Economic analysis is often geared to understand average effects of policies & programs; policies usually target the average person or firm. It’s important to understand underlying causes behind inequalities we observe, be it in income, income growth, health or other indicators.
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The United States, as a massive country, has rich variety in race, income, health and almost any other indicator one may imagine. This map shows spatial differences in patterns of race, income, and health outcomes in the contiguous United States.pic.twitter.com/VYDeatyfKS
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Starting today, we are running a series of 7 blog posts, each of which either focuses on an interesting heterogeneity and its effects or focuses on a heterogeneity in an economic indicator and delves deeper to understand the root causes underlying it.
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NEW: Some Places Are Much More Unequal than Others → https://nyfed.org/2LQQzlA pic.twitter.com/ZRlIoy87an
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Economic inequality in the United States is much more pronounced in some parts of the country than others. The most unequal places tend to be large urban areas with strong economies where wage growth has been particularly strong for those at the top of the wage distribution.pic.twitter.com/qC22Tzm9qK
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The least unequal places tend to have relatively sluggish economies that deliver slower wage growth for high, middle, and lower wage earners alike and are concentrated in the Rust Belt.pic.twitter.com/q7ri54PtS4
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While technological change and globalization have been the key drivers of these geographic patterns, there are two other important factors contributing to and reinforcing regional differences in wage inequality.
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Agglomeration economies—or the benefits that arise when people and firms locate in large numbers near one another in cities—have enhanced the productivity and wages of skilled workers in large, dense metropolitan areas.
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There are vast differences between individuals in the United States in lifetime earnings—total income from wages, salaries and self-employment income over ages 25 to 55.pic.twitter.com/JGeNXDHxzb
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Compared to individuals in the bottom 10th percentile of the population, those in the 90th percentile earn around 7x more, and those in the top percentile earn almost 20x more.pic.twitter.com/p5zdnlE4kd
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In lifetime earnings, male workers at the median experience a 60% annual wage increase over the course of their careers. Those at the lower end, conversely, may experience a decline in their annual wages over the same period, while top 1% of lifetime earners see a 2700% increase.pic.twitter.com/l0t8LyXQuM
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Individuals with lower incomes (below the bottom 20%) are significantly more likely to become unemployed compared to top earners, which can lead to long-lasting effects on their subsequent employment and earnings.
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What accounts for these vastly different experiences in the labor market? Previous research has shown that the “job ladder” is important for wage growth. To move to better jobs, workers first need to be able to hold on to the ones they have.
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This chart shows that low income earners indeed face a much larger risk of losing their job—and by a large margin: Individuals at the bottom quintile are more than 3x more likely to become unemployed than those in the top quintile.pic.twitter.com/VIxsYocDmj
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We also looked at job finding rates. Nearly 80% of unemployed in top group are employed again after 4 months, compared to 31% of lowest earners. Low-income earners lose their job frequently & go through longer unemployment spells, underscoring a less stable job ladder.pic.twitter.com/28zInLwOux
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With a high risk of job loss, a longer time to find jobs and a much lower likelihood of being contacted by better employers, it is no surprise that there arise huge differences in earnings growth over a thirty year period.
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NEW: Who Borrows for College—and Who Repays? https://nyfed.org/2nA9kR6 pic.twitter.com/NTMQHKvmLt
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As the student loan program has played an increasing part of higher education finance, it’s come with a share of challenges. The growth in balances overall has been due to an increase in both average balances and prevalence, when balances on other types of debt contracted.
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Aggregate student loan balances neared $1.5T in Q2 2019, more than 5x nominal terms from start of 2003. The rapid growth of the aggregate balance was due to increases in number of borrowers & nearly 3x average balance per borrower, from $13,300 in 2003 to $33,500 in 2019.
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Repayment on student loans has been slow, with high delinquency and default rates. Overall, 15% of Q2 2019 borrowers were 90 or more days past due or in default on a student loan, an improvement from 2013, when the share peaked at over 17%.
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Ten years after leaving school, 2005 grads had repaid under 40% of their outstanding balances; 2010 grads fared especially poorly, with only 9% of their balances repaid 5 years after graduating. Slow repayment has contributed to the burgeoning aggregate balance.pic.twitter.com/Rn0acNA9ED
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The student loan program by design distributes loans to borrowers across the income spectrum without regard to credit-worthiness. Although higher-balance borrowers are only 6.8% of the 43.4M borrowers, their balances add up: they owe 35% of the aggregate student loan debt.pic.twitter.com/qCRGDCZZvu
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Debt burdens are somewhat constant across income quartiles, notable especially given the wide gaps in income (and educational attainment) in the United States. But, this difference in average balances is dwarfed by the differences in income across the distribution.pic.twitter.com/Wxs9DWAkHp
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Consequently, borrowers from poorer areas are more likely to struggle with repayment and have higher delinquency rates. In the top quartile, just over 9% of borrowers are 90+ days past due or in default on their student loan, lower than the 23% rate seen in the first quartile.pic.twitter.com/kgILqLkJ1w
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Although delinquency rates in higher-income areas are lower, there remains a large share of borrowers who have not reduced their balances since one year ago. This category may include borrowers who are either still enrolled, recently graduated, or on some type of repayment plan.pic.twitter.com/134oxw6xQS
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NEW: Is Free College the Solution to Student Debt Woes? Studying the Heterogeneous Impacts of Merit Aid Programs → https://nyfed.org/31393DN pic.twitter.com/XMsvVjoxMc
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The rising cost of a college education is an important topic of discussion among policymakers & practitioners. At least 11 states have recently introduced programs to make public 2-year education in the state tuition free. 27 states have implemented some type of merit aid.
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Investigating the effects of these programs gives us insight into the implications of lowering college cost. To do this, we compared outcomes of students who were merit eligible because of their home state and year of birth with those that were not merit eligible.
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