Carlos Mulas
Carlos Mulas 

Carlos Mulas, artículos

Carlos Mulas - Granados

Fiscal adjustment and growth: Beware of the credit constraints

Emanuele Baldacci, Sanjeev Gupta, Carlos Mulas-Granados 31 March 2014

The recent debate on the link between austerity and growth has focused on the short run. This column discusses recent research into the link between fiscal consolidation and medium-term growth under different financial conditions. If credit is not available to consumers and investors, private demand is less able to compensate for cutbacks in public demand, so large spending cuts can have a negative effect on growth. Difficult financial conditions probably explain why fiscal adjustments that worked in the 1990s have not produced similar beneficial effects on growth in recent years.

In the aftermath of the recent financial crisis, the discussion of the effects of fiscal adjustment on economic growth has intensified. While some scholars have focused on the characteristics of the fiscal consolidation needed to bring public debt down from historically high levels, others have examined the effects of alternative strategies on economic performance. The VoxEU debate aptly covered in “Has Austerity Gone Too Far?” (Corsetti 2012) sums up the conflicting positions. Most scholars have delved into different dimensions of fiscal adjustments, including their timing, composition, and duration. The empirical analysis of the growth effects of these policies, however, has largely concentrated on the short run. This has left unanswered the question of how fiscal consolidations affect growth over the longer term.

In our view, important insights are gained from taking a medium-term perspective of fiscal adjustment and its effects on growth. In particular, the composition of fiscal adjustment, and its interaction with initial and accompanying conditions, has important consequences for economic activity. Monetary policy, exchange rates, and financial conditions are important factors shaping the medium-term effects of fiscal consolidations on economic performance (see Cottarelli 2012 and Buti 2014).

In this context, we would like to draw attention to another dimension – the interplay of credit constraints, the composition of fiscal adjustment, and growth. This is particularly relevant in the current environment, where the legacy of the financial crisis has constrained credit supply and affected the channels through which fiscal policy impacts growth.

Debt-reduction episodes under different financial conditions

In a recent paper (Baldacci et al. 2013), we show that there is a link between fiscal adjustment and medium-term output growth in the presence of credit constraints. We use a database of 79 debt-reduction episodes achieved by means of fiscal adjustment, covering advanced, emerging, and developing economies between 1980 and 2012. In particular, we focus on the relationship between the quality of adjustment (measured by the relative contribution of cuts in current spending to total deficit reduction) and average economic growth in the medium term. In this context, we define the medium term as the five years after the debt-reduction episode has ended. The relationship between the quality of adjustment and medium-term growth is weakly positive under normal conditions in our sample. However, this relationship becomes negative when credit constraints and bank deleveraging conditions are taken into account.

A shortage of credit and impaired financial channels can damage growth, while spillovers of risks from the financial sector to sovereign debt markets can affect public debt sustainability. While these figures are only illustrative, in the paper we perform a robust empirical analysis in which we interact traditional variables that measure the size and the composition of fiscal adjustments with indicators that measure the relative health of the financial sector. In particular, we focus on two financial variables: the growth of credit to the private sector and bank deleveraging, with the latter measured by the change in the capital-to-assets ratio.

We find that if credit is not available to consumers and investors, private demand has more difficulties in compensating for cutbacks in public demand. As a consequence, strong spending cuts can have a negative effect on medium-term output growth; this impact is larger than in traditional models that do not take credit constraints into account. When countries start the adjustment with high unemployment, the negative effect of spending cuts on growth is even more acute.

The combination of low credit growth, bank deleveraging, and public debt consolidation can change the way economic agents assess the effects of government policies. In particular, the fiscal mix (that the mix of expenditure and revenue policies) that under normal circumstances would have delivered growth-boosting public debt reductions may not be successful in an environment of credit restrictions and uncertainty about the future. The presence of troubled financial conditions probably explains why fiscal adjustments that worked in the 1990s have not produced similar beneficial effects on growth in recent years.

Related work

These results are consistent with those of Eggertsson and Krugman (2010), who illustrate the adverse growth consequences of deleveraging when the effectiveness of monetary and fiscal policy is constrained by the liquidity trap. They also confirm that the deleveraging of both the public and the private sector at the same time has a negative impact on growth (Bornhorst and Ruiz Arranz 2013).

Policy implications

The policy implications of these results are significant – when bank deleveraging is high and credit is not flowing to the private sector, public debt consolidations should be gradual. They should also be based on an appropriate combination of revenue and expenditure measures rather than spending cuts alone (IMF 2013).

In a nutshell, credit conditions matter for the medium-term success of fiscal adjustments, as judged by their impact on growth. The expenditure-based consolidations of the past, which worked well in an era without credit constraints, may disappoint when financial conditions are less favourable. Fiscal adjustments based on a prudent mix of both revenue and expenditure measures may be a better recipe for success at the current juncture.

Disclaimer: The views expressed herein are those of the authors and should not be attributed to the institutions to which the authors are affiliated, the IMF and ISTAT, nor to their Executive Boards, or their management.

References

Baldacci, Emanuele, Sanjeev Gupta, and Carlos Mulas-Granados (2013), “Debt Reduction, Fiscal Adjustments, and Growth in Credit Constrained-Economies”, IMF Working Paper 13/238.

Bornhorst, Fabian and Marta Ruiz Arranz (2013), “Indebtedness and Deleveraging in the Euro Area”, 2013 Article IV Consultation on Euro Area Polices: Selected Issues Paper, IMF Country Report 13/232, Chapter 3.

Buti, Marco (2014), “A consistent trinity for the Eurozone”, VoxEU.org, 8 January.

Corsetti, Giancarlo (2012), “Has austerity gone too far?”, VoxEU.org, 2 April.

Cottarelli, Carlo (2012), “The austerity debate: Festina lente!”, VoxEU.org, 20 April.

Eggertsson, Gauti B and Paul Krugman (2010), “Debt, Deleveraging and the Liquidity Trap: A Fisher-Minsky-Koo Approach”, mimeo.

IMF (2013), “Reassessing the Role and Modalities of Fiscal Policy in Advanced Economies”, IMF Policy Paper.

 

Carlos Mulas

 

 

How much is a lot? Fiscal adjustments in perspective

Julio Escolano, Laura Jaramillo, Carlos Mulas-Granados, Gilbert Terrier 27 February 2015

Fiscal consolidation is back at the top of the policy agenda. This column provides historical context by examining 91 episodes of fiscal consolidation in advanced and developing economies between 1945 and 2012. By focusing on cases in which the adjustment was necessary and desired in order to stabilise the debt-to-GDP ratio, the authors find larger average fiscal adjustments than previous studies. Most consolidation episodes resulted in stabilisation of the debt-to-GDP ratio, but at a new, higher level.

High public debt is one of the legacies from the Great Recession that is becoming a pressing issue in the wake of the economic recovery. According the latest IMF’s Fiscal Monitor (October 2014) the public debt ratio of the G-7 is close to 120 percent of GDP and that of the group of advanced economies near 106 percent of GDP. The Euro area as a whole is estimated to have finished 2014 with an average public debt ratio equivalent to 96 percent of GDP. Five years of strong fiscal efforts have stabilised aggregate debt levels, but today, several countries still face the challenge of restoring debt sustainability by continuing with their fiscal adjustment plans.

In this context, the debate around fiscal consolidation is far from over. The VoxEU debate “Has Austerity Gone Too Far?” (Corsetti 2012) has been reflecting the conflicting positions. While some contributors have focused on the characteristics of the fiscal consolidation needed to bring public debt down from historically high levels (Buti and Pench 2012), others have examined the effects of alternative strategies on economic performance (Van Reenen 2012 and Cottarelli 2012) which tend to be more negative in the presence of credit constraints which typically follow financial crises (Baldacci et al. 2013a and 2013b). Adjustment fatigue is setting in within some of the countries hardest hit by the crisis, but the debate about the feasibility of large and sustained fiscal adjustment has also become heated in other countries.

Putting fiscal consolidation in context

In this debate, a crucial question remains to be answered: How much fiscal adjustment is a lot? To answer this question, a relevant angle is to look at what size of fiscal adjustment has been actually feasible in the past. Answering this question is precisely the subject of our latest paper (Escolano et al. 2014). In this contribution we take stock of past consolidation episodes in terms of the size of fiscal adjustments, their duration, and the factors that have accompanied such adjustments.

Our approach adds to the existing literature in several ways.

  • First, we draw lessons from a broad set of consolidation episodes by looking at both advanced and developing countries, and including a time period that spans from 1945 to 2012.
  • Second, we make a very careful selection of the relevant episodes by choosing consolidation episodes where countries needed and wanted to adjust in order to stabilise the debt-to-GDP ratio.

This is a major novelty, since most papers in the literature looked at the characteristics (size, duration, composition, etc.) of all improvements in the primary balance, regardless of whether the country really needed and wanted to adjust.

This choice by previous authors played down the average size achieved by past adjustments. Instead, we looked at those episodes in which countries had large primary gaps (defined as the difference between the actual primary balance and the level of primary balance that would stabilise the debt-to-GDP ratio); and selected only those cases in which countries went beyond pure intentions and showed consistent reductions in their cyclically adjusted primary deficits.

Looking at this set of 91 consolidation episodes that occurred in advanced and developing economies between 1945 and 2012, we found that in most cases fiscal adjustments were sizable and larger than previously identified by other studies. In at least half of the episodes, countries managed to improve their primary balance by 5.4% of GDP (4.8% of GDP in cyclically adjusted terms). And in 25% of cases, the size of the overall deficit reduction was around 8% of GDP.

Debt stabilisation at new, higher levels

The size of the fiscal adjustment implemented during those episodes was enough to close the primary gap in two-thirds of cases. This implies that debt stabilised, and in most cases was put on a downward trend. But debt-to-GDP ratios did not return to initial levels. While countries kept primary balances well above those observed before the adjustment episode, they did not sustain primary balances at the highest levels for prolonged periods of time. This suggests that countries tend to make substantial efforts to stabilise debt but, once this is achieved, they cease consolidation efforts and do not necessarily seek to get back to the lower initial debt-to-GDP ratio.

Factors affecting fiscal consolidation

Finally, in our paper, we also looked at what factors were associated with the size of fiscal adjustments. Based on regression analysis, we found that fiscal adjustment was larger the greater the initial deficit, and that a sustained approach to deficit reduction increases the size of total consolidation. The results also show that fiscal adjustment tended to be higher when accompanied by an easing of monetary conditions (as measured through a reduction in short-term interest rates) and, to a lesser extent, an improvement of credit conditions (measured as the change in credit to the private sector as a percentage of GDP), especially in advanced economies.

Concluding remarks

So, how much is a lot? The historical evidence indicates that it depends greatly on how much is needed. Countries adjust as much as they need to regain control over their increasing debt levels. After that, once debt is stabilised, adjustment efforts seem to run out of steam.

Disclaimer: The views expressed herein are those of the authors and should not be attributed to the IMF, nor to its Executive Board, or its management.

References

Baldacci, E, S Gupta, and C Mulas-Granados (2013a), “Debt Reduction, Fiscal Adjustments and Growth in Credit Constrained-Economies”, IMF Working Paper 13/238.

Baldacci, E, S Gupta, and C Mulas-Granados (2013b), “Fiscal adjustment and growth: Beware of the credit constraints”, VoxEU.org, 31 March.

Buti, M and L R Pench (2012), “Fiscal austerity and policy credibility”, VoxEU.org, 20 April.

Corsetti, G (2012), “Has austerity gone too far?”, VoxEU.org, 2 April.

Cottarelli, C (2012), “The austerity debate: Festina lente!”, VoxEU.org, 20 April.

Escolano, J, L Jaramillo, C Mulas-Granados, and G Terrier (2014), “How Much is a Lot? Historical Evidence on the Size of Fiscal Adjustments”, IMF Working Paper 14/179.

Van Reenen, J (2012), “Fiscal consolidation: Too much of a good thing?”, VoxEU.org, 27 April.

Spatial distribution of R&D expenditure and patent applications across EU regions and its impact on economic cohesion

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 economic cohesion.

JEL classification: O19, O38, R11.

Key words: Spatial Distribution, EU Technology Policy, economic cohesion, Convergence, Technology Indicators.

 

1. Introducción

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 [1]

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 sigmadispersion indexes.

SigmaINCOME = SigmaPATENTS + SigmaTERD + SigmaGERD + ε [2]

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 following equation10:

∆GDPit = α0 + βo (GDPli,t–1) + β1 (TIfi,t–1) + βg (TIgi *cohesiongi,t–1) + + δt + ωp + øi + εti [3]

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. 

The Dynamic State: a new concept and its degree of implementation in Spain

 

Carlos Mulas

 

1. INTRODUCTION
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 origin
family, intellectual and educational environment in which we grow, so they can be
resolved.

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 disabilities.
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 public.

 

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, health,
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
(Sapir, 2006).
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 transformation.


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 state.
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 Security.
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 12,638,000
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 nurseries).
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.

 

6. CONCLUSION
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.

 

BIBLIOGRAPHIC REFERENCES

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.


The growing wage dispersion increases income inequality
05/28/2015

 

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.

Carlos Mulas-Granados, Emanuele Baldacci and Sanjeev Gupta (2012) "How to cut debt?", Economic Policy July 2012.
 Carlos Mulas. The fourth dimension: financial supervision and economic governance
 
Carlos Mulas-Granados (2009) "The fourth dimension: financial supervision and economic governance", After the crisis: A new socio-economic settlement for EU, Policy Network pp:77-87
 
 Carlos Mulas. Do budget institutions matter? Fiscal consolidation in the new EU member states
 
Carlos Mulas-Granados, J. Onrubia y J.Salinas (2009) “Do budget institutions matter? Fiscal consolidation in the new EU member states”, Eastern European Economics, Vol 47. N. 1. pp: 61-95.
 Carlos Mulas. The Dispersion of Technology and Income in Europe: Evaluation and Mutual Relationship Across Regions
 
Carlos Mulas-Granados e Ismael Sanz (2008) “The Dispersion of Technology and Income in Europe: Evaluation and Mutual Relationship Across Regions”, Research Policy, Vol 37. N.5. pp: 836-848.
 Carlos Mulas. What Makes Fiscal policy sustainable? a survival analysis of fiscal consolidations in Europe
 
Reyes Maroto and Carlos Mulas-Granados (2007) “What Makes Fiscal policy sustainable? a survival analysis of fiscal consolidations in Europe”, Public Choice, Vol 134. N. 3-4. pp: 147-161.


 Carlos Mulas. The Phasing of Fiscal Adjustments: What Works in Emerging Market Economies?
 
Emanuele Baldacci, Benedict Clements, Sanjeev Gupta y Carlos Mulas-Granados (2006).“The Phasing of Fiscal Adjustments: What Works in Emerging Market Economies?”, Review of Development Economics, Vol. 10. N. 4. pp: 612-631.
 Carlos Mulas. An Enlarged Monetary Union? The Procedural Sources of Fiscal Policy in the New Member States
 
Carlos Mulas-Granados, Jorge Onrubia y Javier Salinas (2006) “An Enlarged Monetary Union? The Procedural Sources of Fiscal Policy in the New Member States”, International Journal of Public Policy, Vol. 1, No. 3. pp: 34-61.
 Fiscal Policy, Expenditure Composition and Growth in Low-Income Countries
 
Sanjeev Gupta, Benedict Clements, Emanuele Baldacci, y Carlos Mulas-Granados (2005) “Fiscal Policy, Expenditure Composition and Growth in Low-Income Countries”, Journal of International Money and Finance, Vol. 24. pp: 441-463.
 Voting Against Spending Cuts: The Electoral Costs of Fiscal Adjustments in Europe
 
 
Carlos Mulas-Granados (2004) “Voting Against Spending Cuts: The Electoral Costs of Fiscal Adjustments in Europe”, European Union Politics, Vol. 5, No. 4. pp: 467-493.
 Carlos Mulas. The Persistence of Fiscal Adjustments in Developing Countries
 
Sanjeev Gupta, Benedict Clements, Emanuele Baldacci, y Carlos Mulas-Granados (2004). “The Persistence of Fiscal Adjustments in Developing Countries”, Applied Economic Letters, Vol. 11. pp: 209-212.
 Carlos Mulas. The Political and Economic Determinants of Budgetary Consolidation in the EU
 
Carlos Mulas-Granados (2003) “The Political and Economic Determinants of Budgetary Consolidation in the EU”, European Political Economy Review, Vol.1, No.1. pp: 25-49.

Prudence and profligacy

Carlos Mulas
Austerity is hard to measure but, by any reckoning, Europe’s periphery has purged

 

A better method is to look at changes in the cyclically adjusted primary budget balance—ie, the surplus or deficit after stripping out interest payments and temporary effects of the economic cycle. Isolating temporary effects is not an exact science, but the OECD, a club of mostly rich countries, has had a go. The change in this measure, from the point when public spending was at its most profligate to the moment when it was most restrained (or the projected balance for this year if belt-tightening continues), provides a fairer measure of austerity (see chart).

Portugal, Ireland, Italy, Greece and Spain—the PIIGS, as investment bankers’ shorthand has it—were in the direst fiscal straits in the crisis and, naturally, have been the most austere since. Italy has reduced its underlying primary deficit by 4.7% of GDP; the others, by more than 8% of GDP. These figures are huge: 8% of GDP is equivalent to average government spending on pensions in the OECD. No one should accuse the Greek government, in particular, of not cutting back enough: the figures reveal tightening of a whopping 17.2% of underlying GDP between 2009 and 2015. At the other end of the scale, Germany has barely had to cut back at all, and in fact the OECD expects it to loosen its purse-strings slightly this year. No wonder the PIIGS have squealed.

Even this measure of austerity is not perfect, however. By measuring from the high point of profligacy, it includes one-off borrowing intended to inject life into slumping economies. For example, the apparent 6.4% improvement in America’s underlying primary balance rests in part on the expiry of a fiscal stimulus estimated by the IMF to be worth around 2% of GDP in 2009. Although withdrawing stimulus is painful, most would agree that this fiscal splurge in the base year makes governments appear to be donning a hairier shirt than they really are.

Cutting to stand still

The other caveat is that the measure obscures the distinction between countries that saw GDP growth and those that saw massive declines. When an economy is shrinking fast, even keeping spending flat as a share of GDP involves deep cuts in cash terms. Thus Greece has had to slash actual spending by more than a quarter to achieve an 11.2 percentage-point cut in spending as a share of GDP. The British government, in contrast, will have managed to reduce underlying spending, excluding debt interest, as a share of GDP by 3.2 percentage points, but economic growth has allowed it to achieve this by holding this measure of spending roughly constant in real terms (ie, after accounting for inflation).

Aggregate numbers mask other differences, too. Public-sector workers take little comfort from the knowledge that overall spending is buoyant if their salaries have been frozen while spending on social welfare has grown. The OECD’s estimates suggest that this is indeed what has happened: in America, Britain and the PIIGS, spending on public services has been cut relative to spending on benefits and pensions. In Portugal general government consumption (a broad measure of spending on public services) has been slashed by almost a fifth in real terms since 2009, whereas social-security spending has crept up by 4%. And even rising spending on social welfare may feel austere if ageing populations are putting pressure on pension systems.

From any perspective, however, the recent bout of belt-tightening looks severe. Apaper published last year by Julio Escolano, Laura Jaramillo, Carlos Mulas-Granados and Gilbert Terrier of the IMF puts the cuts in historical context. The authors compiled a database of 48 austerity drives in rich countries between 1945 and 2012, all aimed at steadying public debt as a share of GDP. They find that around half of these consolidations amounted to 5% or more of GDP, and a quarter to 7.5% or more. Italy’s recent experience is about average, therefore, and Britain’s (so far) below par. But Greece, Ireland, Portugal and Spain have been far more austere than the norm.

Greece’s recent privations are the most severe of all those that the authors evaluated. Second place is also taken by Greece, which underwent a previous bout of austerity in 1990 to secure (you guessed it) membership of the euro. Germany’s fiscal retrenchment in 1996 earns fifth place. But that dose of Swabian spending restraint, which induced huge strikes, ultimately amounted to just 10% or so of GDP, a little over half of what Greece has endured since 2009.

Austerity has not been adopted at random. Those governments that have cut back the most were also those that spent most recklessly before. Greece may have tightened by 17% of GDP, but at its peak its underlying primary deficit was a clearly unsustainable 12%. Citizens of less spendthrift countries such as Germany are entitled to condemn the PIIGS’ past excesses. They may legitimately rail about the pace of structural reform. But they cannot denounce them for doing too little on the public finances.

 
 













 

In the past five years, concerns about increasing income inequality have been at the center of economic policy debates. There is one area though that has remained relatively unexplored. This is the area that deals with the relationship between the labor share of income and personal income inequality. Income inequality refers to the personal distribution of income, and the labor share refers to the remuneration of employees in total factor income (value added) in a given year. When one looks at these two series, the visual impact is striking. For example, between 1970 and 2012 the labor share in G7 countries declined on average by 12 percent while income inequality increased by 25 percent.

The analysis of factor shares (labor and capital) of national income was considered the principal problem of political economy by classic economists like David Ricardo. Up until the 1960s, this topic was given great preeminence in economic textbooks and academic research. When Kaldor famously summarized the long term properties of economic growth in the 1960s, he stated that the shares of national income received by labor and capital were roughly constant over long periods of time. The analysis of factor income shares was the subject of ninety percent of the papers presented at the conference of the International Economic Association in 1965. The dominant theme was that factor shares were important for the macroeconomic performance of economies, as they were linked to the potential problem of profits squeeze or real wages growing above productivity.

Since the 1970s, however, the analysis of factor shares has no longer been at the center of economic debates, given their lack of volatility and reflecting the fact that the division of income could be easily explained by a Cobb-Douglas production function. Those concerned with personal income distribution started to emphasize that there was no direct (or mechanical) link between factors shares and inequality, and that differences in personal income were related to differences in educational attainment. In addition, a broader share of the population was starting to enjoy some kind of capital income. As home ownership, financial assets holdings and capital-funded pensions expanded in advanced economies between 1970 and 1990, the division into (pure) workers receiving only wages and (pure) capitalists/landlords receiving only profits/rents became blurred, thus contributing to the decline in attention paid to this theme.

The interest in the analysis of factor shares returned, however, in the early 2000s. Atkinson cited in 2009 three reasons to explain this renovated attention: first, the analysis of factor shares was useful to understand the link between incomes at the macroeconomic level (national accounts) and incomes at the individual/household level; second, factor shares could potentially help explain inequality in the personal income (at least partly, if certain types of income were mainly received by some type of economic agents); and last but not least, they addressed the concern of social justice with the fairness of different sources of income.

Initially, researchers returning to work in this area focused on explaining the shifts in the labor share, its gradual but constant decline and the relationship between wages and productivity. The perception that citizens were not fully enjoying the fruits of the long period of economic expansion of the late 1990s and early 2000s attracted the attention also of national policy-makers and international organizations. In 2006 Ben Bernanke, the Fed’s Chairman expressed the hope that “corporations would use some of those profit margins to meet demands from workers for higher wages” and in 2007, Germany’s finance minister asked European companies to “give a fairer share of their soaring profits.”  The IMF, the European Commission, the Bank of International Settlements and the OECD all published reports in the mid 2000s that documented the decline in the labor share of income and provided several explanations of this trend, mainly linked to the impact of globalization and technological change on labor skills, international capital mobility, and wage bargaining. The interest in this field returned after the financial crisis, because the decline in the labor share of income and the sharp increase in personal income inequality ran in parallel and this led many analysts to think that they were strongly correlated.

But the truth is that while apparently correlated, the decline in the labor share of income and the increase in personal income inequality are not directly linked in a causal relationship.  In a recent study entitled “Functional Income Distribution and its

Role in Explaining Inequality” that I have co-authored with Maura Franzese and will be published by the IMF, we test if the declining labor share of income has been a key driving factor for growing inequality. We conclude that it has not been a key factor. Instead, the most important determinant of rising income inequality has been the growing dispersion of wages, especially at the top of the wage distribution. Using a unique database that combines household surveys and macroeconomic data from 81 countries over 4 decades, we show that the most important determinant of increasing income inequality has not the declining share of income that accrues to labor, but the growing dispersion of wages within labor income. This result reflects the fact that the lion’s share of household income is labor earnings. It also occurs because top salaries have grown enormously and wage dispersion has become a driving force behind income inequality. We also found that the increase in wage dispersion has been associated with growing financial globalization, a decrease in industry unionization and a decline in the size of the state.

From a policy perspective our results suggest that to avoid unfavorable (or undesired) distributional consequences, policymakers will have to pay attention to labor market outcomes and to the dispersion of wages, including distortions induced in the labor market by different policy interventions or by changes in labor market institutions. In addition, tax and transfer policies should be properly assessed in terms of their costs and the relative effectiveness in correcting market income inequalities while minimizing distortions. Finally, public policies that support inclusive growth (by for example promoting participation in the labor market and strengthening the human capital of low income groups) should be reinforced to prevent the rise in economic disparities.