Distribution of income in Germany

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Figure 1.Gini coefficient (in%) of the distribution of disposable income (World Bank, 2014)

The distribution of income in Germany considers the distribution of income in Germany. The personal income distribution regarded as the income of a national economy on individuals or groups (eg. As private households is distributed). When interpreting statistical data, the different uses of the term income must be taken into account, because a distinction must be made between gross income , income , taxable income and net income or disposable income .

In 2016, the Gini coefficient for measuring inequality in disposable income in Germany was around 0.295. According to the Hans Böckler Foundation , this value has increased by around 19% since the end of the 1990s .

The mean gross hourly wage in 2010 was € 12.84. The 10% of employees with the highest hourly wage received € 27.77 or more in 2010, and the 10% with the lowest hourly wage received € 5.05 or less. On October 31, 2018, the German federal government decided to increase the minimum wage from € 8.84 to € 9.19 from January 1, 2019 and to € 9.35 from 2020.

Methods of representation

Market Income and Disposable Income

There are two types of income distribution:

  • Distribution of market income : primary income distribution, i.e. H. Income from employment, business activity, rental, capital before taxes and duties.
  • Distribution of Disposable Income : Secondary Income Distribution , d. H. after direct taxes, social security contributions and including public (e.g. social assistance , unemployment benefit ) and private (e.g. maintenance ) transfers.

The comparison of the two income distributions allows conclusions to be drawn about the degree of redistribution by the state.

Available income

If the persons whose disposable income is being examined are lined up in a row according to the respective income level, the median income is the income that is in the middle of the series. The mean income is more robust with regard to statistical distortions compared to the mean income. A large difference between middle and average income indicates a highly unequal distribution of income.

The median disposable income per person in Germany in 2013 was € 1,345, the net equivalent income € 1,957.

The following table shows the situation with the net equivalent income of the 39.3 million German households in 2013. In the top line, the persons are sorted in ascending order according to the amount of the monthly net equivalent income. These people were then divided into 10% groups (deciles). The bottom line shows the income level of the respective decile. For example, the second column means that the bottom 10% earn an average of € 826 per month. And the last column shows that the top 10% are making $ 4,329.

Table 1. Net equivalent income of German households in 2013
Share of people (%) of all people 10 20th 30th 40 50 60 70 80 90 100
Equivalent Net Income (€) 826 1,142 1,399 1,630 1,847 2,070 2,332 2,659 3,156 4,329

Development of personal income distribution

Inequality in income distribution in Germany has been increasing since the 1990s. While the incomes of people in the upper spectrum have been growing steadily since then, earnings in the lower half are mainly decreasing. That is, the high and low earners move away from the middle income earner. Corporate and property incomes have increased, while mass incomes have stagnated and low wages have declined.

According to the OECD, income inequality in Germany has increased since 1995 and increased more between 2000 and 2008 than in any other OECD country. According to data from the OECD (2009: 0.288; 2016: 0.294) and Eurostat (2009: 0.291; 2017: 0.291), inequality, measured by the Gini coefficient (explained in the next section), has remained roughly at this level.

At the same time as income inequality, income poverty rises.

Figure 2. Lorenz curve of the distribution of income from work (green) in Germany in relation to the blue uniform distribution based on the SOEP database for 2005.

causes

Economically

In 2008, the OECD saw the following reasons for increasing income inequality in Germany:

“The increasing inequality is induced by the labor market. On the one hand, the spread of wages and salaries has increased dramatically since 1995 - notably after a long period of stability. On the other hand, the number of households without any work income rose to 19% - the highest figure in the OECD. Likewise, the rise in inequality is due to changes in household structure, such as the increase in single households and single parents. Despite ongoing state redistribution through taxes and transfers, the gap between rich and poor widened. Transfers are less targeted at people with lower incomes than in other countries. "

Historical

In Germany, as in other European countries, income is unevenly distributed regionally, among other things. Jörg Baten and Ralph Hippe (2017) found that one reason for these regional differences within Europe was the agricultural structures in the 19th century. The decisive factor is the size of the farms, which in turn was influenced by the nature of the soil. In the smaller farms, the farmers attached greater importance to the fact that their children were educated, as they would later take over the farm. This was u. a. typical of northern and northwestern Europe around 1900. However, if the soil and climate were favorable for large wheat fields and thus large estates, political elites often developed. These in turn prevented access to education for rural workers. The resulting educational differences had an impact on general economic development and thus also on income.

Tax

According to scientists who were involved in a study by the Hans Böckler Foundation, previous tax policies favored the inequality that rose in 2016. Wealthy households would have benefited from a lowering of the top tax rate and a reform of the inheritance tax , while poorer households would have been further burdened by higher indirect taxes .

Economically and tax-wise

According to other study results, the causes of a widening gap for high incomes are to be distinguished from the causes for low incomes. While the income spread for low incomes since reunification was mainly caused by characteristics of the labor market, the decisive factor for high incomes were “the sharply increased contribution assessment ceilings for social insurance, which increasingly burden households with average or slightly above-average wages. The peculiarities of the German social security system, combined with increased wage inequality since reunification, have led to a huge redistribution from middle to higher incomes. "

Distribution indicators

Average and median income

Figure 3. Development of nominal and real average and median incomes in Germany.

The median income is the income at which there are just as many people with higher income as lower ones. In other words, if the population were divided into two groups of equal size according to their income, the person who is exactly in the middle of this distribution would receive the median income. The median income can therefore also be understood as the mean income and is explicitly different from the average income indicator , which represents the arithmetic mean of an income type based on the number of income earners. In the distribution analysis, the median income is preferred to the indicator average income because it is viewed as more robust against outliers in a sample:

“In most countries, the distribution of income is characterized by many people with low or middle incomes and a few people with very high incomes; The situation is similar with the distribution of wealth. The arithmetic mean is clearly pulled up by the relatively few cases of very rich households, and the vast majority of households have income or wealth below this average. In order to better identify the middle of the distribution, the median is used in distribution analyzes - at least in addition to the arithmetic mean. "

The real income expressed as an indicator of purchasing power, the amount of consumer goods, which can acquire a consumer with a specific nominal income. The real values ​​are calculated by adjusting / dividing the nominal income or the nominal purchasing power by a price index (e.g. the price level for consumer goods prices). If the prices of consumer goods rise, then real income falls because fewer goods can be purchased with a certain income. The median of the real disposable equivalised income measures how much a person in the middle of the income distribution can afford annually and is therefore an important parameter for assessing material wealth.

Figure 3 shows the development of nominal and real average and median incomes in the period 1996-2018. According to this, the average available nominal annual equivalent income in Germany in 2017 was € 24,780. The median income, however, was € 21,920. The latter figure means that 50% of households were able to generate an income of € 21,920 or more in 2017. Since the median income is significantly higher than the median, the distribution of the nominal annual disposable income is skewed to the right. Looking at the time dimension reveals a continuous and parallel increasing trend in nominal average and median income for the unadjusted nominal values ​​from 2007 to the most recent value from 2017. It is noteworthy that this trend has not been affected by the financial and economic crisis 2008/2009 remains.

Adjusting for the harmonized index of consumer prices ( HICP ) puts the continuously growing trend in the period from 2007 onwards into perspective. In contrast to unadjusted incomes, a longer period of stagnation in real mean and median incomes can now be recorded from 2007 to 2015. During this period, the purchasing power of households did not increase despite nominally higher incomes. Only from 2015 onwards will there be an increase in real incomes, i.e. H. also the purchasing power. Here, too, the real median income is permanently below the real mean income and the course of your graph shows an almost parallel course in the observation period.

However, Figure 3 does not show which income classes have benefited from the increase in real incomes. For this purpose, the population would have to be subdivided into ten groups of equal size according to the level of income (deciles) and the income increases over time would have to be analyzed for the respective income groups. According to a study by DIW , the eight upper deciles achieved income increases of between 5% (3rd decile) and 30% (10 decile) between 1991 and 2015. In the case of the ten percent of people with the lowest incomes, who have an average real monthly average of around EUR 640, their incomes have declined compared to 1991 or stagnated in the second decile.

Gini coefficient

The Gini coefficient is a standard statistical measure often used to measure the inequality of a distribution. It is well suited for determining income inequality and can take values ​​between 0 and 1. The higher the value, the more pronounced the measured income inequality. For example, a Gini coefficient of 0 means that all people compared have exactly the same income. A value of 1, on the other hand, means that one person receives all income and everyone else receives nothing. When interpreting the Gini coefficient as a measure of distribution, however, it must be taken into account that it has weaknesses in measuring the edges of a distribution.

In an EU comparison

Figure 4. Germany's Gini in comparison with the neighboring countries France and Austria as well as the EU-27 average

Germany's Gini coefficient was still below the average value of the EU 27 countries from 2005 to 2017. In this period, income inequality in Germany was lower on average compared to the EU (see Figure 4, based on Eurostat data ). One explanation for the Gini coefficient, which is lower than that of the EU-27, is the social system, which significantly reduces inequality in market income through taxes and transfers. The rule of thumb here is that social spending has a strong redistributive effect in the direction of low incomes, while the tax system (income taxes, social security contributions, consumption taxes, etc.) makes little contribution to direct redistribution.

In comparison with neighboring EU countries, Germany had the second highest income inequality after Luxembourg (33.2) in 2018 with a Gini coefficient of 31.1 . All other EU neighboring countries have a lower Gini coefficient between 28.5 ( France ) and 24.0 (Czech Republic).

Temporal course

Figure 4 suggests an upward shift in the level of the German Gini coefficient. In 2005 and 2006, coefficients below 0.27 were achieved. In contrast, the coefficient rose to over 0.30 in 2007 and later fluctuated between 0.28 and 0.31. In comparison, income inequality reached a coefficient of 0.311 in 2018, its highest level in 13 years.

OECD data allow a longer period from 1992 to 2016 to be considered for the German Gini coefficient of disposable income in Germany. Figure 5. shows an increase in the coefficient from 0.263 (1992) to 0.297 in 2005. Income inequality in Germany increased faster between 2000 and 2005 than in any other OECD country. From 2005 the Gini coefficient remains comparably high and there is no discernible trend towards the lower level seen in the middle of the previous decade.

Figure 5. Gini coefficient according to disposable income and market income in Germany

A similar trend is also found for the Gini coefficient according to market income, i.e. H. before redistribution by the state, to suspect. The traceable course of the coefficients from 2008 onwards runs parallel to one another. Thus the net redistribution stagnates, i. H. the difference between market income and income after taxes and transfers.

The Gini coefficient of market income in 2015 was around 0.504; that of disposable income 0.293. The available or secondary income corresponds to the market or primary income plus pensions and other transfer payments (e.g. child benefit , sickness benefit , unemployment benefit ) as well as pecuniary benefits minus income taxes and social contributions . These values ​​were calculated on the basis of the SOEP . This explains the discrepancies to the Eurostat values ​​in the table, which are based on EU-SILC . Compared with other industrialized countries, Germany is one of the countries with slightly above-average inequality in terms of market income. With regard to the inequality of disposable income, Germany ranks in the middle, but has the lowest value among the major economies.

Table 3. Income tax statistics for Germany
year Gini coefficient Quantiles source
1995 0.422 18th destatis
2004 0.453 22nd destatis
2014 0.532 22nd destatis
Table 2. Gini coefficients according to disposable income and market income for Germany
year 1985 2000 2005 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Gini coefficients according to disposable income
Gini coefficient Eurostat 0.260 0.270 0.260 0.302 0.291 0.293 0.290 0.283 0.297 0.307 0.301 0.295 0.291 0.314
Gini coefficient OECD 0.255 0.264 0.297 0.287 0.288 0.286 0.291 0.289 0.292 0.289 0.293 0.294
Gini coefficient according to market income
Gini coefficient OECD 0.43 0.471 0.494 0.493 0.492 0.505 0.501 0.508 0.500 0.504 0.505

The tax statistics can also be used to calculate the Gini coefficient (Table 3). In 1995, the income tax statistics of the Federal Statistical Office only published data for West Germany. At that time, this resulted in a Gini coefficient of 0.422 for all positive gross incomes divided into 18 quantiles . The comparable Gini coefficient for the 22 quantiles (examined groups) of the income tax statistics for the whole of Germany was 0.497 in 2001, 0.451 in 2003 and 0.453 in 2004. However, there is a difference of two million taxpayers in the lowest quantile between 2001 and 2004. Changes in tax statistics after reforms can impair the informative value of the unequal distribution calculation based on tax statistics. The increase in the number of quantiles from 18 to 22 could have led to an increase in the unequal distribution measures calculated from it, if this uncovered inequalities that were previously hidden within the quantiles. The quantiles at both ends of the income scale are particularly affected by high intra-quantile inequality. The interquantile inequality in the quantiles in the middle is very small, which suggests that the intraquantile inequality is also small there.

Top 10% share of national income

Figure 6. Share of the upper decile in total income for Germany and EU 27

The indicator Top 10% share describes what share of the total national equivalised income the top decile (the 10% of the population with the highest disposable income) has. As can be seen from Figure 6, this proportion in Germany is always just below the EU-27 average for the entire observation period. In Germany, the richest 10% of the population had 23.1% of the total national equivalised income in 2017, while the EU-27 average was 23.8%.

In addition, Figure 6 shows the effects of the global economic crisis in 2008/2009 on the income of the top 10%. The decline in the top 10% share in Germany is significantly more pronounced than in the weighted EU-27 average. The figure thus indicates that income inequality in Germany fell more sharply between 2008 and 2012 than in the other EU countries. This development was interrupted in 2012 by a brief increase in the share of the top 10%. From 2016 the trend is down again. In comparison with the EU-27 average, it can be stated that the top 10% share of total income in other EU countries is permanently higher than in Germany. It must be noted, however, that the figures presented are falsified by retained corporate profits that are not distributed as capital income. The result is a lower share due to the lower capital income of company owners. This smaller proportion is also known as the "corporate veil". The DIW estimates in its own calculations a stable share of national income of about 40% of the top decile for the years from 2008 to 2013. Plausible the significantly higher proportion is only by the underestimation of the top one-Percentage of income distribution. In the last decade in particular, this group was able to benefit from the increasing importance of exports in the gross domestic product and the increasing weighting of capital income compared to wage income and to increase its share.

Gender inequality

S80 / S20 income quintile ratio by gender

Figure 7. S80 / S20 income quantile ratio by gender in Germany

The income quantile ratio is the ratio of the total income of 20% of the population with the highest incomes (top quintile) to the total income of the 20% of the population with the lowest incomes (bottom quintile). According to this indicator, households are ranked according to their income and divided into fifths (quintiles). The sum of the incomes from the top quintile divided by the sum of the incomes from the bottom quintile gives the value for the S80 / S20 ratio. A ratio of 3.0 indicates that the top 20% have three times as much income as the bottom 20%. The higher the factor of the income quintile ratio, the more pronounced the income inequality. As a weakness of the indicator, it must be noted that inequality tends to be underestimated, as the underlying data usually only insufficiently cover the highest income households.

As can be seen in Figure 7, based on Eurostat data, the S80 / S20 ratio for women in the period 1995 to 1999 exceeds the values ​​for men. Due to a lack of data, no statement can be made about the development of the key figure for the period from 2001 to 2004. For the longer period from 2005 to 2017, the value of the income quintile ratio for men exceeds the value for the income quintile ratio for women. In 1995 the ratio was just under 4.5 for men and just over 4.5 for women. A similar level was also achieved in 2017, with the S80 / S20 ratio for men now being higher. The OECD comes to a similar result, according to which the highest income fifth had 4.6 times the total income of the bottom fifth in 2016. In 2000, according to Eurostat, the lowest values ​​were observed with 3.5 for women and 3.6 for men. In the period from 2005 to 2007, strong increases to values ​​close to 5 can be recorded for both men and women. The upward trend was obviously interrupted by the financial and economic crisis of 2008/2009, with the gender-specific gaps in 2008 and 2009 being smaller than in previous years. In the period from 2009 to 2012, the trend for men and women is not uniform. For men, the S80 / S20 ratio increased from 2009 to 2010, then remained the same in 2010 and 2011 and then decreased in 2012. In contrast to this, a permanent decline from 2010 to 2012 can be recorded for women. The largest gender-specific gaps can also be observed during this period. In 2014 there was an increase to a maximum of 5.5 for men and 5.0 for women. Since then, there has been an uninterrupted decline in the income quintile ratio for both sexes. Income inequality for men is slightly higher than for women.

The reforms of the institutions on the German labor market can be used as an explanation for the steep rise in income inequality between 2005 and 2007. In particular, it has been argued again and again since the 1990s that high unemployment is a result of the low flexibility of the labor market, excessively high wage agreements relative to productivity growth and low wage inequality. In addition to a tendency towards decreasing union density and decreasing collective bargaining coverage, politics promoted the expansion of the low-wage sector from 2002 at the latest within the framework of the so-called "Hartz" laws . Finally, the introduction of a statutory minimum wage in 2015 is likely to be one of the reasons for the decline in income inequality. The reasons for the different developments of the S80 / S20 coefficient for men and women can possibly be found in the gender-specific effects of labor market reforms, economic crises and the design of economic stimulus programs.

The gender pay gap

Figure 8. Gender pay gap in Germany and in the EU-27 in the industry, construction and services sectors

The gender pay gap measures the difference between the average income of women in relation to the average income of men, expressed in percent. The gender pay gap usually results from the average difference between the gross hourly wages of all employed men and those of all employed women and is calculated as a percentage of the earnings of the men. This indicator is used to measure equality between women and men in the labor market. The gender pay gap is seen as a product of a large number of structural disadvantages that are upstream on the labor market (education system, unpaid work, interruption due to childbirth) but also partly take place in the labor market itself (job evaluation, opportunities for advancement, income discrimination). Different values ​​for the gender pay gap result from the fact that different influencing factors are taken into account and different methods are used for adjustment.

Figure 8. shows that the gender pay gap in Germany in the industry, construction and services sectors (excluding the public sector) is significantly higher than the gender pay gap of the EU-27 average. Compared to the EU average, Germany has a very high value. It was 20% in 2017, while the EU 27 countries achieved an average of 16%. In addition, the figure shows that the gap between men and women tends to narrow.

The reasons for this high wage difference in Germany can be taken from the amount of investments (this also includes the number of years spent) in education, career choices and different life choices. So z. For example, the years a woman spends raising children have a positive effect on the gender pay gap. This seems intuitive, since women cannot undertake any further training measures necessary for everyday working life during this time. At the same time, there is a large wage difference between male and female-dominated occupational fields, which also has a negative effect on the wage difference. A study by the DIW comes to the conclusion that the size of the gender pay gap is particularly high in occupations with a high proportion of managers and in occupations where long working hours are paid disproportionately. On the other hand, there are jobs in the public sector that have practically no gender pay gap.

Regional inequality

Figure 9. Disposable household income by NUTS 2 regions in Germany (2016)

Regional distribution of disposable income

Germany's regions develop differently, which is reflected in household income. For 2016, the statistics show values ​​between € 17,700 and € 25,900 (per person and year) for the average disposable household income. As can be seen in the figure "Disposable household income by NUTS -2 regions in Germany", the regions with the lowest incomes are in the northeast and the regions with high incomes are in the southern part of Germany. Thus, a strong gap or a strong divergence between the old and the new federal states can be recorded with regard to the regional distribution of disposable income. All regions of the new federal states remain below the median and below the mean of € 21,050 and € 20,097. The regions with the highest income can be found in the two southern federal states of Bavaria and Baden-Württemberg. The Upper Bavaria region has the highest average household income at € 25,900. West German regions and northwest German regions keep their values ​​close to the median and the mean. The federal state of Hamburg is an exception with a value of € 23,700.

Figure 9. shows that the east-west divide in income persists in 2016, clearly visible on the map. A press release by the Hans Böckler Foundation states that regional incomes are higher in some districts than in Luxembourg, and in others at the level of Corsica. Despite visible differences, a slow convergence between the two parts of the country can be observed, since real income increases (after deducting price increases) between 2000 and 2016 were higher in eastern Germany than in western Germany. According to the union-affiliated foundation, the average per capita income at the turn of the millennium was 81.5 percent of the western level, while in 2016 it was almost 85 percent. If only western Germany is considered, a slight north-south divide can be seen, with more affluent regions in Bavaria and Baden-Württemberg. The share of industry is highest in these regions, which in turn correlates with higher disposable income. Regional income equalization usually takes place through income taxation and social transfers. In addition, income differences between the regions are compensated to a considerable extent by the commuting of workers.

Table 4. Distribution of the averages of disposable household incomes in the German NUTS 2 regions
in euros:
minimum 1st quartile Median Average 3rd quartile maximum
17,700 19,950 21,050 20,976 21,925 25,900

Regional risk of poverty

Figure 10. Population groups at risk of poverty and social exclusion in Germany for 2017 by NUTS-2 regions.

A picture similar to that of the regional distribution of disposable household income emerges when considering the population at risk of poverty and social exclusion. In regions with higher disposable household incomes, the risk of poverty is generally lower. The proportion of the population at risk of poverty and social exclusion is between 13% in the economically stronger south and 28% in Bremen , Mecklenburg-Western Pomerania and Berlin . For the whole of Germany, the value is 19% (in 2017).

Even after 25 years after reunification, the Hans Böckler Foundation sees a pattern of higher poverty rates in East and West Germany. Nevertheless, the gap between the new and old federal states would gradually narrow, which was due both to the rising income poverty in western Germany, but also to the significantly lower poverty rate in eastern Germany in recent years.

Table 5. Risk of poverty in%:
minimum 1st quartile Median Average 3rd quartile maximum
13.30 16.95 19.55 19.21 21.40 28.50

Another poverty risk factor is purchasing power poverty, where the national income poverty threshold is adjusted to the price level in the region. "Taking into account the different price levels leads to a significant change in the poverty map. [...] In contrast, the urban-rural divide has widened significantly. The city-states are now closed at the bottom of the ranking, with every fifth to every fourth having poor purchasing power there. "

Other statistics

National

Figure 11. Distribution of gross income in Germany in 2014 (employees)
Figure 12.Distribution of taxable income in Germany in 2014 (persons according to the basic tariff)
Figure 13.Distribution of taxable income in Germany in 2014 (pairs according to splitting tariff)

The Federal Statistical Office determines the income of the population in numerous studies that are repeated at regular intervals. In particular, these are the income and expenditure sample (EVS) drawn every five years and the current economic accounts (LWR), which are drawn up in the other years. In addition, there is the four-year earnings structure survey (up to 2006 at irregular intervals as a salary and wage structure survey , or GLS for short). Monthly incomes over € 18,000 are not taken into account.

The wage and income tax statistics compiled annually in cooperation with the federal states (three years before 2012) as a full survey also include income over € 18,000. A distinction is made between gross income , income and taxable income .

The Federal Employment Agency's IAB sample of employees (IABS) has been in existence since 1975 and also publishes microdata sets that contain regional data. The datasets contain studies based on the daily earnings of full-time employees. Self-employed, civil servants, part-time and low-wage employees are not recorded by the IABS.

The Socio-Economic Panel (SOEP) is a panel survey that has been carried out by the German Institute for Economic Research since 1984. It publishes hourly wages for employees of all groups and supplements them with a great deal of detailed socio-economic information. The disadvantage is the relatively small sample size.

The Institute for Work and Qualification at the University of Duisburg-Essen under the title Social Policy Current Tables and graphics, including on income distribution. Various of the aforementioned surveys are evaluated and summarized.

According to a non-representative survey from the beginning of 2020, the majority of respondents (75%) rate the income distribution in Germany as negative: 28% consider the distribution to be rather unjust, 47% as absolutely not at all. The extent of the negative evaluation differs depending on the party preference and ranges from 48% for supporters of the FDP to 94% of voters of the left.

International

The Employment statistics database of the OECD is the basis of the published annual OECD Employment Outlook. It contains a large amount of data on labor market outcomes in OECD countries.

Results of a Europe-wide structure of earnings survey were published by the European Structure of Earnings Survey (SES) as early as 1995. The SES is made up of national statistical offices and evaluates data from 27 member states of the European Union and two countries of the European Free Trade Association (EFTA).

The International Labor Organization (ILO) makes its knowledge available in the LABORSTA database with extensive labor market statistics.

For data collected worldwide, the World Income Inequality Database (WIID) of the World Institute for Development Economics Research (WIDER) of the United Nations University (UNU) .

See also

bibliography

Web links

Individual evidence

  1. ↑ a b c Eurostat - Data Explorer. Retrieved May 16, 2019 .
  2. ↑ a b c OECD Income Distribution Database (IDD): Gini, poverty, income, Methods and Concepts - OECD. Retrieved May 16, 2019 .
  3. ↑ a b New study: income distributed more unequally than ever before. In: br.de. Bayerischer Rundfunk, October 7, 2019, accessed on October 21, 2019 .
  4. ↑ http://www.diw.de/documents/publikationen/73/diw_01.c.388567.de/11-45-1.pdf Weak wage development in the last decade, p. 9, accessed on August 13, 2017
  5. ↑ https://www.bundesregierung.de/breg-de/aktuelles/mindestlohn-steig-1138404
  6. ↑ DESTATIS: Income and Consumption Sample - Income Distribution in Germany, Fachserie 15 Heft 6 - 2013, p. 35ff, https://www.destatis.de/DE/Publikationen/Themati/EinkommenKonsumLebensbedingungen/EinkommenVerbrauch/Einkommensversorgung.html .
  7. ^ Stefan Bach: Income and wealth distribution in Germany
  8. ↑ OECD (2008), Growing Unequal? - Income Distribution and Poverty in OECD Countries: Country Note Germany (in German): Deutschland (PDF; 257 kB); DIW: The income differences have increased sharply since the turn of the millennium - both in absolute numbers and in relative proportions. (PDF; 469 kB) p. 5.
  9. ↑ OECD: PDF
  10. ↑ OECD (2008), Growing Unequal? - Income Distribution and Poverty in OECD Countries: Country Note Germany (in German): Deutschland (PDF; 257 kB)
  11. ↑ Baten, Joerg, and Ralph Hippe. "Geography, land inequality and regional numeracy in Europe in historical perspective." Journal of Economic Growth 23.1 (2018): 79-109.
  12. ↑ Andreas Haupt, Gerd Nollmann: Why are more and more households at risk of poverty ?: To explain increased poverty risk rates with unconditional quantile regressions . In: KZfSS Cologne journal for sociology and social psychology . tape 66 , no. 4 , December 2014, ISSN  0023-2653 , p. 603–627 , doi : 10.1007 / s11577-014-0287-0 ( springer.com [accessed June 16, 2020]).
  13. ↑ Andreas Haupt, Gerd Nollmann: The gap opens: New wealth of income in reunified Germany . In: KZfSS Cologne journal for sociology and social psychology . tape 69 , no. 3 , October 2017, ISSN  0023-2653 , p. 375-408 , doi : 10.1007 / s11577-017-0482-x ( springer.com [accessed June 16, 2020]).
  14. ↑ DIW Berlin: DIW Berlin: Middle Income. March 1, 2007, accessed May 16, 2019 .
  15. ↑ DIW Berlin: DIW Berlin: Middle Income. March 1, 2007, accessed May 16, 2019 .
  16. ↑ Real income, real purchasing power - Konrad-Adenauer-Stiftung eV Accessed on May 16, 2019 .
  17. ^ AK Prosperity Report: Cornerstones of a Prosperity- Oriented Economic Policy. Chamber for workers and employees for Vienna, accessed on May 19, 2019 .
  18. ↑ DIW Berlin: DIW Berlin: Real incomes rose in Germany between 1991 and 2015, but lower income groups did not benefit from it. March 1, 2007, accessed May 16, 2019 .
  19. ^ DIW Berlin: DIW Berlin: Gini coefficient. March 1, 2007, accessed May 16, 2019 .
  20. ↑ AK-Wohstandsbericht: Key Elements of a welfare-oriented economic policy. Chamber for Workers and Salaried Employees for Vienna, p. 20 , accessed on May 19, 2019 .
  21. ↑ Eurostat: Gini coefficient of equivalised disposable income Source: SILC. Retrieved May 8, 2019 .
  22. ↑ AK Prosperity Report 2018: Cornerstones of a Prosperity- Oriented Economic Policy. Chamber for Workers and Salaried Employees for Vienna, p. 21 , accessed on May 19, 2019 .
  23. ↑ AK Prosperity Report 2018: Cornerstones of a Prosperity- Oriented Economic Policy. Chamber for Workers and Salaried Employees for Vienna, p. 21 , accessed on May 19, 2019 .
  24. ↑ a b c Gini coefficient of equivalized disposable income - EU-SILC survey. In: Eurostat - Tables, Graphs and Maps Interface (TGM) table. Eurostat, accessed on January 18, 2020 .
  25. ↑ OECD: OECD Income Distribution Database (IDD): Gini, poverty, income, Methods and Concepts. Retrieved May 9, 2019 .
  26. ↑ Deutsche Welle (www.dw.com): Can a wealth tax bridge Germany's divide between rich and poor? | DW | 08/27/2019. Retrieved June 18, 2020 (UK English).
  27. ↑ Peichl, Andreas and Stöckli, Marc: Inequality and redistribution in Germany: trends and options for action . Ed .: Ces ifo Schnelldienst 15/2018 Volume 71, August 9, 2018.
  28. ↑ OECD: OED Income Distribution Database. Retrieved December 10, 2018 .
  29. ↑ Examples: the state pays contributions to the pension insurance for certain people because they cannot bear the contributions
  30. ↑ Federal Ministry of Labor and Social Affairs: Scientific evaluation of theories and instruments for inclusive growth in Germany. Retrieved December 10, 2018 .
  31. ↑ Unequal distributions calculated from the income tax statistics of the Federal Statistical Office. Gross total income (profit cases) distributed over 22 quantiles: 2004 , 2003 , 2001 . Positive gross total income distributed over 18 quantiles (profit cases in West Germany): 1995
  32. ↑ A value of 0 means absolute equal distribution, a value of 1 means absolute unequal distribution
  33. ↑ a b destatis, Chapter 20.10.4 in the 1999 Statistical Yearbook
  34. ↑ Income distributed over 22 quantiles of the compressed income tax statistics 2004 ( memento of the original from May 31, 2008 in the Internet Archive ) Info: The archive link was automatically inserted and not yet checked. Please check the original and archive link according to the instructions and then remove this notice. , April 28, 2008 @1@ 2Template: Webachiv / IABot / www.destatis.de
  35. ↑ Federal Statistical Office (Destatis): Wage and Income Tax - Fachserie 14 Reihe 7.1 - 2014 | url = https://www.destatis.de/DE/ZahlenFakten/GesellschaftStaat/OeffigteFinanzenSteuern/Steuern/LohnEinkommensteuer/LohnEinkommensteuer.html , published on 21 June 2018
  36. ^ Income Distribution and Poverty: by country. Retrieved May 16, 2019 .
  37. ↑ To calculate the welfare function from the Theil index for Germany, see per capita income
  38. ^ Jan, Behringer, Thomas, Theobald, Till, van Treeck: Institute for Macroeconomic and Economic Research, Macroeconomic Policy Institute , Report, Income and Wealth Distribution in Germany: A Macroeconomic View . Ed .: Institute for Macroeconomic and Business Cycle ResearchMacroeconomic Policy Institute. October 2014, p. 5 .
  39. ↑ DIW weekly report 3/2018: Distribution of income in Germany. Retrieved May 16, 2019 .
  40. ↑ Federal Agency for Civic Education: Income Inequality | bpb. Retrieved May 19, 2019 .
  41. ↑ AK Prosperity Report 2018: Cornerstones of a Prosperity- Oriented Economic Policy. Chamber for Workers and Salaried Employees for Vienna, p. 20 , accessed on May 19, 2019 .
  42. ↑ EuroStat: [1] S80 / S20 income ratio by gender
  43. ↑ AK Prosperity Report 2018: Cornerstones of a Prosperity- Oriented Economic Policy. Chamber for Workers and Salaried Employees for Vienna, p. 20 , accessed on May 19, 2019 .
  44. ↑ Simon Sturn and Till van Treeck: Labor market reforms in Germany: High social costs without macroeconomic benefits. Hans Böckler Foundation, WSI 11/2010, p. 593 , accessed on May 19, 2019 .
  45. ↑ Simon Sturn and Till van Treeck: Labor market reforms in Germany: High social costs without macroeconomic benefits. Hans Böckler Foundation, WSI 11/2010, p. 594 , accessed on May 19, 2019 .
  46. ↑ AK Prosperity Report 2018: Cornerstones of a Prosperity- Oriented Economic Policy. Chamber for Workers and Salaried Employees for Vienna, p. 22 , accessed on May 19, 2019 .
  47. ^ DIW Berlin: DIW Berlin: Gender Pay Gap. March 1, 2007, accessed May 19, 2019 .
  48. ↑ AK Prosperity Report 2018: Cornerstones of a Prosperity- Oriented Economic Policy. Chamber for Workers and Salaried Employees for Vienna, p. 23 , accessed on May 19, 2019 .
  49. ^ DIW Berlin: DIW Berlin: Gender Pay Gap. March 1, 2007, accessed May 19, 2019 .
  50. ↑ Christina Anger Jörg Schmidt: [2] Gender Wage Gap and Family Policy , accessed on May 8, 2019
  51. ↑ DIW weekly report 10/2019: The size of gender pay gaps in individual occupations are strongly related to the disproportionate remuneration of long working hours. DIW Berlin, accessed on May 19, 2019 .
  52. ↑ KATHARINA WROHLICH: "Great differences in income between women and men". DIW weekly report No. 43/2017, accessed on May 19, 2019 .
  53. ↑ Press releases. Retrieved May 19, 2019 .
  54. ↑ Press releases. Retrieved May 19, 2019 .
  55. ↑ Press releases. Retrieved May 19, 2019 .
  56. ^ Karl Brenke: Increasing regional income differences in Germany, but strong equalization effects through commuter income and social transfers. DIW Berlin weekly report No. 11/2006, accessed on May 19, 2019 .
  57. ^ Karl Brenke: Increasing regional income differences in Germany, but strong equalization effects through commuter income and social transfers. DIW Berlin weekly report, accessed on May 19, 2019 .
  58. ↑ Poverty Rates East and West. Retrieved May 19, 2019 .
  59. ↑ Klaus-Heiner Röhl, Christoph Schröder: https://www.iwkoeln.de/fileadmin/publikationen/2017/326106/IW-Analyse_2017-113_Regionale_Armut_in_Deutschland.pdf .
  60. ↑ a b c Federal Statistical Office: Wage and Income Tax - Fachserie 14 Reihe 7.1 - 2014
  61. ↑ Federal Statistical Office: Income, Income and Expenditures Overview of the results of the sample income and expenditure (EVS) and the current economic calculations (LWR), accessed on October 5, 2013.
  62. ↑ Federal and State Statistical Offices: Earnings Structure Survey / Salary Structure Survey , accessed on October 5, 2013.
  63. ↑ Federal Agency for Civic Education: Data Report 2011, page 136
  64. ↑ Federal and State Statistical Offices: Wage and Income Tax Statistics , accessed on October 5, 2013.
  65. ↑ Research data center of the Federal Employment Agency, - ( Memento of the original from April 8, 2008 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. , April 7, 2008 @1@ 2Template: Webachiv / IABot / fdz.iab.de
  66. ↑ DIW, http://www.diw.de/deutsch/soep/26628.html , April 7, 2008
  67. ^ Current Social Policy: Labor and Household Income, Income Distribution, Poverty , accessed on October 5, 2013.
  68. ↑ Florian Diekmann, DER SPIEGEL: Citizens perceive Germany as extremely unjust - DER SPIEGEL - Economy. Retrieved June 28, 2020 .
  69. ↑ OECD, http://www.oecd.org/document/39/0,3343,en_2649_33927_39080679_1_1_1_1,00.html , April 19, 2008
  70. ↑ European Commission, http://epp.eurostat.ec.europa.eu/portal/page?_pageid=1913,47567825,1913_65204321&_dad=portal&_schema=PORTAL  ( page no longer available , search in web archives )  Info: The link was automatically created as marked defective. Please check the link according to the instructions and then remove this notice. , April 7, 2008@1@ 2Template: Dead Link / epp.eurostat.ec.europa.eu  
  71. ↑ International Labor Organization, http://laborsta.ilo.org/ , April 7, 2008
  72. ↑ UNU-WIDER: World Income Inequality Database V 2.0b May 2007