{"id":14628,"date":"2014-01-29T13:49:31","date_gmt":"2014-01-29T18:49:31","guid":{"rendered":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/short-reads\/%year%\/%monthnum%\/%day%\/new-academic-study-links-rising-income-inequality-to-assortive-mating\/"},"modified":"2024-04-14T03:23:11","modified_gmt":"2024-04-14T08:23:11","slug":"new-academic-study-links-rising-income-inequality-to-assortive-mating","status":"publish","type":"short-read","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/short-reads\/2014\/01\/29\/new-academic-study-links-rising-income-inequality-to-assortive-mating\/","title":{"rendered":"New academic study links rising income inequality to \u2018assortative mating\u2019"},"content":{"rendered":"
\"Women<\/a><\/p>\n

\"Bride<\/a>
\u00a9 Dejan Ristovski \/ istockphoto<\/figcaption><\/figure><\/figure>\n\n

Here\u2019s another reason the rich are getting richer and the poor are falling farther behind:\u00a0 A new working paper by an international team of economists finds that better educated people are increasingly more likely to marry other better-educated people while those with less formal schooling are more likely to choose a less well-educated partner.<\/p>\n\n

As a consequence, income inequality has increased because education is strongly correlated with income\u2014the more schooling you have, the more money you typically earn, according to a team of economists headed by Jeremy Greenwood of the University of Pennsylvania.<\/p>\n\n

Economists call the tendency of people with similar characteristics to marry \u201cassortative mating.\u201d For their study, Greenwood and his team tracked patterns in marriages grouped by education level from 1960 through 2005 using U.S. Census data.<\/p>\n\n

[by education level]<\/p>\n\n\n

But the big surprises came in household income trends among couples with relatively more and relatively less education. Virtually across the board, the income gap between couples with relatively high and those with relatively low levels of education had widened substantially since 1960 relative to the average household income.<\/p>\n\n

For example, in 1960, a husband and wife, each with a high school education, would earn about 103% of the average household income.\u00a0 But in 2005, that same couple would earn only about 83% of the average. At the other end of the education spectrum, a couple in which both partners had done post-graduate work earned about 176% of the mean household income in 1960 but a whopping 219% in 2005.<\/p>\n\n

Expressed another way, the relative earnings of couples with high school degrees had fallen by 20 percentage points relative to the average while the household incomes of highly educated husbands and wives had increased by 43 points.<\/p>\n\n

To assess the overall impact of these trends on income inequality, they conducted a novel test. They first computed the overall level of income inequality in 1960 and 2005.\u00a0 Then they estimated what income inequality would have been if couples were randomly matched by education level. In effect, they asked what income inequality would have been if education didn\u2019t matter in selecting a spouse, and if men and women with lots of schooling were as likely to marry people with relatively little education as they were to choose better educated partners.\u00a0 The difference in those two numbers would mark the impact of associative mating by education on income inequality.<\/p>\n\n

The statistic they used to gauge income inequality was the Gini coefficient, which measures income inequality on a scale from zero to 1.\u00a0 Zero represents no inequality\u2014as if everyone earns exactly the same amount—and 1 represents perfect inequality, which would occur if one person earns everything and everybody else makes nothing.<\/p>\n\n

Greenwood and his colleagues estimated that the Gini coefficient was .34 in 1960, or about a third of the way to complete inequality. When they randomly matched people by education level and recalculated the coefficient, the answer was basically the same:\u00a0 The Gini coefficient still stood at .34, suggesting that assortative mating by education played little, if any, role in income inequality.<\/p>\n\n

Then they applied the same method to 2005 data. Now the overall Gini coefficient was .43, an increase of about .09 since 1960 and consistent with other research. But when they randomly matched people by education and re-ran their analysis, the Gini index plummeted to .34, showing that today, \u201cassortative mating is important for income inequality.\u201d<\/p>\n\n

One reason for these changes is because more married women than ever are joining the labor force (and marrying similarly educated men), which reinforces the income gains for better educated couples.\u00a0 Their evidence: When they randomly matched men and women by education level, income inequality in 2005 declined. (Other studies have also shown that the increase in married women\u2019s labor force participation has not been the same across education groups.\u00a0 College-educated married women have increased their work hours, so it has become even more valuable for college-educated guys to have college-educated wives, at least in monetary terms.)<\/p>\n\n

The study is the latest entry in a contested area of research to examine inequality and income of married couples.\u00a0 On the one hand, economist Gary Burtless of the Brookings Institution has found<\/a> that between 10 percent and 16 percent of income inequality in the United States \u201cwas caused by the growing correlation of earned incomes received by husbands and wives.\u201d<\/p>\n\n

Researchers Deborah Reed and Maria Cancian reported<\/a>\u00a0 in 2001 that the increasing correlation of husbands and wives\u2019 earnings in the late 1960s through the mid-1990s worked to worsen inequality. They also found, contrary to some researchers, that changes in men\u2019s earnings was the largest source of rising income inequality while changes in women\u2019s earning actually reduced the disparity.<\/p>\n\n

About the authors:\u00a0<\/i>Jeremy Greenwood is a professor of economics at the University of Pennsylvania and a research associate at the university\u2019s Population Studies Center. Nezih Guner is an adjunct professor at the Universitat Aut\u00f2noma de Barcelona and Research Professor of the Barcelona Graduate School of\u00a0Economics. Georgi Kocharkov is an assistant professor of economics at the University of Konstanz in Germany. Cezar Santos is an assistant professor of economics at the University of Mannheim in Germany.<\/p>","protected":false},"excerpt":{"rendered":"

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