By: Renato Miguel do Carmo, Frederico Cantante and Margarida Carvalho
Social inequalities are multidimensional and affect different sectors of society.
Social inequalities are multidimensional and affect different sectors of society. This paper will present data regarding several dimensions of inequality. The paper proceeds as follow. Firstly it focuses on income inequalities (disposable income, pre-tax income, salaries and earnings). Then it analyzes the interaction between income disparities and school attainment as the main inequality drivers in Portugal. Our country is still characterized by a considerable schooling deficit and low wage levels of a substantial part of the employed population (especially those who hold lower levels of education and qualification). The final part of the paper it discusses the impact of the economic crises, namely the increasing of unemployment rates and the impact of the austerity measures .
Since the late 80’s, the Portuguese society is characterized by an increase of income inequalities that reach very high levels at the beginning of the XXIst century. In recent years (until 2009) the values tended to decrease although they still remain very high when compared with the European average.
Portugal is one of the most unequal countries in Europe according to the most used income inequality measures: Gini Index (that measures the extent to which the distribution of income among individuals or households within an economy deviates from a perfectly equal distribution); and S80/20 (ratio of total income received by the 20% of the country’s population with the highest income to that received by the 20% of the country’s population with the lowest income).
As can be seen in Figure 1, in 2009 the disposable income of the richest 20% in Portugal (5th quintile) was 5.6 higher than the income of the poorest 20% (1st quintile). In Lithuania the value of this measure of inequality was 7.3 and in Spain and Latvia 6.9. Norway, Slovenia and Hungary are the European countries analyzed in this chart that present the lowest inequality levels between these two quintiles: 3.4.
Figure 2 provides information about the evolution of S80/S20 ratio in Portugal and EU-27. It shows that in Portugal, since 2003, there has been a decreasing trend in the value of this measure of income inequality. In the EU-27 countries the average value of this measure remained stationary in the period 2004-2009.
The Gini index  value has also reduced since 2005 until 2009. Figure 3 shows the evolution of Gini index in Portugal and European Union. As noted with regard to the S80/S20 ratio, the value of Gini index in Portugal has progressively decreased in the last years, which means a reduction in the level of monetary inequality (disposable income).
Figure 4 shows the evolution of the pre-tax income distribution in Portugal between 1976 and 2005, namely the share of income gathered by the richest quantiles. Looking at this figure it can be seen that the concentration of income among the richest quantiles got deeper during this period. Between 1976 and 1982 the income concentration levels decreased. But since 1989 onwards the share of income possessed by the richest subgroups of the population in Portugal increased steadily.
In 1976 the richest 0.1% gathered 1.3% of the country’s income, but in 2005 this value was up to 2.5%. This evolution is from : 5.0% to 6.4% among the richest 0.5%, 7.9% to 9.8% among the richest 1%, 21.1% to 26.0% among the richest 5%, and 31.7% to 38.3% among the richest 10%.
Figure 5 allows a comparative analysis about the income share gathered by the richest 1% in OECD countries (2005). According to this data, which is based on pre-tax income, the United States richest 1% gather 17.4% of the country’s income. The United Kingdom has the second higher result among the OECD countries analyzed in this figure : 14.3%. In Portugal, this measure of income distribution is 9.8%.
Earnings in private sector
Wages and salaries are the main driver of total market income dispersion. Regarding OECD last calculations this income component accounts for 75% of the dispersion in market income. This situation is particular evident in Portugal where a substantial part of the labour force continues to have low wage rates.
Quadros de Pessoal databases have information about the monthly wage of Portuguese companies’ workers. The data presented in this text is about gross average earnings, which include basic pay, regular benefits and extraordinary benefits. The values are in Euros and in constant prices, which enables to control the inflation effect.
Figure 6 presents the average earning in each percentile in 1985 and 2009, that is, the mean value that each 1% of population earns if sorted in ascending order according to the earnings. Its analysis allows us to observe a widening gap in the earnings.
In 1985 61% of workers had an average monthly earning up to 500 Euros. Only from the percentile 93 the earnings are superior to 1,000 Euros, which means that only 7% of workers had earnings above this value. And only 1% earned more than 1,809 Euros (percentile 99).
In 2009 the 500 Euros threshold, below which were 61% of workers in 1985, covers only 16% of workers. In this year 71% of workers earned less than the average earnings for the total of workers (1,001 Euros), which is visible in the figure – the right tab of the graph increased considerably. Indeed, in the right tab of the graph, where are the highest percentiles, the growth occurred between 1985 and 2009 is much higher than the one verified in the remaining distribution ; on the other hand, the gap between these percentiles and the remaining distribution became greater.
Figure 6 highlights that, between 1985 and 2009, increase in earnings occurred mainly in the highest percentiles. The workers with the highest earnings are the ones that experienced the highest growth of their earnings. While in the first percentiles there is also a considerable increase of the average earnings, in the intermediate percentiles the increase was less important.
Figure 7 shows the evolution of average monthly earnings by quintile, that is, by groups that aggregate each 20% of workers : in the 1st quintile are located the workers with the lower average earnings and in the 5th quintile are the ones with the highest average earnings – the richest 20% of workers.
The increasing distance between the 5th quintile and the remaining quintiles is remarkable. From an average monthly earning of 1,304 Euros in 1985, this quintile came up to 2,237 Euros in 2009.
The 1st, 2nd and 3rd quintiles show similar average earnings and, over the years, the distance between them remains almost unchanged. In that period, the gap between the 4th quintile average earnings and the bottom three quintiles widened. Nevertheless, it is very far from the 5th quintile.
With respect to the 4th quintile, while in 1985 its average earning was above the country’s average (579 Euros was the average earning of this quintile, while the country’s average was 535 Euros), in 2009 the average earning for this group is inferior to the global average (1,001 Euros this one, 999 Euros that one).
This means that in 2009 there are only 20% of workers (the 5th quintile) who had an average earning similar or superior to the global average, which points out to very high earnings in this group, namely in the top percentiles. This is the main cause of the overall average increasing.
Portugal is characterized by a huge deficit of schooling, particularly at secondary and tertiary levels. This situation has important impacts in the persistence of social inequalities. Table 1 presents the proportion of population (with ages between 25 and 64) that concluded at least the upper secondary education. In Portugal, in 2010, only 31.9% had completed this education level. Only Malta registers a lower value.
The six Member States in which the percentage of the population aged 25-64 years that concluded at least the upper secondary education is higher belong to the group of the ten countries that integrated European Union in 2004. In Lithuania, Czech Republic and Slovakia the value of this indicator exceeds 90%, comparing to an average of 72.7% in the EU. Germany and Finland are the EU-15 countries better placed.
Averagely, men have slightly higher results than women in the EU-27 countries (73.7% against 71.8%). However this relationship is inverted in several Member States : for example, in Portugal the percentage of women aged 25-64 years that concluded at least upper secondary education is about six percentage points superior to the men’s percentage (35.1% against 28.6%).
The information presented in Figure 8 shows the relationship between the level of school attainment and the belonging to five categories of income (quintiles). We can observe that in 2008 about 67% of individuals that concluded tertiary education belonged to the richest 20% (5th quintile). Among those that concluded upper secondary education or post-secondary non-tertiary education and those who didn’t go beyond lower secondary education this value is 32.8% and 12.8%, respectively. On the other hand, while more than 40% of individuals that who did not go beyond lower secondary education were integrated in the two lowest income quintiles, only 8% of those with tertiary education were in that situation.
Currently, unemployment reaches very high levels, becoming one of the most important problems of Portuguese society ; over time, this may have clear implications in the rise of inequalities as well in poverty growth. According to INE (Statistics Portugal), unemployment in Portugal reached 14% in the 4th quarter of 2011, that is 771 thousand persons. This means an increase of 11.8% of the unemployed population (81.4 thousand persons) comparing to the previous quarter.
The unemployment rate has a higher incidence in the younger age groups, reaching 35.4% among the population with ages between 15 and 24 years and 15.8% in the 25-34 age group. The number of unemployed in these two groups increased, respectively, 13.0% and 19.9% comparing to the previous quarter.
Although the active population that didn’t go beyond lower secondary education clearly constitutes the largest group of unemployed in Portugal (62.8%), it is among active population that concluded upper secondary education or post-secondary non-tertiary education that the unemployment rate has a higher value: 15.4%. The unemployment rate of the population with tertiary education surpassed the barrier of 10% in this quarter. Algarve is clearly the NUTS II region with a higher unemployment rate: 17.5%.
One of the most worrying aspects that have been presented by the Labour Force Survey is related to the long-term unemployment, that is, the unemployment lasting for a year or more. Among the unemployed population, 20.3% were in that situation for 12-24 months and 32.3% for 25 months or more. This means that 405.5 thousand unemployed (52.6%) were in a long-term unemployment situation.
The austerity measures
This economic and social crisis and the respective policies of austerity may dramatically intensify the growing of inequalities. A recent study  simulated the effects of austerity measures in the income of households. This analysis made use of EUROMOD (and SWITCH, for Ireland) to simulate the effects of austerity measures on the households’ disposable income. The analysis was focused on three kinds of austerity policies that were carried in order to “cut the public deficit or stem its growth”: direct taxes, benefits and pensions, pay cuts on public service workers. According to this study, Portugal is one of the countries where cuts in benefits and pensions had a more negative impact on the income of the less well off.
These results took into account only the austerity measures implemented by the previous government, lead by José Sócrates. The countries analyzed in this study were chosen because they had the highest increase in deficit and/or reduction in the GDP or employment since 2007 until June 2011.
The austerity measures adopted in Portugal had a negative impact of 6% in the disposable income of the poorest 10% group. This is the second highest result among the six EU countries analyzed. Ireland is the only country where this decile’s income decreased more. But while in Ireland the income of the richest 50% was proportionally more affected than the income of the poorest 10%, in Portugal the effects of the austerity policies were regressive: “Portugal is the only country with a clear regressive distribution, with percentage losses that are considerably larger in the first and second decile groups than higher up the distribution.” (p. 19)
In Spain and in Estonia the burden of austerity is similarly distributed among income groups, such as in the United Kingdom – although in the UK the richest 10% suffered a higher percentage loss. Among the six countries analyzed, Greece is the only one where the income loss was clearly progressive.
Income inequalities in Portuguese society are comparatively very pronounced. This situation is due to several factors among which we can highlight the disparities regarding the distribution of educational resources. Indeed, in addition to income inequalities, the lack of education emerges as a major factor of inequality in Portugal.
This persistent situation has profound impacts on the efficiency of our economy and its capacity to deal, in a sustainable way, with modern challenges. Investment in human capital is undoubtedly a priority of public policy. But it must be sufficiently diversified as a way to fulfill the needs of training and schooling and to cover a wider range of social and professional groups: such as young people, adults, seniors, workers, but also entrepreneurs and employers, etc.
Along with the economic crisis and the austerity measures, unemployment is reaching unprecedented and unsustainable levels. At the same time several economic sectors such as construction, retail trade, restaurants, tourism, are falling down. People are reducing their consummation practices and in general the quality of life is getting worse. Because of this, young people (including the most qualified and skilled) have no job opportunities and a considerable part of them are migrating to other countries, like Brazil, Angola, or even Germany. The brain drain trends are growing up during this last two years and in the medium-term this will have a tremendous impact in our productive capacity. This paper was firstly published in the Inequality Watch website.
 The Gini index is a measure of inequality in income distribution with values between 0 (when all individuals have the same income) and 100 (when all the income is concentrated in one individual). This scale can also vary between 0 and 1.
 The distributional effect of austerity measures : a comparison of six EU countries (social situation observatory).