By Roberta Kwok
For decades, economists have struggled to understand all the factors that contribute to the wealth gap between richer and poorer countries.
They have assumed that two sources of wealth—physical capital and human capital—are important factors. The first refers to physical objects such as factories, machines, minerals, and fossil fuels. The second includes collective attributes like education level and health that help to make a nation’s population more productive.
But when economists have added up the components known to make up physical and human capital, they haven’t been able to explain as much of the wealth gap as one might expect. “It seemed like [these factors] should matter more,” says Nancy Qian, a professor of managerial economics and decision sciences at Kellogg.
So could one of those elements be missing a crucial factor? In a recent study, Qian and her collaborators investigated a factor in human capital that hadn’t received much attention: on-the-job learning. The researchers found that the rate at which people acquire skills at work seemed to be substantially different in rich versus poor countries.Add Insight
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“In poor countries, workers are not learning nearly as much on the job as in rich countries,” Qian says. And because on-the-job learning is the primary way people gain new skills after their formal schooling ends, this can have dramatic consequences for a nation’s economic development.
The finding suggests that education is not the panacea to global inequality that many have long believed it to be. Rather, policymakers interested in narrowing the wealth gap should investigate why people in poor countries acquire fewer skills at work and improve training accordingly. The goal is to “make poor countries less poor,” Qian says. “The question is how.”
Tackling global wealth disparity
Decades ago, researchers tried to measure human capital simply by accounting for population size and education level.
When their estimates of human capital—combined with estimates of physical capital—didn’t explain enough of the GDP differences between countries, “economists spent 20 years trying to do the accounting better,” Qian says. But even after they added in factors such as health, life expectancy, and education quality, “there was still a lot of difference that was unexplained.”
The goal is to “make poor countries less poor. The question is how.”
— Nancy Qian
That left a rather unsatisfying explanation: attributing remaining wealth differences to a set of vague intangibles called “total factor productivity.” This category might include, for instance, transportation infrastructure or legal institutions for enforcing contracts. Or it might not.Related
“Nobody knows what the hell this thing is,” says coauthor David Lagakos, an associate professor of economics at the University of California, San Diego. “It’s a big egg in the face of economists.”
To figure out if there was a missing element in human capital estimates, Qian and Lagakos collaborated with Benjamin Moll of Princeton University, Tommaso Porzio of the University of California, San Diego, and Todd Schoellman of the Federal Reserve Bank of Minneapolis.
Instead of just considering differences in the amount of schooling, they decided to consider differences in the amount of learning on the job. Previous literature on human capital had assumed that on-the-job learning happened at roughly the same pace in all countries. But Qian and her coauthors were skeptical that this was correct.
An earlier study by the team suggested they might be on the right track. That study found that people in rich countries increased their income much more over the course of their careers than people in poor countries. And only part of that could be explained by differences in education level, and the impact that has on career trajectories. In other words, a college graduate’s salary in, say, Canada rose more steeply over time than that of a college graduate in Vietnam.
But that research still left unanswered questions. After all, the labor markets in poor and rich countries are different, making it difficult to isolate the effects of on-the-job learning.
Stark differences in on-the-job-learning
In order to isolate that one factor, the researchers focused on a single labor market: the United States. Specifically, they looked at immigrants to the U.S. who came from poor and rich countries, and who had varying levels of work experience in their home countries prior to immigrating.
That allowed the team to determine if the skills acquired on the job in rich versus poor home countries affected immigrants’ U.S. earning power differently.
The team looked at census data from 1980 to 2000 as well as data from the American Community Surveys from 2005 to 2013. Their data set did not indicate which immigrants were working in the country legally, but Qian speculates that it likely included most legal and some illegal immigrants.The researchers categorized immigrants based on how long they had worked in their home country before moving. Then, for each home country, the team compared the U.S. wages of those who had acquired a lot of work experience versus those who had not worked much before arriving in the U.S. Finally, the researchers compared those wage patterns across home countries.
They found that, overall, the higher the home country’s GDP per capita, the more the immigrants from that nation tended to be rewarded for foreign work experience. For instance, among immigrants from the UK and Canada, those with 20–24 years of experience earned 125–200 percent more than similarly educated immigrants from the same country with only 0–4 years of experience. But among immigrants from Mexico and Guatemala, highly experienced workers earned only 10–30 percent more than their inexperienced compatriots.
Perhaps jobs in poorer countries don’t offer as many opportunities to bolster soft skills or engage in professional development as jobs in richer countries do.
The researchers continued their analysis, looking at different subsets of the data. For instance, they analyzed new immigrants while controlling for their English-language skills and the U.S. state they lived in. These analyses yielded similar patterns.
“The richer the country of origin, the more valued their home country experience is in the U.S. labor market,” Lagakos says.
Exploring possible explanations for wealth inequality
The researchers came up with three possible explanations for their findings.
First, perhaps immigrants from poor countries represented a different slice of their population than those from rich countries. In other words, maybe people who choose to emigrate from, say, Ghana are worse at learning new skills than the average Ghanaian, while those from Germany tend to be better at learning new skills than the average German.
This hypothesis did not hold up. The data showed that immigrants from both poor and rich countries typically averaged about 12 years of schooling. All countries, regardless of wealth, seemed to be sending highly educated people who were likely to be adept at learning new skills.
The second possibility was that immigrants from poor countries—but not rich ones—were performing jobs in the U.S. that didn’t match their skill level. For example, perhaps engineers from Mexico were not getting hired for engineering jobs, so they became taxi drivers instead—whereas British engineers had no problem finding work in their chosen field.
“Maybe they have the same ability,” Qian says, “but the ones who come from the poor countries take a hit because of labor market discrimination in the U.S.”
To test that hypothesis, the researchers categorized all college-educated immigrants’ jobs in the U.S. as high- or low-skilled. Then they compared those people’s jobs to those of college-educated nonmigrants in their home countries.
Among all immigrants, the likelihood of getting high-skilled work in the U.S. was slightly lower than in their home countries. However, the drop wasn’t substantially larger among people from poor nations.
“Everyone seems less likely to be in a skilled job once they come to the U.S., but it doesn’t seem to disproportionately be about the poor countries,” Lagakos says.
The researchers also looked at the possibility that immigrants from poorer countries were able to get jobs in their chosen fields, but were paid less for their years of experience because U.S. employers didn’t value the experience gained in those home countries. But, again, the data did not bear this out.
Increasing soft skills
That suggested a third option—that people accumulated different levels of human capital in their home countries before arriving in the U.S., and that this was why their work experience was treated as more or less valuable by the U.S. labor market.
In other words, immigrants from poor nations hadn’t learned as much at work as immigrants coming from wealthier nations. Perhaps jobs in poorer countries don’t offer as many opportunities to bolster soft skills or engage in professional development as jobs in richer countries do.
The next step for researchers who want to narrow the wage gap between rich and poor countries is to understand why that’s the case, so steps can be taken to fix the problem.
The most important takeaway from this research, Lagakos says, is that education alone cannot close the income gap.
“When you’re thinking about cross-country differences in human capital,” he says, “you can’t just stop at schooling.”
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