妻友社区

U.S. Citizenship and Immigration Services office. Photo courtesy of iStock.com/Andrei StanescuLast week, President Trump for foreigners seeking employment in the United States. This ban 鈥� which affects those from computer programmers to seasonal workers in the hospitality industry 鈥� will last at least until the end of 2020 and, when combined with extended restrictions on the issuance of new green cards, will keep as many as half a million people out of the U.S.

My research has shown that immigrants make significant contributions to the U.S. economy, particularly as business founders and job creators. As I recently wrote for the Center for Growth and Opportunity鈥檚 , they will play a critical role in pandemic economic recovery, and keeping foreign workers out of the U.S. right now will be detrimental to those efforts.

In the last two decades, the share of immigrant entrepreneurs in the U.S. has increased, along with the shares of Latino and Black business owners, and those of Mexican, Chinese, and Indian descent. (As I testified before Congress a year ago, while immigrants make up about 13 percent of the U.S. population, they are founders of 26 percent of new businesses, and they are more likely than those born in the U.S. to be entrepreneurs.) The creation of new companies and new jobs is much more dependent on these diverse entrepreneurs than it was in the 1990s and early 2000s.

Immigrant entrepreneurs alone create roughly one in four of all jobs among young companies, and 40 percent or more in places such as Silicon Valley, New York City, and other tech hubs. Young companies are responsible for a disproportionate number of newly created jobs, so ensuring the viability of already existing young companies is critical if we want them to continue their role as job creation engines.

Many immigrant-founded firms rely heavily on being able to hire immigrant workers 鈥� either skilled workers through the H-1B visa program, or seasonal workers through various other programs. Some of these workers return home after a period of time; some end up staying and getting their green cards, and some of those eventually start their own businesses. No matter how long they stay in the U.S., they are an important source of labor in our economy.

So not letting these workers enter the U.S. at a time when small businesses have been particularly hard hit by the COVID-19 pandemic will make recovery that much more difficult. Companies founded by immigrants make up a huge part of our economy and create jobs for Americans and immigrants alike. Preventing them from being able to get their businesses back up and running will hurt us all in the long run.

Sari Pekkala Kerr, Ph.D., is a senior research scientist and economist at the 妻友社区. Her studies and teaching focus on the economics of labor markets, education, and families.

A woman graduates from college and starts her first job, earning about the same as the male colleague who sits next to her. She gets promoted a few times, her salary increases, and in her late 20s, she gets married. Her husband gets a job offer in a new city, they move, and she takes a slightly lower-paying job. In her early 30s, she has a baby, and then another baby in her mid-30s. She decides to cut back her hours (and thus her pay) in order to spend more time with her children. My research shows that this is the point in women鈥檚 lives at which the gender pay gap widens.

Fast-forward 15 years: the woman鈥檚 children are growing up and will soon be headed off to college, and she is eager to ramp her career back up. What happens to the gender pay gap now?

Today is Equal Pay Day, a day that symbolizes how far into the year the average woman in the U.S. must work in order to earn what the average man in the U.S. earned the previous year. Equal Pay Day for black women is August 13, for Native American women it鈥檚 October 1, and for Latina women it鈥檚 October 29. Women on average earn $0.82 for each dollar earned by a man; black women earn $0.62, Native American women earn $0.57, and Latina women earn $0.54. The gender pay gap has slowly narrowed over time, but over the past 15 years. Globally, the gap isn鈥檛 expected to close .

But we are learning that the story of the gender pay gap is a complex one. We now know that male and female college grads start their careers earning nearly the same salaries, but . By the time college grads reach their peak earnings, . Less than a third of this gap is caused by differences between the jobs in which men and women work, though women are certainly such as teaching, nursing, and social work 鈥� the usual 鈥減ink-collar鈥� jobs. Much of the widening of the gap comes from married women: their earnings grow much more slowly with age and they see little benefit from job-hopping compared with men and unmarried women. And when women become mothers, they are more likely to than men, even in full-time work.

This paints a bit of a dire picture. Things begin to turn around for women, though, once they reach their late 40s and 50s: the pay gap begins to narrow again. For example, among more recent generations of college-educated women, the they reach their late 50s. This happens as women increase their work effort relative to men once their children leave home.

There are still more questions to be answered before we can fully understand the causes of the gender pay gap, and how policies might help close it. For example, how much of the gap is contributed by dual-career considerations, where a family has to optimize around the primary breadwinner? Can public policies help to better share the burden among working spouses? An improved understanding might help us determine whether policies such as father quotas in parental leave might be part of a solution.

We are slowly gaining a clearer picture of how the gender pay gap evolves over the course of our lives. As our research continues, this picture continues to come into focus.

Sari Pekkala Kerr, Ph.D., is a senior research scientist and economist at the 妻友社区. Her studies and teaching focus on the economics of labor markets, education, and families.

In January 2018, President Trump famously raised his concerns regarding the 鈥渓ack of Norwegians鈥� and the excess of immigrants from low-income countries entering the United States 鈥� and . The concern over the composition of U.S. immigration flow is not at all new, however. Leading immigration economist George Borjas, Ph.D., has pointed out in several academic articles that the relative share of immigrants from Europe steadily declined over the 20^th century, as more immigrants started to arrive from Central and South America, and Asia (Borjas, 1995 and 1999).[1] Borjas argued that in the 1980鈥檚 and 1990鈥檚 the weakening labor market performance of immigrants (as compared to U.S. natives) was directly related to the changing source country composition. More recently, low skilled immigration into the U.S. has drastically declined, as explained by Hanson, Liu, and McIntosh (2017).[2] Should the U.S. be very concerned about the composition of its immigrant pool as Trump rather bluntly argued? And would that give rise to a drastic change in the U.S. immigration policy? Let鈥檚 examine the data.

We took a look at the to evaluate those questions. To avoid arbitrarily categorizing source countries into 鈥渁s good as Norway鈥� versus 鈥渢errible, horrible, no good, very bad countries鈥� we use the World Bank country classification based on the Gross National Income (GNI) per capita and OECD membership. Countries are grouped into low income (e.g. Afghanistan, Haiti, and Somalia), lower middle-income (e.g. Armenia, El Salvador, and India), upper middle-income (e.g. Cuba, Mexico, and China), high-income OECD (e.g. Chile, Norway, and Canada), and high-income non-OECD (e.g. The Bahamas, Saudi Arabia, and Russia). Since Mexico, China, and India currently constitute the vast majority of U.S.-bound immigrants in their respective groups, we look at those countries separately. Also, as we are interested in studying the labor market performance of immigrants relative to U.S. natives, we include individuals aged 18-65 in the descriptive analyses below.

First, worries regarding the huge influx of migrants from low-income countries do not seem warranted: the share of immigrant from low-income countries (as percentage of the total immigrant stock residing in the U.S.) is rather small (around three percent) and has remained steady over the period 2001-2017, both among the recent arrivals and the broader immigrant population. On the other hand, there is a definite downward trend in the share of immigrants who originate from high-income OECD countries, as well as a similar downward trend for Mexicans, with the latter being particularly prominent among recent arrivals. There is a corresponding increase in the number of migrants from lower- and upper middle-income countries, especially from India and China.

So then, are immigrants from low-income countries poorly educated and not succeeding in the U.S. labor market? Perhaps surprisingly, origin country income and the average education level of the immigrant group are not as highly correlated as one might think. Immigrants from Mexico, high-income non-OECD countries, and low-income countries are less likely to have a college degree than similarly aged U.S. natives, whereas those from China, India, and high-income OECD-countries are the most educated. The latter is largely explained by the where a college degree is a minimum requirement for entry into the U.S. Educational attainment is gradually increasing among all groups, including U.S. natives. looks at immigrant niching into specific low-skill and high-skill labor markets (Eckstein and Peri, 2018).[3] The niching is very much related to the type of skills and human capital of the immigrant group. For example, almost one-in-four Indian immigrants works in a computing related job, whereas Mexican immigrants are heavily clustered in low-skilled manual jobs (e.g. laborers in construction, farm workers, cooks, and janitors).

Most analysts of immigrants in host country labor markets are concerned with their 鈥渁ssimilation鈥� 鈥� how easily they are able to find employment and what their relative wage levels look like as compared to natives. We know that since the Great Recession, most immigrants are at least as likely to be employed as the average American native. The only exceptions are those from high-income non-OECD countries, whose employment rates are much lower. Conditional on being employed, immigrants are also more likely to work full time (30 hours or more per week) than employed natives, with the exception of  high-income non-OECD country immigrants in the post-recession years, as well as Chinese immigrants in the last few years of the data.[4].

While immigrants seem to find employment, most of them are not earning wages as high as the average American. There are many likely reasons for the immigrant-native pay gap, including language skills, under-employment relative to education, occupation and sector differences, and so on. Whether looking at the annual earnings, weekly wages, or hourly wage, the relative pay is low especially for those from Mexico and low-income countries. Even if we account for the immigrant 鈥� native differences in education, occupations, geographic locations, and other reasons that explain the pay gap, we still see all immigrant groups except for those from high-income OECD countries earning less than comparable natives.  

Additionally, many studies have looked at the immigrant 鈥� native wage gap in detail and find that the gap shrinks over duration of stay.[5] Immigrants in the U.S. also seem to in the labor market than in most other countries.[6] Many more studies have tried to find impacts that immigrants may have on native employment and wages. Generally those impacts are very small or localized to specific groups.[7] Instead, immigrants are found to be an important economic force as firm founders, job creators, and innovators.[8] Taking the various facts into account, it would be hard to claim that immigrants in the U.S. are a 鈥渘et negative鈥� for the economy.

So are President Trump鈥檚 concerns regarding our immigrant pool valid, at least as far some real data and evidence can attest? We would argue that immigrants seem to fare relatively well in the U.S. labor market, and the changing source country composition is perhaps not much of a cause for concern. It remains, of course, important to ensure that immigrants can assimilate into the U.S. labor market, without any , as that guarantees the greatest positive net impact on the host country.

Sari Pekkala Kerr, Ph.D., is a senior research scientist/economist at the at who studies labor markets, education, and families. is a research associate at the and a former research assistant at the 妻友社区.

[1] Borjas, George. 鈥淗eaven鈥檚 Door.鈥� Princeton, NJ: Princeton University Press, 1999. Borjas, George. 鈥淎ssimilation and Changes in Cohort Quality Revisited: What Happened to Immigrant Earnings in the 1980s? Journal of Labor Economics 13 (1995): 201-245.

[2] Hanson, Gordon, Chen Liu, and Craig McIntosh. 鈥淎long the watchtower: The rise and fall of U.S. low-skilled immigration.鈥� Brookings Papers on Economic Activity, BPEA Conference Drafts, March 2017.

[3] Susan Eckstein and Giovanni Peri. 鈥淚mmigrant Niches and Immigrant Networks in the U.S. Labor Market.鈥� RSF: The Russell Sage Foundation Journal of the Social Sciences 4 (2018): 1鈥�17.

[4] Due to the very large sample sizes in the ACS, most differences that appear small in the graphs are nevertheless statistically significant under standard t-tests for sample means.

[5] E.g. LaLonde and Topel. 鈥淎ssimilation of Immigrants in the U.S. Labor Market.鈥� In Borjas and Freeman (Eds.) Immigration and the Work Force. The University of Chicago Press (1992); Lubotsky. 鈥淐hutes or Ladders? A Longitudinal Analysis of Immigrant Earnings.鈥� Journal of Political Economy 115 (2007): 820鈥�867.

[6] E.g. OECD (2015) 鈥淚ndicators of Immigrant Integration.鈥� OECD, Paris.

[7] E.g. Kerr and Kerr. 鈥淓conomic Impacts of Immigration: A Survey.鈥� Finnish Economic Papers 24 (2011): 1-32; Ottaviano and Peri. 鈥淩ethinking the Effect of Immigration on Wages.鈥� Journal of the European Economic Association 10 (2012): 152鈥�197; Borjas and Doran. "The Collapse of the Soviet Union and the Productivity of American Mathematicians." Quarterly Journal of Economics 127 (2012): 1143-1203.

[8] E.g. Kerr and Kerr. 鈥淚mmigrant Entrepreneurship in America: Evidence from the Survey of Business Owners 2007 & 2012.鈥� NBER Working Paper 24494, 2018; Kerr. 鈥淕ift of Global Talent: How Migration Shapes Business, Economy, and Society.鈥� Stanford University Press, 2018.

We all have heard it, women earn about 20 percent less than men. But when, how, and why does the gap emerge? Everyone has an opinion on it, and these opinions range widely 鈥� which leads to many . Are we eternally stuck in a rut arguing about what the relevant facts are? Or could administrative 鈥渂ig data鈥� shed some new light here and help move us forward? We think so鈥�

Two new studies find that college grads start their career with a tiny gender earnings gap, but . What are women doing wrong, or men doing right, for this to happen? This seems to be a story about 鈥渃areer acrobatics鈥�, one with chutes and ladders. First, it turns out that the gap widens both in existing jobs as men climb the career ladders faster and higher within firms, and through job changes since men disproportionately move across firms to higher paying ones as they age. By the time college grads reach their peak earnings, .

What could possibly account for such enormous earnings gaps during the first 20 years of working life? Not surprisingly for anyone, a chunk of the initial gap and its subsequent growth comes from differences between men and women in terms of the sectors and occupations in which they work. . The best-known examples include teachers, nurses, occupational therapists, and social workers. Many commentators argue that women themselves are responsible for pay gaps as they choose careers where starting salary is low and salary growth modest with work experience and seniority. In reality, the reasons why women congregate in these occupations are complex, and addressing occupational gender differences requires societal changes. More importantly for the debate though, women are not 鈥渃ausing鈥� the earnings gap with their 鈥渂ad choices鈥� 鈥� occupational segregation accounts for no more than a third of the overall earning gap. Something else is at work.

Another expensive 鈥渃hoice鈥� women make is motherhood. Women are more likely to than men 鈥� even in full-time work. How much of that 55 percent gap does motherhood explain? Unfortunately our data does not give a direct answer to that, but arguably all of these factors contribute to the growing earnings gap between ages 25 and 45. What we can say though is that much of the widening of the earnings gap comes from married women: their earnings grow much more slowly with age and they see little benefit from job hopping compared with men and unmarried women. Why are they not able to capitalize on their college degree like others even by switching jobs? This may be related to a phenomenon called 鈥渢ied migration.鈥� Family makes their location decision based on the 鈥減rimary career鈥�, which usually is that of the husband. This is why job moves tend to only benefit that primary career and could even hurt the secondary career. Ironically, the primary career is typically chosen to be the one with greater earnings potential 鈥� bringing us right back to the gender pay gap conundrum. This begins to look like a self-reinforcing cycle.

Career choices that look 鈥渓ess than optimal鈥� in terms of long-run earnings growth may also be explained by college educated women consciously moving to lower-paying firms (within a given industry) in anticipation of needing more time flexibility when children enter the picture. Similarly, the gender earnings gap is largest in sectors, such as financial, insurance, and real estate (FIRE), that are more unforgiving of career interruptions and shorter or more flexible work hours. At age 25-27, female college grads working in FIRE earn almost exactly as much as male college grads. However, already . In this sector men are able to obtain greater career advancements within a given firm, but a sizeable chunk of the earnings gap is due to women鈥檚 disproportionate shift into lower-paying firms by age 34.

We promised that these data could help shed some new light, but there are still many questions in making sense of the patterns. For one, what happens to the career and earnings dynamics within households as the family composition changes? Time-use studies say that the arrival of children makes spouses specialize more: one parent focuses on work while the other takes more responsibility at home, often balancing a job in the mix. It is easy to guess how this specialization usually goes, but might the dynamics look different if it was the father rather than the mother who takes a career break? Answers to those questions can clarify policy recommendations. For example, would a Swedish-style shared parental leave policy reduce gender earnings gaps or do we need a more wholesale approach to workplace organization? The latter approach would include reducing the earnings and career cost of temporal flexibility, making a work-family balance easier for both moms and dads, and reduce the need to designate a 鈥渄efault parent鈥� who takes over the majority of household and child-related responsibilities.

Sari Pekkala Kerr, Ph.D., is a senior research scientist/economist at the 妻友社区 at 妻友社区 College. Her work described above is based on the research she conducted with Erling Barth, Claudia Goldin, and Claudia Olivetti.

Social Justice Dialogue: Eradicating Poverty

A frequent theme in the discussion on poverty is the degree to which poverty persists across generations. While the United States is touted as the land of opportunity where everyone can attain their American dream, poverty is still the most likely outcome for a child born into a poor family. A large body of research demonstrates that education is the best way out of poverty, especially when dealing with inter-generational transmission of poverty. The problem is, however, that children from economically disadvantaged families are much less likely to obtain college education than their wealthier peers. In this article, I review innovative recent studies demonstrating cost-effective ways to increase educational attainment among poor children.

show that high-achieving students from poor families typically apply to selective colleges much less frequently than students from wealthier families, despite the fact that those selective colleges would have generous financial aid available. In their experimental study, Hoxby and Turner offer customized information on the application process and financial aid to students, and find that the college application, admission and enrollment rates of high-achieving low-income students increase dramatically. As their intervention only cost $6 per student, the authors argue that providing information in this manner would be a highly cost effective way to improve the educational attainment of low-income students. Their experiment was adopted by the in an effort to attract poor, high-scoring students to elite colleges. Indeed, has just launched their own effort to advertise financial aid available to low-income families.

tackle the low take-up rate of college financial aid among low-income individuals by providing assistance for filling out the (FAFSA) forms and handing out information on the expected student aid levels relative to college costs. High school seniors whose parents received the assistance were much more likely to enroll in college and complete at least 2 years of education during the 2-year follow-up period. The experiment cost a total of $88 per participant (including a $20 participation incentive and $20 incentive to the H&R Block tax professionals proving the assistance). Even so, the large positive effects of the experiment would far outweigh the modest cost per participant.

Several recent studies have provided information on the benefits of higher education to high school students, concentrating especially to students from economically disadvantaged backgrounds. These studies cover students in a variety of countries such as Canada, Dominican Republic and Finland. In each case, these low-cost interventions find that students exposed to the information provided change their application behavior and/or post-secondary educational attendance. In most cases the effects are particularly large for students stemming from poorer or less educated families.

The studies reviewed here demonstrate that children from poorer families are lacking in their educational attainment at least in part due to insufficient information on the economic benefits of education and available financial aid. In addition, their college attendance may further be hampered due to the application procedures required to obtain financial aid. These disadvantages could be easily, and cheaply, overcome by providing targeted information and assistance to students and their families. As the research shows, the modest investment would be far outweighed by the stemming from greater college attendance and higher future earnings of the participating students. And most importantly, these types of policies could begin to bring children out of chronic poverty by cutting down the inter-generational transmission of economic status.

Sari Pekkala Kerr, Ph.D. is a Senior Research Scientist and Economist at the 妻友社区 at . Her research and teaching focus on the economics of labor markets, education, and families.