Distribution of wealth

Labor and Capital Incomes

In exchange relations two actors come to an agreement to trade with each other on mutually agreed-upon terms. Something is delivered, and something is expected in return, in a quid pro quo (“something for something”) relation. In product and labor markets, exchanges typically involve a flow of goods or services from seller to buyer, in return for a monetary payment. The monetary payments in turn create flows of labor and capital income. For example, when customers buy shoes from a mall shoe store, the incomes created include the payment of a wage to the shoe salesperson, rent to the owners of the mall, and profits to the owners of the business. Labor income is compensation received by workers in the form of wages, salaries, and fringe benefits. Capital income includes rents, profits, and interest. (“Rent,” as economists use the term, refers not just to rent for housing, but to payments for the use of any asset).

Economists have, historically, engaged in vigorous debate about whether profits, rents, and interest income are compensation for productive activities. Some economists argue that such capital incomes are payments that are absolutely necessary and justified for the undertaking of production. Interest, they argue, is what gives people the incentive to save and invest, rather than spending all their income on immediate consumption. Rents encourage people to devote their assets to the most productive uses. Profits, these economists claim, represent a return to an entrepreneur’s contribution of creative talent and compensation to investors for their willingness to take risks. Such economists take a classical view of markets, and believe that markets always generate the appropriate reward.

When profits, rents, and interest seem excessive, however, they have often become controversial. Most economists believe that there is a legitimate role for fair and reasonable profits and dividends, interest payments, and rents. But many economists also acknowledge that ill-gained or excessive capital incomes do not serve the social good. Persistently high profits may be a sign that a company has market power, indicating that a market is not competitive. Substantial profits might not be a sign of economic health, if the companies who earn them create significant negative social or environmental externalities in the process of getting them. Large capital incomes that arise from practices that violate the human dignity of workers are also socially harmful. When high capital incomes contribute to a concentration of wealth and power, political democracy itself may be threatened. Profits, interest and rents are legitimate compensation, in this view, only if they are earned and used in ways that serve the common good as well as the good of the individual owner of capital.

Transfers and Taxes

While incomes from production are vital to supporting economic life, distribution by means of one-way transfer also has a very significant role to play in explaining distribution in contemporary economies. Transfers are flows of money, goods, or services for which nothing specific is given in return—or at least nothing specific at the current time. Transfers can take place between individuals, or between the government and individuals; macroeconomists are particularly interested in transfers involving government.

Transfers from the government are often made in response to people’s dependency needs. Our individual basic needs during some portions of our lifetimes—as infants and children, or when incapacitated by age or illness—cannot be satisfied through exchange, because we have little or nothing to give at those times. During childhood we have no choice but to rely on others—in our families, communities, and nations—to transfer to us the care, shelter, food, etc. that we need to survive and flourish. We may need such transfers again later in life if we become unemployed or incapacitated by injury, ill-health, or old age. Some government programs deliver specific goods and services directly as in-kind transfers, such as when public schools deliver education services, government programs provide free medical services, or international aid programs deliver food.

In the United State, the government runs various cash transfer programs designed to help households achieve income security. Economists often distinguish between two major types.

In the case of social insurance programs, transfers are designed to help people if certain specific events occur. Since no one can predict how long into old age they will live, or whether unfortunate events will befall them, it is difficult for a worker to know just how much to save for retirement or “for a rainy day.” By coming together to create a pool of social insurance, people can be assured of basic provisioning even if their personal needs turn out to exceed their personal savings. Social insurance programs in the United States include the federal Social Security and Medicare programs (mostly for retired persons) and programs at all levels of government that have been designed to help workers and their families should a worker suffer a disability or a period of unemployment. Eligibility for these programs generally depends on a family member having been in the paid labor force for a period of time, but does not depend on the income or wealth of the recipient.

Means-tested programs, on the other hand, are intended to help people who simply have insufficient resources. Unlike most of the social insurance programs, recipients do not need to have established a substantial history of market work in order to qualify for means-tested benefits. Also unlike the social insurance programs, recipients must demonstrate that their other means of support (income and resources) are very low. In recent years, access to means-tested programs in the United States has become increasingly restrictive, with many now limiting assistance to a certain number of months and/or requiring recipients to work a minimum number of hours per week to stay eligible.

Other funds flow towards the government. The federal income tax collects taxes on both wage income and many forms of capital income. Most states also collect income taxes, and you are probably familiar with state sales taxes from your purchases at retail stores. Many localities collect taxes on real estate, figured as a percentage of the value of the property. A progressive income tax system is a system that taxes higher-income households more heavily, in percentage terms, than lower-income households. A progressive tax embodies the principle that those with high incomes should pay more in taxes because of their greater ability to pay without critical sacrifices. While a very poor household, for example, might have to give up eating some meals in order to pay even a small percentage of their income in taxes, a very rich household could pay a substantially larger percentage without much loss in well-being. A proportional income tax applies the same percentage tax rate to all income levels. A regressive income tax applies a higher tax rate to poorer households.

For example, a 10% proportional tax would collect $1,000 from someone with an income of $10,000 per year, and $100,000 from someone with an income of $1,000,000 per year. If, instead, the system collected 10% from the poorer person and more than 10% from the richer, it would be progressive. If the richer person pays a smaller percentage, the tax is regressive. In the U.S. the federal income tax is a progressive tax, although the rates paid by the highest earners have dropped over time. Sales taxes on basic consumer goods, on the other hand, tend to be regressive, since poorer people spend a larger proportion of their income on such goods.

The Distribution of Income

Table 1 Distribution of U.S. Household Income in 2003
Group of
Households
Share of
Aggregate Income
Lower Limit
of Each Fifth
Poorest fifth 3.4%
Second fifth 8.7% $17,984
Middle fifth 14.8% $34,000
Fourth fifth 23.4% $54,453
Richest fifth 49.8% $86,867
Richest 5% 21.4% $154,120
Source: U.S. Census Bureau, Historical Income
Tables – Households, Tables H-1, H2.

How is income distributed across households? Where do you stand, in terms of outcomes of the distributional process? Is your family in the top, middle, or lower portion of the income distribution?

The U.S. Census Bureau has, for a number of decades, published information on the distribution of incomes in the United States, as shown in Table 1 for 2003. The Census Bureau measures incomes by summing up households’ incomes from wages and salaries, rent, interest, and profits, and cash transfer payments received from government agencies.

To understand what this table means, imagine dividing up U.S. households into five equal-sized groups (called “quintiles”), with the poorest households all in one group, and then the next poorest in the next group, and so on. The last group to be formed has the richest one-fifth (or 20%) of households. The highest-income household in the poorest group would, according to Table 1, have an income just short of $17,984. This group, the poorest fifth, received 3.4% of all the household income in the country. The richest fifth, those with incomes of $86,867 or more, received 49.8%—essentially half—of all the income received in the United States

Suppose we look at just the top 5% of households by income. Households in this very top group have annual incomes above $154,120. In 2003, this group—containing one-twentieth of the total population—received just over one-fifth of the total income in the country.

Measuring Inequality

caption Figure 1: Lorenz Curve for U.S. Household Income, 2003. A Lorenz curve is a way of graphically portraying an income distribution. For example, point C indicates that the poorest 60% of households received about 27% of total household income. If income were perfectly equally distributed, the Lorenz curve would be a straight line from the origin to point F. (Source: GDAE)

Economists frequently use a graph called the Lorenz curve—named after the statistician who first developed the technique—to describe the pattern of inequality within an economy. A Lorenz curve for household income in the United States, based on the data in Table 1, is shown in Figure 1. To construct this curve, you first draw a rectangle, as shown in the figure. The horizontal axis represents households, lined up from left to right in order of increasing income. The vertical axis measures the cumulative percentage of total income received by households up to a given income level.

In our example, the data shown in Table 1 are entered into the Lorenz curve in Figure 1 as follows. First, point A represents the fact that the lowest 20% of households received 3.4 % of total income. Point B indicates that the lowest 40% of households received 3.4%+8.7% = 12.1% of total income; point C indicates that the lowest 60% of households received 3.4%+8.7%+14.8% = 26.9% of total income; point D similarly shows the income of the lowest 80%, and point E the income of the lowest 95%. The Lorenz curve must start at the origin, at the lower left corner of the square (since 0% of households have 0% of the total income) and end at point F in the upper right corner (since 100% of households have 100% of the total income).

If income were distributed equally among all households, the Lorenz curve would be a straight line connecting the origin and point F (the diagonal line in Figure 1). This line thus represents a situation of maximum equality. At the other extreme, if one household received all the income, then the Lorenz curve would hug the horizontal axis until all but the very last household was accounted for and then shoot up to point F, just in front of the right-hand-side vertical axis. Such a line would represent a situation of maximum inequality.

caption Figure 2: The Gini Ratio, A/(A + B). The Gini ratio (or Gini coefficient) sums up the income distribution in a single number: the ratio of the area A to the sum of the areas A and B. If income were perfectly equally distributed, the Gini ratio would be equal to 0. (Source: GDAE)

In all real situations, Lorenz curves for distributions of income will fall between these extremes. Graphically, the curve will sag downward to some extent below the diagonal — as in Figure 1. The more the curve sags, the greater is the extent of inequality in the income distribution. This observation led an economist by the name of Corrado Gini to introduce a numerical measure of inequality known as the Gini ratio, which is defined as the ratio of the area between the Lorenz curve and the diagonal to the total area under the diagonal line. Referring to areas A and B in Figure 2, the Gini ratio is A/(A+B). Clearly, the Gini ratio can vary from 0 for perfect equality to 1 for complete inequality. The Gini ratio for U.S. household income in 2003 was 0.464.

The Gini ratio for the U.S. is higher than that of all other industrialized countries, signifying that the U.S. has a greater degree of income inequality. The Gini for Canada, for example, is about 0.32, while the United Kingdom has a Gini of 0.36, Germany about 0.30, and Japan and Sweden both about 0.25. Countries with more unequal distributions of income than the U.S. tend to be less industrialized countries, like Brazil (0.59) and Nigeria (0.51).

Perhaps, you might object, something is wrong with the measure of income we are using. Shouldn’t the effect of tax and transfer programs be more fully included? The U.S. Census Bureau has experimented with at least 15 different definitions of personal income, each of which includes a different way of accounting for income, taxes and transfers. In one definition, for example, it subtracts the value of government transfers and adds in the value of health insurance fringe benefits paid by businesses for their (often middle-class or higher) employees and the value of net capital gains (these are usually earned by the relatively wealthy). Under this definition, the Gini ratio, not surprisingly, rises to over 0.5, showing greater inequality. The share of the bottom fifth drops considerably, while the share of the top fifth rises. Another measure adjusts for the effects of the tax system. This causes some change at the top, but little at the bottom. When they further add in the effects of both cash and non-cash government transfer programs (such as food stamps), the Gini ratio drops down closer to 0.4.

Government tax and transfer policies—and especially the transfer side—have significant effects on the U.S. household income distribution. Even with the most thorough accounting for transfer aid to low-income households, however, the income of the top fifth of the population is still roughly ten times that of the bottom fifth.

Some important goods and services are obtained, of course, without the use of cash income. Many families prefer to produce at least some services (such as child care and cooking) for themselves. In addition, many of the things we enjoy, such as pleasant parks, safe roads, or clean air add to our well-being without requiring payments out of our cash income. If we were to look at the distribution of well-being rather than just the distribution of income, we would need to take account of these non-income sources of important goods and services. No such comprehensive study has been done. Some of these goods may contribute to lessening inequality – for example, everyone, rich or poor, can enjoy a public park or use a public library. Evidence suggests, however, than at least in some cases the distribution of such non-purchased goods may accentuate, rather than lessen, measures of inequality. Proponents of “environmental justice” for example, point out that polluting industries and toxic waste disposal sites tend to be disproportionately located near poor and minority communities.

Income Inequality Over Time

caption Figure 3: Income Shares of the Richest and Poorest Households, 1968-2003. Inequality in the United States has been increasing since 1968. The share of the richest households in aggregate income rose from about 17% to about 22%, while the share of the poorest 20% of the population fell from about 4% to about 3.5%. (Source: GDAE)

The U.S. household income distribution has been recorded every year since 1967. A similar but not quite identical measure, the family income distribution, has been recorded since 1947. These data show that inequality was gradually decreasing—that is, income was becoming more equally distributed—until 1968. In that year, the Gini ratio for household income was 0.388, the lowest (most equal) on record in the United States. Since 1968 the Gini ratio has increased in almost every year.

Figure 3 shows what has happened in recent decades at the very top and the very bottom of the income distribution. The general trend has been for a larger share of income to go to the very richest households (from about 17% in 1968 to about 22% in 2003), while the share going to the bottom (and, not shown in this figure, the middle) quintile(s) has gradually fallen.

Why has income inequality been increasing in the United States over this period? One point economists agree on is that some of the increase in inequality has been due to changing demographic characteristics of the U.S. population.

Increases in the proportion of the population that is aged, and increases in single parenthood, have tended to drive down incomes at the low end. People too old to work and people in single-parent households (where paid work and caring activities compete for a limited resource—the adult’s time) often lack economic resources. About 18% of U.S. children live in poor families. Meanwhile, the entry of women into the labor force in increasing numbers has helped boost the incomes of married-couple households at the top. Demographic change, however, is only part of the story and cannot explain the whole pattern of increasing inequality. Economists continue to debate the relative importance of at least three other explanations. (Note that all three explanations propose reasons why the poor have become poorer or more numerous, while the third one also addresses why the rich have gotten richer.)

First, international trade has been increasing. Competition from imports has eliminated many industrial jobs that formerly fell in the middle of the U.S. income distribution. If middle-income industrial jobs are replaced by lower-income service and retail jobs, inequality will increase.

Second, new technologies such as computers and biotechnology have become more important, increasing the incomes of skilled workers who understand and use the new techniques and equipment, while leaving behind the less-skilled workers who remain in low-technology occupations.

Finally, unions have grown weaker and government policy has become markedly less supportive of unions and low-wage workers, while the compensation given to top executives and board members of large corporations has skyrocketed. According to studies done by Business Week, in 1980 chief executive officers (CEOs) of large U.S. corporations earned an average of 42 times the amount earned by the average hourly worker. In 1990, they earned 85 times as much. In 2000, they earned 531 times as much.

In short, along with demographic change, global competition, technology, or changes in government and business policies—or some combination of these factors—may account for the rise in inequality within the U.S.

Wealth Inequality

The distribution of wealth—what people own in assets (a stock)—tends to be much more unequal than the distribution of income—what people receive in the course of a year (a flow). Most people own relatively little wealth, relying mainly on labor income and/or government, nonprofit, or family transfers to support their expenditures. It is possible to have negative wealth. This happens when the value of a person’s debts (such as for a car, house, or credit cards) is greater than the value of her assets. For people in the middle class, the equity they have in their house is often their most significant asset. On the other hand, those who do own substantial physical and financial wealth are generally in a position to put much of it into assets that increase in value over time and/or yield flows of capital income—which can in turn be invested in the acquisition of still more assets.

The distribution of wealth is, however, less frequently and less systematically studied than the distribution of money income. Partly, this is because wealth can be hard to measure. Much wealth is held in the form of unrealized capital gains. A household receives a capital gain if sells an appreciated asset, such as shares in a company, land, or antiques, for more than the price at which it purchased the asset. An asset may appreciate in value for a long time before it is actually sold. No one, however, will know exactly how much such an asset has really gained or lost in value until the owner actually does sell it, thus “realizing”—turning into actual dollars—the capital gain. Another reason why it is harder to get information on wealth is that—while people are required to report their annual incomes from wages and many investments for tax purposes—the government does not require everyone to regularly and comprehensively report their asset holdings.

One study estimates that the Gini ratio for the distribution of wealth in the United States was 0.83 in 2001—indicating much more inequality than is found in the distribution of income. It has been estimated that in 1998 the top 1% of U.S. households owned about 38% of all household assets, and the top 10% owned about 71%, while the bottom 40% owned only 0.2%.

Further Reading



Disclaimer: This article is taken wholly from, or contains information that was originally published by, the Global Development And Environment Institute. Topic editors and authors for the Encyclopedia of Earth may have edited its content or added new information. The use of information from the Global Development And Environment Institute should not be construed as support for or endorsement by that organization for any new information added by EoE personnel, or for any editing of the original content.

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Citation

Ackerman, F., Goodwin, N., Nelson, J., Weisskopf, T., & Institute, G. (2006). Distribution of wealth. Retrieved from http://www.eoearth.org/view/article/151755

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