Income inequality in the United States has been moving steadily upward for decades. By contrast, during the post-war era, the distribution of income was fairly stable and relatively egalitarian. The Gini coefficient of income inequality, changed very little between 1947 and 1968, when it hit a historic low. However, since this time, it has moved steadily upward, reaching an all-time high in 2015.
What has caused this pronounced shift
in the US income distribution?
In a recent study, I argue that the decline of organized labor has contributed more significantly to rising income inequality in the United States than prior research realizes.
More than 20 years ago, William Julius Wilson wrote that work had disappeared from inner-city neighborhoods. Since then, joblessness has continued to rise—particularly among black men without high school degrees.
In 2016, nearly 50% of less-skilled black men were jobless.
When regular, stable jobs disappear from poor neighborhoods, what type of work do people find? It is well recognized among research scholars that people often cobble together temporary gigs, seasonal positions, and self-employment as a survival strategy to make ends meet.
However, there are few studies that examine this type of employment in a systematic and detailed way due to the methodological challenges of capturing unstable and irregular work experiences.
In a recent study of employment among men recently released from prison, I asked How often and how regularly do people find work? What kind of work do they do, and how consistently do they do it?
Using daily measures of job search and work collected from smartphone surveys, I documented the extreme irregularity of work in people’s everyday lives. I found that the type of work—from landscaper to warehouse worker to concession stand operator—changed nearly as often as the presence of work itself on any given day.
I proposed the concept of work as foraging to emphasize this depth of instability and variation across job types. The term foraging was originally used in employment research to describe the pursuit of short-term income-generating opportunities to maximize profit.
As borrowing rates climb to record highs, one could say that consumers and their banks have never been closer. Generally, we consider these ties to be very formal, with banks and consumers connected only at arm’s length.
Yet in many settings, lenders and borrowers do develop personal relationships. For example, small business owners establish personal relationships with bankers in an effort to secure loans, and lenders build personal relationships with borrowers as a way of gaining access to private information that may affect loan repayment.
Racial and ethnic disparities in wealth in the United States are enormous. In 2016, the median non-Hispanic white household held over $150,000 more net worth than the median non-Hispanic black household and the median Hispanic household.
But the gaps are much smaller among young adults, who tend to have little wealth regardless of race or ethnicity. To understand how today’s middle-aged black, Hispanic, and white adults achieved widely divergent wealth levels, we need to look to the past, as these households either built their nest eggs or faced barriers to accumulating wealth.
In a recent study, we examine how individuals entering adulthood in the United States around 1980 accumulated wealth through their 20s, 30s, and 40s. We find that about half of the accumulation gap can be explained by a legacy of disadvantage for blacks and Hispanics, while the rest of the accumulation gap is created fresh in the current generation.
In the labor movement’s heyday during the 1950s, about one-third of American workers in the private sector belonged to a union. By the late 1970s, that fraction had fallen to roughly 1 in 5. Today, about 1 in 20 private sector workers belong to a union.
This level of unionization places the U.S. near the bottom among advanced democracies. In France, Sweden, and Denmark, over 80 percent of the total workforce is covered by union-negotiated agreements. Over half of the German workforce is covered, and Canada’s coverage rate is roughly double that of the U.S.
Because unions garner generally higher wages for their members – roughly 10 to 25 percent higher than for non-union members – their erosion has meant that workers who may have once belonged to one miss out on this premium.
Strong unions boost the wages of workers who don’t belong to one, too.
Business people working on laptops during a meeting
There is widespread ethno-racial segregation between workplaces in the US, even within the same job sector. Research suggests that as many as 50 percent of all African American and Hispanic workers would have to change jobs to achieve integrated workplaces.
Employers contribute to this segregation through hiring decisions, but what is the role of the choices that we, as employees, make when looking for a workplace? People tend to live, work and socialize within their own ethno-racial group. This has both positives and negatives.
On the positive side, a segregated city may offer a safe zone for individuals belonging to discriminated minorities. In a community with similar others, spaces can be created where the larger society’s racial hierarchy does not apply. On the negative side, the problem is that in societies where there is a lot of ethno-racial inequality, segregation tends to reinforce these differences.
In segregated societies, minorities tend to live in impoverished areas with high crime rates and poor public and commercial services. We know from previous research that ethno-racial inequality is also connected to occupational segregation: children of poor families tend to aim for blue-collar jobs, while children of wealthy families tend to aim for high-level white-collar jobs.
What has been less known, is what causes segregation between workplaces in the same sector. The aim of our study was to find another piece of the puzzle.
Americans love to change their jobs. One of the primary reasons many individuals change companies is undoubtedly the promise of higher wages. Recently however, researchers have begun to examine the extent to which changing jobs benefits men more than women.
The reasons men may see a larger salary increase than women following a job change can be classified into two broad categories. The first category involves the characteristics and treatment of individual men and women. Examples include gender discrimination in hiring practices as well as gender role socialization, e.g. women being reluctant to negotiate for higher wages in the hiring process out of a fear of being or being perceived as too aggressive.
The second category relates to the fact that men and women tend to be employed in different occupations, e.g. occupational segregation. Not only do the occupations that tend to employ men typically pay more, these occupations may also offer greater potential for “job-shopping”, e.g. raising one’s salary by finding a position at a competing firm that is willing and able to pay higher wages.
Are smart machines coming for our jobs?
In the past, technological change has generally led to the displacement of workers from some jobs, but also to the creation of new work. For example, as automation reduced the number of workers needed to grow and harvest crops in the early 20th century, technological change resulted in employment gains in the manufacturing and service sectors.
Today, however, many worry that the historical link between technological innovation and job creation may be coming to an end.
Big data and artificial intelligence make it possible for computers to perform tasks that previously required complex human cognition. Software algorithms are already driving cars, diagnosing diseases, and writing news articles.
A credible case can be made that, thanks to the rapid development of AI, this wave of technological change will usher in an era of widespread unemployment.
Most contemporary inquiries into the future of work offer projections of employment trends at the level of industries or occupations. These studies are useful for helping us conceptualize broad shifts in labor markets, but they aren’t able to shed light on the complex and unpredictable ways in which human workers and software systems interact in real-world settings.
In a recent study, I argue that in-depth examinations of the organizations in which software algorithms are developed and implemented can help us generate new insights into the question of when software systems function autonomously, and when they rely on the assistance of complementary human workers.
This summer we have seen what could be considered one of the largest prison strikes in US history, where prisoners are undertaking nineteen days of peaceful protest.
Some of the demands that underpin these protests are the need for improved prison conditions and greater funding in rehabilitation. But at the heart of this protest is a demonstration against imposed prison labour and the disturbingly low wages that accompany such work. This approach to prison work, an approach where profit is becoming more prevalent and private organisations are becoming more and more involved in the prison system, is not isolated to the US.
The research discussed here is based on a study conducted in the UK and is particularly pertinent in helping us to understand the reasoning behind the strikes and the feelings and experiences of those prisoners protesting.
Employment has been singled out as an important factor in reducing reoffending.
Every fall, a new crop of students enrolls in colleges across the country. Some pack up their belongings, leaving home and moving into dorms on campuses, while others start daily commutes.
And just as students’ paths to college vary, so do the campuses at which they arrive.
Colleges vary across multiple dimensions: from organizational and political culture, to level of prestige, peer culture, party scene, athletic emphasis, and racial-ethnic climate.
In recent work, I ask how some of these differences shape the college experiences of Latino students and find impact on their identity formation, civic engagement and more.