Category Archives: wages

New study challenges immigrant “catch-up” theory

New research is challenging the consensus view of how the USA absorbed the huge wave of immigrant workers who arrived from 1850 to 1910.

Earlier studies showed that on average, immigrants started in lower-skilled jobs compared with native workers, but caught up within a generation as they learned English and adopted American customs. This “start hungry, work hard, sacrifice and succeed” formula has become a version of “the American Dream.”

The reality was more complicated. A study that traced thousands of workers from 1900 to 1920 through their census forms showed that the average immigrant  made about the same amount as natives and moved up the occupational ladder at about the same rate.

Probing more deeply, the authors found that immigrants from high-income European nations – think Austria, England, France and Germany – made more upon arrival than comparable native workers and kept an edge as they assimilated. At the same time, workers from lower-income nations – such as Ireland, Italy and the Scandinavian countries – started close to or slightly below native workers in terms of income, and progressed at about the same rate.

imm_1900_update
Not all immigrants fared the same in the U.S. For many, success depended on the skills and wealth they brought with them. Amounts are in 2010 dollars.

The work was done by Ran Abramitzky of Stanford, Leah Platt Boustan of UCLA and Katherine Eriksson of Cal Poly. A version was published in the Journal of Political Economy last summer. The more detailed version released this week shows that average immigrant workers in the rapidly industrializing Midwest — Ohio, Illinois and Michigan — outearned natives, while the reverse was true in New England and the Great Plains.

The answers could shape ongoing debates about growing income inequality and how to overhaul the nation’s dysfunctional immigration policy.

The study used digital versions of census forms — which are made public after 72 years — from Ancestry.com. The forms were from 1900, 1910 and 1920.

The team focused on men between 18 and 35 years of age in 1900.   About 20,000 men who immigrated between 1880 and 1900 were paired with a similar group of 1,700 native men the same age. That let the researchers avoid averages and study actual people across 20 years as if they were in a long-term study. Lacking actual income data, the researchers used workers’ occupations to classify income. All Southern workers and black workers were excluded because few immigrants moved to the South and blacks were subject to harsh discrimination everywhere.

The consensus that immigrant workers started behind but caught up was due to the earlier need to analyze each census separately, according to the researchers. That approach misses the 25 percent of immigrants in the Great Migration who left, typically due to poor prospects. It also can’t account for the lower skill level of workers who arrived at the end of the period. Both shifts made it seem like long-term immigrants gained skills and income more than they did.

“Some of the conventional wisdom about the ‘American Dream’ for immigrants is more fiction than fact,” said Michelle Ercanbrack, a family historian at Ancestry.com. “The journey of American immigrants was far more complex than what we often think.” The service is offering free access to many of its searchable records through Monday.

The study suggests that sharp curbs on European immigration imposed in the early 1920s probably were not necessary, because the average immigrant worker arrived with  competitive skills and rose on the occupational ladder about as well as natives did. However, “we also note that migrants that arrived with low skill levels did not manage to close their skill gap with natives over time, ” the team noted.

“I wouldn’t make a prescription for today but it’s food for thought,” Abramitzky said.

He said the team is extending its work to look at cultural assimilation. They are analyzing the names that Great Wave immigrants gave to successive children. Preliminary work shows that the “foreignness” of a name affected a child’s later earnings as an adult, he said.

Abramitzky is an immigrant from Israel. His two oldest children have Hebrew names but the youngest does not.

— Paul Overberg

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Data scientists’ pay: details worth $10K

The median data analyst makes about $98,000 –including bonuses — in the U.S., according to a new salary survey from O’Reilly Media. But data people being what they are, the report includes a regression that allows anyone to compare their salary based on 27 variables from location to experience, from tools used to gender.

The survey of 816 people (about two-thirds from the U.S.) isn’t random, and the fact that it deals with data wranglers certainly caught our eye. But a survey that actually breaks down the differences among salaries really stands out.

Why aren’t more salary surveys done this way?

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Salaries have been a tricky thing in the past few years, especially for journalists. Publishing salaries of state or university workers is common at news organizations. They get lots of viewers — and a lot of push back for privacy invasion.

But others have argued that knowing everyone’s salary is the only way to insure pay equity,  and that salary is based on merit not one’s ability to negotiate. It can also avoid scandals such as an $800,000 city manager in a low-income suburb of Los Angeles.

Yet even if the human resources department decided everyone’s pay should be transparent, that still doesn’t provide context — is there a good reason someone earns more?

Which is why the O’Reilly survey is important. Even with the 27 variables that contribute to salary, the regression only explains about 58 percent of the variance. Still, even the attempt to explain variance reveals some interesting findings:

  • Geography matters. Not surprisingly, data scientists in California and the Northeast make more (between $17K and $26K). But working in Texas had the second-highest boost.
  • Startups don’t pay well; neither does government. Analysts in education lowered the expected salary by $30K; start ups drop the salary about $17K.
  •  Experience counts. Every year of age and each year working with data, together adds about $2,500 to the expected salary. Using tools such as Python, Natural Language Processing, NumPy and R can *each* add $1,900 in expected salary. SQL, Python, Excel and R are the most common tools used.
  • Being female hurts. The survey shows a $13K gender pay gap among data scientists — and says no differences in tools, experience or other factors account for it. See also Wage Debate at the Oscars.

Data science –whether it’s in journalism, government contracting or elsewhere  — is a rapidly expanding field, which makes predicting salaries difficult. The O’Reilly survey may not be perfect, but it gives people real tools  to create  transparency, without invading privacy.

–Jodi Upton

Wage debate at the Oscars

Actress Patricia Arquette used her moment at this year’s Oscars to spotlight gender pay equity. Admirable. But what do the data say?

arquetteAfter her speech for best supporting actress for “Boyhood,” social media lit up with comments, including an often-repeated, but highly flawed statistic claiming women make 77 cents for each dollar a man makes.

That number comes from a Census Bureau report that compares annual wages, which can include bonuses and investment income, but can be unfair to workers like teachers who don’t get paid in the summer.

A better measure is median weekly earnings, which is what the Bureau of Labor Statistics reports. Their latest figures shows women overall making 81 percent of what men make.

But even that’s flawed because it doesn’t measure women doing the same work. Women often work fewer hours (35 hours is considered full-time here) and are more likely to be in lower-paying occupations.

gender graphic

Women’s wages grow to 91 percent if you compare genders based on educational attainment and experience, and working in the same occupation and industry, according to a study by economists Francine Blau and Lawrence Kahn.

Two other economists, Claudia Goldin and Lawrence Katz, did a deeper analysis of MBA students. At graduation, males and females had only a tiny difference in salary, they found. But 10 to 15 years later, women’s earnings were 60 percent of men’s.

What happened in the interim? The women were more likely to have taken a break to care for children (especially if they had high-earning husbands), and when working, they were generally clocking fewer hours. The researchers said nearly all of the gap could be explained by these factors.

The women in the study who did not have children had earnings that were 88 percent of male earnings, and economists said that gap can be explained by the fact that the women were disproportionately working in smaller firms, often in the non-profit sector.

These studies raise the question of whether the wage gap is due to discrimination or women’s choices of career and family.  You can read more about this debate here and here and here.

Arquette was basing her comments on personal experience, but outside of anecdotes in leaked Sony emails, getting that data isn’t easy, either. Forbes tried to put together a list of the top 10 highest-earning A-list Hollywood actors between 2013 and 2014. The result? All men.

–MaryJo Webster