Development and Background of Income Distribution in Germany

ABSTRACT

The Economist Simon Kuznets Smith, Nobel Laureate in Economics in 1971, examined the empirical relationship between economic growth and inequality in income distribution of an economy. He stated that inequality increases initially during the development of a country and then decreases. The Kuznets curve is a graphical representation of this relationship. Since the 1990s and 2000s, however, the inequality in OECD countries has begun to rise again. This is indeed the case in Germany. The study shows that the reason for this development cannot be traced to any one single factor, for example globalization, but is rather the result of structural factors and tends to occur in the transition from an industrial society to a highly developed services economy. The study will investigate which factors - such as globalization, advances in technology, politics and institutions, the education level and changes in household structures - are responsible for the rise in income inequality in Germany and how strongly each factor influences this rise.

KEY WORDS

Demographic Changes, Equivalent Income, Gini Coefficient, Globalization, Household Income, Income Inequality, Kuznets Curve, Labour Market Trends, Market Income, Market Regulations, Technological Progress, Transfer Income, Wage Dispersion.

INTRODUCTION

Income Distribution

Differences in living standards within a country are generally based on income inequalities. The Russian-American economist Simon Smith Kuznets (1901 – 1985) together with the American economist Hollis Burnley Cherny (1918 – 1994) presented in 1955 the hypothesis that income inequality in poor countries is initially low, then rises as poverty declines, and then falls again as soon as a certain average income is exceeded. In their model, Kuznets and Cherny described the development of income distribution in many economies, as they evolve from a society characterized initially by agriculture to a more industrial and then later to a modern service-oriented economy.

This development, predicted by Kuznets and Cherny, can be reconstructed for the United States until the early 1970s. After the income inequality reached its all-time low (i.e. relatively low income inequality) at the end of the 1960s, it has been continually increasing again since the early 1970s. Many economists viewed the widening gap between rich and poor not only as a consequence of high economic growth. They held such a gradient even as an important prerequisite for a well functioning market economy. Moreover, not only the liberal economists believed that if the rich are getting richer, the poorer strata of society benefit ultimately.

Meanwhile, the evidence is growing, that stark contrasts between rich and poor have not only a moral dimension, but can also lead to considerable economic damage. Some researchers even see in the drastic increase of income inequality as one of the causes of the financial crisis between 2007 to 2009.^[1]

This article deals with the question of whether the renewed increase in income inequality is typical for developed countries and to what extent the apparent increase in income inequality in the United States can also be observed in Germany, and then investigates the reasons for these developments.

The following hypotheses are examined:

H1: Advanced economies such as in the OECD countries tend, after they have gone through the Kuznets curve, to experience a renewed increase in income inequality.

H2: Even in Germany an increase in income inequality can be observed.

H3: The reasons for the rise in income inequality in Germany are many and various. The increase cannot be attributed to a single cause.

H4: In Germany, the above-average differences in gross income are offset disproportionally by taxes and transfer payments from the social market economy.

MATERIAL AND METHODS

The results of various existing studies (see references) are examined and evaluated in particular for their significance for Germany.

RESULTS AND DISCUSSION

1. The Kuznets Curve

The Kuznets curve is the graphical representation of the empirical relationship between economic growth and inequality in income distribution discovered by Kuznets and Cherny. It indicates that economic inequality first increases during the development of a country and then decreases. The explanation provided by Kuznets, himself, is based on an economy developing from an agricultural characterized society to an industrial characterized one. At the beginning, all workers are employed in agriculture and have roughly equal incomes. With the beginning of industrialization, workers move to cities where they get higher wages so that the income distribution of the population as a whole becomes uneven. In the course of industrialization, more and more people work in factories so the wages there stabilize or even fall. Simultaneously, the supply of labour in agriculture becomes scarce so the income there, in contrast, rises. Thus, the overall income distribution converges again. Viewed over time, the course of income inequality is in the form of an inverted U.^[2]

Figure 1 Kuznets Curve – Living Standards and Income Distribution^[3]

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2. The Gini Coefficient

The Gini coefficient or Gini index is a statistical measure developed by the Italian statistician Corrado Gini (1884 - 1965) for the representation of unequal distributions. Unequal distribution coefficients can be calculated for any kind of distribution. The Gini coefficient is used particularly in welfare economics, for example to determine the degree of equality or inequality of the distribution of wealth and income. Minimum = 0 (complete equality), maximum = 100 (all income by one person, the rest get nothing) The representation is expressed as a percentage; the actual coefficient moves between 0 and 1. In general, a Gini coefficient below 40 indicates a slight inequality of income distribution, over 50 high inequality. High coefficients and hence strong differences in income distribution can be seen primarily in the south of Africa and in South America. But it is also above average in Turkey and in the United States. A relatively low Gini coefficient is found, for example, in the northern European countries like Sweden. In Germany, the Gini is with a value of 29 approximately the average of OECD countries (31).

Table 1 Average Income and Income Inequality, Selected Countries

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Source: World Bank (2012) *Source: United Nations Development Program (2005) **Source: DIW 2010.

Table 1 shows the Gini coefficient in selected countries. In Sweden, the income is distributed relatively equally. Broad levels of the population in Sweden are very well educated. Many people benefit from the opportunities that arise in a service society. High taxes and social security provide a well-developed social network from which all benefit. This results in a very low Gini, lower even than in Bangladesh. Ecuador and Chile, which belong to the medium rich countries, have higher Gini indices. In Bangladesh, where both in rural areas, as well as in the industrial and service sectors, poverty prevails, the Gini is low. When a country begins to develop under such conditions, this benefits the poor and poorly skilled population only slightly. The poor can choose between lingering on the rural countryside or taking low-paid service jobs (as is the case in Ecuador). Either way, income barely rises. In contrast, the few highly-educated ascend and their salaries rise. Thus, the Gini rises to mid-40s and beyond. India is a good example: Here we find rapid economic growth coupled with rising income inequality. Credit card companies, airlines and other business enterprises have shifted service jobs to India, benefitting the well-trained people with good English skills. The rural poor have not benefited. The result: The Gini is much higher than in Sweden.^[4]

Eastern Europe is the only part of the non-wealthy world, where the elite do not distinguish themselves strongly from their fellow citizens, as a result of better education, training and other benefits. Schools have been widely available for many years. Broad spectrums of the population benefit from the demand for well-trained personnel. The Gini in Poland, for example, is fairly low.

At first glance, table 1 reflects the Kuznets hypothesis if it were not for the United States. With a Gini of 45, they rank in the range of medium rich countries, as if they were in the midst of industrialization, even though they are one of the richest nations of the world (GDP per Capita of $ 46,406). Looking at the development of the Gini in the United States over the period of the last forty years shows that the Gini at the end of the 1960s was also at a low level with a value of 38.6 (1968). It then increased steadily until it reached its previous peak value of 47 in 2006, and since then has stagnated at that level with slight fluctuations.

Figure 2 Development of the Gini coefficient in percent in the United States from 1970 to 2010^[5]

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This brings us to the question of whether the Kuznets curve rises in the case of developed market and service economies, and, if so, what the causes are for the increase in the Gini coefficient. The question will now be examined in more detail in the case of Germany.

3. What Is Meant by Income?

Income is the sum of goods and money income that accrues to any person in a household or a firm in a given period. In the economic production process, income arises as compensation for the use of production factors (performance income). Other income sources include wages and salary as compensation for work done, rents and leases in exchange for temporary provision of land and other physical capital, interest in exchange for the provision of money and profit (or loss) as a risk premium. The functional income distribution results from the remuneration of production factors. The distribution of performance income to the economic subjects is called the primary distribution of income.^[6]

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^[1] see: Storbeck, p. 1

^[2] see: Southgate et al., pp. 184-185

^[3] see: Southgate et al., p 184

^[4] see: Southgate et al., p. 186

^[5] Figure by the author based on input from: US Census Bureau 2012

^[6] see: Konrad Adenauer-Stiftung, p. 1