Conclusion The study of the evolution that the distribution of regional technology indicators has experienced over the last decade has provided some clear and important findings which can be very
useful to inform future economic policy debates in the EU. First of all, some technology indicators have converged among regions during the nineties (especially public R&D spending), and this has
ran parallel to a real (though softer) convergence in income per capita levels. On the contrary total R&D expenditures have diverged across regions over time, as a result of an asymmetric
expansion of private R&D activities during the second half of the nineties. Secondly, we have seen that total R&D spending increases economic growth, especially if this R&D activity is
quickly transformed into new patent applications. Since innovation is the real key for economic growth, only when efficient total R&D allocations are easily transformed into new patent
applications, economic performance improves. This positive effect on growth is not exclusive of total R&D expenditures, but also applies with a 4-year delay to public R&D initiatives. Finally
and most importantly, in addition to this lagged positive effect on growth,government R&D spending has also demonstrated to be closely associated to regional economic cohesion in the short and
medium run. When the dispersion of public R&D across regions diminished in the second half of the nineties, income disparities at regional level also decreased. Therefore, while technology policy
based on pure excellence and efficiency criteria should remain as a policy tool for economic growth, this policy should be counterbalanced by European and regional policies which transfer funds to
the least developed regions to maintain a minimum degree of economic cohesion. The results shown in this paper clearly demonstrate that if the current winds of reform succeed in curtailing the public
financing of technology policies, the degree of regional polarization in the EU will most likely increase in the future.
Since the late eighties have been many political scientists, economists and sociologists have discussed the feasibility future of the welfare state. The risks for that viability
came from the diffi culties of funding which would face countries wishing to maintain and
increase their benefits in a context of strong international competition in the markets for goods and services, free capital mobility and aging progressive
population. Political leaders have followed this debate in the distance, until the beginning of thiscentury. For the first time in 2000, in the launching of the Strategy Lisbon in
Europe to this area the world's most competitive leaders European addressed this issue. His position then he was optimistic, and bowed to send a message of
sustainability European social model (all versions) perfectly compatible with reforms economic they would be addressed
to travel to what was then called as "knowledge society".
In 2005, European leaders again to meet at Hampton Court (UK) and their conclusion was not as positive. They had past five years, the necessary reforms they had just undertaken,
and the global horizon appeared competitors each time more potent between economies emerging. This time the message It was more nuanced. Welfare states Europeans would be
sustainable only in the If that converge towards an intermediate point among the broad benefits Scandinavian model and concise model Anglo. In all cases, the question It
would not be size but operating logic. The European social model should reform to make the state Wellness in a more active agent, more focused on the individual to the
collective, enhancing their skills and nonjudgmental between public and private, focused in the provision of quality public services to do consistent effi ciency and equity
to aspiring societies European.
The challenge is huge, and barely They have taken the first steps. This article theoretical advances in the defi nition this new dynamic state, and analyzes the
degree to which it has been implemented in Spain.
The following section clarifi es the debate around policies that constitute what
It has been called in the literature as "Pillars of welfare." Section 3 is stops at the new pillars of the State Wellness. Section 4 defi ne the State dynamic, and Section 5
examines your application in Spain. Section 6 concludes Article.
2. the traditional pillars WELFARE STATE
Numerous studies have endeavored to differentiate welfare models advanced democracies. From work Esping-Andersen (1990) to the most recent Sapir (2006), the typologies
are based on the degree of effi ciency and equity They are generating different models, and the intervention level of the sector public economy, and the type of
relationships labor force in each model. TO Despite all the national differences
that can be observed between different welfare models, a number of features common to all of them, allowing identification of the essence of the welfare state, a system of public
hedging unwilling to which the citizen it is checked.
2.1. Traditional risks
The three risks traditionally hascovered the welfare state are those preventing human beings use their strength work, the only way of life that has and it
makes it self-suffi cient, and therefore free, the risk of falling ill, losing employment, and the "aging",
understood as the uncertainty of the moment the aging undermine defi nitely intellectual or physical capabilities own in which the activity is based labor. If these
risks had not been covered publicly by insurance health, unemployment insurance and
pension system, people who suffer the realization of any of these risks would be relegated to exclusion and to marginalization.
The coverage of these three risks justified the public sector birth and consolidation of the welfare state during the last century, and they constitute three first pillars, which
came to add, then a fourth pillar to cover the risk birth or becoming disabled.
In this group of pillars of State Wellness is usually included mistakenly Education, however, sense strict, public provision of a universal education has nothing to do with
no risk coverage, but with a preference for equality of opportunity, characteristic of progressive thinking.
From this view, inequality social differences are not due to background insurmountable between individuals, as claimed by the conservative thought, but a related social
family, intellectual and educational environment in which we grow, so they can be
herefore, and from this perspective,
Welfare state could metaphorically defi ne
as an entire building, with educational foundations and four pillars that full realization of the potential of each citizen is located, as these pillars cover public sector occupational
risks which all are exposed involuntarily.
2.2. Public coverage of risks
Public coverage of those risks and involuntary are two important issues which should explain, above all, in view of the volume of public expenditure generated. European countries
spend a average of 23.4% of GDP in fi nance traditional pillars of the welfare state, especially in health and pensions (and arrive
almost 30%, if we include educational expenses). Given the amount of resources used,
There is a first question to answer: Why should be public universal coverage
these risks? A priori seem logical that the risks of being unemployed, sick, grow old or become disabled could be covered by insurance through private mechanisms market, like
car insurance us It covers involuntary risk of having an accident. However, apart from the connotations they all share moral, these four face risks to market failures that
make your Private coverage is not profitable for companies in the case of certain social groups, which therefore would be unprotected, as in countries like the United US
(where 15% of the population He has health insurance).
Each pillar of the welfare state responds to a specific market failure:
- Health: the classic failure that is often mentioned here is the
adverse selection, leading to private insurance to ensure only people with good health coverage and would leave (or prohibitive premiums) citizens with chronic diseases. In addition, there
problems of natural monopoly (be tech health vices which by their size are too expensive and complex for the private sector). And of course, there are problems for the negative externalities on
public health of the community (in the case of epidemics), of which the State can only deal.
- Unemployment: market failures
justify public provision of unemployment insurance are similar to those of health. On the one hand there is also a potential problem of adverse selection, if insurance were private; and on the other
there is an added problem of restriction of credit, a credit is needed when the information is incomplete and needs some time to find the right job. Finally, the negative externalities that can cause
work stoppage resulted in poverty, are more than evident.
- Pensions and dependence: in both cases, the selection problems
adverse are very relevant, especially in the second, because when disability occurs and is maintained with a certain probability over time, private insurance market expel citizens with permanent
Also, both the elderly as the dependency
They require constant care, usually made by family members, who are deprived of leading a fully active life, with the negative consequences that this causes them and the whole of society.
- Education: in the case of basic education dedicated to ensuring the
equal opportunities, the risk must be ensured (to be born in
a family without resources), requires action for which there is not even
a market. Add to that an initial problem of credit restrictions,
since no private insurance education credits granted until the child had shown good ability to generate future income to pay back the loan. So education loans for university studies exist only
because in the early stages of education, that role is exercised by the State. And finally, we must again mention the negative externalities of political and economic nature whereby illiterate
societies without democratic culture and unable to accumulate human capital.
In summary, there are market failures that generate collective neglected if we limit private insurance coverage, and it is our collective preference for the universality of what that
coverage necessary that such insurance be public.
Now, another important question to be answered is: why must be covered only those four involuntary risks ?, Why not expand the welfare state to protect people against other risks willingly
assumed? The answer is obvious: if the State cover risks that can be avoided, then everyone would take more risks than usual and the price system and incentives it would break our economies. That is
the reason why there is no public insurance to cover any debts of citizens who risk their savings in the stock market, or for those who lose their homes to have contracted variable rate mortgages
when they could have secured themselves contracting a fixed rate mortgage.
In fact, the possible attribution of responsibility to the individual to an unfavorable situation marks a limit to the degree of coverage
the welfare state, so no incentives to fraud entering the
sociales1 performance. And in those countries where it has not been respected that limit, welfare states have become unsustainable, inefficient and have produced a public disaffection for the
3. THE NEW PILLARS AND NEW WELFARE STATE POLICIES
3.1. New risks
For at least a decade the traditional welfare state, with its foundations and its four pillars, is facing new social risks (such as the multiplication of entries and exits from the labor market that
young people face, or obsolescence production capacity and long-term unemployment experienced by older), as well as new realities that generate new requirements (such as an aging population,
proliferation of single-parent households, or definitive incorporation of women into the labor market) 2. The ability to meet these new needs and addressing emerging social risks is, however,
constrained by the process of economic globalization
(Which tends to make countries less competitive with welfare states
more rigid and bulky) and by ankylosing
These incentives are given when an individual has secured a perceived social benefit, regardless of the reasons that allowed him
be in a position to perceive. For example, receive unemployment benefits regardless of whether one forced the dismissal, or if you are doing everything
possible to find a new job, it can produce distortions which require a change in the rules and control methods for these benefits. 2 For an analysis of new risks affecting European societies, and
Lerais see Liddle (2006). cessing of some traditional public institutions.
3.2. Are new policies or nuevospilares?
Both simultaneously with the emergence of new social risks have two options: take the opportunity to go liquidating the traditional welfare state, or reform it so that it remains a valid instrument
for reducing inequalities and economic growth instrument.
In the reform of welfare states must coexist, in turn, two simultaneous processes: on the one hand, the policies associated with the traditional pillars of the welfare system (education,
pensions, unemployment and disability) must be transformed to cover new areas and to become more agile and dynamic. And secondly, new pillars should be developed in areas where so far
there was no coverage. Examples of adaptation of the pillars
Numerous traditional. For example, globalization and technological change have forced educational systems
modify their curricula and teaching methods to enable students to cope with constant change.
Other changes related to globalization, such as increasing the
mobility of people and the extent of migration, have also affected education systems and health systems. The latter have been heavily impacted by the progressive aging of the population in advanced
democracies, which has led it to tilt its traditional emphasis on healing towards more policy based on disease prevention. Also, exposure of our societies to new
rapid spread of global pandemics, because of the growing
global mobility of people, is requiring additional health coordination efforts, until recently unthinkable. Adaptation efforts are also being developed in distinctly new as those related to diseases
caused by climate change areas.
While these changes in the education or health are important, so far the most important adaptations to boost the traditional pillars of the welfare policies have taken place in the labor market area.
The best known are the policies of the Welfare to Work (consisting of cutting taxes or contributions to companies that hire long-term unemployed) and the Make Work Pay (who advance loans to start new
actividadesy recycle knowledge, in order to do more attractive work to collect a subsidy). In the business area they have also taken these experiences. For example, all policies
promotion of micro, self-employment, reinstatement of women and older, and to reconcile work and personal life, share the same spirit. Also supporting innovative SMEs, funds
venture capital and financing for entrepreneurs have a dynamic character; as well as policies to encourage exceedances
business training, and programs to study and work in the
universities. Alongside this effort to adapt the pillars
traditional welfare to new social risks have emerged piecemeal politics, but that gradually could be gaining consistency and confi gure a new pillar of the welfare state.
This new pillar would come to cover a new risk, entrapment to constant change, being unable to adapt to the unstable economic and social dynamics brought about by globalization, technological change
and renewal of traditional social values.
Every day there are more people who have many different jobs during his career, which do not focus their life around a stable family unit, that have changed the stable circle of friends, by bilateral
relationships that change with time, living in different countries and traveling as usual. These people have gone from being considered "elite" of the advanced societies are now increasingly large
parts of the global middle class. And in that situation, these people are exposed to new risks of being caught in one of these processes of change: the risk of inability to find a new job more; the
risk of being isolated and psychologically affected by the absence of family or friendly ties, especially at older ages; the risk of
to bring up a child without the help of a partner; or the risk of not being able to emancipate themselves despite being a young man with good training.
Social policies dedicated to helping single parents, to the emancipation of young people, the elderly at risk of exclusion or long-term unemployed increasingly absorb more resources and focus the
attention of media and electoral European societies. These are policies that until recently did not exist or were on the margins of their welfare systems and they are gaining importance
through of rental assistance programs, basic income of emancipation, training throughout life, and even new socialization activities aimed at the most diverse groups.
If we group all these risk-based initiatives that aim to cover (The entrapment before the change), and in accordance with the common recipe that relates (that of providing or equipping
training, economically and socially to people affected by the risk) then it is safe to afi rm that this is a new pillar of the welfare state. A pillar to the static entrapment seeks reinstatement
dynamic people in social and productive wheel as the only guarantee of the full exercise of individual freedom in a context in permanent change.
Therefore, in the new social risk welfare states they are undergoing two simultaneous transformations: first are adapting and streamlining its traditional pillars; and on the other they are
developing new policies that will also form a new pillar of the welfare: fifth pillar, the pillar of emancipation, or social reinclusion in situations of
entrapment. And these efforts are being reflected in the data and public spending on new social policies. Related policies
with the renewal of the traditional pillars (such as active employment policies) or the development of new pillars (such as policies to support the family, housing and other social benefits) and
represent both public spending as any of the old pillars.
4. THE WELFARE STATE TO Dynamic State
4.1. A new operating logic
In addition to the new social risks for citizens mentioned in the previous section, globalization and the ongoing economic change they have forced the State traditional welfare to undertake a kind
of reforms that have nothing to do with its size but its operating logic and the new type of programs that are launched in those pillars that each country has decided to keep. In fact, countries with
more developed welfare states, Scandinavia, reformed their models in the nineties, introducing the same logic as the British Labour Party that had
a welfare state of half the size. In both cases, reforms States are getting more agile and modern well, with similar results in terms of efficiency and competitiveness, although with different
results in terms of equality, for the first
The logic of I'm talking about is the logic of dynamic state, which will define below. The Dynamic State is a new kind of welfare state in which there were two simultaneous transformations:
- A change in the means and procedures: it is a State
internally dynamic in its administrative operations, and externally
dynamic in their relationship with other economic and social agents.
- A change in the end: the ultimate goal is a state of dynamic citizens (active) in which equal opportunity is ensured
as the only means for the full exercise of individual freedom with which
every citizen can develop according to their expectations and imagination.
This state of active citizens combine them social protection and revitalizing an active participation of these citizens
the economy and society.
Following this logic, the Dynamic State could be characterized by preventing and anticipating new risks and social demands (rather than simply reacting when risks of unemployment, sickness or
disability have already materialized).
Also, the dynamic state is a catalyst for economic and social change;
it is based on participation and avación citizens (rather than EC ned to compensation and protection of their income); commitment to social investment in education and training of their citizens at
all stages of life; It promotes creativity and self-improvement of the economic and social players, and above all, mobilize all social resources inactive the young, women and the elderly to become
economically and socially useful citizens (versus traditional welfare state
I was passive, discouraged work and generated a grant dependent groups). To achieve its objectives, the Dynamic State
and responsible citizens need to be involved, through their policies promote inclusion and social mobility, and ensure self sustainability
welfare model in the new context mentioned.
In addition, the Dynamic State adopts new functions that the welfare state does not fully covered, such as encouraging the creation of new markets and the proper functioning of the same in terms of
access and competition. Private investors also coordinates activities, promote strategic sectors and helps consolidate sectoral competitive advantages.
Finally, the logic is essential in revitalizing the new relationship that the administration of this new State must establish with citizens: information transparency initiatives, advertising and
public calls data, eliminating duplication between different levels of government, and use and promotion of e-government or electronic license are measured characteristics for such a
4.2. A new logic of financing
Processes such as globalization, changing demográfi co and technology have not only led to new risks for citizens to be covered by policies refurbished or brand new, but have also generated strong
upward pressure on social spending, and a cap the tax burden that can withstand the productive factors. So, with this new logic of internal and external performance, the transformation of the welfare
state in a dynamic state has also involved a new logic of funding.
To understand this new logic, I will use a nearby example, the Spanish case. Suppose a newly elected government wants to launch new social programs demanded by citizens, to address some of the new
social risks (eg, new policies dependency in Spain). Then you have four alternatives, which classifi Care in Spanish depending on the experience in the process of consolidation of the welfare
First, the choice of the first governments of Gonzalez: increase public spending (led by the first development of the welfare state) to a higher growth rate of government revenue, thus incurring a
situation of defi cit, which had an average growth (in cílicamente adjusted terms) of 4.7% during the 13 years of his government.
Moreover, public investment in terms of public spending clearly had not tax investment effort in the previous period Second, the choice of the governments of Aznar: lower taxes, maintain steady
income and reduce investment pubic until 2020. The approach was done about it is that the public sector invests in physical capital (mainly
infrastructure) because they improve the productivity and competitiveness of the productive private sector. So these investments have multiplier effects
on the economy permanent character, because they increase the efficiency of production factors. Specifically, increasing the overall productivity factor
enables consumers have greater resources, raising consumer demand, and companies raise their competitiveness, so they sell and export more. This increase in demand has to be satisfied with domestic
and imported production there is to hire more workers and expand the stock of productive capital. If demand increases less than supply, this means a reduction in inflation.
Given the hypothesis that for each additional point increase in public physical capital increases 0.1% in productivity, product potential of the economy would end ranking in 2012, 1.1 percentage
points above the situation he will not run the PEIT full. For his part, Observed GDP does on a smaller scale, and that takes some time until the increase in potential output is fully
incorporated by agents in their expectations. Thus, again reduced infl ation.
In any case, to meet increased demand would require that employment increased by around 84,000 new jobs (these jobs would be in addition to those directly involved in the construction of
infrastructures, which are incorporated in the baseline scenario)
bringing the unemployment rate would be reduced by two tenths.
Improved technological capital like infrastructure development, the socialist government justified the importance of this type of investment because it significantly increases the productivity of the
factors of the economy. Thus, the mechanisms by which transmit
multiplier effects are the same as in that case, although there is no direct effect on investment in construction did have investment in physical capital.
Elasticity of productivity by technological capital stock by 10% over the medium term was used to calibrate this purpose, in addition, it is assumed that there are small drag effects on investment in
R + D + i private. The level of long-term production of the economy would increase by 0.61 percentage points in 2012, while demand would in just 0.36 points
percentage. As a result, inflation would decline slightly, and 63,000 additional jobs, bringing the unemployment rate would fall by two tenths from the central scenario would be generated.
5.2. The dynamic effects of the care system
Investment in physical and technological capital have been part of a strategy in which economic modernization pursued to face the biggest challenge has been addressed in Spain in recent
decades relation to its welfare state. This challenge has been to recognize a universal right to care for dependent persons, through the implementation of a new national system. Other European
countries had covered the risk of being or becoming disabled / dependent, but in Spain only he has been treated in some communities Autonomous and always very limited3 way. The initial
design was very important, and 3 According to the White Paper on Dependency, until 2005 the attention of Administrations is paid from the health system and from the field of social services with a
clearly insufficient coverage and with significant differences between regions and between urban and rural areas. In Spain, only 3.14% of the elderly in a context of progressive aging of the Spanish
population and potentially increasing demands recognition the right to universal care could assume an unsustainable burden on public budgets in the long term. By Therefore, the introduction
of this new pillar was made from a philosophy and activating the services copayment and a design intended
generate direct jobs and free the family to rejoin the profession, provide the system designed a dynamic profi le that differentiate it from other similar in Europe.
The Law of Personal Autonomy and Care Unit was approved in 2006 and established a new right of citizenship ensuring care and care for dependent persons (the elderly and people with severe
disabilities). According to This Act, which is still developing, the state will guarantee people access is not fend for themselves to social services according to their degree of dependence
and Nive. The National System for Dependency will prioritize the provision of services (Home care, day centers, Telecare, technical assistance, residential places, etc.). In cases where it was
not possible, the benefi ciaries will receive financial benefit linked to the hiring of a service in the private market. Family caregivers may receive an allowance and be incorporated into the Social
The approved text provided for a gradual deployment of the system, first to attend dependent people with disabilities serious (those necesitanres 65 years had a home help service, telecare 2.05%
and 0.46% with a place in a day center. help to perform basic activities daily life as getting out of bed, bathing, eating, etc.). In Spain, according to data of the White Paper on Dependency,
it is estimated that more than 1,125,000 people reside who have severe and severe dependence. Until the entry into force of the Act, the care for these people was carried out, especially in the
family and especially lay women (representing 83% of family caregivers) who, in most cases, They saw unable to conduct activity some work. The financing system was designed so that there is a
funding equal parts of the General Administration State, Autonomous Communities and, where appropriate, of the local governments.
The goal is to spend 0.33% of GDP today that WILL dedicated to dependency more than 1% in 2015; for this, and according to the report of the law, the Central Government would provide more than
euros until 2015 to ensure the benefits and services of the new National System for Dependency. Forecast cost in the first eight years for the central government is broken down in Table 6. Law
No. stressed that in addition to the social benefits, create Spain's National Dependency System would effi cient investment for their social, economic and employment impact. In fact, according
to the White Paper on Dependency and FEDEA report in 2015 they will have been created about 300,000 jobs and the effects on
GDP of our economy could be up to 1.56% in 2010, which in turn imply a differential in cumulative annual real rate of growth of more than 0.28% over the entire period.
Also, the overall tax return, by general taxes and contributions, would cover up to two thirds of the costs associated with the deployment of the National Unit.
5.3. The dynamic effects of globalization of the first cycle of infant education (0-3 years)
Both in the 2004 elections, as in the 2008 elections, the Socialist Party promised universal junior kindergarten. If during his first term in office he delayed this development to the implementation
of the System of Care Unit at
beginning of the second term is publicly committed to develop by 2012.
According to the description of this initiative, 75% of the cost of each of the positions created childhood education (estimated at 5,000 euros per square) would be financed by the Public
Administration and the rest (25%) parents. As a result, this measure immediately imply an increase in government consumption (to hire educators) and construction investment (to raise
As in the case of dependency, this would have a clear multiplier effect on the economy by raising participation women in the labor market. Specifically, according to the LFS 2007, the
probability that a mother had children under 3 years (and partner) to participate in the labor market was 60.8%, well below the which has a similar woman
but without children (84.4%). It is estimated that the creation of a national network of nursery schools would at least halve the gap between the two probabilities. This would be a greater supply of
labor would increase the productive potential of the economy. In addition, building schools and hiring of teachers would increase disposable income of households and private consumption. If the
latter increased demand was lower than the production potential, a decrease of inflationary pressures would be recorded. According to the quantitative estimates economic report published by the
Socialist Party before the 2008 elections, the creation of 300,000 new jobs childhood education allow a minimum of 70,000 more women entering the market work. As a result, the economy's potential
product in 2012 would be 0.35% higher than expected. For its part, the increased demand in 2012 would be slightly lower, so prices
They are reduced. Finally, to meet the increased demand at least 58,000 more jobs would be generated, and the unemployment rate would not be affected.
In view of the evidence presented, it is possible affi rm that Spain is taking the first steps in a complex process, in which at the same time it intends to extend the benefits of the welfare state,
try to make it more dynamic in all its aspects. The most important actions
described they have been complemented by initiatives in housing
rent, scholarships for young people, promoting birth, or work part time.
In Spain this line can still delve into the dynamic state through a fifth pillar to deal with a new cover and fifth involuntary risk, the risk of getting trapped socially. When the economy was not as
globalized and personal and business mobility were limited,
staying in the same job and the socio immobility were part of everyday reality. Today, the assurance professionals face multiple rotations throughout life, combined with less stable family patterns
and accelerated geographical mobility of individuals. This world in which the individual gains presence at the expense of the class, the union and the family, and the changes are permanent creates a
risk that is to be caught in one of those transitions.
As in the four traditional pillars, the state must play a role to cover this risk through programs
to reconsider and reimpulsen the individual to the next stage. In Spain, the fifth pillar should focus primarily on promoting emancipation
models and economic independence groups now find it more difficult to obtain, since the emancipation generate productivity gains for the whole economy, would pay for the additional public services
required, and make it more equal and more free
very important sectors of society. These groups are mainly made up of young people who become independent at a very late age for difficult access to housing and purchasing the limited power of their
wages, who go abroad and speak languages for lack of means, they can not combine training permanent employment, and who find it difficult to have children and keep your career, not to find free
nursery schools, home help or extracurricular activities for their children. This risk of entrapment especially affects women in any age group, when separated, or when they are forced to choose
between their family and professional life.
In all cases, new utilities and a commitment to training throughout life, could solve most of the problems. In short, with or without fifth pillar, the transformation of the State
traditional welfare in a dynamic state has only taken a few steps, but his consolidation a be crucial for the modernization
our social model and to its future economic viability.
ESPING-ANDERSEN, G. (1990): The Three Worlds of Welfare Capitalism, Princeton University Press, Princeton.
IMSERSO (2005): Libro Blanco de la atención a las personas en situación de dependencia en España, Instituto de Mayores y Servicios Sociales, Ministerio de Trabajo y Asuntos Sociales, Madrid.
LABEAGA AZCONA, J. M., SOSVILLA RIVERO, S., ORTEGA MASAGUÉ, A. C. Y HERCE, J. A. (2006): «El Sistema Nacional de Dependencia: evaluación de sus efectos sobre el empleo», Revista del Ministerio de
Trabajo y Asuntos Sociales, 60: 167-198.
LIDDLE, R. Y LERAIS, F. (2006): «Europe’s Social Reality. A Consultation Paper from the Bureau of Economic Policy Advisors», Comisión Europea, Bruselas.
MULAS-GRANADOS, C. (2009): El Estado Dinamizador: nuevas políticas de bienestar en Europa. Madrid:
Editorial Complutense, Colección ICEI, 468.
SAPIR, A. (2006): «Globalization and the Reform of the European Social Models», Journal of Common Market Studies, 44: 369-390.
Carlos Mulas-Granados. Professor of Applied Economics at the Complutense University
In the last five years, concern about rising income inequality has been at the center of economic policy debates. However, there is an area that has been
relatively unexplored. This is the area that deals with the relationship between labor share of income and personal income inequality. Income inequality refers to personal income distribution and the
share of labor refers to the compensation of employees in total factor income (value added) in a given year. When you look at these two series, the visual impact is stunning. For example, between
1970 and 2012 the share of work in the G-7 was reduced on average by 12 percent, while income inequality increased by 25 percent.
The share analysis of the factors (labor and capital) of national income was considered the main problem of the political economy of the classical economists such as David Ricardo. Until the
1960s, this issue was given great prominence in the economic textbooks and academic research. When Kaldor these famous words summed up the properties long-term economic growth in the 1960s, he said
the actions of national income received by labor and capital were more or less constant over long periods of time. The analysis of the factor income shares was subject to a ninety percent of
scientific papers presented at the conference of the International Economic Association in 1965. The dominant theme was that the shares of the factors were important for macroeconomic performance
economies, as they were related to the potential problem of declining profits and real wages grow above productivity.
However, since the 1970s, the share analysis of the factors is no longer at the center of economic debates, given its lack of volatility and reflects the fact that the division of revenues could
easily be explained by a production function of Cobb-Douglas. People concerned about the distribution of personal incomes began to insist that there was a direct (or mechanical) link between the
factors of shares and inequality, and that differences in personal income were related to differences in the level of training .
Citizens do not enjoy economic expansion
In addition, a broader spectrum of everyone was starting to enjoy some kind of capital income. While home ownership, financial holdings and assets funded pension capital expanded in advanced
economies between 1970 and 1990, the division into workers (pure) receive only wages and capitalists / owners (pure) receiving only benefits / income were blurred, contributing to the decline in the
attention paid to this issue.
However, interest in the analysis of factor shares back in the 2000s In 2009, Atkinson cited three reasons for this renewed attention: first, the share analysis of the factors was useful to
understand the relationship between income at the macroeconomic level (national accounts) and income at the individual / household level; Second, the share of factors could potentially help explain
the inequality in personal income (at least in part, if certain types of income are mainly received by some type of economic agents); and last but not least, they went to the concern for social
justice with impartiality of the different sources of income.
Initially, researchers who returned to work in this area focused on explaining changes in the share of labor, its gradual but steady decline and the relationship between wages and productivity.
The perception that the citizens were not fully enjoying the fruits of the long period of economic expansion of the late 1990s and early 2000s also attracted the attention of national policy makers
and international organizations.
In 2006, Ben Bernanke, Fed chairman expressed the hope that "companies would use some of those profit margins to meet the demands of workers for higher wages" and in 2007, the German Finance
Minister asked the European companies "give a more equitable share of the increased profits." The IMF, the European Commission, the Bank for International Settlements and the OECD all reports
published in the mid-2000s that documented the declining share of labor income and provide several explanations for this trend, primarily related to the impact of globalization and technological
change in labor skills, international mobility of capital and wage bargaining. Interest in this area returned after the financial crisis, as the decline of the labor share of income and the sharp
increase in the inequality of personal income would parallel and this led many analysts to think that they were strongly correlated.
Support inclusive growth
But the truth is that, although apparently are correlated, the declining share of labor income and increasing inequality in personal incomes are not directly linked in a causal relationship. In a
recent study entitled "The functional distribution of income and their role in explaining inequality" I've co-written with Maura Franzese, that and will be published by the IMF, we check whether the
decrease in the share of labor income has been a key factor driving the growing inequality. We concluded that it was not a key factor. Instead, the most important in increasing income inequality has
been increasing determining wage dispersion, especially at the top of the wage distribution.
Using a single database, which combines household surveys and economic data from 81 countries over four decades, it shows that the most important determinant of rising income inequality has not
been the declining share of revenues that accumulate work, but the increasing dispersion of wages in labor income. This reflects the fact that most of the family income is labor income. It is also
due to the high salaries have grown tremendously and wage dispersion has become a driving force behind income inequality. It was also found that the increase in wage dispersion has been associated
with the growing financial globalization, a decline of unions in the industry and a decrease in the size of the state administration.
From a policy perspective, our results suggest that to avoid adverse (or undesirable) distributional consequences, authorities will have to pay attention to the results of the labor market and
wage dispersion, including induced distortions in the labor market by different policy interventions, or by changes in labor market institutions. In addition, the tax and transfer policies should be
properly assessed in terms of their cost and relative effectiveness in correcting income inequalities and minimize market distortions. Finally, public policies that support inclusive growth (for
example by promoting participation in the labor market and strengthening the human capital of low-income groups) should be strengthened to avoid increasing economic disparities.
#Carlos Mulas-Granados. Professor of Applied Economics at the Complutense University * currently works as a consultant in the Department of the International Monetary Fund Public Finance. He holds
a doctorate in economics from Cambridge University and a Masters in International Affairs from Columbia University.