{"id":1151,"date":"2014-02-12T17:28:13","date_gmt":"2014-02-12T16:28:13","guid":{"rendered":"https:\/\/blog.iese.edu\/economics\/?p=1151"},"modified":"2014-02-13T11:04:06","modified_gmt":"2014-02-13T10:04:06","slug":"one-solution-for-income-inequality-marry-someone-poorer-than-you","status":"publish","type":"post","link":"https:\/\/blog.iese.edu\/economics\/2014\/02\/12\/one-solution-for-income-inequality-marry-someone-poorer-than-you\/","title":{"rendered":"Marry Someone Poorer than You, Reduce Income Inequality"},"content":{"rendered":"

Everybody is talking about inequality and everybody seems to have their own favorite culprit, from globalization, to deregulation, to skill-biased technical change, and political capture<\/strong>. Yet a recent paper<\/a> by Greenwood, Guner, Kocharkov and Cezar Santos (Greenwood, Jeremy, et al. \u201cMarry Your Like: Assortative Mating and Income Inequality.\u201d National Bureau of Economic Research<\/i>, No. w19829, 2014)\u00a0suggest an additional factor much closer to home: whom you marry<\/strong>.<\/span><\/p>\n

\"Just_married_sign_on_cart\"<\/a><\/p>\n

The argument is simple: Go back to the 1950s<\/strong> when few women worked. As a result, back then household income inequality was largely determined by the income of the men of the house<\/strong>.\u00a0 However, as it was more likely that women married to poorer men worked, household income inequality was actually slightly lower<\/i> than it would have otherwise been with male earnings only.<\/p>\n

Now, fast-forward to the present day, when most women in the developed world<\/strong> have joined the labor force and contribute significantly to household income<\/strong>. All else equal, this should reduce household income inequality<\/strong> as women\u2019s income contributes to smoothen the disparity from men\u2019s income in household income inequality.<\/p>\n

People tend to marry people with a similar profile<\/strong>
\n<\/strong><\/h3>\n

However, people don\u2019t just marry randomly<\/strong>. They tend to marry people with a similar profile<\/strong>, both in terms of income and educational background. This result is on the one hand very intuitive to understand. Romantic serendipities aside, an individual is more likely to primarily be exposed and relate to another individual having a similar social and educational background<\/strong> and, ceteris paribus, more educated and wealthier parents will create more opportunities for their children*.<\/p>\n

They confirm this result constructing contingency tables for years 1960 and 2005 finding both that the ratios of the sums of diagonal elements for both years is larger than one. This finding implies that the number of matches between husband and wife with the identical education level is larger <\/span><\/a>\u00a0<\/strong>than what would occur if matching were random.<\/p>\n

Economists use the Gini-coefficient to measure income inequality<\/strong>. It is always between zero and one with zero being complete income equality and one being complete income inequality (one guy has the income of the whole society). Second, the ratios increase over time. If matching in 2005 between husbands and wives had been random, instead of the pattern observed in the data, the Gini coefficient would have fallen from the observed 0.43 to 0.34.<\/strong> Interestingly, 0.34 is exactly what household income inequality was in 2005. Hence, completely random marrying would have cancelled the rise in household income inequality since 1960.<\/p>\n

The policy implications of this insight are not clear<\/strong>; the analysis does demonstrate the multifaceted causes of rising income inequality, and shows that they go way beyond the scope of just economics<\/strong>.<\/p>\n

Authors: Prof. Morten Olsen and Ria Ivandic<\/strong><\/em><\/p>\n

\n
*Parents who graduated from university are far more likely than non-graduates to raise children who also earn degrees. This is true in all countries, but more so in America and France than in Israel, Finland or South Korea, according to the OECD<\/a>. On average, 20-34 year-olds from a highly educated family are almost twice as likely to be in higher education than their peers.
\n<\/a><\/address>\n
\u00a0<\/address>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Everybody is talking about inequality and everybody seems to have their own favorite culprit, from globalization, to deregulation, to skill-biased technical change, and political capture. Yet a recent paper by Greenwood, Guner, Kocharkov and Cezar Santos (Greenwood, Jeremy, et al. \u201cMarry Your Like: Assortative Mating and Income Inequality.\u201d National Bureau of Economic Research, No. w19829, […]<\/p>\n","protected":false},"author":886,"featured_media":1152,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[19450],"tags":[560,90840,71835],"class_list":["post-1151","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-social-trends","tag-education","tag-inequality","tag-social-trends-2"],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/posts\/1151","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/users\/886"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/comments?post=1151"}],"version-history":[{"count":7,"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/posts\/1151\/revisions"}],"predecessor-version":[{"id":1160,"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/posts\/1151\/revisions\/1160"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/media\/1152"}],"wp:attachment":[{"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/media?parent=1151"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/categories?post=1151"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.iese.edu\/economics\/wp-json\/wp\/v2\/tags?post=1151"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

Compared with a world in which people married randomly, this turns out to be a large contributor to household income inequality<\/strong>. Greenwood et al.<\/em> (2014), using data on hundreds of thousands of households from the United States Census Bureau in the period 1960 to 2005, find that a growing tendency to find a partner from a similar educational and professional background is exacerbating income trends <\/span><\/a>. In a regression analysis they find that the additional impact of a husband\u2019s education on his wife\u2019s education relative to the baseline year (1960) is increasing, implying the degree of assortative mating has increased.<\/p>\n