La nueva normalidad: economía desigual, pobreza, exclusión social y marginalidad (Parte II) (página 2)

Oxfam lleva 70 años trabajando para combatir la pobreza y la injusticia en más de 90 países. Oxfam ha luchado contra el endeudamiento insostenible y contra los paraísos fiscales y, en el transcurso de estas experiencias, ha presenciado de primera mano cómo las personas y los colectivos ricos se apropian de las instituciones políticas para su propio engrandecimiento en detrimento del resto de la sociedad. Vivimos un nivel de desigualdad sin precedentes que pone de manifiesto que, si no se establecen controles sobre las instituciones representativas, éstas se deteriorarán aún más y las diferencias de poder entre ricos y pobres podrían perpetuarse hasta hacerse irreversibles…

La interacción entre la desigualdad y la manipulación de las reglas políticas

La concentración de la riqueza en manos de las élites da lugar a una influencia política indebida que, en último término, arrebata a los ciudadanos los ingresos procedentes de los recursos naturales, genera políticas fiscales injustas, fomenta las prácticas corruptas y desafía el poder normativo de los gobiernos. El conjunto de estas consecuencias empeora la rendición de cuentas y la inclusión social. Todo esto se produce en contextos diferentes. A continuación se exponen algunos estudios de caso de contextos nacionales muy distintos.

Comprar la política: cómo el dinero sesga la representación política e impulsa la desigualdad en Estados Unidos

Desde finales de la década de 1970, la escasa regulación del papel del dinero en la esfera política ha permitido que los ciudadanos acaudalados y las grandes empresas ejerzan una influencia indebida en la elaboración de políticas estatales. Un resultado pernicioso es la manipulación de las políticas públicas en favor de los intereses de las élites, que ha coincidido con una mayor concentración de riqueza en manos del 1% más rico de la población desde los inicios de la Gran Depresión…

A partir de la década de 1980, los sectores financiero y bancario inyectaron millones de dólares destinados a deshacer las normativas puestas en marcha tras la quiebra bursátil y la Gran Depresión de la década de 1930. La desregulación ha tenido dos grandes ramificaciones: por un lado, los directivos de empresas vinculadas a los sectores bancario y financiero se han hecho excepcionalmente ricos, y por otro lado ha aumentado el riesgo de los mercados mundiales, lo cual ha culminado en la crisis económica mundial que empezó en 2008. Tal y como muestra el gráfico 4, existe una correlación directa entre la desregulación financiera y la desigualdad económica en Estados Unidos.

En 2010 el Presidente Obama promulgó la ley de reforma de Wall Street y de protección del consumidor (conocida como Ley Dodd-Frank), cuyo objetivo es regular los mercados financieros y así proteger la economía de una segunda gran crisis. Sin embargo, el sector financiero se ha gastado más de mil millones de dólares en pagar a los cientos de personas que hacen incidencia política para debilitar la Ley y retrasar su plena aplicación. De hecho, en 2012 las cinco mayores asociaciones de consumidores utilizaron los servicios de veinte personas dedicadas a defender la Ley Dodd-Frank, mientras que los cinco grupos financieros más importantes enviaron a 406 personas para abogar por su derogación. A pesar de que la Ley Dodd-Frank se promulgó hace más de tres años, sólo 148 de sus 398 disposiciones se han terminado, y el sistema financiero sigue siendo tan vulnerable a las crisis como lo era en 2008.

El impacto de la austeridad en Europa: el aumento de la brecha de desigualdad

La desigualdad de ingresos iba en aumento en varios países europeos ya antes de la crisis, a pesar del elevado nivel de crecimiento económico. Portugal y el Reino Unido ya se encontraban entre los países más desiguales de la Organización de Cooperación y Desarrollo Económicos (OCDE), lo cual pone seriamente en duda el grado de equidad del crecimiento en estos países una vez que hayan salido totalmente de la recesión.

Con la enorme presión de los mercados financieros, se han puesto en marcha programas de austeridad en toda Europa a pesar de las masivas protestas ciudadanas. Dichas medidas, basadas en impuestos regresivos y en profundos recortes del gasto (especialmente en servicios públicos como la educación, la atención sanitaria y la protección social), ya han empezado a desmantelar los mecanismos de reducción de la desigualdad que permiten un crecimiento sostenible. Las medidas de austeridad también han tratado de debilitar los derechos laborales. Los colectivos más pobres de la sociedad han sido los más perjudicados, ya que son las personas más vulnerables quienes soportan la responsabilidad de los excesos de las últimas décadas, a pesar de ser los menos culpables de ellos. Aunque de forma tardía, los principales defensores de la austeridad, como el FMI, están empezando a reconocer que las duras medidas de austeridad no han dado los resultados esperados en términos de crecimiento y recuperación económicos, y que de hecho han empeorado las perspectivas de crecimiento e igualdad.

Mientras tanto, el 10% más rico de la población ha visto cómo su participación en el total de ingresos ha aumentado. Los ingresos conjuntos de las diez personas más ricas de Europa superan el coste total de las medidas de estímulo aplicadas en la UE entre 2008 y 2010 (217.000 millones frente a 200.000 millones de euros)…

– IMF Policy Paper – Fiscal Policy and Income Inequality – International Monetary Fund – January 23, 2014

Inequality of Income

Over the last three decades, inequality in the personal distribution of income has increased in most economies. Figure 1 presents trends in the average (unweighted) Gini coefficient for disposable incomes (i.e., market incomes minus direct taxes plus cash transfers) across regions over recent decades -which reflects both the inequality of market-determined incomes as well as the distributional impact of income taxes and public transfers. The Gini coefficient ranges between 0 (denoting complete equality) and 1 (denoting complete inequality). Between 1990 and 2010, the Gini for disposable income has increased in nearly all advanced and emerging European economies. Over one-third of advanced economies and half of emerging Europe experienced increases in their Ginis exceeding 3 percentage points, with most of the increases in emerging Europe occurring between 1990 and 1995 during the early years of their transition to market-based systems. Inequality also rose in most economies in Asia and the Pacific and in Middle East and North Africa. While average inequality fell in sub-Saharan Africa over this period, it still rose by more than 3 percentage points in more than one-fourth of these economies. Inequality also increased in over one-third of the economies in Latin America, although on average there was a slight decline. However, since 2000 there has been a substantial decline in the Gini in nearly all countries in this region. This increase in inequality across the globe has also been accompanied by a widespread rise in public support for redistribution.

Note: Disposable income is income available to finance consumption once income taxes and public transfers have been netted out. Therefore, the distributional impacts of indirect taxes and in-kind transfers are not included. The Gini coefficient ranges between 0 (complete equality) and 1 (complete inequality). Number of countries in parentheses.

More striking than changes in inequality within regions are the persistent differences across regions. For instance, between 1990 and 2010, average inequality in each region changed by less than 3¼ percentage points. In contrast, average inequality in the two most unequal regions (sub-Saharan Africa and Latin America) remained 12 percentage points higher than the two most equal regions (emerging Europe and advanced economies). As the following section shows, a large proportion of the differences in regional average disposable income inequalities can be explained by differences in fiscal policies, especially in the levels and composition of taxes and spending.

More recently, the public debate has focused on the sharp increase in the share of total income going to top income groups. Over the last three decades the market income shares of the richest one-percent of the population have increased substantially in English-speaking advanced economies, as well as in China and India (Figure 2). For example, in the United States, the share of market income captured by the richest 10 percent surged from around 30 percent in 1980 to 48 percent by 2012, while the share of the richest one-percent increased from 8 percent to 19 percent. Even more striking is the fourfold increase in the income share of the richest 0.1 percent, from 2.6 percent to 10.4 percent. There has been substantial variation across countries in how much the share of the highest income groups has risen. The increase in the share of the top one-percent has been much less pronounced in Southern European and Nordic economies, and hardly any increases have been observed in continental Europe and Japan. While there is broad consensus about these trends, there is much less consensus on the factors driving them. Some emphasize the impact of new technologies and globalization on the supply and demand for skills (e.g., Goldin and Katz, 2008; Mankiw, 2013) -which can be expected to affect all economies- while others have highlighted the role of policy choices, such as reductions in top income tax rates. Rent-seeking behavior of top executives (at the expense of other incomes) and wealth accumulation have also been identified as factors behind the rising share at the top (see Stiglitz, 2012; Alvaredo and others, 2013)…

Inequality of Wealth

In advanced economies, household net wealth -financial assets and real estate minus debt- has increased substantially over the last four decades. Assessment of trends in this area requires caution, given the limited number of economies with comprehensive data. Internationally comparable data for eight large advanced economies show that the average ratio of net household wealth to national income grew by almost 80 percent between 1970 and 2010 (Piketty and Zucman, 2013). The largest increase was observed in Italy (by 180 percent) and the smallest increase was in the United States (by 21 percent). Explanations for the rapid growth in wealth include asset-price booms and a significant increase in private savings.

Wealth is more unequally distributed than income. The Gini coefficient of wealth in a sample of 26 advanced and developing economies in the early 2000s was 0.68, compared to a Gini of 0.36 for disposable incomes (Figure 4). The share of wealth held by the top 10 percent ranges from slightly less than half in Chile, China, Italy, Japan, Spain, and the United Kingdom, to more than two-thirds in Indonesia, Norway, Sweden, Switzerland, and the United States. In Switzerland and the United States, where wealth is most unequally distributed, the top one-percent alone holds more than one-third of total household wealth.

The inequality of wealth has risen in recent decades in several advanced economies. For instance, between the mid-1980s and early-2000s, the growth of wealth in Canada and Sweden was all concentrated in the two upper deciles of the wealth distribution. During the same period, the Gini coefficients of wealth distribution in Finland and Italy rose from around 0.55 to above 0.6. In the United States, the Gini coefficient of wealth distribution rose from 0.80 in the early-1980s to almost 0.84 in 2007.

Non-financial assets represent a large share of household wealth. Survey data suggest that non-financial assets -such as primary residences and other real estate-represent between 70 and 90 percent of total household gross wealth in advanced economies. In developing economies, this share is even larger: e.g., in the early 2000s it exceeded 90 percent in India and Indonesia (Davies and others, 2008). Financial wealth is generally more unequally distributed than real estate: for example, Fredriksen (2012) reports that the Gini coefficient for financial wealth (on average 0.8 for a group of seven advanced countries) exceeds that for non-financial wealth (0.63).

Lifetime Inequality

Empirical studies suggest that lifetime inequality is usually lower than inequality in any given year. This occurs for two reasons. First, in many economies, individuals experience significant fluctuations in incomes from year to year. Because of this, an individual who has relatively high income in one year may not necessarily have high incomes over their entire lifetime, relative to his or her peers of the same age. Bowlus and Robin (2012) find that because of this "earnings mobility" from one year to the next, the lifetime inequality of income is about 20-30 percent lower than annual income inequality in Canada, the United Kingdom, and the United States. In France and Germany, lifetime inequality is similar to that of annual income. Second, lifetime incomes also tend to be less unequal because of the age-income cycle that affects the entire population: incomes tend to be lower during early working years and peak in later years, before declining again (Paglin, 1975). Taking both of these factors into account, Björklund (1993) finds that the dispersion of lifetime income in Sweden is about 35-40 percent lower than that of annual income. The concept of lifetime income inequality is also important for assessing the redistributive effects of social insurance contributions and benefits.

Inequality of Opportunity

Income inequality can persist across generations, reflecting differences in economic opportunity. Restricted opportunities for increasing incomes can reflect a range of factors, including lack of access to education (including early childhood and tertiary education) and lack of access to certain professions or business opportunities (OECD, 2011a; Corak, 2013). This lack of access is in turn reinforced by low incomes. Therefore, high income inequality is both a symptom and a cause of low economic mobility, and family background is a key factor in determining the adult outcomes of younger generations.

Intergenerational income mobility is lower in countries with higher income inequality. Intergenerational earnings mobility, as measured by the elasticity between a parent"s and an offspring"s earnings, is low in countries such as Italy, the United Kingdom and the United States, which have high Gini coefficients for disposable income. In contrast, mobility is much higher in the more egalitarian Nordic countries (Figure 5). This relationship between income inequality and intergenerational mobility is often referred to as the "Great Gatsby Curve" (Krueger, 2012). In low-mobility countries, about 50 percent of any economic advantage that a father has is passed onto his offspring, whereas in high-mobility countries this falls to less than 20 percent. Evidence for Nordic countries finds that intergenerational income mobility is flat across much of the parental income distribution but rises at the top end. In developing economies with available data, income mobility is extremely low, especially in the high inequality economies of Latin America.

Note: The intergenerational earnings elasticity estimates in the chart are the elasticity between a father"s income and a son"s income. The upward slope of the line suggests that countries with a high inequality of income around 1985 (high Gini coefficients) had high intergenerational earnings elasticities. A high elasticity suggests a strong relationship between a father and son"s income and less mobility of incomes across generations.

(…)

Evidence from recent fiscal consolidation episodes suggests that a progressive mix of adjustment measures can significantly help offset the adverse effects of adjustment on inequality, though the consolidation may still lead to reduced incomes for the poor in the short term. An analysis of 27 recent adjustment episodes in advanced economies and emerging Europe suggests that, in about half of these economies, market income inequality increased during fiscal consolidations. However, in many cases, the increase was muted by the design of adjustment measures. In almost two-thirds of the economies, fiscal measures led to either a decrease in inequality (a decline in the Gini coefficient for disposable income) or at least partly offset the effect of a worsening of market inequality (Figure 13).

Note: An increase in Gini coefficient indicates an increase in inequality. The Gini coefficient for market income is estimated by Euromod based on post-tax income survey data by Eurostat and simulated figures for taxes, using the Euromod micro-simulation model. *Indicates that data for disposable income refer to 2007–11.

– Society at a Glance 2014 – OECD Social Indicators – The crisis and its aftermath – March 2014

(…)

The financial crisis in 2007-08 saw a fast, far-reaching deterioration in economic output for the OECD area as a whole and GDP fell steeply from its pre-recession peaks. But while in some countries, the Great Recession was followed by a moderate but continuous recovery, others avoided outright recession. A number of hard-hit countries, notably in Europe, faced a second recession in 2011-12 and output only began to stabilize in late 2013 (Figure 1.1). More than five years after the Great Recession started, economic output in the OECD is still not back to pre-crisis levels.

Of all the economic losses, however, the income drops suffered by workers have turned out to be the most difficult to reverse. In most countries, the recovery has not yet translated into significant improvements in labour market conditions. Employment and wages have continued to fall until recently (Figure 1.1)…

The demand for social support has persisted despite a public awareness that something needs to be done about often-unprecedented debt levels and structural fiscal deficits. Figure 1.2 for instance, illustrates the findings from a 2013 survey which shows how, in some countries, attitudes have shifted markedly against government debt and in favour of spending cuts.

Since 2007, non-employment rates have increased much more markedly among young people, men, and low-skilled workers than among women and older workers (Figure 1.3). The surge in non-employment, especially among youth and men, reflects a combination of increasing numbers of unemployed (those looking for jobs) and so-called labour-market inactive (including discouraged jobseekers who are no longer available for work or not actively looking)…

The most commonly used statistics of labour-market difficulties refer to individuals rather than households. They therefore do not show how these individual labour-market problems translate into predicaments at the family level. Since 2007 the proportion of people living in households with no income from work has gone up in most countries, approximately doubling in Greece, Ireland and Spain and increasing by 20% or more in

Estonia, Italy, Latvia, Portugal, Slovenia, the United States (Figure 1.5). In debates on fiscal consolidation and other policy reforms, such households deserve special attention as they are particularly vulnerable and highly dependent on government support. With more than one in eight working-age individuals in most countries now living in workless households, the success of redistribution measures and active social policies is gauged to a large extent on whether they can improve economic security for families without any income from work…

What do these recent trends mean for longer-term inequality trends? Information from earlier downturns provides pointers as to the distributional mechanics which tend to be at work well into the recovery phase. Figure 1.6 offers just such a historical perspective on the income trends among low-, middle- and high-income households across earlier economic cycles. These trends are for market incomes that is, before adding social transfers or subtracting taxes. By focusing on market income, Figure 1.6 indicates the space that redistribution policies have to bridge if they are to stem widening gaps between household incomes after taxes and government transfers…

While there are no internationally comparable statistics on food insecurity that are as detailed as those of the United States, some unofficial estimates indicate that growing numbers of families and children suffer from hunger or food insecurity in economically distressed countries. Some 10% of students in Greece fall into that category according to Alderman (2013). The Gallup World Poll includes a question on whether respondents feel that they have "enough money to afford food". Responses confirm that rising numbers of families in OECD countries may have less money to spend on food and a healthy diet. By contrast, while large shares of people in the large emerging economies feel that they cannot afford adequate nutrition, their numbers have mostly declined since 2007 (Figure 1.7)…

General Context Indicators (Reproducción parcial)

Household income

In 2010 half of the people in Mexico had incomes of less than USD 4.500. Half of the people in Luxembourg had incomes about eight times higher (Figure 3.1, Panel A). Countries with low household income included countries in Southern Europe, Turkey and much of Eastern Europe, as well as two Latin American countries -Chile and Mexico. Those with higher household incomes included Norway and Switzerland.

In most OECD countries incomes from work and capital (i.e. market income) fell considerably between 2007 and 2010 (Figure 3.1, Panel B). Higher unemployment and lower real wages brought down household market income, particularly in Estonia, Greece, Iceland, Ireland, Mexico, New Zealand and Spain (5% or more per year). By contrast, market income increased significantly in Chile and Poland as well as to a lower extent in Austria, Germany and the Slovak Republic. On average, between 2007 and 2010, real household disposable income declined by much less than the market income (-0.5%), thanks to the effect of public cash transfers and personal income taxes. At the same time, incomes from work and capital fell by 2% per year.

Figure 3.2 focuses on the top and bottom 10% of the population. While on average across OECD countries real average household disposable income and the average income of the top 10% remained almost stable, the income of the bottom 10% fell by 2% per year over the period 2007 to 2010.

Out of the 33 countries where data are available, the top 10% has done better than the poorest 10% in 21 countries. This pattern was particularly strong in some of the countries where household income decreased the most. In Italy and Spain, while the income of the top 10% remained broadly stable, the average income of the poorest 10% in 2010 was much lower than in 2007. Incomes of poorer households also fell by more than 5% annually in Estonia, Greece, Iceland, Ireland and Mexico. Among these countries, Iceland was the only one where the decrease in average annual income at the top (-13%) exceeded that of the bottom (-8%).

Figure notes: Figures 3.1, Panel B and 3.2: 2007 refers to 2006 for Chile and Japan. 2008 for Australia, Finland, France, Germany, Israel, Italy, Mexico, New Zealand, Norway, Sweden and the United States. 2010 refers to 2009 for Hungary, Japan, New Zealand, Switzerland and Turkey. 2011 for Chile.

Self-sufficiency indicators -ELF- (Reproducción parcial)

Employment

Access to paid work is crucial for people"s ability to support themselves. On average, two out of three working age adults in the OECD area are employed (Figure 4.1, Panel A). In Iceland and Switzerland about eight out of ten are employed, compared to about one out of two in Greece and Turkey. Gender differences in employment rates are small in the Nordic countries, but such differences tend to be largest in Chile, Korea, Mexico and Turkey.

The economic crisis has had a large impact on the employment rates in many countries (Figure 4.1, Panel B). On average, the employment rate declined by 1 percentage point in the OECD area from mid-2007 to mid-2013, but the variation across countries is large. While the rates dropped by 10 or more percentage points in Greece and Spain; Chile, Israel and Turkey experienced an increase of 5 or more percentage points over the same period.

Women have improved their relative position in the labour market compared to men (Figure 4.1, Panel B). Only in Estonia, Korea and Poland, was the change in the employment rate the same for both sexes. In spite of this relatively more favourable development for women, the long-term increasing trend in female employment rates came to a halt in OECD countries after the onset of the crisis.

While employment has dropped, part-time work has increased in many countries. Even if these people avoid unemployment, the consequence for many of them is under-employment and reduced incomes. Involuntary part time as a share of total employment has increased substantially in Ireland, Italy and Spain following the onset of the crisis (Figure 4.2). The increase has been strongest for women, where involuntary part-time reached about 14% of total employment in Italy and Spain in 2012. But also in Australia and Ireland, about 10% of women worked involuntarily in part-time jobs. For men, the share of involuntary part-time was about 5% in Ireland and Spain in 2012.

Immigrants" employment thus seems to be more sensitive to economic conditions than that of the natives. On average, the change in employment rates for the foreign-born between 2007 and 2012 was approximately the same as for the native-born (Figure 4.3).This, however, hides large differences across countries. In those countries which experienced the sharpest drop in employment rates of the native-born (Greece, Ireland and Spain), foreign-born fared even worse than the natives. In contrast, in countries with increasing employment rates, such as Germany, there was a larger increase in the employment rates of the foreign-born than among the natives.

Figure notes: Figure 4.1: Panel A: Data for the Russian Federation are annual and refer to 2012. Data for Mexico refer to Q1 2013. Panel B: Data for South Africa refer to Q1 2007. Figure 4.2: Data for Switzerland refer to 2010 instead of 2012. Countries are ranked in increasing order of the percentage point change of the total population. Figure 4.3: Data refer to 2008 instead of 2007 for Canada, Germany and Ireland; and to Q2 2007 for Switzerland.

Unemployment

Record high unemployment rates in a number of countries have put stress on the benefit systems (see "Recipients of out-of-work benefits" indicator). Unemployment, and particularly long-term unemployment, may also harm career chances in the future, reduce life satisfaction and increase social costs. Establishment in the labour market for youth has become more difficult, while older unemployed often have problems re-entering the workforce.

During the second quarter of 2013, the highest unemployment rates in the OECD were in Greece and Spain – eight times higher than the lowest unemployment rate, in Korea (Figure 4.4, Panel A). The average unemployment rate of 9.1% in the OECD covers a wide diversity. Austria, Japan, Korea, Norway and Switzerland had an unemployment rate below 5%. As many as ten countries had an unemployment rate above 10%.

The economic crisis has had a strong, but varied impact on unemployment rates (Figure 4.4, Panel B). The average OECD unemployment rate increased by 3 percentage points between mid-2007 and mid-2013. Greece and Spain were hit particularly hard, seeing an increase of above 18 percentage points. Increases of more than 5 percentage points were also observed in Ireland, Italy, Portugal and Slovenia. Countries which succeeded in reducing their unemployment rates included Chile, Germany, Israel, Korea and Turkey.

In most countries, male unemployment has been more affected by the crisis than female unemployment. The gender difference is particularly strong in countries such as Ireland, Portugal and Spain, where the contraction of the construction industry is a major factor driving the increased unemployment. High representation of women in the public sector can also be one explanation why women have fared better than men during the crisis in many countries. However, women in Estonia, Luxembourg and Turkey had a stronger increase in the unemployment rates than men.

Long-term unemployment has increased in many countries. The share of people unemployed for one year or more as a percentage of the total unemployment has increased the most in Ireland, Spain and the United States (Figure 4.5), and by as much as 30 percentage points in Ireland. Mid-2013, six out of ten unemployed were out of work for one year or more in Greece, Ireland and the Slovak Republic. The share of long-term unemployed decreased by 10 percentage points or more in Germany and Poland. In spite of the positive achievements, long-term unemployment still accounts for more than 40% of total unemployment in Germany and Poland.

Youth have been hit particularly hard by the deteriorated labour market situation (see also the "NEETs"" indicator). The unemployment rate for young people aged 15-24 increased by 20 percentage points or more from mid-2007 to mid-2013 in Greece, Portugal and Spain (Figure 4.6). At the OECD level, the rate increased by 7 percentage points during the same period. Mid-2013, more than 50% of the age group was out of work in Greece and Spain. At the other end of the scale, youth unemployment rates dropped in Austria, Chile, Germany, Israel and Turkey. Germany, Japan and Switzerland had mid-2013 the lowest unemployment rate for this age group, at about 7%…

Equity indicators (Reproducción parcial)

Income inequality

Income inequality is an indicator of how material resources are distributed across society. Some people consider that high levels of income inequality are morally undesirable. Others regard income inequality as harmful for instrumental reasons – seeing it as causing conflict, limiting co-operation or creating psychological and physical health stresses (Wilkinson and Pickett, 2009). Often the policy concern is focused more on the direction of change of inequality, rather than its level.

Income inequality varied considerably across the OECD countries in 2010 (Figure 5.1, Panel A). The Gini coefficient ranges from 0.24 in Iceland to approximately twice that value in Chile and Mexico. The Nordic and central European countries have the lowest inequality in disposable income while inequality is high in Chile, Israel, Mexico, Turkey and the United States. Alternative indicators of income inequality suggest similar rankings. The gap between the average income of the richest and the poorest 10% of the population was almost 10 to 1 on average across OECD countries in 2010, ranging from 5 to 1 in Denmark, Iceland and Slovenia to almost six times larger (29 to 1) in Mexico.

Keeping measurement-related differences in mind, emerging countries have higher levels of income inequality than OECD countries, particularly in Brazil and South Africa. Comparable data from the early 1990s suggest that inequality increased in Asia, decreased in Latin America and remained very high in South Africa.

The distribution of income from work and capital (market income, pre-taxes and transfers) widened considerably during the first phase of the crisis. Between 2007 and 2010, market income inequality rose by 1 percentage point or more in 18 OECD countries (markers in Figure 5.1, Panel B). The increase was particularly large in Estonia, Greece, Ireland, Japan and Spain, but also in France and Slovenia. On the other hand, market income inequality fell in Poland and, to a smaller extent, in the Netherlands.

The distribution of income that households "take home" (disposable income, post-taxes and transfers) remained unchanged on average, due to the effect of cash public transfers and personal taxes. Between 2007 and 2010, the Gini coefficient for disposable income remained broadly stable in most OECD countries (bars in Figure 5.1, Panel B). It fell the most in Iceland, New Zealand, Poland and Portugal, and increased the most in France, the Slovak Republic, Spain and Sweden. Overall, the welfare state prevented inequality from going from bad to worse during the first phase of the crisis.

Income inequality increased especially at the top of the distribution: the share of pre-tax income of the top 1% earners more than doubled their share from 1985 to 2010 in the United Kingdom and the United States (Figure 5.2). In Spain and Sweden, the data show a clear upward trend albeit less marked than in English-speaking countries. The upward tendency is also less marked in France, Japan and most continental European countries. Overall, the economic 2007/08 crisis has brought about a fall in top income shares in many countries, but this fall appears to be of a temporary nature.

Figure notes: Figure 5.1: Gini coefficients refer to 2009 for Hungary, Japan, New Zealand and Turkey, and 2011 for Chile instead of 2010, and to 2006 for Chile and Japan, 2008 for Australia, Finland, France, Germany, Israel, Mexico, New Zealand, Norway, Sweden and the United States instead of 2007. Data for Switzerland are not available for 2007. Latest data for key partners are for 2008/09. Gini coefficients are based on equivalized incomes for OECD countries and the Russian Federation and per capita incomes for all key partners except India and Indonesia for which per capita consumption was used.

Poverty

Poverty rates measure the share of people at the bottom end of the income distribution. Often a society"s equity concerns are greater for the relatively disadvantaged. Thus poverty measures generally receive more attention than income inequality measures, with greater concerns for certain groups like older people and children, since they have no or limited options for working their way out of poverty.

The average OECD relative poverty rate in 2010 was 11% for the OECD (Figure 5.3, Panel A). Poverty rates were highest at above 20% in Israel and Mexico, while poverty in the Czech Republic and Denmark affected only about one in 20 people. Anglophone and Mediterranean countries and Chile, Japan and Korea have relatively high poverty rates.

The initial phase of the crisis had a limited impact on relative income poverty (i.e. the share of people living with less than half the median income in their country annually). Between 2007 and 2010, poverty increased by more than 1 percentage point only in Italy, the Slovak Republic, Spain and Turkey (bars in Figure 5.3, Panel B). Over the same period, it fell in Chile, Estonia, Portugal and the United Kingdom, while changes were below 1 percentage point in the other OECD countries.

By using an indicator which measures poverty against a benchmark "anchored" to half the median real incomes observed in 2005 (i.e. keeping constant the value of the 2005 poverty line), recent increases in income poverty are much higher than suggested by "relative" income poverty. This is particularly the case in Estonia, Greece, Iceland, Ireland, Italy, Mexico and Spain ("diamond" symbols in Figure 5.3, Panel B). While relative poverty did not increase much or even fell in these countries, "anchored" poverty increased by 2 percentage points or more between 2007 and 2010, reflecting disposable income losses of poorer households in those countries. Only in Belgium, Germany, Israel and Poland did "anchored" poverty fall at the same time as relative poverty stagnated or increased.

Households with children and youth were hit particularly hard during the crisis. Between 2007 and 2010, average relative income poverty in OECD countries rose from 12.8 to 13.4% among children (0-18) and from 12.2 to 13.8% among youth (18-25). Meanwhile, relative income poverty fell from 15.1 to 12.5% among the elderly. This pattern confirms the trends described in previous OECD studies, with youth and children replacing the elderly as the group at greater risk of income poverty across the OECD countries.

Since 2007, child poverty increased considerably in 16 OECD countries, with increases exceeding 2 percentage points in Belgium, Hungary, Italy Slovenia, Spain and Turkey (Figure 5.4). On the other hand, child poverty fell by more than 2 percentage points in Portugal and the United Kingdom. At the same time, youth poverty increased considerably in 19 OECD countries.

In contrast to other age groups, the elderly have been relatively immune to rises in relative income poverty during the crisis. In the three years prior to 2010, poverty among the elderly fell in 20 out of 32 countries, and increased by 2 percentage points or more only in Canada, Korea, Poland and Turkey. This partly reflects the fact that old age pensions were less affected by the recession. In many countries (at least until 2010), pensions were largely exempted from the cuts implemented as part of fiscal consolidation.

Figure notes: Figures 5.3 and 5.4: Data refer to 2009 for Hungary, Japan, New Zealand and Turkey, and 2011 for Chile instead of 2010, and to 2006 for Chile and Japan, 2008 for Australia, Finland, France, Germany, Israel, Mexico, New Zealand, Norway, Sweden and the United States instead of 2007. Data for Switzerland are not available for 2007. Latest data for key partners are for 2008/09, changes are not available.

Living on benefits

Most OECD countries operate transfer programmes that aim at preventing extreme hardship and employ a low income criterion as the central entitlement condition. These guaranteed minimum-income benefits (GMI) provide financial support for low-income families and aim to ensure an acceptable standard of living. As such, they play a crucial role as last-resort safety nets, especially during prolonged economic downturns when long-term unemployment rises and increasing numbers of people exhaust their entitlements for unemployment benefits.

In a large majority of OECD countries, incomes for the long-term unemployed are much lower than for the recently unemployed (Figure 5.6). Making GMI benefits more accessible is key to maintaining a degree of income security for the long-term unemployed. In addition, rising numbers of people who have neither a job nor an unemployment benefit means that the generosity of GMI benefits is likely to receive more public attention.

Benefits of last resort are sometimes significantly lower than commonly used poverty thresholds (Figure 5.5). Poverty avoidance or alleviation is primary objectives of GMI programmes. When comparing benefit generosity across countries, a useful starting point is to look at benefit levels relative to commonly used poverty thresholds.

The gap between benefit levels and poverty thresholds is very large in some countries. In a few countries there is no generally applicable GMI benefit (Greece, Italy and Turkey). For GMI recipients living in rented accommodation, housing-related cash benefits can provide significant further income assistance, bringing overall family incomes close to or somewhat above the poverty line (Denmark, Ireland, Japan and the United Kingdom). However, family incomes in these cases depend strongly on the type of housing, the rent paid and also on the family situation. In all countries, income from sources other than public transfers is needed to avoid substantial poverty risks.

On average across OECD countries, GMI benefit levels have changed little since the onset of the economic and financial crisis. The real value of these benefits was largely the same in 2011 as in 2007. Most countries, including those with significant fiscal consolidation programmes, have so far not reduced benefit levels for the poorest. However, at the same time, countries that were especially hard-hit by the crisis and where GMI were non-existent or very low, have not taken major measures to strengthen benefit adequacy (Greece, Italy, Portugal, Spain and the United States).

Social spending

In 2012-13, public social spending averaged an estimated 21.9% of GDP across the 34 OECD countries (Figure 5.7, Panel A). In general, public spending is high in continental and northern European countries, while it is below the OECD average in most countries in Eastern Europe and outside Europe. Belgium, Denmark, Finland and France spent more than 30% of GDP on social expenditures. By contrast, Korea and Mexico spent less than 10% of GDP. Social spending in the emerging economies in the late 2000s was lower than the OECD average, ranging from around 2% in Indonesia to about 15-16% in Brazil and the Russian Federation (Figure 5.7, Panel A).

Public social spending in per cent of GDP increased in all OECD countries with the exception of Hungary from 2007-08 to 2012-13 (Figure 5.7, Panel B). The growth fully took place during the period 2007-08, as a response to increased unemployment and other consequences of the economic crisis. In this initial phase, Estonia and Ireland had the strongest increase in expenditure shares. From 2009-10 to 2012-13, fiscal consolidation reduced public social spending. Nearly two-thirds of the OECD countries reduced social spending in this period. The real drop in public social spending in some countries is larger than indicated by change in the shares of GDP, since the level of GDP also fell. Indeed in some countries, the rise of the ratio of public social spending in GDP is explained largely by the fact that GDP declined.

On average in the OECD, pensions, health services and income support to the working-age population and other social services each amount to roughly one-third of the total expenditures. In a majority of OECD countries, pensions are the largest expenditure area (Figure 5.8). In Anglophone countries and most other countries outside of Europe, health dominates public social expenditure. In a few countries, such as Denmark, Ireland and Norway, the largest share is devoted to income support of the working age population.

Accounting for the impact of taxation and private social benefits (Figure 5.8) leads to a convergence of spending to- GDP ratios across countries. Net total social spending is 22-28% of GDP in many countries. It is even higher for the United States at 29% of GDP, where the amount of private social spending and tax incentives is much larger than in other countries.

In Europe, people seem to be most satisfied with the health care provisions and less satisfied with the pension provisions, unemployment benefits and the way inequality and poverty are addressed (Figure 5.9). Satisfaction with health care provisions is highest in Belgium, Luxembourg and the Netherlands and lowest in Greece and Poland. Satisfaction with pension provisions is highest in Austria, Luxembourg and the Netherlands and lowest in Greece and Poland. Satisfaction with how inequality and poverty are addressed is in general quite low…

Figure notes: Figure 5.7, Panel A: Data refer to 2009 for Turkey, 2010 for Japan, 2012 for Chile, Korea, and Mexico and to the last years available for key partners. Figure 5.8: Income support to the working-age population refers to cash benefits towards incapacity, family, unemployment and other social policy areas. Data for Israel concern public social spending only. Total net social expenditure data are not available for Hungary, Greece, Switzerland and Turkey. Data for Switzerland refer to 2008

Social cohesion indicators (Reproducción parcial)

Life satisfaction

Life satisfaction is determined not only by economic development, but also by people"s diverse experiences and living conditions. People in Norway and Switzerland are most satisfied with their lives (Figure 7.1, Panel A). The measured level in these countries was 3 steps higher than in Hungary, the country at the bottom of the 11-step ladder in 2012.

There are broad regional or cultural country groupings of life satisfaction. Four of the top five countries are Nordic. Continental Western and Eastern European OECD members are not particularly satisfied with their lives, with the notable exceptions of Switzerland and, to a lesser extent, Austria and the Netherlands. Predominantly Anglophone OECD countries are all in the top half of the list when measuring life satisfaction, and follow in a tight group after the predominately Nordic top cluster.

Life satisfaction deteriorated during the first years of the crisis between 2007 and 2012, particularly in European Mediterranean countries. Indeed life satisfaction dropped mostly in Greece, Italy, Portugal and Spain, followed by the United States (Figure 7.1, Panel B). On the other hand, life satisfaction improved most in non-European countries, in Chile and Mexico, and to a lesser extent in Nordic and Eastern European countries.

Life satisfaction levels for men and women across OECD countries are highly correlated (Figure 7.2). In countries where life satisfaction is high, both men and women tend to have higher life satisfaction than in countries where the levels are lower.

On average across OECD countries, women report slightly higher levels of life satisfaction than men do.

On average, the level of life satisfaction decreases with age (Figure 7.3). Beyond the OECD average, life satisfaction is "u-shaped" in some countries, increasing from about the age of 55. It is not surprising to see that on average 25-34 year-olds (entering the labour market) and 50+ (leaving the labour market) reported lower levels of life satisfaction in 2012 than in 2007. According to related data for Europe, groups who tended to see the greatest deterioration in incomes and labour-market prospects are more likely to have low levels of subjective well-being.

As for emerging economies, life satisfaction also varies between them, from above 6 in Argentina, Brazil and Saudi Arabia, to below 5 in India and South Africa. Between 2007 and 2012, it increased in five countries (Argentina, Brazil, China, Indonesia and the Russian Federation), and it decreased in three countries (India, Saudi Arabia and South Africa).

Figure notes: Figure 7.1: Data refer to 2011 for Chile instead of 2012; and instead of 2007: 2006 for Slovak Republic and Slovenia, average between 2006 and 2008 for Austria, Finland, Ireland, Norway and Portugal, and 2008 for Iceland and Luxembourg.

Figures 7.2 and 7.3: Data refer to 2011 for Brazil and Chile and 2009 for Switzerland; and instead of 2007: 2006 for Slovak Republic, Slovenia and Switzerland; average between 2006 and 2008 for Austria,

Finland, France, Ireland, Norway, Portugal; 2008 for Iceland and Portugal; and 2009 for Luxembourg.

Confidence in institutions

A cohesive society is one where citizens have confidence in national-level institutions and believe that social and economic institutions are not prey to corruption. Confidence and corruption issues are dimensions which are strongly related to societal trust.

Confidence in the national government is generally high in Luxembourg, Norway, Sweden and Switzerland, while it is low in the Czech Republic, Greece and Japan. Large differences can be observed across countries (Figure 7.7, Panel A).

In a majority of OECD countries, trust in national governments declined from 2007 to 2012 (Figure 7.7, Panel B). The decline was particularly large in Greece, Ireland, Portugal and Slovenia, all countries hit hard by the crisis. However, other countries experienced a substantial increase in trust, notably Israel, the Slovak Republic and Switzerland.

Youth tended to have more trust in national governments than the total population, and their confidence declined less from 2007 to 2012. This could be the consequence of less political involvement, but also that youth are more optimistic about the future.

The economic crisis from 2008 was closely related to the crisis in the financial sector. In most OECD countries, confidence in financial institutions fell from 2007 to 2012 (Figure 7.8). Belgium, Ireland, the Netherlands, Portugal, Spain and the United States experienced the most substantial drops in confidence. Only in Iceland, Japan and Norway can a positive change be observed.

Corruption can be a sign of the degree of informality and distrust in the economy. Countries which suffered the biggest declines in GDP from 2007 to 2012 were also among those where corruption had increased (Figure 7.9). Increase in corruption was particularly high in countries such as Estonia, Greece, Ireland and Portugal. These countries also saw a stronger decline in confidence in the national government. Lower levels of corruption could be seen particularly in Australia, Germany, Japan and Mexico.

Among the emerging economies, confidence in national governments increased in Brazil, Indonesia and the Russian Federation, while it declined in India and South Africa. While confidence in financial institutions in general declined in the OECD countries, it increased in Argentina, Indonesia, the Russian Federation and Saudi Arabia.

Figure notes: Figure 7.7: No data available for change in China.

Figure 7.9: No data available for change in Slovenia and Switzerland.

Del Paper – Los daños causados por la crisis ya abarcan "tres generaciones" (abuelos-pensionistas, padres-trabajadores o parados, e hijos-empobrecidos y sin futuro) (Parte II), publicado el 15/1/16

Anexo: Informes de Organismos Internacionales sobre pensiones, salarios y niñez

– Pensions at a Glance 2013 – OECD and G20 indicators

(…)

– Global Wage Report 2014/15 – Wages and income inequality – OIT – December 2014

The global economy contracted sharply between 2007 and 2009, quickly recovered in 2010, but subsequently decelerated (figure 1). While growth rates after 2010 declined across the globe, they remained much higher in emerging and developing economies than in advanced economies…

How have recent economic trends been reflected in average real wages? Figure 2 provides two estimates. The first is a global estimate based on wage data for 130 economies using the methodology described in Appendix I and the Global Wage Database. The second is also a global estimate, but omits China because of its large size (in terms of number of wage earners) and high real wage growth, which remained in double digits for most of the 2000s and accounted for much of the global wage growth. As can be seen from figure 2, global real wage growth dropped sharply during the crisis in 2008 and 2009, recovered somewhat in 2010 and then decelerated again. It has yet to rebound to its pre-crisis rates…

Figure 3 shows estimates for the G20 as a whole and for its developed as well as its emerging members. Together, the countries of the G20 produce about three-quarters of world GDP and employ more than 1 billion of the world"s 1.5 billion paid employees…

Looking at developed economies, it is apparent from figure 4 that the growth rates of average real wages have tended to fluctuate within a low and narrow range since 2006. This pattern has become particularly pronounced in 2012 and 2013, years of virtually flat wages, contributing in the current low inflation environment to concerns about possible risks of deflation…

Figure 5 looks at the individual developed economy members in the G20, which represent the largest developed economies in the world. It shows the variety that exists within the overall trend depicted in figure 4. In France and the United States, average wages are consistent with the pattern shown in figure 4, having been relatively stagnant, with only minor fluctuations. However, Australia and Canada show more positive growth in average wages partially attributed by some to their natural-resource based growth during a boom in commodities (Downes, Hanslow and Tulip, 2014; Statistics Canada, 2014). Conversely, notable declines are observed in Italy and the United Kingdom, where the deep recession was accompanied by an unprecedented period of falling real wages. According to the Low Pay Commission, British wages fell more sharply than at any time since records began in 1964 (Low Pay Commission, 2014)…

Figure 6 shows the extent to which wages changed in selected European countries most affected by the crisis. Most striking is the large decline in Greek wages, resulting in part from a series of specific policy measures, including a 22 per cent cut in the minimum wage for unskilled workers aged 25 and over and a 32 per cent cut for those under 25 in 2012. Collective bargaining was also decentralized, with priority given to enterprise-level agreements in cases of conflict with higher-level agreements, which tended to facilitate downward wage adjustments (ILO, 2014a)…

Are differences in wage trends across countries a product of differences in labour productivity growth? Figure 7 shows the relationship between wages and productivity from 1999 to 2013 in the group of developed economies where labour productivity refers to GDP (output) per worker. This definition captures how productively labour is used to generate output, but also captures the contribution to output of other elements such as changes in hours worked, changes in the skill composition of labour, and the contribution of capital. While other measures of productivity exist, labour productivity as defined here is used by the ILO as a decent work indicator, and is the only one readily available for all countries up to and including 2013.

Figure 7 shows that after a narrowing of the gap during the depth of the crisis between 2008 and 2009, labour productivity has continued to outstrip real wage growth in this group of countries. Even when changes in real wages are calculated using not the CPI but the GDP deflator, the trend presented in figure 7 persists…

Since wages represent only one component of labour costs, it may be more appropriate to compare gains in labour productivity with increases in average compensation per employee (as opposed to wages). Compensation of employees includes wages and salaries payable in cash or in kind and social insurance contributions payable by employers (CEC, IMF, OECD, UN and World Bank, 2009, para. 7.42).

To address this argument, figure 8 compares the change in labour productivity with the changes in average real wages and in average real compensation per employee; as can be seen, the gap still persists…

The overall picture for developed economies is strongly influenced by the largest economies in the group, in particular Germany, Japan and the United States. Figure 9 shows the relationship between productivity and real compensation per employee (as opposed to real wages) for selected developed economies between 1999 and 2013, using both the CPI and the GDP deflator. Real labour compensation per employee is used instead of wages since it is more closely linked to trends in the labour income share. In several countries, labour productivity grew faster than labour compensation. However, in the cases of France and the United Kingdom they grew fairly closely in line, while in Australia, Canada and Italy the relationship between real compensation per employee and labour productivity growth, during this particular period, depends on the deflator used…

Figure 10 shows how the labour income share has changed since 1991 in the developed G20 countries. The unadjusted labour income only includes compensation of employees, whereas the adjusted labour income share used in figure 10 makes an adjustment to account for the self-employed as well. In Canada (and also in Australia), part of the decline is tied to the rise in commodity prices; profits in the mining, oil and gas sectors in Canada doubled between 2000 and 2006 (Sharpe, Arsenault and Harrison, 2008; Rao, Sharpe and Smith, 2005). In Japan, the decline is attributable in part to labour market reforms in the mid-1990s, when more industries were allowed to hire non-regular workers; the consequent influx of non-regular workers, who often earned less than regular workers, contributed to the stagnation of wages over time (Sommer, 2009; Agnese and Sala, 2011). In France, the labour income share remained relatively stable. In Italy and the United Kingdom, the trend is unclear: while the labour income share declined in the early part of the 1990s, since then wages and productivity have grown at a similar pace. In the United Kingdom, the Low Pay Commission has estimated that employees" compensation and productivity have grown at more or less the same rate since 1964 (Low Pay Commission, 2014). In Italy, one factor contributing to the decline in the labour income share at the beginning of the 1990s was a set of labour market reforms that changed the wage bargaining system to curb wage growth (Lucidi and Kleinknecht, 2010). In Germany, after years of wage moderation, the labour income share has partly recovered in recent years.

Turning to European countries most affected by the crisis, figure 11 points to the large decline in the Greek labour income share, to the sharp reversals of wage shares in the Irish labour market, and to the continuously falling labour income share in Spain since 2009…

In emerging and developing economies, data constraints make it difficult to compare wage and labour productivity trends. In addition, labour productivity refers to output per worker, while wages refer only to a subcategory of the working population, namely employees. Employees typically represent about 85 per cent of employment in developed countries, but in emerging and developing economies this proportion is often much lower, and changes more rapidly (see figure 14). For this reason, a more appropriate comparison in this group of countries would be between wages and the labour productivity of employees only. Unfortunately, such data are generally not available. All of these issues create some uncertainty in analyses related to wages and productivity in emerging and developing economies. As a result, subsequent analyses for this group of countries focus only on levels and trends in the labour income share, for which data are more widely available…

The persistent difference in wages between developed economies and emerging and developing economies across the world is evident from figure 19, which shows the shape of the world distribution of average wages if the abovementioned differences between countries" wage data are disregarded and country wages in local currency are converted to purchasing power parity dollars (PPP$), which capture the difference in the cost of living between countries.19 The difference in wage levels between the emerging and developing economies (on the left side of the distribution) and the developed economies (on the right) is quite substantial. For instance, the average wage in the United States, measured in PPP$, is more than triple that in China. However, the figure also shows that the difference in wage levels is decreasing over time. Between 2000 (the red line) and 2012 (the blue line) the wage distribution shifts to the right and becomes more compressed; this implies that in real terms average wages grew across the world, but they grew by much more in emerging and developing economies. This is consistent with trends in average real wage growth presented in section 3 of this report. The average wage in developed economies in 2013 lies at around US$ (PPP) 3.000 compared to an average wage in emerging and developing economies of about US$ (PPP) 1.000. The estimated world average monthly wage is about US$ (PPP) 1.600…

"Top-bottom" inequality is measured by comparing the top and the bottom of the income distribution: see figure 20, where each person represents 10 per cent of the population. The measure of "top-bottom inequality" (also termed the D9 / D1 ratio) is the ratio between two cut-off points: the threshold value above which individuals are in the top 10 per cent and the threshold value below which they are in the bottom 10 per cent of the distribution. Figure 20 also sets out the boundaries of what is understood in this report as constituting "lower", "middle" and "upper" income groups. Middle-class inequality (D7/D3) is measured by cutting out the top and the bottom 30 per cent of the distribution and comparing the "entry point" and the "exit point" of a statistical middle, comprising the 40 per cent of individuals grouped around the median (as shown in figure 20)…

In our sample of developed economies, between 2006 and 2010 "top-bottom inequality" increased in about half of the countries, and decreased or remained stable in the remaining countries. Figure 21(a) shows these trends with countries ordered from left to right, from the countries where inequality decreased to those where it increased. Using the methodology and data sources described in Appendix II, inequality increased most in Spain and the United States (where inequality, measured by the D9/D1 ratio, is highest), and declined most in Bulgaria and Romania.

Over the same period, trends in middle-class inequality in developed economies have also been mixed, increasing in about half the countries where a change can be observed and decreasing in the other half (figure 21(b)). Countries are again ordered from left to right, starting with the countries where inequality decreased most and moving to the countries where it increased most. We see that according to our methodology, the country where inequality among the middle class increased most is Ireland, followed by Spain. On the other side, Romania and the Netherlands are the two countries in the sample where inequality among the middle class fell most. The United Kingdom is one example of a country where middle-class inequality increased while top-bottom inequality remained more or less stable and even declined somewhat…

In developed economies, these mixed trends frequently took place in a context of stagnating or declining household incomes between 2007 and 2009/10 (see figure 23). With the exception of Spain, where inequality increased, some of the countries most adversely affected by the crisis have seen a reduction in inequality as a result of a general downward "flattening effect" of the crisis, meaning that incomes have fallen more for high-income than for lower-income households. Thus, inequality declined in Romania and Portugal and remained almost unchanged in Greece, three countries severely hit by the crisis.28 A few countries, such as Denmark, the Netherlands and Norway, have been able to combine growing household income and falling inequality during this period…

In contrast to developed economies, in emerging and developing economies these trends frequently took place in a context of increasing household incomes (see figure 23). A comparison of figures 21 and 22 also shows that total inequality remains higher in emerging and developing economies than in developed economies even after progress on reducing inequality in the former group. The difference is particularly marked in top-bottom inequality, while the middle class, though more stretched, shows a proportionally smaller difference in inequality…

In developed countries, the labour market effect (i.e. wage plus employment effects) would have increased inequality in two-thirds of countries if other income sources had not offset the increase. In those countries where inequality did increase, other income sources offset about one-third of the increase in inequality generated by the labour market effect. Country-specific developments can be seen in figure 25, which shows the findings from the decomposition of "top-bottom inequality" (D9/D1) for developed economies. Countries are ranked from top to bottom, starting with the country where inequality increased most, to the country where it declined most, over the period 2006-10. The ranking of countries is thus the same as in section 7, but figure 25 focuses on the change in (rather than the levels of) top-bottom inequality. In addition to showing the actual change in inequality, the figure shows how much of the change was due, respectively, to the wage effect, to the employment effect and to changes in other sources of income in the household.

When looking at countries where top-bottom inequality increased, labour market effects (wage plus employment effects) were more important than other income effects in explaining this increase in a majority of cases. In Spain and the United States, the two countries where inequality increased most, the labour market effect accounted for, respectively, 90 per cent and 140 per cent of the increase in inequality – meaning that in Spain inequality was further increased by other income sources, while in the United States (as in some other countries) other income sources partially offset the increase in inequality caused by the labour market effect. The employment effects dominate the wage effects in countries where inequality increased the most, suggesting that job losses were the major cause of top-bottom inequality in these countries during the crisis. (The bars in figure 25 show that within the labour market effect, the wage effect contributed to the overall increase in inequality in both Spain and the United States, but in these two countries the employment effect was even larger, as many workers lost their jobs and hence their wages.)

Among countries where top–bottom inequality declined, this was predominantly a result of the labour market effect in Germany and Belgium. Note that in Greece, Romania and Portugal, the wage effect contributed to less inequality; this occurred because the whole wage distribution was flattened (i.e. wages have fallen more for high-income than for lower-income households). In Bulgaria, Denmark, the Netherlands and Norway, while the wage effect contributed to more inequality, it was more than offset by other factors and inequality declined.

Looking at middle-class inequality (figure 26), the labour market effect contributed to higher inequality in almost three-quarters of the countries in the sample. In countries where inequality increased, other income sources offset only about 5 per cent of the increase. Here again, countries are ranked from top to bottom, from the country where household income inequality increased most, to the country where it declined most, over the period 2006-10. As in the D9/D1 analysis (shown in figure 25), here too the labour market effect is the dominating factor behind the increase in inequality. It is notable, though, that other incomes offset the increase in inequality much less among the middle class (as might be expected, since wages are the major source of household income for the middle classes, as will be seen later in this report).

When looking at middle-class inequality, labour market effect is dominated by changes in the distribution of wages rather than by changes in employment in most countries with increases in middle-class inequality, with Spain the most notable exception. This was the case for example in Ireland, where middle-class inequality increased most, but also in other countries where inequality increased, such as Estonia, Iceland, Sweden and the United States. Considering the labour market effect in those countries where inequality decreased, the decline in inequality was exclusively due to the wage effect in Greece, Portugal and Romania. In Bulgaria and the Netherlands, middle-class inequality fell even though the wage effect pushed towards more inequality.

Taken together, the evidence shows that the labour market effect was the largest force pushing towards more inequality over the period 2006-10; other income sources offset some of these increases in some countries. In this sense, the last few years have been no different from the three decades before the crisis, when other evidence shows that increases in inequality were largely driven by changes in the distribution of wages (see OECD, 2011; Salverda, Nolan and Smeeding, 2009b, p. 11; Daly and Valletta, 2004). The difference is that during the crisis, employment played a larger role in explaining changes in inequality…

To better understand the role of wages in household income, the report next addresses the great variation in the weight of income sources across countries, and across households located at different places in the distribution of income. This is of key importance in order to: (a) understand how recent changes in wages and employment have affected households at different parts of the income distribution, and how this, in turn, has affected income inequality; and (b) develop appropriate policy responses, for example with regard to the mix of minimum wages and transfers. The link between wages and household income is not well documented in the literature, either for developed economies or for emerging and developing economies. This report provides some illustrations of the type of information that policy-makers may find useful in designing policies to address inequality.

It is not surprising that, in most developed economies, wages are a major determinant of changes in inequality, given that wages represent about 80 per cent of household income in the United States and about 70 per cent -with some substantial variation between countries- in Europe. Figure 29 provides an estimate of the respective percentages of total household income that, on average, come from wages and from other income sources across a selection of developed economies. In contrast to the previous section, this section disaggregates other income sources, breaking them down into income from self-employment, capital gains, pensions, unemployment benefits, other social transfers and remaining residual income. As pointed out earlier, households where no member is of working age are excluded from the analyses. In Germany and Sweden, wages represent at least 75 per cent of household income, whereas in Greece and Italy they account for between 50 and 60 per cent, with self-employment and pensions playing a relatively larger role than in other developed countries. Taken together, pensions, unemployment benefits and other social transfers represent on average between 15 and 20 per cent of household income in both Europe and the United States. In all countries, reported capital gains are a relatively small proportion of reported incomes…

We have seen in section 8 that other (non-wage) income sources play a larger role in changes in top-bottom inequality than in respect of middle-class inequality. This reflects the fact that income sources at both the top and the bottom of the income distribution are more diverse than in the middle, where households rely mostly on wages. In figure 30, households are ranked in ascending order by their per capita household income and divided into six groups: the "bottom 10 per cent", the "lower" income group (11th-30th percentiles), the "lower middle" class (31st-50th percentiles), the "upper middle" class (51st-70th percentiles), the "upper" income group (71st-90th percentiles) and the "top 10 per cent". As before, these labels are formulated purely for practical purposes, to facilitate the description of results, and do not have a sociological interpretation. For all the selected countries shown in figure 30, it is for the poorest 10 per cent of households that wages represent the smallest source of household income, and in the middle classes and upper-income groups that wages frequently make up the largest source of household income. This pattern can in fact be observed in almost all developed economies.

There is also great variability across countries in the proportion of household income made up by wages in the top and bottom 10 per cent of households. Figure 30 shows, for example, that among the bottom 10 per cent, wages represent about 50 per cent of household income in the United States, more than 30 per in Italy and about 25 per cent in France. By contrast, in the United Kingdom wages represent less than 20 per cent of household income among the poorest households, in Germany less than 10 per cent, and in Romania less than 5 per cent. In all countries, social transfers play an important role in supporting low-income households (as compared with other income groups), even though the type of transfers varies across countries. In Germany, for instance, unemployment benefits and other social transfers play an almost equally important role, whereas in other countries unemployment benefits make up a much smaller share of household income in the bottom 10 per cent. Among the middle and upper classes, wages represent the highest share of household income in almost all countries, reaching about 80 per cent or more in Germany, the United Kingdom and the United States. In Italy and France, the richest 10 per cent of households draw a large share of their household income from income sources other than wages, particularly from self-employment income and capital gains (even though both of these household income sources are likely to be underestimated in household surveys)…

Figure 31 shows the change in income sources in two countries over the period 2006 to 2010 to provide an illustration of why top-bottom inequality (D9 / D1) increased in Spain (the country in our sample where inequality rose most) and why it declined in Romania (the country in our sample where inequality declined most, together with Bulgaria). The figure shows the real change (i.e., adjusted for inflation) in household income of the top and bottom 10 per cent, broken down by source of income.

In Spain, growing inequality between 2006 and 2010 is the result of household income falling more in real terms in the bottom 10 per cent than in the top 10 per cent (the overall bars -where 2006 serves as the base year equal to 100- shrink more for the bottom 10 per cent across time than for the top 10 per cent). Looking at the different components of the bars, we see that the share of household income from wages declined in real terms between 2007 and 2010 for those in the bottom 10 per cent. Incomes from self-employment and from pensions also declined. For the bottom 10 per cent, only income from unemployment benefits increased, but not enough to prevent a sharp decline in overall real income. For the top 10 per cent, household income from wages also declined, but by proportionally less than at the bottom.

In Romania, a different story emerges: over the whole period 2006-10, top-bottom inequality declined because household income, in real terms, fell at the top (the overall size of the bar shrank) but increased slightly at the bottom. Looking at the different components, wages accounted for a small proportion of household income in both 2006 and 2010 for households at the bottom: most household income came from self-employment and from social transfers. In Romania, the top 10 per cent rely to a much larger extent on wages, although this source of income has been declining. The fall in inequality in the country may have been due to fiscal consolidation measures affecting the top of the income distribution, including public sector wage cuts, and modest gains, mostly from social transfers, for low-income households (Domnisoru, 2014)…

Figure 36 shows the gender wage gap, calculated for each decile of the wage distribution and split into an explained and unexplained component, for selected countries. Wage earners are ranked according to their level of wages, from the lowest decile to the highest. The total unadjusted wage gap is the sum of the two bars: the dark bar represents the proportion of the wage gap which can be explained by observable labour market characteristics, and the light bar is the "unexplained" gap. The gaps are provided in absolute values: for example, in the first decile in Belgium there is an unadjusted gender wage gap of about € 400, whereas in Estonia it is about € 50. The shapes of the decompositions vary across countries and across groups. In Belgium and Estonia, women receive lower wages than men throughout the distribution, but the unexplained part of the gap tends to be higher among better-paid women. In the United States, the unexplained part is proportionally small, and affects predominantly better-paid women. In Peru and Vietnam, the explained part tends to increase at higher wage levels of the wage distribution. By contrast, in Sweden the unadjusted gender wage gap is very small (the light and dark bars generally offset each other; the negative dark bars imply that women would actually earn more than men if discrimination and other unexplained factors did not exist). A similar situation can be observed in Chile and in the Russian Federation, where discrimination and other unexplained factors alone account for differences in pay between men and women.

Figure 37 presents (1) the level of the average gender wage gap at the national level for the countries included (the dark bar) and (2) a counterfactual estimate of the contribution of the unexplained part of the wage gap to the overall unadjusted wage gap (the light bar). The counterfactual wage gap is the gap which would exist if men and women were equally remunerated entirely according to the observable labour market characteristics taken into account in this report (i.e. education, experience, economic activity, location, work intensity and occupation). Once these adjustments are taken into account, in our sample of developed economies (figure 37(a)) the mean gender wage gap nearly disappears (e.g. Austria, Iceland, Italy) or even reverses (e.g. Lithuania, Slovenia, Sweden) in about half the countries in the sample. It declines substantially in other countries but remains largely explained in Germany and the United States. Among our sample of emerging and developing economies (see figure 37(b)), the gender wage gap reverses in Brazil and the Russian Federation. In all other countries in the sample, the wage gap declines substantially, though less so in Argentina and Peru, where much of the gender wage gap is also due to differences in education and other observable labour market characteristics. The existence of negative "explained" gender wage gaps (i.e. negative light bars), in the presence of positive unadjusted wage gaps (i.e. positive dark bars), points to the importance of gaining a better understanding of the factors that influence pay for men and women with equal experience, qualifications and other observable labour market characteristics, in order to address them effectively…

Figure 38 shows the results of applying the counterfactual estimation across different wage levels for two countries with available data, the Russian Federation and the United States. The first column shows the distribution of men by wage level, the second column shows the distribution of women, and the third column shows the distribution of women absent the unexplained wage gap. Consistent with figure 36 -which showed that in the United States the unexplained wage gap is small at the bottom- the elimination of the unexplained component brings about the greatest increase in the proportion of women in the top category with wages above one and a half times the median wage (where, according to figure 38, the unexplained wage penalty is highest). In the Russian Federation, once the unexplained penalty is removed, the percentage of women on low pay declines considerably, and the proportion earning higher wages equal to at least one and a half times the median wage increases…

Figure 39 shows that in Germany, for example, high-wage migrant workers earn less than high-wage nationals, even though they would earn higher wages than nationals if they were remunerated according to their labour market attributes (the dark bar is negative). In Argentina as well, the wage gap among migrant and national top wage earners is exclusively due to the unexplained part.

In Cyprus, even though the overall unadjusted wage gap is higher at the top than at the bottom of the wage distribution, the unexplained part accounts for a larger share of the gap at the bottom. This implies that while the wage gap is smaller at the bottom, migrant workers at the bottom would earn more than their national counterparts if they were remunerated according to their observable labour market characteristics alone. By contrast, among high wage earners the gap is large, but can be attributed to migrants" lower levels of education and other observable labour market attributes. One exception to this pattern is Brazil, where according to the available survey data, high-wage migrants (mostly university graduates) earn more than high-wage nationals for both explained and unexplained reasons.

Figure 40 shows what would remain of the wage gap if the unexplained component was eliminated using the same counterfactual approach as employed for the gender wage gap above. Among developed economies (figure 40(a)), in Denmark, Germany, Luxembourg, the Netherlands, Norway, Poland and Sweden, the mean wage gap reverses when the unexplained part is eliminated, implying that on average migrant workers may have more education or experience, work in higher-paid regions, or be more highly skilled, etc., than their national counterparts.

In most other countries, the migration penalty declines but is not eliminated after the adjustment. In the emerging and developing economies for which data permit analysis (figure 40(b)), the results are similar, except in Chile. There, migrant workers earn more than their national counterparts on average, although if they were paid according to their observable labour market attributes, they would earn slightly less than national workers (as shown by the increase in the light bar).

Figure 41 shows the counterfactual applied across the wage distribution for two countries, Cyprus and Spain. The first column shows the wage distribution of national employees, whereas the second column presents the same information for migrant employees. The third column shows how migrants would be distributed in these groups if the "unexplained" wage gap were eliminated. We see that in Cyprus, migrant workers are heavily represented in the lowest wage groups.

However, this picture changes significantly once the unexplained wage penalty is removed, with the migrant wage distribution becoming more similar to the national wage distribution. This is consistent with figure 37(a), which shows the unexplained component contributing more to the wage gap at the bottom of the wage distribution. By contrast, the corresponding changes in Spain are smaller because most of the wage gap between migrants and nationals is explained by a difference in observable factors.

– Series estadísticas ampliadas, para "arqueólogos" de la economía (dentro del marasmo de la "sobreinformación" disponible en Internet, algunos "sospechosos" cambios de metodología y ciertas "intoxicaciones" políticamente correctas)

Fuentes consultadas:

http://epp.eurostat.ec.europa.eu/portal/page/portal/income_social_inclusion_living_conditions/introduction

– Del Informe "Neoliberalismo y distribución del ingreso en los Estados Unidos de América", de febrero de 2009, del Profesor Carlos Encinas Ferrer, investigador y académico de la Universidad de La Salle Bajío en León, México, publicado en la Revista Latinoamericana de Economía Problemas del Desarrollo, se presentan los gráficos (numerados del 1 al 12), que abarcan del año 1959 al 2007.

– Ingresos de los hogares publicados por el U.S. Department of Commerce y Eurostat: http://www.census.gov/hhes/www/income/data/historical/inequality/IE-1.pdf

– Income, Poverty, and Health Insurance Coverage: 2013 – U.S. Department of Commerce – U.S. Census Bureau – September 2014

– Income and Poverty in the United States: 2013 Current Population Reports – U.S. Department of Commerce – U.S. Census Bureau – September 2014

– Table 693 – "Share of aggregate income received by each fifth and top 5 percent household: 1970 to 2008", cuya fuente es el U.S. Census Bureau – The 2011 Statistical Abstract – The National Data Book.

– Table A-2 Selected measures of household income dispersion: 1967 to 2013 – U.S. Census Bureau

– Income Inequality Update – Rising inequality: youth and poor fall further behind – OECD – June 2014

Un inmenso panorama de sufrimiento y sueños rotos: buscando respuestas