Running head: INCOME DISTRIBUTION IN THE UNITED STATES Income Distribution in the United States and the Lorenz Curve
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Market economies are favored and well-known for generating macroeconomic growth and progress in industrialized nations, such as the United States. Numerous academic studies and economic research have been done not only to measure economic growth, but also to analyze any disparities in income distributions among the general American population. This paper will examine trends and patterns of American wages since the 1970s, focusing on shifts in income distributions to see if these shifts can be interpreted as income inequality across different sectors of our society. Furthermore, this paper will study two important and interlinked methods of measuring income inequality, which are the Lorenz Curve and the Gini Coefficient Index. The Executive Branch of our federal government and the U.S. Congress keep a close eye on income distributions throughout the entire nation. These bodies rely heavily on data collected and analyzed by non-partisan agencies such as the U.S. Census Bureau, the Internal Revenue Service (IRS), the U.S. Bureau of Economic Analysis, the Congressional Budget Office (CBO), and academic institutitions that provide data and statistical analysis to assist in economic and budgetary decisions made by elected officials concerning a wide array of policy issues such as taxes, social insurance programs and other issues that impact the overall economy. Economists like Thomas Piketty and Emmanual Saez and many others have used these collected data to demonstrate a historical trend in how incomes are distributed in this country and if the distributions are heavily concentrated within the top ten percent of the labor force. Piketty and Saez’s have made the observation that the years after the end of World War II and through the late 1970s, United States enjoyed a tremendous economic growth and shared prosperity. The average earnings for the lower and middle classes rose continuously until late 1970s when wages flattened, while the income for the top 10% continued to grow, widening the gap as clearly seen in figure 1 (Piketty & Saez, 2003).
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Figure 1.
One of the indicators of the widening of the income distribution gap can be seen in the progression of the federal minimum wages in this country since the 1970s. Figure 2 shows nominal (red line) and real (green line) minimum wage values that have been adjusted to 2012 dollars to show the real value of the minimum wages. We can see that in real 2012 dollars, the 1967 minimum wage rate was the highest and that starting at about 1979, the real minimum wage rate continued to drop (U.S. Bureau of Labor Statistics, 2013). Some economists agree, while others do not, that this trend of real minimum wages dropping since the late 1970s is a contributor of annual inflation-adjusted incomes being at or below the poverty line for minimum wage workers. It is important to note here that for the purpose of governmental reporting, U.S. households are ranked and divided into five quintiles according to their gross income: Lowest, Second, Middle, Fourth, 81st-99th Percentiles and the Top 1 Percent. Minimum wage earners
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which made up 4.7% of the total labor force in 2012 are included in the lowest quintiles according to the U.S. Bureau of Labor Statistics (2013). Figure 2 demonstrates the historical trend of both nominal and real minimum wage rates and Figure 3 displays the real mean household incomes by different quintiles.
Figure 2.
Inflation adjusted (real) Minimum wage (nominal)
Source: U.S. Bureau of Labor Statistics (2013)
Figure 3.
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A detailed report published by the Congressional Budget Office in 2011 affirms that the real average and inflation-adjusted household incomes increased by 62% between 1979 and 2007. Though this incline may imply a general growth, details should be looked at more closely to see who really benefitted from this income growth. The data from this CBO report shows a 275% income growth for the top 1% of the population, whereas the lowest end of the quintiles saw an income growth of about 18% (Congressional Budget Office, 2011). Figure 4 depicts the growth in real after-tax incomes that are recorded by the CBO from 1979 to 2007.
Figure 4.
275%
65% 18% 27% 35% 43%
What exactly triggered this tremendous increase in income for the top 10% and the much slower growth for the bottom 90th percentile? Studies contribute the changes to various factors, including the fast rise in earnings for top corporate executives and “superstars” such as actors, musicians and athletes, financial markets becoming more powerful, deregulation, immigration and the decline of labor unions which took away a lot of the bargaining powers that union workers used to have (Gordon & Dew-Becker, 2007). It is interesting to note that income inequality has worsened for men than for women during 1979 and 2007, mostly because more
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women joined the workforce and so, the numbers increased substantially for women as more and more women started earning wages (Kopczuk, Saez & Song, 2010). Also, since upward mobility for women has been slow during those periods and fewer women were part of the 1% or higherearning quintiles until the more recent years, income inequality was less prevalent among female workers. In fact, the gains made by women by entering the workforce have actually helped lower the total household income inequality which could have been even higher without the additional income earned by women. While real incomes grew for each quintile from 1979 to 2007 (figure 4), there was a “negative trickle-down” (Greenwood and Holt, 2010) for those households whose income declined relative to other groups in other quintiles, whether or not their real income rose in absolute terms. In essence, their share in the market income dropped as higher-income households gained a much bigger share of the market income. The uneven distribution of the market income shares is illustrated in table 1 with market income shares declining from 1979 for all quintiles, but the top 1%.
Table 1.
Shares of Market Income, 1979 and 2007 (Percent) Lowest Quintile 1979 2007 1979 2007 1979 2007 1979 2007 1979 2007 1979 2007 2.9 2.5 10.1 7.3 15.3 12.2 22.4 19.0 39.1 38.6 10.5 21.3
-14%
Second Quintile
-28%
Middle Quintile
-20%
Fourth Quintile
-15%
81st - 99th Percentiles
-1%
Top 1 Percent
103%
Source: Congressional Budget Office.
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One of the most widely-used and effective methods to measure inequality of income distribution is the Lorenz Curve. This curve was developed by economist Max O. Lorenz in 1905 to show which proportion of total income is in the hands of a given percentage of a population. This is similar to the measures done by quintiles discussed earlier, except that the Lorenz Curve compares the cumulative proportion of income to the cumulative proportion of individuals, instead of using income market shares (Bellu, 2005). The x-axis of the Lorenz Curve is the cumulative proportion of population ranked by income level, whereas the y-axis is the cumulative proportion of income for a given proportion of population which is the “income share calculated by cumulated income of a given share of population, divided by the total income”, (p.2). The formula is:
P being the total number of individuals in the distribution, Y being the total income, k is the position of each individual in the income distribution and Yi being the income of the ith individual in the distribution (p.2). The Lorenz Curve is built by plotting the numbers on a graph and then defining the “benchmark” (p.3) for the Lorenz Curve which is the equality line. This equilibrium line that coincides with the 45-degree line represents the most equal income distribution where every household in the United States would be receiving the same income. In reality, the Lorenz Curve is always below the equality line because incomes are never equal. Another essential inequality measuring method that is interconnected to the Lorenz Curve is the Gini coefficient index that measures the extent to which the distribution of income among households deviates from a perfectly equal distribution. The Gini index measures the area between the equality line and the Lorenz Curve. A Gini index of 0 means a perfect equality,
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whereas an index of 1 shows a perfect inequality (Kakwani, 1977). The Lorenz Curve has been moving outward in the U.S. and the Gini index has been increasing steadily for the last thirty years. Figure 5 shows the Lorenz Curves moving away from the equality line since the 1970s with the Gini index at 0.365 in 1979, 0.432 in 2007 and 0.451 in 2012 (U.S. Census Bureau, 2013). These figures surely confirm that income inequality in America grew from 1979 to 2007. Also, the Gini index is essentially used to compare inequality rates between different nations. According to the World Factbook published by the Central Intelligence Agency in 2013, the United States ranked 99 in income equality out of 139 countries total.
Figure 5.
Equality
% of national income (cumulative)
Line Lorenz Curves
Gini coefficient index area
% of population (cumulative)
Year/Curves: 1976 2007 2012 Gini Coefficient: 0.365 0.432 0.451
Source: U.S. Bureau of Labor Statistics
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Based on historical data findings on income distribution in the United States for the purpose of this research paper, it is rational to concur that there is a continuing rise in inequality among the different categories of wage earners in the United States since the late 1970s. As the U.S. Gross Domestic Product (GDP) rate continues to be the strongest in the world and consumption keeps our economy strong, it is absolutely incomprehensible as to why we have so much disparity in incomes in this country. This is why the study of income inequality should be of even more fundamental importance to the government and economists who continue to monitor changes in the Lorenz Curve and the Gini indexes. By studying the trends in inequality over time, our federal government should use the data more progressively to make betterinformed policy changes such as adjusting the tax rates, investing in education, especially for those who are in the lower income quintiles, raising the minimum wage rate, and imposing regulations on banks and financial institutions who tip off the income equality scale by paying their executives unimaginably high wages. There is no arguing against the tremendous benefits of market economies and the suggested resolution is, by no means, to redistribute wealth in the U.S., but rising income inequality ultimately affects our society as a whole because it hinders economic growth, causes higher levels of poverty, demoralizes large segments of our society, and consequently does not paint an ideal socio-economic picture of a righteous and great nation such as the United States that takes pride in being an exemplary icon for other economies to emulate.
INCOME DISTRIBUTION IN THE UNITED STATES References Bellu, L.G. (2005). Charting Income Inequality. United Nations Food and Agriculture Organization, module 000. Retrieved from http://www.fao.org.
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Congressional Budget Office, United States Congress. (2011). Trends in the Distribution of Household Income between 1979 and 2007. Retrieved from http://www.cbo.gov. Gordon, R.J. & Dew-Becker, I. (2007). Selected Issues in the Rise of Income Inequality. Brookings Papers on Economic Activity, 2007(2), 169-190. Retrieved from http://www.jstor.org. Greenwood, D.T. & Holt, R.P. (2010). Growth, Inequality and Negative Trickle Down. Journal of Economic Issues 44(2), 403-410. Retrieved from http://www.metapress.com. Kakwani, N.C. (1977). Applications of Lorenz Curves in Economic Analysis. Econometrica, 45(3), 719-728. Retrieved from http://www.jstor.org. Kopczuk, W., Saez, E., & Song, J. (2010). Earnings Inequality and Mobility in the United States: Evidence from Social Security Data since 1937. Quarterly Journal of Economics, 125(1), 91-128. Retrieved from http://www.jstor.org. Piketty, T. & Saez, E. (2003). Income Inequality in the United States, 1913-1998. Quarterly Journal of Economics, 118(1), 1-39. Retrieved from http://www.oxfordjournals.org. United States Bureau of Labor Statistics, Department of Labor. (2013). Characteristics of Minimum Wage Workers: 2012. Retrieved from http://www.bls.gov. United States Census Bureau. (2013). Current Population Survey, Annual Social and Economic Supplements. Retrieved from http://www.census.gov. 